Sample records for algorithm na ordenacao
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Analysis of Naïve Bayes Algorithm for Email Spam Filtering across Multiple Datasets
NASA Astrophysics Data System (ADS)
Fitriah Rusland, Nurul; Wahid, Norfaradilla; Kasim, Shahreen; Hafit, Hanayanti
2017-08-01
E-mail spam continues to become a problem on the Internet. Spammed e-mail may contain many copies of the same message, commercial advertisement or other irrelevant posts like pornographic content. In previous research, different filtering techniques are used to detect these e-mails such as using Random Forest, Naïve Bayesian, Support Vector Machine (SVM) and Neutral Network. In this research, we test Naïve Bayes algorithm for e-mail spam filtering on two datasets and test its performance, i.e., Spam Data and SPAMBASE datasets [8]. The performance of the datasets is evaluated based on their accuracy, recall, precision and F-measure. Our research use WEKA tool for the evaluation of Naïve Bayes algorithm for e-mail spam filtering on both datasets. The result shows that the type of email and the number of instances of the dataset has an influence towards the performance of Naïve Bayes.
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Three-dimensional dictionary-learning reconstruction of (23)Na MRI data.
Behl, Nicolas G R; Gnahm, Christine; Bachert, Peter; Ladd, Mark E; Nagel, Armin M
2016-04-01
To reduce noise and artifacts in (23)Na MRI with a Compressed Sensing reconstruction and a learned dictionary as sparsifying transform. A three-dimensional dictionary-learning compressed sensing reconstruction algorithm (3D-DLCS) for the reconstruction of undersampled 3D radial (23)Na data is presented. The dictionary used as the sparsifying transform is learned with a K-singular-value-decomposition (K-SVD) algorithm. The reconstruction parameters are optimized on simulated data, and the quality of the reconstructions is assessed with peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The performance of the algorithm is evaluated in phantom and in vivo (23)Na MRI data of seven volunteers and compared with nonuniform fast Fourier transform (NUFFT) and other Compressed Sensing reconstructions. The reconstructions of simulated data have maximal PSNR and SSIM for an undersampling factor (USF) of 10 with numbers of averages equal to the USF. For 10-fold undersampling, the PSNR is increased by 5.1 dB compared with the NUFFT reconstruction, and the SSIM by 24%. These results are confirmed by phantom and in vivo (23)Na measurements in the volunteers that show markedly reduced noise and undersampling artifacts in the case of 3D-DLCS reconstructions. The 3D-DLCS algorithm enables precise reconstruction of undersampled (23)Na MRI data with markedly reduced noise and artifact levels compared with NUFFT reconstruction. Small structures are well preserved. © 2015 Wiley Periodicals, Inc.
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Discovering new materials and new phenomena with evolutionary algorithms
NASA Astrophysics Data System (ADS)
Oganov, Artem
Thanks to powerful evolutionary algorithms, in particular the USPEX method, it is now possible to predict both the stable compounds and their crystal structures at arbitrary conditions, given just the set of chemical elements. Recent developments include major increases of efficiency and extensions to low-dimensional systems and molecular crystals (which allowed large structures to be handled easily, e.g. Mg(BH4)2 and H2O-H2) and new techniques called evolutionary metadynamics and Mendelevian search. Some of the results that I will discuss include: 1. Theoretical and experimental evidence for a new partially ionic phase of boron, γ-B and an insulating and optically transparent form of sodium. 2. Predicted stability of ``impossible'' chemical compounds that become stable under pressure - e.g. Na3Cl, Na2Cl, Na3Cl2, NaCl3, NaCl7, Mg3O2 and MgO2. 3. Novel surface phases (e.g. boron surface reconstructions). 4. Novel dielectric polymers, and novel permanent magnets confirmed by experiment and ready for applications. 5. Prediction of new ultrahard materials and computational proof that diamond is the hardest possible material.
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Prediction of Effective Drug Combinations by an Improved Naïve Bayesian Algorithm.
Bai, Li-Yue; Dai, Hao; Xu, Qin; Junaid, Muhammad; Peng, Shao-Liang; Zhu, Xiaolei; Xiong, Yi; Wei, Dong-Qing
2018-02-05
Drug combinatorial therapy is a promising strategy for combating complex diseases due to its fewer side effects, lower toxicity and better efficacy. However, it is not feasible to determine all the effective drug combinations in the vast space of possible combinations given the increasing number of approved drugs in the market, since the experimental methods for identification of effective drug combinations are both labor- and time-consuming. In this study, we conducted systematic analysis of various types of features to characterize pairs of drugs. These features included information about the targets of the drugs, the pathway in which the target protein of a drug was involved in, side effects of drugs, metabolic enzymes of the drugs, and drug transporters. The latter two features (metabolic enzymes and drug transporters) were related to the metabolism and transportation properties of drugs, which were not analyzed or used in previous studies. Then, we devised a novel improved naïve Bayesian algorithm to construct classification models to predict effective drug combinations by using the individual types of features mentioned above. Our results indicated that the performance of our proposed method was indeed better than the naïve Bayesian algorithm and other conventional classification algorithms such as support vector machine and K-nearest neighbor.
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ATR-FTIR spectroscopy for the determination of Na4EDTA in detergent aqueous solutions.
Suárez, Leticia; García, Roberto; Riera, Francisco A; Diez, María A
2013-10-15
Fourier transform infrared spectroscopy in the attenuated total reflectance mode (ATR-FTIR) combined with partial last square (PLS) algorithms was used to design calibration and prediction models for a wide range of tetrasodium ethylenediaminetetraacetate (Na4EDTA) concentrations (0.1 to 28% w/w) in aqueous solutions. The spectra obtained using air and water as a background medium were tested for the best fit. The PLS models designed afforded a sufficient level of precision and accuracy to allow even very small amounts of Na4EDTA to be determined. A root mean square error of nearly 0.37 for the validation set was obtained. Over a concentration range below 5% w/w, the values estimated from a combination of ATR-FTIR spectroscopy and a PLS algorithm model were similar to those obtained from an HPLC analysis of NaFeEDTA complexes and subsequent detection by UV absorbance. However, the lowest detection limit for Na4EDTA concentrations afforded by this spectroscopic/chemometric method was 0.3% w/w. The PLS model was successfully used as a rapid and simple method to quantify Na4EDTA in aqueous solutions of industrial detergents as an alternative to HPLC-UV analysis which involves time-consuming dilution and complexation processes. © 2013 Elsevier B.V. All rights reserved.
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A Novel Feature Selection Technique for Text Classification Using Naïve Bayes.
Dey Sarkar, Subhajit; Goswami, Saptarsi; Agarwal, Aman; Aktar, Javed
2014-01-01
With the proliferation of unstructured data, text classification or text categorization has found many applications in topic classification, sentiment analysis, authorship identification, spam detection, and so on. There are many classification algorithms available. Naïve Bayes remains one of the oldest and most popular classifiers. On one hand, implementation of naïve Bayes is simple and, on the other hand, this also requires fewer amounts of training data. From the literature review, it is found that naïve Bayes performs poorly compared to other classifiers in text classification. As a result, this makes the naïve Bayes classifier unusable in spite of the simplicity and intuitiveness of the model. In this paper, we propose a two-step feature selection method based on firstly a univariate feature selection and then feature clustering, where we use the univariate feature selection method to reduce the search space and then apply clustering to select relatively independent feature sets. We demonstrate the effectiveness of our method by a thorough evaluation and comparison over 13 datasets. The performance improvement thus achieved makes naïve Bayes comparable or superior to other classifiers. The proposed algorithm is shown to outperform other traditional methods like greedy search based wrapper or CFS.
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High pressure structural stability of the Na-Te system
NASA Astrophysics Data System (ADS)
Wang, Youchun; Tian, Fubo; Li, Da; Duan, Defang; Xie, Hui; Liu, Bingbing; Zhou, Qiang; Cui, Tian
2018-03-01
The ab initio evolutionary algorithm is used to search for all thermodynamically stable Na-Te compounds at extreme pressure. In our calculations, several new structures are discovered at high pressure, namely, Imma Na2Te, Pmmm NaTe, Imma Na8Te2 and P4/mmm NaTe3. Like the known structures of Na2Te (Fm-3m, Pnma and P63/mmc), the Pmmm NaTe, Imma Na8Te2 and P4/mmm NaTe3 structures also show semiconductor properties with band-gap decreases when pressure increased. However, we find that the band-gap of Imma Na2Te structure increases with pressure. We presume that the result may be caused by the increasing of splitting between Te p states and Na s, Na p and Te d states. Furthermore, we think that the strong hybridization between Na p state and Te d state result in the band gap increasing with pressure.
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NASA Astrophysics Data System (ADS)
Calvin Frans Mariel, Wahyu; Mariyah, Siti; Pramana, Setia
2018-03-01
Deep learning is a new era of machine learning techniques that essentially imitate the structure and function of the human brain. It is a development of deeper Artificial Neural Network (ANN) that uses more than one hidden layer. Deep Learning Neural Network has a great ability on recognizing patterns from various data types such as picture, audio, text, and many more. In this paper, the authors tries to measure that algorithm’s ability by applying it into the text classification. The classification task herein is done by considering the content of sentiment in a text which is also called as sentiment analysis. By using several combinations of text preprocessing and feature extraction techniques, we aim to compare the precise modelling results of Deep Learning Neural Network with the other two commonly used algorithms, the Naϊve Bayes and Support Vector Machine (SVM). This algorithm comparison uses Indonesian text data with balanced and unbalanced sentiment composition. Based on the experimental simulation, Deep Learning Neural Network clearly outperforms the Naϊve Bayes and SVM and offers a better F-1 Score while for the best feature extraction technique which improves that modelling result is Bigram.
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Prototype for Meta-Algorithmic, Content-Aware Image Analysis
2015-03-01
PROTOTYPE FOR META-ALGORITHMIC, CONTENT-AWARE IMAGE ANALYSIS UNIVERSITY OF VIRGINIA MARCH 2015 FINAL TECHNICAL REPORT...ALGORITHMIC, CONTENT-AWARE IMAGE ANALYSIS 5a. CONTRACT NUMBER FA8750-12-C-0181 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62305E 6. AUTHOR(S) S...approaches were studied in detail and their results on a sample dataset are presented. 15. SUBJECT TERMS Image Analysis , Computer Vision, Content
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Sai, Linwei; Tang, Lingli; Zhao, Jijun; Wang, Jun; Kumar, Vijay
2011-11-14
The ground state structures of neutral and anionic clusters of Na(n)Si(m) (1 ≤ n ≤ 3, 1 ≤ m ≤ 11) have been determined using genetic algorithm incorporated in first principles total energy code. The size dependence of the structural and electronic properties is discussed in detail. It is found that the lowest-energy structures of Na(n)Si(m) clusters resemble those of the pure Si clusters. Interestingly, Na atoms in neutral Na(n)Si(m) clusters are usually well separated by the Si(m) skeleton, whereas Na atoms can form Na-Na bonds in some anionic clusters. The ionization potentials, adiabatic electron affinities, and photoelectron spectra are also calculated and the results compare well with the experimental data. © 2011 American Institute of Physics
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Sinha, Snehal K; Kumar, Mithilesh; Guria, Chandan; Kumar, Anup; Banerjee, Chiranjib
2017-10-01
Algal model based multi-objective optimization using elitist non-dominated sorting genetic algorithm with inheritance was carried out for batch cultivation of Dunaliella tertiolecta using NPK-fertilizer. Optimization problems involving two- and three-objective functions were solved simultaneously. The objective functions are: maximization of algae-biomass and lipid productivity with minimization of cultivation time and cost. Time variant light intensity and temperature including NPK-fertilizer, NaCl and NaHCO 3 loadings are the important decision variables. Algal model involving Monod/Andrews adsorption kinetics and Droop model with internal nutrient cell quota was used for optimization studies. Sets of non-dominated (equally good) Pareto optimal solutions were obtained for the problems studied. It was observed that time variant optimal light intensity and temperature trajectories, including optimum NPK fertilizer, NaCl and NaHCO 3 concentration has significant influence to improve biomass and lipid productivity under minimum cultivation time and cost. Proposed optimization studies may be helpful to implement the control strategy in scale-up operation. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi
2017-11-02
Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.
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Parallel consistent labeling algorithms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Samal, A.; Henderson, T.
Mackworth and Freuder have analyzed the time complexity of several constraint satisfaction algorithms. Mohr and Henderson have given new algorithms, AC-4 and PC-3, for arc and path consistency, respectively, and have shown that the arc consistency algorithm is optimal in time complexity and of the same order space complexity as the earlier algorithms. In this paper, they give parallel algorithms for solving node and arc consistency. They show that any parallel algorithm for enforcing arc consistency in the worst case must have O(na) sequential steps, where n is number of nodes, and a is the number of labels per node.more » They give several parallel algorithms to do arc consistency. It is also shown that they all have optimal time complexity. The results of running the parallel algorithms on a BBN Butterfly multiprocessor are also presented.« less
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Assessment of various supervised learning algorithms using different performance metrics
NASA Astrophysics Data System (ADS)
Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.
2017-11-01
Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.
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NASA Astrophysics Data System (ADS)
Avetisyan, H.; Bruna, O.; Holub, J.
2016-11-01
A numerous techniques and algorithms are dedicated to extract emotions from input data. In our investigation it was stated that emotion-detection approaches can be classified into 3 following types: Keyword based / lexical-based, learning based, and hybrid. The most commonly used techniques, such as keyword-spotting method, Support Vector Machines, Naïve Bayes Classifier, Hidden Markov Model and hybrid algorithms, have impressive results in this sphere and can reach more than 90% determining accuracy.
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A hybrid approach to select features and classify diseases based on medical data
NASA Astrophysics Data System (ADS)
AbdelLatif, Hisham; Luo, Jiawei
2018-03-01
Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms
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NASA Astrophysics Data System (ADS)
Ghosh, Karabi
2017-02-01
We briefly comment on a paper by N.A. Gentile [J. Comput. Phys. 230 (2011) 5100-5114] in which the Fleck factor has been modified to include the effects of temperature-dependent opacities in the implicit Monte Carlo algorithm developed by Fleck and Cummings [1,2]. Instead of the Fleck factor, f = 1 / (1 + βcΔtσP), the author derived the modified Fleck factor g = 1 / (1 + βcΔtσP - min [σP‧ (aTr4 - aT4)cΔt/ρCV, 0 ]) to be used in the Implicit Monte Carlo (IMC) algorithm in order to obtain more accurate solutions with much larger time steps. Here β = 4 aT3 / ρCV, σP is the Planck opacity and the derivative of Planck opacity w.r.t. the material temperature is σP‧ = dσP / dT.
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Vectorial mask optimization methods for robust optical lithography
NASA Astrophysics Data System (ADS)
Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong; Arce, Gonzalo R.
2012-10-01
Continuous shrinkage of critical dimension in an integrated circuit impels the development of resolution enhancement techniques for low k1 lithography. Recently, several pixelated optical proximity correction (OPC) and phase-shifting mask (PSM) approaches were developed under scalar imaging models to account for the process variations. However, the lithography systems with larger-NA (NA>0.6) are predominant for current technology nodes, rendering the scalar models inadequate to describe the vector nature of the electromagnetic field that propagates through the optical lithography system. In addition, OPC and PSM algorithms based on scalar models can compensate for wavefront aberrations, but are incapable of mitigating polarization aberrations in practical lithography systems, which can only be dealt with under the vector model. To this end, we focus on developing robust pixelated gradient-based OPC and PSM optimization algorithms aimed at canceling defocus, dose variation, wavefront and polarization aberrations under a vector model. First, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. A steepest descent algorithm is then used to iteratively optimize the mask patterns. Simulations show that the proposed algorithms can effectively improve the process windows of the optical lithography systems.
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NASA Astrophysics Data System (ADS)
Ammendola, R.; Biagioni, A.; Fiorini, M.; Frezza, O.; Lonardo, A.; Lamanna, G.; Lo Cicero, F.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Tosoratto, L.; Vicini, P.
2016-03-01
A GPU-based low level (L0) trigger is currently integrated in the experimental setup of the RICH detector of the NA62 experiment to assess the feasibility of building more refined physics-related trigger primitives and thus improve the trigger discriminating power. To ensure the real-time operation of the system, a dedicated data transport mechanism has been implemented: an FPGA-based Network Interface Card (NaNet-10) receives data from detectors and forwards them with low, predictable latency to the memory of the GPU performing the trigger algorithms. Results of the ring-shaped hit patterns reconstruction will be reported and discussed.
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NASA Astrophysics Data System (ADS)
Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong
2012-03-01
Optical proximity correction (OPC) and phase shifting mask (PSM) are the most widely used resolution enhancement techniques (RET) in the semiconductor industry. Recently, a set of OPC and PSM optimization algorithms have been developed to solve for the inverse lithography problem, which are only designed for the nominal imaging parameters without giving sufficient attention to the process variations due to the aberrations, defocus and dose variation. However, the effects of process variations existing in the practical optical lithography systems become more pronounced as the critical dimension (CD) continuously shrinks. On the other hand, the lithography systems with larger NA (NA>0.6) are now extensively used, rendering the scalar imaging models inadequate to describe the vector nature of the electromagnetic field in the current optical lithography systems. In order to tackle the above problems, this paper focuses on developing robust gradient-based OPC and PSM optimization algorithms to the process variations under a vector imaging model. To achieve this goal, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. The steepest descent algorithm is used to optimize the mask iteratively. In order to improve the efficiency of the proposed algorithms, a set of algorithm acceleration techniques (AAT) are exploited during the optimization procedure.
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NASA Astrophysics Data System (ADS)
Licciardi, A.; Piana Agostinetti, N.
2016-06-01
Information about seismic anisotropy is embedded in the variation of the amplitude of the Ps pulses as a function of the azimuth, on both the Radial and the Transverse components of teleseismic receiver functions (RF). We develop a semi-automatic method to constrain the presence and the depth of anisotropic layers beneath a single seismic broad-band station. An algorithm is specifically designed to avoid trial and error methods and subjective crustal parametrizations in RF inversions, providing a suitable tool for large-size data set analysis. The algorithm couples together information extracted from a 1-D VS profile and from a harmonic decomposition analysis of the RF data set. This information is used to determine the number of anisotropic layers and their approximate position at depth, which, in turn, can be used to, for example, narrow the search boundaries for layer thickness and S-wave velocity in a subsequent parameter space search. Here, the output of the algorithm is used to invert an RF data set by means of the Neighbourhood Algorithm (NA). To test our methodology, we apply the algorithm to both synthetic and observed data. We make use of synthetic RF with correlated Gaussian noise to investigate the resolution power for multiple and thin (1-3 km) anisotropic layers in the crust. The algorithm successfully identifies the number and position of anisotropic layers at depth prior the NA inversion step. In the NA inversion, strength of anisotropy and orientation of the symmetry axis are correctly retrieved. Then, the method is applied to field measurement from station BUDO in the Tibetan Plateau. Two consecutive layers of anisotropy are automatically identified with our method in the first 25-30 km of the crust. The data are then inverted with the retrieved parametrization. The direction of the anisotropic axis in the uppermost layer correlates well with the orientation of the major planar structure in the area. The deeper anisotropic layer is associated with an older phase of crustal deformation. Our results are compared with previous anisotropic RF studies at the same station, showing strong similarities.
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Mono-isotope Prediction for Mass Spectra Using Bayes Network.
Li, Hui; Liu, Chunmei; Rwebangira, Mugizi Robert; Burge, Legand
2014-12-01
Mass spectrometry is one of the widely utilized important methods to study protein functions and components. The challenge of mono-isotope pattern recognition from large scale protein mass spectral data needs computational algorithms and tools to speed up the analysis and improve the analytic results. We utilized naïve Bayes network as the classifier with the assumption that the selected features are independent to predict mono-isotope pattern from mass spectrometry. Mono-isotopes detected from validated theoretical spectra were used as prior information in the Bayes method. Three main features extracted from the dataset were employed as independent variables in our model. The application of the proposed algorithm to publicMo dataset demonstrates that our naïve Bayes classifier is advantageous over existing methods in both accuracy and sensitivity.
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NASA Astrophysics Data System (ADS)
Hering, Julian; Waller, Erik H.; von Freymann, Georg
2017-02-01
Since a large number of optical systems and devices are based on differently shaped focal intensity distributions (point-spread-functions, PSF), the PSF's quality is crucial for the application's performance. E.g., optical tweezers, optical potentials for trapping of ultracold atoms as well as stimulated-emission-depletion (STED) based microscopy and lithography rely on precisely controlled intensity distributions. However, especially in high numerical aperture (NA) systems, such complex laser modes are easily distorted by aberrations leading to performance losses. Although different approaches addressing phase retrieval algorithms have been recently presented[1-3], fast and automated aberration compensation for a broad variety of complex shaped PSFs in high NA systems is still missing. Here, we report on a Gerchberg-Saxton[4] based algorithm (GSA) for automated aberration correction of arbitrary PSFs, especially for high NA systems. Deviations between the desired target intensity distribution and the three-dimensionally (3D) scanned experimental focal intensity distribution are used to calculate a correction phase pattern. The target phase distribution plus the correction pattern are displayed on a phase-only spatial-light-modulator (SLM). Focused by a high NA objective, experimental 3D scans of several intensity distributions allow for characterization of the algorithms performance: aberrations are reliably identified and compensated within less than 10 iterations. References 1. B. M. Hanser, M. G. L. Gustafsson, D. A. Agard, and J. W. Sedat, "Phase-retrieved pupil functions in wide-field fluorescence microscopy," J. of Microscopy 216(1), 32-48 (2004). 2. A. Jesacher, A. Schwaighofer, S. Frhapter, C. Maurer, S. Bernet, and M. Ritsch-Marte, "Wavefront correction of spatial light modulators using an optical vortex image," Opt. Express 15(9), 5801-5808 (2007). 3. A. Jesacher and M. J. Booth, "Parallel direct laser writing in three dimensions with spatially dependent aberration correction," Opt. Express 18(20), 21090-21099 (2010). 4. R. W. Gerchberg and W. O. Saxton, "A practical algorithm for the determination of the phase from image and diffraction plane pictures," Optik 35(2), 237-246 (1972).
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Superquantile Regression: Theory, Algorithms, and Applications
2014-12-01
Example C: Stack loss data scatterplot matrix. 91 Regression α c0 caf cwt cac R̄ 2 α R̄ 2 α,Adj Least Squares NA -39.9197 0.7156 1.2953 -0.1521 0.9136...This is due to a small 92 Model Regression α c0 cwt cwt2 R̄ 2 α R̄ 2 α,Adj f2 Least Squares NA -41.9109 2.8174 — 0.7665 0.7542 Quantile 0.25 -32.0000
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Barbosa, Rommel Melgaço; Nacano, Letícia Ramos; Freitas, Rodolfo; Batista, Bruno Lemos; Barbosa, Fernando
2014-09-01
This article aims to evaluate 2 machine learning algorithms, decision trees and naïve Bayes (NB), for egg classification (free-range eggs compared with battery eggs). The database used for the study consisted of 15 chemical elements (As, Ba, Cd, Co, Cs, Cu, Fe, Mg, Mn, Mo, Pb, Se, Sr, V, and Zn) determined in 52 eggs samples (20 free-range and 32 battery eggs) by inductively coupled plasma mass spectrometry. Our results demonstrated that decision trees and NB associated with the mineral contents of eggs provide a high level of accuracy (above 80% and 90%, respectively) for classification between free-range and battery eggs and can be used as an alternative method for adulteration evaluation. © 2014 Institute of Food Technologists®
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Validation of energy-weighted algorithm for radiation portal monitor using plastic scintillator.
Lee, Hyun Cheol; Shin, Wook-Geun; Park, Hyo Jun; Yoo, Do Hyun; Choi, Chang-Il; Park, Chang-Su; Kim, Hong-Suk; Min, Chul Hee
2016-01-01
To prevent illicit tracking of radionuclides, radiation portal monitor (RPM) systems employing plastic scintillators have been used in ports and airports. However, their poor energy resolution makes the discrimination of radioactive material inaccurate. In this study, an energy weight algorithm was validated to determine (133)Ba, (22)Na, (137)Cs, and (60)Co by using a plastic scintillator. The Compton edges of energy spectra were converted to peaks based on the algorithm. The peaks have a maximum error of 6% towards the theoretical Compton edge. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Integrated Reconfigurable Intelligent Systems (IRIS) for Complex Naval Systems
2010-02-21
RKF45] and Adams Variable Step- Size Predictor - Corrector methods). While such algorithms naturally are usually used to numerically solve differential...verified by yet another function call. Due to their nature, such methods are referred to as predictor - corrector methods. While computationally expensive...CONTRACT NUMBER N00014-09- C -0394 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER N/A 6. Author(s) Dr. Dimitri N. Mavris Dr. Yongchang Li 5d
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Full-Spectrum-Analysis Isotope ID
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mitchell, Dean J.; Harding, Lee; Thoreson, Gregory G.
2017-06-28
FSAIsotopeID analyzes gamma ray spectra to identify radioactive isotopes (radionuclides). The algorithm fits the entire spectrum with combinations of pre-computed templates for a comprehensive set of radionuclides with varying thicknesses and compositions of shielding materials. The isotope identification algorithm is suitable for the analysis of spectra collected by gamma-ray sensors ranging from medium-resolution detectors, such a NaI, to high-resolution detectors, such as HPGe. In addition to analyzing static measurements, the isotope identification algorithm is applied for the radiation search applications. The search subroutine maintains a running background spectrum that is passed to the isotope identification algorithm, and it also selectsmore » temporal integration periods that optimize the responsiveness and sensitivity. Gain stabilization is supported for both types of applications.« less
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Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei
2014-09-01
In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
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Comments on Samal and Henderson: Parallel consistent labeling algorithms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Swain, M.J.
Samal and Henderson claim that any parallel algorithm for enforcing arc consistency in the worst case must have {Omega}(na) sequential steps, where n is the number of nodes, and a is the number of labels per node. The authors argue that Samal and Henderon's argument makes assumptions about how processors are used and give a counterexample that enforces arc consistency in a constant number of steps using O(n{sup 2}a{sup 2}2{sup na}) processors. It is possible that the lower bound holds for a polynomial number of processors; if such a lower bound were to be proven it would answer an importantmore » open question in theoretical computer science concerning the relation between the complexity classes P and NC. The strongest existing lower bound for the arc consistency problem states that it cannot be solved in polynomial log time unless P = NC.« less
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A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors
Han, Manhyung; Bang, Jae Hun; Nugent, Chris; McClean, Sally; Lee, Sungyoung
2014-01-01
Activity recognition for the purposes of recognizing a user's intentions using multimodal sensors is becoming a widely researched topic largely based on the prevalence of the smartphone. Previous studies have reported the difficulty in recognizing life-logs by only using a smartphone due to the challenges with activity modeling and real-time recognition. In addition, recognizing life-logs is difficult due to the absence of an established framework which enables the use of different sources of sensor data. In this paper, we propose a smartphone-based Hierarchical Activity Recognition Framework which extends the Naïve Bayes approach for the processing of activity modeling and real-time activity recognition. The proposed algorithm demonstrates higher accuracy than the Naïve Bayes approach and also enables the recognition of a user's activities within a mobile environment. The proposed algorithm has the ability to classify fifteen activities with an average classification accuracy of 92.96%. PMID:25184486
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1986-08-01
SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTIONAVAILABILITY OF REPORT N/A \\pproved for public release, 21b. OECLASS FI) CAT ) ON/OOWNGRAOING SCMEOLLE...from this set of projections. The Convolution Back-Projection (CBP) algorithm is widely used technique in Computer Aide Tomography ( CAT ). In this work...University of Illinois at Urbana-Champaign. 1985 Ac % DTICEl_ FCTE " AUG 1 11986 Urbana. Illinois U,) I A NEW METHOD OF SYNTHETIC APERTURE RADAR IMAGE
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Ramanujam, Nedunchelian; Kaliappan, Manivannan
2016-01-01
Nowadays, automatic multidocument text summarization systems can successfully retrieve the summary sentences from the input documents. But, it has many limitations such as inaccurate extraction to essential sentences, low coverage, poor coherence among the sentences, and redundancy. This paper introduces a new concept of timestamp approach with Naïve Bayesian Classification approach for multidocument text summarization. The timestamp provides the summary an ordered look, which achieves the coherent looking summary. It extracts the more relevant information from the multiple documents. Here, scoring strategy is also used to calculate the score for the words to obtain the word frequency. The higher linguistic quality is estimated in terms of readability and comprehensibility. In order to show the efficiency of the proposed method, this paper presents the comparison between the proposed methods with the existing MEAD algorithm. The timestamp procedure is also applied on the MEAD algorithm and the results are examined with the proposed method. The results show that the proposed method results in lesser time than the existing MEAD algorithm to execute the summarization process. Moreover, the proposed method results in better precision, recall, and F-score than the existing clustering with lexical chaining approach. PMID:27034971
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1983-10-01
Concurrency Control Algorithms Computer Corporation of America Wente K. Lin, Philip A. Bernstein, Nathan Goodman and Jerry Nolte APPROVED FOR PUBLIC ...84 03 IZ 004 ’KV This report has been reviewed by the RADC Public Affairs Office (PA) an is releasable to the National Technical Information Service...NTIS). At NTIS it will be releasable to the general public , including foreign na~ions. RADC-TR-83-226, Vol II (of three) has been reviewed and is
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Ong, Eng Teo; Lee, Heow Pueh; Lim, Kian Meng
2004-09-01
This article presents a fast algorithm for the efficient solution of the Helmholtz equation. The method is based on the translation theory of the multipole expansions. Here, the speedup comes from the convolution nature of the translation operators, which can be evaluated rapidly using fast Fourier transform algorithms. Also, the computations of the translation operators are accelerated by using the recursive formulas developed recently by Gumerov and Duraiswami [SIAM J. Sci. Comput. 25, 1344-1381(2003)]. It is demonstrated that the algorithm can produce good accuracy with a relatively low order of expansion. Efficiency analyses of the algorithm reveal that it has computational complexities of O(Na), where a ranges from 1.05 to 1.24. However, this method requires substantially more memory to store the translation operators as compared to the fast multipole method. Hence, despite its simplicity in implementation, this memory requirement issue may limit the application of this algorithm to solving very large-scale problems.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Schramm, Georg, E-mail: georg.schramm@kuleuven.be; Maus, Jens; Hofheinz, Frank
Purpose: MR-based attenuation correction (MRAC) in routine clinical whole-body positron emission tomography and magnetic resonance imaging (PET/MRI) is based on tissue type segmentation. Due to lack of MR signal in cortical bone and the varying signal of spongeous bone, standard whole-body segmentation-based MRAC ignores the higher attenuation of bone compared to the one of soft tissue (MRAC{sub nobone}). The authors aim to quantify and reduce the bias introduced by MRAC{sub nobone} in the standard uptake value (SUV) of spinal and pelvic lesions in 20 PET/MRI examinations with [{sup 18}F]NaF. Methods: The authors reconstructed 20 PET/MR [{sup 18}F]NaF patient data setsmore » acquired with a Philips Ingenuity TF PET/MRI. The PET raw data were reconstructed with two different attenuation images. First, the authors used the vendor-provided MRAC algorithm that ignores the higher attenuation of bone to reconstruct PET{sub nobone}. Second, the authors used a threshold-based algorithm developed in their group to automatically segment bone structures in the [{sup 18}F]NaF PET images. Subsequently, an attenuation coefficient of 0.11 cm{sup −1} was assigned to the segmented bone regions in the MRI-based attenuation image (MRAC{sub bone}) which was used to reconstruct PET{sub bone}. The automatic bone segmentation algorithm was validated in six PET/CT [{sup 18}F]NaF examinations. Relative SUV{sub mean} and SUV{sub max} differences between PET{sub bone} and PET{sub nobone} of 8 pelvic and 41 spinal lesions, and of other regions such as lung, liver, and bladder, were calculated. By varying the assigned bone attenuation coefficient from 0.11 to 0.13 cm{sup −1}, the authors investigated its influence on the reconstructed SUVs of the lesions. Results: The comparison of [{sup 18}F]NaF-based and CT-based bone segmentation in the six PET/CT patients showed a Dice similarity of 0.7 with a true positive rate of 0.72 and a false discovery rate of 0.33. The [{sup 18}F]NaF-based bone segmentation worked well in the pelvis and spine. However, it showed artifacts in the skull and in the extremities. The analysis of the 20 [{sup 18}F]NaF PET/MRI examinations revealed relative SUV{sub max} differences between PET{sub nobone} and PET{sub bone} of (−8.8% ± 2.7%, p = 0.01) and (−8.1% ± 1.9%, p = 2.4 × 10{sup −8}) in pelvic and spinal lesions, respectively. A maximum SUV{sub max} underestimation of −13.7% was found in lesion in the third cervical spine. The averaged SUV{sub mean} differences in volumes of interests in lung, liver, and bladder were below 3%. The average SUV{sub max} differences in pelvic and spinal lesions increased from −9% to −18% and −8% to −17%, respectively, when increasing the assigned bone attenuation coefficient from 0.11 to 0.13 cm{sup −1}. Conclusions: The developed automatic [{sup 18}F]NaF PET-based bone segmentation allows to include higher bone attenuation in whole-body MRAC and thus improves quantification accuracy for pelvic and spinal lesions in [{sup 18}F]NaF PET/MRI examinations. In nonbone structures (e.g., lung, liver, and bladder), MRAC{sub nobone} yields clinically acceptable accuracy.« less
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Control of wavepacket dynamics in mixed alkali metal clusters by optimally shaped fs pulses
NASA Astrophysics Data System (ADS)
Bartelt, A.; Minemoto, S.; Lupulescu, C.; Vajda, Š.; Wöste, L.
We have performed adaptive feedback optimization of phase-shaped femtosecond laser pulses to control the wavepacket dynamics of small mixed alkali-metal clusters. An optimization algorithm based on Evolutionary Strategies was used to maximize the ion intensities. The optimized pulses for NaK and Na2K converged to pulse trains consisting of numerous peaks. The timing of the elements of the pulse trains corresponds to integer and half integer numbers of the vibrational periods of the molecules, reflecting the wavepacket dynamics in their excited states.
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The Approximability of Learning and Constraint Satisfaction Problems
2010-10-07
further improved this result to NP ⊆ naPCP1,3/4+²(O(log(n)),3). Around the same time, Zwick [141] showed that naPCP1,5/8(O(log(n)),3)⊆ BPP by giving a...randomized polynomial-time 5/8-approximation algorithm for satisfiable 3CSP. Therefore unless NP⊆ BPP , the best s must be bigger than 5/8. Zwick... BPP [141]. We think that Question 5.1.2 addresses an important missing part in understanding the 3-query PCP systems. In addition, as is mentioned the
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A comparative study of surface waves inversion techniques at strong motion recording sites in Greece
Panagiotis C. Pelekis,; Savvaidis, Alexandros; Kayen, Robert E.; Vlachakis, Vasileios S.; Athanasopoulos, George A.
2015-01-01
Surface wave method was used for the estimation of Vs vs depth profile at 10 strong motion stations in Greece. The dispersion data were obtained by SASW method, utilizing a pair of electromechanical harmonic-wave source (shakers) or a random source (drop weight). In this study, three inversion techniques were used a) a recently proposed Simplified Inversion Method (SIM), b) an inversion technique based on a neighborhood algorithm (NA) which allows the incorporation of a priori information regarding the subsurface structure parameters, and c) Occam's inversion algorithm. For each site constant value of Poisson's ratio was assumed (ν=0.4) since the objective of the current study is the comparison of the three inversion schemes regardless the uncertainties resulting due to the lack of geotechnical data. A penalty function was introduced to quantify the deviations of the derived Vs profiles. The Vs models are compared as of Vs(z), Vs30 and EC8 soil category, in order to show the insignificance of the existing variations. The comparison results showed that the average variation of SIM profiles is 9% and 4.9% comparing with NA and Occam's profiles respectively whilst the average difference of Vs30 values obtained from SIM is 7.4% and 5.0% compared with NA and Occam's.
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Improved plutonium identification and characterization results with NaI(Tl) detector using ASEDRA
NASA Astrophysics Data System (ADS)
Detwiler, R.; Sjoden, G.; Baciak, J.; LaVigne, E.
2008-04-01
The ASEDRA algorithm (Advanced Synthetically Enhanced Detector Resolution Algorithm) is a tool developed at the University of Florida to synthetically enhance the resolved photopeaks derived from a characteristically poor resolution spectra collected at room temperature from scintillator crystal-photomultiplier detector, such as a NaI(Tl) system. This work reports on analysis of a side-by-side test comparing the identification capabilities of ASEDRA applied to a NaI(Tl) detector with HPGe results for a Plutonium Beryllium (PuBe) source containing approximately 47 year old weapons-grade plutonium (WGPu), a test case of real-world interest with a complex spectra including plutonium isotopes and 241Am decay products. The analysis included a comparison of photopeaks identified and photopeak energies between the ASEDRA and HPGe detector systems, and the known energies of the plutonium isotopes. ASEDRA's performance in peak area accuracy, also important in isotope identification as well as plutonium quality and age determination, was evaluated for key energy lines by comparing the observed relative ratios of peak areas, adjusted for efficiency and attenuation due to source shielding, to the predicted ratios from known energy line branching and source isotopics. The results show that ASEDRA has identified over 20 lines also found by the HPGe and directly correlated to WGPu energies.
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An extensive assessment of network alignment algorithms for comparison of brain connectomes.
Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario
2017-06-06
Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.
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A Theoretical Analysis of Why Hybrid Ensembles Work.
Hsu, Kuo-Wei
2017-01-01
Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.
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DOT National Transportation Integrated Search
2016-08-09
The AASHTO codes for Load Resistance Factored Design (LRFD) regarding shallow bridge foundations : and walls have been implemented into a set of spreadsheet algorithms to facilitate the calculations of bearing : capacity and footing settlements on na...
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Influenza-like illness surveillance on Twitter through automated learning of naïve language.
Gesualdo, Francesco; Stilo, Giovanni; Agricola, Eleonora; Gonfiantini, Michaela V; Pandolfi, Elisabetta; Velardi, Paola; Tozzi, Alberto E
2013-01-01
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillance. When speaking of an illness, Twitter users often report a combination of symptoms, rather than a suspected or final diagnosis, using naïve, everyday language. We developed a minimally trained algorithm that exploits the abundance of health-related web pages to identify all jargon expressions related to a specific technical term. We then translated an influenza case definition into a Boolean query, each symptom being described by a technical term and all related jargon expressions, as identified by the algorithm. Subsequently, we monitored all tweets that reported a combination of symptoms satisfying the case definition query. In order to geolocalize messages, we defined 3 localization strategies based on codes associated with each tweet. We found a high correlation coefficient between the trend of our influenza-positive tweets and ILI trends identified by US traditional surveillance systems.
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Graphical processors for HEP trigger systems
NASA Astrophysics Data System (ADS)
Ammendola, R.; Biagioni, A.; Chiozzi, S.; Cotta Ramusino, A.; Di Lorenzo, S.; Fantechi, R.; Fiorini, M.; Frezza, O.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Vicini, P.
2017-02-01
General-purpose computing on GPUs is emerging as a new paradigm in several fields of science, although so far applications have been tailored to employ GPUs as accelerators in offline computations. With the steady decrease of GPU latencies and the increase in link and memory throughputs, time is ripe for real-time applications using GPUs in high-energy physics data acquisition and trigger systems. We will discuss the use of online parallel computing on GPUs for synchronous low level trigger systems, focusing on tests performed on the trigger of the CERN NA62 experiment. Latencies of all components need analysing, networking being the most critical. To keep it under control, we envisioned NaNet, an FPGA-based PCIe Network Interface Card (NIC) enabling GPUDirect connection. Moreover, we discuss how specific trigger algorithms can be parallelised and thus benefit from a GPU implementation, in terms of increased execution speed. Such improvements are particularly relevant for the foreseen LHC luminosity upgrade where highly selective algorithms will be crucial to maintain sustainable trigger rates with very high pileup.
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Influenza-Like Illness Surveillance on Twitter through Automated Learning of Naïve Language
Gesualdo, Francesco; Stilo, Giovanni; Agricola, Eleonora; Gonfiantini, Michaela V.; Pandolfi, Elisabetta; Velardi, Paola; Tozzi, Alberto E.
2013-01-01
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillance. When speaking of an illness, Twitter users often report a combination of symptoms, rather than a suspected or final diagnosis, using naïve, everyday language. We developed a minimally trained algorithm that exploits the abundance of health-related web pages to identify all jargon expressions related to a specific technical term. We then translated an influenza case definition into a Boolean query, each symptom being described by a technical term and all related jargon expressions, as identified by the algorithm. Subsequently, we monitored all tweets that reported a combination of symptoms satisfying the case definition query. In order to geolocalize messages, we defined 3 localization strategies based on codes associated with each tweet. We found a high correlation coefficient between the trend of our influenza-positive tweets and ILI trends identified by US traditional surveillance systems. PMID:24324799
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NASA Astrophysics Data System (ADS)
Cai, X.
2017-12-01
To investigate gravity wave (GW) perturbations in the midlatitude mesopause region during boreal equinox, 433 h of continuous Na lidar full diurnal cycle temperature measurements in September between 2011 and 2015 are utilized to derive the monthly profiles of GW-induced temperature variance, T'^2, and the potential energy density (PED). Operating at Utah State University (42° N, 112° W), these lidar measurements reveal severe GW dissipation near 90 km, where both parameters drop to their minima (˜ 20 K^2 and ˜ 50 m^2/ s^2, respectively). The study also shows that GWs with periods of 3-5 h dominate the midlatitude mesopause region during the summer-winter transition. To derive the precise temperature perturbations a new tide removal algorithm suitable for all ground-based observations is developed to de-trend the lidar temperature measurements and to isolate GW-induced perturbations. It removes the tidal perturbations completely and provides the most accurate GW perturbations for the ground-based observations. This algorithm is validated by comparing the true GW perturbations in the latest mesoscale-resolving Whole Atmosphere Community Climate Model (WACCM) with those derived from the WACCM local outputs by applying this newly developed tidal removal algorithm.
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Reverse engineering and analysis of large genome-scale gene networks
Aluru, Maneesha; Zola, Jaroslaw; Nettleton, Dan; Aluru, Srinivas
2013-01-01
Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web. PMID:23042249
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Perk, T; Bradshaw, T; Muzahir, S
2014-06-15
Purpose: [F-18]NaF PET can be used to image bone metastases; however, tracer uptake in degenerative joint disease (DJD) often appears similar to metastases. This study aims to develop and compare different machine learning algorithms to automatically identify regions of [F-18]NaF scans that correspond to DJD. Methods: 10 metastatic prostate cancer patients received whole body [F-18]NaF PET/CT scans prior to treatment. Image segmentation resulted in 852 ROIs, 69 of which were identified by a nuclear medicine physician as DJD. For all ROIs, various PET and CT textural features were computed. ROIs were divided into training and testing sets used to trainmore » eight different machine learning classifiers. Classifiers were evaluated based on receiver operating characteristics area under the curve (AUC), sensitivity, specificity, and positive predictive value (PPV). We also assessed the added value of including CT features in addition to PET features for training classifiers. Results: The training set consisted of 37 DJD ROIs with 475 non-DJD ROIs, and the testing set consisted of 32 DJD ROIs with 308 non-DJD ROIs. Of all classifiers, generalized linear models (GLM), decision forests (DF), and support vector machines (SVM) had the best performance. AUCs of GLM (0.929), DF (0.921), and SVM (0.889) were significantly higher than the other models (p<0.001). GLM and DF, overall, had the best sensitivity, specificity, and PPV, and gave a significantly better performance (p<0.01) than all other models. PET/CT GLM classifiers had higher AUC than just PET or just CT. GLMs built using PET/CT information had superior or comparable sensitivities, specificities and PPVs to just PET or just CT. Conclusion: Machine learning algorithms trained with PET/CT features were able to identify some cases of DJD. GLM outperformed the other classification algorithms. Using PET and CT information together was shown to be superior to using PET or CT features alone. Research supported by the Prostate Cancer Foundation.« less
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NASA Astrophysics Data System (ADS)
Khan, Asif; Ryoo, Chang-Kyung; Kim, Heung Soo
2017-04-01
This paper presents a comparative study of different classification algorithms for the classification of various types of inter-ply delaminations in smart composite laminates. Improved layerwise theory is used to model delamination at different interfaces along the thickness and longitudinal directions of the smart composite laminate. The input-output data obtained through surface bonded piezoelectric sensor and actuator is analyzed by the system identification algorithm to get the system parameters. The identified parameters for the healthy and delaminated structure are supplied as input data to the classification algorithms. The classification algorithms considered in this study are ZeroR, Classification via regression, Naïve Bayes, Multilayer Perceptron, Sequential Minimal Optimization, Multiclass-Classifier, and Decision tree (J48). The open source software of Waikato Environment for Knowledge Analysis (WEKA) is used to evaluate the classification performance of the classifiers mentioned above via 75-25 holdout and leave-one-sample-out cross-validation regarding classification accuracy, precision, recall, kappa statistic and ROC Area.
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Comparative study of classification algorithms for immunosignaturing data
2012-01-01
Background High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data. Results We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy. Conclusions ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties. PMID:22720696
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Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R
2017-01-01
Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as we have done here, utilizing readily-available off-the-shelf machine learning techniques and resulting in only a fraction of narratives that require manual review. Human-machine ensemble methods are likely to improve performance over total manual coding. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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A Theoretical Analysis of Why Hybrid Ensembles Work
2017-01-01
Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles. PMID:28255296
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Chemodynamical Clustering Applied to APOGEE Data: Rediscovering Globular Clusters
NASA Astrophysics Data System (ADS)
Chen, Boquan; D’Onghia, Elena; Pardy, Stephen A.; Pasquali, Anna; Bertelli Motta, Clio; Hanlon, Bret; Grebel, Eva K.
2018-06-01
We have developed a novel technique based on a clustering algorithm that searches for kinematically and chemically clustered stars in the APOGEE DR12 Cannon data. As compared to classical chemical tagging, the kinematic information included in our methodology allows us to identify stars that are members of known globular clusters with greater confidence. We apply our algorithm to the entire APOGEE catalog of 150,615 stars whose chemical abundances are derived by the Cannon. Our methodology found anticorrelations between the elements Al and Mg, Na and O, and C and N previously identified in the optical spectra in globular clusters, even though we omit these elements in our algorithm. Our algorithm identifies globular clusters without a priori knowledge of their locations in the sky. Thus, not only does this technique promise to discover new globular clusters, but it also allows us to identify candidate streams of kinematically and chemically clustered stars in the Milky Way.
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Zmiri, Dror; Shahar, Yuval; Taieb-Maimon, Meirav
2012-04-01
To test the feasibility of classifying emergency department patients into severity grades using data mining methods. Emergency department records of 402 patients were classified into five severity grades by two expert physicians. The Naïve Bayes and C4.5 algorithms were applied to produce classifiers from patient data into severity grades. The classifiers' results over several subsets of the data were compared with the physicians' assessments, with a random classifier, and with a classifier that selects the maximal-prevalence class. Positive predictive value, multiple-class extensions of sensitivity and specificity combinations, and entropy change. The mean accuracy of the data mining classifiers was 52.94 ± 5.89%, significantly better (P < 0.05) than the mean accuracy of a random classifier (34.60 ± 2.40%). The entropy of the input data sets was reduced through classification by a mean of 10.1%. Allowing for classification deviations of one severity grade led to mean accuracy of 85.42 ± 1.42%. The classifiers' accuracy in that case was similar to the physicians' consensus rate. Learning from consensus records led to better performance. Reducing the number of severity grades improved results in certain cases. The performance of the Naïve Bayes and C4.5 algorithms was similar; in unbalanced data sets, Naïve Bayes performed better. It is possible to produce a computerized classification model for the severity grade of triage patients, using data mining methods. Learning from patient records regarding which there is a consensus of several physicians is preferable to learning from each physician's patients. Either Naïve Bayes or C4.5 can be used; Naïve Bayes is preferable for unbalanced data sets. An ambiguity in the intermediate severity grades seems to hamper both the physicians' agreement and the classifiers' accuracy. © 2010 Blackwell Publishing Ltd.
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Duffy, Ellen B.; Barquera, Blanca
2006-01-01
The membrane topologies of the six subunits of Na+-translocating NADH:quinone oxidoreductase (Na+-NQR) from Vibrio cholerae were determined by a combination of topology prediction algorithms and the construction of C-terminal fusions. Fusion expression vectors contained either bacterial alkaline phosphatase (phoA) or green fluorescent protein (gfp) genes as reporters of periplasmic and cytoplasmic localization, respectively. A majority of the topology prediction algorithms did not predict any transmembrane helices for NqrA. A lack of PhoA activity when fused to the C terminus of NqrA and the observed fluorescence of the green fluorescent protein C-terminal fusion confirm that this subunit is localized to the cytoplasmic side of the membrane. Analysis of four PhoA fusions for NqrB indicates that this subunit has nine transmembrane helices and that residue T236, the binding site for flavin mononucleotide (FMN), resides in the cytoplasm. Three fusions confirm that the topology of NqrC consists of two transmembrane helices with the FMN binding site at residue T225 on the cytoplasmic side. Fusion analysis of NqrD and NqrE showed almost mirror image topologies, each consisting of six transmembrane helices; the results for NqrD and NqrE are consistent with the topologies of Escherichia coli homologs YdgQ and YdgL, respectively. The NADH, flavin adenine dinucleotide, and Fe-S center binding sites of NqrF were localized to the cytoplasm. The determination of the topologies of the subunits of Na+-NQR provides valuable insights into the location of cofactors and identifies targets for mutagenesis to characterize this enzyme in more detail. The finding that all the redox cofactors are localized to the cytoplasmic side of the membrane is discussed. PMID:17041063
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NASA Astrophysics Data System (ADS)
He, Jianbin; Yu, Simin; Cai, Jianping
2016-12-01
Lyapunov exponent is an important index for describing chaotic systems behavior, and the largest Lyapunov exponent can be used to determine whether a system is chaotic or not. For discrete-time dynamical systems, the Lyapunov exponents are calculated by an eigenvalue method. In theory, according to eigenvalue method, the more accurate calculations of Lyapunov exponent can be obtained with the increment of iterations, and the limits also exist. However, due to the finite precision of computer and other reasons, the results will be numeric overflow, unrecognized, or inaccurate, which can be stated as follows: (1) The iterations cannot be too large, otherwise, the simulation result will appear as an error message of NaN or Inf; (2) If the error message of NaN or Inf does not appear, then with the increment of iterations, all Lyapunov exponents will get close to the largest Lyapunov exponent, which leads to inaccurate calculation results; (3) From the viewpoint of numerical calculation, obviously, if the iterations are too small, then the results are also inaccurate. Based on the analysis of Lyapunov-exponent calculation in discrete-time systems, this paper investigates two improved algorithms via QR orthogonal decomposition and SVD orthogonal decomposition approaches so as to solve the above-mentioned problems. Finally, some examples are given to illustrate the feasibility and effectiveness of the improved algorithms.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Claus, Rene A.; Wang, Yow-Gwo; Wojdyla, Antoine
Extreme Ultraviolet (EUV) Lithography mask defects were examined on the actinic mask imaging system, SHARP, at Lawrence Berkeley National Laboratory. Also, a quantitative phase retrieval algorithm based on the Weak Object Transfer Function was applied to the measured through-focus aerial images to examine the amplitude and phase of the defects. The accuracy of the algorithm was demonstrated by comparing the results of measurements using a phase contrast zone plate and a standard zone plate. Using partially coherent illumination to measure frequencies that would otherwise fall outside the numerical aperture (NA), it was shown that some defects are smaller than themore » conventional resolution of the microscope. We found that the programmed defects of various sizes were measured and shown to have both an amplitude and a phase component that the algorithm is able to recover.« less
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Global Network Alignment in the Context of Aging.
Faisal, Fazle Elahi; Zhao, Han; Milenkovic, Tijana
2015-01-01
Analogous to sequence alignment, network alignment (NA) can be used to transfer biological knowledge across species between conserved network regions. NA faces two algorithmic challenges: 1) Which cost function to use to capture "similarities" between nodes in different networks? 2) Which alignment strategy to use to rapidly identify "high-scoring" alignments from all possible alignments? We "break down" existing state-of-the-art methods that use both different cost functions and different alignment strategies to evaluate each combination of their cost functions and alignment strategies. We find that a combination of the cost function of one method and the alignment strategy of another method beats the existing methods. Hence, we propose this combination as a novel superior NA method. Then, since human aging is hard to study experimentally due to long lifespan, we use NA to transfer aging-related knowledge from well annotated model species to poorly annotated human. By doing so, we produce novel human aging-related knowledge, which complements currently available knowledge about aging that has been obtained mainly by sequence alignment. We demonstrate significant similarity between topological and functional properties of our novel predictions and those of known aging-related genes. We are the first to use NA to learn more about aging.
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High-NA metrology and sensing on Berkeley MET5
NASA Astrophysics Data System (ADS)
Miyakawa, Ryan; Anderson, Chris; Naulleau, Patrick
2017-03-01
In this paper we compare two non-interferometric wavefront sensors suitable for in-situ high-NA EUV optical testing. The first is the AIS sensor, which has been deployed in both inspection and exposure tools. AIS is a compact, optical test that directly measures a wavefront by probing various parts of the imaging optic pupil and measuring localized wavefront curvature. The second is an image-based technique that uses an iterative algorithm based on simulated annealing to reconstruct a wavefront based on matching aerial images through focus. In this technique, customized illumination is used to probe the pupil at specific points to optimize differences in aberration signatures.
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Ohura, Takehiko; Sanada, Hiromi; Mino, Yoshio
2004-01-01
In recent years, the concept of cost-effectiveness, including medical delivery and health service fee systems, has become widespread in Japanese health care. In the field of pressure ulcer management, the recent introduction of penalty subtraction in the care fee system emphasizes the need for prevention and cost-effective care of pressure ulcer. Previous cost-effectiveness research on pressure ulcer management tended to focus only on "hardware" costs such as those for pharmaceuticals and medical supplies, while neglecting other cost aspects, particularly those involving the cost of labor. Thus, cost-effectiveness in pressure ulcer care has not yet been fully established. To provide true cost effectiveness data, a comparative prospective study was initiated in patients with stage II and III pressure ulcers. Considering the potential impact of the pressure reduction mattress on clinical outcome, in particular, the same type of pressure reduction mattresses are utilized in all the cases in the study. The cost analysis method used was Activity-Based Costing, which measures material and labor cost aspects on a daily basis. A reduction in the Pressure Sore Status Tool (PSST) score was used to measure clinical effectiveness. Patients were divided into three groups based on the treatment method and on the use of a consistent algorithm of wound care: 1. MC/A group, modern dressings with a treatment algorithm (control cohort). 2. TC/A group, traditional care (ointment and gauze) with a treatment algorithm. 3. TC/NA group, traditional care (ointment and gauze) without a treatment algorithm. The results revealed that MC/A is more cost-effective than both TC/A and TC/NA. This suggests that appropriate utilization of modern dressing materials and a pressure ulcer care algorithm would contribute to reducing health care costs, improved clinical results, and, ultimately, greater cost-effectiveness.
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An efficient tensor transpose algorithm for multicore CPU, Intel Xeon Phi, and NVidia Tesla GPU
NASA Astrophysics Data System (ADS)
Lyakh, Dmitry I.
2015-04-01
An efficient parallel tensor transpose algorithm is suggested for shared-memory computing units, namely, multicore CPU, Intel Xeon Phi, and NVidia GPU. The algorithm operates on dense tensors (multidimensional arrays) and is based on the optimization of cache utilization on x86 CPU and the use of shared memory on NVidia GPU. From the applied side, the ultimate goal is to minimize the overhead encountered in the transformation of tensor contractions into matrix multiplications in computer implementations of advanced methods of quantum many-body theory (e.g., in electronic structure theory and nuclear physics). A particular accent is made on higher-dimensional tensors that typically appear in the so-called multireference correlated methods of electronic structure theory. Depending on tensor dimensionality, the presented optimized algorithms can achieve an order of magnitude speedup on x86 CPUs and 2-3 times speedup on NVidia Tesla K20X GPU with respect to the naïve scattering algorithm (no memory access optimization). The tensor transpose routines developed in this work have been incorporated into a general-purpose tensor algebra library (TAL-SH).
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Park, S W; Bebakar, W M W; Hernandez, P G; Macura, S; Hersløv, M L; de la Rosa, R
2017-02-01
To compare the efficacy and safety of two titration algorithms for insulin degludec/insulin aspart (IDegAsp) administered once daily with metformin in participants with insulin-naïve Type 2 diabetes mellitus. This open-label, parallel-group, 26-week, multicentre, treat-to-target trial, randomly allocated participants (1:1) to two titration arms. The Simple algorithm titrated IDegAsp twice weekly based on a single pre-breakfast self-monitored plasma glucose (SMPG) measurement. The Stepwise algorithm titrated IDegAsp once weekly based on the lowest of three consecutive pre-breakfast SMPG measurements. In both groups, IDegAsp once daily was titrated to pre-breakfast plasma glucose values of 4.0-5.0 mmol/l. Primary endpoint was change from baseline in HbA 1c (%) after 26 weeks. Change in HbA 1c at Week 26 was IDegAsp Simple -14.6 mmol/mol (-1.3%) (to 52.4 mmol/mol; 6.9%) and IDegAsp Stepwise -11.9 mmol/mol (-1.1%) (to 54.7 mmol/mol; 7.2%). The estimated between-group treatment difference was -1.97 mmol/mol [95% confidence interval (CI) -4.1, 0.2] (-0.2%, 95% CI -0.4, 0.02), confirming the non-inferiority of IDegAsp Simple to IDegAsp Stepwise (non-inferiority limit of ≤ 0.4%). Mean reduction in fasting plasma glucose and 8-point SMPG profiles were similar between groups. Rates of confirmed hypoglycaemia were lower for IDegAsp Stepwise [2.1 per patient years of exposure (PYE)] vs. IDegAsp Simple (3.3 PYE) (estimated rate ratio IDegAsp Simple /IDegAsp Stepwise 1.8; 95% CI 1.1, 2.9). Nocturnal hypoglycaemia rates were similar between groups. No severe hypoglycaemic events were reported. In participants with insulin-naïve Type 2 diabetes mellitus, the IDegAsp Simple titration algorithm improved HbA 1c levels as effectively as a Stepwise titration algorithm. Hypoglycaemia rates were lower in the Stepwise arm. © 2016 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.
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NASA Astrophysics Data System (ADS)
Ervin, Katherine; Shipman, Steven
2017-06-01
While rotational spectra can be rapidly collected, their analysis (especially for complex systems) is seldom straightforward, leading to a bottleneck. The AUTOFIT program was designed to serve that need by quickly matching rotational constants to spectra with little user input and supervision. This program can potentially be improved by incorporating an optimization algorithm in the search for a solution. The Particle Swarm Optimization Algorithm (PSO) was chosen for implementation. PSO is part of a family of optimization algorithms called heuristic algorithms, which seek approximate best answers. This is ideal for rotational spectra, where an exact match will not be found without incorporating distortion constants, etc., which would otherwise greatly increase the size of the search space. PSO was tested for robustness against five standard fitness functions and then applied to a custom fitness function created for rotational spectra. This talk will explain the Particle Swarm Optimization algorithm and how it works, describe how Autofit was modified to use PSO, discuss the fitness function developed to work with spectroscopic data, and show our current results. Seifert, N.A., Finneran, I.A., Perez, C., Zaleski, D.P., Neill, J.L., Steber, A.L., Suenram, R.D., Lesarri, A., Shipman, S.T., Pate, B.H., J. Mol. Spec. 312, 13-21 (2015)
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A stable compound of helium and sodium at high pressure
Dong, Xiao; Oganov, Artem R.; Goncharov, Alexander F.; ...
2017-02-06
Helium is generally understood to be chemically inert and this is due to its extremely stable closed-shell electronic configuration, zero electron affinity and an unsurpassed ionization potential. It is not known to form thermodynamically stable compounds, except a few inclusion compounds. Here, using the ab initio evolutionary algorithm USPEX and subsequent high-pressure synthesis in a diamond anvil cell, we report the discovery of a thermodynamically stable compound of helium and sodium, Na 2He, which has a fluorite-type structure and is stable at pressures >113 GPa. We show that the presence of He atoms causes strong electron localization and makes thismore » material insulating. This phase is an electride, with electron pairs localized in interstices, forming eight-centre two-electron bonds within empty Na 8 cubes. As a result, we also predict the existence of Na 2HeO with a similar structure at pressures above 15 GPa.« less
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A stable compound of helium and sodium at high pressure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, Xiao; Oganov, Artem R.; Goncharov, Alexander F.
Helium is generally understood to be chemically inert and this is due to its extremely stable closed-shell electronic configuration, zero electron affinity and an unsurpassed ionization potential. It is not known to form thermodynamically stable compounds, except a few inclusion compounds. Here, using the ab initio evolutionary algorithm USPEX and subsequent high-pressure synthesis in a diamond anvil cell, we report the discovery of a thermodynamically stable compound of helium and sodium, Na 2He, which has a fluorite-type structure and is stable at pressures >113 GPa. We show that the presence of He atoms causes strong electron localization and makes thismore » material insulating. This phase is an electride, with electron pairs localized in interstices, forming eight-centre two-electron bonds within empty Na 8 cubes. We also predict the existence of Na 2HeO with a similar structure at pressures above 15 GPa.« less
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A stable compound of helium and sodium at high pressure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, Xiao; Oganov, Artem R.; Goncharov, Alexander F.
Helium is generally understood to be chemically inert and this is due to its extremely stable closed-shell electronic configuration, zero electron affinity and an unsurpassed ionization potential. It is not known to form thermodynamically stable compounds, except a few inclusion compounds. Here, using the ab initio evolutionary algorithm USPEX and subsequent high-pressure synthesis in a diamond anvil cell, we report the discovery of a thermodynamically stable compound of helium and sodium, Na 2He, which has a fluorite-type structure and is stable at pressures >113 GPa. We show that the presence of He atoms causes strong electron localization and makes thismore » material insulating. This phase is an electride, with electron pairs localized in interstices, forming eight-centre two-electron bonds within empty Na 8 cubes. As a result, we also predict the existence of Na 2HeO with a similar structure at pressures above 15 GPa.« less
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Data fusion for a vision-aided radiological detection system: Calibration algorithm performance
NASA Astrophysics Data System (ADS)
Stadnikia, Kelsey; Henderson, Kristofer; Martin, Allan; Riley, Phillip; Koppal, Sanjeev; Enqvist, Andreas
2018-05-01
In order to improve the ability to detect, locate, track and identify nuclear/radiological threats, the University of Florida nuclear detection community has teamed up with the 3D vision community to collaborate on a low cost data fusion system. The key is to develop an algorithm to fuse the data from multiple radiological and 3D vision sensors as one system. The system under development at the University of Florida is being assessed with various types of radiological detectors and widely available visual sensors. A series of experiments were devised utilizing two EJ-309 liquid organic scintillation detectors (one primary and one secondary), a Microsoft Kinect for Windows v2 sensor and a Velodyne HDL-32E High Definition LiDAR Sensor which is a highly sensitive vision sensor primarily used to generate data for self-driving cars. Each experiment consisted of 27 static measurements of a source arranged in a cube with three different distances in each dimension. The source used was Cf-252. The calibration algorithm developed is utilized to calibrate the relative 3D-location of the two different types of sensors without need to measure it by hand; thus, preventing operator manipulation and human errors. The algorithm can also account for the facility dependent deviation from ideal data fusion correlation. Use of the vision sensor to determine the location of a sensor would also limit the possible locations and it does not allow for room dependence (facility dependent deviation) to generate a detector pseudo-location to be used for data analysis later. Using manually measured source location data, our algorithm-predicted the offset detector location within an average of 20 cm calibration-difference to its actual location. Calibration-difference is the Euclidean distance from the algorithm predicted detector location to the measured detector location. The Kinect vision sensor data produced an average calibration-difference of 35 cm and the HDL-32E produced an average calibration-difference of 22 cm. Using NaI and He-3 detectors in place of the EJ-309, the calibration-difference was 52 cm for NaI and 75 cm for He-3. The algorithm is not detector dependent; however, from these results it was determined that detector dependent adjustments are required.
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A novel artificial immune clonal selection classification and rule mining with swarm learning model
NASA Astrophysics Data System (ADS)
Al-Sheshtawi, Khaled A.; Abdul-Kader, Hatem M.; Elsisi, Ashraf B.
2013-06-01
Metaheuristic optimisation algorithms have become popular choice for solving complex problems. By integrating Artificial Immune clonal selection algorithm (CSA) and particle swarm optimisation (PSO) algorithm, a novel hybrid Clonal Selection Classification and Rule Mining with Swarm Learning Algorithm (CS2) is proposed. The main goal of the approach is to exploit and explore the parallel computation merit of Clonal Selection and the speed and self-organisation merits of Particle Swarm by sharing information between clonal selection population and particle swarm. Hence, we employed the advantages of PSO to improve the mutation mechanism of the artificial immune CSA and to mine classification rules within datasets. Consequently, our proposed algorithm required less training time and memory cells in comparison to other AIS algorithms. In this paper, classification rule mining has been modelled as a miltiobjective optimisation problem with predictive accuracy. The multiobjective approach is intended to allow the PSO algorithm to return an approximation to the accuracy and comprehensibility border, containing solutions that are spread across the border. We compared our proposed algorithm classification accuracy CS2 with five commonly used CSAs, namely: AIRS1, AIRS2, AIRS-Parallel, CLONALG, and CSCA using eight benchmark datasets. We also compared our proposed algorithm classification accuracy CS2 with other five methods, namely: Naïve Bayes, SVM, MLP, CART, and RFB. The results show that the proposed algorithm is comparable to the 10 studied algorithms. As a result, the hybridisation, built of CSA and PSO, can develop respective merit, compensate opponent defect, and make search-optimal effect and speed better.
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In vivo self-gated 23 Na MRI at 7 T using an oval-shaped body resonator.
Platt, Tanja; Umathum, Reiner; Fiedler, Thomas M; Nagel, Armin M; Bitz, Andreas K; Maier, Florian; Bachert, Peter; Ladd, Mark E; Wielpütz, Mark O; Kauczor, Hans-Ulrich; Behl, Nicolas G R
2018-02-09
This work faces three challenges of sodium ( 23 Na) torso MRI on the way to quantitative 23 Na MRI: Development of a 23 Na radiofrequency transmit and receive coil covering a large part of the human body in width and length for 23 Na MRI at 7 T; reduction of blurring due to respiration in free-breathing 23 Na MRI using a self-gating approach; and reduction of image noise using a compressed-sensing reconstruction. An oval-shaped birdcage resonator with a large field of view of (400 mm) 3 and a homogeneous transmit and receive field distribution was designed, simulated, and implemented on a 7T MR system. In free-breathing 3-dimensional radial 23 Na MRI (acquisition time ≈ 30 minutes), retrospective respiratory self-gating was applied, which sorts the acquired projections into two respiratory states based on the intrinsic respiration-dependent signal changes. Furthermore, a 3-dimensional dictionary-learning compressed-sensing reconstruction was applied. The developed body coil provided homogeneous radiofrequency excitation (flip angle error of 4.9% in central region of interest of 23 × 13 × 10 cm 3 ) and homogeneous signal reception. The self-gating approach allowed for separation of the full data set into two subsets associated with different respiratory states (inhaled and exhaled), and thereby reduced blurring due to respiration in the separated images. Image noise was markedly reduced by the compressed-sensing algorithm. The presented body coil enables full body width 23 Na MRI with long z-axis coverage at 7 T for the first time. Additionally, the retrospective respiratory self-gating performance is demonstrated for free-breathing lung and abdominal 23 Na MRI in 3 subjects. © 2018 International Society for Magnetic Resonance in Medicine.
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NASA Astrophysics Data System (ADS)
Langowski, M. P.; von Savigny, C.; Burrows, J. P.; Rozanov, V. V.; Dunker, T.; Hoppe, U.-P.; Sinnhuber, M.; Aikin, A. C.
2015-07-01
An algorithm has been developed for the retrieval of sodium atom (Na) number density on a latitude and altitude grid from SCIAMACHY limb measurements of the Na resonance fluorescence. The results are obtained between 50 and 150 km altitude and the resulting global seasonal variations of Na are analysed. The retrieval approach is adapted from that used for the retrieval of magnesium atom (Mg) and magnesium ion (Mg+) number density profiles recently reported by Langowski et al. (2014). Monthly mean values of Na are presented as a function of altitude and latitude. This data set was retrieved from the 4 years of spectroscopic limb data of the SCIAMACHY mesosphere and lower thermosphere (MLT) measurement mode. The Na layer has a nearly constant altitude of 90-93 km for all latitudes and seasons, and has a full width at half maximum of 5-15 km. Small but substantial seasonal variations in Na are identified for latitudes less than 40°, where the maximum Na number densities are 3000-4000 atoms cm-3. At mid to high latitudes a clear seasonal variation with a winter maximum of up to 6000 atoms cm-3 is observed. The high latitudes, which are only measured in the Summer Hemisphere, have lower number densities with peak densities being approximately 1000 Na atoms cm-3. The full width at half maximum of the peak varies strongly at high latitudes and is 5 km near the polar summer mesopause, while it exceeds 10 km at lower latitudes. In summer the Na atom concentration at high latitudes and at altitudes below 88 km is significantly smaller than that at mid latitudes. The results are compared with other observations and models and there is overall a good agreement with these.
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Phase measurements of EUV mask defects
Claus, Rene A.; Wang, Yow-Gwo; Wojdyla, Antoine; ...
2015-02-22
Extreme Ultraviolet (EUV) Lithography mask defects were examined on the actinic mask imaging system, SHARP, at Lawrence Berkeley National Laboratory. Also, a quantitative phase retrieval algorithm based on the Weak Object Transfer Function was applied to the measured through-focus aerial images to examine the amplitude and phase of the defects. The accuracy of the algorithm was demonstrated by comparing the results of measurements using a phase contrast zone plate and a standard zone plate. Using partially coherent illumination to measure frequencies that would otherwise fall outside the numerical aperture (NA), it was shown that some defects are smaller than themore » conventional resolution of the microscope. We found that the programmed defects of various sizes were measured and shown to have both an amplitude and a phase component that the algorithm is able to recover.« less
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Computing aggregate properties of preimages for 2D cellular automata.
Beer, Randall D
2017-11-01
Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm-incremental aggregation-that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.
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Under-reported data analysis with INAR-hidden Markov chains.
Fernández-Fontelo, Amanda; Cabaña, Alejandra; Puig, Pedro; Moriña, David
2016-11-20
In this work, we deal with correlated under-reported data through INAR(1)-hidden Markov chain models. These models are very flexible and can be identified through its autocorrelation function, which has a very simple form. A naïve method of parameter estimation is proposed, jointly with the maximum likelihood method based on a revised version of the forward algorithm. The most-probable unobserved time series is reconstructed by means of the Viterbi algorithm. Several examples of application in the field of public health are discussed illustrating the utility of the models. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Naïve Bayes Approach for Expert System Design of Children Skin Identification Based on Android
NASA Astrophysics Data System (ADS)
Hartatik; Purnomo, A.; Hartono, R.; Munawaroh, H.
2018-03-01
The development of technology gives some benefits to each person that we can use it properly and correctly. Technology has helped humans in every way. Such as the excess task of an expert in providing information or answers to a problem. Thus problem that often occurs is skin disease that affecting on child. That because the skin of children still vulnerable to the environment. The application was developed using the naïve Bayes algorithm. Through this application, users can consult with a system like an expert to know the symptoms that occur to the child and find the correct treatment to solve the problems.
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1990-05-07
Sawin, and R. A. Brown J-3 COMPARISON OF CF AND CF2 LIF AND ACTINOMETRY IN A CF4 DISCHARGE L. D. Baston , J.-P. Nicolai, and H. H. Sawin J-4 SPATIAL...the algorithm. 109 Comparison of CF and CF7 LIF and Actinometry in a CF4 Discharge, L. D. BASTON , J.-P. NICOLAI, and H. H. SAWIN, MIT- Relative...28Baravian, G. E-32 Clark, R.E.H. J-27 Bardsley, J. N. BC-3, MA-4, NB-1 Clark, S. BB-2Bartnikas, R. NA-16 Colbert, T. NA-30 Baston , L. D. J-3 Colgan, M
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Trajectory NG: portable, compressed, general molecular dynamics trajectories.
Spångberg, Daniel; Larsson, Daniel S D; van der Spoel, David
2011-10-01
We present general algorithms for the compression of molecular dynamics trajectories. The standard ways to store MD trajectories as text or as raw binary floating point numbers result in very large files when efficient simulation programs are used on supercomputers. Our algorithms are based on the observation that differences in atomic coordinates/velocities, in either time or space, are generally smaller than the absolute values of the coordinates/velocities. Also, it is often possible to store values at a lower precision. We apply several compression schemes to compress the resulting differences further. The most efficient algorithms developed here use a block sorting algorithm in combination with Huffman coding. Depending on the frequency of storage of frames in the trajectory, either space, time, or combinations of space and time differences are usually the most efficient. We compare the efficiency of our algorithms with each other and with other algorithms present in the literature for various systems: liquid argon, water, a virus capsid solvated in 15 mM aqueous NaCl, and solid magnesium oxide. We perform tests to determine how much precision is necessary to obtain accurate structural and dynamic properties, as well as benchmark a parallelized implementation of the algorithms. We obtain compression ratios (compared to single precision floating point) of 1:3.3-1:35 depending on the frequency of storage of frames and the system studied.
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ERIC Educational Resources Information Center
Lombardi, Allison; Seburn, Mary; Conley, David
2011-01-01
In this study, Don't Know/Not Applicable (DK/NA) responses on a measure of academic behaviors associated with college readiness for high school students were treated with: (a) casewise deletion, (b) scale inclusion at the lowest level, and (c) imputation using E/M algorithm. Significant differences in mean responses according to treatment…
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Thai Automatic Speech Recognition
2005-01-01
used in an external DARPA evaluation involving medical scenarios between an American Doctor and a naïve monolingual Thai patient. 2. Thai Language... dictionary generation more challenging, and (3) the lack of word segmentation, which calls for automatic segmentation approaches to make n-gram language...requires a dictionary and provides various segmentation algorithms to automatically select suitable segmentations. Here we used a maximal matching
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Graphics Processors in HEP Low-Level Trigger Systems
NASA Astrophysics Data System (ADS)
Ammendola, Roberto; Biagioni, Andrea; Chiozzi, Stefano; Cotta Ramusino, Angelo; Cretaro, Paolo; Di Lorenzo, Stefano; Fantechi, Riccardo; Fiorini, Massimiliano; Frezza, Ottorino; Lamanna, Gianluca; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Neri, Ilaria; Paolucci, Pier Stanislao; Pastorelli, Elena; Piandani, Roberto; Pontisso, Luca; Rossetti, Davide; Simula, Francesco; Sozzi, Marco; Vicini, Piero
2016-11-01
Usage of Graphics Processing Units (GPUs) in the so called general-purpose computing is emerging as an effective approach in several fields of science, although so far applications have been employing GPUs typically for offline computations. Taking into account the steady performance increase of GPU architectures in terms of computing power and I/O capacity, the real-time applications of these devices can thrive in high-energy physics data acquisition and trigger systems. We will examine the use of online parallel computing on GPUs for the synchronous low-level trigger, focusing on tests performed on the trigger system of the CERN NA62 experiment. To successfully integrate GPUs in such an online environment, latencies of all components need analysing, networking being the most critical. To keep it under control, we envisioned NaNet, an FPGA-based PCIe Network Interface Card (NIC) enabling GPUDirect connection. Furthermore, it is assessed how specific trigger algorithms can be parallelized and thus benefit from a GPU implementation, in terms of increased execution speed. Such improvements are particularly relevant for the foreseen Large Hadron Collider (LHC) luminosity upgrade where highly selective algorithms will be essential to maintain sustainable trigger rates with very high pileup.
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Is Self-organization a Rational Expectation?
NASA Astrophysics Data System (ADS)
Luediger, Heinz
Over decades and under varying names the study of biology-inspired algorithms applied to non-living systems has been the subject of a small and somewhat exotic research community. Only the recent coincidence of a growing inability to master the design, development and operation of increasingly intertwined systems and processes, and an accelerated trend towards a naïve if not romanticizing view of nature in the sciences, has led to the adoption of biology-inspired algorithmic research by a wider range of sciences. Adaptive systems, as we apparently observe in nature, are meanwhile viewed as a promising way out of the complexity trap and, propelled by a long list of ‘self’ catchwords, complexity research has become an influential stream in the science community. This paper presents four provocative theses that cast doubt on the strategic potential of complexity research and the viability of large scale deployment of biology-inspired algorithms in an expectation driven world.
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An efficient tensor transpose algorithm for multicore CPU, Intel Xeon Phi, and NVidia Tesla GPU
Lyakh, Dmitry I.
2015-01-05
An efficient parallel tensor transpose algorithm is suggested for shared-memory computing units, namely, multicore CPU, Intel Xeon Phi, and NVidia GPU. The algorithm operates on dense tensors (multidimensional arrays) and is based on the optimization of cache utilization on x86 CPU and the use of shared memory on NVidia GPU. From the applied side, the ultimate goal is to minimize the overhead encountered in the transformation of tensor contractions into matrix multiplications in computer implementations of advanced methods of quantum many-body theory (e.g., in electronic structure theory and nuclear physics). A particular accent is made on higher-dimensional tensors that typicallymore » appear in the so-called multireference correlated methods of electronic structure theory. Depending on tensor dimensionality, the presented optimized algorithms can achieve an order of magnitude speedup on x86 CPUs and 2-3 times speedup on NVidia Tesla K20X GPU with respect to the na ve scattering algorithm (no memory access optimization). Furthermore, the tensor transpose routines developed in this work have been incorporated into a general-purpose tensor algebra library (TAL-SH).« less
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Pediatric negative appendectomy rate: trend, predictors, and differentials.
Oyetunji, Tolulope A; Ong'uti, Sharon K; Bolorunduro, Oluwaseyi B; Cornwell, Edward E; Nwomeh, Benedict C
2012-03-01
Appendectomy is one of the most commonly performed emergency operations in children. The diagnosis of appendicitis can be quite challenging, particularly in children. We set out to determine the accuracy of diagnosis of appendicitis by analyzing the trends in the negative appendectomy rate (NAR) using a national database. Analysis of the Kids Inpatient Database (KID) was performed for the years 2000, 2003, and 2006 on children with appendectomy, excluding incidental appendectomies. Children (<18 y) without appendicitis but who underwent appendectomies were classified as negative appendectomies (NA), and those with appendicitis as positive appendectomies (PA). Comparisons were made between those with PA versus NA by demographic characteristics. The subset of patients with NA was then further analyzed. An estimated 250,783 appendectomies met the inclusion criteria. The NAR was 6.7%. Length of stay (LOS) was longer in NA versus PA (7 versus 3 d, P < 0.05). The NAR was increased in children under 5 y (21.1% versus 5.4% for among the 5-10 y versus 5.9% among the >10 y, P < 0.0001) and in females (9.3% versus 5.1%, P < 0.001). On multivariate analysis, increasing age was associated with lower odds of NA (OR = 0.92, P < 0.001). Females, rural hospitals, and Blacks were significantly more likely to experience NA. Younger age, female gender, Black ethnicity and rural hospitals are independent predictors of NA. These factors can be incorporated into diagnostic algorithms to improve the accuracy of diagnosis of appendicitis in children. Copyright © 2012 Elsevier Inc. All rights reserved.
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Axial field shaping under high-numerical-aperture focusing
NASA Astrophysics Data System (ADS)
Jabbour, Toufic G.; Kuebler, Stephen M.
2007-03-01
Kant reported [J. Mod. Optics47, 905 (2000)] a formulation for solving the inverse problem of vector diffraction, which accurately models high-NA focusing. Here, Kant's formulation is adapted to the method of generalized projections to obtain an algorithm for designing diffractive optical elements (DOEs) that reshape the axial point-spread function (PSF). The algorithm is applied to design a binary phase-only DOE that superresolves the axial PSF with controlled increase in axial sidelobes. An 11-zone DOE is identified that axially narrows the PSF central lobe by 29% while maintaining the sidelobe intensity at or below 52% of the peak intensity. This DOE could improve the resolution achievable in several applications without significantly complicating the optical system.
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NASA Astrophysics Data System (ADS)
Tornga, Shawn R.
The Stand-off Radiation Detection System (SORDS) program is an Advanced Technology Demonstration (ATD) project through the Department of Homeland Security's Domestic Nuclear Detection Office (DNDO) with the goal of detection, identification and localization of weak radiological sources in the presence of large dynamic backgrounds. The Raytheon-SORDS Tri-Modal Imager (TMI) is a mobile truck-based, hybrid gamma-ray imaging system able to quickly detect, identify and localize, radiation sources at standoff distances through improved sensitivity while minimizing the false alarm rate. Reconstruction of gamma-ray sources is performed using a combination of two imaging modalities; coded aperture and Compton scatter imaging. The TMI consists of 35 sodium iodide (NaI) crystals 5x5x2 in3 each, arranged in a random coded aperture mask array (CA), followed by 30 position sensitive NaI bars each 24x2.5x3 in3 called the detection array (DA). The CA array acts as both a coded aperture mask and scattering detector for Compton events. The large-area DA array acts as a collection detector for both Compton scattered events and coded aperture events. In this thesis, developed coded aperture, Compton and hybrid imaging algorithms will be described along with their performance. It will be shown that multiple imaging modalities can be fused to improve detection sensitivity over a broader energy range than either alone. Since the TMI is a moving system, peripheral data, such as a Global Positioning System (GPS) and Inertial Navigation System (INS) must also be incorporated. A method of adapting static imaging algorithms to a moving platform has been developed. Also, algorithms were developed in parallel with detector hardware, through the use of extensive simulations performed with the Geometry and Tracking Toolkit v4 (GEANT4). Simulations have been well validated against measured data. Results of image reconstruction algorithms at various speeds and distances will be presented as well as localization capability. Utilizing imaging information will show signal-to-noise gains over spectroscopic algorithms alone.
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Guan, Hao; Liu, Tao; Jiang, Jiyang; Tao, Dacheng; Zhang, Jicong; Niu, Haijun; Zhu, Wanlin; Wang, Yilong; Cheng, Jian; Kochan, Nicole A.; Brodaty, Henry; Sachdev, Perminder; Wen, Wei
2017-01-01
Amnestic MCI (aMCI) and non-amnestic MCI (naMCI) are considered to differ in etiology and outcome. Accurately classifying MCI into meaningful subtypes would enable early intervention with targeted treatment. In this study, we employed structural magnetic resonance imaging (MRI) for MCI subtype classification. This was carried out in a sample of 184 community-dwelling individuals (aged 73–85 years). Cortical surface based measurements were computed from longitudinal and cross-sectional scans. By introducing a feature selection algorithm, we identified a set of discriminative features, and further investigated the temporal patterns of these features. A voting classifier was trained and evaluated via 10 iterations of cross-validation. The best classification accuracies achieved were: 77% (naMCI vs. aMCI), 81% (aMCI vs. cognitively normal (CN)) and 70% (naMCI vs. CN). The best results for differentiating aMCI from naMCI were achieved with baseline features. Hippocampus, amygdala and frontal pole were found to be most discriminative for classifying MCI subtypes. Additionally, we observed the dynamics of classification of several MRI biomarkers. Learning the dynamics of atrophy may aid in the development of better biomarkers, as it may track the progression of cognitive impairment. PMID:29085292
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Lyakh, Dmitry I.
An efficient parallel tensor transpose algorithm is suggested for shared-memory computing units, namely, multicore CPU, Intel Xeon Phi, and NVidia GPU. The algorithm operates on dense tensors (multidimensional arrays) and is based on the optimization of cache utilization on x86 CPU and the use of shared memory on NVidia GPU. From the applied side, the ultimate goal is to minimize the overhead encountered in the transformation of tensor contractions into matrix multiplications in computer implementations of advanced methods of quantum many-body theory (e.g., in electronic structure theory and nuclear physics). A particular accent is made on higher-dimensional tensors that typicallymore » appear in the so-called multireference correlated methods of electronic structure theory. Depending on tensor dimensionality, the presented optimized algorithms can achieve an order of magnitude speedup on x86 CPUs and 2-3 times speedup on NVidia Tesla K20X GPU with respect to the na ve scattering algorithm (no memory access optimization). Furthermore, the tensor transpose routines developed in this work have been incorporated into a general-purpose tensor algebra library (TAL-SH).« less
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Stinnett, Jacob; Sullivan, Clair J.; Xiong, Hao
2017-03-02
Low-resolution isotope identifiers are widely deployed for nuclear security purposes, but these detectors currently demonstrate problems in making correct identifications in many typical usage scenarios. While there are many hardware alternatives and improvements that can be made, performance on existing low resolution isotope identifiers should be able to be improved by developing new identification algorithms. We have developed a wavelet-based peak extraction algorithm and an implementation of a Bayesian classifier for automated peak-based identification. The peak extraction algorithm has been extended to compute uncertainties in the peak area calculations. To build empirical joint probability distributions of the peak areas andmore » uncertainties, a large set of spectra were simulated in MCNP6 and processed with the wavelet-based feature extraction algorithm. Kernel density estimation was then used to create a new component of the likelihood function in the Bayesian classifier. Furthermore, identification performance is demonstrated on a variety of real low-resolution spectra, including Category I quantities of special nuclear material.« less
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Real-time track-less Cherenkov ring fitting trigger system based on Graphics Processing Units
NASA Astrophysics Data System (ADS)
Ammendola, R.; Biagioni, A.; Chiozzi, S.; Cretaro, P.; Cotta Ramusino, A.; Di Lorenzo, S.; Fantechi, R.; Fiorini, M.; Frezza, O.; Gianoli, A.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Piccini, M.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Vicini, P.
2017-12-01
The parallel computing power of commercial Graphics Processing Units (GPUs) is exploited to perform real-time ring fitting at the lowest trigger level using information coming from the Ring Imaging Cherenkov (RICH) detector of the NA62 experiment at CERN. To this purpose, direct GPU communication with a custom FPGA-based board has been used to reduce the data transmission latency. The GPU-based trigger system is currently integrated in the experimental setup of the RICH detector of the NA62 experiment, in order to reconstruct ring-shaped hit patterns. The ring-fitting algorithm running on GPU is fed with raw RICH data only, with no information coming from other detectors, and is able to provide more complex trigger primitives with respect to the simple photodetector hit multiplicity, resulting in a higher selection efficiency. The performance of the system for multi-ring Cherenkov online reconstruction obtained during the NA62 physics run is presented.
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Mora, Juan David Sandino; Hurtado, Darío Amaya; Sandoval, Olga Lucía Ramos
2016-01-01
Background: Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. Methods: It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. Results: There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. Conclusions: The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands. PMID:27833725
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Mora, Juan David Sandino; Hurtado, Darío Amaya; Sandoval, Olga Lucía Ramos
2016-01-01
Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands.
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Transfer Learning in Integrated Cognitive Systems
2010-09-01
Psychology Press. 2. Falkenhainer, B ., Forbus, K . D., and Gentner, D. (1989). The Structure-mapping Engine: Algorithm and Examples. Artificial...Kaps, A.; Lemcke, K .; Mannhaupt, G.; Pfeiffer, F.; Schuller, C.; Stocker, S. & Weil, B ., "MIPS: A Database for Genomes and Protein Sequences...NAME OF RESPONSIBLE PERSON Deborah A. Cerino a. REPORT U b . ABSTRACT U c. THIS PAGE U 19b. TELEPHONE NUMBER (Include area code) N/A
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NASA Astrophysics Data System (ADS)
Langowski, M. P.; von Savigny, C.; Burrows, J. P.; Rozanov, V. V.; Dunker, T.; Hoppe, U.-P.; Sinnhuber, M.; Aikin, A. C.
2016-01-01
An algorithm has been developed for the retrieval of sodium atom (Na) number density on a latitude and altitude grid from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) limb measurements of the Na resonance fluorescence. The results are obtained between 50 and 150 km altitude and the resulting global seasonal variations of Na are analyzed. The retrieval approach is adapted from that used for the retrieval of magnesium atom (Mg) and magnesium ion (Mg+) number density profiles recently reported by Langowski et al. (2014). Monthly mean values of Na are presented as a function of altitude and latitude. This data set was retrieved from the 4 years of spectroscopic limb data of the SCIAMACHY mesosphere and lower thermosphere (MLT) measurement mode (mid-2008 to early 2012). The Na layer has a nearly constant peak altitude of 90-93 km for all latitudes and seasons, and has a full width at half maximum of 5-15 km. Small but significant seasonal variations in Na are identified for latitudes less than 40°, where the maximum Na number densities are 3000-4000 atoms cm-3. At middle to high latitudes a clear seasonal variation with a winter maximum of up to 6000 atoms cm-3 is observed. The high latitudes, which are only measured in the summer hemisphere, have lower number densities, with peak densities being approximately 1000 Na atoms cm-3. The full width at half maximum of the peak varies strongly at high latitudes and is 5 km near the polar summer mesopause, while it exceeds 10 km at lower latitudes. In summer the Na atom concentration at high latitudes and at altitudes below 88 km is significantly smaller than that at middle latitudes. The results are compared with other observations and models and there is overall a good agreement with these.
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Nelson, Tammie; Fernandez-Alberti, Sebastian; Roitberg, Adrian E; Tretiak, Sergei
2014-04-15
To design functional photoactive materials for a variety of technological applications, researchers need to understand their electronic properties in detail and have ways to control their photoinduced pathways. When excited by photons of light, organic conjugated materials (OCMs) show dynamics that are often characterized by large nonadiabatic (NA) couplings between multiple excited states through a breakdown of the Born-Oppenheimer (BO) approximation. Following photoexcitation, various nonradiative intraband relaxation pathways can lead to a number of complex processes. Therefore, computational simulation of nonadiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons. Over the years, we have developed a nonadiabatic excited-state molecular dynamics (NA-ESMD) framework that efficiently and accurately describes photoinduced phenomena in extended conjugated molecular systems. We use the fewest-switches surface hopping (FSSH) algorithm to treat quantum transitions among multiple adiabatic excited state potential energy surfaces (PESs). Extended molecular systems often contain hundreds of atoms and involve large densities of excited states that participate in the photoinduced dynamics. We can achieve an accurate description of the multiple excited states using the configuration interaction single (CIS) formalism with a semiempirical model Hamiltonian. Analytical techniques allow the trajectory to be propagated "on the fly" using the complete set of NA coupling terms and remove computational bottlenecks in the evaluation of excited-state gradients and NA couplings. Furthermore, the use of state-specific gradients for propagation of nuclei on the native excited-state PES eliminates the need for simplifications such as the classical path approximation (CPA), which only uses ground-state gradients. Thus, the NA-ESMD methodology offers a computationally tractable route for simulating hundreds of atoms on ~10 ps time scales where multiple coupled excited states are involved. In this Account, we review recent developments in the NA-ESMD modeling of photoinduced dynamics in extended conjugated molecules involving multiple coupled electronic states. We have successfully applied the outlined NA-ESMD framework to study ultrafast conformational planarization in polyfluorenes where the rate of torsional relaxation can be controlled based on the initial excitation. With the addition of the state reassignment algorithm to identify instances of unavoided crossings between noninteracting PESs, NA-ESMD can now be used to study systems in which these so-called trivial unavoided crossings are expected to predominate. We employ this technique to analyze the energy transfer between poly(phenylene vinylene) (PPV) segments where conformational fluctuations give rise to numerous instances of unavoided crossings leading to multiple pathways and complex energy transfer dynamics that cannot be described using a simple Förster model. In addition, we have investigated the mechanism of ultrafast unidirectional energy transfer in dendrimers composed of poly(phenylene ethynylene) (PPE) chromophores and have demonstrated that differential nuclear motion favors downhill energy transfer in dendrimers. The use of native excited-state gradients allows us to observe this feature.
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NASA Astrophysics Data System (ADS)
Bakker, Ronald J.
2018-06-01
The program AqSo_NaCl has been developed to calculate pressure - molar volume - temperature - composition (p-V-T-x) properties, enthalpy, and heat capacity of the binary H2O-NaCl system. The algorithms are designed in BASIC within the Xojo programming environment, and can be operated as stand-alone project with Macintosh-, Windows-, and Unix-based operating systems. A series of ten self-instructive interfaces (modules) are developed to calculate fluid inclusion properties and pore fluid properties. The modules may be used to calculate properties of pure NaCl, the halite-liquidus, the halite-vapourus, dew-point and bubble-point curves (liquid-vapour), critical point, and SLV solid-liquid-vapour curves at temperatures above 0.1 °C (with halite) and below 0.1 °C (with ice or hydrohalite). Isochores of homogeneous fluids and unmixed fluids in a closed system can be calculated and exported to a.txt file. Isochores calculated for fluid inclusions can be corrected according to the volumetric properties of quartz. Microthermometric data, i.e. dissolution temperatures and homogenization temperatures, can be used to calculated bulk fluid properties of fluid inclusions. Alternatively, in the absence of total homogenization temperature the volume fraction of the liquid phase in fluid inclusions can be used to obtain bulk properties.
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LDA boost classification: boosting by topics
NASA Astrophysics Data System (ADS)
Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li
2012-12-01
AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.
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Estimating the chance of success in IVF treatment using a ranking algorithm.
Güvenir, H Altay; Misirli, Gizem; Dilbaz, Serdar; Ozdegirmenci, Ozlem; Demir, Berfu; Dilbaz, Berna
2015-09-01
In medicine, estimating the chance of success for treatment is important in deciding whether to begin the treatment or not. This paper focuses on the domain of in vitro fertilization (IVF), where estimating the outcome of a treatment is very crucial in the decision to proceed with treatment for both the clinicians and the infertile couples. IVF treatment is a stressful and costly process. It is very stressful for couples who want to have a baby. If an initial evaluation indicates a low pregnancy rate, decision of the couple may change not to start the IVF treatment. The aim of this study is twofold, firstly, to develop a technique that can be used to estimate the chance of success for a couple who wants to have a baby and secondly, to determine the attributes and their particular values affecting the outcome in IVF treatment. We propose a new technique, called success estimation using a ranking algorithm (SERA), for estimating the success of a treatment using a ranking-based algorithm. The particular ranking algorithm used here is RIMARC. The performance of the new algorithm is compared with two well-known algorithms that assign class probabilities to query instances. The algorithms used in the comparison are Naïve Bayes Classifier and Random Forest. The comparison is done in terms of area under the ROC curve, accuracy and execution time, using tenfold stratified cross-validation. The results indicate that the proposed SERA algorithm has a potential to be used successfully to estimate the probability of success in medical treatment.
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Piekarski, Eve; Chitiboi, Teodora; Ramb, Rebecca; Feng, Li; Axel, Leon
2016-11-25
Arrhythmia can significantly alter the image quality of cardiovascular magnetic resonance (CMR); automatic detection and sorting of the most frequent types of arrhythmias during the CMR acquisition could potentially improve image quality. New CMR techniques, such as non-Cartesian CMR, can allow self-gating: from cardiac motion-related signal changes, we can detect cardiac cycles without an electrocardiogram. We can further use this data to obtain a surrogate for RR intervals (valley intervals: VV). Our purpose was to evaluate the feasibility of an automated method for classification of non-arrhythmic (NA) (regular cycles) and arrhythmic patients (A) (irregular cycles), and for sorting of common arrhythmia patterns between atrial fibrillation (AF) and premature ventricular contraction (PVC), using the cardiac motion-related signal obtained during self-gated free-breathing radial cardiac cine CMR with compressed sensing reconstruction (XD-GRASP). One hundred eleven patients underwent cardiac XD-GRASP CMR between October 2015 and February 2016; 33 were included for retrospective analysis with the proposed method (6 AF, 8 PVC, 19 NA; by recent ECG). We analyzed the VV, using pooled statistics (histograms) and sequential analysis (Poincaré plots), including the median (medVV), the weighted mean (meanVV), the total number of VV values (VVval), and the total range (VVTR) and half range (VVHR) of the cumulative frequency distribution of VV, including the median to half range (medVV/VVHR) and the half range to total range (VVHR/VVTR) ratios. We designed a simple algorithm for using the VV results to differentiate A from NA, and AF from PVC. Between NA and A, meanVV, VVval, VVTR, VVHR, medVV/VVHR and VVHR/VVTR ratios were significantly different (p values = 0.00014, 0.0027, 0.000028, 5×10 -9 , 0.002, respectively). Between AF and PVC, meanVV, VVval and medVV/VVHR ratio were significantly different (p values = 0.018, 0.007, 0.044, respectively). Using our algorithm, sensitivity, specificity, and accuracy were 93 %, 95 % and 94 % to discriminate between NA and A, and 83 %, 71 %, and 77 % to discriminate between AF and PVC, respectively; areas under the ROC curve were 0.93 and 0.89. Our study shows we can reliably detect arrhythmias and differentiate AF from PVC, using self-gated cardiac cine XD-GRASP CMR.
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A novel approach for dimension reduction of microarray.
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.
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Parallel Algorithms for Computer Vision
1990-04-01
NA86-1, Thinking Machines Corporation, Cambridge, MA, December 1986. [43] J. Little, G. Blelloch, and T. Cass. How to program the connection machine for... to program the connection machine for computer vision. In Proc. Workshop on Comp. Architecture for Pattern Analysis and Machine Intell., 1987. [92] J...In Proceedings of SPIE Conf. on Advances in Intelligent Robotics Systems, Bellingham, VA, 1987. SPIE. [91] J. Little, G. Blelloch, and T. Cass. How
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1999-09-01
PERFORMANCE COMPARISON BETWEEN STEREAUSIS AND INCOHERENT WIDEBAND MUSIC FOR LOCALIZATION OF GROUND VEHICLES September 1999 Tien Pham U.S. Army...present experimental results comparing the incoherent wideband MUSIC (IWM) algorithm developed by the Army Research Laboratory (ARL)1, 2 and the...Type N/A Dates Covered (from... to) ("DD MON YYYY") Title and Subtitle Performance Comparison Between Stereausis and Incoherent Wideband Music for
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Giesbrecht, Gerald F; Dewey, Deborah
2014-10-01
The Infant Behavior Questionnaire-Revised (IBQ-R) is a widely used parent report measure of infant temperament. Items marked 'does not apply' (NA) are treated as missing data when calculating scale scores, but the effect of this practice on assessment of infant temperament has not been reported. To determine the effect of NA responses on assessment of infant temperament and to evaluate the remedy offered by several missing data strategies. A prospective, community-based longitudinal cohort study. 401 infants who were born>37 weeks of gestation. Mothers completed the short form of the IBQ-R when infants were 3-months and 6-months of age. The rate of NA responses at the 3-month assessment was three times as high (22%) as the rate at six months (7%). Internal consistency was appreciably reduced and scale means were inflated in the presence of NA responses, especially at 3-months. The total number of NA items endorsed by individual parents was associated with infant age and parity. None of the missing data strategies completely eliminated problems related to NA responses but the Expectation Maximization algorithm greatly reduced these problems. The findings suggest that researchers should exercise caution when interpreting results obtained from infants at 3 months of age. Careful selection of scales, selecting a full length version of the IBQ-R, and use of a modern missing data technique may help to maintain the quality of data obtained from very young infants. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Navarro, Pedro J.; Fernández, Carlos; Borraz, Raúl; Alonso, Diego
2016-01-01
This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%). PMID:28025565
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Navarro, Pedro J; Fernández, Carlos; Borraz, Raúl; Alonso, Diego
2016-12-23
This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%).
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Aligning Biomolecular Networks Using Modular Graph Kernels
NASA Astrophysics Data System (ADS)
Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant
Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.
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HIV Drug Resistance Surveillance in Honduras after a Decade of Widespread Antiretroviral Therapy
Tapia-Trejo, Daniela; Meza, Rita I.; Nuñez, Sandra M.; Parham, Leda; Flores, Norma A.; Valladares, Diana; Pineda, Luisa M.; Flores, Dixiana; Motiño, Roxana; Umanzor, Víctor; Carbajal, Candy; Murillo, Wendy; Lorenzana, Ivette; Palou, Elsa Y.; Reyes-Terán, Gustavo
2015-01-01
Introduction We assessed HIV drug resistance (DR) in individuals failing ART (acquired DR, ADR) and in ART-naïve individuals (pre-ART DR, PDR) in Honduras, after 10 years of widespread availability of ART. Methods 365 HIV-infected, ART-naïve, and 381 ART-experienced Honduran individuals were enrolled in 5 reference centres in Tegucigalpa, San Pedro Sula, La Ceiba, and Choluteca between April 2013 and April 2015. Plasma HIV protease-RT sequences were obtained. HIVDR was assessed using the WHO HIVDR mutation list and the Stanford algorithm. Recently infected (RI) individuals were identified using a multi-assay algorithm. Results PDR to any ARV drug was 11.5% (95% CI 8.4–15.2%). NNRTI PDR prevalence (8.2%) was higher than NRTI (2.2%) and PI (1.9%, p<0.0001). No significant trends in time were observed when comparing 2013 and 2014, when using a moving average approach along the study period or when comparing individuals with >500 vs. <350 CD4+ T cells/μL. PDR in recently infected individuals was 13.6%, showing no significant difference with PDR in individuals with longstanding infection (10.7%). The most prevalent PDR mutations were M46IL (1.4%), T215 revertants (0.5%), and K103NS (5.5%). The overall ADR prevalence in individuals with <48 months on ART was 87.8% and for the ≥48 months on ART group 81.3%. ADR to three drug families increased in individuals with longer time on ART (p = 0.0343). M184V and K103N were the most frequent ADR mutations. PDR mutation frequency correlated with ADR mutation frequency for PI and NNRTI (p<0.01), but not for NRTI. Clusters of viruses were observed suggesting transmission of HIVDR both from ART-experienced to ART-naïve individuals and between ART-naïve individuals. Conclusions The global PDR prevalence in Honduras remains at the intermediate level, after 10 years of widespread availability of ART. Evidence of ADR influencing the presence of PDR was observed by phylogenetic analyses and ADR/PDR mutation frequency correlations. PMID:26558396
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HIV Drug Resistance Surveillance in Honduras after a Decade of Widespread Antiretroviral Therapy.
Avila-Ríos, Santiago; García-Morales, Claudia; Tapia-Trejo, Daniela; Meza, Rita I; Nuñez, Sandra M; Parham, Leda; Flores, Norma A; Valladares, Diana; Pineda, Luisa M; Flores, Dixiana; Motiño, Roxana; Umanzor, Víctor; Carbajal, Candy; Murillo, Wendy; Lorenzana, Ivette; Palou, Elsa Y; Reyes-Terán, Gustavo
2015-01-01
We assessed HIV drug resistance (DR) in individuals failing ART (acquired DR, ADR) and in ART-naïve individuals (pre-ART DR, PDR) in Honduras, after 10 years of widespread availability of ART. 365 HIV-infected, ART-naïve, and 381 ART-experienced Honduran individuals were enrolled in 5 reference centres in Tegucigalpa, San Pedro Sula, La Ceiba, and Choluteca between April 2013 and April 2015. Plasma HIV protease-RT sequences were obtained. HIVDR was assessed using the WHO HIVDR mutation list and the Stanford algorithm. Recently infected (RI) individuals were identified using a multi-assay algorithm. PDR to any ARV drug was 11.5% (95% CI 8.4-15.2%). NNRTI PDR prevalence (8.2%) was higher than NRTI (2.2%) and PI (1.9%, p<0.0001). No significant trends in time were observed when comparing 2013 and 2014, when using a moving average approach along the study period or when comparing individuals with >500 vs. <350 CD4+ T cells/μL. PDR in recently infected individuals was 13.6%, showing no significant difference with PDR in individuals with longstanding infection (10.7%). The most prevalent PDR mutations were M46IL (1.4%), T215 revertants (0.5%), and K103NS (5.5%). The overall ADR prevalence in individuals with <48 months on ART was 87.8% and for the ≥48 months on ART group 81.3%. ADR to three drug families increased in individuals with longer time on ART (p = 0.0343). M184V and K103N were the most frequent ADR mutations. PDR mutation frequency correlated with ADR mutation frequency for PI and NNRTI (p<0.01), but not for NRTI. Clusters of viruses were observed suggesting transmission of HIVDR both from ART-experienced to ART-naïve individuals and between ART-naïve individuals. The global PDR prevalence in Honduras remains at the intermediate level, after 10 years of widespread availability of ART. Evidence of ADR influencing the presence of PDR was observed by phylogenetic analyses and ADR/PDR mutation frequency correlations.
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Applications of the Schur Basis to Quantum Algorithms
2011-01-10
superpolynomial speedups based on quantum circuits. (a) Papers published in peer -reviewed journals (N/A for none) 1. D.A.Bacon, I.L. Chuang, A.W...reporting period. List the papers, including journal references, in the following categories: (b) Papers published in non- peer -reviewed journals or in...MIT, Department of EECS, 2008 7.00Number of Papers published in peer -reviewed journals: Number of Papers published in non peer -reviewed journals: (c
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Dependable Emergency-Response Networking Based on Retaskable Network Infrastructures
2008-04-01
a Focus Group for the National Reliability and Interoperability Council (NRIC VII), which has helped to suggest a list of possible types of agents...APR 2008 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Dependable Emergency-Response Networking Based on Retaskable Network...of his network op- timization algorithms. We would like to thank the TCIP Center team for their feed- back on this work. This work was supported in
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NASA Astrophysics Data System (ADS)
Ammendola, R.; Biagioni, A.; Chiozzi, S.; Cretaro, P.; Cotta Ramusino, A.; Di Lorenzo, S.; Fantechi, R.; Fiorini, M.; Frezza, O.; Gianoli, A.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Piccini, M.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Vicini, P.
2017-03-01
This project aims to exploit the parallel computing power of a commercial Graphics Processing Unit (GPU) to implement fast pattern matching in the Ring Imaging Cherenkov (RICH) detector for the level 0 (L0) trigger of the NA62 experiment. In this approach, the ring-fitting algorithm is seedless, being fed with raw RICH data, with no previous information on the ring position from other detectors. Moreover, since the L0 trigger is provided with a more elaborated information than a simple multiplicity number, it results in a higher selection power. Two methods have been studied in order to reduce the data transfer latency from the readout boards of the detector to the GPU, i.e., the use of a dedicated NIC device driver with very low latency and a direct data transfer protocol from a custom FPGA-based NIC to the GPU. The performance of the system, developed through the FPGA approach, for multi-ring Cherenkov online reconstruction obtained during the NA62 physics runs is presented.
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NASA Astrophysics Data System (ADS)
do Lago, Naydson Emmerson S. P.; Kardec Barros, Allan; Sousa, Nilviane Pires S.; Junior, Carlos Magno S.; Oliveira, Guilherme; Guimares Polisel, Camila; Eder Carvalho Santana, Ewaldo
2018-01-01
This study aims to develop an algorithm of an adaptive filter to determine the percentage of body fat based on the use of anthropometric indicators in adolescents. Measurements such as body mass, height and waist circumference were collected for a better analysis. The development of this filter was based on the Wiener filter, used to produce an estimate of a random process. The Wiener filter minimizes the mean square error between the estimated random process and the desired process. The LMS algorithm was also studied for the development of the filter because it is important due to its simplicity and facility of computation. Excellent results were obtained with the filter developed, being these results analyzed and compared with the data collected.
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An expert fitness diagnosis system based on elastic cloud computing.
Tseng, Kevin C; Wu, Chia-Chuan
2014-01-01
This paper presents an expert diagnosis system based on cloud computing. It classifies a user's fitness level based on supervised machine learning techniques. This system is able to learn and make customized diagnoses according to the user's physiological data, such as age, gender, and body mass index (BMI). In addition, an elastic algorithm based on Poisson distribution is presented to allocate computation resources dynamically. It predicts the required resources in the future according to the exponential moving average of past observations. The experimental results show that Naïve Bayes is the best classifier with the highest accuracy (90.8%) and that the elastic algorithm is able to capture tightly the trend of requests generated from the Internet and thus assign corresponding computation resources to ensure the quality of service.
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The effect of sample size and disease prevalence on supervised machine learning of narrative data.
McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George
2002-01-01
This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878
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Feng, Qi-Long; Wu, Dong-Mei; Cui, Xiang-Li; Zhao, Hua-Chen; Lin, Yuan-Yuan; Zhao, Lu-Ying; Wu, Bo-Wei
2010-10-25
Considering that α-1 repeat region may be involved in the ion binding and translocation of Na(+)-Ca(2+) exchanger (NCX), it is possible that the antibodies against NCX α-1 repeat may have a crucial action on NCX activity. The aim of the present study is to investigate the effect of antibody against α-1 repeat (117-137), designated as α-1(117-137), on NCX activity. The antibody against the synthesized α-1(117-137) was prepared and affinity-purified. Whole-cell patch clamp technique was used to study the change of Na(+)-Ca(2+) exchange current (I(Na/Ca)) in adult rat cardiomyocytes. To evaluate the functional specificity of this antibody, its effects on L-type Ca(2+) current (I(Ca,L)), voltage-gated Na(+) current (I(Na)) and delayed rectifier K(+) current (I(K)) were also observed. The amino acid sequences of α-1(117-137) in NCX and residues 1 076-1 096 within L-type Ca(2+) channel were compared using EMBOSS Pairwise Alignment Algorithms. The results showed that outward and inward I(Na/Ca) were decreased by the antibody against α-1(117-137) dose-dependently in the concentration range from 10 to 160 nmol/L, with IC(50) values of 18.9 nmol/L and 22.4 nmol/L, respectively. Meanwhile, the antibody also decreased I(Ca,L) in a concentration-dependent manner with IC(50) of 22.7 nmol/L. No obvious effects of the antibody on I(Na) and I(K) were observed. Moreover, comparison of the amino acid sequences showed there was 23.8% sequence similarity between NCX α-1(117-137) and residues 1 076-1 096 within L-type Ca(2+) channel. These results suggest that antibody against α-1(117-137) is a blocking antibody to NCX and can also decrease I(Ca,L) in a concentration-dependent manner, while it does not have obvious effects on I(Na) and I(K).
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Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data
Kang, D.-K.; Silvescu, A.; Honavar, V.
2009-01-01
In many application domains, there is a need for learning algorithms that can effectively exploit attribute value taxonomies (AVT)—hierarchical groupings of attribute values—to learn compact, comprehensible and accurate classifiers from data—including data that are partially specified. This paper describes AVT-NBL, a natural generalization of the naïve Bayes learner (NBL), for learning classifiers from AVT and data. Our experimental results show that AVT-NBL is able to generate classifiers that are substantially more compact and more accurate than those produced by NBL on a broad range of data sets with different percentages of partially specified values. We also show that AVT-NBL is more efficient in its use of training data: AVT-NBL produces classifiers that outperform those produced by NBL using substantially fewer training examples. PMID:20351793
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1980-01-01
VPARTER. , STEUERWALT No 0I 76_C-03AI UNCLASSIFIED CSTR -374 ML M EMON~hEE 111112.08 12.5 111112 1.4 1 1. KWOCP RSLINTS CHR NA11~ L .R~l0 ___VRD I-l...4b) are obtained from the well known algorithm for solving diagonally dominant tridiagonal sys- tems; see (16, 10]. The monotonicity of the Ej and the
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2008-12-20
Equation 6 for the sample likelihood function gives a “concentrated likelihood function,” which depends on correlation parameters θh and ph. This...step one and estimates correlation parameters using the new data set including all previous sample points and the new data point x. The algorithm...Unclassified b. ABSTRACT Unclassified c. THIS PAGE Unclassified UU 279 19b. TELEPHONE NUMBER (include area code ) N/A
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Reduze - Feynman integral reduction in C++
NASA Astrophysics Data System (ADS)
Studerus, C.
2010-07-01
Reduze is a computer program for reducing Feynman integrals to master integrals employing a Laporta algorithm. The program is written in C++ and uses classes provided by the GiNaC library to perform the simplifications of the algebraic prefactors in the system of equations. Reduze offers the possibility to run reductions in parallel. Program summaryProgram title:Reduze Catalogue identifier: AEGE_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGE_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions:: yes No. of lines in distributed program, including test data, etc.: 55 433 No. of bytes in distributed program, including test data, etc.: 554 866 Distribution format: tar.gz Programming language: C++ Computer: All Operating system: Unix/Linux Number of processors used: The number of processors is problem dependent. More than one possible but not arbitrary many. RAM: Depends on the complexity of the system. Classification: 4.4, 5 External routines: CLN ( http://www.ginac.de/CLN/), GiNaC ( http://www.ginac.de/) Nature of problem: Solving large systems of linear equations with Feynman integrals as unknowns and rational polynomials as prefactors. Solution method: Using a Gauss/Laporta algorithm to solve the system of equations. Restrictions: Limitations depend on the complexity of the system (number of equations, number of kinematic invariants). Running time: Depends on the complexity of the system.
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Automatic motor task selection via a bandit algorithm for a brain-controlled button
NASA Astrophysics Data System (ADS)
Fruitet, Joan; Carpentier, Alexandra; Munos, Rémi; Clerc, Maureen
2013-02-01
Objective. Brain-computer interfaces (BCIs) based on sensorimotor rhythms use a variety of motor tasks, such as imagining moving the right or left hand, the feet or the tongue. Finding the tasks that yield best performance, specifically to each user, is a time-consuming preliminary phase to a BCI experiment. This study presents a new adaptive procedure to automatically select (online) the most promising motor task for an asynchronous brain-controlled button. Approach. We develop for this purpose an adaptive algorithm UCB-classif based on the stochastic bandit theory and design an EEG experiment to test our method. We compare (offline) the adaptive algorithm to a naïve selection strategy which uses uniformly distributed samples from each task. We also run the adaptive algorithm online to fully validate the approach. Main results. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. More precisely, the offline analysis reveals that the use of this algorithm can reduce the time needed to select the most appropriate task by almost half without loss in precision, or alternatively, allow us to investigate twice the number of tasks within a similar time span. Online tests confirm that the method leads to an optimal task selection. Significance. This study is the first one to optimize the task selection phase by an adaptive procedure. By increasing the number of tasks that can be tested in a given time span, the proposed method could contribute to reducing ‘BCI illiteracy’.
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Context Relevant Prediction Model for COPD Domain Using Bayesian Belief Network
Saleh, Lokman; Ajami, Hicham; Mili, Hafedh
2017-01-01
In the last three decades, researchers have examined extensively how context-aware systems can assist people, specifically those suffering from incurable diseases, to help them cope with their medical illness. Over the years, a huge number of studies on Chronic Obstructive Pulmonary Disease (COPD) have been published. However, how to derive relevant attributes and early detection of COPD exacerbations remains a challenge. In this research work, we will use an efficient algorithm to select relevant attributes where there is no proper approach in this domain. Such algorithm predicts exacerbations with high accuracy by adding discretization process, and organizes the pertinent attributes in priority order based on their impact to facilitate the emergency medical treatment. In this paper, we propose an extension of our existing Helper Context-Aware Engine System (HCES) for COPD. This project uses Bayesian network algorithm to depict the dependency between the COPD symptoms (attributes) in order to overcome the insufficiency and the independency hypothesis of naïve Bayesian. In addition, the dependency in Bayesian network is realized using TAN algorithm rather than consulting pneumologists. All these combined algorithms (discretization, selection, dependency, and the ordering of the relevant attributes) constitute an effective prediction model, comparing to effective ones. Moreover, an investigation and comparison of different scenarios of these algorithms are also done to verify which sequence of steps of prediction model gives more accurate results. Finally, we designed and validated a computer-aided support application to integrate different steps of this model. The findings of our system HCES has shown promising results using Area Under Receiver Operating Characteristic (AUC = 81.5%). PMID:28644419
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On improving the algorithm efficiency in the particle-particle force calculations
NASA Astrophysics Data System (ADS)
Kozynchenko, Alexander I.; Kozynchenko, Sergey A.
2016-09-01
The problem of calculating inter-particle forces in the particle-particle (PP) simulation models takes an important place in scientific computing. Such simulation models are used in diverse scientific applications arising in astrophysics, plasma physics, particle accelerators, etc., where the long-range forces are considered. The inverse-square laws such as Coulomb's law of electrostatic forces and Newton's law of universal gravitation are the examples of laws pertaining to the long-range forces. The standard naïve PP method outlined, for example, by Hockney and Eastwood [1] is straightforward, processing all pairs of particles in a double nested loop. The PP algorithm provides the best accuracy of all possible methods, but its computational complexity is O (Np2), where Np is a total number of particles involved. Too low efficiency of the PP algorithm seems to be the challenging issue in some cases where the high accuracy is required. An example can be taken from the charged particle beam dynamics where, under computing the own space charge of the beam, so-called macro-particles are used (see e.g., Humphries Jr. [2], Kozynchenko and Svistunov [3]).
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Prediction of carbonate rock type from NMR responses using data mining techniques
NASA Astrophysics Data System (ADS)
Gonçalves, Eduardo Corrêa; da Silva, Pablo Nascimento; Silveira, Carla Semiramis; Carneiro, Giovanna; Domingues, Ana Beatriz; Moss, Adam; Pritchard, Tim; Plastino, Alexandre; Azeredo, Rodrigo Bagueira de Vasconcellos
2017-05-01
Recent studies have indicated that the accurate identification of carbonate rock types in a reservoir can be employed as a preliminary step to enhance the effectiveness of petrophysical property modeling. Furthermore, rock typing activity has been shown to be of key importance in several steps of formation evaluation, such as the study of sedimentary series, reservoir zonation and well-to-well correlation. In this paper, a methodology based exclusively on the analysis of 1H-NMR (Nuclear Magnetic Resonance) relaxation responses - using data mining algorithms - is evaluated to perform the automatic classification of carbonate samples according to their rock type. We analyze the effectiveness of six different classification algorithms (k-NN, Naïve Bayes, C4.5, Random Forest, SMO and Multilayer Perceptron) and two data preprocessing strategies (discretization and feature selection). The dataset used in this evaluation is formed by 78 1H-NMR T2 distributions of fully brine-saturated rock samples from six different rock type classes. The experiments reveal that the combination of preprocessing strategies with classification algorithms is able to achieve a prediction accuracy of 97.4%.
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NASA Astrophysics Data System (ADS)
Khalilinezhad, Mahdieh; Minaei, Behrooz; Vernazza, Gianni; Dellepiane, Silvana
2015-03-01
Data mining (DM) is the process of discovery knowledge from large databases. Applications of data mining in Blood Transfusion Organizations could be useful for improving the performance of blood donation service. The aim of this research is the prediction of healthiness of blood donors in Blood Transfusion Organization (BTO). For this goal, three famous algorithms such as Decision Tree C4.5, Naïve Bayesian classifier, and Support Vector Machine have been chosen and applied to a real database made of 11006 donors. Seven fields such as sex, age, job, education, marital status, type of donor, results of blood tests (doctors' comments and lab results about healthy or unhealthy blood donors) have been selected as input to these algorithms. The results of the three algorithms have been compared and an error cost analysis has been performed. According to this research and the obtained results, the best algorithm with low error cost and high accuracy is SVM. This research helps BTO to realize a model from blood donors in each area in order to predict the healthy blood or unhealthy blood of donors. This research could be useful if used in parallel with laboratory tests to better separate unhealthy blood.
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Finding the Missing Physics: Simulating Polydisperse Polymer Melts
NASA Astrophysics Data System (ADS)
Rorrer, Nichoals; Dorgan, John
2014-03-01
A Monte Carlo algorithm has been developed to model polydisperse polymer melts. For the first time, this enables the specification of a predetermined molecular weight distribution for lattice based simulations. It is demonstrated how to map an arbitrary probability distributions onto a discrete number of chains residing on an fcc lattice. The resulting algorithm is able to simulate a wide variety of behaviors for polydisperse systems including confinement effects, shear flow, and parabolic flow. The dynamic version of the algorithm accurately captures Rouse dynamics for short polymer chains, and reptation-like dynamics for longer chain lengths.1 When polydispersity is introduced, smaller Rouse times and broadened the transition between different scaling regimes are observed. Rouse times also decrease under confinement for both polydisperse and monodisperse systems and chain length dependent migration effects are observed. The steady-state version of the algorithm enables the simulation of flow and when polydisperse systems are subject to parabolic (Poiseulle) flow, a migration phenomenon based on chain length is again present. These and other phenomena highlight the importance of including polydispersity in obtaining physically realistic simulations of polymeric melts. 1. Dorgan, J.R.; Rorrer, N.A.; Maupin, C.M., Macromolecules 2012, 45(21), 8833-8840. Work funded by the Fluid Dynamics program of the National Science Foundation under grant CBET-1067707.
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Electronic structure calculation by nonlinear optimization: Application to metals
NASA Astrophysics Data System (ADS)
Benedek, R.; Min, B. I.; Woodward, C.; Garner, J.
1988-04-01
There is considerable interest in the development of novel algorithms for the calculation of electronic structure (e.g., at the level of the local-density approximation of density-functional theory). In this paper we consider a first-order equation-of-motion method. Two methods of solution are described, one proposed by Williams and Soler, and the other base on a Born-Dyson series expansion. The extension of the approach to metallic systems is outlined and preliminary numerical calculations for Zintl-phase NaTl are presented.
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Gamma signatures of the C-BORD Tagged Neutron Inspection System
NASA Astrophysics Data System (ADS)
Sardet, A.; Pérot, B.; Carasco, C.; Sannié, G.; Moretto, S.; Nebbia, G.; Fontana, C.; Pino, F.; Iovene, A.; Tintori, C.
2018-01-01
In the frame of C-BORD project (H2020 program of the EU), a Rapidly relocatable Tagged Neutron Inspection System (RRTNIS) is being developed to non-intrusively detect explosives, chemical threats, and other illicit goods in cargo containers. Material identification is performed through gamma spectroscopy, using twenty NaI detectors and four LaBr3 detectors, to determine the different elements composing the inspected item from their specific gamma signatures induced by fast neutrons. This is performed using an unfolding algorithm to decompose the energy spectrum of a suspect item, selected by X-ray radiography and on which the RRTNIS inspection is focused, on a database of pure element gamma signatures. This paper reports on simulated signatures for the NaI and LaBr3 detectors, constructed using the MCNP6 code. First experimental spectra of a few elements of interest are also presented.
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Simulating Operation of a Complex Sensor Network
NASA Technical Reports Server (NTRS)
Jennings, Esther; Clare, Loren; Woo, Simon
2008-01-01
Simulation Tool for ASCTA Microsensor Network Architecture (STAMiNA) ["ASCTA" denotes the Advanced Sensors Collaborative Technology Alliance.] is a computer program for evaluating conceptual sensor networks deployed over terrain to provide military situational awareness. This or a similar program is needed because of the complexity of interactions among such diverse phenomena as sensing and communication portions of a network, deployment of sensor nodes, effects of terrain, data-fusion algorithms, and threat characteristics. STAMiNA is built upon a commercial network-simulator engine, with extensions to include both sensing and communication models in a discrete-event simulation environment. Users can define (1) a mission environment, including terrain features; (2) objects to be sensed; (3) placements and modalities of sensors, abilities of sensors to sense objects of various types, and sensor false alarm rates; (4) trajectories of threatening objects; (5) means of dissemination and fusion of data; and (6) various network configurations. By use of STAMiNA, one can simulate detection of targets through sensing, dissemination of information by various wireless communication subsystems under various scenarios, and fusion of information, incorporating such metrics as target-detection probabilities, false-alarm rates, and communication loads, and capturing effects of terrain and threat.
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BiNA: A Visual Analytics Tool for Biological Network Data
Gerasch, Andreas; Faber, Daniel; Küntzer, Jan; Niermann, Peter; Kohlbacher, Oliver; Lenhof, Hans-Peter; Kaufmann, Michael
2014-01-01
Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA - the Biological Network Analyzer - a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/. PMID:24551056
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NASA Astrophysics Data System (ADS)
Akkaş, Efe; Evren Çubukçu, H.; Akin, Lutfiye; Erkut, Volkan; Yurdakul, Yasin; Karayigit, Ali Ihsan
2016-04-01
Identification of zeolite group minerals is complicated due to their similar chemical formulas and habits. Although the morphologies of various zeolite crystals can be recognized under Scanning Electron Microscope (SEM), it is relatively more challenging and problematic process to identify zeolites using their mineral chemical data. SEMs integrated with energy dispersive X-ray spectrometers (EDS) provide fast and reliable chemical data of minerals. However, considering elemental similarities of characteristic chemical formulae of zeolite species (e.g. Clinoptilolite ((Na,K,Ca)2 -3Al3(Al,Si)2Si13O3612H2O) and Erionite ((Na2,K2,Ca)2Al4Si14O36ṡ15H2O)) EDS data alone does not seem to be sufficient for correct identification. Furthermore, the physical properties of the specimen (e.g. roughness, electrical conductivity) and the applied analytical conditions (e.g. accelerating voltage, beam current, spot size) of the SEM-EDS should be uniform in order to obtain reliable elemental results of minerals having high alkali (Na, K) and H2O (approx. %14-18) contents. This study which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK Project No: 113Y439), aims to construct a database as large as possible for various zeolite minerals and to develop a general prediction model for the identification of zeolite minerals using SEM-EDS data. For this purpose, an artificial neural network and rule based decision tree algorithm were employed. Throughout the analyses, a total of 1850 chemical data were collected from four distinct zeolite species, (Clinoptilolite-Heulandite, Erionite, Analcime and Mordenite) observed in various rocks (e.g. coals, pyroclastics). In order to obtain a representative training data set for each minerals, a selection procedure for reference mineral analyses was applied. During the selection procedure, SEM based crystal morphology data, XRD spectra and re-calculated cationic distribution, obtained by EDS have been used for the characterization of the training set. Consequently, for each zeolite species 250 EDS data (as elemental intensities) used for training and 200 ±50 analyses were tested. Finally, two prediction models were developed. The constructed models with various cross-correlation values (r) yielded an average accuracy of >91% for the best predictions using C5.0 Decision Tree algorithm and back propagation artificial neural network. Despite having similar accuracies, the developed models exhibit different prediction behaviors for some zeolite minerals. The results demonstrate that artificial neural network as a nonlinear tool and decision tree algorithm as a rule based prediction model would be employed to provide considerably efficient and reliable identification/classification of some zeolite minerals regardless of their similar elemental compositions. Keywords: mineral identification; zeolites; energy dispersive spectrometry; artificial neural networks; decision tree.
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NASA Astrophysics Data System (ADS)
Ojo, A. O.; Xie, Jun; Olorunfemi, M. O.
2018-01-01
To reduce ambiguity related to nonlinearities in the resistivity model-data relationships, an efficient direct-search scheme employing the Neighbourhood Algorithm (NA) was implemented to solve the 1-D resistivity problem. In addition to finding a range of best-fit models which are more likely to be global minimums, this method investigates the entire multi-dimensional model space and provides additional information about the posterior model covariance matrix, marginal probability density function and an ensemble of acceptable models. This provides new insights into how well the model parameters are constrained and make assessing trade-offs between them possible, thus avoiding some common interpretation pitfalls. The efficacy of the newly developed program is tested by inverting both synthetic (noisy and noise-free) data and field data from other authors employing different inversion methods so as to provide a good base for comparative performance. In all cases, the inverted model parameters were in good agreement with the true and recovered model parameters from other methods and remarkably correlate with the available borehole litho-log and known geology for the field dataset. The NA method has proven to be useful whilst a good starting model is not available and the reduced number of unknowns in the 1-D resistivity inverse problem makes it an attractive alternative to the linearized methods. Hence, it is concluded that the newly developed program offers an excellent complementary tool for the global inversion of the layered resistivity structure.
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Pashley, Clare L.; Hewitt, Eric W.; Radford, Sheena E.
2016-01-01
The mouse and human β2-microglobulin protein orthologs are 70 % identical in sequence and share 88 % sequence similarity. These proteins are predicted by various algorithms to have similar aggregation and amyloid propensities. However, whilst human β2m (hβ2m) forms amyloid-like fibrils in denaturing conditions (e.g. pH 2.5) in the absence of NaCl, mouse β2m (mβ2m) requires the addition of 0.3 M NaCl to cause fibrillation. Here, the factors which give rise to this difference in amyloid propensity are investigated. We utilise structural and mutational analyses, fibril growth kinetics and solubility measurements under a range of pH and salt conditions, to determine why these two proteins have different amyloid propensities. The results show that, although other factors influence the fibril growth kinetics, a striking difference in the solubility of the proteins is a key determinant of the different amyloidogenicity of hβ2m and mβ2m. The relationship between protein solubility and lag time of amyloid formation is not captured by current aggregation or amyloid prediction algorithms, indicating a need to better understand the role of solubility on the lag time of amyloid formation. The results demonstrate the key contribution of protein solubility in determining amyloid propensity and lag time of amyloid formation, highlighting how small differences in protein sequence can have dramatic effects on amyloid formation. PMID:26780548
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Computing a Comprehensible Model for Spam Filtering
NASA Astrophysics Data System (ADS)
Ruiz-Sepúlveda, Amparo; Triviño-Rodriguez, José L.; Morales-Bueno, Rafael
In this paper, we describe the application of the Desicion Tree Boosting (DTB) learning model to spam email filtering.This classification task implies the learning in a high dimensional feature space. So, it is an example of how the DTB algorithm performs in such feature space problems. In [1], it has been shown that hypotheses computed by the DTB model are more comprehensible that the ones computed by another ensemble methods. Hence, this paper tries to show that the DTB algorithm maintains the same comprehensibility of hypothesis in high dimensional feature space problems while achieving the performance of other ensemble methods. Four traditional evaluation measures (precision, recall, F1 and accuracy) have been considered for performance comparison between DTB and others models usually applied to spam email filtering. The size of the hypothesis computed by a DTB is smaller and more comprehensible than the hypothesis computed by Adaboost and Naïve Bayes.
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Machine learning methods in chemoinformatics
Mitchell, John B O
2014-01-01
Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure–activity relationships (QSAR), many others exist in the technical literature. This discussion is methods-based and focused on some algorithms that chemoinformatics researchers frequently use. It makes no claim to be exhaustive. We concentrate on methods for supervised learning, predicting the unknown property values of a test set of instances, usually molecules, based on the known values for a training set. Particularly relevant approaches include Artificial Neural Networks, Random Forest, Support Vector Machine, k-Nearest Neighbors and naïve Bayes classifiers. WIREs Comput Mol Sci 2014, 4:468–481. How to cite this article: WIREs Comput Mol Sci 2014, 4:468–481. doi:10.1002/wcms.1183 PMID:25285160
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An expert support system for breast cancer diagnosis using color wavelet features.
Issac Niwas, S; Palanisamy, P; Chibbar, Rajni; Zhang, W J
2012-10-01
Breast cancer diagnosis can be done through the pathologic assessments of breast tissue samples such as core needle biopsy technique. The result of analysis on this sample by pathologist is crucial for breast cancer patient. In this paper, nucleus of tissue samples are investigated after decomposition by means of the Log-Gabor wavelet on HSV color domain and an algorithm is developed to compute the color wavelet features. These features are used for breast cancer diagnosis using Support Vector Machine (SVM) classifier algorithm. The ability of properly trained SVM is to correctly classify patterns and make them particularly suitable for use in an expert system that aids in the diagnosis of cancer tissue samples. The results are compared with other multivariate classifiers such as Naïves Bayes classifier and Artificial Neural Network. The overall accuracy of the proposed method using SVM classifier will be further useful for automation in cancer diagnosis.
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Level Zero Trigger Processor for the NA62 experiment
NASA Astrophysics Data System (ADS)
Soldi, D.; Chiozzi, S.
2018-05-01
The NA62 experiment is designed to measure the ultra-rare decay K+ arrow π+ ν bar nu branching ratio with a precision of ~ 10% at the CERN Super Proton Synchrotron (SPS). The trigger system of NA62 consists in three different levels designed to select events of physics interest in a high beam rate environment. The L0 Trigger Processor (L0TP) is the lowest level system of the trigger chain. It is hardware implemented using programmable logic. The architecture of the NA62 L0TP system is a new approach compared to existing systems used in high-energy physics experiments. It is fully digital, based on a standard gigabit Ethernet communication between detectors and the L0TP Board. The L0TP Board is a commercial development board, mounting a programmable logic device (FPGA). The primitives generated by sub-detectors are sent asynchronously using the UDP protocol to the L0TP during the entire beam spill period. The L0TP realigns in time the primitives coming from seven different sources and performs a data selection based on the characteristics of the event such as energy, multiplicity and topology of hits in the sub-detectors. It guarantees a maximum latency of 1 ms. The maximum input rate is about 10 MHz for each sub-detector, while the design maximum output trigger rate is 1 MHz. A description of the trigger algorithm is presented here.
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Oden, Neal L; VanVeldhuisen, Paul C; Wakim, Paul G; Trivedi, Madhukar H; Somoza, Eugene; Lewis, Daniel
2011-09-01
In clinical trials of treatment for stimulant abuse, researchers commonly record both Time-Line Follow-Back (TLFB) self-reports and urine drug screen (UDS) results. To compare the power of self-report, qualitative (use vs. no use) UDS assessment, and various algorithms to generate self-report-UDS composite measures to detect treatment differences via t-test in simulated clinical trial data. We performed Monte Carlo simulations patterned in part on real data to model self-report reliability, UDS errors, dropout, informatively missing UDS reports, incomplete adherence to a urine donation schedule, temporal correlation of drug use, number of days in the study period, number of patients per arm, and distribution of drug-use probabilities. Investigated algorithms include maximum likelihood and Bayesian estimates, self-report alone, UDS alone, and several simple modifications of self-report (referred to here as ELCON algorithms) which eliminate perceived contradictions between it and UDS. Among the algorithms investigated, simple ELCON algorithms gave rise to the most powerful t-tests to detect mean group differences in stimulant drug use. Further investigation is needed to determine if simple, naïve procedures such as the ELCON algorithms are optimal for comparing clinical study treatment arms. But researchers who currently require an automated algorithm in scenarios similar to those simulated for combining TLFB and UDS to test group differences in stimulant use should consider one of the ELCON algorithms. This analysis continues a line of inquiry which could determine how best to measure outpatient stimulant use in clinical trials (NIDA. NIDA Monograph-57: Self-Report Methods of Estimating Drug Abuse: Meeting Current Challenges to Validity. NTIS PB 88248083. Bethesda, MD: National Institutes of Health, 1985; NIDA. NIDA Research Monograph 73: Urine Testing for Drugs of Abuse. NTIS PB 89151971. Bethesda, MD: National Institutes of Health, 1987; NIDA. NIDA Research Monograph 167: The Validity of Self-Reported Drug Use: Improving the Accuracy of Survey Estimates. NTIS PB 97175889. GPO 017-024-01607-1. Bethesda, MD: National Institutes of Health, 1997).
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Kitahata, Mari M; Drozd, Daniel R; Crane, Heidi M; Van Rompaey, Stephen E; Althoff, Keri N; Gange, Stephen J; Klein, Marina B; Lucas, Gregory M; Abraham, Alison G; Lo Re, Vincent; McReynolds, Justin; Lober, William B; Mendes, Adell; Modur, Sharada P; Jing, Yuezhou; Morton, Elizabeth J; Griffith, Margaret A; Freeman, Aimee M; Moore, Richard D
2015-01-01
The burden of HIV disease has shifted from traditional AIDS-defining illnesses to serious non-AIDS-defining comorbid conditions. Research aimed at improving HIV-related comorbid disease outcomes requires well-defined, verified clinical endpoints. We developed methods to ascertain and verify end-stage renal disease (ESRD) and end-stage liver disease (ESLD) and validated screening algorithms within the largest HIV cohort collaboration in North America (NA-ACCORD). Individuals who screened positive among all participants in twelve cohorts enrolled between January 1996 and December 2009 underwent medical record review to verify incident ESRD or ESLD using standardized protocols. We randomly sampled 6% of contributing cohorts to determine the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ESLD and ESRD screening algorithms in a validation subcohort. Among 43,433 patients screened for ESRD, 822 screened positive of which 620 met clinical criteria for ESRD. The algorithm had 100% sensitivity, 99% specificity, 82% PPV, and 100% NPV for ESRD. Among 41,463 patients screened for ESLD, 2,024 screened positive of which 645 met diagnostic criteria for ESLD. The algorithm had 100% sensitivity, 95% specificity, 27% PPV, and 100% NPV for ESLD. Our methods proved robust for ascertainment of ESRD and ESLD in persons infected with HIV.
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Raposo, Letícia M; Nobre, Flavio F
2017-08-30
Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.
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Pile-up correction by Genetic Algorithm and Artificial Neural Network
NASA Astrophysics Data System (ADS)
Kafaee, M.; Saramad, S.
2009-08-01
Pile-up distortion is a common problem for high counting rates radiation spectroscopy in many fields such as industrial, nuclear and medical applications. It is possible to reduce pulse pile-up using hardware-based pile-up rejections. However, this phenomenon may not be eliminated completely by this approach and the spectrum distortion caused by pile-up rejection can be increased as well. In addition, inaccurate correction or rejection of pile-up artifacts in applications such as energy dispersive X-ray (EDX) spectrometers can lead to losses of counts, will give poor quantitative results and even false element identification. Therefore, it is highly desirable to use software-based models to predict and correct any recognized pile-up signals in data acquisition systems. The present paper describes two new intelligent approaches for pile-up correction; the Genetic Algorithm (GA) and Artificial Neural Networks (ANNs). The validation and testing results of these new methods have been compared, which shows excellent agreement with the measured data with 60Co source and NaI detector. The Monte Carlo simulation of these new intelligent algorithms also shows their advantages over hardware-based pulse pile-up rejection methods.
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Boundary identification and error analysis of shocked material images
NASA Astrophysics Data System (ADS)
Hock, Margaret; Howard, Marylesa; Cooper, Leora; Meehan, Bernard; Nelson, Keith
2017-06-01
To compute quantities such as pressure and velocity from laser-induced shock waves propagating through materials, high-speed images are captured and analyzed. Shock images typically display high noise and spatially-varying intensities, causing conventional analysis techniques to have difficulty identifying boundaries in the images without making significant assumptions about the data. We present a novel machine learning algorithm that efficiently segments, or partitions, images with high noise and spatially-varying intensities, and provides error maps that describe a level of uncertainty in the partitioning. The user trains the algorithm by providing locations of known materials within the image but no assumptions are made on the geometries in the image. The error maps are used to provide lower and upper bounds on quantities of interest, such as velocity and pressure, once boundaries have been identified and propagated through equations of state. This algorithm will be demonstrated on images of shock waves with noise and aberrations to quantify properties of the wave as it progresses. DOE/NV/25946-3126 This work was done by National Security Technologies, LLC, under Contract No. DE- AC52-06NA25946 with the U.S. Department of Energy and supported by the SDRD Program.
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Human versus Robots in the Discovery and Crystallization of Gigantic Polyoxometalates.
Duros, Vasilios; Grizou, Jonathan; Xuan, Weimin; Hosni, Zied; Long, De-Liang; Miras, Haralampos N; Cronin, Leroy
2017-08-28
The discovery of new gigantic molecules formed by self-assembly and crystal growth is challenging as it combines two contingent events; first is the formation of a new molecule, and second its crystallization. Herein, we construct a workflow that can be followed manually or by a robot to probe the envelope of both events and employ it for a new polyoxometalate cluster, Na 6 [Mo 120 Ce 6 O 366 H 12 (H 2 O) 78 ]⋅200 H 2 O (1) which has a trigonal-ring type architecture (yield 4.3 % based on Mo). Its synthesis and crystallization was probed using an active machine-learning algorithm developed by us to explore the crystallization space, the algorithm results were compared with those obtained by human experimenters. The algorithm-based search is able to cover ca. 9 times more crystallization space than a random search and ca. 6 times more than humans and increases the crystallization prediction accuracy to 82.4±0.7 % over 77.1±0.9 % from human experimenters. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.
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Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow
2017-01-01
Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.
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2007-07-20
science.msfc.nasa.gov/ss/pad/ sppb /workshoV7/&eoma&ne/Reo cgn/geo c&m.for. See also the GEOPACK library at http:/nssdcftp.gsfc.na-a.gov/models...calculations, fed into the inverse computation, should reproduce the original coordinate grid. This test of the consistency of the direct and inverse...algorithm. A test of this type was performed for a uniform grid, for line traces from 7200 km to the ground, and for 800 km to the ground. The maximum
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Symetrica Measurements at PNNL
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kouzes, Richard T.; Mace, Emily K.; Redding, Rebecca L.
2009-01-26
Symetrica is a small company based in Southampton, England, that has developed an algorithm for processing gamma ray spectra obtained from a variety of scintillation detectors. Their analysis method applied to NaI(Tl), BGO, and LaBr spectra results in deconvoluted spectra with the “resolution” improved by about a factor of three to four. This method has also been applied by Symetrica to plastic scintillator with the result that full energy peaks are produced. If this method is valid and operationally viable, it could lead to a significantly improved plastic scintillator based radiation portal monitor system.
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An effective method to screen sodium-based layered materials for sodium ion batteries
NASA Astrophysics Data System (ADS)
Zhang, Xu; Zhang, Zihe; Yao, Sai; Chen, An; Zhao, Xudong; Zhou, Zhen
2018-03-01
Due to the high cost and insufficient resource of lithium, sodium-ion batteries are widely investigated for large-scale applications. Typically, insertion-type materials possess better cyclic stability than alloy-type and conversion-type ones. Therefore, in this work, we proposed a facile and effective method to screen sodium-based layered materials based on Materials Project database as potential candidate insertion-type materials for sodium ion batteries. The obtained Na-based layered materials contains 38 kinds of space group, which reveals that the credibility of our screening approach would not be affected by the space group. Then, some important indexes of the representative materials, including the average voltage, volume change and sodium ion mobility, were further studied by means of density functional theory computations. Some materials with extremely low volume changes and Na diffusion barriers are promising candidates for sodium ion batteries. We believe that our classification algorithm could also be used to search for other alkali and multivalent ion-based layered materials, to accelerate the development of battery materials.
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NASA Astrophysics Data System (ADS)
Badoni, D.; Bizzarri, M.; Bonaiuto, V.; Checcucci, B.; De Simone, N.; Federici, L.; Fucci, A.; Paoluzzi, G.; Papi, A.; Piccini, M.; Salamon, A.; Salina, G.; Santovetti, E.; Sargeni, F.; Venditti, S.
2014-01-01
The goal of the NA62 experiment at the CERN SPS is the measurement of the Branching Ratio of the very rare kaon decay K+→π+ ν bar nu with a 10% accuracy by collecting 100 events in two years of data taking. An efficient photon veto system is needed to reject the K+→π+ π0 background and a liquid krypton electromagnetic calorimeter will be used for this purpose in the 1-10 mrad angular region. The L0 trigger system for the calorimeter consists of a peak reconstruction algorithm implemented on FPGA by using a mixed parallel architecture based on soft core Altera NIOS II embedded processors together with custom VHDL modules. This solution allows an efficient and flexible reconstruction of the energy-deposition peak. The system will be totally composed of 36 TEL62 boards, 108 mezzanine cards and 215 high-performance FPGAs. We describe the design, current status and the results of the first performance tests.
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Kesler, Shelli R; Rao, Vikram; Ray, William J; Rao, Arvind
2017-01-01
Breast cancer chemotherapy is associated with accelerated aging and potentially increased risk for Alzheimer's disease (AD). We calculated the probability of AD diagnosis from brain network and demographic and genetic data obtained from 47 female AD converters and 47 matched healthy controls. We then applied this algorithm to data from 78 breast cancer survivors. The classifier discriminated between AD and healthy controls with 86% accuracy ( P < .0001). Chemotherapy-treated breast cancer survivors demonstrated significantly higher probability of AD compared to healthy controls ( P < .0001) and chemotherapy-naïve survivors ( P = .007), even after stratifying for apolipoprotein e4 genotype. Chemotherapy-naïve survivors also showed higher AD probability compared to healthy controls ( P = .014). Chemotherapy-treated breast cancer survivors who have a particular profile of brain structure may have a higher risk for AD, especially those who are older and have lower cognitive reserve.
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Optimal design of wide-view-angle waveplate used for polarimetric diagnosis of lithography system
NASA Astrophysics Data System (ADS)
Gu, Honggang; Jiang, Hao; Zhang, Chuanwei; Chen, Xiuguo; Liu, Shiyuan
2016-03-01
The diagnosis and control of the polarization aberrations is one of the main concerns in a hyper numerical aperture (NA) lithography system. Waveplates are basic and indispensable optical components in the polarimetric diagnosis tools for the immersion lithography system. The retardance of a birefringent waveplate is highly sensitive to the incident angle of the light, which makes the conventional waveplate not suitable to be applied in the polarimetric diagnosis for the immersion lithography system with a hyper NA. In this paper, we propose a method for the optimal design of a wideview- angle waveplate by combining two positive waveplates made from magnesium fluoride (MgF2) and two negative waveplates made from sapphire using the simulated annealing algorithm. Theoretical derivations and numerical simulations are performed and the results demonstrate that the maximum variation in the retardance of the optimally designed wide-view-angle waveplate is less than +/- 0.35° for a wide-view-angle range of +/- 20°.
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Schüpbach, Jörg; Gebhardt, Martin D.; Scherrer, Alexandra U.; Bisset, Leslie R.; Niederhauser, Christoph; Regenass, Stephan; Yerly, Sabine; Aubert, Vincent; Suter, Franziska; Pfister, Stefan; Martinetti, Gladys; Andreutti, Corinne; Klimkait, Thomas; Brandenberger, Marcel; Günthard, Huldrych F.
2013-01-01
Background Tests for recent infections (TRIs) are important for HIV surveillance. We have shown that a patient's antibody pattern in a confirmatory line immunoassay (Inno-Lia) also yields information on time since infection. We have published algorithms which, with a certain sensitivity and specificity, distinguish between incident (< = 12 months) and older infection. In order to use these algorithms like other TRIs, i.e., based on their windows, we now determined their window periods. Methods We classified Inno-Lia results of 527 treatment-naïve patients with HIV-1 infection < = 12 months according to incidence by 25 algorithms. The time after which all infections were ruled older, i.e. the algorithm's window, was determined by linear regression of the proportion ruled incident in dependence of time since infection. Window-based incident infection rates (IIR) were determined utilizing the relationship ‘Prevalence = Incidence x Duration’ in four annual cohorts of HIV-1 notifications. Results were compared to performance-based IIR also derived from Inno-Lia results, but utilizing the relationship ‘incident = true incident + false incident’ and also to the IIR derived from the BED incidence assay. Results Window periods varied between 45.8 and 130.1 days and correlated well with the algorithms' diagnostic sensitivity (R2 = 0.962; P<0.0001). Among the 25 algorithms, the mean window-based IIR among the 748 notifications of 2005/06 was 0.457 compared to 0.453 obtained for performance-based IIR with a model not correcting for selection bias. Evaluation of BED results using a window of 153 days yielded an IIR of 0.669. Window-based IIR and performance-based IIR increased by 22.4% and respectively 30.6% in 2008, while 2009 and 2010 showed a return to baseline for both methods. Conclusions IIR estimations by window- and performance-based evaluations of Inno-Lia algorithm results were similar and can be used together to assess IIR changes between annual HIV notification cohorts. PMID:23990968
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An efficient grid layout algorithm for biological networks utilizing various biological attributes
Kojima, Kaname; Nagasaki, Masao; Jeong, Euna; Kato, Mitsuru; Miyano, Satoru
2007-01-01
Background Clearly visualized biopathways provide a great help in understanding biological systems. However, manual drawing of large-scale biopathways is time consuming. We proposed a grid layout algorithm that can handle gene-regulatory networks and signal transduction pathways by considering edge-edge crossing, node-edge crossing, distance measure between nodes, and subcellular localization information from Gene Ontology. Consequently, the layout algorithm succeeded in drastically reducing these crossings in the apoptosis model. However, for larger-scale networks, we encountered three problems: (i) the initial layout is often very far from any local optimum because nodes are initially placed at random, (ii) from a biological viewpoint, human layouts still exceed automatic layouts in understanding because except subcellular localization, it does not fully utilize biological information of pathways, and (iii) it employs a local search strategy in which the neighborhood is obtained by moving one node at each step, and automatic layouts suggest that simultaneous movements of multiple nodes are necessary for better layouts, while such extension may face worsening the time complexity. Results We propose a new grid layout algorithm. To address problem (i), we devised a new force-directed algorithm whose output is suitable as the initial layout. For (ii), we considered that an appropriate alignment of nodes having the same biological attribute is one of the most important factors of the comprehension, and we defined a new score function that gives an advantage to such configurations. For solving problem (iii), we developed a search strategy that considers swapping nodes as well as moving a node, while keeping the order of the time complexity. Though a naïve implementation increases by one order, the time complexity, we solved this difficulty by devising a method that caches differences between scores of a layout and its possible updates. Conclusion Layouts of the new grid layout algorithm are compared with that of the previous algorithm and human layout in an endothelial cell model, three times as large as the apoptosis model. The total cost of the result from the new grid layout algorithm is similar to that of the human layout. In addition, its convergence time is drastically reduced (40% reduction). PMID:17338825
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A Generic and Efficient E-field Parallel Imaging Correlator for Next-Generation Radio Telescopes
NASA Astrophysics Data System (ADS)
Thyagarajan, Nithyanandan; Beardsley, Adam P.; Bowman, Judd D.; Morales, Miguel F.
2017-05-01
Modern radio telescopes are favouring densely packed array layouts with large numbers of antennas (NA ≳ 1000). Since the complexity of traditional correlators scales as O(N_A^2), there will be a steep cost for realizing the full imaging potential of these powerful instruments. Through our generic and efficient E-field Parallel Imaging Correlator (epic), we present the first software demonstration of a generalized direct imaging algorithm, namely the Modular Optimal Frequency Fourier imager. Not only does it bring down the cost for dense layouts to O(N_A log _2N_A) but can also image from irregular layouts and heterogeneous arrays of antennas. epic is highly modular, parallelizable, implemented in object-oriented python, and publicly available. We have verified the images produced to be equivalent to those from traditional techniques to within a precision set by gridding coarseness. We have also validated our implementation on data observed with the Long Wavelength Array (LWA1). We provide a detailed framework for imaging with heterogeneous arrays and show that epic robustly estimates the input sky model for such arrays. Antenna layouts with dense filling factors consisting of a large number of antennas such as LWA, the Square Kilometre Array, Hydrogen Epoch of Reionization Array, and Canadian Hydrogen Intensity Mapping Experiment will gain significant computational advantage by deploying an optimized version of epic. The algorithm is a strong candidate for instruments targeting transient searches of fast radio bursts as well as planetary and exoplanetary phenomena due to the availability of high-speed calibrated time-domain images and low output bandwidth relative to visibility-based systems.
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Sathiyamoorthy, V; Sekar, T; Elango, N
2015-01-01
Formation of spikes prevents achievement of the better material removal rate (MRR) and surface finish while using plain NaNO3 aqueous electrolyte in electrochemical machining (ECM) of die tool steel. Hence this research work attempts to minimize the formation of spikes in the selected workpiece of high carbon high chromium die tool steel using copper nanoparticles suspended in NaNO3 aqueous electrolyte, that is, nanofluid. The selected influencing parameters are applied voltage and electrolyte discharge rate with three levels and tool feed rate with four levels. Thirty-six experiments were designed using Design Expert 7.0 software and optimization was done using multiobjective genetic algorithm (MOGA). This tool identified the best possible combination for achieving the better MRR and surface roughness. The results reveal that voltage of 18 V, tool feed rate of 0.54 mm/min, and nanofluid discharge rate of 12 lit/min would be the optimum values in ECM of HCHCr die tool steel. For checking the optimality obtained from the MOGA in MATLAB software, the maximum MRR of 375.78277 mm(3)/min and respective surface roughness Ra of 2.339779 μm were predicted at applied voltage of 17.688986 V, tool feed rate of 0.5399705 mm/min, and nanofluid discharge rate of 11.998816 lit/min. Confirmatory tests showed that the actual performance at the optimum conditions was 361.214 mm(3)/min and 2.41 μm; the deviation from the predicted performance is less than 4% which proves the composite desirability of the developed models.
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Pashley, Clare L; Hewitt, Eric W; Radford, Sheena E
2016-02-13
The mouse and human β2-microglobulin protein orthologs are 70% identical in sequence and share 88% sequence similarity. These proteins are predicted by various algorithms to have similar aggregation and amyloid propensities. However, whilst human β2m (hβ2m) forms amyloid-like fibrils in denaturing conditions (e.g. pH2.5) in the absence of NaCl, mouse β2m (mβ2m) requires the addition of 0.3M NaCl to cause fibrillation. Here, the factors which give rise to this difference in amyloid propensity are investigated. We utilise structural and mutational analyses, fibril growth kinetics and solubility measurements under a range of pH and salt conditions, to determine why these two proteins have different amyloid propensities. The results show that, although other factors influence the fibril growth kinetics, a striking difference in the solubility of the proteins is a key determinant of the different amyloidogenicity of hβ2m and mβ2m. The relationship between protein solubility and lag time of amyloid formation is not captured by current aggregation or amyloid prediction algorithms, indicating a need to better understand the role of solubility on the lag time of amyloid formation. The results demonstrate the key contribution of protein solubility in determining amyloid propensity and lag time of amyloid formation, highlighting how small differences in protein sequence can have dramatic effects on amyloid formation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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The influence of negative training set size on machine learning-based virtual screening.
Kurczab, Rafał; Smusz, Sabina; Bojarski, Andrzej J
2014-01-01
The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening.
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3D imaging and wavefront sensing with a plenoptic objective
NASA Astrophysics Data System (ADS)
Rodríguez-Ramos, J. M.; Lüke, J. P.; López, R.; Marichal-Hernández, J. G.; Montilla, I.; Trujillo-Sevilla, J.; Femenía, B.; Puga, M.; López, M.; Fernández-Valdivia, J. J.; Rosa, F.; Dominguez-Conde, C.; Sanluis, J. C.; Rodríguez-Ramos, L. F.
2011-06-01
Plenoptic cameras have been developed over the last years as a passive method for 3d scanning. Several superresolution algorithms have been proposed in order to increase the resolution decrease associated with lightfield acquisition with a microlenses array. A number of multiview stereo algorithms have also been applied in order to extract depth information from plenoptic frames. Real time systems have been implemented using specialized hardware as Graphical Processing Units (GPUs) and Field Programmable Gates Arrays (FPGAs). In this paper, we will present our own implementations related with the aforementioned aspects but also two new developments consisting of a portable plenoptic objective to transform every conventional 2d camera in a 3D CAFADIS plenoptic camera, and the novel use of a plenoptic camera as a wavefront phase sensor for adaptive optics (OA). The terrestrial atmosphere degrades the telescope images due to the diffraction index changes associated with the turbulence. These changes require a high speed processing that justify the use of GPUs and FPGAs. Na artificial Laser Guide Stars (Na-LGS, 90km high) must be used to obtain the reference wavefront phase and the Optical Transfer Function of the system, but they are affected by defocus because of the finite distance to the telescope. Using the telescope as a plenoptic camera allows us to correct the defocus and to recover the wavefront phase tomographically. These advances significantly increase the versatility of the plenoptic camera, and provides a new contribution to relate the wave optics and computer vision fields, as many authors claim.
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The influence of negative training set size on machine learning-based virtual screening
2014-01-01
Background The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. Results The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. Conclusions In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening. PMID:24976867
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Sands, Bruce E; Duh, Mei-Sheng; Cali, Clorinda; Ajene, Anuli; Bohn, Rhonda L; Miller, David; Cole, J Alexander; Cook, Suzanne F; Walker, Alexander M
2006-01-01
A challenge in the use of insurance claims databases for epidemiologic research is accurate identification and verification of medical conditions. This report describes the development and validation of claims-based algorithms to identify colonic ischemia, hospitalized complications of constipation, and irritable bowel syndrome (IBS). From the research claims databases of a large healthcare company, we selected at random 120 potential cases of IBS and 59 potential cases each of colonic ischemia and hospitalized complications of constipation. We sought the written medical records and were able to abstract 107, 57, and 51 records, respectively. We established a 'true' case status for each subject by applying standard clinical criteria to the available chart data. Comparing the insurance claims histories to the assigned case status, we iteratively developed, tested, and refined claims-based algorithms that would capture the diagnoses obtained from the medical records. We set goals of high specificity for colonic ischemia and hospitalized complications of constipation, and high sensitivity for IBS. The resulting algorithms substantially improved on the accuracy achievable from a naïve acceptance of the diagnostic codes attached to insurance claims. The specificities for colonic ischemia and serious complications of constipation were 87.2 and 92.7%, respectively, and the sensitivity for IBS was 98.9%. U.S. commercial insurance claims data appear to be usable for the study of colonic ischemia, IBS, and serious complications of constipation. (c) 2005 John Wiley & Sons, Ltd.
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NASA Astrophysics Data System (ADS)
Ruske, S. T.; Topping, D. O.; Foot, V. E.; Kaye, P. H.; Stanley, W. R.; Morse, A. P.; Crawford, I.; Gallagher, M. W.
2016-12-01
Characterisation of bio-aerosols has important implications within Environment and Public Health sectors. Recent developments in Ultra-Violet Light Induced Fluorescence (UV-LIF) detectors such as the Wideband Integrated bio-aerosol Spectrometer (WIBS) and the newly introduced Multiparameter bio-aerosol Spectrometer (MBS) has allowed for the real time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal Spores and pollen. This new generation of instruments has enabled ever-larger data sets to be compiled with the aim of studying more complex environments, yet the algorithms used for specie classification remain largely invalidated. It is therefore imperative that we validate the performance of different algorithms that can be used for the task of classification, which is the focus of this study. For unsupervised learning we test Hierarchical Agglomerative Clustering with various different linkages. For supervised learning, ten methods were tested; including decision trees, ensemble methods: Random Forests, Gradient Boosting and AdaBoost; two implementations for support vector machines: libsvm and liblinear; Gaussian methods: Gaussian naïve Bayesian, quadratic and linear discriminant analysis and finally the k-nearest neighbours algorithm. The methods were applied to two different data sets measured using a new Multiparameter bio-aerosol Spectrometer. We find that clustering, in general, performs slightly worse than the supervised learning methods correctly classifying, at best, only 72.7 and 91.1 percent for the two data sets. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 88.1 and 97.8 percent of the testing data respectively across the two data sets. We discuss the wider relevance of these results with regards to challenging existing classification in real-world environments.
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Optimizing LX-17 Thermal Decomposition Model Parameters with Evolutionary Algorithms
NASA Astrophysics Data System (ADS)
Moore, Jason; McClelland, Matthew; Tarver, Craig; Hsu, Peter; Springer, H. Keo
2017-06-01
We investigate and model the cook-off behavior of LX-17 because this knowledge is critical to understanding system response in abnormal thermal environments. Thermal decomposition of LX-17 has been explored in conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (thermogravimetric analysis), and DSC (differential scanning calorimetry) experiments using varied temperature profiles. These experimental data are the basis for developing multiple reaction schemes with coupled mechanics in LLNL's multi-physics hydrocode, ALE3D (Arbitrary Lagrangian-Eulerian code in 2D and 3D). We employ evolutionary algorithms to optimize reaction rate parameters on high performance computing clusters. Once experimentally validated, this model will be scalable to a number of applications involving LX-17 and can be used to develop more sophisticated experimental methods. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC.
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NASA Astrophysics Data System (ADS)
Ariyanto, P.; Syuhada; Rosid, S.; Anggono, T.; Januarti, Y.
2018-03-01
In this study, we applied receiver functions analysis to determine the crustal thickness, the ratio of Vp/Vs and the S wave velocity in the southern part of the Central Java. We selected tele-seismic data with magnitude more than 6 (M>6) and epicenter distance 30°-90° recorded from 3 broadband stations: UGM, YOGI, and WOJI station, as part of Indonesia-Geophone Network (IA-GE). Inversions were performed using nonlinear Neighborhood Algorithm (NA). We observed Ps phase conversion on the receiver functions corresponding to Moho depth at around 36-39 km. We also observed strong negative phase arrivals at around 10-12 s which might be associated with Indo-Australian subducting slab underneath the stations. The inversion results show the presence of low velocity zone with high Vp/Vs ratio (>1.78) in the middle crust around the study area which could be related to the Merapi-Lawu Anomaly (MLA).
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Multiplex primer prediction software for divergent targets
Gardner, Shea N.; Hiddessen, Amy L.; Williams, Peter L.; Hara, Christine; Wagner, Mark C.; Colston, Bill W.
2009-01-01
We describe a Multiplex Primer Prediction (MPP) algorithm to build multiplex compatible primer sets to amplify all members of large, diverse and unalignable sets of target sequences. The MPP algorithm is scalable to larger target sets than other available software, and it does not require a multiple sequence alignment. We applied it to questions in viral detection, and demonstrated that there are no universally conserved priming sequences among viruses and that it could require an unfeasibly large number of primers (∼3700 18-mers or ∼2000 10-mers) to generate amplicons from all sequenced viruses. We then designed primer sets separately for each viral family, and for several diverse species such as foot-and-mouth disease virus (FMDV), hemagglutinin (HA) and neuraminidase (NA) segments of influenza A virus, Norwalk virus, and HIV-1. We empirically demonstrated the application of the software with a multiplex set of 16 short (10 nt) primers designed to amplify the Poxviridae family to produce a specific amplicon from vaccinia virus. PMID:19759213
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Knowing what to expect, forecasting monthly emergency department visits: A time-series analysis.
Bergs, Jochen; Heerinckx, Philipe; Verelst, Sandra
2014-04-01
To evaluate an automatic forecasting algorithm in order to predict the number of monthly emergency department (ED) visits one year ahead. We collected retrospective data of the number of monthly visiting patients for a 6-year period (2005-2011) from 4 Belgian Hospitals. We used an automated exponential smoothing approach to predict monthly visits during the year 2011 based on the first 5 years of the dataset. Several in- and post-sample forecasting accuracy measures were calculated. The automatic forecasting algorithm was able to predict monthly visits with a mean absolute percentage error ranging from 2.64% to 4.8%, indicating an accurate prediction. The mean absolute scaled error ranged from 0.53 to 0.68 indicating that, on average, the forecast was better compared with in-sample one-step forecast from the naïve method. The applied automated exponential smoothing approach provided useful predictions of the number of monthly visits a year in advance. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Classification Algorithms for Big Data Analysis, a Map Reduce Approach
NASA Astrophysics Data System (ADS)
Ayma, V. A.; Ferreira, R. S.; Happ, P.; Oliveira, D.; Feitosa, R.; Costa, G.; Plaza, A.; Gamba, P.
2015-03-01
Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP), which is an open-source, distributed framework for automatic image interpretation, is presented. The tool, named ICP: Data Mining Package, is able to perform supervised classification procedures on huge amounts of data, usually referred as big data, on a distributed infrastructure using Hadoop MapReduce. The tool has four classification algorithms implemented, taken from WEKA's machine learning library, namely: Decision Trees, Naïve Bayes, Random Forest and Support Vector Machines (SVM). The results of an experimental analysis using a SVM classifier on data sets of different sizes for different cluster configurations demonstrates the potential of the tool, as well as aspects that affect its performance.
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Baldewsing, Radj A; Schaar, Johannes A; Mastik, Frits; Oomens, Cees W J; van der Steen, Antonius F W
2005-04-01
Intravascular ultrasound (IVUS) elastography visualizes local radial strain of arteries in so-called elastograms to detect rupture-prone plaques. However, due to the unknown arterial stress distribution these elastograms cannot be directly interpreted as a morphology and material composition image. To overcome this limitation we have developed a method that reconstructs a Young's modulus image from an elastogram. This method is especially suited for thin-cap fibroatheromas (TCFAs), i.e., plaques with a media region containing a lipid pool covered by a cap. Reconstruction is done by a minimization algorithm that matches the strain image output, calculated with a parametric finite element model (PFEM) representation of a TCFA, to an elastogram by iteratively updating the PFEM geometry and material parameters. These geometry parameters delineate the TCFA media, lipid pool and cap regions by circles. The material parameter for each region is a Young's modulus, EM, EL, and EC, respectively. The method was successfully tested on computer-simulated TCFAs (n = 2), one defined by circles, the other by tracing TCFA histology, and additionally on a physical phantom (n = 1) having a stiff wall (measured EM = 16.8 kPa) with an eccentric soft region (measured EL = 4.2 kPa). Finally, it was applied on human coronary plaques in vitro (n = 1) and in vivo (n = 1). The corresponding simulated and measured elastograms of these plaques showed radial strain values from 0% up to 2% at a pressure differential of 20, 20, 1, 20, and 1 mmHg respectively. The used/reconstructed Young's moduli [kPa] were for the circular plaque EL = 50/66, EM = 1500/1484, EC = 2000/2047, for the traced plaque EL = 25/1, EM = 1000/1148, EC = 1500/1491, for the phantom EL = 4.2/4 kPa, EM = 16.8/16, for the in vitro plaque EL = n.a./29, EM = n.a./647, EC = n.a./1784 kPa and for the in vivo plaque EL = n.a./2, EM = n.a./188, Ec = n.a./188 kPa.
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Automated validation of patient safety clinical incident classification: macro analysis.
Gupta, Jaiprakash; Patrick, Jon
2013-01-01
Patient safety is the buzz word in healthcare. Incident Information Management System (IIMS) is electronic software that stores clinical mishaps narratives in places where patients are treated. It is estimated that in one state alone over one million electronic text documents are available in IIMS. In this paper we investigate the data density available in the fields entered to notify an incident and the validity of the built in classification used by clinician to categories the incidents. Waikato Environment for Knowledge Analysis (WEKA) software was used to test the classes. Four statistical classifier based on J48, Naïve Bayes (NB), Naïve Bayes Multinominal (NBM) and Support Vector Machine using radial basis function (SVM_RBF) algorithms were used to validate the classes. The data pool was 10,000 clinical incidents drawn from 7 hospitals in one state in Australia. In first part of the study 1000 clinical incidents were selected to determine type and number of fields worth investigating and in the second part another 5448 clinical incidents were randomly selected to validate 13 clinical incident types. Result shows 74.6% of the cells were empty and only 23 fields had content over 70% of the time. The percentage correctly classified classes on four algorithms using categorical dataset ranged from 42 to 49%, using free-text datasets from 65% to 77% and using both datasets from 72% to 79%. Kappa statistic ranged from 0.36 to 0.4. for categorical data, from 0.61 to 0.74. for free-text and from 0.67 to 0.77 for both datasets. Similar increases in performance in the 3 experiments was noted on true positive rate, precision, F-measure and area under curve (AUC) of receiver operating characteristics (ROC) scores. The study demonstrates only 14 of 73 fields in IIMS have data that is usable for machine learning experiments. Irrespective of the type of algorithms used when all datasets are used performance was better. Classifier NBM showed best performance. We think the classifier can be improved further by reclassifying the most confused classes and there is scope to apply text mining tool on patient safety classifications.
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Shahinfar, Saleh; Page, David; Guenther, Jerry; Cabrera, Victor; Fricke, Paul; Weigel, Kent
2014-02-01
When making the decision about whether or not to breed a given cow, knowledge about the expected outcome would have an economic impact on profitability of the breeding program and net income of the farm. The outcome of each breeding can be affected by many management and physiological features that vary between farms and interact with each other. Hence, the ability of machine learning algorithms to accommodate complex relationships in the data and missing values for explanatory variables makes these algorithms well suited for investigation of reproduction performance in dairy cattle. The objective of this study was to develop a user-friendly and intuitive on-farm tool to help farmers make reproduction management decisions. Several different machine learning algorithms were applied to predict the insemination outcomes of individual cows based on phenotypic and genotypic data. Data from 26 dairy farms in the Alta Genetics (Watertown, WI) Advantage Progeny Testing Program were used, representing a 10-yr period from 2000 to 2010. Health, reproduction, and production data were extracted from on-farm dairy management software, and estimated breeding values were downloaded from the US Department of Agriculture Agricultural Research Service Animal Improvement Programs Laboratory (Beltsville, MD) database. The edited data set consisted of 129,245 breeding records from primiparous Holstein cows and 195,128 breeding records from multiparous Holstein cows. Each data point in the final data set included 23 and 25 explanatory variables and 1 binary outcome for of 0.756 ± 0.005 and 0.736 ± 0.005 for primiparous and multiparous cows, respectively. The naïve Bayes algorithm, Bayesian network, and decision tree algorithms showed somewhat poorer classification performance. An information-based variable selection procedure identified herd average conception rate, incidence of ketosis, number of previous (failed) inseminations, days in milk at breeding, and mastitis as the most effective explanatory variables in predicting pregnancy outcome. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Ebrahimi, Mansour; Aghagolzadeh, Parisa; Shamabadi, Narges; Tahmasebi, Ahmad; Alsharifi, Mohammed; Adelson, David L; Hemmatzadeh, Farhid; Ebrahimie, Esmaeil
2014-01-01
The evolution of the influenza A virus to increase its host range is a major concern worldwide. Molecular mechanisms of increasing host range are largely unknown. Influenza surface proteins play determining roles in reorganization of host-sialic acid receptors and host range. In an attempt to uncover the physic-chemical attributes which govern HA subtyping, we performed a large scale functional analysis of over 7000 sequences of 16 different HA subtypes. Large number (896) of physic-chemical protein characteristics were calculated for each HA sequence. Then, 10 different attribute weighting algorithms were used to find the key characteristics distinguishing HA subtypes. Furthermore, to discover machine leaning models which can predict HA subtypes, various Decision Tree, Support Vector Machine, Naïve Bayes, and Neural Network models were trained on calculated protein characteristics dataset as well as 10 trimmed datasets generated by attribute weighting algorithms. The prediction accuracies of the machine learning methods were evaluated by 10-fold cross validation. The results highlighted the frequency of Gln (selected by 80% of attribute weighting algorithms), percentage/frequency of Tyr, percentage of Cys, and frequencies of Try and Glu (selected by 70% of attribute weighting algorithms) as the key features that are associated with HA subtyping. Random Forest tree induction algorithm and RBF kernel function of SVM (scaled by grid search) showed high accuracy of 98% in clustering and predicting HA subtypes based on protein attributes. Decision tree models were successful in monitoring the short mutation/reassortment paths by which influenza virus can gain the key protein structure of another HA subtype and increase its host range in a short period of time with less energy consumption. Extracting and mining a large number of amino acid attributes of HA subtypes of influenza A virus through supervised algorithms represent a new avenue for understanding and predicting possible future structure of influenza pandemics.
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Ebrahimi, Mansour; Aghagolzadeh, Parisa; Shamabadi, Narges; Tahmasebi, Ahmad; Alsharifi, Mohammed; Adelson, David L.
2014-01-01
The evolution of the influenza A virus to increase its host range is a major concern worldwide. Molecular mechanisms of increasing host range are largely unknown. Influenza surface proteins play determining roles in reorganization of host-sialic acid receptors and host range. In an attempt to uncover the physic-chemical attributes which govern HA subtyping, we performed a large scale functional analysis of over 7000 sequences of 16 different HA subtypes. Large number (896) of physic-chemical protein characteristics were calculated for each HA sequence. Then, 10 different attribute weighting algorithms were used to find the key characteristics distinguishing HA subtypes. Furthermore, to discover machine leaning models which can predict HA subtypes, various Decision Tree, Support Vector Machine, Naïve Bayes, and Neural Network models were trained on calculated protein characteristics dataset as well as 10 trimmed datasets generated by attribute weighting algorithms. The prediction accuracies of the machine learning methods were evaluated by 10-fold cross validation. The results highlighted the frequency of Gln (selected by 80% of attribute weighting algorithms), percentage/frequency of Tyr, percentage of Cys, and frequencies of Try and Glu (selected by 70% of attribute weighting algorithms) as the key features that are associated with HA subtyping. Random Forest tree induction algorithm and RBF kernel function of SVM (scaled by grid search) showed high accuracy of 98% in clustering and predicting HA subtypes based on protein attributes. Decision tree models were successful in monitoring the short mutation/reassortment paths by which influenza virus can gain the key protein structure of another HA subtype and increase its host range in a short period of time with less energy consumption. Extracting and mining a large number of amino acid attributes of HA subtypes of influenza A virus through supervised algorithms represent a new avenue for understanding and predicting possible future structure of influenza pandemics. PMID:24809455
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Thomas, Philipp; Matuschek, Hannes; Grima, Ramon
2012-01-01
The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen's system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA's performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with circadian rhythms. The software iNA is freely available as executable binaries for Linux, MacOSX and Microsoft Windows, as well as the full source code under an open source license.
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Carvajal, Guido; Roser, David J; Sisson, Scott A; Keegan, Alexandra; Khan, Stuart J
2015-11-15
Risk management for wastewater treatment and reuse have led to growing interest in understanding and optimising pathogen reduction during biological treatment processes. However, modelling pathogen reduction is often limited by poor characterization of the relationships between variables and incomplete knowledge of removal mechanisms. The aim of this paper was to assess the applicability of Bayesian belief network models to represent associations between pathogen reduction, and operating conditions and monitoring parameters and predict AS performance. Naïve Bayes and semi-naïve Bayes networks were constructed from an activated sludge dataset including operating and monitoring parameters, and removal efficiencies for two pathogens (native Giardia lamblia and seeded Cryptosporidium parvum) and five native microbial indicators (F-RNA bacteriophage, Clostridium perfringens, Escherichia coli, coliforms and enterococci). First we defined the Bayesian network structures for the two pathogen log10 reduction values (LRVs) class nodes discretized into two states (< and ≥ 1 LRV) using two different learning algorithms. Eight metrics, such as Prediction Accuracy (PA) and Area Under the receiver operating Curve (AUC), provided a comparison of model prediction performance, certainty and goodness of fit. This comparison was used to select the optimum models. The optimum Tree Augmented naïve models predicted removal efficiency with high AUC when all system parameters were used simultaneously (AUCs for C. parvum and G. lamblia LRVs of 0.95 and 0.87 respectively). However, metrics for individual system parameters showed only the C. parvum model was reliable. By contrast individual parameters for G. lamblia LRV prediction typically obtained low AUC scores (AUC < 0.81). Useful predictors for C. parvum LRV included solids retention time, turbidity and total coliform LRV. The methodology developed appears applicable for predicting pathogen removal efficiency in water treatment systems generally. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry.
Chowdhury, Alok Kumar; Tjondronegoro, Dian; Chandran, Vinod; Trost, Stewart G
2017-09-01
To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbor, support vector machine, and neural network). The study used three independent data sets that included wrist-worn accelerometer data. For each data set, a four-step classification framework consisting of data preprocessing, feature extraction, normalization and feature selection, and classifier training and testing was implemented. For the custom ensemble, decisions from the single classifiers were aggregated using three decision fusion methods: weighted majority vote, naïve Bayes combination, and behavior knowledge space combination. Classifiers were cross-validated using leave-one subject out cross-validation and compared on the basis of average F1 scores. In all three data sets, ensemble learning methods consistently outperformed the individual classifiers. Among the conventional ensemble methods, random forest models provided consistently high activity recognition; however, the custom ensemble model using weighted majority voting demonstrated the highest classification accuracy in two of the three data sets. Combining multiple individual classifiers using conventional or custom ensemble learning methods can improve activity recognition accuracy from wrist-worn accelerometer data.
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Ravichandran, M; Kulanthaivel, G; Chellatamilan, T
2015-01-01
Every day, huge numbers of instant tweets (messages) are published on Twitter as it is one of the massive social media for e-learners interactions. The options regarding various interesting topics to be studied are discussed among the learners and teachers through the capture of ideal sources in Twitter. The common sentiment behavior towards these topics is received through the massive number of instant messages about them. In this paper, rather than using the opinion polarity of each message relevant to the topic, authors focus on sentence level opinion classification upon using the unsupervised algorithm named bigram item response theory (BIRT). It differs from the traditional classification and document level classification algorithm. The investigation illustrated in this paper is of threefold which are listed as follows: (1) lexicon based sentiment polarity of tweet messages; (2) the bigram cooccurrence relationship using naïve Bayesian; (3) the bigram item response theory (BIRT) on various topics. It has been proposed that a model using item response theory is constructed for topical classification inference. The performance has been improved remarkably using this bigram item response theory when compared with other supervised algorithms. The experiment has been conducted on a real life dataset containing different set of tweets and topics.
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Roetker, Nicholas S; Page, C David; Yonker, James A; Chang, Vicky; Roan, Carol L; Herd, Pamela; Hauser, Taissa S; Hauser, Robert M; Atwood, Craig S
2013-10-01
We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.
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Multiagency Urban Search Experiment Detector and Algorithm Test Bed
NASA Astrophysics Data System (ADS)
Nicholson, Andrew D.; Garishvili, Irakli; Peplow, Douglas E.; Archer, Daniel E.; Ray, William R.; Swinney, Mathew W.; Willis, Michael J.; Davidson, Gregory G.; Cleveland, Steven L.; Patton, Bruce W.; Hornback, Donald E.; Peltz, James J.; McLean, M. S. Lance; Plionis, Alexander A.; Quiter, Brian J.; Bandstra, Mark S.
2017-07-01
In order to provide benchmark data sets for radiation detector and algorithm development, a particle transport test bed has been created using experimental data as model input and validation. A detailed radiation measurement campaign at the Combined Arms Collective Training Facility in Fort Indiantown Gap, PA (FTIG), USA, provides sample background radiation levels for a variety of materials present at the site (including cinder block, gravel, asphalt, and soil) using long dwell high-purity germanium (HPGe) measurements. In addition, detailed light detection and ranging data and ground-truth measurements inform model geometry. This paper describes the collected data and the application of these data to create background and injected source synthetic data for an arbitrary gamma-ray detection system using particle transport model detector response calculations and statistical sampling. In the methodology presented here, HPGe measurements inform model source terms while detector response calculations are validated via long dwell measurements using 2"×4"×16" NaI(Tl) detectors at a variety of measurement points. A collection of responses, along with sampling methods and interpolation, can be used to create data sets to gauge radiation detector and algorithm (including detection, identification, and localization) performance under a variety of scenarios. Data collected at the FTIG site are available for query, filtering, visualization, and download at muse.lbl.gov.
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Taft, L M; Evans, R S; Shyu, C R; Egger, M J; Chawla, N; Mitchell, J A; Thornton, S N; Bray, B; Varner, M
2009-04-01
The IOM report, Preventing Medication Errors, emphasizes the overall lack of knowledge of the incidence of adverse drug events (ADE). Operating rooms, emergency departments and intensive care units are known to have a higher incidence of ADE. Labor and delivery (L&D) is an emergency care unit that could have an increased risk of ADE, where reported rates remain low and under-reporting is suspected. Risk factor identification with electronic pattern recognition techniques could improve ADE detection rates. The objective of the present study is to apply Synthetic Minority Over Sampling Technique (SMOTE) as an enhanced sampling method in a sparse dataset to generate prediction models to identify ADE in women admitted for labor and delivery based on patient risk factors and comorbidities. By creating synthetic cases with the SMOTE algorithm and using a 10-fold cross-validation technique, we demonstrated improved performance of the Naïve Bayes and the decision tree algorithms. The true positive rate (TPR) of 0.32 in the raw dataset increased to 0.67 in the 800% over-sampled dataset. Enhanced performance from classification algorithms can be attained with the use of synthetic minority class oversampling techniques in sparse clinical datasets. Predictive models created in this manner can be used to develop evidence based ADE monitoring systems.
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Magnetic resonance studies of inorganic oxides and a new pulse programming system for pulsed EMR
NASA Astrophysics Data System (ADS)
Schwartz, Dwight Allen
We have investigated several inorganic oxide systems using nuclear and electron magnetic resonance spectroscopies and also report a new pulse programming system for a pulsed S-band EMR spectrometer. We show in a study of simple perovskites (Ca,Sr,Ba)(Ti,Zr) Osb3 that magic-angle spinning O-17 NMR provides unique, highly-resolved spectra in these materials and gives evidence of being useful as a diagnostic tool in mixed phase materials (Asb{x}Asbsp{1-x}{'})BOsb3. Various used NMR and EMR techniques to study of the commercial borosilicate glasses CGW-3320, CGW-7502, CGW-7740 (Pyrex) and GSC-4, and T-08 (pure silica glass) which had received 5-10 gigarad doses of Co-60 gamma-radiation in the presence and absence of hydrogen gas. We show that B-11, Al-27 and Si-29 MAS NMR spectra contain indications of structural changes in these glasses as a result of large doses of radiation. We also observed the reduction of trace Ti(IV) to Ti(III) when Hsb2 gas was present during irradiation of glass samples. Static NMR and EMR studies in the (Na,Li)POsb3 system indicate a possible mixed alkali effect in the spin-lattice relaxation of Na-23 in NaPOsb3 and Lisb{0.4}Nasb{0.6}POsb3. Static Na-23 NMR studies of NaPOsb3 reveal the presence of different structural or dynamical environments as a function of temperatures between 23-566 C. We have investigated glass and glass fibers of Lisb{0.6}Nasb{0.4}POsb3 and Na(Psb{0.99},Vsb{0.01})Osb3, and show P-31 NMR and EMR evidence that these materials remained structurally isotropic when pulled into fibers. We show that vanadium (in Na(Psb{0.99},Vsb{0.01})Osb3) appears to suppress radiolytic unpaired electron and hole defect production which does take place in nominally vanadium-free NaPOsb3 during small doses of gamma-radiation. We describe hardware and software developed for a pulse programming system for a pulsed S-band EMR spectrometer. This system supports user-programmable automatic independent control of all pulse sequence parameters (pulse and delay durations, and pulse phases). We demonstrate the capabilities of this new system in 2-, 3-, and 4-pulse EMR experiments, and also demonstrate a new software suite for interactive simulation and simulation optimization of electron spin echo envelope modulation (ESEEM) patterns using a genetic algorithm.
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Liu, Zhihong; Zheng, Minghao; Yan, Xin; Gu, Qiong; Gasteiger, Johann; Tijhuis, Johan; Maas, Peter; Li, Jiabo; Xu, Jun
2014-09-01
Predicting compound chemical stability is important because unstable compounds can lead to either false positive or to false negative conclusions in bioassays. Experimental data (COMDECOM) measured from DMSO/H2O solutions stored at 50 °C for 105 days were used to predicted stability by applying rule-embedded naïve Bayesian learning, based upon atom center fragment (ACF) features. To build the naïve Bayesian classifier, we derived ACF features from 9,746 compounds in the COMDECOM dataset. By recursively applying naïve Bayesian learning from the data set, each ACF is assigned with an expected stable probability (p(s)) and an unstable probability (p(uns)). 13,340 ACFs, together with their p(s) and p(uns) data, were stored in a knowledge base for use by the Bayesian classifier. For a given compound, its ACFs were derived from its structure connection table with the same protocol used to drive ACFs from the training data. Then, the Bayesian classifier assigned p(s) and p(uns) values to the compound ACFs by a structural pattern recognition algorithm, which was implemented in-house. Compound instability is calculated, with Bayes' theorem, based upon the p(s) and p(uns) values of the compound ACFs. We were able to achieve performance with an AUC value of 84% and a tenfold cross validation accuracy of 76.5%. To reduce false negatives, a rule-based approach has been embedded in the classifier. The rule-based module allows the program to improve its predictivity by expanding its compound instability knowledge base, thus further reducing the possibility of false negatives. To our knowledge, this is the first in silico prediction service for the prediction of the stabilities of organic compounds.
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Prevalence and patterns of HIV transmitted drug resistance in Guatemala.
Avila-Ríos, Santiago; Mejía-Villatoro, Carlos R; García-Morales, Claudia; Soto-Nava, Maribel; Escobar, Ingrid; Mendizabal, Ricardo; Girón, Amalia; García, Leticia; Reyes-Terán, Gustavo
2011-12-01
To assess human immunodeficiency virus (HIV) diversity and the prevalence of transmitted drug resistance (TDR) in Guatemala. One hundred forty-five antiretroviral treatment-naïve patients referred to the Roosevelt Hospital in Guatemala City were enrolled from October 2010 to March 2011. Plasma HIV pol sequences were obtained and TDR was assessed with the Stanford algorithm and the World Health Organization (WHO) TDR surveillance mutation list. HIV subtype B was highly prevalent in Guatemala (96.6%, 140/145), and a 2.8% (4/145) prevalence of BF1 recombinants and 0.7% (1/145) prevalence of subtype C viruses were found. TDR prevalence for the study period was 8.3% (12/145) with the Stanford database algorithm (score > 15) and the WHO TDR surveillance mutation list. Most TDR cases were associated with non-nucleoside reverse transcriptase inhibitors (NNRTIs) (83.3%, 10/12); a low prevalence of nucleoside reverse transcriptase inhibitors and protease inhibitors was observed in the cohort (< 1% for both families). Low selection of antiretroviral drug resistance mutations was found, except for NNRTI-associated mutations. Major NNRTI mutations such as K101E, K103N, and E138K showed higher frequencies than expected in ART-naïve populations. Higher literacy was associated with a greater risk of TDR (odds ratio 4.14, P = 0.0264). This study represents one of the first efforts to describe HIV diversity and TDR prevalence and trends in Guatemala. TDR prevalence in Guatemala was at the intermediate level. Most TDR cases were associated with NNRTIs. Further and continuous TDR surveillance is necessary to gain more indepth knowledge about TDR spread and trends in Guatemala and to optimize treatment outcomes in the country.
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NASA Astrophysics Data System (ADS)
Pullanagari, R. R.; Kereszturi, Gábor; Yule, I. J.
2016-07-01
On-farm assessment of mixed pasture nutrient concentrations is important for animal production and pasture management. Hyperspectral imaging is recognized as a potential tool to quantify the nutrient content of vegetation. However, it is a great challenge to estimate macro and micro nutrients in heterogeneous mixed pastures. In this study, canopy reflectance data was measured by using a high resolution airborne visible-to-shortwave infrared (Vis-SWIR) imaging spectrometer measuring in the wavelength region 380-2500 nm to predict nutrient concentrations, nitrogen (N) phosphorus (P), potassium (K), sulfur (S), zinc (Zn), sodium (Na), manganese (Mn) copper (Cu) and magnesium (Mg) in heterogeneous mixed pastures across a sheep and beef farm in hill country, within New Zealand. Prediction models were developed using four different methods which are included partial least squares regression (PLSR), kernel PLSR, support vector regression (SVR), random forest regression (RFR) algorithms and their performance compared using the test data. The results from the study revealed that RFR produced highest accuracy (0.55 ⩽ R2CV ⩽ 0.78; 6.68% ⩽ nRMSECV ⩽ 26.47%) compared to all other algorithms for the majority of nutrients (N, P, K, Zn, Na, Cu and Mg) described, and the remaining nutrients (S and Mn) were predicted with high accuracy (0.68 ⩽ R2CV ⩽ 0.86; 13.00% ⩽ nRMSECV ⩽ 14.64%) using SVR. The best training models were used to extrapolate over the whole farm with the purpose of predicting those pasture nutrients and expressed through pixel based spatial maps. These spatially registered nutrient maps demonstrate the range and geographical location of often large differences in pasture nutrient values which are normally not measured and therefore not included in decision making when considering more effective ways to utilized pasture.
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Marcano, Mariano; Layton, Anita T; Layton, Harold E
2010-02-01
In a mathematical model of the urine concentrating mechanism of the inner medulla of the rat kidney, a nonlinear optimization technique was used to estimate parameter sets that maximize the urine-to-plasma osmolality ratio (U/P) while maintaining the urine flow rate within a plausible physiologic range. The model, which used a central core formulation, represented loops of Henle turning at all levels of the inner medulla and a composite collecting duct (CD). The parameters varied were: water flow and urea concentration in tubular fluid entering the descending thin limbs and the composite CD at the outer-inner medullary boundary; scaling factors for the number of loops of Henle and CDs as a function of medullary depth; location and increase rate of the urea permeability profile along the CD; and a scaling factor for the maximum rate of NaCl transport from the CD. The optimization algorithm sought to maximize a quantity E that equaled U/P minus a penalty function for insufficient urine flow. Maxima of E were sought by changing parameter values in the direction in parameter space in which E increased. The algorithm attained a maximum E that increased urine osmolality and inner medullary concentrating capability by 37.5% and 80.2%, respectively, above base-case values; the corresponding urine flow rate and the concentrations of NaCl and urea were all within or near reported experimental ranges. Our results predict that urine osmolality is particularly sensitive to three parameters: the urea concentration in tubular fluid entering the CD at the outer-inner medullary boundary, the location and increase rate of the urea permeability profile along the CD, and the rate of decrease of the CD population (and thus of CD surface area) along the cortico-medullary axis.
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Behavioral Modeling for Mental Health using Machine Learning Algorithms.
Srividya, M; Mohanavalli, S; Bhalaji, N
2018-04-03
Mental health is an indicator of emotional, psychological and social well-being of an individual. It determines how an individual thinks, feels and handle situations. Positive mental health helps one to work productively and realize their full potential. Mental health is important at every stage of life, from childhood and adolescence through adulthood. Many factors contribute to mental health problems which lead to mental illness like stress, social anxiety, depression, obsessive compulsive disorder, drug addiction, and personality disorders. It is becoming increasingly important to determine the onset of the mental illness to maintain proper life balance. The nature of machine learning algorithms and Artificial Intelligence (AI) can be fully harnessed for predicting the onset of mental illness. Such applications when implemented in real time will benefit the society by serving as a monitoring tool for individuals with deviant behavior. This research work proposes to apply various machine learning algorithms such as support vector machines, decision trees, naïve bayes classifier, K-nearest neighbor classifier and logistic regression to identify state of mental health in a target group. The responses obtained from the target group for the designed questionnaire were first subject to unsupervised learning techniques. The labels obtained as a result of clustering were validated by computing the Mean Opinion Score. These cluster labels were then used to build classifiers to predict the mental health of an individual. Population from various groups like high school students, college students and working professionals were considered as target groups. The research presents an analysis of applying the aforementioned machine learning algorithms on the target groups and also suggests directions for future work.
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a Fully Automated Pipeline for Classification Tasks with AN Application to Remote Sensing
NASA Astrophysics Data System (ADS)
Suzuki, K.; Claesen, M.; Takeda, H.; De Moor, B.
2016-06-01
Nowadays deep learning has been intensively in spotlight owing to its great victories at major competitions, which undeservedly pushed `shallow' machine learning methods, relatively naive/handy algorithms commonly used by industrial engineers, to the background in spite of their facilities such as small requisite amount of time/dataset for training. We, with a practical point of view, utilized shallow learning algorithms to construct a learning pipeline such that operators can utilize machine learning without any special knowledge, expensive computation environment, and a large amount of labelled data. The proposed pipeline automates a whole classification process, namely feature-selection, weighting features and the selection of the most suitable classifier with optimized hyperparameters. The configuration facilitates particle swarm optimization, one of well-known metaheuristic algorithms for the sake of generally fast and fine optimization, which enables us not only to optimize (hyper)parameters but also to determine appropriate features/classifier to the problem, which has conventionally been a priori based on domain knowledge and remained untouched or dealt with naïve algorithms such as grid search. Through experiments with the MNIST and CIFAR-10 datasets, common datasets in computer vision field for character recognition and object recognition problems respectively, our automated learning approach provides high performance considering its simple setting (i.e. non-specialized setting depending on dataset), small amount of training data, and practical learning time. Moreover, compared to deep learning the performance stays robust without almost any modification even with a remote sensing object recognition problem, which in turn indicates that there is a high possibility that our approach contributes to general classification problems.
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The Analysis Performance Method Naive Bayes Andssvm Determine Pattern Groups of Disease
NASA Astrophysics Data System (ADS)
Sitanggang, Rianto; Tulus; Situmorang, Zakarias
2017-12-01
Information is a very important element and into the daily needs of the moment, to get a precise and accurate information is not easy, this research can help decision makers and make a comparison. Researchers perform data mining techniques to analyze the performance of methods and algorithms naïve Bayes methods Smooth Support Vector Machine (ssvm) in the grouping of the disease.The pattern of disease that is often suffered by people in the group can be in the detection area of the collection of information contained in the medical record. Medical records have infromasi disease by patients in coded according to standard WHO. Processing of medical record data to find patterns of this group of diseases that often occur in this community take the attribute address, sex, type of disease, and age. Determining the next analysis is grouping of four ersebut attribute. From the results of research conducted on the dataset fever diabete mellitus, naïve Bayes method produces an average value of 99% and an accuracy and SSVM method produces an average value of 93% accuracy
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Quantitative DIC microscopy using an off-axis self-interference approach.
Fu, Dan; Oh, Seungeun; Choi, Wonshik; Yamauchi, Toyohiko; Dorn, August; Yaqoob, Zahid; Dasari, Ramachandra R; Feld, Michael S
2010-07-15
Traditional Normarski differential interference contrast (DIC) microscopy is a very powerful method for imaging nonstained biological samples. However, one of its major limitations is the nonquantitative nature of the imaging. To overcome this problem, we developed a quantitative DIC microscopy method based on off-axis sample self-interference. The digital holography algorithm is applied to obtain quantitative phase gradients in orthogonal directions, which leads to a quantitative phase image through a spiral integration of the phase gradients. This method is practically simple to implement on any standard microscope without stringent requirements on polarization optics. Optical sectioning can be obtained through enlarged illumination NA.
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5W1H Information Extraction with CNN-Bidirectional LSTM
NASA Astrophysics Data System (ADS)
Nurdin, A.; Maulidevi, N. U.
2018-03-01
In this work, information about who, did what, when, where, why, and how on Indonesian news articles were extracted by combining Convolutional Neural Network and Bidirectional Long Short-Term Memory. Convolutional Neural Network can learn semantically meaningful representations of sentences. Bidirectional LSTM can analyze the relations among words in the sequence. We also use word embedding word2vec for word representation. By combining these algorithms, we obtained F-measure 0.808. Our experiments show that CNN-BLSTM outperforms other shallow methods, namely IBk, C4.5, and Naïve Bayes with the F-measure 0.655, 0.645, and 0.595, respectively.
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Computing aggregate properties of preimages for 2D cellular automata
NASA Astrophysics Data System (ADS)
Beer, Randall D.
2017-11-01
Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm—incremental aggregation—that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.
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Prinyakupt, Jaroonrut; Pluempitiwiriyawej, Charnchai
2015-06-30
Blood smear microscopic images are routinely investigated by haematologists to diagnose most blood diseases. However, the task is quite tedious and time consuming. An automatic detection and classification of white blood cells within such images can accelerate the process tremendously. In this paper we propose a system to locate white blood cells within microscopic blood smear images, segment them into nucleus and cytoplasm regions, extract suitable features and finally, classify them into five types: basophil, eosinophil, neutrophil, lymphocyte and monocyte. Two sets of blood smear images were used in this study's experiments. Dataset 1, collected from Rangsit University, were normal peripheral blood slides under light microscope with 100× magnification; 555 images with 601 white blood cells were captured by a Nikon DS-Fi2 high-definition color camera and saved in JPG format of size 960 × 1,280 pixels at 15 pixels per 1 μm resolution. In dataset 2, 477 cropped white blood cell images were downloaded from CellaVision.com. They are in JPG format of size 360 × 363 pixels. The resolution is estimated to be 10 pixels per 1 μm. The proposed system comprises a pre-processing step, nucleus segmentation, cell segmentation, feature extraction, feature selection and classification. The main concept of the segmentation algorithm employed uses white blood cell's morphological properties and the calibrated size of a real cell relative to image resolution. The segmentation process combined thresholding, morphological operation and ellipse curve fitting. Consequently, several features were extracted from the segmented nucleus and cytoplasm regions. Prominent features were then chosen by a greedy search algorithm called sequential forward selection. Finally, with a set of selected prominent features, both linear and naïve Bayes classifiers were applied for performance comparison. This system was tested on normal peripheral blood smear slide images from two datasets. Two sets of comparison were performed: segmentation and classification. The automatically segmented results were compared to the ones obtained manually by a haematologist. It was found that the proposed method is consistent and coherent in both datasets, with dice similarity of 98.9 and 91.6% for average segmented nucleus and cell regions, respectively. Furthermore, the overall correction rate in the classification phase is about 98 and 94% for linear and naïve Bayes models, respectively. The proposed system, based on normal white blood cell morphology and its characteristics, was applied to two different datasets. The results of the calibrated segmentation process on both datasets are fast, robust, efficient and coherent. Meanwhile, the classification of normal white blood cells into five types shows high sensitivity in both linear and naïve Bayes models, with slightly better results in the linear classifier.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Diaz, Ivan; Verdun, Francis R.; Bochud, François O., E-mail: francois.bochud@chuv.ch
Purpose: Signal detection on 3D medical images depends on many factors, such as foveal and peripheral vision, the type of signal, and background complexity, and the speed at which the frames are displayed. In this paper, the authors focus on the speed with which radiologists and naïve observers search through medical images. Prior to the study, the authors asked the radiologists to estimate the speed at which they scrolled through CT sets. They gave a subjective estimate of 5 frames per second (fps). The aim of this paper is to measure and analyze the speed with which humans scroll throughmore » image stacks, showing a method to visually display the behavior of observers as the search is made as well as measuring the accuracy of the decisions. This information will be useful in the development of model observers, mathematical algorithms that can be used to evaluate diagnostic imaging systems. Methods: The authors performed a series of 3D 4-alternative forced-choice lung nodule detection tasks on volumetric stacks of chest CT images iteratively reconstructed in lung algorithm. The strategy used by three radiologists and three naïve observers was assessed using an eye-tracker in order to establish where their gaze was fixed during the experiment and to verify that when a decision was made, a correct answer was not due only to chance. In a first set of experiments, the observers were restricted to read the images at three fixed speeds of image scrolling and were allowed to see each alternative once. In the second set of experiments, the subjects were allowed to scroll through the image stacks at will with no time or gaze limits. In both static-speed and free-scrolling conditions, the four image stacks were displayed simultaneously. All trials were shown at two different image contrasts. Results: The authors were able to determine a histogram of scrolling speeds in frames per second. The scrolling speed of the naïve observers and the radiologists at the moment the signal was detected was measured at 25–30 fps. For the task chosen, the performance of the observers was not affected by the contrast or experience of the observer. However, the naïve observers exhibited a different pattern of scrolling than the radiologists, which included a tendency toward higher number of direction changes and number of slices viewed. Conclusions: The authors have determined a distribution of speeds for volumetric detection tasks. The speed at detection was higher than that subjectively estimated by the radiologists before the experiment. The speed information that was measured will be useful in the development of 3D model observers, especially anthropomorphic model observers which try to mimic human behavior.« less
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A rib-specific multimodal registration algorithm for fused unfolded rib visualization using PET/CT
NASA Astrophysics Data System (ADS)
Kaftan, Jens N.; Kopaczka, Marcin; Wimmer, Andreas; Platsch, Günther; Declerck, Jérôme
2014-03-01
Respiratory motion affects the alignment of PET and CT volumes from PET/CT examinations in a non-rigid manner. This becomes particularly apparent if reviewing fine anatomical structures such as ribs when assessing bone metastases, which frequently occur in many advanced cancers. To make this routine diagnostic task more efficient, a fused unfolded rib visualization for 18F-NaF PET/CT is presented. It allows to review the whole rib cage in a single image. This advanced visualization is enabled by a novel rib-specific registration algorithm that rigidly optimizes the local alignment of each individual rib in both modalities based on a matched filter response function. More specifically, rib centerlines are automatically extracted from CT and subsequently individually aligned to the corresponding bone-specific PET rib uptake pattern. The proposed method has been validated on 20 PET/CT scans acquired at different clinical sites. It has been demonstrated that the presented rib- specific registration method significantly improves the rib alignment without having to run complex deformable registration algorithms. At the same time, it guarantees that rib lesions are not further deformed, which may otherwise affect quantitative measurements such as SUVs. Considering clinically relevant distance thresholds, the centerline portion with good alignment compared to the ground truth improved from 60:6% to 86:7% after registration while approximately 98% can be still considered as acceptably aligned.
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Optimized principal component analysis on coronagraphic images of the fomalhaut system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Meshkat, Tiffany; Kenworthy, Matthew A.; Quanz, Sascha P.
We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing angular differential imaging and locally optimized combination of images (LOCI) for increasing the contrast achievable next to a bright star. The stellar point spread function (PSF) is constructed by removing linear combinations of principal components, allowing the flux from an extrasolar planet to shine through. The number of principal components used determines how well the stellar PSF is globally modeled. Using more principal components may decrease the number of speckles in the final image, but also increases themore » background noise. We apply PCA to Fomalhaut Very Large Telescope NaCo images acquired at 4.05 μm with an apodized phase plate. We do not detect any companions, with a model dependent upper mass limit of 13-18 M {sub Jup} from 4-10 AU. PCA achieves greater sensitivity than the LOCI algorithm for the Fomalhaut coronagraphic data by up to 1 mag. We make several adaptations to the PCA code and determine which of these prove the most effective at maximizing the signal-to-noise from a planet very close to its parent star. We demonstrate that optimizing the number of principal components used in PCA proves most effective for pulling out a planet signal.« less
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Improving Spectral Image Classification through Band-Ratio Optimization and Pixel Clustering
NASA Astrophysics Data System (ADS)
O'Neill, M.; Burt, C.; McKenna, I.; Kimblin, C.
2017-12-01
The Underground Nuclear Explosion Signatures Experiment (UNESE) seeks to characterize non-prompt observables from underground nuclear explosions (UNE). As part of this effort, we evaluated the ability of DigitalGlobe's WorldView-3 (WV3) to detect and map UNE signatures. WV3 is the current state-of-the-art, commercial, multispectral imaging satellite; however, it has relatively limited spectral and spatial resolutions. These limitations impede image classifiers from detecting targets that are spatially small and lack distinct spectral features. In order to improve classification results, we developed custom algorithms to reduce false positive rates while increasing true positive rates via a band-ratio optimization and pixel clustering front-end. The clusters resulting from these algorithms were processed with standard spectral image classifiers such as Mixture-Tuned Matched Filter (MTMF) and Adaptive Coherence Estimator (ACE). WV3 and AVIRIS data of Cuprite, Nevada, were used as a validation data set. These data were processed with a standard classification approach using MTMF and ACE algorithms. They were also processed using the custom front-end prior to the standard approach. A comparison of the results shows that the custom front-end significantly increases the true positive rate and decreases the false positive rate.This work was done by National Security Technologies, LLC, under Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy. DOE/NV/25946-3283.
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Roetker, Nicholas S.; Yonker, James A.; Chang, Vicky; Roan, Carol L.; Herd, Pamela; Hauser, Taissa S.; Hauser, Robert M.
2013-01-01
Objectives. We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. Methods. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors—13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors—18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. Results. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. Conclusions. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic–environmental–sociobehavioral interactions in depressive symptoms. PMID:23927508
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Alkali-ion microsolvation with benzene molecules.
Marques, J M C; Llanio-Trujillo, J L; Albertí, M; Aguilar, A; Pirani, F
2012-05-24
The target of this investigation is to characterize by a recently developed methodology, the main features of the first solvation shells of alkaline ions in nonpolar environments due to aromatic rings, which is of crucial relevance to understand the selectivity of several biochemical phenomena. We employ an evolutionary algorithm to obtain putative global minima of clusters formed with alkali-ions (M(+)) solvated with n benzene (Bz) molecules, i.e., M(+)-(Bz)(n). The global intermolecular interaction has been decomposed in Bz-Bz and in M(+)-Bz contributions, using a potential model based on different decompositions of the molecular polarizability of benzene. Specifically, we have studied the microsolvation of Na(+), K(+), and Cs(+) with benzene molecules. Microsolvation clusters up to n = 21 benzene molecules are involved in this work and the achieved global minimum structures are reported and discussed in detail. We observe that the number of benzene molecules allocated in the first solvation shell increases with the size of the cation, showing three molecules for Na(+) and four for both K(+) and Cs(+). The structure of this solvation shell keeps approximately unchanged as more benzene molecules are added to the cluster, which is independent of the ion. Particularly stable structures, so-called "magic numbers", arise for various nuclearities of the three alkali-ions. Strong "magic numbers" appear at n = 2, 3, and 4 for Na(+), K(+), and Cs(+), respectively. In addition, another set of weaker "magic numbers" (three per alkali-ion) are reported for larger nuclearities.
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Accelerated Monte Carlo Methods for Coulomb Collisions
NASA Astrophysics Data System (ADS)
Rosin, Mark; Ricketson, Lee; Dimits, Andris; Caflisch, Russel; Cohen, Bruce
2014-03-01
We present a new highly efficient multi-level Monte Carlo (MLMC) simulation algorithm for Coulomb collisions in a plasma. The scheme, initially developed and used successfully for applications in financial mathematics, is applied here to kinetic plasmas for the first time. The method is based on a Langevin treatment of the Landau-Fokker-Planck equation and has a rich history derived from the works of Einstein and Chandrasekhar. The MLMC scheme successfully reduces the computational cost of achieving an RMS error ɛ in the numerical solution to collisional plasma problems from (ɛ-3) - for the standard state-of-the-art Langevin and binary collision algorithms - to a theoretically optimal (ɛ-2) scaling, when used in conjunction with an underlying Milstein discretization to the Langevin equation. In the test case presented here, the method accelerates simulations by factors of up to 100. We summarize the scheme, present some tricks for improving its efficiency yet further, and discuss the method's range of applicability. Work performed for US DOE by LLNL under contract DE-AC52- 07NA27344 and by UCLA under grant DE-FG02-05ER25710.
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Sentiment analysis of Arabic tweets using text mining techniques
NASA Astrophysics Data System (ADS)
Al-Horaibi, Lamia; Khan, Muhammad Badruddin
2016-07-01
Sentiment analysis has become a flourishing field of text mining and natural language processing. Sentiment analysis aims to determine whether the text is written to express positive, negative, or neutral emotions about a certain domain. Most sentiment analysis researchers focus on English texts, with very limited resources available for other complex languages, such as Arabic. In this study, the target was to develop an initial model that performs satisfactorily and measures Arabic Twitter sentiment by using machine learning approach, Naïve Bayes and Decision Tree for classification algorithms. The datasets used contains more than 2,000 Arabic tweets collected from Twitter. We performed several experiments to check the performance of the two algorithms classifiers using different combinations of text-processing functions. We found that available facilities for Arabic text processing need to be made from scratch or improved to develop accurate classifiers. The small functionalities developed by us in a Python language environment helped improve the results and proved that sentiment analysis in the Arabic domain needs lot of work on the lexicon side.
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Development of a compact and cost effective multi-input digital signal processing system
NASA Astrophysics Data System (ADS)
Darvish-Molla, Sahar; Chin, Kenrick; Prestwich, William V.; Byun, Soo Hyun
2018-01-01
A prototype digital signal processing system (DSP) was developed using a microcontroller interfaced with a 12-bit sampling ADC, which offers a considerably inexpensive solution for processing multiple detectors with high throughput. After digitization of the incoming pulses, in order to maximize the output counting rate, a simple algorithm was employed for pulse height analysis. Moreover, an algorithm aiming at the real-time pulse pile-up deconvolution was implemented. The system was tested using a NaI(Tl) detector in comparison with a traditional analogue and commercial digital systems for a variety of count rates. The performance of the prototype system was consistently superior to the analogue and the commercial digital systems up to the input count rate of 61 kcps while was slightly inferior to the commercial digital system but still superior to the analogue system in the higher input rates. Considering overall cost, size and flexibility, this custom made multi-input digital signal processing system (MMI-DSP) was the best reliable choice for the purpose of the 2D microdosimetric data collection, or for any measurement in which simultaneous multi-data collection is required.
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Wang, Liang; Yang, Die; Fang, Cheng; Chen, Zuliang; Lesniewski, Peter J; Mallavarapu, Megharaj; Naidu, Ravendra
2015-01-01
Sodium potassium absorption ratio (SPAR) is an important measure of agricultural water quality, wherein four exchangeable cations (K(+), Na(+), Ca(2+) and Mg(2+)) should be simultaneously determined. An ISE-array is suitable for this application because its simplicity, rapid response characteristics and lower cost. However, cross-interferences caused by the poor selectivity of ISEs need to be overcome using multivariate chemometric methods. In this paper, a solid contact ISE array, based on a Prussian blue modified glassy carbon electrode (PB-GCE), was applied with a novel chemometric strategy. One of the most popular independent component analysis (ICA) methods, the fast fixed-point algorithm for ICA (fastICA), was implemented by the genetic algorithm (geneticICA) to avoid the local maxima problem commonly observed with fastICA. This geneticICA can be implemented as a data preprocessing method to improve the prediction accuracy of the Back-propagation neural network (BPNN). The ISE array system was validated using 20 real irrigation water samples from South Australia, and acceptable prediction accuracies were obtained. Copyright © 2014 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Sun, Jiasong; Zhang, Yuzhen; Chen, Qian; Zuo, Chao
2017-02-01
Fourier ptychographic microscopy (FPM) is a newly developed super-resolution technique, which employs angularly varying illuminations and a phase retrieval algorithm to surpass the diffraction limit of a low numerical aperture (NA) objective lens. In current FPM imaging platforms, accurate knowledge of LED matrix's position is critical to achieve good recovery quality. Furthermore, considering such a wide field-of-view (FOV) in FPM, different regions in the FOV have different sensitivity of LED positional misalignment. In this work, we introduce an iterative method to correct position errors based on the simulated annealing (SA) algorithm. To improve the efficiency of this correcting process, large number of iterations for several images with low illumination NAs are firstly implemented to estimate the initial values of the global positional misalignment model through non-linear regression. Simulation and experimental results are presented to evaluate the performance of the proposed method and it is demonstrated that this method can both improve the quality of the recovered object image and relax the LED elements' position accuracy requirement while aligning the FPM imaging platforms.
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Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms
NASA Astrophysics Data System (ADS)
Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.
2017-12-01
Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
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Patel, Sanjay R.; Weng, Jia; Rueschman, Michael; Dudley, Katherine A.; Loredo, Jose S.; Mossavar-Rahmani, Yasmin; Ramirez, Maricelle; Ramos, Alberto R.; Reid, Kathryn; Seiger, Ashley N.; Sotres-Alvarez, Daniela; Zee, Phyllis C.; Wang, Rui
2015-01-01
Study Objectives: While actigraphy is considered objective, the process of setting rest intervals to calculate sleep variables is subjective. We sought to evaluate the reproducibility of actigraphy-derived measures of sleep using a standardized algorithm for setting rest intervals. Design: Observational study. Setting: Community-based. Participants: A random sample of 50 adults aged 18–64 years free of severe sleep apnea participating in the Sueño sleep ancillary study to the Hispanic Community Health Study/Study of Latinos. Interventions: N/A. Measurements and Results: Participants underwent 7 days of continuous wrist actigraphy and completed daily sleep diaries. Studies were scored twice by each of two scorers. Rest intervals were set using a standardized hierarchical approach based on event marker, diary, light, and activity data. Sleep/wake status was then determined for each 30-sec epoch using a validated algorithm, and this was used to generate 11 variables: mean nightly sleep duration, nap duration, 24-h sleep duration, sleep latency, sleep maintenance efficiency, sleep fragmentation index, sleep onset time, sleep offset time, sleep midpoint time, standard deviation of sleep duration, and standard deviation of sleep midpoint. Intra-scorer intraclass correlation coefficients (ICCs) were high, ranging from 0.911 to 0.995 across all 11 variables. Similarly, inter-scorer ICCs were high, also ranging from 0.911 to 0.995, and mean inter-scorer differences were small. Bland-Altman plots did not reveal any systematic disagreement in scoring. Conclusions: With use of a standardized algorithm to set rest intervals, scoring of actigraphy for the purpose of generating a wide array of sleep variables is highly reproducible. Citation: Patel SR, Weng J, Rueschman M, Dudley KA, Loredo JS, Mossavar-Rahmani Y, Ramirez M, Ramos AR, Reid K, Seiger AN, Sotres-Alvarez D, Zee PC, Wang R. Reproducibility of a standardized actigraphy scoring algorithm for sleep in a US Hispanic/Latino population. SLEEP 2015;38(9):1497–1503. PMID:25845697
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Kapetanovic, Suad; Aaron, Lisa; Montepiedra, Grace; Anthony, Patricia; Thuvamontolrat, Kasalyn; Pahwa, Savita; Burchett, Sandra; Weinberg, Adriana; Kovacs, Andrea
2015-01-01
Background We examined the effect of cytomegalovirus (CMV) co-infection and viremia on reconstitution of selected CD4+ and CD8+ T-cell subsets in perinatally HIV-infected (PHIV+) children ≥ 1-year old who participated in a partially randomized, open-label, 96-week combination antiretroviral therapy (cART)-algorithm study. Methods Participants were categorized as CMV-naïve, CMV-positive (CMV+) viremic, and CMV+ aviremic, based on blood, urine, or throat culture, CMV IgG and DNA polymerase chain reaction measured at baseline. At weeks 0, 12, 20 and 40, T-cell subsets including naïve (CD62L+CD45RA+; CD95-CD28+), activated (CD38+HLA-DR+) and terminally differentiated (CD62L-CD45RA+; CD95+CD28-) CD4+ and CD8+ T-cells were measured by flow cytometry. Results Of the 107 participants included in the analysis, 14% were CMV+ viremic; 49% CMV+ aviremic; 37% CMV-naïve. In longitudinal adjusted models, compared with CMV+ status, baseline CMV-naïve status was significantly associated with faster recovery of CD8+CD62L+CD45RA+% and CD8+CD95-CD28+% and faster decrease of CD8+CD95+CD28-%, independent of HIV VL response to treatment, cART regimen and baseline CD4%. Surprisingly, CMV status did not have a significant impact on longitudinal trends in CD8+CD38+HLA-DR+%. CMV status did not have a significant impact on any CD4+ T-cell subsets. Conclusions In this cohort of PHIV+ children, the normalization of naïve and terminally differentiated CD8+ T-cell subsets in response to cART was detrimentally affected by the presence of CMV co-infection. These findings may have implications for adjunctive treatment strategies targeting CMV co-infection in PHIV+ children, especially those that are now adults or reaching young adulthood and may have accelerated immunologic aging, increased opportunistic infections and aging diseases of the immune system. PMID:25794163
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Demons versus Level-Set motion registration for coronary 18F-sodium fluoride PET.
Rubeaux, Mathieu; Joshi, Nikhil; Dweck, Marc R; Fletcher, Alison; Motwani, Manish; Thomson, Louise E; Germano, Guido; Dey, Damini; Berman, Daniel S; Newby, David E; Slomka, Piotr J
2016-02-27
Ruptured coronary atherosclerotic plaques commonly cause acute myocardial infarction. It has been recently shown that active microcalcification in the coronary arteries, one of the features that characterizes vulnerable plaques at risk of rupture, can be imaged using cardiac gated 18 F-sodium fluoride ( 18 F-NaF) PET. We have shown in previous work that a motion correction technique applied to cardiac-gated 18 F-NaF PET images can enhance image quality and improve uptake estimates. In this study, we further investigated the applicability of different algorithms for registration of the coronary artery PET images. In particular, we aimed to compare demons vs. level-set nonlinear registration techniques applied for the correction of cardiac motion in coronary 18 F-NaF PET. To this end, fifteen patients underwent 18 F-NaF PET and prospective coronary CT angiography (CCTA). PET data were reconstructed in 10 ECG gated bins; subsequently these gated bins were registered using demons and level-set methods guided by the extracted coronary arteries from CCTA, to eliminate the effect of cardiac motion on PET images. Noise levels, target-to-background ratios (TBR) and global motion were compared to assess image quality. Compared to the reference standard of using only diastolic PET image (25% of the counts from PET acquisition), cardiac motion registration using either level-set or demons techniques almost halved image noise due to the use of counts from the full PET acquisition and increased TBR difference between 18 F-NaF positive and negative lesions. The demons method produces smoother deformation fields, exhibiting no singularities (which reflects how physically plausible the registration deformation is), as compared to the level-set method, which presents between 4 and 8% of singularities, depending on the coronary artery considered. In conclusion, the demons method produces smoother motion fields as compared to the level-set method, with a motion that is physiologically plausible. Therefore, level-set technique will likely require additional post-processing steps. On the other hand, the observed TBR increases were the highest for the level-set technique. Further investigations of the optimal registration technique of this novel coronary PET imaging technique are warranted.
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Demons versus level-set motion registration for coronary 18F-sodium fluoride PET
NASA Astrophysics Data System (ADS)
Rubeaux, Mathieu; Joshi, Nikhil; Dweck, Marc R.; Fletcher, Alison; Motwani, Manish; Thomson, Louise E.; Germano, Guido; Dey, Damini; Berman, Daniel S.; Newby, David E.; Slomka, Piotr J.
2016-03-01
Ruptured coronary atherosclerotic plaques commonly cause acute myocardial infarction. It has been recently shown that active microcalcification in the coronary arteries, one of the features that characterizes vulnerable plaques at risk of rupture, can be imaged using cardiac gated 18F-sodium fluoride (18F-NaF) PET. We have shown in previous work that a motion correction technique applied to cardiac-gated 18F-NaF PET images can enhance image quality and improve uptake estimates. In this study, we further investigated the applicability of different algorithms for registration of the coronary artery PET images. In particular, we aimed to compare demons vs. level-set nonlinear registration techniques applied for the correction of cardiac motion in coronary 18F-NaF PET. To this end, fifteen patients underwent 18F-NaF PET and prospective coronary CT angiography (CCTA). PET data were reconstructed in 10 ECG gated bins; subsequently these gated bins were registered using demons and level-set methods guided by the extracted coronary arteries from CCTA, to eliminate the effect of cardiac motion on PET images. Noise levels, target-to-background ratios (TBR) and global motion were compared to assess image quality. Compared to the reference standard of using only diastolic PET image (25% of the counts from PET acquisition), cardiac motion registration using either level-set or demons techniques almost halved image noise due to the use of counts from the full PET acquisition and increased TBR difference between 18F-NaF positive and negative lesions. The demons method produces smoother deformation fields, exhibiting no singularities (which reflects how physically plausible the registration deformation is), as compared to the level-set method, which presents between 4 and 8% of singularities, depending on the coronary artery considered. In conclusion, the demons method produces smoother motion fields as compared to the level-set method, with a motion that is physiologically plausible. Therefore, level-set technique will likely require additional post-processing steps. On the other hand, the observed TBR increases were the highest for the level-set technique. Further investigations of the optimal registration technique of this novel coronary PET imaging technique are warranted.
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2D evaluation of spectral LIBS data derived from heterogeneous materials using cluster algorithm
NASA Astrophysics Data System (ADS)
Gottlieb, C.; Millar, S.; Grothe, S.; Wilsch, G.
2017-08-01
Laser-induced Breakdown Spectroscopy (LIBS) is capable of providing spatially resolved element maps in regard to the chemical composition of the sample. The evaluation of heterogeneous materials is often a challenging task, especially in the case of phase boundaries. In order to determine information about a certain phase of a material, the need for a method that offers an objective evaluation is necessary. This paper will introduce a cluster algorithm in the case of heterogeneous building materials (concrete) to separate the spectral information of non-relevant aggregates and cement matrix. In civil engineering, the information about the quantitative ingress of harmful species like Cl-, Na+ and SO42- is of great interest in the evaluation of the remaining lifetime of structures (Millar et al., 2015; Wilsch et al., 2005). These species trigger different damage processes such as the alkali-silica reaction (ASR) or the chloride-induced corrosion of the reinforcement. Therefore, a discrimination between the different phases, mainly cement matrix and aggregates, is highly important (Weritz et al., 2006). For the 2D evaluation, the expectation-maximization-algorithm (EM algorithm; Ester and Sander, 2000) has been tested for the application presented in this work. The method has been introduced and different figures of merit have been presented according to recommendations given in Haddad et al. (2014). Advantages of this method will be highlighted. After phase separation, non-relevant information can be excluded and only the wanted phase displayed. Using a set of samples with known and unknown composition, the EM-clustering method has been validated regarding to Gustavo González and Ángeles Herrador (2007).
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2015-01-01
Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377
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Alexander, Joshua M.; Kopun, Judy G.; Stelmachowicz, Patricia G.
2014-01-01
Summary: Listeners with normal hearing and mild to moderate loss identified fricatives and affricates that were recorded through hearing aids with frequency transposition (FT) or nonlinear frequency compression (NFC). FT significantly degraded performance for both groups. When frequencies up to ~9 kHz were lowered with NFC and with a novel frequency compression algorithm, spectral envelope decimation, performance significantly improved relative to conventional amplification (NFC-off) and was equivalent to wideband speech. Significant differences between most conditions could be largely attributed to an increase or decrease in confusions for /s/ and /z/. Objectives: Stelmachowicz and colleagues have demonstrated that the limited bandwidth associated with conventional hearing aid amplification prevents useful high-frequency speech information from being transmitted. The purpose of this study was to examine the efficacy of two popular frequency-lowering algorithms and one novel algorithm (spectral envelope decimation) in adults with mild-to-moderate sensorineural hearing loss and in normal-hearing controls. Design: Participants listened monaurally through headphones to recordings of nine fricatives and affricates spoken by three women in a vowel-consonant (VC) context. Stimuli were mixed with speech-shaped noise at 10 dB SNR and recorded through a Widex Inteo IN-9 and a Phonak Naída UP V behind-the-ear (BTE) hearing aid. Frequency transposition (FT) is used in the Inteo and nonlinear frequency compression (NFC) used in the Naída. Both devices were programmed to lower frequencies above 4 kHz, but neither device could lower frequencies above 6-7 kHz. Each device was tested under four conditions: frequency lowering deactivated (FT-off and NFC-off), frequency lowering activated (FT and NFC), wideband (WB), and a fourth condition unique to each hearing aid. The WB condition was constructed by mixing recordings from the first condition with high-pass filtered versions of the source stimuli. For the Inteo, the fourth condition consisted of recordings made with the same settings as the first, but with the noise reduction feature activated (FT-off). For the Naída, the fourth condition was the same as the first condition except that source stimuli were pre-processed by a novel frequency compression algorithm, spectral envelope decimation (SED), designed in MATLAB that allowed for a more complete lowering of the 4-10 kHz input band. A follow up experiment with NFC used Phonak’s Naída SP V BTE, which could also lower a greater range of input frequencies. Results: For normal-hearing (NH) and hearing-impaired (HI) listeners, performance with FT was significantly worse compared to the other conditions. Consistent with previous findings, performance for the HI listeners in the WB condition was significantly better than in the FT-off condition. In addition, performance in the SED and WB conditions were both significantly better than the NFC-off condition and the NFC condition with 6 kHz input bandwidth. There were no significant differences between SED and WB, indicating that improvements in fricative identification obtained by increasing bandwidth can also be obtained using this form of frequency compression. Significant differences between most conditions could be largely attributed to an increase or decrease in confusions for the phonemes /s/ and /z/. In the follow up experiment, performance in the NFC condition with 10 kHz input bandwidth was significantly better than NFC-off, replicating the results obtained with SED. Furthermore, listeners who performed poorly with NFC-off tended to show the most improvement with NFC. Conclusions: Improvements in the identification of stimuli chosen to be sensitive to the effects of frequency lowering have been demonstrated using two forms of frequency compression (NFC and SED) in individuals with mild to moderate high-frequency SNHL. However, negative results caution against using FT for this population. Results also indicate that the advantage of an extended bandwidth as reported here and elsewhere applies to the input bandwidth for frequency compression (NFC/SED) when the start frequency is ≥ 4 kHz. PMID:24699702
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Kusano, Kristofer; Gabler, Hampton C
2014-01-01
The odds of death for a seriously injured crash victim are drastically reduced if he or she received care at a trauma center. Advanced automated crash notification (AACN) algorithms are postcrash safety systems that use data measured by the vehicles during the crash to predict the likelihood of occupants being seriously injured. The accuracy of these models are crucial to the success of an AACN. The objective of this study was to compare the predictive performance of competing injury risk models and algorithms: logistic regression, random forest, AdaBoost, naïve Bayes, support vector machine, and classification k-nearest neighbors. This study compared machine learning algorithms to the widely adopted logistic regression modeling approach. Machine learning algorithms have not been commonly studied in the motor vehicle injury literature. Machine learning algorithms may have higher predictive power than logistic regression, despite the drawback of lacking the ability to perform statistical inference. To evaluate the performance of these algorithms, data on 16,398 vehicles involved in non-rollover collisions were extracted from the NASS-CDS. Vehicles with any occupants having an Injury Severity Score (ISS) of 15 or greater were defined as those requiring victims to be treated at a trauma center. The performance of each model was evaluated using cross-validation. Cross-validation assesses how a model will perform in the future given new data not used for model training. The crash ΔV (change in velocity during the crash), damage side (struck side of the vehicle), seat belt use, vehicle body type, number of events, occupant age, and occupant sex were used as predictors in each model. Logistic regression slightly outperformed the machine learning algorithms based on sensitivity and specificity of the models. Previous studies on AACN risk curves used the same data to train and test the power of the models and as a result had higher sensitivity compared to the cross-validated results from this study. Future studies should account for future data; for example, by using cross-validation or risk presenting optimistic predictions of field performance. Past algorithms have been criticized for relying on age and sex, being difficult to measure by vehicle sensors, and inaccuracies in classifying damage side. The models with accurate damage side and including age/sex did outperform models with less accurate damage side and without age/sex, but the differences were small, suggesting that the success of AACN is not reliant on these predictors.
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A Comparative Study with RapidMiner and WEKA Tools over some Classification Techniques for SMS Spam
NASA Astrophysics Data System (ADS)
Foozy, Cik Feresa Mohd; Ahmad, Rabiah; Faizal Abdollah, M. A.; Chai Wen, Chuah
2017-08-01
SMS Spamming is a serious attack that can manipulate the use of the SMS by spreading the advertisement in bulk. By sending the unwanted SMS that contain advertisement can make the users feeling disturb and this against the privacy of the mobile users. To overcome these issues, many studies have proposed to detect SMS Spam by using data mining tools. This paper will do a comparative study using five machine learning techniques such as Naïve Bayes, K-NN (K-Nearest Neighbour Algorithm), Decision Tree, Random Forest and Decision Stumps to observe the accuracy result between RapidMiner and WEKA for dataset SMS Spam UCI Machine Learning repository.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Boman, Erik G.
This LDRD project was a campus exec fellowship to fund (in part) Donald Nguyen’s PhD research at UT-Austin. His work has focused on parallel programming models, and scheduling irregular algorithms on shared-memory systems using the Galois framework. Galois provides a simple but powerful way for users and applications to automatically obtain good parallel performance using certain supported data containers. The naïve user can write serial code, while advanced users can optimize performance by advanced features, such as specifying the scheduling policy. Galois was used to parallelize two sparse matrix reordering schemes: RCM and Sloan. Such reordering is important in high-performancemore » computing to obtain better data locality and thus reduce run times.« less
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Sindona, A; Pisarra, M; Maletta, S; Riccardi, P; Falcone, G
2010-12-01
Resonant neutralization of hyperthermal energy Na(+) ions impinging on Cu(100) surfaces is studied, focusing on two specific collision events: one in which the projectile is reflected off the surface, the other in which the incident atom penetrates the outer surface layers initiating a series of scattering processes, within the target, and coming out together with a single surface atom. A semi-empirical model potential is adopted that embeds: (i) the electronic structure of the sample, (ii) the central field of the projectile, and (iii) the contribution of the Cu atom ejected in multiple scattering events. The evolution of the ionization orbital of the scattered atom is simulated, backwards in time, using a wavepacket propagation algorithm. The output of the approach is the neutralization probability, obtained by projecting the time-reversed valence wavefunction of the projectile onto the initially filled conduction band states. The results are in agreement with available data from the literature (Keller et al 1995 Phys. Rev. Lett. 75 1654) indicating that the motion of surface atoms, exiting the targets with kinetic energies of the order of a few electronvolts, plays a significant role in the final charge state of projectiles.
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NASA Astrophysics Data System (ADS)
Abbas, Mahmoud I.; Badawi, M. S.; Ruskov, I. N.; El-Khatib, A. M.; Grozdanov, D. N.; Thabet, A. A.; Kopatch, Yu. N.; Gouda, M. M.; Skoy, V. R.
2015-01-01
Gamma-ray detector systems are important instruments in a broad range of science and new setup are continually developing. The most recent step in the evolution of detectors for nuclear spectroscopy is the construction of large arrays of detectors of different forms (for example, conical, pentagonal, hexagonal, etc.) and sizes, where the performance and the efficiency can be increased. In this work, a new direct numerical method (NAM), in an integral form and based on the efficiency transfer (ET) method, is used to calculate the full-energy peak efficiency of a single hexagonal NaI(Tl) detector. The algorithms and the calculations of the effective solid angle ratios for a point (isotropic irradiating) gamma-source situated coaxially at different distances from the detector front-end surface, taking into account the attenuation of the gamma-rays in the detector's material, end-cap and the other materials in-between the gamma-source and the detector, are considered as the core of this (ET) method. The calculated full-energy peak efficiency values by the (NAM) are found to be in a good agreement with the measured experimental data.
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Mycofier: a new machine learning-based classifier for fungal ITS sequences.
Delgado-Serrano, Luisa; Restrepo, Silvia; Bustos, Jose Ricardo; Zambrano, Maria Mercedes; Anzola, Juan Manuel
2016-08-11
The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level. A fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level. The final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git .
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Movement imagery classification in EMOTIV cap based system by Naïve Bayes.
Stock, Vinicius N; Balbinot, Alexandre
2016-08-01
Brain-computer interfaces (BCI) provide means of communications and control, in assistive technology, which do not require motor activity from the user. The goal of this study is to promote classification of two types of imaginary movements, left and right hands, in an EMOTIV cap based system, using the Naïve Bayes classifier. A preliminary analysis with respect to results obtained by other experiments in this field is also conducted. Processing of the electroencephalography (EEG) signals is done applying Common Spatial Pattern filters. The EPOC electrodes cap is used for EEG acquisition, in two test subjects, for two distinct trial formats. The channels picked are FC5, FC6, P7 and P8 of the 10-20 system, and a discussion about the differences of using C3, C4, P3 and P4 positions is proposed. Dataset 3 of the BCI Competition II is also analyzed using the implemented algorithms. The maximum classification results for the proposed experiment and for the BCI Competition dataset were, respectively, 79% and 85% The conclusion of this study is that the picked positions for electrodes may be applied for BCI systems with satisfactory classification rates.
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Kumar, Anup; Guria, Chandan; Chitres, G; Chakraborty, Arunangshu; Pathak, A K
2016-10-01
A comprehensive mathematical model involving NPK-10:26:26 fertilizer, NaCl, NaHCO3, light and temperature operating variables for Dunaliella tertiolecta cultivation is formulated to predict microalgae-biomass and lipid productivity. Proposed model includes Monod/Andrews kinetics for the absorption of essential nutrients into algae-biomass and Droop model involving internal nutrient cell quota for microalgae growth, assuming algae-biomass is composed of sugar, functional-pool and neutral-lipid. Biokinetic model parameters are determined by minimizing the residual-sum-of-square-errors between experimental and computed microalgae-biomass and lipid productivity using genetic algorithm. Developed model is validated with the experiments of Dunaliella tertiolecta cultivation using air-agitated sintered-disk chromatographic glass-bubble column and the effects of operating variables on microalgae-biomass and lipid productivity is investigated. Finally, parametric sensitivity analysis is carried out to know the sensitivity of model parameters on the obtained results in the input parameter space. Proposed model may be helpful in scale-up studies and implementation of model-based control strategy in large-scale algal cultivation. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Grima, Ramon
2012-01-01
The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen’s system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA’s performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with circadian rhythms. The software iNA is freely available as executable binaries for Linux, MacOSX and Microsoft Windows, as well as the full source code under an open source license. PMID:22723865
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Fujiwara, Masakazu; Kawasaki, Yohei; Yamada, Hiroshi
2016-01-01
Rapid dissemination of information regarding adverse drug reactions is a key aspect for improving pharmacovigilance. There is a possibility that unknown adverse drug reactions will become apparent through post-marketing administration. Currently, although there have been studies evaluating the relationships between a drug and adverse drug reactions using the JADER database which collects reported spontaneous adverse drug reactions, an efficient approach to assess the association between adverse drug reactions of drugs with the same indications as well as the influence of demographics (e.g. gender) has not been proposed. We utilized the REAC and DEMO tables from the May 2015 version of JADER for patients taking antidepressant drugs (SSRI, SNRI, and NaSSA). We evaluated the associations using association analyses with an apriori algorithm. Support, confidence, lift, and conviction were used as indicators for associations. The highest score in adverse drug reactions for SSRI was obtained for "aspartate aminotransferase increased", "alanine aminotransferase increased", with values of 0.0059, 0.93, 135.5, and 13.9 for support, confidence, lift and conviction, respectively. For SNRI, "international normalized ratio increased", "drug interaction" were observed with 0.0064, 1.00, 71.9, and NA. For NaSSA, "anxiety", "irritability" were observed with 0.0058, 0.80, 49.9, and 4.9. For female taking SSRI, the highest support scores were observed in "twenties", "suicide attempt", whereas "thirties", "neuroleptic malignant syndrome" were observed for male. Second, for SNRI, "eighties", "inappropriate antidiuretic hormone secretion" were observed for female, whereas "interstitial lung disease" and "hepatitis fulminant" were for male. Finally, for NaSSA, "suicidal ideation" was for female, and "rhabdomyolysis" was for male. Different combinations of adverse drug reactions were noted between the antidepressants. In addition, the reported adverse drug reactions differed by gender. This approach using a large database for examining the associations can improve safety monitoring during the post-marketing phase.
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Henritzi, Dinah; Zhao, Na; Starick, Elke; Simon, Gaelle; Krog, Jesper S; Larsen, Lars Erik; Reid, Scott M; Brown, Ian H; Chiapponi, Chiara; Foni, Emanuela; Wacheck, Silke; Schmid, Peter; Beer, Martin; Hoffmann, Bernd; Harder, Timm C
2016-11-01
A diversifying pool of mammalian-adapted influenza A viruses (IAV) with largely unknown zoonotic potential is maintained in domestic swine populations worldwide. The most recent human influenza pandemic in 2009 was caused by a virus with genes originating from IAV isolated from swine. Swine influenza viruses (SIV) are widespread in European domestic pig populations and evolve dynamically. Knowledge regarding occurrence, spread and evolution of potentially zoonotic SIV in Europe is poorly understood. Efficient SIV surveillance programmes depend on sensitive and specific diagnostic methods which allow for cost-effective large-scale analysis. New SIV haemagglutinin (HA) and neuraminidase (NA) subtype- and lineage-specific multiplex real-time RT-PCRs (RT-qPCR) have been developed and validated with reference virus isolates and clinical samples. A diagnostic algorithm is proposed for the combined detection in clinical samples and subtyping of SIV strains currently circulating in Europe that is based on a generic, M-gene-specific influenza A virus RT-qPCR. In a second step, positive samples are examined by tetraplex HA- and triplex NA-specific RT-qPCRs to differentiate the porcine subtypes H1, H3, N1 and N2. Within the HA subtype H1, lineages "av" (European avian-derived), "hu" (European human-derived) and "pdm" (human pandemic A/H1N1, 2009) are distinguished by RT-qPCRs, and within the NA subtype N1, lineage "pdm" is differentiated. An RT-PCR amplicon Sanger sequencing method of small fragments of the HA and NA genes is also proposed to safeguard against failure of multiplex RT-qPCR subtyping. These new multiplex RT-qPCR assays provide adequate tools for sustained SIV monitoring programmes in Europe. © 2016 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.
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Fujiwara, Masakazu; Kawasaki, Yohei; Yamada, Hiroshi
2016-01-01
Background Rapid dissemination of information regarding adverse drug reactions is a key aspect for improving pharmacovigilance. There is a possibility that unknown adverse drug reactions will become apparent through post-marketing administration. Currently, although there have been studies evaluating the relationships between a drug and adverse drug reactions using the JADER database which collects reported spontaneous adverse drug reactions, an efficient approach to assess the association between adverse drug reactions of drugs with the same indications as well as the influence of demographics (e.g. gender) has not been proposed. Methods and Findings We utilized the REAC and DEMO tables from the May 2015 version of JADER for patients taking antidepressant drugs (SSRI, SNRI, and NaSSA). We evaluated the associations using association analyses with an apriori algorithm. Support, confidence, lift, and conviction were used as indicators for associations. The highest score in adverse drug reactions for SSRI was obtained for "aspartate aminotransferase increased", "alanine aminotransferase increased", with values of 0.0059, 0.93, 135.5, and 13.9 for support, confidence, lift and conviction, respectively. For SNRI, "international normalized ratio increased", "drug interaction" were observed with 0.0064, 1.00, 71.9, and NA. For NaSSA, "anxiety", "irritability" were observed with 0.0058, 0.80, 49.9, and 4.9. For female taking SSRI, the highest support scores were observed in "twenties", "suicide attempt", whereas "thirties", "neuroleptic malignant syndrome" were observed for male. Second, for SNRI, "eighties", "inappropriate antidiuretic hormone secretion" were observed for female, whereas "interstitial lung disease" and "hepatitis fulminant" were for male. Finally, for NaSSA, "suicidal ideation" was for female, and "rhabdomyolysis" was for male. Conclusions Different combinations of adverse drug reactions were noted between the antidepressants. In addition, the reported adverse drug reactions differed by gender. This approach using a large database for examining the associations can improve safety monitoring during the post-marketing phase. PMID:27119382
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NASA Astrophysics Data System (ADS)
Stavrou, Elissaios
As evidenced by numerous experimental and theoretical studies, application of high pressure can dramatically modify the atomic arrangement and electronic structures of both elements and compounds. However, the great majority of research has been focused on the effect of pressure on compounds with constant stoichiometries (typically those stable under ambient conditions). Recent theoretical predictions, using advanced search algorithms, suggest that composition is another important variable in the search for stable compounds, i.e. that the more stable stoichiometry at elevated pressures is not a priory the same as that at ambient pressure. Indeed, thermodynamically stable compounds with novel compositions were theoretically predicted and experimentally verified even in relatively simple chemical systems including: Na-Cl, C-N, Li-H, Na-H, Cs-N, H-N, Na-He, Xe-Fe. These materials are stable due to the formation of novel chemical bonds that are absent, or even forbidden, at ambient conditions. Tuning the composition of the system thus represents another important, but poorly explored approach to the synthesis of novel materials. By varying the stoichiometry one can design novel materials with enhanced properties (e.g. high energy density, hardness, superconductivity etc.), that are metastable at ambient conditions and synthesized at thermodynamic conditions less extreme than that those required for known stoichiometries. Moreover, current outstanding questions, ``anomalies'' and ``paradoxes'' in geo- and planetary science (e.g. the Xenon paradox) could be addressed based on the stability of surprising, stoichiometries that challenge our traditional ``textbook'' picture. In this talk, I will briefly present recent results and highlight the need of close synergy between experimental and theoretical efforts to understand the challenging and complex field of variable stoichiometry under pressure. Finally, possible new routes for the synthesis of novel materials will be discussed. This work was performed under the auspices of the U. S. Department of Energy by Lawrence Livermore National Security, LLC under Contract DE-AC52-07NA27344.
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Benndorf, Matthias; Burnside, Elizabeth S; Herda, Christoph; Langer, Mathias; Kotter, Elmar
2015-08-01
Lesions detected at mammography are described with a highly standardized terminology: the breast imaging-reporting and data system (BI-RADS) lexicon. Up to now, no validated semantic computer assisted classification algorithm exists to interactively link combinations of morphological descriptors from the lexicon to a probabilistic risk estimate of malignancy. The authors therefore aim at the external validation of the mammographic mass diagnosis (MMassDx) algorithm. A classification algorithm like MMassDx must perform well in a variety of clinical circumstances and in datasets that were not used to generate the algorithm in order to ultimately become accepted in clinical routine. The MMassDx algorithm uses a naïve Bayes network and calculates post-test probabilities of malignancy based on two distinct sets of variables, (a) BI-RADS descriptors and age ("descriptor model") and (b) BI-RADS descriptors, age, and BI-RADS assessment categories ("inclusive model"). The authors evaluate both the MMassDx (descriptor) and MMassDx (inclusive) models using two large publicly available datasets of mammographic mass lesions: the digital database for screening mammography (DDSM) dataset, which contains two subsets from the same examinations-a medio-lateral oblique (MLO) view and cranio-caudal (CC) view dataset-and the mammographic mass (MM) dataset. The DDSM contains 1220 mass lesions and the MM dataset contains 961 mass lesions. The authors evaluate discriminative performance using area under the receiver-operating-characteristic curve (AUC) and compare this to the BI-RADS assessment categories alone (i.e., the clinical performance) using the DeLong method. The authors also evaluate whether assigned probabilistic risk estimates reflect the lesions' true risk of malignancy using calibration curves. The authors demonstrate that the MMassDx algorithms show good discriminatory performance. AUC for the MMassDx (descriptor) model in the DDSM data is 0.876/0.895 (MLO/CC view) and AUC for the MMassDx (inclusive) model in the DDSM data is 0.891/0.900 (MLO/CC view). AUC for the MMassDx (descriptor) model in the MM data is 0.862 and AUC for the MMassDx (inclusive) model in the MM data is 0.900. In all scenarios, MMassDx performs significantly better than clinical performance, P < 0.05 each. The authors furthermore demonstrate that the MMassDx algorithm systematically underestimates the risk of malignancy in the DDSM and MM datasets, especially when low probabilities of malignancy are assigned. The authors' results reveal that the MMassDx algorithms have good discriminatory performance but less accurate calibration when tested on two independent validation datasets. Improvement in calibration and testing in a prospective clinical population will be important steps in the pursuit of translation of these algorithms to the clinic.
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Prominent feature extraction for review analysis: an empirical study
NASA Astrophysics Data System (ADS)
Agarwal, Basant; Mittal, Namita
2016-05-01
Sentiment analysis (SA) research has increased tremendously in recent times. SA aims to determine the sentiment orientation of a given text into positive or negative polarity. Motivation for SA research is the need for the industry to know the opinion of the users about their product from online portals, blogs, discussion boards and reviews and so on. Efficient features need to be extracted for machine-learning algorithm for better sentiment classification. In this paper, initially various features are extracted such as unigrams, bi-grams and dependency features from the text. In addition, new bi-tagged features are also extracted that conform to predefined part-of-speech patterns. Furthermore, various composite features are created using these features. Information gain (IG) and minimum redundancy maximum relevancy (mRMR) feature selection methods are used to eliminate the noisy and irrelevant features from the feature vector. Finally, machine-learning algorithms are used for classifying the review document into positive or negative class. Effects of different categories of features are investigated on four standard data-sets, namely, movie review and product (book, DVD and electronics) review data-sets. Experimental results show that composite features created from prominent features of unigram and bi-tagged features perform better than other features for sentiment classification. mRMR is a better feature selection method as compared with IG for sentiment classification. Boolean Multinomial Naïve Bayes) algorithm performs better than support vector machine classifier for SA in terms of accuracy and execution time.
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Chi-square-based scoring function for categorization of MEDLINE citations.
Kastrin, A; Peterlin, B; Hristovski, D
2010-01-01
Text categorization has been used in biomedical informatics for identifying documents containing relevant topics of interest. We developed a simple method that uses a chi-square-based scoring function to determine the likelihood of MEDLINE citations containing genetic relevant topic. Our procedure requires construction of a genetic and a nongenetic domain document corpus. We used MeSH descriptors assigned to MEDLINE citations for this categorization task. We compared frequencies of MeSH descriptors between two corpora applying chi-square test. A MeSH descriptor was considered to be a positive indicator if its relative observed frequency in the genetic domain corpus was greater than its relative observed frequency in the nongenetic domain corpus. The output of the proposed method is a list of scores for all the citations, with the highest score given to those citations containing MeSH descriptors typical for the genetic domain. Validation was done on a set of 734 manually annotated MEDLINE citations. It achieved predictive accuracy of 0.87 with 0.69 recall and 0.64 precision. We evaluated the method by comparing it to three machine-learning algorithms (support vector machines, decision trees, naïve Bayes). Although the differences were not statistically significantly different, results showed that our chi-square scoring performs as good as compared machine-learning algorithms. We suggest that the chi-square scoring is an effective solution to help categorize MEDLINE citations. The algorithm is implemented in the BITOLA literature-based discovery support system as a preprocessor for gene symbol disambiguation process.
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Fast-SG: an alignment-free algorithm for hybrid assembly.
Di Genova, Alex; Ruz, Gonzalo A; Sagot, Marie-France; Maass, Alejandro
2018-05-01
Long-read sequencing technologies are the ultimate solution for genome repeats, allowing near reference-level reconstructions of large genomes. However, long-read de novo assembly pipelines are computationally intense and require a considerable amount of coverage, thereby hindering their broad application to the assembly of large genomes. Alternatively, hybrid assembly methods that combine short- and long-read sequencing technologies can reduce the time and cost required to produce de novo assemblies of large genomes. Here, we propose a new method, called Fast-SG, that uses a new ultrafast alignment-free algorithm specifically designed for constructing a scaffolding graph using light-weight data structures. Fast-SG can construct the graph from either short or long reads. This allows the reuse of efficient algorithms designed for short-read data and permits the definition of novel modular hybrid assembly pipelines. Using comprehensive standard datasets and benchmarks, we show how Fast-SG outperforms the state-of-the-art short-read aligners when building the scaffoldinggraph and can be used to extract linking information from either raw or error-corrected long reads. We also show how a hybrid assembly approach using Fast-SG with shallow long-read coverage (5X) and moderate computational resources can produce long-range and accurate reconstructions of the genomes of Arabidopsis thaliana (Ler-0) and human (NA12878). Fast-SG opens a door to achieve accurate hybrid long-range reconstructions of large genomes with low effort, high portability, and low cost.
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NASA Astrophysics Data System (ADS)
Cordero, M. J.; Hénault-Brunet, V.; Pilachowski, C. A.; Balbinot, E.; Johnson, C. I.; Varri, A. L.
2017-03-01
We use radial velocities from spectra of giants obtained with the WIYN telescope, coupled with existing chemical abundance measurements of Na and O for the same stars, to probe the presence of kinematic differences among the multiple populations of the globular cluster (GC) M13. To characterize the kinematics of various chemical subsamples, we introduce a method using Bayesian inference along with a Markov chain Monte Carlo algorithm to fit a six-parameter kinematic model (including rotation) to these subsamples. We find that the so-called extreme population (Na-enhanced and extremely O-depleted) exhibits faster rotation around the centre of the cluster than the other cluster stars, in particular, when compared with the dominant `intermediate' population (moderately Na-enhanced and O-depleted). The most likely difference between the rotational amplitude of this extreme population and that of the intermediate population is found to be ˜4 km s-1 , with a 98.4 per cent probability that the rotational amplitude of the extreme population is larger than that of the intermediate population. We argue that the observed difference in rotational amplitudes, obtained when splitting subsamples according to their chemistry, is not a product of the long-term dynamical evolution of the cluster, but more likely a surviving feature imprinted early in the formation history of this GC and its multiple populations. We also find an agreement (within uncertainties) in the inferred position angle of the rotation axis of the different subpopulations considered. We discuss the constraints that these results may place on various formation scenarios.
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A new computational strategy for predicting essential genes.
Cheng, Jian; Wu, Wenwu; Zhang, Yinwen; Li, Xiangchen; Jiang, Xiaoqian; Wei, Gehong; Tao, Shiheng
2013-12-21
Determination of the minimum gene set for cellular life is one of the central goals in biology. Genome-wide essential gene identification has progressed rapidly in certain bacterial species; however, it remains difficult to achieve in most eukaryotic species. Several computational models have recently been developed to integrate gene features and used as alternatives to transfer gene essentiality annotations between organisms. We first collected features that were widely used by previous predictive models and assessed the relationships between gene features and gene essentiality using a stepwise regression model. We found two issues that could significantly reduce model accuracy: (i) the effect of multicollinearity among gene features and (ii) the diverse and even contrasting correlations between gene features and gene essentiality existing within and among different species. To address these issues, we developed a novel model called feature-based weighted Naïve Bayes model (FWM), which is based on Naïve Bayes classifiers, logistic regression, and genetic algorithm. The proposed model assesses features and filters out the effects of multicollinearity and diversity. The performance of FWM was compared with other popular models, such as support vector machine, Naïve Bayes model, and logistic regression model, by applying FWM to reciprocally predict essential genes among and within 21 species. Our results showed that FWM significantly improves the accuracy and robustness of essential gene prediction. FWM can remarkably improve the accuracy of essential gene prediction and may be used as an alternative method for other classification work. This method can contribute substantially to the knowledge of the minimum gene sets required for living organisms and the discovery of new drug targets.
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Alici, Ferizan; Buerkle, Bernd; Tempfer, Clemens B
2014-07-01
To describe the performance curve of hysteroscopy-naïve probands repeatedly working through a surgery algorithm on a hysteroscopy trainer. We prospectively recruited medical students to a 30min demonstration session teaching a standardized surgery algorithm. Subjects subsequently performed three training courses immediately after training (T1) and after 24h (T2) and 48h (T3). Skills were recorded with a 20-item Objective Structured Assessment of Technical Skills (OSATS) at T1, T2, and T3. The presence of a sustained OSATS score improvement from T1 to T3 was the primary outcome. Performance time (PT) and self assessment (SA) were secondary outcomes. Statistics were performed using paired T-test and multiple linear regression analysis. 92 subjects were included. OSATS scores significantly improved over time from T1 to T2 (15.21±1.95 vs. 16.02±2.06, respectively; p<0.0001) and from T2 to T3 (16.02±2.06 vs. 16.95±1.61, respectively; p<0.0001). The secondary outcomes PT (414±119s vs. 357±88s vs. 304±91s; p<0.0001) and SA (3.02±0.85 vs. 3.80±0.76 vs. 4.41±0.67; p<0.0001) also showed an improvement over time with quicker performance and higher confidence. SA, but not PT demonstrated construct validity. In a multiple linear regression analysis, gender (odds ratio (OR) 0.96; 95% confidence interval (CI) 0.35-2.71; p=0.9) did not independently influence the likelihood of OSATS score improvement. In a hysteroscopy-naïve population, there is a continuous and sustained improvement of surgical proficiency and confidence after multiple training courses on a hysteroscopy trainer. Serial hysteroscopy trainings may be helpful for teaching hysteroscopy skills. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Byers, J. M.; Doctor, K.
2017-12-01
A common application of the satellite and airborne acquired hyperspectral imagery in the visible and NIR spectrum is the assessment of vegetation. Various absorption features of plants related to both water and chlorophyll content can be used to measure the vigor and access to underlying water sources of the vegetation. The typical strategy is to form hand-crafted features from the hyperspectral data cube by selecting two wavelengths to form difference or ratio images in the pixel space. The new image attempts to provide greater contrast for some feature of the vegetation. The Normalized Difference Vegetation Index (NDVI) is a widely used example formed from the ratio of differences and sums at two different wavelengths. There are dozens of these indices that are ostensibly formed using insights about the underlying physics of the spectral absorption with claims to efficacy in representing various properties of vegetation. In the language of machine learning these vegetation indices are features that can be used as a useful data representation within an algorithm. In this work we use a powerful approach from machine learning, probabilistic graphical models (PGM), to balance the competing needs of using existing hydrological classifications of terrain while finding statistically reliable features within hyperspectral data for identifying the generative process of the data. The algorithm in its simplest form is called a Naïve Bayes (NB) classifier and can be constructed in a data-driven estimation procedure of the conditional probability distributions that form the PGM. The Naïve Bayes model assumes that all vegetation indices (VI) are independent of one another given the hydrological class label. We seek to test its validity in a pilot study of detecting subsurface water flow pathways from VI. A more sophisticated PGM will also be explored called a tree-augmented NB that accounts for the probabilistic dependence between VI features. This methodology provides a general approach for classifying hydrological structures from hyperspectral data.
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Single-Photon Computed Tomography With Large Position-Sensitive Phototubes*
NASA Astrophysics Data System (ADS)
Feldmann, John; Ranck, Amoreena; Saunders, Robert S.; Welsh, Robert E.; Bradley, Eric L.; Saha, Margaret S.; Kross, Brian; Majewski, Stan; Popov, Vladimir; Weisenberger, Andrew G.; Wojcik, Randolph
2000-10-01
Position-sensitive photomultiplier tubes (PSPMTs) coupled to pixelated CsI(Tl) scintillators have been used with parallel-hole collimators to view the metabolism in small animals of radiopharmaceuticals tagged with ^125I. We report here our preliminary results analyzed using a tomography program^1 written in IDL programming language. The PSPMTs are mounted on a rotating gantry so as to view the subject animal from any azimuth. Preliminary results to test the tomography algorithm have been obtained by placing a variety of plastic mouse-brain phantoms (loaded with Na^125I) in front of one of the detectors and rotating the phantom in steps through 360 degrees. Results of this simulation taken with a variety of collimator hole sizes will be compared and discussed. Extentions of this technique to the use of very small PSPMTs (Hamamatsu M-64) which are capable of a very close approach to those parts of the animal of greatest interest will be described. *Supported in part by The Department of Energy, The National Science Foundation, The American Diabetes Association, The Howard Hughes Foundation and The Jeffress Trust. 1. Tomography algorithm kindly provided by Dr. S. Meikle of The Royal Prince Albert Hospital, Sydney, Australia
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A comparison between skeleton and bounding box models for falling direction recognition
NASA Astrophysics Data System (ADS)
Narupiyakul, Lalita; Srisrisawang, Nitikorn
2017-12-01
Falling is an injury that can lead to a serious medical condition in every range of the age of people. However, in the case of elderly, the risk of serious injury is much higher. Due to the fact that one way of preventing serious injury is to treat the fallen person as soon as possible, several works attempted to implement different algorithms to recognize the fall. Our work compares the performance of two models based on features extraction: (i) Body joint data (Skeleton Data) which are the joint's positions in 3 axes and (ii) Bounding box (Box-size Data) covering all body joints. Machine learning algorithms that were chosen are Decision Tree (DT), Naïve Bayes (NB), K-nearest neighbors (KNN), Linear discriminant analysis (LDA), Voting Classification (VC), and Gradient boosting (GB). The results illustrate that the models trained with Skeleton data are performed far better than those trained with Box-size data (with an average accuracy of 94-81% and 80-75%, respectively). KNN shows the best performance in both Body joint model and Bounding box model. In conclusion, KNN with Body joint model performs the best among the others.
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NASA Astrophysics Data System (ADS)
Xie, S.; Protat, A.; Zhao, C.
2013-12-01
One primary goal of the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program is to obtain and retrieve cloud microphysical properties from detailed cloud observations using ground-based active and passive remote sensors. However, there is large uncertainty in the retrieved cloud property products. Studies have shown that the uncertainty could arise from instrument limitations, measurement errors, sampling errors, retrieval algorithm deficiencies in assumptions, as well as inconsistent input data and constraints used by different algorithms. To quantify the uncertainty in cloud retrievals, a scientific focus group, Quantification of Uncertainties In Cloud Retrievals (QUICR), was recently created by the DOE Atmospheric System Research (ASR) program. This talk will provide an overview of the recent research activities conducted within QUICR and discuss its current collaborations with the European cloud retrieval community and future plans. The goal of QUICR is to develop a methodology for characterizing and quantifying uncertainties in current and future ARM cloud retrievals. The Work at LLNL was performed under the auspices of the U. S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research by Lawrence Livermore National Laboratory under contract No. DE-AC52-07NA27344. LLNL-ABS-641258.
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Identification of metal ion binding sites based on amino acid sequences
Cao, Xiaoyong; Zhang, Xiaojin; Gao, Sujuan; Ding, Changjiang; Feng, Yonge; Bao, Weihua
2017-01-01
The identification of metal ion binding sites is important for protein function annotation and the design of new drug molecules. This study presents an effective method of analyzing and identifying the binding residues of metal ions based solely on sequence information. Ten metal ions were extracted from the BioLip database: Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+ and Co2+. The analysis showed that Zn2+, Cu2+, Fe2+, Fe3+, and Co2+ were sensitive to the conservation of amino acids at binding sites, and promising results can be achieved using the Position Weight Scoring Matrix algorithm, with an accuracy of over 79.9% and a Matthews correlation coefficient of over 0.6. The binding sites of other metals can also be accurately identified using the Support Vector Machine algorithm with multifeature parameters as input. In addition, we found that Ca2+ was insensitive to hydrophobicity and hydrophilicity information and Mn2+ was insensitive to polarization charge information. An online server was constructed based on the framework of the proposed method and is freely available at http://60.31.198.140:8081/metal/HomePage/HomePage.html. PMID:28854211
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B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis
Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar
2012-01-01
The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187
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Identification of metal ion binding sites based on amino acid sequences.
Cao, Xiaoyong; Hu, Xiuzhen; Zhang, Xiaojin; Gao, Sujuan; Ding, Changjiang; Feng, Yonge; Bao, Weihua
2017-01-01
The identification of metal ion binding sites is important for protein function annotation and the design of new drug molecules. This study presents an effective method of analyzing and identifying the binding residues of metal ions based solely on sequence information. Ten metal ions were extracted from the BioLip database: Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+ and Co2+. The analysis showed that Zn2+, Cu2+, Fe2+, Fe3+, and Co2+ were sensitive to the conservation of amino acids at binding sites, and promising results can be achieved using the Position Weight Scoring Matrix algorithm, with an accuracy of over 79.9% and a Matthews correlation coefficient of over 0.6. The binding sites of other metals can also be accurately identified using the Support Vector Machine algorithm with multifeature parameters as input. In addition, we found that Ca2+ was insensitive to hydrophobicity and hydrophilicity information and Mn2+ was insensitive to polarization charge information. An online server was constructed based on the framework of the proposed method and is freely available at http://60.31.198.140:8081/metal/HomePage/HomePage.html.
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Detecting Diseases in Medical Prescriptions Using Data Mining Tools and Combining Techniques.
Teimouri, Mehdi; Farzadfar, Farshad; Soudi Alamdari, Mahsa; Hashemi-Meshkini, Amir; Adibi Alamdari, Parisa; Rezaei-Darzi, Ehsan; Varmaghani, Mehdi; Zeynalabedini, Aysan
2016-01-01
Data about the prevalence of communicable and non-communicable diseases, as one of the most important categories of epidemiological data, is used for interpreting health status of communities. This study aims to calculate the prevalence of outpatient diseases through the characterization of outpatient prescriptions. The data used in this study is collected from 1412 prescriptions for various types of diseases from which we have focused on the identification of ten diseases. In this study, data mining tools are used to identify diseases for which prescriptions are written. In order to evaluate the performances of these methods, we compare the results with Naïve method. Then, combining methods are used to improve the results. Results showed that Support Vector Machine, with an accuracy of 95.32%, shows better performance than the other methods. The result of Naive method, with an accuracy of 67.71%, is 20% worse than Nearest Neighbor method which has the lowest level of accuracy among the other classification algorithms. The results indicate that the implementation of data mining algorithms resulted in a good performance in characterization of outpatient diseases. These results can help to choose appropriate methods for the classification of prescriptions in larger scales.
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NASA Astrophysics Data System (ADS)
Wan, Bo; Zhang, Xue-Ying; Chen, Liang; Ge, Hong-Lin; Ma, Fei; Zhang, Hong-Bin; Ju, Yong-Qin; Zhang, Yan-Bin; Li, Yan-Yan; Xu, Xiao-Wei
2015-11-01
A digital pulse shape discrimination system based on a programmable module NI-5772 has been established and tested with an EJ-301 liquid scintillation detector. The module was operated by running programs developed in LabVIEW, with a sampling frequency up to 1.6 GS/s. Standard gamma sources 22Na, 137Cs and 60Co were used to calibrate the EJ-301 liquid scintillation detector, and the gamma response function was obtained. Digital algorithms for the charge comparison method and zero-crossing method have been developed. The experimental results show that both digital signal processing (DSP) algorithms can discriminate neutrons from γ-rays. Moreover, the zero-crossing method shows better n-γ discrimination at 80 keVee and lower, whereas the charge comparison method gives better results at higher thresholds. In addition, the figure-of-merit (FOM) for detectors of two different dimensions were extracted at 9 energy thresholds, and it was found that the smaller detector presented better n-γ separation for fission neutrons. Supported by National Natural Science Foundation of China (91226107, 11305229) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA03030300)
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NASA Astrophysics Data System (ADS)
Dufaux, Frederic
2011-06-01
The issue of privacy in video surveillance has drawn a lot of interest lately. However, thorough performance analysis and validation is still lacking, especially regarding the fulfillment of privacy-related requirements. In this paper, we first review recent Privacy Enabling Technologies (PET). Next, we discuss pertinent evaluation criteria for effective privacy protection. We then put forward a framework to assess the capacity of PET solutions to hide distinguishing facial information and to conceal identity. We conduct comprehensive and rigorous experiments to evaluate the performance of face recognition algorithms applied to images altered by PET. Results show the ineffectiveness of naïve PET such as pixelization and blur. Conversely, they demonstrate the effectiveness of more sophisticated scrambling techniques to foil face recognition.
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Unattended Sensor System With CLYC Detectors
NASA Astrophysics Data System (ADS)
Myjak, Mitchell J.; Becker, Eric M.; Gilbert, Andrew J.; Hoff, Jonathan E.; Knudson, Christa K.; Landgren, Peter C.; Lee, Samantha F.; McDonald, Benjamin S.; Pfund, David M.; Redding, Rebecca L.; Smart, John E.; Taubman, Matthew S.; Torres-Torres, Carlos R.; Wiseman, Clinton G.
2016-06-01
We have developed an unattended sensor for detecting anomalous radiation sources. The system combines several technologies to reduce size and weight, increase battery lifetime, and improve decision-making capabilities. Sixteen Cs2LiYCl6:Ce (CLYC) scintillators allow for gamma-ray spectroscopy and neutron detection in the same volume. Low-power electronics for readout, high voltage bias, and digital processing reduce the total operating power to 1.7 W. Computationally efficient analysis algorithms perform spectral anomaly detection and isotope identification. When an alarm occurs, the system transmits alarm information over a cellular modem. In this paper, we describe the overall design of the unattended sensor, present characterization results, and compare the performance to stock NaI:Tl and 3He detectors.
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Unattended Sensor System With CLYC Detectors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Myjak, Mitchell J.; Becker, Eric M.; Gilbert, Andrew J.
2016-06-01
We have developed a next-generation unattended sensor for detecting anomalous radiation sources. The system combines several technologies to reduce size and weight, increase battery lifetime, and improve decision-making capabilities. Sixteen Cs2LiYCl6:Ce (CLYC) scintillators allow for gamma-ray spectroscopy and neutron detection in the same volume. Low-power electronics for readout, high voltage bias, and digital processing reduce the total operating power to 1.3 W. Computationally efficient analysis algorithms perform spectral anomaly detection and isotope identification. When an alarm occurs, the system transmits alarm information over a cellular modem. In this paper, we describe the overall design of the unattended sensor, present characterizationmore » results, and compare the performance to stock NaI:Tl and 3He detectors.« less
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A machine learning-based framework to identify type 2 diabetes through electronic health records
Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You
2016-01-01
Objective To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. Materials and methods We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. Results We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Discussion Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature engineering to loosen such selection criteria to achieve a high identification rate of cases and controls. Conclusions Our proposed framework demonstrates a more accurate and efficient approach for identifying subjects with and without T2DM from EHR. PMID:27919371
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On avoided words, absent words, and their application to biological sequence analysis.
Almirantis, Yannis; Charalampopoulos, Panagiotis; Gao, Jia; Iliopoulos, Costas S; Mohamed, Manal; Pissis, Solon P; Polychronopoulos, Dimitris
2017-01-01
The deviation of the observed frequency of a word w from its expected frequency in a given sequence x is used to determine whether or not the word is avoided . This concept is particularly useful in DNA linguistic analysis. The value of the deviation of w , denoted by [Formula: see text], effectively characterises the extent of a word by its edge contrast in the context in which it occurs. A word w of length [Formula: see text] is a [Formula: see text]-avoided word in x if [Formula: see text], for a given threshold [Formula: see text]. Notice that such a word may be completely absent from x . Hence, computing all such words naïvely can be a very time-consuming procedure, in particular for large k . In this article, we propose an [Formula: see text]-time and [Formula: see text]-space algorithm to compute all [Formula: see text]-avoided words of length k in a given sequence of length n over a fixed-sized alphabet. We also present a time-optimal [Formula: see text]-time algorithm to compute all [Formula: see text]-avoided words (of any length) in a sequence of length n over an integer alphabet of size [Formula: see text]. In addition, we provide a tight asymptotic upper bound for the number of [Formula: see text]-avoided words over an integer alphabet and the expected length of the longest one. We make available an implementation of our algorithm. Experimental results, using both real and synthetic data, show the efficiency and applicability of our implementation in biological sequence analysis. The systematic search for avoided words is particularly useful for biological sequence analysis. We present a linear-time and linear-space algorithm for the computation of avoided words of length k in a given sequence x . We suggest a modification to this algorithm so that it computes all avoided words of x , irrespective of their length, within the same time complexity. We also present combinatorial results with regards to avoided words and absent words.
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A machine learning-based framework to identify type 2 diabetes through electronic health records.
Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You
2017-01-01
To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature engineering to loosen such selection criteria to achieve a high identification rate of cases and controls. Our proposed framework demonstrates a more accurate and efficient approach for identifying subjects with and without T2DM from EHR. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Exact algorithms for haplotype assembly from whole-genome sequence data.
Chen, Zhi-Zhong; Deng, Fei; Wang, Lusheng
2013-08-15
Haplotypes play a crucial role in genetic analysis and have many applications such as gene disease diagnoses, association studies, ancestry inference and so forth. The development of DNA sequencing technologies makes it possible to obtain haplotypes from a set of aligned reads originated from both copies of a chromosome of a single individual. This approach is often known as haplotype assembly. Exact algorithms that can give optimal solutions to the haplotype assembly problem are highly demanded. Unfortunately, previous algorithms for this problem either fail to output optimal solutions or take too long time even executed on a PC cluster. We develop an approach to finding optimal solutions for the haplotype assembly problem under the minimum-error-correction (MEC) model. Most of the previous approaches assume that the columns in the input matrix correspond to (putative) heterozygous sites. This all-heterozygous assumption is correct for most columns, but it may be incorrect for a small number of columns. In this article, we consider the MEC model with or without the all-heterozygous assumption. In our approach, we first use new methods to decompose the input read matrix into small independent blocks and then model the problem for each block as an integer linear programming problem, which is then solved by an integer linear programming solver. We have tested our program on a single PC [a Linux (x64) desktop PC with i7-3960X CPU], using the filtered HuRef and the NA 12878 datasets (after applying some variant calling methods). With the all-heterozygous assumption, our approach can optimally solve the whole HuRef data set within a total time of 31 h (26 h for the most difficult block of the 15th chromosome and only 5 h for the other blocks). To our knowledge, this is the first time that MEC optimal solutions are completely obtained for the filtered HuRef dataset. Moreover, in the general case (without the all-heterozygous assumption), for the HuRef dataset our approach can optimally solve all the chromosomes except the most difficult block in chromosome 15 within a total time of 12 days. For both of the HuRef and NA12878 datasets, the optimal costs in the general case are sometimes much smaller than those in the all-heterozygous case. This implies that some columns in the input matrix (after applying certain variant calling methods) still correspond to false-heterozygous sites. Our program, the optimal solutions found for the HuRef dataset available at http://rnc.r.dendai.ac.jp/hapAssembly.html.
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Mapping the receptor site for alpha-scorpion toxins on a Na+ channel voltage sensor.
Wang, Jinti; Yarov-Yarovoy, Vladimir; Kahn, Roy; Gordon, Dalia; Gurevitz, Michael; Scheuer, Todd; Catterall, William A
2011-09-13
The α-scorpions toxins bind to the resting state of Na(+) channels and inhibit fast inactivation by interaction with a receptor site formed by domains I and IV. Mutants T1560A, F1610A, and E1613A in domain IV had lower affinities for Leiurus quinquestriatus hebraeus toxin II (LqhII), and mutant E1613R had ~73-fold lower affinity. Toxin dissociation was accelerated by depolarization and increased by these mutations, whereas association rates at negative membrane potentials were not changed. These results indicate that Thr1560 in the S1-S2 loop, Phe1610 in the S3 segment, and Glu1613 in the S3-S4 loop in domain IV participate in toxin binding. T393A in the SS2-S6 loop in domain I also had lower affinity for LqhII, indicating that this extracellular loop may form a secondary component of the receptor site. Analysis with the Rosetta-Membrane algorithm resulted in a model of LqhII binding to the voltage sensor in a resting state, in which amino acid residues in an extracellular cleft formed by the S1-S2 and S3-S4 loops in domain IV interact with two faces of the wedge-shaped LqhII molecule. The conserved gating charges in the S4 segment are in an inward position and form ion pairs with negatively charged amino acid residues in the S2 and S3 segments of the voltage sensor. This model defines the structure of the resting state of a voltage sensor of Na(+) channels and reveals its mode of interaction with a gating modifier toxin.
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Level Zero Trigger Processor for the ultra rare kaon decay experiment: NA62
NASA Astrophysics Data System (ADS)
Soldi, Dario; Chiozzi, S.; Gamberini, E.; Gianoli, A.; Mila, G.; Neri, I.; Petrucci, F.
2017-02-01
The NA62 experiment is designed to measure the (ultra-)rare decay K+ →π+ ν ν bar branching ratio with a precision of ∼ 10 % at the CERN Super Proton Synchrotron (SPS). The L0 Trigger Processor (L0TP) is the lowest level system of the trigger chain. It is hardware implemented using programmable logic. The architecture of the L0TP is completely new for a high energy physics experiment. It is fully digital, based on a standard gigabit ethernet communication between detectors and L0TP Board. The L0TP Board is a commercial development board, Terasic DE4, mounting an Altera Stratix IV FPGA. The primitives generated by sub-detectors are sent asynchronously using the UDP protocol to the L0TP during the entire beam spill period (about 5 seconds). The L0TP realigns in time the primitives coming from 7 different sources and manages the information of the time plus all the characteristics of the event as energy, multiplicity and position of hits in order to select good events with a comparison with preset masks. It should guarantee a maximum latency of 1 ms. The maximum input rate is 10 MHz for each sub-detector, while the design maximum output trigger rate is 1 MHz. A complete trigger-less parasitic acquisition of the primitives is possible using mirroring switches to monitor the L0 behavior. A first version of the L0TP was commissioned during the 2014 NA62 pilot run and it is used in the current data taking. A description of the trigger algorithm is here presented.
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Modelling the acid/base 1H NMR chemical shift limits of metabolites in human urine.
Tredwell, Gregory D; Bundy, Jacob G; De Iorio, Maria; Ebbels, Timothy M D
2016-01-01
Despite the use of buffering agents the 1 H NMR spectra of biofluid samples in metabolic profiling investigations typically suffer from extensive peak frequency shifting between spectra. These chemical shift changes are mainly due to differences in pH and divalent metal ion concentrations between the samples. This frequency shifting results in a correspondence problem: it can be hard to register the same peak as belonging to the same molecule across multiple samples. The problem is especially acute for urine, which can have a wide range of ionic concentrations between different samples. To investigate the acid, base and metal ion dependent 1 H NMR chemical shift variations and limits of the main metabolites in a complex biological mixture. Urine samples from five different individuals were collected and pooled, and pre-treated with Chelex-100 ion exchange resin. Urine samples were either treated with either HCl or NaOH, or were supplemented with various concentrations of CaCl 2 , MgCl 2 , NaCl or KCl, and their 1 H NMR spectra were acquired. Nonlinear fitting was used to derive acid dissociation constants and acid and base chemical shift limits for peaks from 33 identified metabolites. Peak pH titration curves for a further 65 unidentified peaks were also obtained for future reference. Furthermore, the peak variations induced by the main metal ions present in urine, Na + , K + , Ca 2+ and Mg 2+ , were also measured. These data will be a valuable resource for 1 H NMR metabolite profiling experiments and for the development of automated metabolite alignment and identification algorithms for 1 H NMR spectra.
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Interference techniques in fluorescence microscopy
NASA Astrophysics Data System (ADS)
Dogan, Mehmet
We developed a set of interference-based optical microscopy techniques to study biological structures through nanometer-scale axial localization of fluorescent biomarkers. Spectral self-interference fluorescence microscopy (SSFM) utilizes interference of direct and reflected waves emitted from fluorescent molecules in the vicinity of planar reflectors to reveal the axial position of the molecules. A comprehensive calculation algorithm based on Green's function formalism is presented to verify the validity of approximations used in a far-field approach that describes the emission of fluorescent markers near interfaces. Using the validated model, theoretical limits of axial localization were determined with emphasis given to numerical aperture (NA) dependence of localization uncertainty. SSFM was experimentally demonstrated in conformational analysis of nucleoproteins. In particular, interaction between surface-tethered 75-mer double strand DNA and integration host factor (IHF) protein was probed on Si-SiO2 substrates by determining the axial position of fluorescent labels attached to the free ends of DNA molecules. Despite its sub-nanometer precision axial localization capability, SSFM lacks high lateral resolution due to the low-NA requirement for planar reflectors. We developed a second technique, 4Pi-SSFM, which improves the lateral resolution of a conventional SSFM system by an order of magnitude while achieving nanometer-scale axial localization precision. Using two opposing high-NA objectives, fluorescence signal is interferometrically collected and spectral interference pattern is recorded. Axial position of emitters is found from analysis of the spectra. The 4Pi-SSFM technique was experimentally demonstrated by determining the surface profiles of fabricated glass surfaces and outer membranes of Shigella, a type of Gram-negative bacteria. A further discussion is presented to localize surface O antigen, which is an important oligosaccharide structure in the virulence mechanism of the Gram-negative bacteria, including E. coli and Shigella.
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NASA Astrophysics Data System (ADS)
Wigdahl, J.; Agurto, C.; Murray, V.; Barriga, S.; Soliz, P.
2013-03-01
Diabetic retinopathy (DR) affects more than 4.4 million Americans age 40 and over. Automatic screening for DR has shown to be an efficient and cost-effective way to lower the burden on the healthcare system, by triaging diabetic patients and ensuring timely care for those presenting with DR. Several supervised algorithms have been developed to detect pathologies related to DR, but little work has been done in determining the size of the training set that optimizes an algorithm's performance. In this paper we analyze the effect of the training sample size on the performance of a top-down DR screening algorithm for different types of statistical classifiers. Results are based on partial least squares (PLS), support vector machines (SVM), k-nearest neighbor (kNN), and Naïve Bayes classifiers. Our dataset consisted of digital retinal images collected from a total of 745 cases (595 controls, 150 with DR). We varied the number of normal controls in the training set, while keeping the number of DR samples constant, and repeated the procedure 10 times using randomized training sets to avoid bias. Results show increasing performance in terms of area under the ROC curve (AUC) when the number of DR subjects in the training set increased, with similar trends for each of the classifiers. Of these, PLS and k-NN had the highest average AUC. Lower standard deviation and a flattening of the AUC curve gives evidence that there is a limit to the learning ability of the classifiers and an optimal number of cases to train on.
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Douglas, P K; Harris, Sam; Yuille, Alan; Cohen, Mark S
2011-05-15
Machine learning (ML) has become a popular tool for mining functional neuroimaging data, and there are now hopes of performing such analyses efficiently in real-time. Towards this goal, we compared accuracy of six different ML algorithms applied to neuroimaging data of persons engaged in a bivariate task, asserting their belief or disbelief of a variety of propositional statements. We performed unsupervised dimension reduction and automated feature extraction using independent component (IC) analysis and extracted IC time courses. Optimization of classification hyperparameters across each classifier occurred prior to assessment. Maximum accuracy was achieved at 92% for Random Forest, followed by 91% for AdaBoost, 89% for Naïve Bayes, 87% for a J48 decision tree, 86% for K*, and 84% for support vector machine. For real-time decoding applications, finding a parsimonious subset of diagnostic ICs might be useful. We used a forward search technique to sequentially add ranked ICs to the feature subspace. For the current data set, we determined that approximately six ICs represented a meaningful basis set for classification. We then projected these six IC spatial maps forward onto a later scanning session within subject. We then applied the optimized ML algorithms to these new data instances, and found that classification accuracy results were reproducible. Additionally, we compared our classification method to our previously published general linear model results on this same data set. The highest ranked IC spatial maps show similarity to brain regions associated with contrasts for belief > disbelief, and disbelief < belief. Copyright © 2010 Elsevier Inc. All rights reserved.
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Toward automated face detection in thermal and polarimetric thermal imagery
NASA Astrophysics Data System (ADS)
Gordon, Christopher; Acosta, Mark; Short, Nathan; Hu, Shuowen; Chan, Alex L.
2016-05-01
Visible spectrum face detection algorithms perform pretty reliably under controlled lighting conditions. However, variations in illumination and application of cosmetics can distort the features used by common face detectors, thereby degrade their detection performance. Thermal and polarimetric thermal facial imaging are relatively invariant to illumination and robust to the application of makeup, due to their measurement of emitted radiation instead of reflected light signals. The objective of this work is to evaluate a government off-the-shelf wavelet based naïve-Bayes face detection algorithm and a commercial off-the-shelf Viola-Jones cascade face detection algorithm on face imagery acquired in different spectral bands. New classifiers were trained using the Viola-Jones cascade object detection framework with preprocessed facial imagery. Preprocessing using Difference of Gaussians (DoG) filtering reduces the modality gap between facial signatures across the different spectral bands, thus enabling more correlated histogram of oriented gradients (HOG) features to be extracted from the preprocessed thermal and visible face images. Since the availability of training data is much more limited in the thermal spectrum than in the visible spectrum, it is not feasible to train a robust multi-modal face detector using thermal imagery alone. A large training dataset was constituted with DoG filtered visible and thermal imagery, which was subsequently used to generate a custom trained Viola-Jones detector. A 40% increase in face detection rate was achieved on a testing dataset, as compared to the performance of a pre-trained/baseline face detector. Insights gained in this research are valuable in the development of more robust multi-modal face detectors.
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Phage display peptide libraries: deviations from randomness and correctives
Ryvkin, Arie; Ashkenazy, Haim; Weiss-Ottolenghi, Yael; Piller, Chen; Pupko, Tal; Gershoni, Jonathan M
2018-01-01
Abstract Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications. PMID:29420788
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Cavaco-Silva, Joana; Abecasis, Ana; Miranda, Ana Cláudia; Poças, José; Narciso, Jorge; Águas, Maria João; Maltez, Fernando; Almeida, Isabel; Germano, Isabel; Diniz, António; Gonçalves, Maria de Fátima; Gomes, Perpétua; Cunha, Celso; Camacho, Ricardo Jorge
2014-01-01
To characterize the HIV-2 integrase gene polymorphisms and the pathways to resistance of HIV-2 patients failing a raltegravir-containing regimen, we studied 63 integrase strand transfer inhibitors (INSTI)-naïve patients, and 10 heavily pretreated patients exhibiting virological failure while receiving a salvage raltegravir-containing regimen. All patients were infected by HIV-2 group A. 61.4% of the integrase residues were conserved, including the catalytic motif residues. No INSTI-major resistance mutations were detected in the virus population from naïve patients, but two amino acids that are secondary resistance mutations to INSTIs in HIV-1 were observed. The 10 raltegravir-experienced patients exhibited resistance mutations via three main genetic pathways: N155H, Q148R, and eventually E92Q - T97A. The 155 pathway was preferentially used (7/10 patients). Other mutations associated to raltegravir resistance in HIV-1 were also observed in our HIV-2 population (V151I and D232N), along with several novel mutations previously unreported. Data retrieved from this study should help build a more robust HIV-2-specific algorithm for the genotypic interpretation of raltegravir resistance, and contribute to improve the clinical monitoring of HIV-2-infected patients.
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FPscope: a field-portable high-resolution microscope using a cellphone lens.
Dong, Siyuan; Guo, Kaikai; Nanda, Pariksheet; Shiradkar, Radhika; Zheng, Guoan
2014-10-01
The large consumer market has made cellphone lens modules available at low-cost and in high-quality. In a conventional cellphone camera, the lens module is used to demagnify the scene onto the image plane of the camera, where image sensor is located. In this work, we report a 3D-printed high-resolution Fourier ptychographic microscope, termed FPscope, which uses a cellphone lens in a reverse manner. In our platform, we replace the image sensor with sample specimens, and use the cellphone lens to project the magnified image to the detector. To supersede the diffraction limit of the lens module, we use an LED array to illuminate the sample from different incident angles and synthesize the acquired images using the Fourier ptychographic algorithm. As a demonstration, we use the reported platform to acquire high-resolution images of resolution target and biological specimens, with a maximum synthetic numerical aperture (NA) of 0.5. We also show that, the depth-of-focus of the reported platform is about 0.1 mm, orders of magnitude longer than that of a conventional microscope objective with a similar NA. The reported platform may enable healthcare accesses in low-resource settings. It can also be used to demonstrate the concept of computational optics for educational purposes.
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Gaye, M. M.; Valentine, S. J.; Hu, Y.; Mirjankar, N.; Hammoud, Z. T.; Mechref, Y.; Lavine, B. K.; Clemmer, D. E.
2012-01-01
Three disease phenotypes, Barrett’s esophagus (BE), high-grade dysplasia (HGD), esophageal adenocarcinoma (EAC), and a set of normal control (NC) serum samples are examined using a combination of ion mobility spectrometry (IMS), mass spectrometry (MS) and principal component analysis (PCA) techniques. Samples from a total of 136 individuals were examined, including: 7 characterized as BE, 12 as HGD, 56 as EAC and 61 as NC. In typical datasets it was possible to assign ~20 to 30 glycan ions based on MS measurements. Ion mobility distributions for these ions show multiple features. In some cases, such as the [S1H5N4+3Na]3+ and [S1F1H5N4+3Na]3+ glycan ions, the ratio of intensities of high-mobility features to low-mobility features vary significantly for different groups. The degree to which such variations in mobility profiles can be used to distinguish phenotypes is evaluated for eleven N-linked glycan ions. An outlier analysis on each sample class followed by an unsupervised PCA using a genetic algorithm for pattern recognition reveals that EAC samples are separated from NC samples based on 46 features originating from the 11-glycan composite IMS distribution. PMID:23126309
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Yang, Li-Bo; Zhan, Xiao-Bei; Zhu, Li; Gao, Min-Jie; Lin, Chi-Chung
2016-05-18
The production of erythritol by Yarrowia lipolytica from low-cost substitutable substrates for high yield was investigated. Crude glycerol, urea, and NaCl related to osmotic pressure were the most significant factors affecting erythritol production. An artificial neural network model and genetic algorithm were used to search the optimal composition of the significant factors and locate the resulting erythritol yield. Medium with 232.39 g/L crude glycerol, 1.57 g/L urea, and 31.03 g/L NaCl led to predictive maximum erythritol concentration of 110.7 g/L. The erythritol concentration improved from 50.4 g/L to 109.2 g/L with the optimized medium, which was reproducible. Erythritol fermentation kinetics were investigated in a batch system. Multistep fermentation kinetic models with hyperosmotic inhibitory effects were developed. The resulting mathematical equations provided a good description of temporal variations such as microbial growth (X), substrate consumption (S), and product formation (P) in erythritol fermentation. The accordingly derived model is the first reported model for fermentative erythritol production from glycerol, providing useful information to optimize the growth of Y. lipolytica and contributing visual description for the erythritol fermentation process under high osmotic pressure, as well as improvement of productivity and efficiency.
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Cavaco-Silva, Joana; Abecasis, Ana; Miranda, Ana Cláudia; Poças, José; Narciso, Jorge; Águas, Maria João; Maltez, Fernando; Almeida, Isabel; Germano, Isabel; Diniz, António; Gonçalves, Maria de Fátima; Gomes, Perpétua; Cunha, Celso; Camacho, Ricardo Jorge
2014-01-01
To characterize the HIV-2 integrase gene polymorphisms and the pathways to resistance of HIV-2 patients failing a raltegravir-containing regimen, we studied 63 integrase strand transfer inhibitors (INSTI)-naïve patients, and 10 heavily pretreated patients exhibiting virological failure while receiving a salvage raltegravir-containing regimen. All patients were infected by HIV-2 group A. 61.4% of the integrase residues were conserved, including the catalytic motif residues. No INSTI-major resistance mutations were detected in the virus population from naïve patients, but two amino acids that are secondary resistance mutations to INSTIs in HIV-1 were observed. The 10 raltegravir-experienced patients exhibited resistance mutations via three main genetic pathways: N155H, Q148R, and eventually E92Q - T97A. The 155 pathway was preferentially used (7/10 patients). Other mutations associated to raltegravir resistance in HIV-1 were also observed in our HIV-2 population (V151I and D232N), along with several novel mutations previously unreported. Data retrieved from this study should help build a more robust HIV-2-specific algorithm for the genotypic interpretation of raltegravir resistance, and contribute to improve the clinical monitoring of HIV-2-infected patients. PMID:24681625
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Circadian Rest-Activity Rhythm in Pediatric Type 1 Narcolepsy.
Filardi, Marco; Pizza, Fabio; Bruni, Oliviero; Natale, Vincenzo; Plazzi, Giuseppe
2016-06-01
Pediatric type 1 narcolepsy is often challenging to diagnose and remains largely undiagnosed. Excessive daytime sleepiness, disrupted nocturnal sleep, and a peculiar phenotype of cataplexy are the prominent features. The knowledge available about the regulation of circadian rhythms in affected children is scarce. This study compared circadian rest-activity rhythm and actigraphic estimated sleep measures of children with type 1 narcolepsy versus healthy controls. Twenty-two drug-naïve type 1 narcolepsy children and 21 age- and sex- matched controls were monitored for seven days during the school week by actigraphy. Circadian activity rhythms were analyzed through functional linear modeling; nocturnal and diurnal sleep measures were estimated from activity using a validated algorithm. Children with type 1 narcolepsy presented an altered rest-activity rhythm characterized by enhanced motor activity throughout the night and blunted activity in the first afternoon. No difference was found between children with type 1 narcolepsy and controls in the timing of the circadian phase. Actigraphic sleep measures showed good discriminant capabilities in assessing type 1 narcolepsy nycthemeral disruption. Actigraphy reliably renders the nycthemeral disruption typical of narcolepsy type 1 in drug-naïve children with recent disease onset, indicating the sensibility of actigraphic assessment in the diagnostic work-up of childhood narcolepsy type 1. © 2016 Associated Professional Sleep Societies, LLC.
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Novel Modeling of Combinatorial miRNA Targeting Identifies SNP with Potential Role in Bone Density
Coronnello, Claudia; Hartmaier, Ryan; Arora, Arshi; Huleihel, Luai; Pandit, Kusum V.; Bais, Abha S.; Butterworth, Michael; Kaminski, Naftali; Stormo, Gary D.; Oesterreich, Steffi; Benos, Panayiotis V.
2012-01-01
MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies. PMID:23284279
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Satellite skill in detecting extreme episodes in near-surface air quality
NASA Astrophysics Data System (ADS)
Ruiz, D. J.; Prather, M. J.
2017-12-01
Ozone (O3) contributes to ambient air pollution, adversely affecting public health, agriculture, and ecosystems. Reliable, long-term, densely distributed surface networks are required to establish the scale, intensity and repeatability of major pollution events (designated here in a climatological sense as air quality extremes, AQX as defined in Schnell's work). Regrettably, such networks are only available for North America (NA) and Europe (EU), which does not include many populated regions where the deaths associated with air pollution exposure are alarmingly high. Directly measuring surface pollutants from space without lidar is extremely difficult. Mapping of daily pollution events requires cross-track nadir scanners and these have limited sensitivity to surface O3 levels. This work examines several years of coincident surface and OMI satellite measurements over NA-EU, in combination with a chemistry-transport model (CTM) hindcast of that period to understand how the large-scale AQX episodes may extend into the free troposphere and thus be more amenable to satellite mapping. We show how extreme NA-EU episodes are measured from OMI and then look for such patterns over other polluted regions of the globe. We gather individual high-quality O3 surface site measurements from these other regions, to check on our satellite detection. Our approach with global satellite detection would avoid issues associated with regional variations in seasonality, chemical regime, data product biases; and it does not require defining a separate absolute threshold for each data product (surface site and satellite). This also enables coherent linking of the extreme events into large-scale pollution episodes whose magnitude evolves over 100's of km for several days. Tools used here include the UC Irvine CTM, which shows that much of the O3 surface variability is lost at heights above 2 km, but AQX local events are readily seen in a 0-3 km column average. The OMI data are taken from X. Liu's dataset using an improved algorithm for detection of tropospheric O3. Surface site observations outside NA and EU are taken from research stations where possible.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Gearhart, A; Peterson, T; Johnson, L
2015-06-15
Purpose: To evaluate the impact of the exceptional energy resolution of germanium detectors for preclinical SPECT in comparison to conventional detectors. Methods: A cylindrical water phantom was created in GATE with a spherical Tc-99m source in the center. Sixty-four projections over 360 degrees using a pinhole collimator were simulated. The same phantom was simulated using air instead of water to establish the true reconstructed voxel intensity without attenuation. Attenuation correction based on the Chang method was performed on MLEM reconstructed images from the water phantom to determine a quantitative measure of the effectiveness of the attenuation correction. Similarly, a NEMAmore » phantom was simulated, and the effectiveness of the attenuation correction was evaluated. Both simulations were carried out using both NaI detectors with an energy resolution of 10% FWHM and Ge detectors with an energy resolution of 1%. Results: Analysis shows that attenuation correction without scatter correction using germanium detectors can reconstruct a small spherical source to within 3.5%. Scatter analysis showed that for standard sized objects in a preclinical scanner, a NaI detector has a scatter-to-primary ratio between 7% and 12.5% compared to between 0.8% and 1.5% for a Ge detector. Preliminary results from line profiles through the NEMA phantom suggest that applying attenuation correction without scatter correction provides acceptable results for the Ge detectors but overestimates the phantom activity using NaI detectors. Due to the decreased scatter, we believe that the spillover ratio for the air and water cylinders in the NEMA phantom will be lower using germanium detectors compared to NaI detectors. Conclusion: This work indicates that the superior energy resolution of germanium detectors allows for less scattered photons to be included within the energy window compared to traditional SPECT detectors. This may allow for quantitative SPECT without implementing scatter correction, reducing uncertainties introduced by scatter correction algorithms. Funding provided by NIH/NIBIB grant R01EB013677; Todd Peterson, Ph.D., has had a research contract with PHDs Co., Knoxville, TN.« less
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Scherrer, A U; Hasse, B; von Wyl, V; Yerly, S; Böni, J; Bürgisser, P; Klimkait, T; Bucher, H C; Ledergerber, B; Günthard, H F
2009-11-01
Etravirine (ETV) is a novel nonnucleoside reverse transcriptase inhibitor (NNRTI) with reduced cross-resistance to first-generation NNRTIs, which has been primarily studied in randomized clinical trials and not in routine clinical settings. ETV resistance-associated mutations (RAMs) were investigated by analysing 6072 genotypic tests. The antiviral activity of ETV was predicted using different interpretation systems: International AIDS Society-USA (IAS-USA), Stanford, Rega and Agence Nationale de Recherches sur le Sida et les hépatites virales (ANRS). The prevalence of ETV RAMs was higher in NNRTI-exposed patients [44.9%, 95% confidence interval (CI) 41.0-48.9%] than in treatment-naïve patients (9.6%, 95% CI 8.5-10.7%). ETV RAMs in treatment-naïve patients mainly represent polymorphism, as prevalence estimates in genotypic tests for treatment-naïve patients with documented recent (<1 year) infection, who had acquired HIV before the introduction of NNRTIs, were almost identical (9.8%, 95% CI 3.3-21.4). Discontinuation of NNRTI treatment led to a marked drop in the detection of ETV RAMs, from 51.7% (95% CI 40.8-62.6%) to 34.5% (95% CI 24.6-45.4%, P=0.032). Differences in prevalence among subtypes were found for V90I and V179T (P<0.001). Estimates of restricted virological response to ETV varied among algorithms in patients with exposure to efavirenz (EFV)/nevirapine (NVP), ranging from 3.8% (95% CI 2.5-5.6%) for ANRS to 56.2% (95% CI 52.2-60.1%) for Stanford. The predicted activity of ETV decreased as the sensitivity of potential optimized background regimens decreased. The presence of major IAS-USA mutations (L100I, K101E/H/P and Y181C/I/V) reduced the treatment response at week 24. Most ETV RAMs in drug-naïve patients are polymorphisms rather than transmitted RAMs. Uncertainty regarding predictions of antiviral activity for ETV in NNRTI-treated patients remains high. The lowest activity was predicted for patients harbouring extensive multidrug-resistant viruses, thus limiting ETV use in those who are most in need.
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2012-01-01
Abstract In this study we report the prevalence of antiretroviral drug resistant HIV-1 genotypes of virus isolated from Djiboutian patients who failed first-line antiretroviral therapy (ART) and from ART naïve patients. Patients and methods A total of 35 blood samples from 16 patients who showed first-line ART failure (>1000 viral genome copies/ml) and 19 ART-naïve patients were collected in Djibouti from October 2009 to December 2009. Both the protease (PR) and reverse transcriptase (RT) genes were amplified and sequenced using National Agency for AIDS Research (ANRS) protocols. The Stanford HIV database algorithm was used for interpretation of resistance data and genotyping. Results Among the 16 patients with first-line ART failure, nine (56.2%) showed reverse transcriptase inhibitor-resistant HIV-1 strains: two (12.5%) were resistant to nucleoside (NRTI), one (6.25%) to non-nucleoside (NNRTI) reverse transcriptase inhibitors, and six (37.5%) to both. Analysis of the DNA sequencing data indicated that the most common mutations conferring drug resistance were M184V (38%) for NRTI and K103N (25%) for NNRTI. Only NRTI primary mutations K101Q, K103N and the PI minor mutation L10V were found in ART naïve individuals. No protease inhibitor resistant strains were detected. In our study, we found no detectable resistance in ∼ 44% of all patients who experienced therapeutic failure which was explained by low compliance, co-infection with tuberculosis and malnutrition. Genotyping revealed that 65.7% of samples were infected with subtype C, 20% with CRF02_AG, 8.5% with B, 2.9% with CRF02_AG/C and 2.9% with K/C. Conclusion The results of this first study about drug resistance mutations in first-line ART failures show the importance of performing drug resistance mutation test which guides the choice of a second-line regimen. This will improve the management of HIV-infected Djiboutian patients. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2051206212753973 PMID:23044036
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Elmi Abar, Aden; Jlizi, Asma; Darar, Houssein Youssouf; Kacem, Mohamed Ali Ben Hadj; Slim, Amine
2012-10-08
In this study we report the prevalence of antiretroviral drug resistant HIV-1 genotypes of virus isolated from Djiboutian patients who failed first-line antiretroviral therapy (ART) and from ART naïve patients. A total of 35 blood samples from 16 patients who showed first-line ART failure (>1000 viral genome copies/ml) and 19 ART-naïve patients were collected in Djibouti from October 2009 to December 2009. Both the protease (PR) and reverse transcriptase (RT) genes were amplified and sequenced using National Agency for AIDS Research (ANRS) protocols. The Stanford HIV database algorithm was used for interpretation of resistance data and genotyping. Among the 16 patients with first-line ART failure, nine (56.2%) showed reverse transcriptase inhibitor-resistant HIV-1 strains: two (12.5%) were resistant to nucleoside (NRTI), one (6.25%) to non-nucleoside (NNRTI) reverse transcriptase inhibitors, and six (37.5%) to both. Analysis of the DNA sequencing data indicated that the most common mutations conferring drug resistance were M184V (38%) for NRTI and K103N (25%) for NNRTI. Only NRTI primary mutations K101Q, K103N and the PI minor mutation L10V were found in ART naïve individuals. No protease inhibitor resistant strains were detected. In our study, we found no detectable resistance in ∼ 44% of all patients who experienced therapeutic failure which was explained by low compliance, co-infection with tuberculosis and malnutrition. Genotyping revealed that 65.7% of samples were infected with subtype C, 20% with CRF02_AG, 8.5% with B, 2.9% with CRF02_AG/C and 2.9% with K/C. The results of this first study about drug resistance mutations in first-line ART failures show the importance of performing drug resistance mutation test which guides the choice of a second-line regimen. This will improve the management of HIV-infected Djiboutian patients. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2051206212753973.
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A Comparative Analysis of Pitch Detection Methods Under the Influence of Different Noise Conditions.
Sukhostat, Lyudmila; Imamverdiyev, Yadigar
2015-07-01
Pitch is one of the most important components in various speech processing systems. The aim of this study was to evaluate different pitch detection methods in terms of various noise conditions. Prospective study. For evaluation of pitch detection algorithms, time-domain, frequency-domain, and hybrid methods were considered by using Keele and CSTR speech databases. Each of them has its own advantages and disadvantages. Experiments have shown that BaNa method achieves the highest pitch detection accuracy. The development of methods for pitch detection, which are robust to additive noise at different signal-to-noise ratio, is an important field of research with many opportunities for enhancement the modern methods. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
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Linguistic Phylogenies Support Back-Migration from Beringia to Asia
Sicoli, Mark A.; Holton, Gary
2014-01-01
Recent arguments connecting Na-Dene languages of North America with Yeniseian languages of Siberia have been used to assert proof for the origin of Native Americans in central or western Asia. We apply phylogenetic methods to test support for this hypothesis against an alternative hypothesis that Yeniseian represents a back-migration to Asia from a Beringian ancestral population. We coded a linguistic dataset of typological features and used neighbor-joining network algorithms and Bayesian model comparison based on Bayes factors to test the fit between the data and the linguistic phylogenies modeling two dispersal hypotheses. Our results support that a Dene-Yeniseian connection more likely represents radiation out of Beringia with back-migration into central Asia than a migration from central or western Asia to North America. PMID:24621925
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Crystal structure and phase stability of tungsten borides
NASA Astrophysics Data System (ADS)
Li, Quan; Zhou, Dan; Ma, Yanming; Chen, Changfeng
2013-03-01
We address the longstanding and controversial issue of ground-state structures of technically important tungsten borides using a first-principles structural search method via a particle-swarm optimization (PSO) algorithm. We have explored a large set of stable chemical compositions (convex hull) and clarified the ground-state structures for a wide range of boron concentrations, including W2B, W3B2,WB,W2B3, WB2,W2B5, WB3, and WB4. We further assessed relative stability of various tungsten borides and compared the calculated results with previously reported experimental data. The phase diagram predicted by the presented calculations may serve as a useful guide for synthesis of a variety of tungsten borides. This work was supported by DOE Grant No. DE-FC52-06NA26274.
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XUV coherent diffraction imaging in reflection geometry with low numerical aperture.
Zürch, Michael; Kern, Christian; Spielmann, Christian
2013-09-09
We present an experimental realization of coherent diffraction imaging in reflection geometry illuminating the sample with a laser driven high harmonic generation (HHG) based XUV source. After recording the diffraction pattern in reflection geometry, the data must be corrected before the image can be reconstructed with a hybrid-input-output (HIO) algorithm. In this paper we present a detailed investigation of sources of spoiling the reconstructed image due to the nonlinear momentum transfer, errors in estimating the angle of incidence on the sample, and distortions by placing the image off center in the computation grid. Finally we provide guidelines for the necessary parameters to realize a satisfactory reconstruction within a spatial resolution in the range of one micron for an imaging scheme with a numerical aperture NA < 0.03.
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Wen, Tingxi; Zhang, Zhongnan
2017-01-01
Abstract In this paper, genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of interclass distance and intraclass distance. Moreover, the proposed feature search method can search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable; thus, GAFDS exhibits good extensibility. Multiple classical classifiers (i.e., k-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Naïve Bayes) achieve satisfactory classification accuracies by using the features generated by the GAFDS method and the optimized feature selection. The accuracies for 2-classification and 3-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in the extraction of effective features for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy. PMID:28489789
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NASA Astrophysics Data System (ADS)
Hamel, M. C.; Polack, J. K.; Poitrasson-Rivière, A.; Clarke, S. D.; Pozzi, S. A.
2017-01-01
In this work we present a technique for isolating the gamma-ray and neutron energy spectra from multiple radioactive sources localized in an image. Image reconstruction algorithms for radiation scatter cameras typically focus on improving image quality. However, with scatter cameras being developed for non-proliferation applications, there is a need for not only source localization but also source identification. This work outlines a modified stochastic origin ensembles algorithm that provides localized spectra for all pixels in the image. We demonstrated the technique by performing three experiments with a dual-particle imager that measured various gamma-ray and neutron sources simultaneously. We showed that we could isolate the peaks from 22Na and 137Cs and that the energy resolution is maintained in the isolated spectra. To evaluate the spectral isolation of neutrons, a 252Cf source and a PuBe source were measured simultaneously and the reconstruction showed that the isolated PuBe spectrum had a higher average energy and a greater fraction of neutrons at higher energies than the 252Cf. Finally, spectrum isolation was used for an experiment with weapons grade plutonium, 252Cf, and AmBe. The resulting neutron and gamma-ray spectra showed the expected characteristics that could then be used to identify the sources.
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Analysis of physiological signals for recognition of boredom, pain, and surprise emotions.
Jang, Eun-Hye; Park, Byoung-Jun; Park, Mi-Sook; Kim, Sang-Hyeob; Sohn, Jin-Hun
2015-06-18
The aim of the study was to examine the differences of boredom, pain, and surprise. In addition to that, it was conducted to propose approaches for emotion recognition based on physiological signals. Three emotions, boredom, pain, and surprise, are induced through the presentation of emotional stimuli and electrocardiography (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmography (PPG) as physiological signals are measured to collect a dataset from 217 participants when experiencing the emotions. Twenty-seven physiological features are extracted from the signals to classify the three emotions. The discriminant function analysis (DFA) as a statistical method, and five machine learning algorithms (linear discriminant analysis (LDA), classification and regression trees (CART), self-organizing map (SOM), Naïve Bayes algorithm, and support vector machine (SVM)) are used for classifying the emotions. The result shows that the difference of physiological responses among emotions is significant in heart rate (HR), skin conductance level (SCL), skin conductance response (SCR), mean skin temperature (meanSKT), blood volume pulse (BVP), and pulse transit time (PTT), and the highest recognition accuracy of 84.7% is obtained by using DFA. This study demonstrates the differences of boredom, pain, and surprise and the best emotion recognizer for the classification of the three emotions by using physiological signals.
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A Comparison of Vibration and Oil Debris Gear Damage Detection Methods Applied to Pitting Damage
NASA Technical Reports Server (NTRS)
Dempsey, Paula J.
2000-01-01
Helicopter Health Usage Monitoring Systems (HUMS) must provide reliable, real-time performance monitoring of helicopter operating parameters to prevent damage of flight critical components. Helicopter transmission diagnostics are an important part of a helicopter HUMS. In order to improve the reliability of transmission diagnostics, many researchers propose combining two technologies, vibration and oil monitoring, using data fusion and intelligent systems. Some benefits of combining multiple sensors to make decisions include improved detection capabilities and increased probability the event is detected. However, if the sensors are inaccurate, or the features extracted from the sensors are poor predictors of transmission health, integration of these sensors will decrease the accuracy of damage prediction. For this reason, one must verify the individual integrity of vibration and oil analysis methods prior to integrating the two technologies. This research focuses on comparing the capability of two vibration algorithms, FM4 and NA4, and a commercially available on-line oil debris monitor to detect pitting damage on spur gears in the NASA Glenn Research Center Spur Gear Fatigue Test Rig. Results from this research indicate that the rate of change of debris mass measured by the oil debris monitor is comparable to the vibration algorithms in detecting gear pitting damage.
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Scalp reconstruction: an algorithmic approach and systematic review.
Desai, Shaun C; Sand, Jordan P; Sharon, Jeffrey D; Branham, Gregory; Nussenbaum, Brian
2015-01-01
Reconstruction of the scalp after acquired defects remains a common challenge for the reconstructive surgeon, especially in a patient with a history of radiation to the area. To review the current literature and describe a novel algorithm to help guide the reconstructive surgeon in determining the optimal reconstruction from a cosmetic and functional standpoint. Pertinent surgical anatomy, considerations for patient and technique selection, reconstructive goals, as well as the reconstructive ladder, are also discussed. A PubMed and Medline search was performed of the entire English literature with respect to scalp reconstruction. Priority of review was given to those studies with higher-quality levels of evidence. Size, location, radiation history, and potential for hairline distortion are important factors in determining the ideal reconstruction. The tighter and looser areas of the scalp play a major role in the potential for primary or local flap closure. Patients with medium to large defects and a history of radiation will likely benefit from free tissue transfer. Ideal reconstruction of scalp defects relies on a comprehensive understanding of scalp anatomy, a full consideration of the armamentarium of surgical techniques, and a detailed appraisal of patient factors and expectations. The simplest reconstruction should be used whenever possible to provide the most functional and aesthetic scalp reconstruction, with the least amount of complexity. NA.
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Mu, John C.; Tootoonchi Afshar, Pegah; Mohiyuddin, Marghoob; Chen, Xi; Li, Jian; Bani Asadi, Narges; Gerstein, Mark B.; Wong, Wing H.; Lam, Hugo Y. K.
2015-01-01
A high-confidence, comprehensive human variant set is critical in assessing accuracy of sequencing algorithms, which are crucial in precision medicine based on high-throughput sequencing. Although recent works have attempted to provide such a resource, they still do not encompass all major types of variants including structural variants (SVs). Thus, we leveraged the massive high-quality Sanger sequences from the HuRef genome to construct by far the most comprehensive gold set of a single individual, which was cross validated with deep Illumina sequencing, population datasets, and well-established algorithms. It was a necessary effort to completely reanalyze the HuRef genome as its previously published variants were mostly reported five years ago, suffering from compatibility, organization, and accuracy issues that prevent their direct use in benchmarking. Our extensive analysis and validation resulted in a gold set with high specificity and sensitivity. In contrast to the current gold sets of the NA12878 or HS1011 genomes, our gold set is the first that includes small variants, deletion SVs and insertion SVs up to a hundred thousand base-pairs. We demonstrate the utility of our HuRef gold set to benchmark several published SV detection tools. PMID:26412485
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Shulkind, Gal; Nazarathy, Moshe
2012-12-17
We present an efficient method for system identification (nonlinear channel estimation) of third order nonlinear Volterra Series Transfer Function (VSTF) characterizing the four-wave-mixing nonlinear process over a coherent OFDM fiber link. Despite the seemingly large number of degrees of freedom in the VSTF (cubic in the number of frequency points) we identified a compressed VSTF representation which does not entail loss of information. Additional slightly lossy compression may be obtained by discarding very low power VSTF coefficients associated with regions of destructive interference in the FWM phased array effect. Based on this two-staged VSTF compressed representation, we develop a robust and efficient algorithm of nonlinear system identification (optical performance monitoring) estimating the VSTF by transmission of an extended training sequence over the OFDM link, performing just a matrix-vector multiplication at the receiver by a pseudo-inverse matrix which is pre-evaluated offline. For 512 (1024) frequency samples per channel, the VSTF measurement takes less than 1 (10) msec to complete with computational complexity of one real-valued multiply-add operation per time sample. Relative to a naïve exhaustive three-tone-test, our algorithm is far more tolerant of ASE additive noise and its acquisition time is orders of magnitude faster.
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Wen, Tingxi; Zhang, Zhongnan
2017-05-01
In this paper, genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of interclass distance and intraclass distance. Moreover, the proposed feature search method can search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable; thus, GAFDS exhibits good extensibility. Multiple classical classifiers (i.e., k-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Naïve Bayes) achieve satisfactory classification accuracies by using the features generated by the GAFDS method and the optimized feature selection. The accuracies for 2-classification and 3-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in the extraction of effective features for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy.
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Code of Federal Regulations, 2012 CFR
2012-07-01
... NA NA NA NA NA NA NA NA NA NA Chamber Cleaning In situ plasma cleaning: 1-Ui NA NA NA NA NA NA 0.23... NA NA NA NA NA In Situ Thermal Cleaning: 1-Ui NA NA NA NA NA NA 0.28 NA NA NA NA BCF4 NA NA NA NA NA...
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Kunenkov, Erast V; Kononikhin, Alexey S; Perminova, Irina V; Hertkorn, Norbert; Gaspar, Andras; Schmitt-Kopplin, Philippe; Popov, Igor A; Garmash, Andrew V; Nikolaev, Evgeniy N
2009-12-15
The ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrum of natural organic matter (NOM) contains several thousand peaks with dozens of molecules matching the same nominal mass. Such a complexity poses a significant challenge for automatic data interpretation, in which the most difficult task is molecular formula assignment, especially in the case of heavy and/or multielement ions. In this study, a new universal algorithm for automatic treatment of FTICR mass spectra of NOM and humic substances based on total mass difference statistics (TMDS) has been developed and implemented. The algorithm enables a blind search for unknown building blocks (instead of a priori known ones) by revealing repetitive patterns present in spectra. In this respect, it differs from all previously developed approaches. This algorithm was implemented in designing FIRAN-software for fully automated analysis of mass data with high peak density. The specific feature of FIRAN is its ability to assign formulas to heavy and/or multielement molecules using "virtual elements" approach. To verify the approach, it was used for processing mass spectra of sodium polystyrene sulfonate (PSS, M(w) = 2200 Da) and polymethacrylate (PMA, M(w) = 3290 Da) which produce heavy multielement and multiply-charged ions. Application of TMDS identified unambiguously monomers present in the polymers consistent with their structure: C(8)H(7)SO(3)Na for PSS and C(4)H(6)O(2) for PMA. It also allowed unambiguous formula assignment to all multiply-charged peaks including the heaviest peak in PMA spectrum at mass 4025.6625 with charge state 6- (mass bias -0.33 ppm). Application of the TMDS-algorithm to processing data on the Suwannee River FA has proven its unique capacities in analysis of spectra with high peak density: it has not only identified the known small building blocks in the structure of FA such as CH(2), H(2), C(2)H(2)O, O but the heavier unit at 154.027 amu. The latter was identified for the first time and assigned a formula C(7)H(6)O(4) consistent with the structure of dihydroxyl-benzoic acids. The presence of these compounds in the structure of FA has so far been numerically suggested but never proven directly. It was concluded that application of the TMDS-algorithm opens new horizons in unfolding molecular complexity of NOM and other natural products.
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Estimation of splitting functions from Earth's normal mode spectra using the neighbourhood algorithm
NASA Astrophysics Data System (ADS)
Pachhai, Surya; Tkalčić, Hrvoje; Masters, Guy
2016-01-01
The inverse problem for Earth structure from normal mode data is strongly non-linear and can be inherently non-unique. Traditionally, the inversion is linearized by taking partial derivatives of the complex spectra with respect to the model parameters (i.e. structure coefficients), and solved in an iterative fashion. This method requires that the earthquake source model is known. However, the release of energy in large earthquakes used for the analysis of Earth's normal modes is not simple. A point source approximation is often inadequate, and a more complete account of energy release at the source is required. In addition, many earthquakes are required for the solution to be insensitive to the initial constraints and regularization. In contrast to an iterative approach, the autoregressive linear inversion technique conveniently avoids the need for earthquake source parameters, but it also requires a number of events to achieve full convergence when a single event does not excite all singlets well. To build on previous improvements, we develop a technique to estimate structure coefficients (and consequently, the splitting functions) using a derivative-free parameter search, known as neighbourhood algorithm (NA). We implement an efficient forward method derived using the autoregresssion of receiver strips, and this allows us to search over a multiplicity of structure coefficients in a relatively short time. After demonstrating feasibility of the use of NA in synthetic cases, we apply it to observations of the inner core sensitive mode 13S2. The splitting function of this mode is dominated by spherical harmonic degree 2 axisymmetric structure and is consistent with the results obtained from the autoregressive linear inversion. The sensitivity analysis of multiple events confirms the importance of the Bolivia, 1994 earthquake. When this event is used in the analysis, as little as two events are sufficient to constrain the splitting functions of 13S2 mode. Apart from not requiring the knowledge of earthquake source, the newly developed technique provides an approximate uncertainty measure of the structure coefficients and allows us to control the type of structure solved for, for example to establish if elastic structure is sufficient.
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NASA Astrophysics Data System (ADS)
Dimov, D.; Kuhn, J.; Conrad, C.
2016-06-01
In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID) e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object's textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.
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Triplet supertree heuristics for the tree of life
Lin, Harris T; Burleigh, J Gordon; Eulenstein, Oliver
2009-01-01
Background There is much interest in developing fast and accurate supertree methods to infer the tree of life. Supertree methods combine smaller input trees with overlapping sets of taxa to make a comprehensive phylogenetic tree that contains all of the taxa in the input trees. The intrinsically hard triplet supertree problem takes a collection of input species trees and seeks a species tree (supertree) that maximizes the number of triplet subtrees that it shares with the input trees. However, the utility of this supertree problem has been limited by a lack of efficient and effective heuristics. Results We introduce fast hill-climbing heuristics for the triplet supertree problem that perform a step-wise search of the tree space, where each step is guided by an exact solution to an instance of a local search problem. To realize time efficient heuristics we designed the first nontrivial algorithms for two standard search problems, which greatly improve on the time complexity to the best known (naïve) solutions by a factor of n and n2 (the number of taxa in the supertree). These algorithms enable large-scale supertree analyses based on the triplet supertree problem that were previously not possible. We implemented hill-climbing heuristics that are based on our new algorithms, and in analyses of two published supertree data sets, we demonstrate that our new heuristics outperform other standard supertree methods in maximizing the number of triplets shared with the input trees. Conclusion With our new heuristics, the triplet supertree problem is now computationally more tractable for large-scale supertree analyses, and it provides a potentially more accurate alternative to existing supertree methods. PMID:19208181
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Than, Trung Duc, E-mail: dtt581@uowmail.edu.au; Alici, Gursel, E-mail: gursel@uow.edu.au; Zhou, Hao, E-mail: hz467@uowmail.edu.au
2014-07-15
Purpose: Over the last decade, wireless capsule endoscope has been the tool of choice for noninvasive inspection of the gastrointestinal tract, especially in the small intestine. However, the latest clinical products have not been equipped with a sufficiently accurate localization system which makes it difficult to determine the location of intestinal abnormalities, and to apply follow-up interventions such as biopsy or drug delivery. In this paper, the authors present a novel localization method based on tracking three positron emission markers embedded inside an endoscopic capsule. Methods: Three spherical {sup 22}Na markers with diameters of less than 1 mm are embeddedmore » in the cover of the capsule. Gamma ray detectors are arranged around a patient body to detect coincidence gamma rays emitted from the three markers. The position of each marker can then be estimated using the collected data by the authors’ tracking algorithm which consists of four consecutive steps: a method to remove corrupted data, an initialization method, a clustering method based on the Fuzzy C-means clustering algorithm, and a failure prediction method. Results: The tracking algorithm has been implemented inMATLAB utilizing simulation data generated from the Geant4 Application for Emission Tomography toolkit. The results show that this localization method can achieve real-time tracking with an average position error of less than 0.4 mm and an average orientation error of less than 2°. Conclusions: The authors conclude that this study has proven the feasibility and potential of the proposed technique in effectively determining the position and orientation of a robotic endoscopic capsule.« less
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Code of Federal Regulations, 2013 CFR
2013-07-01
... C5F8 C4F8O Plasma Etching 1-Ui 0.80 0.80 0.48 0.14 NA 0.29 0.32 0.37 0.09 NA NA BCF4 NA NA 0.0018 0... NA NA NA NA NA Chamber Cleaning In situ plasma cleaning: 1-Ui NA NA NA NA NA NA 0.23 NA NA NA NA BCF4... NA NA NA NA NA Remote Plasma Cleaning: 1-Ui NA NA NA NA 0.063 NA 0.018 NA NA NA NA BCF4 NA NA NA NA...
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NASA Astrophysics Data System (ADS)
Brogan, R.; Young, C. J.; Ballard, S.
2017-12-01
A major problem with developing new data processing algorithms for seismic event monitoring is the lack of standard, high-quality "ground-truth" data sets to test against. The unfortunate effect of this is that new algorithms are often developed and tested with new data sets, making comparison of algorithms difficult and subjective. In an effort towards resolving this problem, we have developed the Unconstrained Event Bulletin (UEB), a ground-truth data set from the International Monitoring System (IMS) primary and auxiliary seismic networks for a two-week period in May 2010. All UEB analysis was performed by the same expert, who has more than 30 years of experience analyzing seismic data for nuclear explosion monitoring. We used the most complete International Data Centre (IDC) analyst-review event bulletin (the Late Event Bulletin or LEB) as a starting point for this analysis. To make the UEB more complete, we relaxed the minimum event definite criteria to the level of a pair of P-type and an S-type phases at a single station and using azimuth/slowness as defining. To add even more events that our analyst recognized and didn't want to omit, in rare cases, events were constructed using only 1 P-phase. Perhaps most importantly, on average our analyst spent more than 60 hours per day of data, far more than was possible in the production of the LEB. The result of all this was that while the LEB had 2,101 LEB events for the 2-week time period, we ended up with 11,435 events in the UEB, an increase of over 400%. New events are located all over the world and include both earthquakes and manmade events such as mining explosions. Our intent is to make our UEB data set openly available for all researchers to use for testing detection, correlation, and location algorithms, thus making it much easier to objectively compare different research efforts. Acknowledgement: Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.
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Code of Federal Regulations, 2012 CFR
2012-07-01
... C4F6 C5F8 C4F8O Plasma Etching 1-Ui 0.69 0.56 0.38 0.093 NA 0.25 0.038 0.20 0.14 NA NA BCF4 NA 0.23 0... NA NA NA NA NA NA NA Chamber Cleaning In situ plasma cleaning: 1-Ui 0.92 0.55 NA NA 0.40 0.10 0.18 NA... BC3F8 NA NA NA NA NA NA NA NA NA NA NA Remote plasma cleaning: 1-Ui NA NA NA NA NA NA 0.018 NA NA NA NA...
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Code of Federal Regulations, 2013 CFR
2013-07-01
... C4F6 C5F8 C4F8O Plasma Etching 1-Ui 0.69 0.56 0.38 0.093 NA 0.25 0.038 0.20 0.14 NA NA BCF4 NA 0.23 0... NA NA NA NA NA NA NA Chamber Cleaning In situ plasma cleaning: 1-Ui 0.92 0.55 NA NA 0.40 0.10 0.18 NA... BC3F8 NA NA NA NA NA NA NA NA NA NA NA Remote plasma cleaning: 1-Ui NA NA NA NA NA NA 0.018 NA NA NA NA...
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Mossadegh, Somayyeh; He, Shan; Parker, Paul
2016-05-01
Various injury severity scores exist for trauma; it is known that they do not correlate accurately to military injuries. A promising anatomical scoring system for blast pelvic and perineal injury led to the development of an improved scoring system using machine-learning techniques. An unbiased genetic algorithm selected optimal anatomical and physiological parameters from 118 military cases. A Naïve Bayesian model was built using the proposed parameters to predict the probability of survival. Ten-fold cross validation was employed to evaluate its performance. Our model significantly out-performed Injury Severity Score (ISS), Trauma ISS, New ISS, and the Revised Trauma Score in virtually all areas; positive predictive value 0.8941, specificity 0.9027, accuracy 0.9056, and area under curve 0.9059. A two-sample t test showed that the predictive performance of the proposed scoring system was significantly better than the other systems (p < 0.001). With limited resources and the simplest of Bayesian methodologies, we have demonstrated that the Naïve Bayesian model performed significantly better in virtually all areas assessed by current scoring systems used for trauma. This is encouraging and highlights that more can be done to improve trauma systems not only for our military injured, but also for civilian trauma victims. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.
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Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E
2016-07-15
Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.
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Optical imaging modalities: From design to diagnosis of skin cancer
NASA Astrophysics Data System (ADS)
Korde, Vrushali Raj
This study investigates three high resolution optical imaging modalities to better detect and diagnose skin cancer. The ideal high resolution optical imaging system can visualize pre-malignant tissue growth non-invasively with resolution comparable to histology. I examined 3 modalities which approached this goal. The first method examined was high magnification microscopy of thin stained tissue sections, together with a statistical analysis of nuclear chromatin patterns termed Karyometry. This method has subcellular resolution, but it necessitates taking a biopsy at the desired tissue site and imaging the tissue ex-vivo. My part of this study was to develop an automated nuclear segmentation algorithm to segment cell nuclei in skin histology images for karyometric analysis. The results of this algorithm were compared to hand segmented cell nuclei in the same images, and it was concluded that the automated segmentations can be used for karyometric analysis. The second optical imaging modality I investigated was Optical Coherence Tomography (OCT). OCT is analogous to ultrasound, in which sound waves are delivered into the body and the echo time and reflected signal magnitude are measured. Due to the fast speed of light and detector temporal integration times, low coherence interferometry is needed to gate the backscattered light. OCT acquires cross sectional images, and has an axial resolution of 1-15 mum (depending on the source bandwidth) and a lateral resolution of 10-20 mum (depending on the sample arm optics). While it is not capable of achieving subcellular resolution, it is a non-invasive imaging modality. OCT was used in this study to evaluate skin along a continuum from normal to sun damaged to precancer. I developed algorithms to detect statistically significant differences between images of sun protected and sun damaged skin, as well as between undiseased and precancerous skin. An Optical Coherence Microscopy (OCM) endoscope was developed in the third portion of this study. OCM is a high resolution en-face imaging modality. It is a hybrid system that combines the principles of confocal microscopy with coherence gating to provide an increased imaging depth. It can also be described as an OCT system with a high NA objective. Similar to OCT, the axial resolution is determined by the source center wavelength and bandwidth. The NA of the sample arm optics determines the lateral resolution, usually on the order of 1-5 mum. My effort on this system was to develop a handheld endoscope. To my knowledge, an OCM endoscope has not been developed prior to this work. An image of skin was taken as a proof of concept. This rigid handheld OCM endoscope will be useful for applications ranging from minimally invasive surgical imaging to non-invasively assessing dysplasia and sun damage in skin.
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A compact Acousto-Optic Lens for 2D and 3D femtosecond based 2-photon microscopy.
Kirkby, Paul A; Srinivas Nadella, K M Naga; Silver, R Angus
2010-06-21
We describe a high speed 3D Acousto-Optic Lens Microscope (AOLM) for femtosecond 2-photon imaging. By optimizing the design of the 4 AO Deflectors (AODs) and by deriving new control algorithms, we have developed a compact spherical AOL with a low temporal dispersion that enables 2-photon imaging at 10-fold lower power than previously reported. We show that the AOLM can perform high speed 2D raster-scan imaging (>150 Hz) without scan rate dependent astigmatism. It can deflect and focus a laser beam in a 3D random access sequence at 30 kHz and has an extended focusing range (>137 mum; 40X 0.8NA objective). These features are likely to make the AOLM a useful tool for studying fast physiological processes distributed in 3D space.
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NASA Astrophysics Data System (ADS)
Gambino, James; Tarver, Craig; Springer, H. Keo; White, Bradley; Fried, Laurence
2017-06-01
We present a novel method for optimizing parameters of the Ignition and Growth reactive flow (I&G) model for high explosives. The I&G model can yield accurate predictions of experimental observations. However, calibrating the model is a time-consuming task especially with multiple experiments. In this study, we couple the differential evolution global optimization algorithm to simulations of shock initiation experiments in the multi-physics code ALE3D. We develop parameter sets for HMX based explosives LX-07 and LX-10. The optimization finds the I&G model parameters that globally minimize the difference between calculated and experimental shock time of arrival at embedded pressure gauges. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC LLNL-ABS- 724898.
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Visual attitude propagation for small satellites
NASA Astrophysics Data System (ADS)
Rawashdeh, Samir A.
As electronics become smaller and more capable, it has become possible to conduct meaningful and sophisticated satellite missions in a small form factor. However, the capability of small satellites and the range of possible applications are limited by the capabilities of several technologies, including attitude determination and control systems. This dissertation evaluates the use of image-based visual attitude propagation as a compliment or alternative to other attitude determination technologies that are suitable for miniature satellites. The concept lies in using miniature cameras to track image features across frames and extracting the underlying rotation. The problem of visual attitude propagation as a small satellite attitude determination system is addressed from several aspects: related work, algorithm design, hardware and performance evaluation, possible applications, and on-orbit experimentation. These areas of consideration reflect the organization of this dissertation. A "stellar gyroscope" is developed, which is a visual star-based attitude propagator that uses relative motion of stars in an imager's field of view to infer the attitude changes. The device generates spacecraft relative attitude estimates in three degrees of freedom. Algorithms to perform the star detection, correspondence, and attitude propagation are presented. The Random Sample Consensus (RANSAC) approach is applied to the correspondence problem to successfully pair stars across frames while mitigating falsepositive and false-negative star detections. This approach provides tolerance to the noise levels expected in using miniature optics and no baffling, and the noise caused by radiation dose on orbit. The hardware design and algorithms are validated using test images of the night sky. The application of the stellar gyroscope as part of a CubeSat attitude determination and control system is described. The stellar gyroscope is used to augment a MEMS gyroscope attitude propagation algorithm to minimize drift in the absence of an absolute attitude sensor. The stellar gyroscope is a technology demonstration experiment on KySat-2, a 1-Unit CubeSat being developed in Kentucky that is in line to launch with the NASA ELaNa CubeSat Launch Initiative. It has also been adopted by industry as a sensor for CubeSat Attitude Determination and Control Systems (ADCS). KEYWORDS: Small Satellites, Attitude Determination, Egomotion Estimation, RANSAC, Image Processing.
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Rothermundt, Christian; Bailey, Alexandra; Cerbone, Linda; Eisen, Tim; Escudier, Bernard; Gillessen, Silke; Grünwald, Viktor; Larkin, James; McDermott, David; Oldenburg, Jan; Porta, Camillo; Rini, Brian; Schmidinger, Manuela; Sternberg, Cora; Putora, Paul M
2015-09-01
With the advent of targeted therapies, many treatment options in the first-line setting of metastatic clear cell renal cell carcinoma (mccRCC) have emerged. Guidelines and randomized trial reports usually do not elucidate the decision criteria for the different treatment options. In order to extract the decision criteria for the optimal therapy for patients, we performed an analysis of treatment algorithms from experts in the field. Treatment algorithms for the treatment of mccRCC from experts of 11 institutions were obtained, and decision trees were deduced. Treatment options were identified and a list of unified decision criteria determined. The final decision trees were analyzed with a methodology based on diagnostic nodes, which allows for an automated cross-comparison of decision trees. The most common treatment recommendations were determined, and areas of discordance were identified. The analysis revealed heterogeneity in most clinical scenarios. The recommendations selected for first-line treatment of mccRCC included sunitinib, pazopanib, temsirolimus, interferon-α combined with bevacizumab, high-dose interleukin-2, sorafenib, axitinib, everolimus, and best supportive care. The criteria relevant for treatment decisions were performance status, Memorial Sloan Kettering Cancer Center risk group, only or mainly lung metastases, cardiac insufficiency, hepatic insufficiency, age, and "zugzwang" (composite of multiple, related criteria). In the present study, we used diagnostic nodes to compare treatment algorithms in the first-line treatment of mccRCC. The results illustrate the heterogeneity of the decision criteria and treatment strategies for mccRCC and how available data are interpreted and implemented differently among experts. The data provided in the present report should not be considered to serve as treatment recommendations for the management of treatment-naïve patients with multiple metastases from metastatic clear cell renal cell carcinoma outside a clinical trial; however, the data highlight the different treatment options and the criteria used to select them. The diversity in decision making and how results from phase III trials can be interpreted and implemented differently in daily practice are demonstrated. ©AlphaMed Press.
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Design of a multimodal (1H/23Na MR/CT) anthropomorphic thorax phantom.
Neumann, Wiebke; Lietzmann, Florian; Schad, Lothar R; Zöllner, Frank G
2017-06-01
This work proposes a modular, anthropomorphic MR and CT thorax phantom that enables the comparison of experimental studies for quantitative evaluation of deformable, multimodal image registration algorithms and realistic multi-nuclear MR imaging techniques. A human thorax phantom was developed with insertable modules representing lung, liver, ribs and additional tracking spheres. The quality of human tissue mimicking characteristics was evaluated for 1 H and 23 Na MR as well as CT imaging. The position of landmarks in the lung lobes was tracked during CT image acquisition at several positions during breathing cycles. 1 H MR measurements of the liver were repeated after seven months to determine long term stability. The modules possess HU, T 1 and T 2 values comparable to human tissues (lung module: -756±148HU, artificial ribs: 218±56HU (low CaCO 3 concentration) and 339±121 (high CaCO 3 concentration), liver module: T 1 =790±28ms, T 2 =65±1ms). Motion analysis showed that the landmarks in the lung lobes follow a 3D trajectory similar to human breathing motion. The tracking spheres are well detectable in both CT and MRI. The parameters of the tracking spheres can be adjusted in the following ranges to result in a distinct signal: HU values from 150 to 900HU, T 1 relaxation time from 550ms to 2000ms, T 2 relaxation time from 40ms to 200ms. The presented anthropomorphic multimodal thorax phantom fulfills the demands of a simple, inexpensive system with interchangeable components. In future, the modular design allows for complementing the present set up with additional modules focusing on specific research targets such as perfusion studies, 23 Na MR quantification experiments and an increasing level of complexity for motion studies. Copyright © 2016. Published by Elsevier GmbH.
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Hodder, S; Arasteh, K; De Wet, J; Gathe, J; Gold, J; Kumar, P; Mohapi, L; Short, W; Crauwels, H; Vanveggel, S; Boven, K
2012-08-01
A week 48 efficacy and safety analysis with respect to gender and race was conducted using pooled data from the phase III, double-blind, double-dummy efficacy comparison in treatment-naïve, HIV-infected subjects of TMC278 and efavirenz (ECHO) and TMC278 against HIV, in a once-daily regimen versus efavirenz (THRIVE) trials. Treatment-naïve, HIV-1-infected adults were randomized to receive rilpivirine (RPV; TMC278) 25 mg once a day (qd), or efavirenz (EFV) 600 mg qd, plus tenofovir/emtricitabine (ECHO) or tenofovir/emtricitabine, zidovudine/lamivudine or abacavir/lamivudine (THRIVE). A total of 1368 participants (76% male and 61% White, of those with available race data) were randomized and treated. No gender-related differences in response rate (percentage of patients with HIV-1 viral load < 50 HIV-1 RNA copies/mL, using an intent-to-treat, time-to-loss-of-virological-response algorithm) were observed (RPV: men, 85%; women, 83%; EFV: men, 82%; women, 83%). Response rates were lower in Black compared with Asian and White participants (RPV: 75% vs. 95% and 85%, respectively; EFV: 74% vs. 93% and 83%, respectively); this finding was mostly a result of higher discontinuation and virological failure rates in Black patients. Safety findings were generally similar across race and gender subgroups. However, nausea occurred more commonly in women than in men in both treatment groups. In men, diarrhoea was more frequent in the EFV group, and abnormal dreams/nightmares were more frequent in men in both the EFV and RPV groups. Overall response rates were high for both RPV and EFV. No gender differences were observed. However, response rates were lower among Black patients, regardless of treatment group. Gender appeared to influence the incidence of gastrointestinal adverse events and abnormal dreams/nightmares for both treatments. © 2012 British HIV Association.
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NASA Astrophysics Data System (ADS)
Marion, Giles M.; Farren, Ronald E.
1999-05-01
The Spencer-Møller-Weare (SMW) (1990) model is parameterized for the Na-K-Mg-Ca-Cl-SO 4-H 2O system over the temperature range from -60° to 25°C. This model is one of the few complex chemical equilibrium models for aqueous solutions parameterized for subzero temperatures. The primary focus of the SMW model parameterization and validation deals with chloride systems. There are problems with the sulfate parameterization of the SMW model, most notably with sodium sulfate and magnesium sulfate. The primary objective of this article is to re-estimate the Pitzer-equation parameters governing interactions among sodium, potassium, magnesium, and calcium with sulfate in the SMW model. A mathematical algorithm is developed to estimate 22 temperature-dependent Pitzer-equation parameters. The sodium sulfate reparameterization reduces the overall standard error (SE) from 0.393 with the SMW Pitzer-equation parameters to 0.155. Similarly, the magnesium sulfate reparameterization reduces the SE from 0.335 to 0.124. In addition to the sulfate reparameterization, five additional sulfate minerals are included in the model, which allows a more complete treatment of sulfate chemistry in the Na-K-Mg-Ca-Cl-SO 4-H 2O system. Application of the model to seawater evaporation predicts gypsum precipitation at a seawater concentration factor (SCF) of 3.37 and halite precipitation at an SCF of 10.56, which are in good agreement with previous experimental and theoretical estimates. Application of the model to seawater freezing helps explain the two pathways for seawater freezing. Along the thermodynamically stable "Gitterman pathway," calcium precipitates as gypsum and the seawater eutectic is -36.2°C. Along the metastable "Ringer-Nelson-Thompson pathway," calcium precipitates as antarcticite and the seawater eutectic is -53.8°C.
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An RNAi in silico approach to find an optimal shRNA cocktail against HIV-1
2010-01-01
Background HIV-1 can be inhibited by RNA interference in vitro through the expression of short hairpin RNAs (shRNAs) that target conserved genome sequences. In silico shRNA design for HIV has lacked a detailed study of virus variability constituting a possible breaking point in a clinical setting. We designed shRNAs against HIV-1 considering the variability observed in naïve and drug-resistant isolates available at public databases. Methods A Bioperl-based algorithm was developed to automatically scan multiple sequence alignments of HIV, while evaluating the possibility of identifying dominant and subdominant viral variants that could be used as efficient silencing molecules. Student t-test and Bonferroni Dunn correction test were used to assess statistical significance of our findings. Results Our in silico approach identified the most common viral variants within highly conserved genome regions, with a calculated free energy of ≥ -6.6 kcal/mol. This is crucial for strand loading to RISC complex and for a predicted silencing efficiency score, which could be used in combination for achieving over 90% silencing. Resistant and naïve isolate variability revealed that the most frequent shRNA per region targets a maximum of 85% of viral sequences. Adding more divergent sequences maintained this percentage. Specific sequence features that have been found to be related with higher silencing efficiency were hardly accomplished in conserved regions, even when lower entropy values correlated with better scores. We identified a conserved region among most HIV-1 genomes, which meets as many sequence features for efficient silencing. Conclusions HIV-1 variability is an obstacle to achieving absolute silencing using shRNAs designed against a consensus sequence, mainly because there are many functional viral variants. Our shRNA cocktail could be truly effective at silencing dominant and subdominant naïve viral variants. Additionally, resistant isolates might be targeted under specific antiretroviral selective pressure, but in both cases these should be tested exhaustively prior to clinical use. PMID:21172023
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Turabekova, Malakhat A.; Rasulev, Bakhtiyor F.; Levkovich, Mikhail G.; Abdullaev, Nasrulla D.; Leszczynski, Jerzy
2015-01-01
Early pharmacological studies of Aconitum and Delphinium sp. alkaloids suggested that these neurotoxins act at site 2 of voltage-gated Na+ channel and allosterically modulate its function. Understanding structural requirements for these compounds to exhibit binding activity at voltage-gated Na+ channel has been important in various fields. This paper reports quantum-chemical studies and quantitative structure-activity relationships (QSARs) based on a total of 65 natural alkaloids from two plant species, which includes both blockers and openers of sodium ion channel. A series of 18 antagonist alkaloids (9 blockers and 9 openers) have been studied using AM1 and DFT computational methods in order to reveal their structure-activity (structure-toxicity) relationship at electronic level. An examination of frontier orbitals obtained for ground and protonated forms of the compounds revealed that HOMOs and LUMOs were mainly represented by nitrogen atom and benzyl/benzoylester orbitals with –OH and –OCOCH3 contributions. The results obtained from this research have confirmed the experimental findings suggesting that neurotoxins acting at type 2 receptor site of voltage-dependent sodium channel are activators and blockers with common structural features and differ only in efficacy. The energetic tendency of HOMO-LUMO energy gap can probably distinguish activators and blockers that have been observed. Genetic Algorithm with Multiple Linear Regression Analysis (GA-MLRA) technique was also applied for the generation of two-descriptor QSAR models for the set of 65 blockers. Additionally to the computational studies, the HOMO-LUMO gap descriptor in each obtained QSAR model has confirmed the crucial role of charge transfer in receptor-ligand interactions. A number of other descriptors such as logP, IBEG, nNH2, nHDon, nCO have been selected as complementary ones to LUMO and their role in activity alteration has also been discussed. PMID:18201930
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A new algorithm for reducing the workload of experts in performing systematic reviews.
Matwin, Stan; Kouznetsov, Alexandre; Inkpen, Diana; Frunza, Oana; O'Blenis, Peter
2010-01-01
To determine whether a factorized version of the complement naïve Bayes (FCNB) classifier can reduce the time spent by experts reviewing journal articles for inclusion in systematic reviews of drug class efficacy for disease treatment. The proposed classifier was evaluated on a test collection built from 15 systematic drug class reviews used in previous work. The FCNB classifier was constructed to classify each article as containing high-quality, drug class-specific evidence or not. Weight engineering (WE) techniques were added to reduce underestimation for Medical Subject Headings (MeSH)-based and Publication Type (PubType)-based features. Cross-validation experiments were performed to evaluate the classifier's parameters and performance. Work saved over sampling (WSS) at no less than a 95% recall was used as the main measure of performance. The minimum workload reduction for a systematic review for one topic, achieved with a FCNB/WE classifier, was 8.5%; the maximum was 62.2% and the average over the 15 topics was 33.5%. This is 15.0% higher than the average workload reduction obtained using a voting perceptron-based automated citation classification system. The FCNB/WE classifier is simple, easy to implement, and produces significantly better results in reducing the workload than previously achieved. The results support it being a useful algorithm for machine-learning-based automation of systematic reviews of drug class efficacy for disease treatment.
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A Multi-Fidelity Surrogate Model for the Equation of State for Mixtures of Real Gases
NASA Astrophysics Data System (ADS)
Ouellet, Frederick; Park, Chanyoung; Koneru, Rahul; Balachandar, S.; Rollin, Bertrand
2017-11-01
The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the products of detonated explosives must be treated as real gases while the ideal gas equation of state is used for the ambient air. As the products expand outward, they mix with the air and create a region where both state equations must be satisfied. One of the most accurate, yet expensive, methods to handle this problem is an algorithm that iterates between both state equations until both pressure and thermal equilibrium are achieved inside of each computational cell. This work creates a multi-fidelity surrogate model to replace this process. This is achieved by using a Kriging model to produce a curve fit which interpolates selected data from the iterative algorithm. The surrogate is optimized for computing speed and model accuracy by varying the number of sampling points chosen to construct the model. The performance of the surrogate with respect to the iterative method is tested in simulations using a finite volume code. The model's computational speed and accuracy are analyzed to show the benefits of this novel approach. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program, under Contract No. DE-NA00023.
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Analysis of a Multi-Fidelity Surrogate for Handling Real Gas Equations of State
NASA Astrophysics Data System (ADS)
Ouellet, Frederick; Park, Chanyoung; Rollin, Bertrand; Balachandar, S.
2017-06-01
The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the detonation products of the explosive must be treated as real gas while the ideal gas equation of state is used for the surrounding air. As the products expand outward from the detonation point, they mix with ambient air and create a mixing region where both state equations must be satisfied. One of the most accurate, yet computationally expensive, methods to handle this problem is an algorithm that iterates between both equations of state until pressure and thermal equilibrium are achieved inside of each computational cell. This work aims to use a multi-fidelity surrogate model to replace this process. A Kriging model is used to produce a curve fit which interpolates selected data from the iterative algorithm using Bayesian statistics. We study the model performance with respect to the iterative method in simulations using a finite volume code. The model's (i) computational speed, (ii) memory requirements and (iii) computational accuracy are analyzed to show the benefits of this novel approach. Also, optimizing the combination of model accuracy and computational speed through the choice of sampling points is explained. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program as a Cooperative Agreement under the Predictive Science Academic Alliance Program under Contract No. DE-NA0002378.
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Resolution of singularities for multi-loop integrals
NASA Astrophysics Data System (ADS)
Bogner, Christian; Weinzierl, Stefan
2008-04-01
We report on a program for the numerical evaluation of divergent multi-loop integrals. The program is based on iterated sector decomposition. We improve the original algorithm of Binoth and Heinrich such that the program is guaranteed to terminate. The program can be used to compute numerically the Laurent expansion of divergent multi-loop integrals regulated by dimensional regularisation. The symbolic and the numerical steps of the algorithm are combined into one program. Program summaryProgram title: sector_decomposition Catalogue identifier: AEAG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAG_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 47 506 No. of bytes in distributed program, including test data, etc.: 328 485 Distribution format: tar.gz Programming language: C++ Computer: all Operating system: Unix RAM: Depending on the complexity of the problem Classification: 4.4 External routines: GiNaC, available from http://www.ginac.de, GNU scientific library, available from http://www.gnu.org/software/gsl Nature of problem: Computation of divergent multi-loop integrals. Solution method: Sector decomposition. Restrictions: Only limited by the available memory and CPU time. Running time: Depending on the complexity of the problem.
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A Multifluid Numerical Algorithm for Interpenetrating Plasma Dynamics
NASA Astrophysics Data System (ADS)
Ghosh, Debojyoti; Kavouklis, Christos; Berger, Richard; Chapman, Thomas; Hittinger, Jeffrey
2017-10-01
Interpenetrating plasmas occur in situations including inertial confinement fusion experiments, where plasmas ablate off the hohlraum and capsule surfaces and interact with each other, and in high-energy density physics experiments that involve the collision of plasma streams ablating off discs irradiated by laser beams. Single-fluid, multi-species hydrodynamic models are not well-suited to study this interaction because they cannot support more than a single fluid velocity; this results in unphysical solutions. Though kinetic models yield accurate solutions for multi-fluid interactions, they are prohibitively expensive for at-scale three-dimensional (3D) simulations. In this study, we propose a multifluid approach where the compressible fluid equations are solved for each ion species and the electrons. Electrostatic forces and inter-species friction and thermal equilibration couple the species. A high-order finite-volume algorithm with explicit time integration is used to solve on a 3D Cartesian domain, and a high-order Poisson solver is used to compute the electrostatic potential. We present preliminary results for the interpenetration of two plasma streams in vacuum and in the presence of a gas fill. This work was performed under the auspices of the U.S. DOE by Lawrence Livermore National Laboratory under Contract No. DE-AC52- 07NA27344 and funded by the LDRD Program at LLNL under project tracking code 17-ERD-081.
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Evangelista, Daniela; Zuccaro, Antonio; Lančinskas, Algirdas; Žilinskas, Julius; Guarracino, Mario R
2016-02-17
The cost per patient of next generation sequencing for detection of rare mutations may be significantly reduced using pooled experiments. Recently, some techniques have been proposed for the planning of pooled experiments and for the optimal allocation of patients into pools. However, the lack of a user friendly resource for planning the design of pooled experiments forces the scientists to do frequent, complex and long computations. OPENDoRM is a powerful collection of novel mathematical algorithms usable via an intuitive graphical user interface. It enables researchers to speed up the planning of their routine experiments, as well as, to support scientists without specific bioinformatics expertises. Users can automatically carry out analysis in terms of costs associated with the optimal allocation of patients in pools. They are also able to choose between three distinct pooling mathematical methods, each of which also suggests the optimal configuration for the submitted experiment. Importantly, in order to keep track of the performed experiments, users can save and export the results of their experiments in standard tabular and charts contents. OPENDoRM is a freely available web-oriented application for the planning of pooled NGS experiments, available at: http://www-labgtp.na.icar.cnr.it/OPENDoRM. Its easy and intuitive graphical user interface enables researchers to plan theirs experiments using novel algorithms, and to interactively visualize the results.
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Synthesis and Structural Characterization of the Aluminosilicate LZ-135, a Zeolite Related to ZSM-10
DOE Office of Scientific and Technical Information (OSTI.GOV)
McCusker, Lynne B.; Baerlocher, Christian; Wilson, Stephen T.
2009-09-02
The aluminosilicate LZ-135 was one of the first zeolites to be prepared in the presence of two or more organic structure-directing agents (in this case, Me{sub 4}N{sup +} (TMA) and Et{sub 4}N{sup +} (TEA)) and was patented 20 years ago. However, the material was polycrystalline, and at the time, its aluminosilicate framework structure could not be determined. In view of the fact that methods of structure determination from powder diffraction data have developed considerably in the meantime, a fresh analysis of the problem was undertaken. High-resolution synchrotron powder diffraction data were collected on a calcined sample of LZ-135 (as synthesizedmore » composition ca. |Na{sub 26}TMA{sub 6}|[Si{sub 76}Al{sub 32}O{sub 216}]), and the new powder charge-flipping structure-solution algorithm was applied. The framework structure (P6{sub 3}/mmc; a = 31.3830(2) {angstrom}, c = 7.6513(1) {angstrom}) was revealed immediately, and then the positions of the Na{sup +} ions and a few water molecules were located in a series of difference electron density maps. The [001] projection of the framework structure is identical to that of ZSM-10 (P6{sub 3}/mmm), but the (up-down) orientations of the (Si,Al) tetrahedra, and therefore their connectivities, are different, and this leads to a distinctly different topology with two 1-dimensional, 12-ring channel systems with effective pore widths of 7.2 and 6.5 {angstrom}. The new framework has been assigned the framework type code LTF by the International Zeolite Association. The framework structures of LZ-135 and ZSM-10 are related to one another in the same way as are those of mazzite and zeolite L. Approximately 27.5 Na{sup +} ions were located in six different sites, and all are coordinated to oxygen atoms of the framework. Twelve H{sub 2}O molecules per unit cell are associated with one of the Na{sup +} ion positions, where they serve to complete an octahedral coordination geometry around the ion, and 5.2 are located in the larger of the two 12-ring channels, where they make hydrogen-bonding contacts to framework oxygen atoms and are probably associated with protons.« less
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Host galaxy properties of calcium II and sodium I quasar absorption-line systems
NASA Astrophysics Data System (ADS)
Cherinka, Brian
Many questions remain within the areas of galaxy formation and evolution. Understanding the origin of gas in galaxy environments, whether as tidal debris, infalling High Velocity Clouds, galaxy outflows, or as gaseous material residing in galaxy disks, is an important step in answering those questions. Quasar absorption-lines can often be used to probe the environments of intervening galaxies. Traditionally, quasar absorption-lines are studied independently of the host galaxy but this method denies us the exploration of the connection between galaxy and environment. Instead, one can select pairs of known galaxies and quasars. This gives much more information regarding the host galaxy and allows us to better connect galaxy properties with associated absorbers. We use the seventh data release of the Sloan Digital Sky Survey to generate a sample of spectroscopic galaxy-quasar pairs. We cross-correlated a sample of 105,000 quasars and ˜800,000 galaxies to produce ˜98,000 galaxy-quasar pairs, with the quasar projected within 100 kpc of the galaxy. Adopting an automated line-finding algorithm and using the galaxy redshift as a prior, we search through all quasar spectra and identify Ca II and Na I absorption due to the intervening galaxy. This procedure produced 1745 Ca II absorbers and 4500 Na I absorbers detected at or above 2σ. Stacking analysis of a subset of absorbers at z > 0.01, with significances at or above 3σ, showed strong Ca II and Na I features around external galaxies. Using the same subset of absorbers at z > 0.01, we looked for correlations between absorber and galaxy properties and examined differences in galaxy properties between the absorbers and non-absorbers. We found no correlations with absorber strength or differences between many galaxy properties at the 3σ level. The lack of correlations and differences between absorbers and non-absorbers suggest a ubiquitous nature for Ca II and Na I around all types of galaxies, with the absorbers showing no geometric preference within galaxy halos. This suggests a possible origin as leftover debris from past mergers that has been redistributed within the halo over time. The main results are presented in Chapters 3 and 4, with complimentary work presented in Chapter 5.
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Cationic influences upon synaptic transmission at the hair cell-afferent fiber synapse of the frog
NASA Technical Reports Server (NTRS)
Cochran, S. L.
1995-01-01
The concentrations of inorganic cations (K+, Na+, and Ca2+) bathing the isolated frog labyrinth were varied in order to assess their role in influencing and mediating synaptic transmission at the hair cell-afferent fiber synapse. Experiments employed intracellular recordings of synaptic activity from VIIIth nerve afferents. Recordings were digitized continuously at 50 kHz, and excitatory postsynaptic potentials were detected and parameters quantified by computer algorithms. Particular attention was focused on cationic effects upon excitatory postsynaptic potential frequency of occurrence and excitatory postsynaptic potential amplitude, in order to discriminate between pre- and postsynaptic actions. Because the small size of afferents preclude long term stable recordings, alterations in cationic concentrations were applied transiently and their peak effects on synaptic activity were assessed. Increases in extracellular K+ concentration of a few millimolar produced a large increase in the frequency of occurrence of excitatory postsynaptic potentials with little change in amplitude, indicating that release of transmitter from the hair cell is tightly coupled to its membrane potential. Increasing extracellular Na+ concentration resulted in an increase in excitatory postsynaptic potential amplitude with no significant change in excitatory postsynaptic potential frequency of occurrence, suggesting that the transmitter-gated subsynaptic channel conducts Na+ ions. Decreases in extracellular Ca2+ concentration had little effect upon excitatory postsynaptic potential frequency, but increased excitatory postsynaptic potential frequency and amplitude. These findings suggest that at higher concentrations Ca2+ act presynaptically to prevent transmitter release and postsynaptically to prevent Na+ influx during the generation of the excitatory postsynaptic potential. The influences of these ions on synaptic activity at this synapse are remarkably similar to those reported at the vertebrate neuromuscular junction. The major differences between these two synapses are the neurotransmitters and the higher resting release rate and higher sensitivity of release to increased K+ concentrations of the hair cells over that of motor nerve terminals. These differences reflect the functional roles of the two synapses: the motor nerve terminal response in an all-or-nothing signal consequent from action potential invasion, while the hair cell releases transmitter in a graded fashion, proportionate to the extent of stereocilial deflection. Despite these differences between the two junctions, the similar actions of these elemental cations upon synaptic function at each implies that these ions may participate similarly in the operations of other synapses, independent of the neurotransmitter type.(ABSTRACT TRUNCATED AT 400 WORDS).
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Rucher, Guillaume; Cameliere, Lucie; Fendri, Jihene; Abbas, Ahmed; Dupont, Kevin; Kamel, Said; Delcroix, Nicolas; Dupont, Axel; Berger, Ludovic; Manrique, Alain
2018-04-30
The purpose of this study was to assess the impact of positron emission tomography/X-ray computed tomography (PET/CT) acquisition and reconstruction parameters on the assessment of mineralization process in a mouse model of atherosclerosis. All experiments were performed on a dedicated preclinical PET/CT system. CT was evaluated using five acquisition configurations using both a tungsten wire phantom for in-plane resolution assessment and a bar pattern phantom for cross-plane resolution. Furthermore, the radiation dose of these acquisition configurations was calculated. The PET system was assessed using longitudinal line sources to determine the optimal reconstruction parameters by measuring central resolution and its coefficient of variation. An in vivo PET study was performed using uremic ApoE -/- , non-uremic ApoE -/- , and control mice to evaluate optimal PET reconstruction parameters for the detection of sodium [ 18 F]fluoride (Na[ 18 F]F) aortic uptake and for quantitative measurement of Na[ 18 F]F bone influx (Ki) with a Patlak analysis. For CT, the use of 1 × 1 and 2 × 2 binning detector mode increased both in-plane and cross-plane resolution. However, resolution improvement (163 to 62 μm for in-plane resolution) was associated with an important radiation dose increase (1.67 to 32.78 Gy). With PET, 3D-ordered subset expectation maximization (3D-OSEM) algorithm increased the central resolution compared to filtered back projection (1.42 ± 0.35 mm vs. 1.91 ± 0.08, p < 0.001). The use of 3D-OSEM with eight iterations and a zoom factor 2 yielded optimal PET resolution for preclinical study (FWHM = 0.98 mm). These PET reconstruction parameters allowed the detection of Na[ 18 F]F aortic uptake in 3/14 ApoE -/- mice and demonstrated a decreased Ki in uremic ApoE -/- compared to non-uremic ApoE -/- and control mice (p < 0.006). Optimizing reconstruction parameters significantly impacted on the assessment of mineralization process in a preclinical model of accelerated atherosclerosis using Na[ 18 F]F PET. In addition, improving the CT resolution was associated with a dramatic radiation dose increase.
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Neutron and Gamma Imaging for National Security Applications
NASA Astrophysics Data System (ADS)
Hornback, Donald
2017-09-01
The Department of Energy, National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D/NA-22) possesses, in part, the mission to develop technologies in support of nuclear security efforts in coordination with other U.S. government entities, such as the Department of Defense and the Department of Homeland Security. DNN R&D has long supported research in nuclear detection at national labs, universities, and through the small business innovation research (SBIR) program. Research topics supported include advanced detector materials and electronics, detection algorithm development, and advanced gamma/neutron detection systems. Neutron and gamma imaging, defined as the directional detection of radiation as opposed to radiography, provides advanced detection capabilities for the NNSA mission in areas of emergency response, international safeguards, and nuclear arms control treaty monitoring and verification. A technical and programmatic overview of efforts in this field of research will be summarized.
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A compact acousto-optic lens for 2D and 3D femtosecond based 2-photon microscopy
Kirkby, Paul A.; Naga Srinivas, N.K.M.; Silver, R. Angus
2010-01-01
We describe a high speed 3D Acousto-Optic Lens Microscope (AOLM) for femtosecond 2-photon imaging. By optimizing the design of the 4 AO Deflectors (AODs) and by deriving new control algorithms, we have developed a compact spherical AOL with a low temporal dispersion that enables 2-photon imaging at 10-fold lower power than previously reported. We show that the AOLM can perform high speed 2D raster-scan imaging (>150 Hz) without scan rate dependent astigmatism. It can deflect and focus a laser beam in a 3D random access sequence at 30 kHz and has an extended focusing range (>137 μm; 40X 0.8NA objective). These features are likely to make the AOLM a useful tool for studying fast physiological processes distributed in 3D space PMID:20588506
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Seismic Characterization of EGS Reservoirs
NASA Astrophysics Data System (ADS)
Templeton, D. C.; Pyle, M. L.; Matzel, E.; Myers, S.; Johannesson, G.
2014-12-01
To aid in the seismic characterization of Engineered Geothermal Systems (EGS), we enhance the traditional microearthquake detection and location methodologies at two EGS systems. We apply the Matched Field Processing (MFP) seismic imaging technique to detect new seismic events using known discrete microearthquake sources. Events identified using MFP are typically smaller magnitude events or events that occur within the coda of a larger event. Additionally, we apply a Bayesian multiple-event seismic location algorithm, called MicroBayesLoc, to estimate the 95% probability ellipsoids for events with high signal-to-noise ratios (SNR). Such probability ellipsoid information can provide evidence for determining if a seismic lineation could be real or simply within the anticipated error range. We apply this methodology to the Basel EGS data set and compare it to another EGS dataset. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bramer, Lisa M.; Chatterjee, Samrat; Holmes, Aimee E.
Business intelligence problems are particularly challenging due to the use of large volume and high velocity data in attempts to model and explain complex underlying phenomena. Incremental machine learning based approaches for summarizing trends and identifying anomalous behavior are often desirable in such conditions to assist domain experts in characterizing their data. The overall goal of this research is to develop a machine learning algorithm that enables predictive analysis on streaming data, detects changes and anomalies in the data, and can evolve based on the dynamic behavior of the data. Commercial shipping transaction data for the U.S. is used tomore » develop and test a Naïve Bayes model that classifies several companies into lines of businesses and demonstrates an ability to predict when the behavior of these companies changes by venturing into other lines of businesses.« less
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Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro
2018-05-09
Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.
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[Quenched fluorescein: a reference dye for instrument response function of TCSPC].
Pan, Hai-feng; Ding, Jing-xin; Liang, Rong-rong; Tao, Zhan-dong; Liu, Meng-wei; Zhang, San-jun; Xu, Jian-hua
2014-08-01
Measuring the instrument response function (IRF) and fitting by reconvolution algorithms are routines to improve time resolution in fluorescence lifetime measurements. Iodide ions were successfully used to quench the fluorescence of fluorescein in this study. By systematically adding saturated NaI water solution in basic fluorescein solution, the lifetimes of fluorescein were reduced from 4 ns to 24 ps. The quenched lifetime of fluorescein obtained from the analysis of Time-Correlated Single Photon Counting (TCSPC) measurement agrees well with that from femtosecond frequency up-conversion measurement. In time resolved excitation spectra measurements, the IRF should be measured at various detection wavelengths providing scattring materials are used. This study could not only reduce the complexity of IRF measurement, but also avoid the existing color effect in system. This study should have wide applications in time resolved fluorescence spectroscopy and fluorescence lifetime imaging.
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Exploring the CAESAR database using dimensionality reduction techniques
NASA Astrophysics Data System (ADS)
Mendoza-Schrock, Olga; Raymer, Michael L.
2012-06-01
The Civilian American and European Surface Anthropometry Resource (CAESAR) database containing over 40 anthropometric measurements on over 4000 humans has been extensively explored for pattern recognition and classification purposes using the raw, original data [1-4]. However, some of the anthropometric variables would be impossible to collect in an uncontrolled environment. Here, we explore the use of dimensionality reduction methods in concert with a variety of classification algorithms for gender classification using only those variables that are readily observable in an uncontrolled environment. Several dimensionality reduction techniques are employed to learn the underlining structure of the data. These techniques include linear projections such as the classical Principal Components Analysis (PCA) and non-linear (manifold learning) techniques, such as Diffusion Maps and the Isomap technique. This paper briefly describes all three techniques, and compares three different classifiers, Naïve Bayes, Adaboost, and Support Vector Machines (SVM), for gender classification in conjunction with each of these three dimensionality reduction approaches.
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Spectroscopy of an unusual emission line M star
NASA Technical Reports Server (NTRS)
Schneider, Donald P.; Greenstein, Jesse L.; Schmidt, Maarten; Gunn, James E.
1991-01-01
Moderate-resolution spectroscopy of an unusual late-type faint emission-line star, PC 0025 + 0047, is reported. A very strong (greater than 250 A equivalent width) an H-alpha emission line was detected by the present automated line search algorithm. The spectrum was found to have two unresolved emission lines (H-alpha and H-beta) near zero velocity, superposed on the absorption spectrum of a very red M dwarf which has strong K I, and relatively weak bands of TiO. From the weakness of the subordinate lines of Na I (8192 A) and other spectral features, it is inferred that it is definitely a cooler, and probably fainter, analog of LHS 2924. The strength of the emission lines indicates that PC 0025 + 0447 is very young and may be a fading predecessor brown drawf at an estimated M(bol) approaching 14m at a distance of about 60 pc.
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Circadian Rest-Activity Rhythm in Pediatric Type 1 Narcolepsy
Filardi, Marco; Pizza, Fabio; Bruni, Oliviero; Natale, Vincenzo; Plazzi, Giuseppe
2016-01-01
Study Objectives: Pediatric type 1 narcolepsy is often challenging to diagnose and remains largely undiagnosed. Excessive daytime sleepiness, disrupted nocturnal sleep, and a peculiar phenotype of cataplexy are the prominent features. The knowledge available about the regulation of circadian rhythms in affected children is scarce. This study compared circadian rest-activity rhythm and actigraphic estimated sleep measures of children with type 1 narcolepsy versus healthy controls. Methods: Twenty-two drug-naïve type 1 narcolepsy children and 21 age- and sex- matched controls were monitored for seven days during the school week by actigraphy. Circadian activity rhythms were analyzed through functional linear modeling; nocturnal and diurnal sleep measures were estimated from activity using a validated algorithm. Results: Children with type 1 narcolepsy presented an altered rest-activity rhythm characterized by enhanced motor activity throughout the night and blunted activity in the first afternoon. No difference was found between children with type 1 narcolepsy and controls in the timing of the circadian phase. Actigraphic sleep measures showed good discriminant capabilities in assessing type 1 narcolepsy nycthemeral disruption. Conclusions: Actigraphy reliably renders the nycthemeral disruption typical of narcolepsy type 1 in drug-naïve children with recent disease onset, indicating the sensibility of actigraphic assessment in the diagnostic work-up of childhood narcolepsy type 1. Citation: Filardi M, Pizza F, Bruni O, Natale V, Plazzi G. Circadian rest-activity rhythm in pediatric type 1 narcolepsy. SLEEP 2016;39(6):1241–1247. PMID:27091539
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Mattson, Eric C; Unger, Miriam; Clède, Sylvain; Lambert, François; Policar, Clotilde; Imtiaz, Asher; D'Souza, Roshan; Hirschmugl, Carol J
2013-10-07
Advancements in widefield infrared spectromicroscopy have recently been demonstrated following the commissioning of IRENI (InfraRed ENvironmental Imaging), a Fourier Transform infrared (FTIR) chemical imaging beamline at the Synchrotron Radiation Center. The present study demonstrates the effects of magnification, spatial oversampling, spectral pre-processing and deconvolution, focusing on the intracellular detection and distribution of an exogenous metal tris-carbonyl derivative 1 in a single MDA-MB-231 breast cancer cell. We demonstrate here that spatial oversampling for synchrotron-based infrared imaging is critical to obtain accurate diffraction-limited images at all wavelengths simultaneously. Resolution criteria and results from raw and deconvoluted images for two Schwarzschild objectives (36×, NA 0.5 and 74×, NA 0.65) are compared to each other and to prior reports for raster-scanned, confocal microscopes. The resolution of the imaging data can be improved by deconvolving the instrumental broadening that is determined with the measured PSFs, which is implemented with GPU programming architecture for fast hyperspectral processing. High definition, rapidly acquired, FTIR chemical images of respective spectral signatures of the cell 1 and shows that 1 is localized next to the phosphate- and Amide-rich regions, in agreement with previous infrared and luminescence studies. The infrared image contrast, localization and definition are improved after applying proven spectral pre-processing (principal component analysis based noise reduction and RMie scattering correction algorithms) to individual pixel spectra in the hyperspectral cube.
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MATLAB implementation of a dynamic clamp with bandwidth >125 KHz capable of generating INa at 37°C
Clausen, Chris; Valiunas, Virginijus; Brink, Peter R.; Cohen, Ira S.
2012-01-01
We describe the construction of a dynamic clamp with bandwidth >125 KHz that utilizes a high performance, yet low cost, standard home/office PC interfaced with a high-speed (16 bit) data acquisition module. High bandwidth is achieved by exploiting recently available software advances (code-generation technology, optimized real-time kernel). Dynamic-clamp programs are constructed using Simulink, a visual programming language. Blocks for computation of membrane currents are written in the high-level matlab language; no programming in C is required. The instrument can be used in single- or dual-cell configurations, with the capability to modify programs while experiments are in progress. We describe an algorithm for computing the fast transient Na+ current (INa) in real time, and test its accuracy and stability using rate constants appropriate for 37°C. We then construct a program capable of supplying three currents to a cell preparation: INa, the hyperpolarizing-activated inward pacemaker current (If), and an inward-rectifier K+ current (IK1). The program corrects for the IR drop due to electrode current flow, and also records all voltages and currents. We tested this program on dual patch-clamped HEK293 cells where the dynamic clamp controls a current-clamp amplifier and a voltage-clamp amplifier controls membrane potential, and current-clamped HEK293 cells where the dynamic clamp produces spontaneous pacing behavior exhibiting Na+ spikes in otherwise passive cells. PMID:23224681
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Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang
2017-02-15
Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.
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2006-04-01
b. Principles of Decontamination Operations. Decontaminate immediately for an agent on the skin . Perform higher levels of decontamination as a...the mask and hood with paper towels or rags. NOTE: Cool, soapy water is not as effective for removing contamination, but it can be used if you scrub ...N/A N/A 5 N/A Sponge, cellulose II Each As required N/A N/A N/A N/A 2 N/A 4 6 Brush, scrub II Each As required N/A N/A N/A N/A 2 N/A 2 N/A Towels
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2002-02-19
File name :DSC_0028.JPG File size :2.8MB(2950833Bytes) Date taken :2002/02/19 09:49:01 Image size :3008 x 2000 Resolution :300 x 300 dpi Number of bits :8bit/channel Protection attribute :Off Hide Attribute :Off Camera ID :N/A Camera :NIKON D100 Quality mode :N/A Metering mode :Matrix Exposure mode :Shutter priority Speed light :Yes Focal length :24 mm Shutter speed :1/60second Aperture :F3.5 Exposure compensation :0 EV White Balance :N/A Lens :N/A Flash sync mode :N/A Exposure difference :N/A Flexible program :N/A Sensitivity :N/A Sharpening :N/A Image Type :Color Color Mode :N/A Hue adjustment :N/A Saturation Control :N/A Tone compensation :N/A Latitude(GPS) :N/A Longitude(GPS) :N/A Altitude(GPS) :N/A
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2002-02-24
File name :DSC_0047.JPG File size :2.8MB(2931574Bytes) Date taken :2002/02/24 10:06:57 Image size :3008 x 2000 Resolution :300 x 300 dpi Number of bits :8bit/channel Protection attribute :Off Hide Attribute :Off Camera ID :N/A Camera :NIKON D100 Quality mode :N/A Metering mode :Matrix Exposure mode :Shutter priority Speed light :Yes Focal length :24 mm Shutter speed :1/180second Aperture :F20.0 Exposure compensation :+0.3 EV White Balance :N/A Lens :N/A Flash sync mode :N/A Exposure difference :N/A Flexible program :N/A Sensitivity :N/A Sharpening :N/A Image Type :Color Color Mode :N/A Hue adjustment :N/A Saturation Control :N/A Tone compensation :N/A Latitude(GPS) :N/A Longitude(GPS) :N/A Altitude(GPS) :N/A
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Sustainability Product Properties in Building Information Models
2012-09-01
Covrlhovses, Oota c enters, Hospitals IAcvle care and Children’s), Hotels/ Mote ~, Hovses of Worship, K- 12 Schools, Med1cal Offic&s, Offices, Restdence Holts...RenewableContent n/a n/a 70 RenewableMaterial n/a n/a Cotton BiobasedContent n/a n/a 70 BiobasedMaterial n/a n/a Cotton RawMaterialLocation n/a n/a
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Study of Cetane Properties of ATJ Blends Based on World Survey of Jet Fuels
2016-01-28
49.84 N/A N/A N/A 46.92 N/A N/A N/A 12 (100% Syn.) 1 57.79 N/A N/A N/A 53.48 N/A N/A N/A a - Conventional petroleum based jet fuel; b - Oil Shale ...Australia (% Nitrogen content unknown) c - Oil Shale , Australia (Low Nitrogen); d - Oil Shale , Australia (High Nitrogen) U/A – Unavailable in PQIS...fuel b - Oil Shale , Australia (% Nitrogen content unknown) c - Oil Shale , Australia (Low Nitrogen) d - Oil Shale , Australia (High Nitrogen) U/A
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Formation of Si grains from a NaSi melt prepared by reaction of SiO2 and Na
NASA Astrophysics Data System (ADS)
Yamane, Hisanori; Morito, Haruhiko; Uchikoshi, Masahito
2013-08-01
A mixture of Na2SiO3 and NaSi was found to be formed by reaction of SiO2 and Na at 650 °C as follows: 5Na+3SiO2→2Na2SiO3+NaSi. Single crystals of NaSi were grown by cooling the mixture of Na2SiO3 and NaSi with an excess amount of Na from 850 °C, and polycrystalline Si was obtained by vaporization of Na from the crystals. Coarse grains of Si were also crystallized by Na evaporation after the formation of Na2SiO3 and Si-dissolved liquid Na at 830 °C. The Si grains were collected by washing the product with water. The yield of the Si grains was 85% of the ideal amount expected from the reaction.
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Condition of Si crystal formation by vaporizing Na from NaSi
NASA Astrophysics Data System (ADS)
Morito, Haruhiko; Karahashi, Taiki; Yamane, Hisanori
2012-09-01
NaSi was heated at various Na vapor pressures (pNa 0.1-1.2 atm) and temperatures (973-1173 K) to investigate the condition of Si crystal formation from NaSi by Na evaporation. Silicon single crystals 1-3 mm in diameter were grown by evaporation of Na from Na-Si melt at 1173 K and pNa=0.74 atm.
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NASA Technical Reports Server (NTRS)
Remsberg, E. E.; Marshall, B. T.; Garcia-Comas, M.; Krueger, D.; Lingenfelser, G. S.; Martin-Torres, J.; Mlynczak, M. G.; Russell, J. M., III; Smith, A. K.; Zhao, Y.;
2008-01-01
The quality of the retrieved temperature-versus-pressure (or T(p)) profiles is described for the middle atmosphere for the publicly available Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) Version 1.07 (V1.07) data set. The primary sources of systematic error for the SABER results below about 70 km are (1) errors in the measured radiances, (2) biases in the forward model, and (3) uncertainties in the corrections for ozone and in the determination of the reference pressure for the retrieved profiles. Comparisons with other correlative data sets indicate that SABER T(p) is too high by 1-3 K in the lower stratosphere but then too low by 1 K near the stratopause and by 2 K in the middle mesosphere. There is little difference between the local thermodynamic equilibrium (LTE) algorithm results below about 70 km from V1.07 and V1.06, but there are substantial improvements/differences for the non-LTE results of V1.07 for the upper mesosphere and lower thermosphere (UMLT) region. In particular, the V1.07 algorithm uses monthly, diurnally averaged CO2 profiles versus latitude from the Whole Atmosphere Community Climate Model. This change has improved the consistency of the character of the tides in its kinetic temperature (T(sub k)). The T(sub k) profiles agree with UMLT values obtained from ground-based measurements of column-averaged OH and O2 emissions and of the Na lidar returns, at least within their mutual uncertainties. SABER T(sub k) values obtained near the mesopause with its daytime algorithm also agree well with the falling sphere climatology at high northern latitudes in summer. It is concluded that the SABER data set can be the basis for improved, diurnal-to-interannual-scale temperatures for the middle atmosphere and especially for its UMLT region.
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Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S
2018-02-01
Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to detect the dynamic muscle fatigue conditions. Copyright © 2017 Elsevier B.V. All rights reserved.
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Evaluation of PET Imaging Resolution Using 350 mu{m} Pixelated CZT as a VP-PET Insert Detector
NASA Astrophysics Data System (ADS)
Yin, Yongzhi; Chen, Ximeng; Li, Chongzheng; Wu, Heyu; Komarov, Sergey; Guo, Qingzhen; Krawczynski, Henric; Meng, Ling-Jian; Tai, Yuan-Chuan
2014-02-01
A cadmium-zinc-telluride (CZT) detector with 350 μm pitch pixels was studied in high-resolution positron emission tomography (PET) imaging applications. The PET imaging system was based on coincidence detection between a CZT detector and a lutetium oxyorthosilicate (LSO)-based Inveon PET detector in virtual-pinhole PET geometry. The LSO detector is a 20 ×20 array, with 1.6 mm pitches, and 10 mm thickness. The CZT detector uses ac 20 ×20 ×5 mm substrate, with 350 μm pitch pixelated anodes and a coplanar cathode. A NEMA NU4 Na-22 point source of 250 μm in diameter was imaged by this system. Experiments show that the image resolution of single-pixel photopeak events was 590 μm FWHM while the image resolution of double-pixel photopeak events was 640 μm FWHM. The inclusion of double-pixel full-energy events increased the sensitivity of the imaging system. To validate the imaging experiment, we conducted a Monte Carlo (MC) simulation for the same PET system in Geant4 Application for Emission Tomography. We defined LSO detectors as a scanner ring and 350 μm pixelated CZT detectors as an insert ring. GATE simulated coincidence data were sorted into an insert-scanner sinogram and reconstructed. The image resolution of MC-simulated data (which did not factor in positron range and acolinearity effect) was 460 μm at FWHM for single-pixel events. The image resolutions of experimental data, MC simulated data, and theoretical calculation are all close to 500 μm FWHM when the proposed 350 μm pixelated CZT detector is used as a PET insert. The interpolation algorithm for the charge sharing events was also investigated. The PET image that was reconstructed using the interpolation algorithm shows improved image resolution compared with the image resolution without interpolation algorithm.
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Developing robust arsenic awareness prediction models using machine learning algorithms.
Singh, Sushant K; Taylor, Robert W; Rahman, Mohammad Mahmudur; Pradhan, Biswajeet
2018-04-01
Arsenic awareness plays a vital role in ensuring the sustainability of arsenic mitigation technologies. Thus far, however, few studies have dealt with the sustainability of such technologies and its associated socioeconomic dimensions. As a result, arsenic awareness prediction has not yet been fully conceptualized. Accordingly, this study evaluated arsenic awareness among arsenic-affected communities in rural India, using a structured questionnaire to record socioeconomic, demographic, and other sociobehavioral factors with an eye to assessing their association with and influence on arsenic awareness. First a logistic regression model was applied and its results compared with those produced by six state-of-the-art machine-learning algorithms (Support Vector Machine [SVM], Kernel-SVM, Decision Tree [DT], k-Nearest Neighbor [k-NN], Naïve Bayes [NB], and Random Forests [RF]) as measured by their accuracy at predicting arsenic awareness. Most (63%) of the surveyed population was found to be arsenic-aware. Significant arsenic awareness predictors were divided into three types: (1) socioeconomic factors: caste, education level, and occupation; (2) water and sanitation behavior factors: number of family members involved in water collection, distance traveled and time spent for water collection, places for defecation, and materials used for handwashing after defecation; and (3) social capital and trust factors: presence of anganwadi and people's trust in other community members, NGOs, and private agencies. Moreover, individuals' having higher social network positively contributed to arsenic awareness in the communities. Results indicated that both the SVM and the RF algorithms outperformed at overall prediction of arsenic awareness-a nonlinear classification problem. Lower-caste, less educated, and unemployed members of the population were found to be the most vulnerable, requiring immediate arsenic mitigation. To this end, local social institutions and NGOs could play a crucial role in arsenic awareness and outreach programs. Use of SVM or RF or a combination of the two, together with use of a larger sample size, could enhance the accuracy of arsenic awareness prediction. Copyright © 2018 Elsevier Ltd. All rights reserved.
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NMR studies on Na+ transport in Synechococcus PCC 6311
NASA Technical Reports Server (NTRS)
Nitschmann, W. H.; Packer, L.
1992-01-01
The freshwater cyanobacterium Synechococcus PCC 6311 is able to adapt to grow after sudden exposure to salt (NaCl) stress. We have investigated the mechanism of Na+ transport in these cells during adaptation to high salinity. Na+ influx under dark aerobic conditions occurred independently of delta pH or delta psi across the cytoplasmic membrane, ATPase activity, and respiratory electron transport. These findings are consistent with the existence of Na+/monovalent anion cotransport or simultaneous Na+/H+ +anion/OH- exchange. Na+ influx was dependent on Cl-, Br-, NO3-, or NO2-. No Na+ uptake occurred after addition of NaI, NaHCO3, or Na2SO4. Na+ extrusion was absolutely dependent on delta pH and on an ATPase activity and/or on respiratory electron transport. This indicates that Na+ extrusion via Na+/H+ exchange is driven by primary H+ pumps in the cytoplasmic membrane. Cells grown for 4 days in 0.5 m NaCl medium, "salt-grown cells," differ from control cells by a lower maximum velocity of Na+ influx and by lower steady-state ratios of [Na+]in/[Na+]out. These results indicate that cells grown in high-salt medium increase their capacity to extrude Na+. During salt adaptation Na+ extrusion driven by respiratory electron transport increased from about 15 to 50%.
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Lu, Fang-Min
2017-01-01
Decades ago, it was proposed that Na transport in cardiac myocytes is modulated by large changes in cytoplasmic Na concentration within restricted subsarcolemmal spaces. Here, we probe this hypothesis for Na/K pumps by generating constitutive transsarcolemmal Na flux with the Na channel opener veratridine in whole-cell patch-clamp recordings. Using 25 mM Na in the patch pipette, pump currents decay strongly during continuous activation by extracellular K (τ, ∼2 s). In contradiction to depletion hypotheses, the decay becomes stronger when pump currents are decreased by hyperpolarization. Na channel currents are nearly unchanged by pump activity in these conditions, and conversely, continuous Na currents up to 0.5 nA in magnitude have negligible effects on pump currents. These outcomes are even more pronounced using 50 mM Li as a cytoplasmic Na congener. Thus, the Na/K pump current decay reflects mostly an inactivation mechanism that immobilizes Na/K pump charge movements, not cytoplasmic Na depletion. When channel currents are increased beyond 1 nA, models with unrestricted subsarcolemmal diffusion accurately predict current decay (τ ∼15 s) and reversal potential shifts observed for Na, Li, and K currents through Na channels opened by veratridine, as well as for Na, K, Cs, Li, and Cl currents recorded in nystatin-permeabilized myocytes. Ion concentrations in the pipette tip (i.e., access conductance) track without appreciable delay the current changes caused by sarcolemmal ion flux. Importantly, cytoplasmic mixing volumes, calculated from current decay kinetics, increase and decrease as expected with osmolarity changes (τ >30 s). Na/K pump current run-down over 20 min reflects a failure of pumps to recover from inactivation. Simulations reveal that pump inactivation coupled with Na-activated recovery enhances the rapidity and effectivity of Na homeostasis in cardiac myocytes. In conclusion, an autoregulatory mechanism enhances cardiac Na/K pump activity when cytoplasmic Na rises and suppresses pump activity when cytoplasmic Na declines. PMID:28606910
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Concentration dependence of Li+/Na+ diffusion in manganese hexacyanoferrates
NASA Astrophysics Data System (ADS)
Takachi, Masamitsu; Fukuzumi, Yuya; Moritomo, Yutaka
2016-06-01
Manganese hexacyanoferrates (Mn-HCFs) with a jungle-gym-type structure are promising cathode materials for Li+/Na+ secondary batteries (LIBs/SIBs). Here, we investigated the diffusion constants D Li/D Na of Li+/Na+ against the Li+/Na+ concentration x Na/x Li and temperature (T) of A 1.32Mn[Fe(CN)6]0.833.6H2O (A = Li and Na). We evaluated the activation energy E\\text{a}\\text{Li}/E\\text{a}\\text{Na} of D Li/D Na against x Na/x Li. We found that E\\text{a}\\text{Na} steeply increases with x Na from 0.41 eV at x Na = 0.69 to 0.7 eV at 1.1. The increase in E\\text{a}\\text{Na} is ascribed to the occupancy effect of the Na+ site. The increase in E\\text{a}\\text{Li} is suppressed, probably because the number of Li+ sites is three times that of Na+ sites.
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Metal Residue Deposition from Military Pyrotechnic Devices and Field Sampling Guidance
2012-05-01
given NA 0.002 NA NA Chromium Oxide 1308-38-9 NA NA NA 0.015 Cobalt Naphthenate 61789-51-3 NA NA NA 0.017 Copper Oxide Black 1317-38-0 NA 1.32 NA...the whistling booby trap simulators included 73% potassium perchlorate, 24% gallic acid , and 3 % red gum (McIntyre 1980). Whereas the booby-trap...M21 Flash Artillery Simulator 50 3785.8 2/5/10 All – indicates the entire volume of stained snow was removed . MI – multi-increment. Rep
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Spectral anomaly methods for aerial detection using KUT nuisance rejection
NASA Astrophysics Data System (ADS)
Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.
2015-06-01
This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.
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Roshani, G H; Karami, A; Khazaei, A; Olfateh, A; Nazemi, E; Omidi, M
2018-05-17
Gamma ray source has very important role in precision of multi-phase flow metering. In this study, different combination of gamma ray sources (( 133 Ba- 137 Cs), ( 133 Ba- 60 Co), ( 241 Am- 137 Cs), ( 241 Am- 60 Co), ( 133 Ba- 241 Am) and ( 60 Co- 137 Cs)) were investigated in order to optimize the three-phase flow meter. Three phases were water, oil and gas and the regime was considered annular. The required data was numerically generated using MCNP-X code which is a Monte-Carlo code. Indeed, the present study devotes to forecast the volume fractions in the annular three-phase flow, based on a multi energy metering system including various radiation sources and also one NaI detector, using a hybrid model of artificial neural network and Jaya Optimization algorithm. Since the summation of volume fractions is constant, a constraint modeling problem exists, meaning that the hybrid model must forecast only two volume fractions. Six hybrid models associated with the number of used radiation sources are designed. The models are employed to forecast the gas and water volume fractions. The next step is to train the hybrid models based on numerically obtained data. The results show that, the best forecast results are obtained for the gas and water volume fractions of the system including the ( 241 Am- 137 Cs) as the radiation source. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Automatic detection of freezing of gait events in patients with Parkinson's disease.
Tripoliti, Evanthia E; Tzallas, Alexandros T; Tsipouras, Markos G; Rigas, George; Bougia, Panagiota; Leontiou, Michael; Konitsiotis, Spiros; Chondrogiorgi, Maria; Tsouli, Sofia; Fotiadis, Dimitrios I
2013-04-01
The aim of this study is to detect freezing of gait (FoG) events in patients suffering from Parkinson's disease (PD) using signals received from wearable sensors (six accelerometers and two gyroscopes) placed on the patients' body. For this purpose, an automated methodology has been developed which consists of four stages. In the first stage, missing values due to signal loss or degradation are replaced and then (second stage) low frequency components of the raw signal are removed. In the third stage, the entropy of the raw signal is calculated. Finally (fourth stage), four classification algorithms have been tested (Naïve Bayes, Random Forests, Decision Trees and Random Tree) in order to detect the FoG events. The methodology has been evaluated using several different configurations of sensors in order to conclude to the set of sensors which can produce optimal FoG episode detection. Signals recorded from five healthy subjects, five patients with PD who presented the symptom of FoG and six patients who suffered from PD but they do not present FoG events. The signals included 93 FoG events with 405.6s total duration. The results indicate that the proposed methodology is able to detect FoG events with 81.94% sensitivity, 98.74% specificity, 96.11% accuracy and 98.6% area under curve (AUC) using the signals from all sensors and the Random Forests classification algorithm. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
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Shamir, Reuben R; Dolber, Trygve; Noecker, Angela M; Walter, Benjamin L; McIntyre, Cameron C
2015-01-01
Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization. Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication. Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: (1) information retrieval; (2) visualization of treatment, and; (3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest. Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P < 0.05) and their effect on outcomes was of similar magnitude to that of DBS. Using those results, the combined machine learning algorithms were able to accurately predict 86% (12/14) of the motor improvement scores at one year after surgery. Using patient-specific details, an appropriately parameterized CDSS could help select theoretically optimal DBS parameter settings and medication dosages that have potential to improve the clinical management of PD patients. Copyright © 2015 Elsevier Inc. All rights reserved.
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Detecting Seismic Events Using a Supervised Hidden Markov Model
NASA Astrophysics Data System (ADS)
Burks, L.; Forrest, R.; Ray, J.; Young, C.
2017-12-01
We explore the use of supervised hidden Markov models (HMMs) to detect seismic events in streaming seismogram data. Current methods for seismic event detection include simple triggering algorithms, such as STA/LTA and the Z-statistic, which can lead to large numbers of false positives that must be investigated by an analyst. The hypothesis of this study is that more advanced detection methods, such as HMMs, may decreases false positives while maintaining accuracy similar to current methods. We train a binary HMM classifier using 2 weeks of 3-component waveform data from the International Monitoring System (IMS) that was carefully reviewed by an expert analyst to pick all seismic events. Using an ensemble of simple and discrete features, such as the triggering of STA/LTA, the HMM predicts the time at which transition occurs from noise to signal. Compared to the STA/LTA detection algorithm, the HMM detects more true events, but the false positive rate remains unacceptably high. Future work to potentially decrease the false positive rate may include using continuous features, a Gaussian HMM, and multi-class HMMs to distinguish between types of seismic waves (e.g., P-waves and S-waves). Acknowledgement: Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.SAND No: SAND2017-8154 A
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Response of saliva Na/K ratio to changing Na supply of lactating cows under tropical conditions.
Thiangtum, Wandee; Schonewille, J Thomas; Verstegen, Martin Wa; Arsawakulsudhi, Supot; Rukkwamsuk, Theera; Hendriks, Wouter H
2017-06-01
Factorial determination of the sodium (Na) requirement of heat-stressed lactating cows is hindered by accurate estimates of the Na losses through sweat. Direct studies, therefore, may be needed requiring information on the time course of healthy animals to become Na depleted and the subsequent rate of repletion. The rate of Na depletion and subsequent rate of Na repletion with two levels of dietary Na to lactating dairy cows housed under tropical conditions were investigated using the salivary Na/K. The 12 lactating cows (salivary Na/K ratio 14.6) rapidly developed clinical signs of Na deficiency, including pica, polyuria and polydipsia, reduced body weight and reduced milk yield when fed a low-Na ration (0.33 g kg -1 dry matter (DM)) for 3 weeks. Deficiency symptoms were associated with a rapid decrease in salivary Na/K ratio to <4.3 from 7 to 21 days. Subsequent repletion of the cows with NaCl to a ration concentration of 1.1 or 1.6 g Na kg -1 DM for 5 weeks did not restore salivary Na/K ratio to values of >6. A daily Na intake of heat-stressed lactating cows to a ration intake of 1.6 g Na kg -1 DM was insufficient to restore Na deficiency. One week was sufficient to deplete heat-stressed lactating cows of Na, allowing for rapid dose-response studies utilizing the salivary Na/K ratio as a parameter for Na status of cows under tropical conditions. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.
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[Effects of different salt and alkali stresses on ion distribution in Red globe/Beta grapevines].
Du, Yuan-peng; Jin, Xue-juan; Guo, Shu-hua; Fu, Qing-qing; Zhai, Heng
2015-06-01
The potted Red globe/Beta grapevines were selected to irrigated with NaCl, Na2SO4, NaHCO3, NH4Cl, (NH4)2SO4. Hence, the ions which induced leaf etiolation were screened and the impacts of different salt and alkali on ion distribution in different organs of grapevines were investigated. It was found that NaHCO3 exerted the greatest effects on grapevines, leaf etiolation at 14 days after treatment. By contrast, NaCl and NH4Cl treatments induced leaf etiolation at 28 days after treatment. The Na+ content in all the detected organs were significantly increased under NaHCO3 and NaCl treatment, and Na+ content in root under NaHCO3 treatment was 6.4 times as that in control root. NaHCO3 and NaCl treatments significantly decreased K+ content in the organs with the exception of leaf. NaHCO3 treatment significantly decreased K/Na in different organs, which declined to 0.1 in root. By contrast, NaCl treatment significantly decreased K/Na in the detected organs with exception of stem. Besides, the transport of Ca2+, Mg2+, Fe2+ to aboveground organs was significantly decreased by NaHCO3 and NaCl treatments. K/Na ratio in the detected organs were decreased under NH4Cl, (NH4) 2SO4 and Na2SO4 treatments, especially under NH4 Cl treatment. Taken together, NaHCO3 was the primary factor resulting in leaf etiolation, followed by NaCl and NH4Cl, while (NH4) 2SO4 and Na2SO4 produced impacts.
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Thermal decomposition of sodium amide, NaNH2, and sodium amide hydroxide composites, NaNH2-NaOH.
Jepsen, Lars H; Wang, Peikun; Wu, Guotao; Xiong, Zhitao; Besenbacher, Flemming; Chen, Ping; Jensen, Torben R
2016-09-14
Sodium amide, NaNH 2 , has recently been shown to be a useful catalyst to decompose NH 3 into H 2 and N 2 , however, sodium hydroxide is omnipresent and commercially available NaNH 2 usually contains impurities of NaOH (<2%). The thermal decomposition of NaNH 2 and NaNH 2 -NaOH composites is systematically investigated and discussed. NaNH 2 is partially dissolved in NaOH at T > 100 °C, forming a non-stoichiometric solid solution of Na(OH) 1-x (NH 2 ) x (0 < x < ∼0.30), which crystallizes in an orthorhombic unit cell with the space group P2 1 2 1 2 1 determined by synchrotron powder X-ray diffraction. The composite xNaNH 2 -(1 - x)NaOH (∼0.70 < x < 0.72) shows a lowered melting point, ∼160 °C, compared to 200 and 318 °C for neat NaNH 2 and NaOH, respectively. We report that 0.36 mol of NH 3 per mol of NaNH 2 is released below 400 °C during heating in an argon atmosphere, initiated at its melting point, T = 200 °C, possibly due to the formation of the mixed sodium amide imide solid solution. Furthermore, NaOH reacts with NaNH 2 at elevated temperatures and provides the release of additional NH 3 .
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Babsky, Andriy M; Topper, Stephen; Zhang, Hong; Gao, Yong; James, Judy R; Hekmatyar, Shahryar K; Bansal, Navin
2008-03-01
The mechanism of water and sodium apparent diffusion coefficient (ADC) changes in rat skeletal muscle during global ischemia was examined by in vivo 1H and 23Na magnetic resonance spectroscopy (MRS). The ADCs of Na+ and water are expected to have similar characteristics because sodium is present as an aqua-cation in tissue. The shift reagent, TmDOTP5(-), was used to separate intra- and extracellular sodium (Na+i and Na+e, respectively) signals. Water, total tissue sodium (Na+t), Na+i, and Na+e ADCs were measured before and 1, 2, 3, and 4 hr after ischemia. Contrary to the general perception, Na+i and Na+e ADCs were identical before ischemia. Thus, ischemia-induced changes in Na+e ADC cannot be explained by a simple change in the size of relative intracellular or extracellular space. Na+t and Na+e ADCs decreased after 2-4 hr of ischemia, while water and Na+i ADC remained unchanged. The correlation between Na+t and Na+e ADCs was observed because of high Na+e concentration. Similarly, the correlation between water and Na+i ADCs was observed because cells occupy 80% of the tissue space in the skeletal muscle. Ischemia also caused an increase in the Na+i and an equal decrease in Na+e signal intensity due to cessation of Na+/K+-ATPase function. (c) 2008 Wiley-Liss, Inc.
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Reconstruction of multiple-pinhole micro-SPECT data using origin ensembles.
Lyon, Morgan C; Sitek, Arkadiusz; Metzler, Scott D; Moore, Stephen C
2016-10-01
The authors are currently developing a dual-resolution multiple-pinhole microSPECT imaging system based on three large NaI(Tl) gamma cameras. Two multiple-pinhole tungsten collimator tubes will be used sequentially for whole-body "scout" imaging of a mouse, followed by high-resolution (hi-res) imaging of an organ of interest, such as the heart or brain. Ideally, the whole-body image will be reconstructed in real time such that data need only be acquired until the area of interest can be visualized well-enough to determine positioning for the hi-res scan. The authors investigated the utility of the origin ensemble (OE) algorithm for online and offline reconstructions of the scout data. This algorithm operates directly in image space, and can provide estimates of image uncertainty, along with reconstructed images. Techniques for accelerating the OE reconstruction were also introduced and evaluated. System matrices were calculated for our 39-pinhole scout collimator design. SPECT projections were simulated for a range of count levels using the MOBY digital mouse phantom. Simulated data were used for a comparison of OE and maximum-likelihood expectation maximization (MLEM) reconstructions. The OE algorithm convergence was evaluated by calculating the total-image entropy and by measuring the counts in a volume-of-interest (VOI) containing the heart. Total-image entropy was also calculated for simulated MOBY data reconstructed using OE with various levels of parallelization. For VOI measurements in the heart, liver, bladder, and soft-tissue, MLEM and OE reconstructed images agreed within 6%. Image entropy converged after ∼2000 iterations of OE, while the counts in the heart converged earlier at ∼200 iterations of OE. An accelerated version of OE completed 1000 iterations in <9 min for a 6.8M count data set, with some loss of image entropy performance, whereas the same dataset required ∼79 min to complete 1000 iterations of conventional OE. A combination of the two methods showed decreased reconstruction time and no loss of performance when compared to conventional OE alone. OE-reconstructed images were found to be quantitatively and qualitatively similar to MLEM, yet OE also provided estimates of image uncertainty. Some acceleration of the reconstruction can be gained through the use of parallel computing. The OE algorithm is useful for reconstructing multiple-pinhole SPECT data and can be easily modified for real-time reconstruction.
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Chittavong, Malavanh; Jansson, Anna; Lindberg, Jan Erik
2013-10-01
Thirty castrated male Moo Lath pigs (6-8 weeks of age) were used in a 15-week growth trial to study the effect of high dietary sodium chloride (NaCl) content on feed and water intake, performance, sodium (Na) and potassium (K) balance, and plasma aldosterone concentration. The pigs were randomly allocated (ten per treatment) to diets containing 0.24 % Na (Na0.24), 0.28 % Na (Na0.28), and 0.32 % Na (Na0.32) per kg diet. Feed and water was provided ad libitum, and water consumption, feed offered, and feed residues were recorded daily. Every third week, the pigs were weighed, blood samples were collected, and a 3-day total collection of urine and feces was performed. Water intake was higher (P = 0.001) in pigs fed with diets Na0.28 (3.7 L/day) and Na0.32 (3.9 L/day) than in pigs fed with diet Na0.24 (3.4 L/day), and dry matter (DM) intake was higher on diet Na0.32 (P = 0.041) than on the other diets. The average daily body weight (BW) gain was higher on diet Na0.32 than on the other diets (P = 0.031). The feed conversion ratio (in kilogram feed DM to kilogram BW gain) was 4.6, 4.6, and 4.1 on treatments Na0.24, Na0.28, and Na0.32, respectively (P = 0.14). The highest Na balance was observed on diet Na0.32 followed by diets Na0.28 and Na0.24 (P < 0.001), while there was no treatment-related pattern for the K balance. The Na/K ratio in feces and urine increased (P < 0.001), and the K/Na ratio in feces (P < 0.001) decreased with increasing Na content in the diet. Plasma aldosterone concentration decreased (P < 0.001) with increasing dietary content of Na. These results indicate that high NaCl intake and free access to water will increase Na balance but do not negatively influence feed intake and performance of growing local pigs.
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Metal Residue Deposition from Military Pyrotechnic Devices and Field Sampling Guidance
2012-05-01
0.002 26.4 NA 0.082 Cerium none given NA 0.002 NA NA Chromium Oxide 1308-38-9 NA NA NA 0.015 Cobalt Naphthenate 61789-51-3 NA NA NA 0.017 Copper...the 1980s, the constituents in the whistling booby trap simulators included 73% potassium perchlorate, 24% gallic acid , and 3 % red gum (McIntyre...Test 3, MI snow sample, Rep 3 M21 Flash Artillery Simulator 50 3785.8 2/5/10 All – indicates the entire volume of stained snow was removed . MI
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Thermal Aspects of Future Spacecraft Thermal Management Systems.
1986-07-01
eutectic salt ) (278 278) (168) (n-a n-a) (0.78 0.78) (2290 2290) (inexpensive))) (95.4 % NaNO3 - 4.6 % NaCl) (inorganic eutectic salt ) (297 297) (178) (n-a...n-a) (0.69 0.69) (2260 2260) (inexpensive))) (69.9 % CaC12 - 30.1 % NaCI) (inorganic eutectic salt ) (490 490) (233) (n-a n-a) (4 4) (2400 2400...inexpensive))) (46.2 % KC1 - 29.9 X CaCI2 -23.9 X NaCi) (inorganic eutectic salt ) (515 515) (265) (n-a n-a) (3.8 3.8) (2160 2160) (inexpensive))) (79
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Reif, Roberto; Baran, Utku; Wang, Ruikang K
2014-07-01
Optical coherence tomography (OCT) is a technique that allows for the three-dimensional (3D) imaging of small volumes of tissue (a few millimeters) with high resolution (∼10 μm). Optical microangiography (OMAG) is a method of processing OCT data, which allows for the extraction of the tissue vasculature with capillary resolution from the OCT images. Cross-sectional B-frame OMAG images present the location of the patent blood vessels; however, the signal-to-noise-ratio of these images can be affected by several factors such as the quality of the OCT system and the tissue motion artifact. This background noise can appear in the en face projection view image. In this work we propose to develop a binary mask that can be applied on the cross-sectional B-frame OMAG images, which will reduce the background noise while leaving the signal from the blood vessels intact. The mask is created by using a naïve Bayes (NB) classification algorithm trained with a gold standard image which is manually segmented by an expert. The masked OMAG images present better contrast for binarizing the image and quantifying the result without the influence of noise. The results are compared with a previously developed frequency rejection filter (FRF) method which is applied on the en face projection view image. It is demonstrated that both the NB and FRF methods provide similar vessel length fractions. The advantage of the NB method is that the results are applicable in 3D and that its use is not limited to periodic motion artifacts.
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BNDB - the Biochemical Network Database.
Küntzer, Jan; Backes, Christina; Blum, Torsten; Gerasch, Andreas; Kaufmann, Michael; Kohlbacher, Oliver; Lenhof, Hans-Peter
2007-10-02
Technological advances in high-throughput techniques and efficient data acquisition methods have resulted in a massive amount of life science data. The data is stored in numerous databases that have been established over the last decades and are essential resources for scientists nowadays. However, the diversity of the databases and the underlying data models make it difficult to combine this information for solving complex problems in systems biology. Currently, researchers typically have to browse several, often highly focused, databases to obtain the required information. Hence, there is a pressing need for more efficient systems for integrating, analyzing, and interpreting these data. The standardization and virtual consolidation of the databases is a major challenge resulting in a unified access to a variety of data sources. We present the Biochemical Network Database (BNDB), a powerful relational database platform, allowing a complete semantic integration of an extensive collection of external databases. BNDB is built upon a comprehensive and extensible object model called BioCore, which is powerful enough to model most known biochemical processes and at the same time easily extensible to be adapted to new biological concepts. Besides a web interface for the search and curation of the data, a Java-based viewer (BiNA) provides a powerful platform-independent visualization and navigation of the data. BiNA uses sophisticated graph layout algorithms for an interactive visualization and navigation of BNDB. BNDB allows a simple, unified access to a variety of external data sources. Its tight integration with the biochemical network library BN++ offers the possibility for import, integration, analysis, and visualization of the data. BNDB is freely accessible at http://www.bndb.org.
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Ioannidis, Konstantinos; Chamberlain, Samuel R; Treder, Matthias S; Kiraly, Franz; Leppink, Eric W; Redden, Sarah A; Stein, Dan J; Lochner, Christine; Grant, Jon E
2016-12-01
Problematic internet use is common, functionally impairing, and in need of further study. Its relationship with obsessive-compulsive and impulsive disorders is unclear. Our objective was to evaluate whether problematic internet use can be predicted from recognised forms of impulsive and compulsive traits and symptomatology. We recruited volunteers aged 18 and older using media advertisements at two sites (Chicago USA, and Stellenbosch, South Africa) to complete an extensive online survey. State-of-the-art out-of-sample evaluation of machine learning predictive models was used, which included Logistic Regression, Random Forests and Naïve Bayes. Problematic internet use was identified using the Internet Addiction Test (IAT). 2006 complete cases were analysed, of whom 181 (9.0%) had moderate/severe problematic internet use. Using Logistic Regression and Naïve Bayes we produced a classification prediction with a receiver operating characteristic area under the curve (ROC-AUC) of 0.83 (SD 0.03) whereas using a Random Forests algorithm the prediction ROC-AUC was 0.84 (SD 0.03) [all three models superior to baseline models p < 0.0001]. The models showed robust transfer between the study sites in all validation sets [p < 0.0001]. Prediction of problematic internet use was possible using specific measures of impulsivity and compulsivity in a population of volunteers. Moreover, this study offers proof-of-concept in support of using machine learning in psychiatry to demonstrate replicability of results across geographically and culturally distinct settings. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.
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Chandra, Sharat; Pandey, Jyotsana; Tamrakar, Akhilesh Kumar; Siddiqi, Mohammad Imran
2017-01-01
In insulin and leptin signaling pathway, Protein-Tyrosine Phosphatase 1B (PTP1B) plays a crucial controlling role as a negative regulator, which makes it an attractive therapeutic target for both Type-2 Diabetes (T2D) and obesity. In this work, we have generated classification models by using the inhibition data set of known PTP1B inhibitors to identify new inhibitors of PTP1B utilizing multiple machine learning techniques like naïve Bayesian, random forest, support vector machine and k-nearest neighbors, along with structural fingerprints and selected molecular descriptors. Several models from each algorithm have been constructed and optimized, with the different combination of molecular descriptors and structural fingerprints. For the training and test sets, most of the predictive models showed more than 90% of overall prediction accuracies. The best model was obtained with support vector machine approach and has Matthews Correlation Coefficient of 0.82 for the external test set, which was further employed for the virtual screening of Maybridge small compound database. Five compounds were subsequently selected for experimental assay. Out of these two compounds were found to inhibit PTP1B with significant inhibitory activity in in-vitro inhibition assay. The structural fragments which are important for PTP1B inhibition were identified by naïve Bayesian method and can be further exploited to design new molecules around the identified scaffolds. The descriptive and predictive modeling strategy applied in this study is capable of identifying PTP1B inhibitors from the large compound libraries. Copyright © 2016 Elsevier Inc. All rights reserved.
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The Confusion Assessment Method (CAM): A Systematic Review of Current Usage
Wei, Leslie A.; Fearing, Michael A.; Sternberg, Eliezer J.; Inouye, Sharon K.
2008-01-01
Objectives To examine the psychometric properties, adaptations, translations, and applications of the Confusion Assessment Method (CAM), a widely-used instrument and diagnostic algorithm for identification of delirium. Design Systematic literature review Setting NA Measurements Electronic searches of PubMED, EMBASE, PsychINFO, CINAHL, Ageline, and Google Scholar, augmented by reviews of reference listings, were conducted to identify original English-language articles utilizing the CAM from January 1, 1991 to December 31, 2006. Two reviewers independently abstracted key information from each article. Participants NA Results Of 239 original articles, 10 (4%) were categorized as validation studies, 16 (7%) as adaptations; 12 (5%) as translations, and 222 (93%) as applications. Validation studies evaluated performance of the CAM against a reference standard. Results were combined across 7 high quality studies (n=1071), demonstrating an overall sensitivity of 94% (95% confidence interval, CI, 91–97%), and specificity of 89% (95% CI, 85–94%). CAM has been adapted for use in ICU, emergency, and institutional settings, and for scoring severity and subsyndromal delirium. CAM has been translated into 10 languages where published articles are available. In application studies, CAM-rated delirium is most commonly used as a risk factor or outcome, but also as an intervention or reference standard. Conclusions The CAM has helped to improve identification of delirium in clinical and research settings. To optimize performance, the CAM should be scored based on observations made during formal cognitive testing, and training is recommended. Future action is needed to optimize use of the CAM and to improve the recognition and management of delirium. PMID:18384586
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NASA Astrophysics Data System (ADS)
Marjani, Azam
2016-07-01
For biomolecules and cell particles purification and separation in biological engineering, besides the chromatography as mostly applied process, aqueous two-phase systems (ATPS) are of the most favorable separation processes that are worth to be investigated in thermodynamic theoretically. In recent years, thermodynamic calculation of ATPS properties has attracted much attention due to their great applications in chemical industries such as separation processes. These phase calculations of ATPS have inherent complexity due to the presence of ions and polymers in aqueous solution. In this work, for target ternary systems of polyethylene glycol (PEG4000)-salt-water, thermodynamic investigation for constituent systems with three salts (NaCl, KCl and LiCl) has been carried out as PEG is the most favorable polymer in ATPS. The modified perturbed hard sphere chain (PHSC) equation of state (EOS), extended Debye-Hückel and Pitzer models were employed for calculation of activity coefficients for the considered systems. Four additional statistical parameters were considered to ensure the consistency of correlations and introduced as objective functions in the particle swarm optimization algorithm. The results showed desirable agreement to the available experimental data, and the order of recommendation of studied models is PHSC EOS > extended Debye-Hückel > Pitzer. The concluding remark is that the all the employed models are reliable in such calculations and can be used for thermodynamic correlation/predictions; however, by using an ion-based parameter calculation method, the PHSC EOS reveals both reliability and universality of applications.
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Behrens, Georg; Rijnders, Bart; Nelson, Mark; Orkin, Chloe; Cohen, Calvin; Mills, Anthony; Elion, Richard A; Vanveggel, Simon; Stevens, Marita; Rimsky, Laurence; Thorpe, David; Bosse, Matthew; White, Kirsten; Zhong, Lijie; DeMorin, Jennifer; Chuck, Susan K
2014-04-01
The once daily, single-tablet regimen (STR) combining rilpivirine (RPV), emtricitabine (FTC), and tenofovir disoproxil fumarate (TDF) provides a simplified treatment option for antiretroviral therapy (ART)-naïve patients with baseline HIV-1 RNA (BLVL) of ≤100,000 copies/mL. The aim of this analysis is to compare long-term efficacy, safety, and tolerability of RPV+FTC/TDF vs. efavirenz (EFV)+FTC/TDF as individual components in subjects with BLVL ≤100,000 copies/mL. Week 96 efficacy and safety data from subjects with BLVL ≤100,000 copies/mL, who received daily RPV 25 mg or EFV 600 mg with FTC/TDF in the phase 3, randomized, double-blind, double-dummy, active-controlled, registrational trials ECHO and THRIVE, were analyzed. Virologic response was evaluated by intent-to-treat, time to loss of virological response (ITT-TLOVR), and Snapshot algorithms. Through Week 96, RPV+FTC/TDF demonstrated non-inferior efficacy to EFV+FTC/TDF (84% vs. 81%, respectively; ITT-TLOVR) in 543 subjects with BLVL ≤100,000 copies/mL, and overall rates of virologic failure (VF) were 5.9% vs. 2.4%, respectively. Resistance development was lower in Year 2 than Year 1. Subjects in both arms with suboptimal adherence (≤95%) had lower virologic responses (63% vs. 62%, respectively). Treatment with RPV+FTC/TDF was associated with significantly fewer treatment-related adverse events (AEs), grade 2-4 AEs, neurological and psychiatric AEs (including dizziness and abnormal dreams/nightmares), and rash. Additionally, grade 2-4 treatment-emergent laboratory abnormalities and grade 1-3 lipid abnormalities were significantly less common with RPV+FTC/TDF than EFV+FTC/TDF. RPV+FTC/TDF demonstrated non-inferior efficacy to EFV+FTC/TDF in ART-naïve subjects with BLVL ≤100,000 copies/mL and was associated with a higher rate of VF but a more favorable safety and tolerability profile through Week 96.
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Wide-Field Gamma-Spectrometer BDRG: GRB Monitor On-Board the Lomonosov Mission
NASA Astrophysics Data System (ADS)
Svertilov, S. I.; Panasyuk, M. I.; Bogomolov, V. V.; Amelushkin, A. M.; Barinova, V. O.; Galkin, V. I.; Iyudin, A. F.; Kuznetsova, E. A.; Prokhorov, A. V.; Petrov, V. L.; Rozhkov, G. V.; Yashin, I. V.; Gorbovskoy, E. S.; Lipunov, V. M.; Park, I. H.; Jeong, S.; Kim, M. B.
2018-02-01
The study of GRB prompt emissions (PE) is one of the main goals of the Lomonosov space mission. The payloads of the GRB monitor (BDRG) with the wide-field optical cameras (SHOK) and the ultra-fast flash observatory (UFFO) onboard the Lomonosov satellite are intended for the observation of GRBs, and in particular, their prompt emissions. The BDRG gamma-ray spectrometer is designed to obtain the temporal and spectral information of GRBs in the energy range of 10-3000 keV as well as to provide GRB triggers on several time scales (10 ms, 1 s and 20 s) for ground and space telescopes, including the UFFO and SHOK. The BDRG instrument consists of three identical detector boxes with axes shifted by 90° from each other. This configuration allows us to localize a GRB source in the sky with an accuracy of ˜ 2°. Each BDRG box contains a phoswich NaI(Tl)/CsI(Tl) scintillator detector. A thick CsI(Tl) crystal in size of \\varnothing 130 × 17 mm is placed underneath the NaI(Tl) as an active shield in the soft energy range and as the main detector in the hard energy range. The ratio of the CsI(Tl) to NaI(Tl) event rates at varying energies can be employed as an independent metric to distinguish legitimate GRB signals from false positives originating from electrons in near-Earth vicinities. The data from three detectors are collected in a BA BDRG information unit, which generates a GRB trigger and a set of data frames in output format. The scientific data output is ˜ 500 Mb per day, including ˜ 180 Mb of continuous data for events with durations in excess of 100 ms for 16 channels in each detector, detailed energy spectra, and sets of frames with ˜ 5 Mb of detailed information for each burst-like event. A number of pre-flight tests including those for the trigger algorithm and calibration were carried out to confirm the reliability of the BDRG for operation in space.
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Model and Analytic Processes for Export License Assessments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thompson, Sandra E.; Whitney, Paul D.; Weimar, Mark R.
2011-09-29
This paper represents the Department of Energy Office of Nonproliferation Research and Development (NA-22) Simulations, Algorithms and Modeling (SAM) Program's first effort to identify and frame analytical methods and tools to aid export control professionals in effectively predicting proliferation intent; a complex, multi-step and multi-agency process. The report focuses on analytical modeling methodologies that alone, or combined, may improve the proliferation export control license approval process. It is a follow-up to an earlier paper describing information sources and environments related to international nuclear technology transfer. This report describes the decision criteria used to evaluate modeling techniques and tools to determinemore » which approaches will be investigated during the final 2 years of the project. The report also details the motivation for why new modeling techniques and tools are needed. The analytical modeling methodologies will enable analysts to evaluate the information environment for relevance to detecting proliferation intent, with specific focus on assessing risks associated with transferring dual-use technologies. Dual-use technologies can be used in both weapons and commercial enterprises. A decision-framework was developed to evaluate which of the different analytical modeling methodologies would be most appropriate conditional on the uniqueness of the approach, data availability, laboratory capabilities, relevance to NA-22 and Office of Arms Control and Nonproliferation (NA-24) research needs and the impact if successful. Modeling methodologies were divided into whether they could help micro-level assessments (e.g., help improve individual license assessments) or macro-level assessment. Macro-level assessment focuses on suppliers, technology, consumers, economies, and proliferation context. Macro-level assessment technologies scored higher in the area of uniqueness because less work has been done at the macro level. An approach to developing testable hypotheses for the macro-level assessment methodologies is provided. The outcome of this works suggests that we should develop a Bayes Net for micro-level analysis and continue to focus on Bayes Net, System Dynamics and Economic Input/Output models for assessing macro-level problems. Simultaneously, we need to develop metrics for assessing intent in export control, including the risks and consequences associated with all aspects of export control.« less
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Silva, E N; Silveira, J A G; Rodrigues, C R F; Viégas, R A
2015-09-01
This study assessed the capacity of Jatropha curcas to physiologically adjust to salinity. Seedlings were exposed to increasing NaCl concentrations (25, 50, 75 and 100 mm) for 15 days. Treatment without NaCl was adopted as control. Shoot dry weight was strongly reduced by NaCl, reaching values of 35% to 65% with 25 to 100 mm NaCl. The shoot/root ratio was only affected with 100 mm NaCl. Relative water content (RWC) increased only with 100 mm NaCl, while electrolyte leakage (EL) was much enhanced with 50 mm NaCl. The Na(+) transport rate to the shoot was more affected with 50 and 100 mm NaCl. In parallel, Cl(-) transport rate increased with 75 and 100 mm NaCl, while K(+) transport rate fell from 50 mm to 100 mm NaCl. In roots, Na(+) and Cl(-) transport rates fell slightly only in 50 mm (to Na(+)) and 50 and 100 mm (to Cl(-)) NaCl, while K(+) transport rate fell significantly with increasing NaCl. In general, our data demonstrate that J. curcas seedlings present changes in key physiological processes that allow this species to adjust to salinity. These responses are related to accumulation of Na(+) and Cl(-) in leaves and roots, K(+)/Na(+) homeostasis, transport of K(+) and selectivity (K-Na) in roots, and accumulation of organic solutes contributing to osmotic adjustment of the species. © 2015 German Botanical Society and The Royal Botanical Society of the Netherlands.
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The system Na2CO3-CaCO3 at 3 GPa
NASA Astrophysics Data System (ADS)
Podborodnikov, Ivan V.; Shatskiy, Anton; Arefiev, Anton V.; Rashchenko, Sergey V.; Chanyshev, Artem D.; Litasov, Konstantin D.
2018-04-01
It was suggested that alkali-alkaline earth carbonates may have a substantial role in petrological processes relevant to metasomatism and melting of the Earth's mantle. Because natrite, Na2CO3, Na-Ca carbonate (shortite and/or nyerereite), and calcite, CaCO3, have been recently reported from xenoliths of shallow mantle (110-115 km) origin, we performed experiments on phase relations in the system Na2CO3-CaCO3 at 3 GPa and 800-1300 °C. We found that the system has one intermediate compound, Na2Ca3(CO3)4, at 800 °C, and two intermediate compounds, Na2Ca(CO3)2 and Na2Ca3(CO3)4, at 850 °C. CaCO3 crystals recovered from experiments at 950 and 1000 °C are aragonite and calcite, respectively. Maximum solid solution of CaCO3 in Na2CO3 is 20 mol% at 850 °C. The Na-carbonate-Na2Ca(CO3)2 eutectic locates near 860 °C and 56 mol% Na2CO3. Na2Ca(CO3)2 melts incongruently near 880 °C to produce Na2Ca3(CO3)4 and a liquid containing about 51 mol% Na2CO3. Na2Ca3(CO3)4 disappears above 1000 °C via incongruent melting to calcite and a liquid containing about 43 mol% Na2CO3. At 1050 °C, the liquid, coexisting with Na-carbonate, contains 87 mol% Na2CO3. Na-carbonate remains solid up to 1150 °C and melts at 1200 °C. The Na2CO3 content in the liquid coexisting with calcite decreases to 15 mol% as temperature increases to 1300 °C. Considering the present and previous data, a range of the intermediate compounds on the liquidus of the Na2CO3-CaCO3 join changes as pressure increases in the following sequence: Na2Ca(CO3)2 (0.1 GPa) → Na2Ca(CO3)2, Na2Ca3(CO3)4 (3 GPa) → Na4Ca(CO3)3, Na2Ca3(CO3)4 (6 GPa). Thus, the Na2Ca(CO3)2 nyerereite stability field extends to the shallow mantle pressures. Consequently, findings of nyerereite among daughter phases in the melt inclusions in olivine from the sheared garnet peridotites are consistent with their mantle origin.
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Selective retransplant after graft loss to nonadherence: success with a second chance.
Dunn, T B; Browne, B J; Gillingham, K J; Kandaswamy, R; Humar, A; Payne, W D; Sutherland, D E R; Matas, A J
2009-06-01
Nonadherence (NA) is a difficult posttransplant problem that can lead to graft loss. A retransplant is controversial because of a fear of recurrent NA. We reviewed our center's data base and identified 114 kidney recipients who lost their graft to overt NA; of this group, 35 (31%) underwent a retransplant after a thorough reevaluation. We compared this NA retransplant group to a control group of second transplant recipients who did not lose their first graft to overt NA (non-NA) (n = 552). After 8 years of follow-up, we found no significant differences between the groups in actuarial graft or patient survival rates, renal function, or the incidence of biopsy-proven chronic rejection. However, 5 of 35 (14%) NA recipients versus 10 of 552 (2%) non-NA recipients lost their retransplant to NA (p = 0.0001). Twenty of 35 (57%) of the NA group exhibited repeat NA behavior after retransplant. We conclude that prior graft loss to NA is associated with increased graft loss to NA after retransplant. However, the majority of NA retransplant recipients did well-with overall long-term outcomes similar to those of the non-NA group. With careful patient selection and aggressive intervention, prior overt NA should not be an absolute contraindication to retransplantation.
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Lee, Jaegi; Lee, Yongwon; Lee, Jeongmin; Lee, Sang-Min; Choi, Jeong-Hee; Kim, Hyungsub; Kwon, Mi-Sook; Kang, Kisuk; Lee, Kyu Tae; Choi, Nam-Soon
2017-02-01
We present an ultraconcentrated electrolyte composed of 5 M sodium bis(fluorosulfonyl)imide in 1,2-dimethoxyethane for Na metal anodes coupled with high-voltage cathodes. Using this electrolyte, a very high Coulombic efficiency of 99.3% at the 120th cycle for Na plating/stripping is obtained in Na/stainless steel (SS) cells with highly reduced corrosivity toward Na metal and high oxidation durability (over 4.9 V versus Na/Na + ) without corrosion of the aluminum cathode current collector. Importantly, the use of this ultraconcentrated electrolyte results in substantially improved rate capability in Na/SS cells and excellent cycling performance in Na/Na symmetric cells without the increase of polarization. Moreover, this ultraconcentrated electrolyte exhibits good compatibility with high-voltage Na 4 Fe 3 (PO 4 ) 2 (P 2 O 7 ) and Na 0.7 (Fe 0.5 Mn 0.5 )O 2 cathodes charged to high voltages (>4.2 V versus Na/Na + ), resulting in outstanding cycling stability (high reversible capacity of 109 mAh g -1 over 300 cycles for the Na/Na 4 Fe 3 (PO 4 ) 2 (P 2 O 7 ) cell) compared with the conventional dilute electrolyte, 1 M NaPF 6 in ethylene carbonate/propylene carbonate (5/5, v/v).
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China Macroeconomic: Documentation Data Banks. Volume 3. Foreign Trade.
1984-11-15
1983 data from Chlnese "Cmtan, Statistics," Econmic Infomation and Agency, THoE ong Pr ious years from CIA "International Trade Statistics" Load fram...204,097 145,564 515,062 1984 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 6 Sources, see below 19F, 1983 data from Chinese "Customs Statistics," Econmic ...Statistics," EconmIc Information and Agency, F org Previous years fran CIA "Internationl Trade Statistics" Load from rw 12 to row 54 -.96 - A B C D E F G H
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Impact of a potential glycosylation site at neuraminidase amino acid 264 of influenza A/H9N2 virus.
Shao, Hongxia; Zhou, Xiaoxiang; Fan, Zhonglei; Wan, Zhimin; Qian, Kun; Perez, Daniel; Qin, Aijian; Ye, Jianqiang
2016-11-30
To determine the role of the potential glycosylation site NA264N, which has been shown to be prevalent in recent Chinese H9N2 isolates, four reverse genetic viruses, rgWS1-NA264N, rgWS1-NA264H, rgBJ-NA264H and rgBJ-NA264N, were rescued. Growth kinetics showed that viruses with NA264H grew faster than viruses with NA264N. Mouse studies revealed that rgBJ-NA264H replicated to a significantly higher titer than rgBJ-NA264N at 3dpi. Notably, in contact chickens, rgBJ-NA264H and rgWS1-NA264H shed significantly more virus than rgBJ-NA264N at 6dpi from the larynx and rgWS1-NA264N at 4dpi from the cloaca, respectively. The present study demonstrates that NA264N affects viral replication of H9N2. Copyright © 2016 Elsevier B.V. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
He, Mingfu; Lau, Kah Chun; Ren, Xiaodi
Alkali metal-oxygen batteries are of great interests for energy storage because of their unparalleled theoretical energy densities. Particularly attractive is the emerging Na-O 2 battery because of the formation of superoxide as the discharge product. Dimethyl sulfoxide (DMSO) is a promising solvent for this battery but its instability towards Na makes it impractical in the Na-O 2 battery. Here in this paper, we report the enhanced stability of Na in DMSO solutions containing concentrated sodium trifluoromethanesulfonimide (NaTFSI) salts (>3molkg -1). Raman spectra of NaTFSI/DMSO electrolytes and abinitio molecular dynamics simulation reveal the Na + solvation number in DMSO and themore » formation of Na(DMSO) 3(TFSI)-like solvation structure. The majority of DMSO molecules solvating Na + in concentrated solutions reduces the available free DMSO molecules that can react with Na and renders the TFSI anion decomposition, which protects Na from reacting with the electrolyte. Using these concentrated electrolytes, Na-O 2 batteries can be cycled forming sodium superoxide (NaO 2) as the sole discharge product with improved long cycle life, highlighting the beneficial role of concentrated electrolytes for Na-based batteries.« less
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2010 Department of Defense (DoD) Chemical and Biological Defense Program (CBDP) Portfolio
2010-03-01
a new oxime and (2) obtaining approval for use of pyridostigmine bromide , the component of Soman Nerve Agent Pretreatment Pyridostigmine (SNAPP) for...Pralidoxime Chloride Autoinjector N/A 6505-01-125-3248 11704-620-01 N/A DLA 8 Pyridostigmine Bromide Tabs USP 30 mg I.S. (SNAPP) N/A 6505-01-178-7903 N...Soman Nerve Agent Pretreatment Pyridostigmine (SNAPP) N/A 6505-01-483-7162 N/A N/A N/A N/A Vaccines Anthrax Vaccine Adsorbed (AVA) N/A 6505-01-399
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Biel, Philippe; Mohn, Dirk; Attin, Thomas; Zehnder, Matthias
2017-04-01
A clinically useful all-in-one endodontic irrigant with combined proteolytic and decalcifying properties is still elusive. In this study, the chemical effects of dissolving the tetrasodium salts of 1-hydroxyethane 1,1-diphosphonic acid (Na 4 HEDP) or Na 4 EDTA directly in sodium hypochlorite (NaOCl) irrigants in polypropylene syringes were assessed during the course of 1 hour. The solubility of the salts in water was determined. Their compatibility with 1% and 5% NaOCl was measured by iodometric titration and in a calcium complexation experiment by using a Ca 2+ -selective electrode. The salts dissolved within 1 minute. The dissolution maximum of Na 4 HEDP in water (wt/total wt) was 44.6% ± 1.6%. The corresponding dissolution maximum of Na 4 EDTA was 38.2% ± 0.8%. Na 4 HEDP at 18% in 5% NaOCl caused a mere loss of 16% of the initially available chlorine during 1 hour. In contrast, a corresponding mixture between NaOCl and the Na 4 EDTA salt caused 95% reduction in available chlorine after 1 minute. Mixtures of 3% Na 4 EDTA with 1% NaOCl were more stable, but only for 30 minutes. Na 4 HEDP lost 24% of its calcium complexation capacity after 60 minutes. The corresponding loss for Na 4 EDTA was 34%. The compatibility and solubility of particulate Na 4 HEDP with/in NaOCl solutions are such that these components can be mixed and used for up to 1 hour. In contrast, short-term compatibility of the Na 4 EDTA salt with NaOCl solutions was considerably lower, decreasing at higher concentrations of either compound. Especially for Na 4 HEDP but also for Na 4 EDTA, the NaOCl had little effect on calcium complexation. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.
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Apical membrane permeability and kinetic properties of the sodium pump in rabbit urinary bladder.
Lewis, S A; Wills, N K
1983-08-01
Previous studies have shown that aldosterone stimulates the rate of Na+ transport across the rabbit urinary bladder epithelium by increasing the apical membrane permeability to Na+. Paradoxically, ion-sensitive and conventional micro-electrode measurements demonstrated that intracellular Na+ activity aiNa+ was essentially unchanged by aldosterone, i.e. aiNa+ was constant regardless of the rate of Na+ transport. The present study was designed to resolve this apparent contradiction. The effects of elevated, endogenous aldosterone levels produced by low-Na+ diet (Lewis & Diamond, 1976) on urinary bladder Na+ transport were investigated in vitro using Ussing-type chambers and intracellular conventional and ion-sensitive microelectrodes. Apical membrane selectivity and kinetics of the Na+ pump were assessed as a function of hormone stimulation. The aldosterone-stimulated increase in Na+ transport was accounted for by increases in both the relative selective permeability of the apical membrane to Na+ and an increase in its absolute Na+ permeability. The kinetics of the Na+ pump were evaluated electrically by loading the cells with Na+ (monitored with Na+-sensitive micro-electrodes) or alternatively by manipulating serosal solution K+ concentration and measuring changes in the basolateral membrane electromotive forces and resistance. From these measurements the current generated by the pump was calculated as a function of intracellular Na+ or extracellular K+. The kinetics of the pump were not altered by aldosterone. A model of highly co-operative binding estimated Km for Na+ as 14.2 mM and 2.3 mM for K+. Hill coefficients for these ions were 2.8 and 1.8, respectively, consistent with a pump stoichiometry of 3 Na+ to 2 K+. The kinetic properties of the Na-K pump indicate that physiological levels of aiNa+ are poised at the foot of a step kinetic curve which energetically favours Na+ extrusion.
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Chapman, R A; Coray, A; McGuigan, J A
1983-01-01
A method for mounting and rapidly perfusing small ventricular trabeculae (diameter around 250 micron) from either ferret or guinea-pig is described. Tension, membrane potential (Em) and intracellular Na activity (aiNa) were measured. aiNa was measured using Na-sensitive micro-electrodes. At room temperature (22-26 degrees C), [Na]o 155 mmol/l and [Ca]o 5.4 mmol/l, aiNa was 10.9 mmol/l +/- S.D. 4.2 mmol/l (n = 148). When [Na]o was reduced from 155 to 1.5 mmol/l contractures developed. These were about twitch height in guinea-pig but less than the twitch height in ferret. Associated with the development of the contracture there was a decrease in aiNa. The aiNa halved within 30 s. The decrease in aiNa was not influenced by changing pHo from 7.4 to 9.5, K-free solution or strophanthidin 50 mumol/l and was not passive since, even when the [Na]o was 1.5 mmol/l, the driving force for Na ions remained inward. The aiNa decreased if [Ca]o was increased and [Na]o decreased or vice versa. On the basis of these findings it is concluded that the decrease in aiNa is mainly due to Na/Ca exchange. Despite the large decrease in aiNa the [Ca]i, as monitored by tension changes, hardly increased. Since Ca uptake does occur in Na-free conditions in heart muscle it is proposed that the mitochondria take up Ca ions and so prevent an excessive rise in cytoplasmic Ca. Strophanthidin increased both aiNa and the withdrawal contracture, but collected results from a number of experiments showed no clear correlation between the initial aiNa and contracture amplitude. Strophanthidin may, therefore, have actions additional to increasing aiNa. PMID:6644617
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Spatial and mineralogic variation of Na-Ca alteration in Laramide porphyry systems of Arizona
NASA Astrophysics Data System (ADS)
Runyon, S.; Seedorff, E.; Barton, M. D.; Mazdab, F. K.; Lecumberri-Sanchez, P.; Steele-MacInnis, M.
2017-12-01
Na-Ca alteration is characterized by the metasomatic addition of Ca ± Na and the loss of K. Minor volumes of Na-Ca alteration in Laramide porphyry systems develops from 3 to 8 km paleodepth. Mineral assemblages, mineral compositions, hydrogen isotopes, whole-rock analyses, and reconnaissance fluid inclusion characteristics have been documented for Na-Ca alteration in Laramide porphyry systems such as Tea Cup and Sierrita. Volumetrically minor Na-Ca alteration in Laramide porphyry systems documented in this study commonly takes the form of one of three mineral assemblages: albite-epidote-chlorite, Na-plagioclase-actinolite ± epidote, and garnet- or diopside-stable Na-plagioclase-actinolite ± epidote. These different Na-Ca mineral assemblages have broad spatial relationships, from shallow albite-chlorite-epidote to deeper Na-plagioclase-actinolite within a given district. Hydrogen isotope data on Na-Ca alteration minerals shows consistently distinct δD compositions of Na-Ca alteration minerals compared to igneous minerals in a given district. Further, calculated hydrogen isotope composition of fluids in equilibrium with Na-Ca alteration minerals are consistently enriched in δD compared to magmatic-hydrothermal fluids. Whole-rock analyses show consistent losses of K and variable addition of Na and Ca across different Na-Ca alteration assemblages. Na-Ca alteration has been well documented associated with the Jurassic arc. Previous studies demonstrated through mass balance, timing and spatial relationships, isotopic, and fluid inclusion studies that Na-Ca alteration associated with the Jurassic arc likely formed from the circulation of external, highly saline, non-magmatic fluids (e.g., Battles and Barton, 1995; Dilles et al., 1995). Na-Ca alteration documented in Laramide systems is generally similar to Na-Ca alteration documented along the Jurassic arc in mineral assemblages, compositions, and timing, but the volume of Na-Ca alteration in the Laramide systems is small as compared to the voluminous Na-Ca alteration documented in systems associated with the Jurassic arc.
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Functional identification and characterization of sodium binding sites in Na symporters
Loo, Donald D. F.; Jiang, Xuan; Gorraitz, Edurne; Hirayama, Bruce A.; Wright, Ernest M.
2013-01-01
Sodium cotransporters from several different gene families belong to the leucine transporter (LeuT) structural family. Although the identification of Na+ in binding sites is beyond the resolution of the structures, two Na+ binding sites (Na1 and Na2) have been proposed in LeuT. Na2 is conserved in the LeuT family but Na1 is not. A biophysical method has been used to measure sodium dissociation constants (Kd) of wild-type and mutant human sodium glucose cotransport (hSGLT1) proteins to identify the Na+ binding sites in hSGLT1. The Na1 site is formed by residues in the sugar binding pocket, and their mutation influences sodium binding to Na1 but not to Na2. For the canonical Na2 site formed by two –OH side chains, S392 and S393, and three backbone carbonyls, mutation of S392 to cysteine increased the sodium Kd by sixfold. This was accompanied by a dramatic reduction in the apparent sugar and phlorizin affinities. We suggest that mutation of S392 in the Na2 site produces a structural rearrangement of the sugar binding pocket to disrupt both the binding of the second Na+ and the binding of sugar. In contrast, the S393 mutations produce no significant changes in sodium, sugar, and phlorizin affinities. We conclude that the Na2 site is conserved in hSGLT1, the side chain of S392 and the backbone carbonyl of S393 are important in the first Na+ binding, and that Na+ binding to Na2 promotes binding to Na1 and also sugar binding. PMID:24191006
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Sodium uptake in different life stages of crustaceans: the water flea Daphnia magna Strauss.
Bianchini, Adalto; Wood, Chris M
2008-02-01
The concentration-dependent kinetics and main mechanisms of whole-body Na+ uptake were assessed in neonate and adult water flea Daphnia magna Strauss acclimated to moderately hard water (0.6 mmol l(-1) NaCl, 1.0 mmol l(-1) CaCO3 and 0.15 mmol l(-1) MgSO4.7H2O; pH 8.2). Whole-body Na+ uptake is independent of the presence of Cl(-) in the external medium and kinetic parameters are dependent on the life stage. Adults have a lower maximum capacity of Na+ transport on a mass-specific basis but a higher affinity for Na+ when compared to neonates. Based on pharmacological analyses, mechanisms involved in whole-body Na+ uptake differ according to the life stage considered. In neonates, a proton pump-coupled Na+ channel appears to play an important role in the whole-body Na+ uptake at the apical membrane. However, they do not appear to contribute to whole-body Na+ uptake in adults, where only the Na+ channel seems to be present, associated with the Na+/H+ exchanger. In both cases, carbonic anhydrase contributes by providing H+ for the transporters. At the basolateral membrane of the salt-transporting epithelia of neonates, Na+ is pumped from the cells to the extracellular fluid by a Na+, K+-ATPase and a Na+/Cl(-) exchanger whereas K+ and Cl(-) move through specific channels. In adults, a Na+/K+/2Cl(-) cotransporter replaces the Na+/Cl(-) exchanger. Differential sensitivity of neonates and adults to iono- and osmoregulatory toxicants, such as metals, are discussed with respect to differences in whole-body Na+ uptake kinetics, as well as in the mechanisms of Na+ transport involved in the whole-body Na+ uptake in the two life stages.
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Zhang, Wei; Zhou, Zhen; An, Ying; Du, Silu; Ruan, Danian; Zhao, Chengyue; Ren, Ning; Tian, Xiaoce
2017-07-01
Simultaneous zeolites regeneration and nitrogen removal were investigated by using a mixed solution of NaClO and NaCl (NaClO-NaCl solution), and effects of the regenerant on ammonium removal performance and textural properties of zeolites were analyzed by long-term adsorption and regeneration operations. Mixed NaClO-NaCl solution removed more NH 4 + exchanged on zeolites and converted more of them to nitrogen than using NaClO or NaCl solution alone. Response surface methodological analysis indicated that molar ratio of hypochlorite and nitrogen (ClO - /N), NaCl concentration and pH value all had significant effects on zeolites regeneration and NH 4 + conversion to nitrogen, and the optimum condition was obtained at ClO - /N of 1.75, NaCl concentration of 20 g/L and pH of 10.0. Zeolites regenerated by mixed NaClO-NaCl solution showed higher ammonium adsorption rate and lower capacity than unused zeolites. Zeolites and the regeneration solution were both effective even after 20 cycles of use. Composition and morphological analysis revealed that the main mineral species and surface morphology of zeolites before and after NaClO-NaCl regeneration were unchanged. Textural analysis indicated that NaClO-NaCl regeneration leads to an increased surface area of zeolites, especially the microporosity. The results indicated that NaClO-NaCl regeneration is an attractive method to achieve sustainable removal of nitrogen from wastewater through zeolite. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Chao, Dongman; He, Xiaozhou; Yang, Yilin; Bazzy-Asaad, Alia; Lazarus, Lawrence H; Balboni, Gianfranco; Kim, Dong H; Xia, Ying
2012-08-01
Activation of delta-opioid receptors (DOR) is neuroprotective against hypoxic/ischemic injury in the cortex, which is at least partially related to its action against hypoxic/ischemic disruption of ionic homeostasis that triggers neuronal injury. Na(+) influx through TTX-sensitive voltage-gated Na(+) channels may be a main mechanism for hypoxia-induced disruption of K(+) homeostasis, with DOR activation attenuating the disruption of ionic homeostasis by targeting voltage-gated Na(+) channels. In the present study we examined the role of DOR in the regulation of Na(+) influx in anoxia and simulated ischemia (oxygen-glucose deprivation) as well as the effect of DOR activation on the Na(+) influx induced by a Na(+) channel opener without anoxic/ischemic stress and explored a potential PKC mechanism underlying the DOR action. We directly measured extracellular Na(+) activity in mouse cortical slices with Na(+) selective electrodes and found that (1) anoxia-induced Na(+) influx occurred mainly through TTX-sensitive Na(+) channels; (2) DOR activation inhibited the anoxia/ischemia-induced Na(+) influx; (3) veratridine, a Na(+) channel opener, enhanced the anoxia-induced Na(+) influx; this could be attenuated by DOR activation; (4) DOR activation did not reduce the anoxia-induced Na(+) influx in the presence of chelerythrine, a broad-spectrum PKC blocker; and (5) DOR effects were blocked by PKCβII peptide inhibitor, and PKCθ pseudosubstrate inhibitor, respectively. We conclude that DOR activation inhibits anoxia-induced Na(+) influx through Na(+) channels via PKC (especially PKCβII and PKCθ isoforms) dependent mechanisms in the cortex. Copyright © 2012 Elsevier Inc. All rights reserved.
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Gabor domain optical coherence microscopy
NASA Astrophysics Data System (ADS)
Murali, Supraja
Time domain Optical Coherence Tomography (TD-OCT), first reported in 1991, makes use of the low temporal coherence properties of a NIR broadband laser to create depth sectioning of up to 2mm under the surface using optical interferometry and point to point scanning. Prior and ongoing work in OCT in the research community has concentrated on improving axial resolution through the development of broadband sources and speed of image acquisition through new techniques such as Spectral domain OCT (SD-OCT). In SD-OCT, an entire depth scan is acquired at once with a low numerical aperture (NA) objective lens focused at a fixed point within the sample. In this imaging geometry, a longer depth of focus is achieved at the expense of lateral resolution, which is typically limited to 10 to 20 mum. Optical Coherence Microscopy (OCM), introduced in 1994, combined the advantages of high axial resolution obtained in OCT with high lateral resolution obtained by increasing the NA of the microscope placed in the sample arm. However, OCM presented trade-offs caused by the inverse quadratic relationship between the NA and the DOF of the optics used. For applications requiring high lateral resolution, such as cancer diagnostics, several solutions have been proposed including the periodic manual re-focusing of the objective lens in the time domain as well as the spectral domain C-mode configuration in order to overcome the loss in lateral resolution outside the DOF. In this research, we report for the first time, high speed, sub-cellular imaging (lateral resolution of 2 mum) in OCM using a Gabor domain image processing algorithm with a custom designed and fabricated dynamic focus microscope interfaced to a Ti:Sa femtosecond laser centered at 800 nm within an SD-OCM configuration. It is envisioned that this technology will provide a non-invasive replacement for the current practice of multiple biopsies for skin cancer diagnosis. The research reported here presents three important advances to this technology all of which have been demonstrated in full functional hardware conceived and built during the course of this research. First, it has been demonstrated that the coherence gate created by the femtosecond laser can be coupled into a scanning optical microscope using optical design methods to include liquid lens technology that enables scanning below the surface of skin with no moving parts and at high resolution throughout a 2x2x2 mm imaging cube. Second, the integration the variable-focus liquid lens technology within a fixed-optics microscope custom optical design helped increase the working NA by an order of magnitude over the limitation imposed by the liquid lens alone. Thus, this design has enabled homogenous axial and lateral resolution at the micron-level (i.e., 2 mum) while imaging in the spectral domain, and still maintaining in vivo speeds. The latest images in biological specimens clearly demonstrate sub-cellular resolution in all dimensions throughout the imaging volume. Third, this new modality for data collection has been integrated with an automated Gabor domain image registration and fusion algorithm to provide full resolution images across the data cube in real-time. We refer to this overall OCM method as Gabor domain OCM (GD-OCM). These advantages place GD-OCM in a unique position with respect to the diagnosis of cancer, because when fully developed, it promises to enable fast and accurate screening for early symptoms that could lead to prevention. The next step for this technology is to apply it directly, in a clinical environment. This step is underway and is expected to be reported by the next generation of researchers within this group.
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Asaro, Fioretta; Feruglio, Luigi; Galantini, Luciano; Nardelli, Alessia
2013-02-15
The growth of the aggregates of the dihydroxylated bile salt sodium taurodeoxycholate (NaTDC) upon NaCl addition and the involvement of the counterion were investigated by NMR spectroscopy of monoatomic ionic species. (23)Na T(1) values from 0.015, 0.100, and 0.200 mol kg(-1) NaTDC solutions in D(2)O, at variable NaCl content, proved to be sensitive to the transition from primary to secondary aggregates, which occurs in the former sample, and to intermicellar interaction. Some (79)Br NMR measurements were performed on a 0.100 mol kg(-1) NaTDC sample added by NaBr in place of NaCl for comparison purposes. The (23)Na, (35)Cl, and (37)Cl double quantum filtered (DQF) patterns, from the 0.100 mol kg(-1) NaTDC sample, and (23)Na ones also from the 0.200 mol kg(-1) NaTDC one, in the presence of 0.750 mol kg(-1) NaCl, are a clear manifestation of motional anisotropy. Moreover, the DQF spectra of (23)Na and (37)Cl, which possess close quadrupole moments, display a striking similarity. The DQF lineshapes were simulated exploiting the Scilab environment to obtain an estimate of the residual quadrupole splitting magnitude. These results support the description of NaTDC micelles as cylindrical aggregates, strongly interacting at high ionic strengths, and capable of association with added electrolytes. Copyright © 2012 Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Portnoy, David; Fisher, Brian; Phifer, Daniel
2015-06-01
The detection of radiological and nuclear threats is extremely important to national security. The federal government is spending significant resources developing new detection systems and attempting to increase the performance of existing ones. The detection of illicit radionuclides that may pose a radiological or nuclear threat is a challenging problem complicated by benign radiation sources (e.g., cat litter and medical treatments), shielding, and large variations in background radiation. Although there is a growing acceptance within the community that concentrating efforts on algorithm development (independent of the specifics of fully assembled systems) has the potential for significant overall system performance gains, there are two major hindrances to advancements in gamma spectral analysis algorithms under the current paradigm: access to data and common performance metrics along with baseline performance measures. Because many of the signatures collected during performance measurement campaigns are classified, dissemination to algorithm developers is extremely limited. This leaves developers no choice but to collect their own data if they are lucky enough to have access to material and sensors. This is often combined with their own definition of metrics for measuring performance. These two conditions make it all but impossible for developers and external reviewers to make meaningful comparisons between algorithms. Without meaningful comparisons, performance advancements become very hard to achieve and (more importantly) recognize. The objective of this work is to overcome these obstacles by developing and freely distributing real and synthetically generated gamma-spectra data sets as well as software tools for performance evaluation with associated performance baselines to national labs, academic institutions, government agencies, and industry. At present, datasets for two tracks, or application domains, have been developed: one that includes temporal spectral data at 1 s time intervals, which represents data collected by a mobile system operating in a dynamic radiation background environment; and one that represents static measurements with a foreground spectrum (background plus source) and a background spectrum. These data include controlled variations in both Source Related Factors (nuclide, nuclide combinations, activities, distances, collection times, shielding configurations, and background spectra) and Detector Related Factors (currently only gain shifts, but resolution changes and non-linear energy calibration errors will be added soon). The software tools will allow the developer to evaluate the performance impact of each of these factors. Although this first implementation is somewhat limited in scope, considering only NaI-based detection systems and two application domains, it is hoped that (with community feedback) a wider range of detector types and applications will be included in the future. This article describes the methods used for dataset creation, the software validation/performance measurement tools, the performance metrics used, and examples of baseline performance.
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Kinetic properties of the sodium-calcium exchanger in rat brain synaptosomes.
Fontana, G; Rogowski, R S; Blaustein, M P
1995-01-01
1. The kinetic properties of the internal Na+ (Na+i)- dependent 45Ca2+ influx and external Na+ (Na+o)-dependent 45Ca2+ efflux were determined in isolated rat brain nerve terminals (synaptosomes) under conditions which the concentrations of internal Na+ ([Na+]i), external Na+ ([Na+]o), external Ca2+ (Ca2+]o), and external K+ ([K+]o) were varied. Both fluxes are manifestations of Na(+)-Ca2+ exchange. 2. Ca2+ uptake was augmented by raising [Na+]i and / or lowering [Na+]o. The increase in Ca2+ uptake induced by removing external Na+ was, in most instances, quantitatively equal to the Na+i-dependent Ca2+ uptake. 3. The Na+i-dependent Ca2+ uptake (measured at 1 s) was activated with an apparent half-maximal [Ca2+]o (KCa(o)) of about 0.23 mM. External Na+ inhibited the uptake in a non- competitive manner: increasing [Na+]o from 4.7 to 96 mM reduced the maximal Na+(i)-dependent Ca2+ uptake but did not affect KCa(o). 4. The inhibition of Ca2+ uptake by Na+o was proportional to ([Na+]o)2, and had a Hill coefficient (nH) of approximately 2.0. The mean apparent half-maximal [Na+]o for inhibition (KI(Na)) was about 60mM, and was independent of [Ca2+]o between 0.1 and 1.2mM; this, too, is indicative of non-competitive inhibition. 5. Low concentrations of alkali metal ions (M+) in the medium, including Na+, stimulated the Na+i-dependent uptake. The external Na+ and K+ concentrations required for apparent half-maximal activation (KM(Na) and KM(K), respectively) were 0.12 and 0.10mM. Thus, the relationship between Ca2+ uptake and [Na+]o was biphasic: uptake was stimulated by [Na+]o < or = 10 mM, and inhibited by higher [Na+]o. 6. The calculated maximal Na+i-dependent Ca2+ uptake (Jmax) was about 1530 pmol (mg protein) -1s-1 at 30 degrees C saturating [Ca2+]o and external M+ concentration ([M+]o), and with negligible inhibition by external Na+. 7. Internal Na+ activated the Ca2+ uptake with an apparent half-maximal concentration (KNa(i)) of about 20 mM and a Hill coefficient, nH, of approximately 3.0. 8. The Jmax for the Na+o-dependent efflux of Ca2+ from 45Ca(2+)-loaded synaptosomes treated with carbonyl cyanide p-trifluormethoxy-phenylhydrazone (FCCP) and caffeine (to release stored Ca2+ and raise the internal Ca2+ concentration ([Ca2+]i) was about 1800-2000 pmol (mg protein -1s-1 at 37 degrees C. 9. When the membrane potential (Vm) was reduced (depolarized) by increasing [K+]o, the Na+i-dependent Ca2+ influx increased, and the Na+o-dependent Ca2+ efflux declined. Both fluxes changed about 2-fold per 60 mV change in Vm. This voltage sensitivity corresponds to the movement of one elementary charge through about 60% of the membrane electric field. The symmetry suggests that the voltage-sensitive step is reversible. 10. The Jmax values for both Ca2P influx and efflux correspond to a Na+-Ca2+ exchange-mediated flux of about 425-575 jumol Ca2P (1 cell water)-' s-' or a turnover of about one quarter of the total synaptosome Ca2P in 1 s. We conclude that the Na+-Ca2P exchanger may contribute to Ca2P entry during nerve terminal depolarization; it is likely to be a major mechanism mediating Ca2P extrusion during subsequent repolarization and recovery. PMID:7666363
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Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-15
.... The types of ordnances proposed for use at BT-9 and BT- 11 include small arms, large arms, bombs...) 48 48 4.8 Rockets--5.0'' (live) 20 20 15.0 Rockets--2.75'' and 5'' (inert) 876 NA N/A Bombs and G911 grenades (live) 0 NA 0.5 Bombs and grenades (inert) 4,199 NA NA Missile--TOW 0 NA NA Missile--Hellfire 0 NA...
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Sodium iron hexacyanoferrate with high Na content as a Na-rich cathode material for Na-ion batteries
DOE Office of Scientific and Technical Information (OSTI.GOV)
You, Ya; Yu, Xi -Qian; Yin, Ya -Xia
Owing to the worldwide abundance and low-cost of Na, room-temperature Na-ion batteries are emerging as attractive energy storage systems for large-scale grids. Increasing the Na content in cathode material is one of the effective ways to achieve high energy density. Prussian blue and its analogues (PBAs) are promising Na-rich cathode materials since they can theoretically store two Na ions per formula. However, increasing the Na content in PBAs cathode materials is a big challenge in the current. Here we show that sodium iron hexacyanoferrate with high Na content could be obtained by simply controlling the reducing agent and reaction atmospheremore » during synthesis. The Na content can reach as high as 1.63 per formula, which is the highest value for sodium iron hexacyanoferrate. This Na-rich sodium iron hexacyanoferrate demonstrates a high specific capacity of 150 mA h g -1 and remarkable cycling performance with 90% capacity retention after 200 cycles. Furthermore, the Na intercalation/de-intercalation mechanism is systematically studied by in situ Raman, X-ray diffraction and X-ray absorption spectroscopy analysis for the first time. As a result, the Na-rich sodium iron hexacyanoferrate could function as a plenteous Na reservoir and has great potential as a cathode material toward practical Na-ion batteries.« less
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Alparone, Andrea; Librando, Vito
2012-04-01
Structure, IR and Raman spectra of 1-, 2- and 9-nitroanthracene isomers (1-NA, 2-NA and 9-NA) were calculated and analyzed through density functional theory computations using the B3LYP functional with the 6-311+G** basis set. Steric and π-conjugative effects determine the characteristic ONCC dihedral angles, which vary from 0° (2-NA) to 28-29° (1-NA) and 59° (9-NA), influencing the relative order of stability along the series 9-NA<1-NA<2-NA. The spectral regions at wavenumber values>3000 cm(-1) and <1000 cm(-1) little depend on the substituent position. The Raman and IR intensity values of the characteristic symmetric nitro group stretching transition, appearing between 1310 and 1345 cm(-1), are rather sensitive to the position of the substituent, decreasing regularly on passing from the planar to the NO2-rotated isomers (9-NA<1-NA<2-NA). In the medium-energy spectral region (1000-1700 cm(-1)), the number and the relative position of the strongest Raman bands are of potential utility to discriminate the NA isomers. Structural and spectroscopic results suggest that the unknown mutagenic activity of 1-NA is expected to be between that of 9-NA and 2-NA. Copyright © 2011 Elsevier B.V. All rights reserved.
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Sodium iron hexacyanoferrate with high Na content as a Na-rich cathode material for Na-ion batteries
You, Ya; Yu, Xi -Qian; Yin, Ya -Xia; ...
2014-10-27
Owing to the worldwide abundance and low-cost of Na, room-temperature Na-ion batteries are emerging as attractive energy storage systems for large-scale grids. Increasing the Na content in cathode material is one of the effective ways to achieve high energy density. Prussian blue and its analogues (PBAs) are promising Na-rich cathode materials since they can theoretically store two Na ions per formula. However, increasing the Na content in PBAs cathode materials is a big challenge in the current. Here we show that sodium iron hexacyanoferrate with high Na content could be obtained by simply controlling the reducing agent and reaction atmospheremore » during synthesis. The Na content can reach as high as 1.63 per formula, which is the highest value for sodium iron hexacyanoferrate. This Na-rich sodium iron hexacyanoferrate demonstrates a high specific capacity of 150 mA h g -1 and remarkable cycling performance with 90% capacity retention after 200 cycles. Furthermore, the Na intercalation/de-intercalation mechanism is systematically studied by in situ Raman, X-ray diffraction and X-ray absorption spectroscopy analysis for the first time. As a result, the Na-rich sodium iron hexacyanoferrate could function as a plenteous Na reservoir and has great potential as a cathode material toward practical Na-ion batteries.« less
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Thermodynamic properties of Na2O-SiO2-CaO melts at 1000 to 1100 °C
NASA Astrophysics Data System (ADS)
Neudorf, D. A.; Elliott, J. F.
1980-12-01
The thermodynamic properties of Na2O-SiO2 and Na2O-SiO2-CaO melts have been measured using the galvanic cellbegin{array}{*{20}c} {O_2 (g), (Na_2 O), Pt} \\ {Na_2 O - WO_3 liq} \\ left| begin{gathered} Na^ + \\ β - alumina \\ right| begin{array}{*{20}c} {Pt,(Na_2 O), O_2 (g)} \\ {Na_2 O - SiO_2 - CaO liq} \\ Activities of Na2O were calculated from the reversible emf of the cell. This is possible because the activity of Na2O in the Na2O-WO3 liquid is known from previous work. Data for the binary Na2O-SiO2 system were obtained between 1000 and 1100 °C and for compositions ranging from 25 wt pct to 40 wt pct Na2O. At 1050 °C, Loga_{Na_2 O} varied from approximately 10.2 at 25 wt pct Na2O to approximately -8.3 at 40 wt pct Na2O, the dependence with respect to composition being nearly linear. The Gibbs-Duhem equation was used to calculate the activities of SiO2(s), and the integral mixing properties, G M, HM, and S M, were derived. At the di-silicate composition, G M = -83 kJ/mol, H M = -41 kJ mol and S M = 33 J/mol K at 1000 °C. (Standard states are pure, liquid Na2O and pure, solid tridymite.) The activity data are interpreted in terms of the polymeric nature of silicate melts. Activities of Na2O in the Na2O-CaO-SiO2 system were measured for the 25, 30 and 35 wt pct Na2O binary compositions with up to 10 wt pct CaO added. The addition of CaO caused an increase in the activity of Na2O at constantN_{Na_2 O} /N_{SiO_2 } . The experimental data agree well with the behavior predicted by Richardson’s ternary mixing model.
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1988-06-01
Fuseaje mode%, 6/un/im NA 10 10 10 6/10 6/9 6/10 6/10 4/0 NA rigid body / elastic Aerodynamics on NA NA NA NA NA CP CP CP CP NA NA fuselage Pylon CP PR GDOF... motions were cyclic and body modes using the moving-block allowed to decay freely. The body pitch and roll analysis. A complete discussion of the model...conditions. Quick-acting and slow- o acting (self-centering) snubbers were intalled to 0 0 arrest the fuselage motion divergences or co lock 0 0 out body
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2006-09-05
NA NA no yes BMAA1128 ABC Transporter 3 GGGAAACGCGAAAC 6 5 yes no BMAA1873 Hypothetical protein 4 No (-C) NA NA no yes BMAA1868 Aconitate hydratase 5...no yes BMAA1868 Aconitate hydratase 3 GTGCTGTC 21 22 no yes BMAA0375 Transcriptional regulator Human Blood 1 TTGGCGC 111 109 no no BMAA1866 Conserved...NA NA no yes BMAA1128 ABC transporter 5 No (-C) NA NA no yes BMAA1868 Aconitate hydratase NA: Not applicable.Page 3 of 11 (page number not for
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F-22 Increment 3.2B Modernization (F-22 Inc 3.2B Mod)
2015-12-01
Production Jan 2018 Jan 2018 Jul 2018 Jul 2018 Required Assets Available ( RAA ) Mar 2019 Mar 2019 Sep 2019 Sep 2019 Change Explanations None Notes... RAA is defined as six aircraft and associated support equipment. F-22 Inc 3.2B Mod December 2015 SAR March 23, 2016 16:11:54 UNCLASSIFIED 9...Mar 2016 N/A Jun 2016 RAA N/A Mar 2019 N/A Sep 2019 Total Cost (TY $M) N/A 1584.1 N/A 1542.6 Total Quantity N/A 152 N/A 152 PAUC N/A 10.422 N/A 10.149
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Evaluation of Nondestructive Methods for Determining Pavement Thickness
2011-09-01
38, PCC 10.38 10.38 9.57 N/A 39, PCC 11.21 11.21 10.31 N/A 40c*, PCC 8.92 8.92 9.84 N/A SB = stabilized limestone base, PCC = portland cement ...PCC 8.92 8.92 8.07 8.92 SB = stabilized limestone base, PCC = portland cement concrete, and AC = asphalt concrete. * Denotes a test location used as...10.38 N/A N/A 39, PCC 11.21 11.21 N/A N/A 40c*, PCC 8.92 8.92 N/A N/A SB = stabilized limestone base, PCC = portland cement concrete, and AC
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Comparison of fluorescence probes for intracellular sodium imaging in prostate cancer cell lines.
Iamshanova, Oksana; Mariot, Pascal; Lehen'kyi, V'yacheslav; Prevarskaya, Natalia
2016-10-01
Sodium (Na + ) ions are known to regulate many signaling pathways involved in both physiological and pathological conditions. In particular, alterations in intracellular concentrations of Na + and corresponding changes in membrane potential are known to be major actors of cancer progression to metastatic phenotype. Though the functionality of Na + channels and the corresponding Na + currents can be investigated using the patch-clamp technique, the latter is rather invasive and a technically difficult method to study intracellular Na + transients compared to Na + fluorescence imaging. Despite the fact that Na + signaling is considered an important controller of cancer progression, only few data using Na + imaging approaches are available so far, suggesting the persisting challenge within the scientific community. In this study, we describe in detail the approach for application of Na + imaging technique to measure intracellular Na + variations in human prostate cancer cells. Accordingly, we used three Na + -specific fluorescent dyes-Na + -binding benzofuran isophthalate (SBFI), CoroNa™ Green (Corona) and Asante NaTRIUM Green-2 (ANG-2). These dyes have been assessed for optimal loading conditions, dissociation constant and working range after different calibration methods, and intracellular Na + sensitivity, in order to determine which probe can be considered as the most reliable to visualize Na + fluctuations in vitro.
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Dendrite-Free Sodium-Metal Anodes for High-Energy Sodium-Metal Batteries.
Sun, Bing; Li, Peng; Zhang, Jinqiang; Wang, Dan; Munroe, Paul; Wang, Chengyin; Notten, Peter H L; Wang, Guoxiu
2018-05-31
Sodium (Na) metal is one of the most promising electrode materials for next-generation low-cost rechargeable batteries. However, the challenges caused by dendrite growth on Na metal anodes restrict practical applications of rechargeable Na metal batteries. Herein, a nitrogen and sulfur co-doped carbon nanotube (NSCNT) paper is used as the interlayer to control Na nucleation behavior and suppress the Na dendrite growth. The N- and S-containing functional groups on the carbon nanotubes induce the NSCNTs to be highly "sodiophilic," which can guide the initial Na nucleation and direct Na to distribute uniformly on the NSCNT paper. As a result, the Na-metal-based anode (Na/NSCNT anode) exhibits a dendrite-free morphology during repeated Na plating and striping and excellent cycling stability. As a proof of concept, it is also demonstrated that the electrochemical performance of sodium-oxygen (Na-O 2 ) batteries using the Na/NSCNT anodes show significantly improved cycling performances compared with Na-O 2 batteries with bare Na metal anodes. This work opens a new avenue for the development of next-generation high-energy-density sodium-metal batteries. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Concentrated Electrolyte for the Sodium-Oxygen Battery: Solvation Structure and Improved Cycle Life.
He, Mingfu; Lau, Kah Chun; Ren, Xiaodi; Xiao, Neng; McCulloch, William D; Curtiss, Larry A; Wu, Yiying
2016-12-05
Alkali metal-oxygen batteries are of great interests for energy storage because of their unparalleled theoretical energy densities. Particularly attractive is the emerging Na-O 2 battery because of the formation of superoxide as the discharge product. Dimethyl sulfoxide (DMSO) is a promising solvent for this battery but its instability towards Na makes it impractical in the Na-O 2 battery. Herein we report the enhanced stability of Na in DMSO solutions containing concentrated sodium trifluoromethanesulfonimide (NaTFSI) salts (>3 mol kg -1 ). Raman spectra of NaTFSI/DMSO electrolytes and ab initio molecular dynamics simulation reveal the Na + solvation number in DMSO and the formation of Na(DMSO) 3 (TFSI)-like solvation structure. The majority of DMSO molecules solvating Na + in concentrated solutions reduces the available free DMSO molecules that can react with Na and renders the TFSI anion decomposition, which protects Na from reacting with the electrolyte. Using these concentrated electrolytes, Na-O 2 batteries can be cycled forming sodium superoxide (NaO 2 ) as the sole discharge product with improved long cycle life, highlighting the beneficial role of concentrated electrolytes for Na-based batteries. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Concentrated Electrolyte for the Sodium-Oxygen Battery: Solvation Structure and Improved Cycle Life
He, Mingfu; Lau, Kah Chun; Ren, Xiaodi; ...
2016-11-03
Alkali metal-oxygen batteries are of great interests for energy storage because of their unparalleled theoretical energy densities. Particularly attractive is the emerging Na-O 2 battery because of the formation of superoxide as the discharge product. Dimethyl sulfoxide (DMSO) is a promising solvent for this battery but its instability towards Na makes it impractical in the Na-O 2 battery. Here in this paper, we report the enhanced stability of Na in DMSO solutions containing concentrated sodium trifluoromethanesulfonimide (NaTFSI) salts (>3molkg -1). Raman spectra of NaTFSI/DMSO electrolytes and abinitio molecular dynamics simulation reveal the Na + solvation number in DMSO and themore » formation of Na(DMSO) 3(TFSI)-like solvation structure. The majority of DMSO molecules solvating Na + in concentrated solutions reduces the available free DMSO molecules that can react with Na and renders the TFSI anion decomposition, which protects Na from reacting with the electrolyte. Using these concentrated electrolytes, Na-O 2 batteries can be cycled forming sodium superoxide (NaO 2) as the sole discharge product with improved long cycle life, highlighting the beneficial role of concentrated electrolytes for Na-based batteries.« less
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Larsen, Brian Roland; Holm, Rikke; Vilsen, Bente
2016-01-01
Key points Management of glutamate and K+ in brain extracellular space is of critical importance to neuronal function.The astrocytic α2β2 Na+/K+‐ATPase isoform combination is activated by the K+ transients occurring during neuronal activity.In the present study, we report that glutamate transporter‐mediated astrocytic Na+ transients stimulate the Na+/K+‐ATPase and thus the clearance of extracellular K+.Specifically, the astrocytic α2β1 Na+/K+‐ATPase subunit combination displays an apparent Na+ affinity primed to react to physiological changes in intracellular Na+.Accordingly, we demonstrate a distinct physiological role in K+ management for each of the two astrocytic Na+/K+‐ATPase β‐subunits. Abstract Neuronal activity is associated with transient [K+]o increases. The excess K+ is cleared by surrounding astrocytes, partly by the Na+/K+‐ATPase of which several subunit isoform combinations exist. The astrocytic Na+/K+‐ATPase α2β2 isoform constellation responds directly to increased [K+]o but, in addition, Na+/K+‐ATPase‐mediated K+ clearance could be governed by astrocytic [Na+]i. During most neuronal activity, glutamate is released in the synaptic cleft and is re‐absorbed by astrocytic Na+‐coupled glutamate transporters, thereby elevating [Na+]i. It thus remains unresolved whether the different Na+/K+‐ATPase isoforms are controlled by [K+]o or [Na+]i during neuronal activity. Hippocampal slice recordings of stimulus‐induced [K+]o transients with ion‐sensitive microelectrodes revealed reduced Na+/K+‐ATPase‐mediated K+ management upon parallel inhibition of the glutamate transporter. The apparent intracellular Na+ affinity of isoform constellations involving the astrocytic β2 has remained elusive as a result of inherent expression of β1 in most cell systems, as well as technical challenges involved in measuring intracellular affinity in intact cells. We therefore expressed the different astrocytic isoform constellations in Xenopus oocytes and determined their apparent Na+ affinity in intact oocytes and isolated membranes. The Na+/K+‐ATPase was not fully saturated at basal astrocytic [Na+]i, irrespective of isoform constellation, although the β1 subunit conferred lower apparent Na+ affinity to the α1 and α2 isoforms than the β2 isoform. In summary, enhanced astrocytic Na+/K+‐ATPase‐dependent K+ clearance was obtained with parallel glutamate transport activity. The astrocytic Na+/K+‐ATPase isoform constellation α2β1 appeared to be specifically geared to respond to the [Na+]i transients associated with activity‐induced glutamate transporter activity. PMID:27231201
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NASA Astrophysics Data System (ADS)
Liu, Ruijian; Li, Yongfeng; Yao, Bin; Ding, Zhanhui; Deng, Rui; Zhang, Ligong; Zhao, Haifeng; Liu, Lei
2015-08-01
We report that a band-tail emission at 3.08 eV, lower than near-band-edge energy, is observed in photoluminescence measurements of bulk Na-doped CuAlO2. The band-tail emission is attributed to Na-related defects. Electronic structure calculations based on the first-principles method demonstrate that the donor-acceptor compensated complex of NaAl-2Na i in Na-doped CuAlO2 plays a key role in leading to the band-tail emission and bandgap narrowing. Furthermore, Hall effect measurements indicates that the hole concentration in CuAlO2 is independent on Na doping, which is well understood by the donor-acceptor compensation effect of NaAl-2Na i complex.
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Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth
Just, Marcel Adam; Pan, Lisa; Cherkassky, Vladimir L.; McMakin, Dana; Cha, Christine; Nock, Matthew K.; Brent, David
2017-01-01
The clinical assessment of suicidal risk would be significantly complemented by a biologically-based measure that assesses alterations in the neural representations of concepts related to death and life in people who engage in suicidal ideation. This study used machine-learning algorithms (Gaussian Naïve Bayes) to identify such individuals (17 suicidal ideators vs 17 controls) with high (91%) accuracy, based on their altered fMRI neural signatures of death and life-related concepts. The most discriminating concepts were death, cruelty, trouble, carefree, good, and praise. A similar classification accurately (94%) discriminated 9 suicidal ideators who had made a suicide attempt from 8 who had not. Moreover, a major facet of the concept alterations was the evoked emotion, whose neural signature served as an alternative basis for accurate (85%) group classification. The study establishes a biological, neurocognitive basis for altered concept representations in participants with suicidal ideation, which enables highly accurate group membership classification. PMID:29367952
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Event Discrimination Using Seismoacoustic Catalog Probabilities
NASA Astrophysics Data System (ADS)
Albert, S.; Arrowsmith, S.; Bowman, D.; Downey, N.; Koch, C.
2017-12-01
Presented here are three seismoacoustic catalogs from various years and locations throughout Utah and New Mexico. To create these catalogs, we combine seismic and acoustic events detected and located using different algorithms. Seismoacoustic events are formed based on similarity of origin time and location. Following seismoacoustic fusion, the data is compared against ground truth events. Each catalog contains events originating from both natural and anthropogenic sources. By creating these seismoacoustic catalogs, we show that the fusion of seismic and acoustic data leads to a better understanding of the nature of individual events. The probability of an event being a surface blast given its presence in each seismoacoustic catalog is quantified. We use these probabilities to discriminate between events from natural and anthropogenic sources. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.
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Optical proximity correction for anamorphic extreme ultraviolet lithography
NASA Astrophysics Data System (ADS)
Clifford, Chris; Lam, Michael; Raghunathan, Ananthan; Jiang, Fan; Fenger, Germain; Adam, Kostas
2017-10-01
The change from isomorphic to anamorphic optics in high numerical aperture (NA) extreme ultraviolet (EUV) scanners necessitates changes to the mask data preparation flow. The required changes for each step in the mask tape out process are discussed, with a focus on optical proximity correction (OPC). When necessary, solutions to new problems are demonstrated, and verified by rigorous simulation. Additions to the OPC model include accounting for anamorphic effects in the optics, mask electromagnetics, and mask manufacturing. The correction algorithm is updated to include awareness of anamorphic mask geometry for mask rule checking (MRC). OPC verification through process window conditions is enhanced to test different wafer scale mask error ranges in the horizontal and vertical directions. This work will show that existing models and methods can be updated to support anamorphic optics without major changes. Also, the larger mask size in the Y direction can result in better model accuracy, easier OPC convergence, and designs which are more tolerant to mask errors.
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Predicting asthma exacerbations using artificial intelligence.
Finkelstein, Joseph; Wood, Jeffrey
2013-01-01
Modern telemonitoring systems identify a serious patient deterioration when it already occurred. It would be much more beneficial if the upcoming clinical deterioration were identified ahead of time even before a patient actually experiences it. The goal of this study was to assess artificial intelligence approaches which potentially can be used in telemonitoring systems for advance prediction of changes in disease severity before they actually occur. The study dataset was based on daily self-reports submitted by 26 adult asthma patients during home telemonitoring consisting of 7001 records. Two classification algorithms were employed for building predictive models: naïve Bayesian classifier and support vector machines. Using a 7-day window, a support vector machine was able to predict asthma exacerbation to occur on the day 8 with the accuracy of 0.80, sensitivity of 0.84 and specificity of 0.80. Our study showed that methods of artificial intelligence have significant potential in developing individualized decision support for chronic disease telemonitoring systems.
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Development of low level 226Ra analysis for live fish using gamma-ray spectrometry
NASA Astrophysics Data System (ADS)
Chandani, Z.; Prestwich, W. V.; Byun, S. H.
2017-06-01
A low level 226Ra analysis method for live fish was developed using a 4π NaI(Tl) gamma-ray spectrometer. In order to find out the best algorithm for accomplishing the lowest detection limit, the gamma-ray spectrum from a 226Ra point was collected and nine different methods were attempted for spectral analysis. The lowest detection limit of 0.99 Bq for an hour counting occurred when the spectrum was integrated in the energy region of 50-2520 keV. To extend 226Ra analysis to live fish, a Monte Carlo simulation model with a cylindrical fish in a water container was built using the MCNP code. From simulation results, the spatial distribution of the efficiency and the efficiency correction factor for the live fish model were determined. The MCNP model will be able to be conveniently modified when a different fish or container geometry is employed as fish grow up in real experiments.
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An ultra low power feature extraction and classification system for wearable seizure detection.
Page, Adam; Pramod Tim Oates, Siddharth; Mohsenin, Tinoosh
2015-01-01
In this paper we explore the use of a variety of machine learning algorithms for designing a reliable and low-power, multi-channel EEG feature extractor and classifier for predicting seizures from electroencephalographic data (scalp EEG). Different machine learning classifiers including k-nearest neighbor, support vector machines, naïve Bayes, logistic regression, and neural networks are explored with the goal of maximizing detection accuracy while minimizing power, area, and latency. The input to each machine learning classifier is a 198 feature vector containing 9 features for each of the 22 EEG channels obtained over 1-second windows. All classifiers were able to obtain F1 scores over 80% and onset sensitivity of 100% when tested on 10 patients. Among five different classifiers that were explored, logistic regression (LR) proved to have minimum hardware complexity while providing average F-1 score of 91%. Both ASIC and FPGA implementations of logistic regression are presented and show the smallest area, power consumption, and the lowest latency when compared to the previous work.
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Using deep neural networks to augment NIF post-shot analysis
NASA Astrophysics Data System (ADS)
Humbird, Kelli; Peterson, Luc; McClarren, Ryan; Field, John; Gaffney, Jim; Kruse, Michael; Nora, Ryan; Spears, Brian
2017-10-01
Post-shot analysis of National Ignition Facility (NIF) experiments is the process of determining which simulation inputs yield results consistent with experimental observations. This analysis is typically accomplished by running suites of manually adjusted simulations, or Monte Carlo sampling surrogate models that approximate the response surfaces of the physics code. These approaches are expensive and often find simulations that match only a small subset of observables simultaneously. We demonstrate an alternative method for performing post-shot analysis using inverse models, which map directly from experimental observables to simulation inputs with quantified uncertainties. The models are created using a novel machine learning algorithm which automates the construction and initialization of deep neural networks to optimize predictive accuracy. We show how these neural networks, trained on large databases of post-shot simulations, can rigorously quantify the agreement between simulation and experiment. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
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NASA Astrophysics Data System (ADS)
Gambino, D.; Sangiovanni, D. G.; Alling, B.; Abrikosov, I. A.
2017-09-01
We use the color diffusion (CD) algorithm in nonequilibrium (accelerated) ab initio molecular dynamics simulations to determine Ti monovacancy jump frequencies in NaCl-structure titanium nitride (TiN), at temperatures ranging from 2200 to 3000 K. Our results show that the CD method extended beyond the linear-fitting rate-versus-force regime [Sangiovanni et al., Phys. Rev. B 93, 094305 (2016), 10.1103/PhysRevB.93.094305] can efficiently determine metal vacancy migration rates in TiN, despite the low mobilities of lattice defects in this type of ceramic compound. We propose a computational method based on gamma-distribution statistics, which provides unambiguous definition of nonequilibrium and equilibrium (extrapolated) vacancy jump rates with corresponding statistical uncertainties. The acceleration-factor achieved in our implementation of nonequilibrium molecular dynamics increases dramatically for decreasing temperatures from 500 for T close to the melting point Tm, up to 33 000 for T ≈0.7 Tm .
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Activity recognition with smartphone support.
Guiry, John J; van de Ven, Pepijn; Nelson, John; Warmerdam, Lisanne; Riper, Heleen
2014-06-01
In this paper, the authors describe a method of accurately detecting human activity using a smartphone accelerometer paired with a dedicated chest sensor. The design, implementation, testing and validation of a custom mobility classifier are also presented. Offline analysis was carried out to compare this custom classifier to de-facto machine learning algorithms, including C4.5, CART, SVM, Multi-Layer Perceptrons, and Naïve Bayes. A series of trials were carried out in Ireland, initially involving N=6 individuals to test the feasibility of the system, before a final trial with N=24 subjects took place in the Netherlands. The protocol used and analysis of 1165min of recorded activities from these trials are described in detail in this paper. Analysis of collected data indicate that accelerometers placed in these locations, are capable of recognizing activities including sitting, standing, lying, walking, running and cycling with accuracies as high as 98%. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.
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Predictive analysis and data mining among the employment of fresh graduate students in HEI
NASA Astrophysics Data System (ADS)
Rahman, Nor Azziaty Abdul; Tan, Kian Lam; Lim, Chen Kim
2017-10-01
Management of higher education have a problem in producing 100% of graduates who can meet the needs of industry while industry is also facing the problem of finding skilled graduates who suit their needs partly due to the lack of an effective method in assessing problem solving skills as well as weaknesses in the assessment of problem-solving skills. The purpose of this paper is to propose a suitable classification model that can be used in making prediction and assessment of the attributes of the student's dataset to meet the selection criteria of work demanded by the industry of the graduates in the academic field. Supervised and unsupervised Machine Learning Algorithms were used in this research where; K-Nearest Neighbor, Naïve Bayes, Decision Tree, Neural Network, Logistic Regression and Support Vector Machine. The proposed model will help the university management to make a better long-term plans for producing graduates who are skilled, knowledgeable and fulfill the industry needs as well.
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Real-time radionuclide identification in γ-emitter mixtures based on spiking neural network.
Bobin, C; Bichler, O; Lourenço, V; Thiam, C; Thévenin, M
2016-03-01
Portal radiation monitors dedicated to the prevention of illegal traffic of nuclear materials at international borders need to deliver as fast as possible a radionuclide identification of a potential radiological threat. Spectrometry techniques applied to identify the radionuclides contributing to γ-emitter mixtures are usually performed using off-line spectrum analysis. As an alternative to these usual methods, a real-time processing based on an artificial neural network and Bayes' rule is proposed for fast radionuclide identification. The validation of this real-time approach was carried out using γ-emitter spectra ((241)Am, (133)Ba, (207)Bi, (60)Co, (137)Cs) obtained with a high-efficiency well-type NaI(Tl). The first tests showed that the proposed algorithm enables a fast identification of each γ-emitting radionuclide using the information given by the whole spectrum. Based on an iterative process, the on-line analysis only needs low-statistics spectra without energy calibration to identify the nature of a radiological threat. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Multi-level Monte Carlo Methods for Efficient Simulation of Coulomb Collisions
NASA Astrophysics Data System (ADS)
Ricketson, Lee
2013-10-01
We discuss the use of multi-level Monte Carlo (MLMC) schemes--originally introduced by Giles for financial applications--for the efficient simulation of Coulomb collisions in the Fokker-Planck limit. The scheme is based on a Langevin treatment of collisions, and reduces the computational cost of achieving a RMS error scaling as ɛ from O (ɛ-3) --for standard Langevin methods and binary collision algorithms--to the theoretically optimal scaling O (ɛ-2) for the Milstein discretization, and to O (ɛ-2 (logɛ)2) with the simpler Euler-Maruyama discretization. In practice, this speeds up simulation by factors up to 100. We summarize standard MLMC schemes, describe some tricks for achieving the optimal scaling, present results from a test problem, and discuss the method's range of applicability. This work was performed under the auspices of the U.S. DOE by the University of California, Los Angeles, under grant DE-FG02-05ER25710, and by LLNL under contract DE-AC52-07NA27344.
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Multi-Sensor Fusion for Enhanced Contextual Awareness of Everyday Activities with Ubiquitous Devices
Guiry, John J.; van de Ven, Pepijn; Nelson, John
2014-01-01
In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances. PMID:24662406
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A hadoop-based method to predict potential effective drug combination.
Sun, Yifan; Xiong, Yi; Xu, Qian; Wei, Dongqing
2014-01-01
Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request.
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A Hadoop-Based Method to Predict Potential Effective Drug Combination
Xiong, Yi; Xu, Qian; Wei, Dongqing
2014-01-01
Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request. PMID:25147789
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Sentimental analysis of Amazon reviews using naïve bayes on laptop products with MongoDB and R
NASA Astrophysics Data System (ADS)
Kamal Hassan, Mohan; Prasanth Shakthi, Sana; Sasikala, R.
2017-11-01
Start In Today’s era the e-commerce is developing rapidly these years, buying products on-line has become more and more fashionable owing to its variety of options, low cost value (high discounts) and quick supply systems, so abundant folks intend to do online shopping. In the meantime the standard and delivery of merchandise is uneven, fake branded products are delivered. We use product users review comments about product and review about retailers from Amazon as data set and classify review text by subjectivity/objectivity and negative/positive attitude of buyer. Such reviews are helpful to some extent, promising both the shoppers and products makers. This paper presents an empirical study of efficacy of classifying product review by tagging the keyword. In the present study, we tend to analyse the fundamentals of determining, positive and negative approach towards the product. Thus we hereby propose completely different approaches by removing the unstructured data and then classifying comments employing Naive Bayes algorithm.
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Guiry, John J; van de Ven, Pepijn; Nelson, John
2014-03-21
In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances.
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Training Impact Analysis for Land Warrior Block II
2006-01-01
maximum W... ... 384 384 instructor requirement - S~ Infantry OSUT STraining company size (25 training companies) NA NA 200•:• LW systems to equip all...Grenade, NA NA 10 M 18 Green SMK C-111 TACTICAL Low Expertise Medium Expertise High Expertise EMPLOYMENT Tasks/Skills Taught No Task Number...Practical Exercise of Tactical Employment on LW Capabilities (Leader Task) G945 Hand Grenade, NA NA 10 M18 Yellow SMK G950 Hand Grenade, NA NA 3 M18 Red SMK
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NASA Astrophysics Data System (ADS)
Komwatana, P.; Dinudom, A.; Young, J. A.; Cook, D. I.
1996-07-01
In tight Na+-absorbing epithelial cells, the rate of Na+ entry through amiloride-sensitive apical membrane Na+ channels is matched to basolateral Na+ extrusion so that cell Na+ concentration and volume remain steady. Control of this process by regulation of apical Na+ channels has been attributed to changes in cytosolic Ca2+ concentration or pH, secondary to changes in cytosolic Na+ concentration, although cytosolic Cl- seems also to be involved. Using mouse mandibular gland duct cells, we now demonstrate that increasing cytosolic Na+ concentration inhibits apical Na+ channels independent of changes in cytosolic Ca2+, pH, or Cl-, and the effect is blocked by GDP-β -S, pertussis toxin, and antibodies against the α -subunits of guanine nucleotide-binding regulatory proteins (Go). In contrast, the inhibitory effect of cytosolic anions is blocked by antibodies to inhibitory guanine nucleotide-binding regulatory proteins (Gi1/Gi2. It thus appears that apical Na+ channels are regulated by Go and Gi proteins, the activities of which are controlled, respectively, by cytosolic Na+ and Cl-.
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Na+/Ca2+ exchange and Na+/K+-ATPase in the heart
Shattock, Michael J; Ottolia, Michela; Bers, Donald M; Blaustein, Mordecai P; Boguslavskyi, Andrii; Bossuyt, Julie; Bridge, John H B; Chen-Izu, Ye; Clancy, Colleen E; Edwards, Andrew; Goldhaber, Joshua; Kaplan, Jack; Lingrel, Jerry B; Pavlovic, Davor; Philipson, Kenneth; Sipido, Karin R; Xie, Zi-Jian
2015-01-01
This paper is the third in a series of reviews published in this issue resulting from the University of California Davis Cardiovascular Symposium 2014: Systems approach to understanding cardiac excitation–contraction coupling and arrhythmias: Na+ channel and Na+ transport. The goal of the symposium was to bring together experts in the field to discuss points of consensus and controversy on the topic of sodium in the heart. The present review focuses on cardiac Na+/Ca2+ exchange (NCX) and Na+/K+-ATPase (NKA). While the relevance of Ca2+ homeostasis in cardiac function has been extensively investigated, the role of Na+ regulation in shaping heart function is often overlooked. Small changes in the cytoplasmic Na+ content have multiple effects on the heart by influencing intracellular Ca2+ and pH levels thereby modulating heart contractility. Therefore it is essential for heart cells to maintain Na+ homeostasis. Among the proteins that accomplish this task are the Na+/Ca2+ exchanger (NCX) and the Na+/K+ pump (NKA). By transporting three Na+ ions into the cytoplasm in exchange for one Ca2+ moved out, NCX is one of the main Na+ influx mechanisms in cardiomyocytes. Acting in the opposite direction, NKA moves Na+ ions from the cytoplasm to the extracellular space against their gradient by utilizing the energy released from ATP hydrolysis. A fine balance between these two processes controls the net amount of intracellular Na+ and aberrations in either of these two systems can have a large impact on cardiac contractility. Due to the relevant role of these two proteins in Na+ homeostasis, the emphasis of this review is on recent developments regarding the cardiac Na+/Ca2+ exchanger (NCX1) and Na+/K+ pump and the controversies that still persist in the field. PMID:25772291
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Varecka, L; Peterajová, E; Písová, E
1998-08-14
The properties of the 45Ca2+ influx by human red blood cells (RBC) induced by NaVO3 or NaF were compared. The NaVO3-induced 45Ca2+ influx was slower and less extensive than that induced by NaF. Both processes were saturable with Ca2+. Substitution of Na+ by K+ inhibited the 45Ca2+ influx induced by NaVO3 but stimulated that by NaF. The NaVO3-induced Ca2+ influx was sensitive to nifedipine (IC50 = 50 mol/l), Cu2+ (IC50=9 mol/l), DTNB (5,5'-dithiobis-(dinitrobenzoic acid)) (IC50 = 12 mol/l) (maximal inhibition 16%, 18%, and 28%, respectively, if NaF was used as inducer). On the other hand, tetrodotoxin (TTX) and cyclosporin A inhibited only the NaF-induced 45Ca2+ influx (IC50 = 21 mol/l and 28 mol/l, respectively). Pig RBC, known not to display the NaVO3-induced Ca2+ influx, exhibited Ca2+ influx induced by NaF. The results show that NaVO3 activates the Ca2+ influx via a pathway homologous to the L-type Ca2+ channel while the NaF-induced Ca2+ influx is mediated via the TTX-sensitive Na+ channel in the presence of NaF with possible participation of calcineurin or cyclophilin. Thus, the Gardos effect induced by NaVO3 and NaF represents two phenomena activated by different mechanisms present in the cryptic state in the RBC membrane.
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[Effect of NaOH-treatment on dry-thermophilic anaerobic digestion of Spartina alterniflora].
Chen, Guang-Yin; Zheng, Zheng; Chang, Zhi-Zhou; Ye, Xiao-Mei; Luo, Yan
2011-07-01
In order to improve the biotransformation rate of lignocellulosic materials, sodium hydroxide (NaOH) was widely used to pretreat lignocellulosic materials. Effect of NaOH-treatment on dry-thermophilic anaerobic digestion of Spartina alternflora was studied by batch model under the temperature of 55 degrees C +/- 1 degrees C, at the initial total solid loading (TSL) of 20%. The results indicated that biogas production was inhibited by NaOH-treatment and improved by NaOH-treatment with water washed. The cumulative biogas yield of control (CK), NaOH-treated and NaOH-treated with water washed (NaOH + water) were 268.35 mL/g, 205.76 mL/g and 299.97 mL/g, respectively. The methane content of CK and NaOH + water treatments kept stable while fluctuation of NaOH-treated treatment during anaerobic digestion process was observed. Compared with CK and NaOH + water treatments, methane content of NaOH-treated treatment was improved by 5.30%. The content of hemi-cellulose and cellulose of S. alternifora decreased while content of lignin of S. alterniflora increased after 51-day anaerobic digestion. The crystallinity of cellulose of S. alterniflora increased after NaOH-treatment which was consistent to the result of FTIR. The lignocellulosic structure was destroyed and the biodegradability of S. alterniflora was increased by NaOH pretreatment. However, the amount of Na+ was taken into the anaerobic system, besides the high Na+ content in the plant itself which inhibited the anaerobic microorganisms. Therefore, NaOH-treatment is considered to be unsuitable for the anaerobic digestion of S. alterniflora.
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Synthesis of zeolites Na-A and Na-X from tablet compressed and calcinated coal fly ash
NASA Astrophysics Data System (ADS)
Hu, Tao; Gao, Wenyan; Liu, Xin; Zhang, Yifu; Meng, Changgong
2017-10-01
Zeolites Na-A and Na-X are important synthetic zeolites widely used for separation and adsorption in industry. It is of great significance to develop energy-efficient routines that can synthesize zeolites Na-A and Na-X from low-cost raw materials. Coal fly ash (CFA) is the major residue from the combustion of coal and biomass containing more than 85% SiO2 and Al2O3, which can readily replace the conventionally used sodium silicate and aluminate for zeolite synthesis. We used Na2CO3 to replace the expensive NaOH used for the calcination of CFA and showed that tablet compression can enhance the contact with Na2CO3 for the activation of CFA through calcination for the synthesis of zeolites Na-A and Na-X under mild conditions. We optimized the control variables for zeolite synthesis and showed that phase-pure zeolite Na-A can be synthesized with CFA at reactant molar ratio, hydrothermal reaction temperature and reaction time of 1.3Na2O: 0.6Al2O3: 1SiO2: 38H2O at 80°C for 6 h, respectively, while phase-pure zeolite Na-X can be synthesized at 2.2Na2O: 0.2Al2O3: 1SiO2: 88H2O at 100°C for 8 h, respectively. The composition, morphology, specific surface area, vibration spectrum and thermogravimetry of synthesized Na-A and Na-X were further characterized.
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2013-01-01
Introduction In mammals, internal Na+ homeostasis is maintained through Na+ reabsorption via a variety of Na+ transport proteins with mutually compensating functions, which are expressed in different segments of the nephrons. In zebrafish, Na+ homeostasis is achieved mainly through the skin/gill ionocytes, namely Na+/H+ exchanger (NHE3b)-expressing H+-ATPase rich (HR) cells and Na+-Cl- cotransporter (NCC)-expressing NCC cells, which are functionally homologous to mammalian proximal and distal convoluted tubular cells, respectively. The present study aimed to investigate whether or not the functions of HR and NCC ionocytes are differentially regulated to compensate for disruptions of internal Na+ homeostasis and if the cell differentiation of the ionocytes is involved in this regulation pathway. Results Translational knockdown of ncc caused an increase in HR cell number and a resulting augmentation of Na+ uptake in zebrafish larvae, while NHE3b loss-of-function caused an increase in NCC cell number with a concomitant recovery of Na+ absorption. Environmental acid stress suppressed nhe3b expression in HR cells and decreased Na+ content, which was followed by up-regulation of NCC cells accompanied by recovery of Na+ content. Moreover, knockdown of ncc resulted in a significant decrease of Na+ content in acid-acclimated zebrafish. Conclusions These results provide evidence that HR and NCC cells exhibit functional redundancy in Na+ absorption, similar to the regulatory mechanisms in mammalian kidney, and suggest this functional redundancy is a critical strategy used by zebrafish to survive in a harsh environment that disturbs body fluid Na+ homeostasis. PMID:23924428
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Duan, Yuhua
2014-01-01
ABSTRACT: Sodium metatitanate (Na2TiO3) was successfully synthesized via a solid-state reaction. The Na2TiO3 structure and microstructure were characterized using X-ray diffraction, scanning and transmission electron microscopy, and N2 adsorption. Then, the CO2 chemisorption mechanism on Na2TiO3 was systematically analyzed to determine the influence of temperature. The CO2 chemisorption capacity of Na2TiO3 was evaluated both dynamically and isothermally, and the products were reanalyzed to elucidate the Na2TiO3-CO2 reaction mechanism. Different chemical species (Na2CO3, Na2O, and Na4Ti5O12 or Na16Ti10O28) were identified during the CO2 capture process in Na2TiO3. In addition, some CO2 chemisorption kinetic parameters were determined. The ΔH‡ was found tomore » be 140.9 kJ/mol, to the Na2TiO3-CO2 system, between 600 and 780 °C. Results evidenced that CO2 chemisorption on Na2TiO3 highly depends on the reaction temperature. Furthermore, the experiments were theoretically supported by different thermodynamic calculations. The calculated thermodynamic properties of CO2 capture reactions by (Na2TiO3, Na4Ti5O12, and Na16Ti10O28) sodium titanates were fully investigated.« less
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Kong, Xiangqiang; Luo, Zhen; Dong, Hezhong; Eneji, A. Egrinya
2012-01-01
A new split-root system was established through grafting to study cotton response to non-uniform salinity. Each root half was treated with either uniform (100/100 mM) or non-uniform NaCl concentrations (0/200 and 50/150 mM). In contrast to uniform control, non-uniform salinity treatment improved plant growth and water use, with more water absorbed from the non- and low salinity side. Non-uniform treatments decreased Na+ concentrations in leaves. The [Na+] in the ‘0’ side roots of the 0/200 treatment was significantly higher than that in either side of the 0/0 control, but greatly decreased when the ‘0’ side phloem was girdled, suggesting that the increased [Na+] in the ‘0’ side roots was possibly due to transportation of foliar Na+ to roots through phloem. Plants under non-uniform salinity extruded more Na+ from the root than those under uniform salinity. Root Na+ efflux in the low salinity side was greatly enhanced by the higher salinity side. NaCl-induced Na+ efflux and H+ influx were inhibited by amiloride and sodium orthovanadate, suggesting that root Na+ extrusion was probably due to active Na+/H+ antiport across the plasma membrane. Improved plant growth under non-uniform salinity was thus attributed to increased water use, reduced leaf Na+ concentration, transport of excessive foliar Na+ to the low salinity side, and enhanced Na+ efflux from the low salinity root. PMID:22200663
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NASA Technical Reports Server (NTRS)
Kohl, F. J.; Stearns, C. A.
1979-01-01
Sodium chloride is believed to be the primary source of turbine engine contamination that contributes to hot corrosion. The behavior of NaCl-containing aerosols ingested with turbine intake air is very complex; some of the NaCl may vaporize during combustion while some may remain as particulates. The NaCl can lead to Na2SO4 formation by several possible routes or it can contribute to corrosion directly. Hydrogen or oxygen atom reaction with NaCl(c) was shown to result in the release of Na(g). Gaseous NaCl in flames can be partially converted to gaseous Na2SO4 by homogeneous reactions. The remaining gaseous NaCl and other Na-containing molecules can act as sodium carriers for condensate deposition of Na2SO4 on cool surfaces. A frozen boundary layer theory was developed to predict the rates of deposition. The condensed phase NaCl can be converted directly to condensed Na2SO4 by reaction with sulfur oxides and O2. Reaction of gaseous NaCl with Cr2O3 results in the vapor phase transport of chromium by the formation of complex Cr-containing gaseous molecules. Similar gaseous complexes are formed with molybdenum. The presence of gaseous NaCl was shown to affect the oxidation kinetics of Ni-Cr alloys. It also causes changes in the surface morphology of Al2O3 scales formed on Al-containing alloys.
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Hydrogen production by sodium borohydride in NaOH aqueous solution
NASA Astrophysics Data System (ADS)
Wang, Q.; Zhang, L. F.; Zhao, Z. G.
2018-01-01
The kinetics of hydrolysis reaction of NaBH4 in NaOH aqueous solution is studied. The influence of pH of the NaOH aqueous solution on the rate of hydrogen production and the hydrogen production efficiency are studied for the hydrolysis reaction of NaBH4. The results show that the activation energy of hydrolysis reaction of NaBH4 increased with the increase of the initial pH of NaOH aqueous solution.With the increasing of the initial pH of NaOH aqueous solution, the rate of hydrogen production and hydrogen production efficiency of NaBH4 hydrolysis decrease.
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1991-01-01
The properties of Na-Ca-K exchange current through the plasma membrane of intact rod outer segments (ROS) isolated from bovine retinas were studied with the optical probe neutral red. Small cellular organelles such as bovine ROS do not offer an adequate collecting area to measure Na-Ca-K exchange currents with electrophysiological techniques. This study demonstrates that Na-Ca-K exchange current in bovine ROS can be measured with the dye neutral red and dual-wavelength spectrophotometry. The binding of neutral red is sensitive to transport of cations across the plasma membrane of ROS by the effect of the translocated cations on the surface potential of the intracellular disk membranes (1985. J. Membr. Biol. 88: 249-262). Electrogenic Na+ fluxes through the ROS plasma membrane were measured with a resolution of 10(5) Na+ ions/ROS per s, equivalent to a current of approximately 0.01 pA; maximal electrogenic Na-Ca-K exchange flux in bovine ROS was equivalent to a maximal exchange current of 1-2 pA. Electrogenic Na+ fluxes were identified as Na-Ca-K exchange current based on a comparison between electrogenic Na+ flux and Na(+)-stimulated Ca2+ release with respect to flux rate, Na+ dependence, and ion selectivity. Neutral red monitored the net entry of a single positive charge carried by Na+ for each Ca2+ ion released (i.e., monitored the Na-Ca-K exchange current). Na-Ca-K exchange in the plasma membrane of bovine ROS had the following properties: (a) Inward Na-Ca-K exchange current required internal Ca2+ (half-maximal stimulation at a free Ca2+ concentration of 0.9 microM), whereas outward Na-Ca-K exchange current required both external Ca2+ (half-maximal stimulation at a free Ca2+ concentration of 1.1 microM) and external K+. (b) Inward Na-Ca-K exchange current depended in a sigmoidal manner on the external Na+ concentration, identical to Na(+)-stimulated Ca2+ release measured with Ca(2+)- indicating dyes. (c) The neutral red method was modified to measure Ca(2+)-activated K+ fluxes (half-maximal stimulation at 2.7 microM free Ca2+) via the Na-Ca-K exchanger in support of the notion that the rod Na-Ca exchanger is in effect a Na-Ca-K exchanger. (d) Competitive interactions between Ca2+ and Na+ ions on the exchanger protein are described. PMID:1722239
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Sodium shortage as a constraint on the carbon cycle in an inland tropical rainforest.
Kaspari, Michael; Yanoviak, Stephen P; Dudley, Robert; Yuan, May; Clay, Natalie A
2009-11-17
Sodium (Na) is uncommon in plants but essential to the metabolism of plant consumers, both decomposers and herbivores. One consequence, previously unexplored, is that as Na supplies decrease (e.g., from coastal to inland forests), ecosystem carbon should accumulate as detritus. Here, we show that adding NaCl solution to the leaf litter of an inland Amazon forest enhanced mass loss by 41%, decreased lignin concentrations by 7%, and enhanced decomposition of pure cellulose by up to 50%, compared with stream water alone. These effects emerged after 13-18 days. Termites, a common decomposer, increased 7-fold on +NaCl plots, suggesting an agent for the litter loss. Ants, a common predator, increased 2-fold, suggesting that NaCl effects cascade upward through the food web. Sodium, not chloride, was likely the driver of these patterns for two reasons: two compounds of Na (NaCl and NaPO(4)) resulted in equivalent cellulose loss, and ants in choice experiments underused Cl (as KCl, MgCl(2), and CaCl(2)) relative to NaCl and three other Na compounds (NaNO(3), Na(3)PO(4), and Na(2)SO(4)). We provide experimental evidence that Na shortage slows the carbon cycle. Because 80% of global landmass lies >100 km inland, carbon stocks and consumer activity may frequently be regulated via Na limitation.
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Sodium shortage as a constraint on the carbon cycle in an inland tropical rainforest
Kaspari, Michael; Yanoviak, Stephen P.; Dudley, Robert; Yuan, May; Clay, Natalie A.
2009-01-01
Sodium (Na) is uncommon in plants but essential to the metabolism of plant consumers, both decomposers and herbivores. One consequence, previously unexplored, is that as Na supplies decrease (e.g., from coastal to inland forests), ecosystem carbon should accumulate as detritus. Here, we show that adding NaCl solution to the leaf litter of an inland Amazon forest enhanced mass loss by 41%, decreased lignin concentrations by 7%, and enhanced decomposition of pure cellulose by up to 50%, compared with stream water alone. These effects emerged after 13–18 days. Termites, a common decomposer, increased 7-fold on +NaCl plots, suggesting an agent for the litter loss. Ants, a common predator, increased 2-fold, suggesting that NaCl effects cascade upward through the food web. Sodium, not chloride, was likely the driver of these patterns for two reasons: two compounds of Na (NaCl and NaPO4) resulted in equivalent cellulose loss, and ants in choice experiments underused Cl (as KCl, MgCl2, and CaCl2) relative to NaCl and three other Na compounds (NaNO3, Na3PO4, and Na2SO4). We provide experimental evidence that Na shortage slows the carbon cycle. Because 80% of global landmass lies >100 km inland, carbon stocks and consumer activity may frequently be regulated via Na limitation. PMID:19884505
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The H,K-ATPase beta-subunit can act as a surrogate for the beta-subunit of Na,K-pumps.
Horisberger, J D; Jaunin, P; Reuben, M A; Lasater, L S; Chow, D C; Forte, J G; Sachs, G; Rossier, B C; Geering, K
1991-10-15
Na,K-ATPase and H,K-ATPase are the only members of the P-type ATPases in which a glycosylated beta-subunit is part of the purified active enzyme. In this study, we have followed the synthesis and the posttranslational processing of the beta-subunit of H,K-ATPase (beta HK) in Xenopus oocytes injected with beta HK cRNA and have tested whether it can act as a surrogate for the beta-subunit of Na,K-ATPase (beta NaK) to support the functional expression of Na,K-pumps. In Xenopus oocytes, beta HK is processed from an Endo H-sensitive 51-kDa coreglycosylated form to an Endo H-resistant 71-kDa fully glycosylated form. Similar to beta NaK, beta HK can stabilize and increase the trypsin resistance of alpha-subunits of Na,K-ATPase (alpha NaK). Finally, expression of beta HK together with alpha NaK leads to an increased number of ouabain binding sites at the plasma membrane accompanied by an increased Rb+ uptake and Na,K-pump current. Our data suggest that beta HK, similar to beta NaK, can assemble to alpha NaK, support the structural maturation and the intracellular transport of catalytic alpha NaK, and ultimately form active alpha NaK-beta HK complexes with Na,K-pump transport properties.
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Effect of NaNO3 concentration on anodic electrochemical behavior on the Sb surface in NaOH solution
NASA Astrophysics Data System (ADS)
He, Yun-long; Xu, Rui-dong; He, Shi-wei; Chen, Han-sen; Li, Kuo; Zhu, Yun; Shen, Qing-feng
2018-03-01
The effect of NaNO3 concentration on the anodic electrochemical behavior of antimony in 4 M NaOH solution was investigated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) analyses. The mechanism of NO 3 - concentration effect on the anodic electrochemical behavior of antimony was proposed, and its availability was confirmed by experimental results. The effect of NaNO3 on the anodic behavior of antimony in NaOH solution can be interpreted as a stepwise formation of different antimony compounds with different NaNO3 concentrations. Metallic antimony is apt to be oxidized into Sb2O3 within the NaNO3 concentration range of 0-0.48 M. NaSbO3 can be found on the antimony surface when the NaNO3 concentration increases gradually. Insoluable NaSbO3 inhibits the anodic oxidation of antimony due to its shielding effect on the mass transport of the reactants and products. Surface morphology and composition were analyzed by X-ray photoelectron spectroscopy (XPS), scanning electronic microscopy (SEM), and electron dispersion spectroscopy (EDS) analyses. Results indicate that the anodic oxidation layer is composed of Sb2O3, NaSbO3, and Sb. The atomic proportion of antimony in the form of NaSbO3 increases with increasing NaNO3 concentration due to the powerful oxidizing property of NaNO3.
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Hydrogen-fluorine exchange in NaBH4-NaBF4.
Rude, L H; Filsø, U; D'Anna, V; Spyratou, A; Richter, B; Hino, S; Zavorotynska, O; Baricco, M; Sørby, M H; Hauback, B C; Hagemann, H; Besenbacher, F; Skibsted, J; Jensen, T R
2013-11-07
Hydrogen-fluorine exchange in the NaBH4-NaBF4 system is investigated using a range of experimental methods combined with DFT calculations and a possible mechanism for the reactions is proposed. Fluorine substitution is observed using in situ synchrotron radiation powder X-ray diffraction (SR-PXD) as a new Rock salt type compound with idealized composition NaBF2H2 in the temperature range T = 200 to 215 °C. Combined use of solid-state (19)F MAS NMR, FT-IR and DFT calculations supports the formation of a BF2H2(-) complex ion, reproducing the observation of a (19)F chemical shift at -144.2 ppm, which is different from that of NaBF4 at -159.2 ppm, along with the new absorption bands observed in the IR spectra. After further heating, the fluorine substituted compound becomes X-ray amorphous and decomposes to NaF at ~310 °C. This work shows that fluorine-substituted borohydrides tend to decompose to more stable compounds, e.g. NaF and BF3 or amorphous products such as closo-boranes, e.g. Na2B12H12. The NaBH4-NaBF4 composite decomposes at lower temperatures (300 °C) compared to NaBH4 (476 °C), as observed by thermogravimetric analysis. NaBH4-NaBF4 (1:0.5) preserves 30% of the hydrogen storage capacity after three hydrogen release and uptake cycles compared to 8% for NaBH4 as measured using Sievert's method under identical conditions, but more than 50% using prolonged hydrogen absorption time. The reversible hydrogen storage capacity tends to decrease possibly due to the formation of NaF and Na2B12H12. On the other hand, the additive sodium fluoride appears to facilitate hydrogen uptake, prevent foaming, phase segregation and loss of material from the sample container for samples of NaBH4-NaF.
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1982-01-01
Na+- and CA2+-sensitive microelectrodes were used to measure intracellular Na+ and Ca2+ activities (alpha iCa) of sheep ventricular muscle and Purkinje strands to study the interrelationship between Na+ and Ca2+ electrochemical gradients (delta muNa and delta muCa) under various conditions. In ventricular muscle, alpha iNa was 6.4 +/- 1.2 mM and alpha iCa was 87 +/- 20 nM ([Ca/+] = 272 nM). A graded decrease of external Na+ activity (alpha oNa) resulted in decrease of alpha iNa, and increase of alpha iCa. There was increase of twitch tension in low- alpha oNa solutions, and occasional increase of resting tension in 40% alpha oNa. Increase of external Ca2+ (alpha oCa) resulted in increase of alpha iCa and decrease of alpha iNa. Decrease of alpha oCa resulted in decrease of alpha iCa and increase of alpha iNa. The apparent resting Na-Ca energy ratio (delta muCa/delta muNa) was between 2.43 and 2.63. When the membrane potential (Vm) was depolarized by 50 mM K+ in ventricular muscle, Vm depolarized by 50 mV, alpha iNa decreased, and alpha iCa increased, with the development of a contracture. The apparent energy coupling ratio did not change with depolarization. 5 x 10(-6) M ouabain induced a large increase in alpha iNa ad alpha iCa, accompanied by an increase in twitch and resting tension. Under the conditions we have studied, delta muNa and delta muCa appeared to be coupled and n was nearly constant at 2.5, as would be expected if the Na-Ca exchange system was able to set the steady level of alpha iCa. Tension threshold was about 230 nM alpha iCa. The magnitude of twitch tension was directly related to alpha iCa. PMID:6292328
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Yılmaz, Zehra Vural; Akkaş, Elif; Türkmen, Gülenay Gençosmanoğlu; Kara, Özgür; Yücel, Aykan; Uygur, Dilek
2017-02-01
In this study, we hypothesized that dietary salt and potassium intake may be related with blood pressure, kidney damage and perinatal outcome in pregnants with preeclampsia (PE). In total, 200 women (50 control women with healthy pregnancy, 150 women with PE) were recruited for the study. Daily salt and potassium intake was estimated based on calculation of 24-hour urinary sodium U[Na+] and potassium U[K+] excretion. U[Na+]/[K+] was calculated by dividing U[Na+] by U[K+]. At the end of the measurements, the pregnant women with PE (n=150) were divided into tertiles according to U[Na+]/[K+]: low Na/K group (n=50, mean U[Na+]/[K+]: 1,04±0,32), medium Na/K group (n=50, mean U[Na+]/[K+]: 2,49± 0,54), high Na/K group (n=50, mean U[Na+]/[K+]: 6,62±3,41). The mean SBP and DBP levels were significantly lower in low Na/K group compared with medium or high Na/K groups (p=0.024, p=0.0002; respectively). Serum creatinine was significantly lower in low Na/K group than high Na/K group (p=0.025). Frequency of severe preeclampsia is lower in low Na/K group than medium or high Na/K groups (p=0.002, p=0.0001; respectively). Birth weight and gestational age at birth were higher in low Na/K group compared with high Na/K group (p=0.045, p=0.0002; respectively). After adjusting for covariates, SBP and DBP and creatinine levels were independently associated with 24 hours urinary [Na+]/[K+] Conclusion: These findings suggest that pregnant with PE with high dietary salt and low potassium intake may have greater maternal and neonatal morbidity risk than pregnant with PE under low dietary salt and high potassium intake.
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NASA Astrophysics Data System (ADS)
Szymański, Zygmunt
2015-03-01
In the paper present's an analysis of suitableness an application of compact and hybrid drive system in hoisting machine. In the paper presented the review of constructional solutions of hoisting machines drive system, driving with AC and DC motor. In the paper presented conception of modern, energy sparing hoisting machine supply system, composed with compact motor, an supplied with transistor or thyristor converter supply system, and intelligent control system composed with multilevel microprocessor controller. In the paper present's also analysis of suitableness application an selected method of artificial intelligent in hoisting machine control system, automation system, and modern diagnostic system. In the paper one limited to analysis of: fuzzy logic method, genetic algorithms method, and modern neural net II and III generation. That method enables realization of complex control algorithms of hosting machine with insurance of energy sparing exploitation conditions, monitoring of exploitation parameters, and prediction diagnostic of hoisting machine technical state, minimization a number of failure states. In the paper present's a conception of control and diagnostic system of the hoisting machine based on fuzzy logic neural set control. In the chapter presented also a selected control algorithms and results of computer simulations realized for particular mathematical models of hoisting machine. Results of theoretical investigation were partly verified in laboratory and industrial experiments.
Przedstawiono analizę celowości wprowadzania, napędów zintegrowanych oraz napędów hybrydowych, do układów napędowych maszyn wyciągowych. Zamieszczono przegląd rozwiązań konstrukcyjnych wybranych hybrydowych oraz zintegrowanych napędów maszyn wyciągowych z silnikami DC i AC. Opisano koncepcję nowoczesnego, energooszczędnego układu zasilania górniczych maszyny wyciągowej, złożonego z silnika zintegrowanego, (tranzystorowego lub tyrystorowego) zasilacza przekształtnikowego, oraz inteligentnego obwodu sterowania zbudowanego na wielopoziomowych sterownikach mikroprocesorowych. Przedstawiono analizę możliwości zastosowania wybranych metod sztucznej inteligencji w układach sterowania, automatyki oraz diagnostyki maszyn wyciągowych. W referacie ograniczono się do analizy metod sterowania rozmytego, metod algorytmów genetycznych oraz nowoczesnych sieci neuronowych II oraz III generacji. Metody te zapewniają realizację złożonych algorytmów sterowania maszyną wyciągową z zapewnieniem energooszczędnych warunków eksploatacyjnych, monitoringu parametrów eksploatacyjnych oraz predykcyjną diagnostykę stanu technicznego maszyny wyciągowej, minimalizującą liczbę stanów awaryjnych. Przedstawiono koncepcję układu sterowania i diagnostyki maszyny bazującej na metodzie: fuzzy-logic neuro set control system (sterowanie rozmyte w sieciach neuronowych). Przedstawiono wybrane algorytmy sterowania oraz wyniki analiz komputerowych wybranych modeli matematycznych maszyny wyciągowej. Wyniki rozważań teoretycznych zostały częściowo sprawdzone w warunkach laboratoryjnych oraz przemysłowych. -
2012-03-23
Carrier-based fighters 0 0 0 0 0 ~60 ~90 Helicopters n/a n/a n/a n/a ~34 ~153 ~157 Subtotal above aircraft n/a n/a n/a n/a ~179 ~468 ~ 505 Source...strategic emphasis on the Asia-Pacific region and the Middle East, but are applicable anywhere on the globe where U.S. national security or vital...support application against ground forces. Developing a near-term, long-range naval gunfire engagement capability for air, missile, and surface
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1995-03-15
10 200 1-Chloro-2,3-epoxypropene NA Acetonitrile NA Ethylene oxide NA Methyl methacrylate NA NA = Information not available. A library search can be...05-4 Vinyl Chloride C2H3CL 75-01-4 Xylene, total TXYLEN - 1-Chloro-2,3-epoxypropene Acetonitrile CH3CN Ethylene oxide ETOX Methyl methacrylate PLEXI...0.010 10 200 Vinyl Chloride 0.010 10 200 Xylene, total 0.010 10 200 1-Chloro-2,3-epoxypropene NA Acetonitrile NA Ethylene oxide NA Methyl methacrylate
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A cluster ion chemistry for the mesospheric sodium layer
NASA Technical Reports Server (NTRS)
Richter, E. S.; Sechrist, C. F., Jr.
1979-01-01
A cluster ion chemistry for sodium is developed which relates the Na(+) profile to the Na profile using reactions involving Na(+).N2, Na(+).CO2, and Na(+).H2O. Removal of sodium from the mesosphere is accomplished by the formation of higher order clusters of the form Na(+).(H2O)n which presumably precipitate to the lower atmosphere. This sink is most effective in the 80-85 km altitude range. The chemical equilibrium model is applied to experimental observations of the Na and Na(+) layers.
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Asano, Y
1978-01-01
Thyroid hormone (T3) increased Na+ dependent respiration accompanied by an increase in NaK-ATPase activity. Administration of T3 increased intracellular K+ concentration and Na/K ratio in thyroidectomized rats, and the Na+ efflux rate constant incubated in oxygenized Na+, K+-Ringers in euthyroid rats. However, the magnitude of the changes in intracellular K+ concentration was modest or invisible in comparison to the changes in QO2(t) and NaK-ATPase activity. The Na+ and K+ efflux rate constants in K+-free +ouabain Ringers were increased by T3 in both thyroidectomized and euthyroid rats. Thus, thyroid hormone stimulates not only Na pump but also the permeability of cell membrane to Na+ and K+. The both effects might contribute to the thyroid thermogenesis.
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Wehner, Frank; Tinel, Hanna
1998-01-01
In rat hepatocytes under hypertonic stress, the entry of Na+ (which is thereafter exchanged for K+ via Na+-K+-ATPase) plays the key role in regulatory volume increase (RVI).In the present study, the contributions of Na+ conductance, Na+-H+ exchange and Na+-K+-2Cl− symport to this process were quantified in confluent primary cultures by means of intracellular microelectrodes and cable analysis, microfluorometric determinations of cell pH and buffer capacity, and measurements of frusemide (furosemide)/bumetanide-sensitive 86Rb+ uptake, respectively. Osmolarity was increased from 300 to 400 mosmol l−1 by addition of sucrose.The experiments indicate a relative contribution of approximately 4:1:1 to hypertonicity-induced Na+ entry for the above-mentioned transporters and the overall Na+ yield equalled 51 mmol l−1 (10 min)−1.This Na+ gain is in good agreement with the stimulation of Na+ extrusion via Na+-K+-ATPase plus the actual increase in cell Na+, namely 55 mmol l−1 (10 min)−1, as was determined on the basis of ouabain-sensitive 86Rb+ uptake and by means of Na+-sensitive microelectrodes, respectively.The overall increase in Na+ and K+ activity plus the expected concomitant increase in cell Cl− equalled 68 mmol l−1, which fits well with the increase in osmotic activity expected to occur from an initial cell shrinkage to 87.5 % and a RVI to 92.6 % of control, namely 53 mosmol l−1.The prominent role of Na+ conductance in the RVI of rat hepatocytes could be confirmed on the basis of the pharmacological profile of this process, which was characterized by means of confocal laser-scanning microscopy. PMID:9481677
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1985-01-01
Noise analysis of the Na+ channels of the apical membranes of frog skin bathed symmetrically in a Cl-HCO3 Ringer solution was done with amiloride and CGS 4270. Tissues were studied in their control states and after inhibition of transepithelial Na+ transport (Isc) by addition of quinine or quinidine to the apical solution. A critical examination of the amiloride-induced noise indicated that the single channel Na+ currents (iNa) were decreased by quinine and quinidine, probably because of depolarization of apical membrane voltage. Despite considerable statistical uncertainty in the methods of estimation of the Na+ channel density with amiloride-induced noise (NA, see text), the striking observation was a large increase of NA with amiloride inhibition of the rate of Na+ entry into the cells. NA was increased to 406% of control, whereas Isc was inhibited to 8.6% of control by 6 microM amiloride. Studies were done also with the Na+ channel blocker CGS 4270. Noise analysis with this compound was advantageous, permitting iCGSNa and NCGS to be measured in individual tissues with a relatively small inhibition of Isc. As with amiloride, inhibition of Isc with CGS 4270 caused large increases of the Na+ channel density (approximately 200% at approximately 35% inhibition of the Isc). Quinine and quinidine caused an approximately 50% increase of Na+ channel density while inhibiting iNa by approximately 60-70%. As inhibition of Na+ entry leads to an increase of Na+ channel density, a mechanism of autoregulation appears to be a major factor in adjusting the apical membrane Na+ permeability of the cells. PMID:2409219
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Differences in the sodium content of bread products in the USA and UK: implications for policy.
Coyne, Kasey J; Baldridge, Abigail S; Huffman, Mark D; Jenner, Katharine; Xavier, Dagan; Dunford, Elizabeth K
2018-02-01
Americans consume Na in excess of daily recommendations. Most dietary Na comes from packaged foods, and bread is a major contributor. In the UK, national Na reduction strategies contributed to lower Na levels in packaged foods and lower population Na intake. Similar initiatives are emerging in the USA and require surveillance to assess effectiveness. We aimed to examine Na levels in bread products in the USA and compare levels with similar UK products. Na data for bread products were obtained from the US Label Insight Open Data Initiative (n 4466) and the FoodSwitch UK database (n 1651). Mean, median and range of Na content, and proportion of products meeting Na targets established by the National Salt Reduction Initiative (NSRI) and the UK Department of Health (DH) were calculated overall, by bread type and by country. Mean (sd) Na content in bread was 455 (170) mg/100 g in the USA and 406 (179) mg/100 g in the UK. In both countries, savoury bread had the highest mean Na (USA=584 mg/100 g, UK=543 mg/100 g) and fruit bread the lowest mean Na (USA=345 mg/100 g, UK=277 mg/100 g). Na content of US bread products was 12 % higher than in the UK, with 21 % of US bread products and 31 % of UK bread products meeting the NSRI and DH targets, respectively. US bread products have, on average, 12 % more Na than similar products in the UK. Variation in Na content within product categories, and between countries, suggests the feasibility of manufacturing products with lower Na to lower dietary Na intake.
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Three homologous subunits form a high affinity peptide-gated ion channel in Hydra.
Dürrnagel, Stefan; Kuhn, Anne; Tsiairis, Charisios D; Williamson, Michael; Kalbacher, Hubert; Grimmelikhuijzen, Cornelis J P; Holstein, Thomas W; Gründer, Stefan
2010-04-16
Recently, three ion channel subunits of the degenerin (DEG)/epithelial Na(+) channel (ENaC) gene family have been cloned from the freshwater polyp Hydra magnipapillata, the Hydra Na(+) channels (HyNaCs) 2-4. Two of them, HyNaC2 and HyNaC3, co-assemble to form an ion channel that is gated by the neuropeptides Hydra-RFamides I and II. The HyNaC2/3 channel is so far the only cloned ionotropic receptor from cnidarians and, together with the related ionotropic receptor FMRFamide-activated Na(+) channel (FaNaC) from snails, the only known peptide-gated ionotropic receptor. The HyNaC2/3 channel has pore properties, like a low Na(+) selectivity and a low amiloride affinity, that are different from other channels of the DEG/ENaC gene family, suggesting that a component of the native Hydra channel might still be lacking. Here, we report the cloning of a new ion channel subunit from Hydra, HyNaC5. The new subunit is closely related to HyNaC2 and -3 and co-localizes with HyNaC2 and -3 to the base of the tentacles. Coexpression in Xenopus oocytes of HyNaC5 with HyNaC2 and -3 largely increases current amplitude after peptide stimulation and affinity of the channel to Hydra-RFamides I and II. Moreover, the HyNaC2/3/5 channel has altered pore properties and amiloride affinity, more similarly to other DEG/ENaC channels. Collectively, our results suggest that the three homologous subunits HyNaC2, -3, and -5 form a peptide-gated ion channel in Hydra that could contribute to fast synaptic transmission.
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Quantification of Na+,K+ pumps and their transport rate in skeletal muscle: Functional significance
2013-01-01
During excitation, muscle cells gain Na+ and lose K+, leading to a rise in extracellular K+ ([K+]o), depolarization, and loss of excitability. Recent studies support the idea that these events are important causes of muscle fatigue and that full use of the Na+,K+-ATPase (also known as the Na+,K+ pump) is often essential for adequate clearance of extracellular K+. As a result of their electrogenic action, Na+,K+ pumps also help reverse depolarization arising during excitation, hyperkalemia, and anoxia, or from cell damage resulting from exercise, rhabdomyolysis, or muscle diseases. The ability to evaluate Na+,K+-pump function and the capacity of the Na+,K+ pumps to fill these needs require quantification of the total content of Na+,K+ pumps in skeletal muscle. Inhibition of Na+,K+-pump activity, or a decrease in their content, reduces muscle contractility. Conversely, stimulation of the Na+,K+-pump transport rate or increasing the content of Na+,K+ pumps enhances muscle excitability and contractility. Measurements of [3H]ouabain binding to skeletal muscle in vivo or in vitro have enabled the reproducible quantification of the total content of Na+,K+ pumps in molar units in various animal species, and in both healthy people and individuals with various diseases. In contrast, measurements of 3-O-methylfluorescein phosphatase activity associated with the Na+,K+-ATPase may show inconsistent results. Measurements of Na+ and K+ fluxes in intact isolated muscles show that, after Na+ loading or intense excitation, all the Na+,K+ pumps are functional, allowing calculation of the maximum Na+,K+-pumping capacity, expressed in molar units/g muscle/min. The activity and content of Na+,K+ pumps are regulated by exercise, inactivity, K+ deficiency, fasting, age, and several hormones and pharmaceuticals. Studies on the α-subunit isoforms of the Na+,K+-ATPase have detected a relative increase in their number in response to exercise and the glucocorticoid dexamethasone but have not involved their quantification in molar units. Determination of ATPase activity in homogenates and plasma membranes obtained from muscle has shown ouabain-suppressible stimulatory effects of Na+ and K+. PMID:24081980
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NASA Technical Reports Server (NTRS)
Rowan, Lawrence C.; Watson, Kenneth; Miller, Susanne H.
1992-01-01
The Iron Hill carbonatite-alkalic igneous rock complex is in the Powderhorn mining district, approximately 40 km south-southwest of Gunnison, Colorado. The complex, which occupies about 30 sq km, was emplaced in metasedimentay and metavolcanic rocks during the later Precambrian or early Cambrian. The main rock types in the complex, from oldest to youngest, are fenite, pyroxenite, uncompahgrite, ijolite, nepheline syenite, and dolomitic carbonatite. The carbonatite is limonitic and forms an elliptially shaped 4 sq km stock. Calcitic and dolomitic carbonatite dikes are also numerous throughout the complex and in the pre-existing rocks. Pyroxenite is the most widespread rock type within the complex, but pyroxene is extensively altered to biotite, phlogopite, and vermiculite. Fenite, which formed through Na, K-metasomatism of the country rocks, typically contains more feldspar and less quartz than the equivalent unaltered country rocks. The other alkalic rock types are less widespread and less well exposed. Parts of the complex are covered by Oligocene ash-flow tuff and alluvial, colluvial, and glacial deposits. Sagebrush and grass cover is moderately dense to very dense at low to intermediate elevations; coniferous tree cover is dense at high elevations and on some north-facing slopes at lower elevations. A new algorithm was used to compute spectral emissivity ratios, independent of any emissivity assumptions. This algorithm has the advantage that any of the possible emissivity ratios can be computed and, thus, a large variety of composite ratio images can be constructed, which permits examination of various geologic hypotheses based on the spectral properties of the surface materials.
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GeneRIF indexing: sentence selection based on machine learning.
Jimeno-Yepes, Antonio J; Sticco, J Caitlin; Mork, James G; Aronson, Alan R
2013-05-31
A Gene Reference Into Function (GeneRIF) describes novel functionality of genes. GeneRIFs are available from the National Center for Biotechnology Information (NCBI) Gene database. GeneRIF indexing is performed manually, and the intention of our work is to provide methods to support creating the GeneRIF entries. The creation of GeneRIF entries involves the identification of the genes mentioned in MEDLINE®; citations and the sentences describing a novel function. We have compared several learning algorithms and several features extracted or derived from MEDLINE sentences to determine if a sentence should be selected for GeneRIF indexing. Features are derived from the sentences or using mechanisms to augment the information provided by them: assigning a discourse label using a previously trained model, for example. We show that machine learning approaches with specific feature combinations achieve results close to one of the annotators. We have evaluated different feature sets and learning algorithms. In particular, Naïve Bayes achieves better performance with a selection of features similar to one used in related work, which considers the location of the sentence, the discourse of the sentence and the functional terminology in it. The current performance is at a level similar to human annotation and it shows that machine learning can be used to automate the task of sentence selection for GeneRIF annotation. The current experiments are limited to the human species. We would like to see how the methodology can be extended to other species, specifically the normalization of gene mentions in other species.
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NASA Astrophysics Data System (ADS)
Knobler, Ron; Scheffel, Peter; Jackson, Scott; Gaj, Kris; Kaps, Jens Peter
2013-05-01
Various embedded systems, such as unattended ground sensors (UGS), are deployed in dangerous areas, where they are subject to compromise. Since numerous systems contain a network of devices that communicate with each other (often times with commercial off the shelf [COTS] radios), an adversary is able to intercept messages between system devices, which jeopardizes sensitive information transmitted by the system (e.g. location of system devices). Secret key algorithms such as AES are a very common means to encrypt all system messages to a sufficient security level, for which lightweight implementations exist for even very resource constrained devices. However, all system devices must use the appropriate key to encrypt and decrypt messages from each other. While traditional public key algorithms (PKAs), such as RSA and Elliptic Curve Cryptography (ECC), provide a sufficiently secure means to provide authentication and a means to exchange keys, these traditional PKAs are not suitable for very resource constrained embedded systems or systems which contain low reliability communication links (e.g. mesh networks), especially as the size of the network increases. Therefore, most UGS and other embedded systems resort to pre-placed keys (PPKs) or other naïve schemes which greatly reduce the security and effectiveness of the overall cryptographic approach. McQ has teamed with the Cryptographic Engineering Research Group (CERG) at George Mason University (GMU) to develop an approach using revolutionary cryptographic techniques that provides both authentication and encryption, but on resource constrained embedded devices, without the burden of large amounts of key distribution or storage.
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SPHERE: SPherical Harmonic Elastic REgistration of HARDI Data
Yap, Pew-Thian; Chen, Yasheng; An, Hongyu; Yang, Yang; Gilmore, John H.; Lin, Weili
2010-01-01
In contrast to the more common Diffusion Tensor Imaging (DTI), High Angular Resolution Diffusion Imaging (HARDI) allows superior delineation of angular microstructures of brain white matter, and makes possible multiple-fiber modeling of each voxel for better characterization of brain connectivity. However, the complex orientation information afforded by HARDI makes registration of HARDI images more complicated than scalar images. In particular, the question of how much orientation information is needed for satisfactory alignment has not been sufficiently addressed. Low order orientation representation is generally more robust than high order representation, although the latter provides more information for correct alignment of fiber pathways. However, high order representation, when naïvely utilized, might not necessarily be conducive to improving registration accuracy since similar structures with significant orientation differences prior to proper alignment might be mistakenly taken as non-matching structures. We present in this paper a HARDI registration algorithm, called SPherical Harmonic Elastic REgistration (SPHERE), which in a principled means hierarchically extracts orientation information from HARDI data for structural alignment. The image volumes are first registered using robust, relatively direction invariant features derived from the Orientation Distribution Function (ODF), and the alignment is then further refined using spherical harmonic (SH) representation with gradually increasing orders. This progression from non-directional, single-directional to multi-directional representation provides a systematic means of extracting directional information given by diffusion-weighted imaging. Coupled with a template-subject-consistent soft-correspondence-matching scheme, this approach allows robust and accurate alignment of HARDI data. Experimental results show marked increase in accuracy over a state-of-the-art DTI registration algorithm. PMID:21147231
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Simulations of a micro-PET system based on liquid xenon
NASA Astrophysics Data System (ADS)
Miceli, A.; Glister, J.; Andreyev, A.; Bryman, D.; Kurchaninov, L.; Lu, P.; Muennich, A.; Retiere, F.; Sossi, V.
2012-03-01
The imaging performance of a high-resolution preclinical micro-positron emission tomography (micro-PET) system employing liquid xenon (LXe) as the gamma-ray detection medium was simulated. The arrangement comprises a ring of detectors consisting of trapezoidal LXe time projection ionization chambers and two arrays of large area avalanche photodiodes for the measurement of ionization charge and scintillation light. A key feature of the LXePET system is the ability to identify individual photon interactions with high energy resolution and high spatial resolution in three dimensions and determine the correct interaction sequence using Compton reconstruction algorithms. The simulated LXePET imaging performance was evaluated by computing the noise equivalent count rate, the sensitivity and point spread function for a point source according to the NEMA-NU4 standard. The image quality was studied with a micro-Derenzo phantom. Results of these simulation studies included noise equivalent count rate peaking at 1326 kcps at 188 MBq (705 kcps at 184 MBq) for an energy window of 450-600 keV and a coincidence window of 1 ns for mouse (rat) phantoms. The absolute sensitivity at the center of the field of view was 12.6%. Radial, tangential and axial resolutions of 22Na point sources reconstructed with a list-mode maximum likelihood expectation maximization algorithm were ⩽0.8 mm (full-width at half-maximum) throughout the field of view. Hot-rod inserts of <0.8 mm diameter were resolvable in the transaxial image of a micro-Derenzo phantom. The simulations show that a LXe system would provide new capabilities for significantly enhancing PET images.
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Feature selection for the classification of traced neurons.
López-Cabrera, José D; Lorenzo-Ginori, Juan V
2018-06-01
The great availability of computational tools to calculate the properties of traced neurons leads to the existence of many descriptors which allow the automated classification of neurons from these reconstructions. This situation determines the necessity to eliminate irrelevant features as well as making a selection of the most appropriate among them, in order to improve the quality of the classification obtained. The dataset used contains a total of 318 traced neurons, classified by human experts in 192 GABAergic interneurons and 126 pyramidal cells. The features were extracted by means of the L-measure software, which is one of the most used computational tools in neuroinformatics to quantify traced neurons. We review some current feature selection techniques as filter, wrapper, embedded and ensemble methods. The stability of the feature selection methods was measured. For the ensemble methods, several aggregation methods based on different metrics were applied to combine the subsets obtained during the feature selection process. The subsets obtained applying feature selection methods were evaluated using supervised classifiers, among which Random Forest, C4.5, SVM, Naïve Bayes, Knn, Decision Table and the Logistic classifier were used as classification algorithms. Feature selection methods of types filter, embedded, wrappers and ensembles were compared and the subsets returned were tested in classification tasks for different classification algorithms. L-measure features EucDistanceSD, PathDistanceSD, Branch_pathlengthAve, Branch_pathlengthSD and EucDistanceAve were present in more than 60% of the selected subsets which provides evidence about their importance in the classification of this neurons. Copyright © 2018 Elsevier B.V. All rights reserved.
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Nuclear Nonproliferation Ontology Assessment Team Final Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Strasburg, Jana D.; Hohimer, Ryan E.
Final Report for the NA22 Simulations, Algorithm and Modeling (SAM) Ontology Assessment Team's efforts from FY09-FY11. The Ontology Assessment Team began in May 2009 and concluded in September 2011. During this two-year time frame, the Ontology Assessment team had two objectives: (1) Assessing the utility of knowledge representation and semantic technologies for addressing nuclear nonproliferation challenges; and (2) Developing ontological support tools that would provide a framework for integrating across the Simulation, Algorithm and Modeling (SAM) program. The SAM Program was going through a large assessment and strategic planning effort during this time and as a result, the relative importancemore » of these two objectives changed, altering the focus of the Ontology Assessment Team. In the end, the team conducted an assessment of the state of art, created an annotated bibliography, and developed a series of ontological support tools, demonstrations and presentations. A total of more than 35 individuals from 12 different research institutions participated in the Ontology Assessment Team. These included subject matter experts in several nuclear nonproliferation-related domains as well as experts in semantic technologies. Despite the diverse backgrounds and perspectives, the Ontology Assessment team functioned very well together and aspects could serve as a model for future inter-laboratory collaborations and working groups. While the team encountered several challenges and learned many lessons along the way, the Ontology Assessment effort was ultimately a success that led to several multi-lab research projects and opened up a new area of scientific exploration within the Office of Nuclear Nonproliferation and Verification.« less
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A General Uncertainty Quantification Methodology for Cloud Microphysical Property Retrievals
NASA Astrophysics Data System (ADS)
Tang, Q.; Xie, S.; Chen, X.; Zhao, C.
2014-12-01
The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program provides long-term (~20 years) ground-based cloud remote sensing observations. However, there are large uncertainties in the retrieval products of cloud microphysical properties based on the active and/or passive remote-sensing measurements. To address this uncertainty issue, a DOE Atmospheric System Research scientific focus study, Quantification of Uncertainties in Cloud Retrievals (QUICR), has been formed. In addition to an overview of recent progress of QUICR, we will demonstrate the capacity of an observation-based general uncertainty quantification (UQ) methodology via the ARM Climate Research Facility baseline cloud microphysical properties (MICROBASE) product. This UQ method utilizes the Karhunen-Loéve expansion (KLE) and Central Limit Theorems (CLT) to quantify the retrieval uncertainties from observations and algorithm parameters. The input perturbations are imposed on major modes to take into account the cross correlations between input data, which greatly reduces the dimension of random variables (up to a factor of 50) and quantifies vertically resolved full probability distribution functions of retrieved quantities. Moreover, this KLE/CLT approach has the capability of attributing the uncertainties in the retrieval output to individual uncertainty source and thus sheds light on improving the retrieval algorithm and observations. We will present the results of a case study for the ice water content at the Southern Great Plains during an intensive observing period on March 9, 2000. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
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Oxidation of ethanol on NaX zeolite modified with transition metals
NASA Astrophysics Data System (ADS)
Mirzai, J. I.; Nadirov, P. A.; Velieva, A. D.; Muradkhanli, V. G.
2017-06-01
NaLaX, NaX + Co, and NaPdX catalysts are synthesized by modification of NaX zeolite with transition metals (La, Co, Pd). The activity of the prepared materials in catalytic ethanol oxidation is studied in the temperature range of 423-723 K. It is shown that NaPdX and NaX + Co accelerate the reactions of partial and complete oxidation of ethanol as the temperature rises. NaLaX accelerates both intramolecular and intermolecular dehydration of alcohol. It is shown that the NaPdX (1.0% Pd) sample has the highest activity in the complete oxidation of alcohol with the formation of CO2.
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Veterans Attitude Tracking Study -- 1983, Wave I. Data Tables. Supplement 1,
1984-05-01
5.6 9.9 6.8 8.2 Admini strative 18.5 20.4 13.U 17.2 Medical 3.6 0.7 0.7 1.3 Other 0.4 0.7 0.0 0.9 Dont know .b 4.6 4.1 3.4 1) Asked only of respondents...toward Guard/ Reserve participation, -- Talked with their co-workers about enlisting in the Guard/Reserve, or -- Seen notices, posters , or other...A N/A 72.9 9 17 Total N/A N/A N/A N/A 100% (11.6%) (23.5%) Seen any notices, posters , or other literature at workplace(’Q R-35b) Yes N/A N/A N/A N/A
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Åsli, Magnus; Ofstad, Ragni; Böcker, Ulrike; Jessen, Flemming; Einen, Olai; Mørkøre, Turid
2016-03-15
Negative health effects associated with excessive sodium (Na) intake have increased the demand for tasty low-Na products (<2% NaCl) rather than traditional heavily salted fish products (∼20% NaCl). This study investigates the causes of improved yield and liquid retention of fish muscle brined with a combination of salt (NaCl) and sodium bicarbonate (NaHCO3 ). Water characteristics and microstructure of saithe (Pollachius virens L.) muscle brined in solutions of NaCl and NaHCO3 or NaCl alone were compared using low-field nuclear magnetic resonance (LF-NMR) T2 relaxometry, microscopy, salt content, liquid retention and colorimetric measurements. Saithe muscle was brined for 92 h in 0, 30, 60, 120 or 240 g kg(-1) NaCl or the respective solutions with added 7.5 g kg(-1) NaHCO3 . NaHCO3 inclusion improved the yield in solutions ranging from 0 to 120 g kg(-1) NaCl, with the most pronounced effect being observed at 30 g kg(-1) NaCl. The changes in yield were reflected in water mobility, with significantly shorter T2 relaxation times in all corresponding brine concentrations. Salt-dependent microstructural changes were revealed by light microscopy, where NaHCO3 supplementation resulted in greater intracellular space at 30 and 60 g kg(-1) NaCl. Sodium bicarbonate addition to low-salt solutions can improve yield and flesh quality of fish muscle owing to altered water mobility and wider space between the muscle cells. © 2015 Society of Chemical Industry.
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Iron bioavailability in corn-masa tortillas is improved by the addition of disodium EDTA.
Walter, Tomás; Pizarro, Fernando; Olivares, Manuel
2003-10-01
Corn-masa flour flat bread tortillas are the main staple of Mexican and Central American populations. Due to high concentrations of inhibitors of iron absorption, the bioavailability from this matrix is unknown. We wanted to determine the most suitable fortificant that would efficaciously improve iron bioavailability. In tortillas prepared with commercial precooked, lime-treated, corn-masa flour, we examined the in vitro solubility of the following forms of iron: native iron with and without Na2EDTA, elemental reduced iron plus Na2EDTA, ferrous fumarate with and without Na2EDTA, bisglycine iron, ferrous sulfate and NaFeEDTA. We also examined the in vivo bioavailability in humans with double radioiron erythrocyte incorporation of ferrous fumarate with and without Na2EDTA, bisglycine iron, NaFeEDTA and native iron plus Na2EDTA, beans and rice. In vitro, solubility ranged from 1% in iron forms without Na2EDTA to 19.4% for NaFeEDTA. Forms of iron with Na2EDTA had intermediate values. In vivo radioiron studies showed that iron forms without Na2EDTA also had low bioavailability (< or =1%). NaFeEDTA had the highest bioavailability (5.3%). The bioavailability of all iron forms improved significantly when tested with Na2EDTA (<0.05). Adding Na2EDTA to ferrous fumarate increased bioavailability from 0.87% to 2.9% (P < 0.001). We conclude that NaFeEDTA is the form of iron best absorbed, but alternatively, ferrous fumarate plus Na2EDTA comprises a feasible option as a fortificant.
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Cation activation of the pig kidney sodium pump: transmembrane allosteric effects of sodium.
Karlish, S J; Stein, W D
1985-01-01
We have studied activation by Na or Rb ions of different transport modes of the Na-K pump, using phospholipid vesicles reconstituted with pig kidney Na-K-ATPase. The shape of the activation curves, sigmoid or quasi-hyperbolic, depends on the nature of the cation at the opposite surface and not on the specific mode of transport. ATP-dependent Na uptake into K-containing vesicles (Na-K exchange) is activated by cytoplasmic Na along a highly sigmoid curve in the absence of extracellular Na (Hill number, nH = 1.9). Activation displays progressively less-sigmoid curves as extracellular Na is raised to 150 mM (nH = 1.2). The maximal rate of the Na-K exchange is not affected. Na is not transported from the extracellular face by the pump in the presence of excess extracellular K, and the transmembrane effects of the extracellular Na are therefore 'allosteric' in nature. ATP-dependent Na-Na exchange (Lee & Blostein, 1980) and classical ATP-plus-ADP-dependent Na-Na exchange are activated by cytoplasmic Na along hyperbolic curves. ATP-dependent Na uptake into Tris-containing vesicles is activated by cytoplasmic Na along a somewhat sigmoidal curve. (ATP + Pi)-dependent Rb-Rb exchange is activated by cytoplasmic and extracellular Rb along strictly hyperbolic curves. The same applies for Rb-Rb exchange in the presence or absence of ATP or Pi alone. The presence of a high concentration of extracellular Na together with extracellular Rb induces a sigmoidal activation by cytoplasmic Rb of (ATP + Pi)-dependent Rb-Rb exchange (nH = 1.45) but does not affect the maximal rate of exchange. Slow passive Rb fluxes through the pump observed in the absence of other pump ligands (see Karlish & Stein, 1982 alpha) are activated by cytoplasmic Rb along a strictly hyperbolic curve with extracellular Rb, nH = 1.0 (Rb-Rb exchange), along a strongly sigmoid curve with extracellular Na, nH = 1.5 (Rb-Na exchange), and along less-sigmoid curves with extracellular Tris, nH = 1.24 (net Rb flux) or extracellular Li, nH = 1.2 (Rb-Li exchange). Activation of the passive Rb fluxes by extracellular Rb is hyperbolic in the presence of cytoplasmic Rb, Li or Tris but is sigmoid in the presence of cytoplasmic Na (nH = 1.36). Inhibition by cytoplasmic Na of passive Rb fluxes from the cytoplasmic to the extracellular face of the pump depends on the nature of the cation at the extracellular surface.(ABSTRACT TRUNCATED AT 400 WORDS) PMID:2582111
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Hosny, E A; Al-Shora, H I; Elmazar, M M
2001-09-01
Insulin suppositories were formulated using Witepsol W35 as a base to investigate the effect of various bile salts/acids on the plasma glucose concentration of diabetic beagle dogs. Comparison of the effect of these formulations was made with that produced by insulin subcutaneous injections. Of the bile salts/acids studied, incorporation of 100 mg of deoxycholic acid (DCA), sodium cholate (NaC), or sodium deoxycholate (NaDC) with insulin (10 U/Kg) showed that suppositories containing NaDC produced the highest area under the curve (AUC) and relative hypoglycemia (RH) of 290 +/- 83 mg%h and 28% +/- 8.1%, respectively. To study the optimum amount of NaDC in insulin suppositories to produce the highest RH, 50-200 mg/suppository were used, and we found that 150 mg NaDC produced 35% +/- 13% RH. We also studied the influence of different doses of insulin (5-20 U/kg) in the presence of NaDC (100 mg). It was found that increase of the insulin dose was accompanied by an increase in AUC and maximum reduction in plasma glucose level Cmax. A combination of NaDC (100 mg) and NaC (50 mg) produced an AUC of 252 +/- 13mg%h and an RH of 49% +/- 2.6%, which were higher than produced by either of its individual components (NaC 50 mg or NaDC 100 mg) when used alone or when compared with an equivalent amount of NaDC (150 mg). When the effect of sodium taurocholate (NaTC) and sodium taurodeoxycholate (NaTDC) was studied, it was found that an insulin suppository containing 100 mg of either NaTC or NaTDC produced an RH equivalent to that produced previouslY with a mixture of NaDC (100 mg) and NaC (50 mg). On the other hand, NaC (50 mg) did not improve the hypoglycemic effect of NaTC any further. In conclusion, a relative hYpoglycemia of about 50% can be reached using insulin suppositories containing Witepsol W35 as a base and NaDC plus NaC (100 mg plus 50 mg, respectively), NaTDC (100mg), or NaTC (100 mg) as rectal absorption enhancers of insulin. A desirable hypoglycemia, expressed as Cmax, and/or AUC can be reached by adjusting the insulin dose in the formulation according to the degree of hyperglycemia.
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Dietary sodium induces a redistribution of the tubular metabolic workload
Udwan, Khalil; Abed, Ahmed; Roth, Isabelle; Dizin, Eva; Maillard, Marc; Bettoni, Carla; Loffing, Johannes; Wagner, Carsten A.; Edwards, Aurélie
2017-01-01
Key points Body Na+ content is tightly controlled by regulated urinary Na+ excretion.The intrarenal mechanisms mediating adaptation to variations in dietary Na+ intake are incompletely characterized.We confirmed and expanded observations in mice that variations in dietary Na+ intake do not alter the glomerular filtration rate but alter the total and cell‐surface expression of major Na+ transporters all along the kidney tubule.Low dietary Na+ intake increased Na+ reabsorption in the proximal tubule and decreased it in more distal kidney tubule segments.High dietary Na+ intake decreased Na+ reabsorption in the proximal tubule and increased it in distal segments with lower energetic efficiency.The abundance of apical transporters and Na+ delivery are the main determinants of Na+ reabsorption along the kidney tubule.Tubular O2 consumption and the efficiency of sodium reabsorption are dependent on sodium diet. Abstract Na+ excretion by the kidney varies according to dietary Na+ intake. We undertook a systematic study of the effects of dietary salt intake on glomerular filtration rate (GFR) and tubular Na+ reabsorption. We examined the renal adaptive response in mice subjected to 7 days of a low sodium diet (LSD) containing 0.01% Na+, a normal sodium diet (NSD) containing 0.18% Na+ and a moderately high sodium diet (HSD) containing 1.25% Na+. As expected, LSD did not alter measured GFR and increased the abundance of total and cell‐surface NHE3, NKCC2, NCC, α‐ENaC and cleaved γ‐ENaC compared to NSD. Mathematical modelling predicted that tubular Na+ reabsorption increased in the proximal tubule but decreased in the distal nephron because of diminished Na+ delivery. This prediction was confirmed by the natriuretic response to diuretics targeting the thick ascending limb, the distal convoluted tubule or the collecting system. On the other hand, HSD did not alter measured GFR but decreased the abundance of the aforementioned transporters compared to NSD. Mathematical modelling predicted that tubular Na+ reabsorption decreased in the proximal tubule but increased in distal segments with lower transport efficiency with respect to O2 consumption. This prediction was confirmed by the natriuretic response to diuretics. The activity of the metabolic sensor adenosine monophosphate‐activated protein kinase (AMPK) was related to the changes in tubular Na+ reabsorption. Our data show that fractional Na+ reabsorption is distributed differently according to dietary Na+ intake and induces changes in tubular O2 consumption and sodium transport efficiency. PMID:28940314
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Evolutionary diversification of Mesobuthus α-scorpion toxins affecting sodium channels.
Zhu, Shunyi; Peigneur, Steve; Gao, Bin; Lu, Xiuxiu; Cao, Chunyang; Tytgat, Jan
2012-01-01
α-Scorpion toxins constitute a family of peptide modulators that induce a prolongation of the action potential of excitable cells by inhibiting voltage-gated sodium channel inactivation. Although they all adopt a conserved structural scaffold, the potency and phylogentic preference of these toxins largely vary, which render them an intriguing model for studying evolutionary diversification among family members. Here, we report molecular characterization of a new multigene family of α-toxins comprising 13 members (named MeuNaTxα-1 to MeuNaTxα-13) from the scorpion Mesobuthus eupeus. Of them, five native toxins (MeuNaTxα-1 to -5) were purified to homogeneity from the venom and the solution structure of MeuNaTxα-5 was solved by nuclear magnetic resonance. A systematic functional evaluation of MeuNaTxα-1, -2, -4, and -5 was conducted by two-electrode voltage-clamp recordings on seven cloned mammalian voltage-gated sodium channels (Na(v)1.2 to Na(v)1.8) and the insect counterpart DmNa(v)1 expressed in Xenopus oocytes. Results show that all these four peptides slow inactivation of DmNa(v)1 and are inactive on Na(v)1.8 at micromolar concentrations. However, they exhibit differential specificity for the other six channel isoforms (Na(v)1.2 to Na(v)1.7), in which MeuNaTxα-4 shows no activity on these isoforms and thus represents the first Mesobuthus-derived insect-selective α-toxin identified so far with a half maximal effective concentration of 130 ± 2 nm on DmNa(v)1 and a half maximal lethal dose of about 200 pmol g(-1) on the insect Musca domestica; MeuNaTxα-2 only affects Na(v)1.4; MeuNaTxα-1 and MeuNaTxα-5 have a wider range of channel spectrum, the former active on Na(v)1.2, Na(v)1.3, Na(v)1.6, and Na(v)1.7, whereas the latter acting on Na(v)1.3-Na(v)1.7. Remarkably, MeuNaTxα-4 and MeuNaTxα-5 are two nearly identical peptides differing by only one point mutation at site 50 (A50V) but exhibit rather different channel subtype selectivity, highlighting a switch role of this site in altering the target specificity. By the maximum likelihood models of codon substitution, we detected nine positively selected sites (PSSs) that could be involved in functional diversification of Mesobuthus α-toxins. The PSSs include site 50 and other seven sites located in functional surfaces of α-toxins. This work represents the first thorough investigation of evolutionary diversification of α-toxins derived from a specific scorpion lineage from the perspectives of sequence, structure, function, and evolution.
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On the Post-Compaction Evolution of Tensile Strength of Sodium Chloride-Starch Mixture Tablets.
Radojevic, Jovana; Zavaliangos, Antonios
2017-08-01
This study focuses on the evolution of mechanical behavior of starch and sodium chloride (NaCl) mixture tablets after compaction. This type of mixture has attracted attention in the past because such tablets exhibit lower tensile strengths than the ones of its individual components. Here we demonstrate that the strengths of NaCl-starch mixtures and NaCl tablets evolve after compaction in an opposite way. When stored at relative humidity of 60%, NaCl tablets strengthen with time, whereas NaCl-starch mixtures weaken. To explain this behavior, we propose that in the NaCl-starch mixture, the presence of 2 materials with significantly different elastic moduli leads to creation of tensile stresses at the stiffer NaCl-NaCl contacts. Such tensile stresses lead to a reduction in strength of the compacted mixtures by negating a local dissolution-reprecipitation mechanism, which strengthens the NaCl-NaCl in pure NaCl tablet. This effect is proven by experimental results from NaCl specimens diametrically loaded during storage. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
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Eichelberger, Maryna C; Morens, David M; Taubenberger, Jeffery K
2018-04-16
Neuraminidase (NA) plays an essential role in influenza virus replication, facilitating multicycle infection predominantly by releasing virions from infected cells. NA-inhibiting antibodies provide resistance to disease and NA-specific antibodies contribute to vaccine efficacy. The primary reason NA vaccine content and immunogenicity was not routinely measured in the past, was the lack of suitable assays to quantify NA and NA-specific antibodies. These are now available and with recent appreciation of its contribution to immunity, NA content of seasonal and pandemic vaccines is being considered. An added benefit of NA as a vaccine antigen is that many NA-specific antibodies bind to domains that are well conserved within a subtype, protecting against heterologous viruses. This suggests NA may be a good choice for inclusion in universal influenza vaccines. Published by Elsevier Ltd.
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Moon, Chan Hong; Kim, Jung-Hwan; Zhao, Tiejun; Bae, Kyongtae Ty
2013-11-01
To develop quantitative dual-tuned (DT) (1) H/(23) Na MRI of human knee cartilage in vivo at 7 Tesla (T). A sensitive (23) Na transceiver array RF coil was developed at 7T. B1 fields generated by the transceiver array coil were characterized and corrected in the (23) Na images. Point spread function (PSF) of the (23) Na images was measured, and the signal decrease due to partial-volume-effect was compensated in [(23) Na] quantification of knee cartilage. SNR and [(23) Na] in anterior femoral cartilage were measured from seven healthy subjects. SNR of (23) Na image with the transceiver array coil was higher than that of birdcage coil. SNR in the cartilage at 2-mm isotropic resolution was 26.80 ± 3.69 (n = 7). B1 transmission and reception fields produced by the DT coil at 7T were similar to each other. Effective full-width-half-maximum of (23) Na image was ∼5 mm at 2-mm resolution. Mean [(23) Na] was 288.13 ± 29.50 mM (n = 7) in the anterior femoral cartilage of normal subjects. We developed a new high-sensitivity (23) Na RF coil for knee MRI at 7T. Our (1) H/(23) Na MRI allowed quantitative measurement of [(23) Na] in knee cartilage by measuring PSF and cartilage thickness from (23) Na and (1) H image, respectively. Copyright © 2013 Wiley Periodicals, Inc.
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Györy, A Z; Roby, H
1977-01-01
1. With the aid of micropuncture techniques, proximal tubular transepithelial concentration differences for Na (deltaC Na) and chloride (deltaC Cl) were measured in kidney cortex slices at bathing fluid Na concentrations from 10 to 400 m-mole. kg-1. Tissue content of water, Na and K was also measured in such slices. Under steady-state conditions of zero net flux of NaCl and water, deltaC Na represents the sum of active Na transport, factored by the tubular permeability coefficient added to a component of flux due to electrical forces. 2. The relation between bathing fluid Na concentraton and deltaC Na appeared sigmoid in form suggesting an allosteric mechanism for the transport step. 3. Transtubular potential difference, calculated from transepithelial Cl distribution ratios, did not appear constant at the various bathing fluid Na concentrations. Correcting for the effect of these potential differences on the value of each deltaC Na did not convert the sigmoid transport curve to a hyperbolic one, confirming the suggested allosteric nature of the active Na transport step. 4. Intracellular Na content varied linearly with bathing fluid Na concentrations implying free entry of this cation into the cell. This also suggests that the sigmoid transport curve is related to the properties of the active Na transport pump. PMID:856986
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Allan, Phoebe K.; Griffin, John M.; Darwiche, Ali; ...
2016-01-29
We use operando pair distribution function (PDF) analysis and ex situ 23Na magic-angle spinning solid-state nuclear magnetic resonance (MAS ssNMR) spectroscopy to gain insight into the alloying mechanism of high-capacity antimony anodes for sodium-ion batteries. Subtraction of the PDF of crystalline Na xSb phases from the total PDF, an approach constrained by chemical phase information gained from 23Na ssNMR in reference to relevant model compounds, identifies two previously uncharacterized intermediate species formed electrochemically; a-Na 3–xSb (x ≈ 0.4–0.5), a structure locally similar to crystalline Na 3Sb (c-Na 3Sb) but with significant numbers of sodium vacancies and a limited correlation length,more » and a-Na1.7Sb, a highly amorphous structure featuring some Sb–Sb bonding. The first sodiation breaks down the crystalline antimony to form first a-Na 3–xSb and, finally, crystalline Na 3Sb. Desodiation results in the formation of an electrode formed of a composite of crystalline and amorphous antimony networks. We link the different reactivity of these networks to a series of sequential sodiation reactions manifesting as a cascade of processes observed in the electrochemical profile of subsequent cycles. The amorphous network reacts at higher voltages reforming a-Na 1.7Sb, then a-Na 3–xSb, whereas lower potentials are required for the sodiation of crystalline antimony, which reacts to form a-Na 3–xSb without the formation of a-Na 1.7Sb. a-Na 3–xSb is converted to crystalline Na 3Sb at the end of the second discharge. In the end, we find no evidence of formation of NaSb. Variable temperature 23Na NMR experiments reveal significant sodium mobility within c-Na 3Sb; this is a possible contributing factor to the excellent rate performance of Sb anodes.« less
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Identification of a 3rd Na+ Binding Site of the Glycine Transporter, GlyT2.
Subramanian, Nandhitha; Scopelitti, Amanda J; Carland, Jane E; Ryan, Renae M; O'Mara, Megan L; Vandenberg, Robert J
2016-01-01
The Na+/Cl- dependent glycine transporters GlyT1 and GlyT2 regulate synaptic glycine concentrations. Glycine transport by GlyT2 is coupled to the co-transport of three Na+ ions, whereas transport by GlyT1 is coupled to the co-transport of only two Na+ ions. These differences in ion-flux coupling determine their respective concentrating capacities and have a direct bearing on their functional roles in synaptic transmission. The crystal structures of the closely related bacterial Na+-dependent leucine transporter, LeuTAa, and the Drosophila dopamine transporter, dDAT, have allowed prediction of two Na+ binding sites in GlyT2, but the physical location of the third Na+ site in GlyT2 is unknown. A bacterial betaine transporter, BetP, has also been crystallized and shows structural similarity to LeuTAa. Although betaine transport by BetP is coupled to the co-transport of two Na+ ions, the first Na+ site is not conserved between BetP and LeuTAa, the so called Na1' site. We hypothesized that the third Na+ binding site (Na3 site) of GlyT2 corresponds to the BetP Na1' binding site. To identify the Na3 binding site of GlyT2, we performed molecular dynamics (MD) simulations. Surprisingly, a Na+ placed at the location consistent with the Na1' site of BetP spontaneously dissociated from its initial location and bound instead to a novel Na3 site. Using a combination of MD simulations of a comparative model of GlyT2 together with an analysis of the functional properties of wild type and mutant GlyTs we have identified an electrostatically favorable novel third Na+ binding site in GlyT2 formed by Trp263 and Met276 in TM3, Ala481 in TM6 and Glu648 in TM10.
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Identification of a 3rd Na+ Binding Site of the Glycine Transporter, GlyT2
Subramanian, Nandhitha; Scopelitti, Amanda J.; Carland, Jane E.; Ryan, Renae M.; O’Mara, Megan L.; Vandenberg, Robert J.
2016-01-01
The Na+/Cl- dependent glycine transporters GlyT1 and GlyT2 regulate synaptic glycine concentrations. Glycine transport by GlyT2 is coupled to the co-transport of three Na+ ions, whereas transport by GlyT1 is coupled to the co-transport of only two Na+ ions. These differences in ion-flux coupling determine their respective concentrating capacities and have a direct bearing on their functional roles in synaptic transmission. The crystal structures of the closely related bacterial Na+-dependent leucine transporter, LeuTAa, and the Drosophila dopamine transporter, dDAT, have allowed prediction of two Na+ binding sites in GlyT2, but the physical location of the third Na+ site in GlyT2 is unknown. A bacterial betaine transporter, BetP, has also been crystallized and shows structural similarity to LeuTAa. Although betaine transport by BetP is coupled to the co-transport of two Na+ ions, the first Na+ site is not conserved between BetP and LeuTAa, the so called Na1' site. We hypothesized that the third Na+ binding site (Na3 site) of GlyT2 corresponds to the BetP Na1' binding site. To identify the Na3 binding site of GlyT2, we performed molecular dynamics (MD) simulations. Surprisingly, a Na+ placed at the location consistent with the Na1' site of BetP spontaneously dissociated from its initial location and bound instead to a novel Na3 site. Using a combination of MD simulations of a comparative model of GlyT2 together with an analysis of the functional properties of wild type and mutant GlyTs we have identified an electrostatically favorable novel third Na+ binding site in GlyT2 formed by Trp263 and Met276 in TM3, Ala481 in TM6 and Glu648 in TM10. PMID:27337045
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Vedovato, Natascia
2014-01-01
A single Na+/K+-ATPase pumps three Na+ outwards and two K+ inwards by alternately exposing ion-binding sites to opposite sides of the membrane in a conformational sequence coupled to pump autophosphorylation from ATP and auto-dephosphorylation. The larger flow of Na+ than K+ generates outward current across the cell membrane. Less well understood is the ability of Na+/K+ pumps to generate an inward current of protons. Originally noted in pumps deprived of external K+ and Na+ ions, as inward current at negative membrane potentials that becomes amplified when external pH is lowered, this proton current is generally viewed as an artifact of those unnatural conditions. We demonstrate here that this inward current also flows at physiological K+ and Na+ concentrations. We show that protons exploit ready reversibility of conformational changes associated with extracellular Na+ release from phosphorylated Na+/K+ pumps. Reversal of a subset of these transitions allows an extracellular proton to bind an acidic side chain and to be subsequently released to the cytoplasm. This back-step of phosphorylated Na+/K+ pumps that enables proton import is not required for completion of the 3 Na+/2 K+ transport cycle. However, the back-step occurs readily during Na+/K+ transport when external K+ ion binding and occlusion are delayed, and it occurs more frequently when lowered extracellular pH raises the probability of protonation of the externally accessible carboxylate side chain. The proton route passes through the Na+-selective binding site III and is distinct from the principal pathway traversed by the majority of transported Na+ and K+ ions that passes through binding site II. The inferred occurrence of Na+/K+ exchange and H+ import during the same conformational cycle of a single molecule identifies the Na+/K+ pump as a hybrid transporter. Whether Na+/K+ pump–mediated proton inflow may have any physiological or pathophysiological significance remains to be clarified. PMID:24688018
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Allan, Phoebe K.; Griffin, John M.; Darwiche, Ali
We use operando pair distribution function (PDF) analysis and ex situ 23Na magic-angle spinning solid-state nuclear magnetic resonance (MAS ssNMR) spectroscopy to gain insight into the alloying mechanism of high-capacity antimony anodes for sodium-ion batteries. Subtraction of the PDF of crystalline Na xSb phases from the total PDF, an approach constrained by chemical phase information gained from 23Na ssNMR in reference to relevant model compounds, identifies two previously uncharacterized intermediate species formed electrochemically; a-Na 3–xSb (x ≈ 0.4–0.5), a structure locally similar to crystalline Na 3Sb (c-Na 3Sb) but with significant numbers of sodium vacancies and a limited correlation length,more » and a-Na1.7Sb, a highly amorphous structure featuring some Sb–Sb bonding. The first sodiation breaks down the crystalline antimony to form first a-Na 3–xSb and, finally, crystalline Na 3Sb. Desodiation results in the formation of an electrode formed of a composite of crystalline and amorphous antimony networks. We link the different reactivity of these networks to a series of sequential sodiation reactions manifesting as a cascade of processes observed in the electrochemical profile of subsequent cycles. The amorphous network reacts at higher voltages reforming a-Na 1.7Sb, then a-Na 3–xSb, whereas lower potentials are required for the sodiation of crystalline antimony, which reacts to form a-Na 3–xSb without the formation of a-Na 1.7Sb. a-Na 3–xSb is converted to crystalline Na 3Sb at the end of the second discharge. In the end, we find no evidence of formation of NaSb. Variable temperature 23Na NMR experiments reveal significant sodium mobility within c-Na 3Sb; this is a possible contributing factor to the excellent rate performance of Sb anodes.« less
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A Sensor Based on LiCl/NaA Zeolite Composites for Effective Humidity Sensing.
Zhang, Ying; Xiang, Hongyu; Sun, Liang; Xie, Qiuhong; Liu, Man; Chen, Yu; Ruan, Shengping
2018-03-01
LiCl/NaA zeolite composites were successfully prepared by doping 1 wt%, 2 wt%, 5 wt%, and 8 wt% of LiCl into NaA zeolite. The humidity sensing properties of LiCl/NaA composites were investigated among 11% 95% relative humidity (RH). The LiCl/NaA composites exhibited better humidity sensing properties than pure NaA zeolite. The sensor made by 2 wt% Li-doped NaA zeolite possesses the best linearly in the whole RH. These results demonstrate that the LiCl/NaA composites have the potential application in humidity sensing.
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2012-10-17
0 0 ~60 ~90 Helicopters n/a n/a n/a n/a ~34 ~153 ~157 Subtotal above aircraft n/a n/a n/a n/a ~179 ~468 ~ 505 Source: Prepared by CRS. Source for...Congressional Research Service 87 The Air-Sea Battle Concept centers on networked, integrated, attack-in-depth to disrupt, destroy and defeat ( NIA -D3) A2/AD...of U.S. forces; and defeat an adversary’s employed weapons to preserve essential U.S. Joint forces and their enablers. Through NIA -D3, air and naval
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Aboussatar, Mohamed; Laboratoire de Physico-Chimie de l’État Solide, Faculté des Sciences de Sfax, Université de Sfax, BP 1171, 3000 Sfax; Mbarek, Aïcha
Isothermal sections of the diagram representing phase relationships in the NaF-CdO-NaPO{sub 3} system have been investigated by solid state reactions and powder X-ray diffraction. This phase diagram investigation confirms the polymorphism of the NaCdPO{sub 4} side component and the structure of the ß high temperature polymorph (orthorhombic, space group Pnma and unit cell parameters a=9.3118(2), b=7.0459(1), c=5.1849(1) Å has been refined. A new fluorophosphate, Na{sub 2}CdPO{sub 4}F, has been discovered and its crystal structure determined and refined from powder X-ray diffraction data. It exhibits a new 3D structure with orthorhombic symmetry, space group Pnma and unit cell parameters a=5.3731(1), b=6.8530(1),more » c=12.2691(2) Å. The structure is closely related to those of the high temperature polymorph of the nacaphite Na{sub 2}CaPO{sub 4}F and the fluorosilicate Ca{sub 2}NaSiO{sub 4}F but differs essentially in the cationic repartition since the structure is fully ordered with one Na site (8d) and one Cd site (4c). Relationships with other Na{sub 2}M{sup II}PO{sub 4}F (M{sup II}=Mg, Ca, Mn, Fe, Co, Ni) have been examined and the crystal-chemical and topographical analysis of these fluorophosphates is briefly reviewed. IR, Raman, optical and {sup 19}F, {sup 23}Na, {sup 31}P MAS NMR characterizations of Na{sub 2}CdPO{sub 4}F have been investigated. - Graphical abstract: The structure of the compound Na{sub 2}CdPO{sub 4}F, discovered during the study of the phase relationships in the NaF-CdO-NaPO{sub 3} system, has been determined and compared with other Na{sub 2}M{sup II}PO{sub 4}F fluorophosphates. - Highlights: • XRD analysis of the isothermal section of the NaF-CdO-NaPO{sub 3} system at 923 K. • Rietveld refinement of the high temperature polymorph β-NaCdPO{sub 4}. • Crystal structure of the new Na{sub 2}CdPO{sub 4}F fluorophosphate determined from powder XRD. • Crystal structure - composition relationships of Na{sub 2}M{sup II}PO{sub 4}F compounds are reviewed. • IR, Raman, optical and {sup 19}F, {sup 23}Na, {sup 31}P MAS NMR characterizations of Na{sub 2}CdPO{sub 4}F.« less
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Kostyrko, Vitaly A.; Bertsova, Yulia V.; Serebryakova, Marina V.; Baykov, Alexander A.
2015-01-01
ABSTRACT Na+-translocating NADH:quinone oxidoreductase (Na+-NQR) catalyzes electron transfer from NADH to ubiquinone in the bacterial respiratory chain, coupled with Na+ translocation across the membrane. Na+-NQR maturation involves covalent attachment of flavin mononucleotide (FMN) residues, catalyzed by flavin transferase encoded by the nqr-associated apbE gene. Analysis of complete bacterial genomes has revealed another putative gene (duf539, here renamed nqrM) that usually follows the apbE gene and is present only in Na+-NQR-containing bacteria. Expression of the Vibrio harveyi nqr operon alone or with the associated apbE gene in Escherichia coli, which lacks its own Na+-NQR, resulted in an enzyme incapable of Na+-dependent NADH or reduced nicotinamide hypoxanthine dinucleotide (dNADH) oxidation. However, fully functional Na+-NQR was restored when these genes were coexpressed with the V. harveyi nqrM gene. Furthermore, nqrM lesions in Klebsiella pneumoniae and V. harveyi prevented production of functional Na+-NQR, which could be recovered by an nqrM-containing plasmid. The Na+-NQR complex isolated from the nqrM-deficient strain of V. harveyi lacks several subunits, indicating that nqrM is necessary for Na+-NQR assembly. The protein product of the nqrM gene, NqrM, contains a single putative transmembrane α-helix and four conserved Cys residues. Mutating one of these residues (Cys33 in V. harveyi NqrM) to Ser completely prevented Na+-NQR maturation, whereas mutating any other Cys residue only decreased the yield of the mature protein. These findings identify NqrM as the second specific maturation factor of Na+-NQR in proteobacteria, which is presumably involved in the delivery of Fe to form the (Cys)4[Fe] center between subunits NqrD and NqrE. IMPORTANCE Na+-translocating NADH:quinone oxidoreductase complex (Na+-NQR) is a unique primary Na+ pump believed to enhance the vitality of many bacteria, including important pathogens such as Vibrio cholerae, Vibrio parahaemolyticus, Haemophilus influenzae, Neisseria gonorrhoeae, Pasteurella multocida, Porphyromonas gingivalis, Enterobacter aerogenes, and Yersinia pestis. Production of Na+-NQR in bacteria requires Na+-NQR-specific maturation factors. We earlier identified one such factor (ApbE) that covalently attaches flavin residues to Na+-NQR. Here we identify the other protein factor, designated NqrM, and show that NqrM and ApbE suffice to produce functional Na+-NQR from the Vibrio harveyi nqr operon. NqrM may be involved in Fe delivery to a unique Cys4[Fe] center during Na+-NQR assembly. Besides highlighting Na+-NQR biogenesis, these findings suggest a novel drug target to combat Na+-NQR-containing bacteria. PMID:26644436
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Analysis of bakery products by laser-induced breakdown spectroscopy.
Bilge, Gonca; Boyacı, İsmail Hakkı; Eseller, Kemal Efe; Tamer, Uğur; Çakır, Serhat
2015-08-15
In this study, we focused on the detection of Na in bakery products by using laser-induced breakdown spectroscopy (LIBS) as a quick and simple method. LIBS experiments were performed to examine the Na at 589 nm to quantify NaCl. A series of standard bread sample pellets containing various concentrations of NaCl (0.025-3.5%) were used to construct the calibration curves and to determine the detection limits of the measurements. Calibration graphs were drawn to indicate functions of NaCl and Na concentrations, which showed good linearity in the range of 0.025-3.5% NaCl and 0.01-1.4% Na concentrations with correlation coefficients (R(2)) values greater than 0.98 and 0.96. The obtained detection limits for NaCl and Na were 175 and 69 ppm, respectively. Performed experimental studies showed that LIBS is a convenient method for commercial bakery products to quantify NaCl concentrations as a rapid and in situ technique. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Novel duplex vapor-electrochemical method for silicon solar cells
NASA Technical Reports Server (NTRS)
Nanis, L.; Sanjurjo, A.; Westphal, S.
1979-01-01
Optimization studies were carried out for the SiF4-Na reaction with solid Na feed. The goals of the study were the consistent production of high purity reaction products and the gathering of relevant information needed to scale-up the reactor. Parameters studied include: (1) effect of surface to volume ratio of Na slices on the extent of reaction; (2) effect of Na surface oxidation on the extent of reaction; (3) effect of external heating on the extent of SiF4-Na reaction; (4) effect of Na slice addition rate on extent of the reaction; and (5) SiF4-Na reaction - high pressure experiments. An investigation was also made of the possible role played by NaF as a fluxing agent during the separation of silicon by melting of the reaction product (Si + NaF) mixture. Since silicon can be produced by the thermite reaction between Na2SiF6 and Na, studies were initiated to gather information on parameters which control the efficiency of the thermite reaction.
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Interaction of NaOH solutions with silica surfaces
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rimsza, Jessica M.; Jones, Reese E.; Criscenti, Louise J.
Sodium adsorption on silica surfaces depends on the solution counter-ion. Here, we use NaOH solutions to investigate basic environments. Sodium adsorption on hydroxylated silica surfaces from NaOH solutions were investigated through molecular dynamics with a dissociative force field, allowing for the development of secondary molecular species. Furthermore, across the NaOH concentrations (0.01 M – 1.0 M), ~50% of the Na + ions were concentrated in the surface region, developing silica surface charges between –0.01 C/m 2 (0.01 M NaOH) and –0.76 C/m 2 (1.0 M NaOH) due to surface site deprotonation. Five inner-sphere adsorption complexes were identified, including monodentate, bidentate,more » and tridentate configurations and two additional structures, with Na + ions coordinated by bridging oxygen and hydroxyl groups or water molecules. Coordination of Na + ions by bridging oxygen atoms indicates partial or complete incorporation of Na + ions into the silica surface. Residence time analysis identified that Na + ions coordinated by bridging oxygen atoms stayed adsorbed onto the surface four times longer than the mono/bi/tridentate species, indicating formation of relatively stable and persistent Na + ion adsorption structures. Such inner-sphere complexes form only at NaOH concentrations of > 0.5 M. Na + adsorption and lifetimes have implications for the stability of silica surfaces.« less
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Interaction of NaOH solutions with silica surfaces
Rimsza, Jessica M.; Jones, Reese E.; Criscenti, Louise J.
2018-01-16
Sodium adsorption on silica surfaces depends on the solution counter-ion. Here, we use NaOH solutions to investigate basic environments. Sodium adsorption on hydroxylated silica surfaces from NaOH solutions were investigated through molecular dynamics with a dissociative force field, allowing for the development of secondary molecular species. Furthermore, across the NaOH concentrations (0.01 M – 1.0 M), ~50% of the Na + ions were concentrated in the surface region, developing silica surface charges between –0.01 C/m 2 (0.01 M NaOH) and –0.76 C/m 2 (1.0 M NaOH) due to surface site deprotonation. Five inner-sphere adsorption complexes were identified, including monodentate, bidentate,more » and tridentate configurations and two additional structures, with Na + ions coordinated by bridging oxygen and hydroxyl groups or water molecules. Coordination of Na + ions by bridging oxygen atoms indicates partial or complete incorporation of Na + ions into the silica surface. Residence time analysis identified that Na + ions coordinated by bridging oxygen atoms stayed adsorbed onto the surface four times longer than the mono/bi/tridentate species, indicating formation of relatively stable and persistent Na + ion adsorption structures. Such inner-sphere complexes form only at NaOH concentrations of > 0.5 M. Na + adsorption and lifetimes have implications for the stability of silica surfaces.« less
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Comprehensive Insights into the Reactivity of Electrolytes Based on Sodium Ions.
Eshetu, Gebrekidan Gebresilassie; Grugeon, Sylvie; Kim, Huikyong; Jeong, Sangsik; Wu, Liming; Gachot, Gregory; Laruelle, Stephane; Armand, Michel; Passerini, Stefano
2016-03-08
We report a systematic investigation of Na-based electrolytes that comprise various NaX [X=hexafluorophosphate (PF6 ), perchlorate (ClO4 ), bis(trifluoromethanesulfonyl)imide (TFSI), fluorosulfonyl-(trifluoromethanesulfonyl)imide (FTFSI), and bis(fluorosulfonyl)imide (FSI)] salts and solvent mixtures [ethylene carbonate (EC)/dimethyl carbonate (DMC), EC/diethyl carbonate (DEC), and EC/propylene carbonate (PC)] with respect to the Al current collector stability, formation of soluble degradation compounds, reactivity towards sodiated hard carbon (Nax -HC), and solid-electrolyte interphase (SEI) layer formation. Cyclic voltammetry demonstrates that the stability of Al is highly influenced by the nature of the anions, solvents, and additives. GC-MS analysis reveals that the formation of SEI telltales depends on the nature of the linear alkyl carbonates and the battery chemistry (Li(+) vs. Na(+) ). FTIR spectroscopy shows that double alkyl carbonates are the main components of the SEI layer on Nax -HC. In the presence of Na salts, EC/DMC and EC/DEC presented a higher reactivity towards Nax -HC than EC/PC. For a fixed solvent mixture, the onset temperature follows the sequence NaClO4
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Hettinger, Thomas P.; Savoy, Lawrence D.; Frank, Marion E.
2012-01-01
Component signaling in taste mixtures containing both beneficial and dangerous chemicals depends on peripheral processing. Unidirectional mixture suppression of chorda tympani (CT) nerve responses to sucrose by quinine and acid is documented for golden hamsters (Mesocricetus auratus). To investigate mixtures of NaCl and acids, we recorded multifiber responses to 50 mM NaCl, 1 and 3 mM citric acid and acetic acid, 250 μM citric acid, 20 mM acetic acid, and all binary combinations of each acid with NaCl (with and without 30 μM amiloride added). By blocking epithelial Na+ channels, amiloride treatment separated amiloride-sensitive NaCl-specific responses from amiloride-insensitive electrolyte-generalist responses, which encompass all of the CT response to the acids as well as responses to NaCl. Like CT sucrose responses, the amiloride-sensitive NaCl responses were suppressed by as much as 50% by citric acid (P = 0.001). The amiloride-insensitive electrolyte-generalist responses to NaCl + acid mixtures approximated the sum of NaCl and acid component responses. Thus, although NaCl-specific responses to NaCl were weakened in NaCl–acid mixtures, electrolyte-generalist responses to acid and NaCl, which tastes KCl-like, were transmitted undiminished in intensity to the central nervous system. The 2 distinct CT pathways are consistent with known rodent behavioral discriminations. PMID:22451526
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Nieves-González, Aniel; Clausen, Chris; Marcano, Mariano; Layton, Anita T; Layton, Harold E; Moore, Leon C
2013-03-15
Thick ascending limb (TAL) cells are capable of reducing tubular fluid Na(+) concentration to as low as ~25 mM, and yet they are thought to transport Na(+) efficiently owing to passive paracellular Na(+) absorption. Transport efficiency in the TAL is of particular importance in the outer medulla where O(2) availability is limited by low blood flow. We used a mathematical model of a TAL cell to estimate the efficiency of Na(+) transport and to examine how tubular dilution and cell volume regulation influence transport efficiency. The TAL cell model represents 13 major solutes and the associated transporters and channels; model equations are based on mass conservation and electroneutrality constraints. We analyzed TAL transport in cells with conditions relevant to the inner stripe of the outer medulla, the cortico-medullary junction, and the distal cortical TAL. At each location Na(+) transport efficiency was computed as functions of changes in luminal NaCl concentration ([NaCl]), [K(+)], [NH(4)(+)], junctional Na(+) permeability, and apical K(+) permeability. Na(+) transport efficiency was calculated as the ratio of total net Na(+) transport to transcellular Na(+) transport. Transport efficiency is predicted to be highest at the cortico-medullary boundary where the transepithelial Na(+) gradient is the smallest. Transport efficiency is lowest in the cortex where luminal [NaCl] approaches static head.
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An RNA-Cleaving Catalytic DNA Accelerated by Freezing.
Yu, Tianmeng; Zhou, Wenhu; Liu, Juewen
2018-05-18
The EtNa DNAzyme was isolated during the isopropanol precipitation step of an in vitro selection effort. Although inactive with the intended cofactor, its RNA cleavage activity was observed under a few conditions. With Na + , EtNa was highly active in ∼50 % ethanol, whereas in water, it was highly active with Ca 2+ . In this work, we showed that the EtNa DNAzyme was accelerated by freezing in water in the presence of Na + . The apparent K d value reached 6.2 mm Na + under the frozen condition, over 20 times tighter than that in water at room temperature. With 10 mm Na + , EtNa had a cleavage rate of 0.12 h -1 after freezing at -20 °C. This effect was unique to EtNa, as all other tested DNAzymes were inhibited by freezing except for the Na + -specific NaA43. Freezing also inhibited EtNa if Ca 2+ was used. We attributed this to the concentrations of EtNa and Na + in the micropockets between ice crystals, but divalent metals might misfold DNA. Overall, we have systematically studied the effect of freezing on the RNA-cleavage activity of DNAzymes. The DNAzyme sequence and the metal ion species are both crucial to determine the effect of freezing. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Validation of estimating food intake in gray wolves by 22Na turnover
DelGiudice, G.D.; Duquette, L.S.; Seal, U.S.; Mech, L.D.
1991-01-01
We studied 22sodium (22Na) turnover as a means of estimating food intake in 6 captive, adult gray wolves (Canis lupus) (2 F, 4 M) over a 31-day feeding period. Wolves were fed white-tailed deer (Odocoileus virginianus) meat only. Mean mass-specific exchangeable Na pool was 44.8 .+-. 0.7 mEq/kg; there was no differeence between males and females. Total exchangeable Na was related (r2 = 0.85, P < 0.009) to body mass. Overall, 22Na turnover overestimated Na intake by 9.8 .+-. 2.4% after 32 days. Actual Na intake was similar in males and females; however, Na turnover (P < 0.05) and the discrepancy (P < 0.01) between turnover and actual Na intake were greater in females than males. From Day 8 to the end of the study, the absolute difference (mEq) between Na intake and Na turnover remained stable. Sodium turnover (mEq/kg/day) was a reliable (r2 = 0.91, P < 0.001) estimator of food consumption (g/kg/day) in wolves over a 32-day period. Sampling blood and weighing wolves every 1-4 days permitted identification of several potential sources of error, including changes in size of exchangeable Na pools, exchange of 22Na with gastrointestinal and bone Na, and rapid loss of the isotope by urinary excretion.
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Møller, Inge S; Gilliham, Matthew; Jha, Deepa; Mayo, Gwenda M; Roy, Stuart J; Coates, Juliet C; Haseloff, Jim; Tester, Mark
2009-07-01
Soil salinity affects large areas of cultivated land, causing significant reductions in crop yield globally. The Na+ toxicity of many crop plants is correlated with overaccumulation of Na+ in the shoot. We have previously suggested that the engineering of Na+ exclusion from the shoot could be achieved through an alteration of plasma membrane Na+ transport processes in the root, if these alterations were cell type specific. Here, it is shown that expression of the Na+ transporter HKT1;1 in the mature root stele of Arabidopsis thaliana decreases Na+ accumulation in the shoot by 37 to 64%. The expression of HKT1;1 specifically in the mature root stele is achieved using an enhancer trap expression system for specific and strong overexpression. The effect in the shoot is caused by the increased influx, mediated by HKT1;1, of Na+ into stelar root cells, which is demonstrated in planta and leads to a reduction of root-to-shoot transfer of Na+. Plants with reduced shoot Na+ also have increased salinity tolerance. By contrast, plants constitutively expressing HKT1;1 driven by the cauliflower mosaic virus 35S promoter accumulated high shoot Na+ and grew poorly. Our results demonstrate that the modification of a specific Na+ transport process in specific cell types can reduce shoot Na+ accumulation, an important component of salinity tolerance of many higher plants.
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Na and K Dependence of the Na/K Pump in Cystic Fibrosis Fibroblasts
NASA Astrophysics Data System (ADS)
Reznik, Vivian M.; Schneider, Jerry A.; Mendoza, Stanley A.
1981-11-01
The Na and K dependence of the Na/K pump was measured in skin fibroblasts from patients with cystic fibrosis and age/sex-matched controls. Under basal conditions, there was no difference between control and cystic fibrosis cells in protein per cell, intracellular Na and K content, or Na/K pump activity (measured as ouabain-sensitive 86Rb uptake). There was no difference in the Na dependence of the Na/K pump between cystic fibrosis cells and control cells. In cells from patients with cystic fibrosis, the Na/K pump had a significantly lower affinity for K (Km = 1.6 mM) when compared to normals (Km = 0.9 mM). This difference was demonstrated by using two independent experimental designs.
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Scheibener, S A; Richardi, V S; Buchwalter, D B
2016-02-01
The importance of insects in freshwater ecosystems has led to their extensive use in ecological monitoring programs. As freshwater systems are increasingly challenged by salinization and metal contamination, it is important to understand fundamental aspects of aquatic insect physiology (e.g., osmoregulatory processes) that contribute to insect responses to these stressors. Here we compared the uptake dynamics of Na as NaCl, NaHCO3 and Na2SO4 in the caddisfly Hydropsyche betteni across a range of Na concentrations (0.06-15.22 mM) encompassing the vast majority of North American freshwater ecosystems. Sulfate as the major anion resulted in decreased Na uptake rates relative to the chloride and bicarbonate salts. A comparison of Na (as NaHCO3) turnover rates in the caddisfly Hydropsyche sparna and the mayfly Maccaffertium sp. revealed different patterns in the 2 species. Both species appeared to tightly regulate their whole body sodium concentrations (at ∼47±1.8 μmol/g wet wt) across a range of Na concentrations (0.06-15.22 mM) over 7 days. However, at the highest Na concentration (15.22 mM), Na uptake rates in H. sparna (419.1 μM Na g(-1) hr(-1) wet wt) appeared close to saturation while Na uptake rates in Maccaffertium sp. were considerably faster (715 g μM Na g(-1) hr(-1) wet wt) and appeared to not be close to saturation. Na efflux studies in H. sparna revealed that loss rates are commensurate with uptake rates and are responsive to changes in water Na concentrations. A comparison of Na uptake rates (at 0.57 mM Na) across 9 species representing 4 major orders (Ephemeroptera, Plecoptera, Trichoptera and Diptera) demonstrated profound physiological differences across species after accounting for the influence of body weight. Faster Na uptake rates were associated with species described as being sensitive to salinization in field studies. The metals silver (Ag) and copper (Cu), known to be antagonistic to Na uptake in other aquatic taxa did not generally exhibit this effect in aquatic insects. Ag only reduced Na uptake at extremely high concentrations, while Cu generally stimulated Na uptake in aquatic insects, rather than suppress it. These results help explain the lack of insect responses to dissolved metal exposures in traditional toxicity testing and highlight the need to better understand fundamental physiological processes in this ecologically important faunal group. Copyright © 2015 Elsevier B.V. All rights reserved.
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Amaral, C C F; Ormiga, F; Boldrini, L C; Miranda, P G; Mendonça, T A; Granjeiro, J M; Gomes, J A C P
2018-05-15
To evaluate the effects of the [NaF 12 g/L + NaCl 1 g/L] solution used in the electrochemical dissolution process of fractured endodontic files, as well as its NiTi-containing product, on dentine hardness, topography and human fibroblast viability. Sixty single-rooted human teeth were evaluated for dentine microhardness using the Vickers hardness test and the area and number of dentinal tubules by scanning electron microscopy. The samples were divided according to the dentine surface treatment: distilled water; 17% EDTA; [NaF 12 g/L + NaCl 1 g/L]; and 17% EDTA + [NaF 12 g/L + NaCl 1 g/L]. Thirty-six single-rooted human teeth were divided according to the irrigation protocol: Dulbecco's Modified Eagle's Medium + 10% fetal bovine serum; 5.25% NaOCl; [NaF 12 g/L + NaCl 1 g/L]; and [NaF 12 g/L + NaCl 1 g/L+NiTi]. The extracts in contact with the apical foramen were used in the MTT assay to evaluate human fibroblast viability, with dilutions of 100, 50, 25 and 12.5%. Statistical tests used were paired t-tests, one-way ANOVA, Tukey's test, Kruskal-Wallis test and Dunn's post-test. The [NaF 12 g/L + NaCl 1 g/L] solution did not modify the dentine microhardness or the average dentinal tubule area. However, the EDTA induced changes in the dentine structure and microhardness (p<0.05). The [NaF 12 g/L + NaCl 1 g/L] solution and its NiTi-containing product had lower cytotoxicity than NaOCl at dilutions of 25% and 50% (p<0.01). The [NaF 12 g/L + NaCl 1 g/L] solution did not alter dentine microhardness or damage the dentine structure. It also demonstrated lower cytotoxicity than NaOCl. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Ma, Xuchu; Xu, Fen; Atkins, Tonya; Goforth, Andrea M.; Neiner, Doinita; Navrotsky, Alexandra; Kauzlarich, Susan M.
2010-01-01
Na4Si4 and Na4Ge4 are ideal chemical precursors for inorganic clathrate structures, clusters, and nanocrystals. The monoclinic Zintl phases, Na4Si4 and Na4Ge4, contain isolated homo-tetrahedranide [Si4]4− and [Ge4]4− clusters surrounded by alkali metal cations. In this study, a simple scalable route has been applied to prepare Zintl phases of composition Na4Si4 and Na4Ge4 using the reaction between NaH and Si or Ge at low temperature (420 °C for Na4Si4 and 270 °C for Na4Ge4). The method was also applied to K4Ge4, using KH and Ge as raw materials, to show the versatility of this approach. The influence of specific reaction conditions on the purity of these Zintl phases has been studied by controlling five factors: the method of reagent mixing (manual or ball milled), the stoichiometry between raw materials, the reaction temperature, the heating time and the gas flow rate. Moderate ball-milling and excess NaH or KH facilitate the formation of pure Na4Si4, Na4Ge4 or K4Ge4 at 420 °C (Na4Si4) or 270 °C (both M4Ge4 compounds, M = Na, K). TG/DSC analysis of the reaction of NaH and Ge indicates that ball milling reduces the temperature for reaction and confirms the formation temperature. This method provides large quantities of high quality Na4Si4 and Na4Ge4 without the need for specialized laboratory equipment, such as Schlenk lines, niobium/tantalum containers, or an arc welder, thereby expanding the accessibility and chemical utility of these phases by making them more convenient to prepare. This new synthetic method may also be extended to lithium-containing Zintl phases (LiH is commercially available) as well as to alkali metal-tetrel Zintl compounds of other compositions, e.g. K4Ge9. PMID:19921060
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Balashov, Sergei P.; Imasheva, Eleonora S.; Dioumaev, Andrei K.; ...
2014-11-06
A group of microbial retinal proteins most closely related to the proton pump xanthorhodopsin has a novel sequence motif and a novel function. Instead of, or in addition to, proton transport, they perform light-driven sodium ion transport, as reported for one representative of this group (KR2) from Krokinobacter. In this paper, we examine a similar protein, GLR from Gillisia limnaea, expressed in Escherichia coli, which shares some properties with KR2 but transports only Na +. The absorption spectrum of GLR is insensitive to Na + at concentrations of ≤3 M. However, very low concentrations of Na + cause profound differencesmore » in the decay and rise time of photocycle intermediates, consistent with a switch from a “Na +-independent” to a “Na +-dependent” photocycle (or photocycle branch) at ~60 μM Na +. The rates of photocycle steps in the latter, but not the former, are linearly dependent on Na + concentration. This suggests that a high-affinity Na + binding site is created transiently after photoexcitation, and entry of Na + from the bulk to this site redirects the course of events in the remainder of the cycle. A greater concentration of Na + is needed for switching the reaction path at lower pH. The data suggest therefore competition between H + and Na + to determine the two alternative pathways. The idea that a Na + binding site can be created at the Schiff base counterion is supported by the finding that upon perturbation of this region in the D251E mutant, Na + binds without photoexcitation. Furthermore, binding of Na+ to the mutant shifts the chromophore maximum to the red like that of H +, which occurs in the photocycle of the wild type.« less
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Mechanistic origin of low polarization in aprotic Na-O2 batteries.
Ma, Shunchao; McKee, William C; Wang, Jiawei; Guo, Limin; Jansen, Martin; Xu, Ye; Peng, Zhangquan
2017-05-21
Research interest in aprotic sodium-air (Na-O 2 ) batteries is growing because of their considerably high theoretical specific energy and potentially better reversibility than lithium-air (Li-O 2 ) batteries. While Li 2 O 2 has been unequivocally identified as the major discharge product in Li-O 2 batteries containing relatively stable electrolytes, a multitude of discharge products, including NaO 2 , Na 2 O 2 and Na 2 O 2 ·2H 2 O, have been reported for Na-O 2 batteries and the corresponding cathodic electrochemistry remains incompletely understood. Herein, we provide molecular-level insights into the key mechanistic differences between Na-O 2 and Li-O 2 batteries based on gold electrodes in strictly dry, aprotic dimethyl sulfoxide electrolytes through a combination of in situ spectroelectrochemistry and density functional theory based modeling. While like Li-O 2 batteries, the formation of oxygen reduction products (i.e., O 2 - , NaO 2 and Na 2 O 2 ) in Na-O 2 batteries depends critically on the electrode potential, two factors lead to a better reversibility of Na-O 2 electrochemistry, and are therefore highly beneficial to a viable rechargeable metal-air battery design: (i) only O 2 - and NaO 2 , and no Na 2 O 2 , form down to as low as ∼1.5 V vs. Na/Na + during discharge; (ii) solid NaO 2 is quite soluble and its formation and oxidation can proceed through micro-reversible EC (a chemical reaction of the product after the electron transfer) and CE (a chemical reaction preceding the electron transfer) processes, respectively, with O 2 - as the key intermediate.
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Irving, Roy M.; Pinkerton, Marie E.; Elfarra, Adnan A.
2012-01-01
N-Acetyl-S-(1,2-dichlorovinyl)-L-cysteine (NA-DCVC) has been detected in the urine of humans exposed to trichloroethylene and its related sulfoxide, N-acetyl-S-(1,2-dichlorovinyl)-L-cysteine sulfoxide (NA-DCVCS), has been detected as hemoglobin adducts in blood of rats dosed with S-(1,2-dichlorovinyl)-L-cysteine (DCVC) or S-(1,2-dichlorovinyl)-L-cysteine sulfoxide (DCVCS). Because the in vivo nephrotoxicity of NA-DCVCS was unknown, in this study, male Sprague-Dawley rats were dosed (i.p.) with 230 µmol/kg b.w. NA-DCVCS or its potential precursors, DCVCS or NA-DCVC. At 24 h post treatment, rats given NA-DCVC or NA-DCVCS exhibited kidney lesions and effects on renal function distinct from those caused by DCVCS. NA-DCVC and NA-DCVCS primarily affected the cortico-medullary proximal tubules (S2–S3 segments) while DCVCS primarily affected the outer cortical proximal tubules (S1–S2 segments). When NA-DCVCS or DCVCS was incubated with GSH in phosphate buffer pH 7.4 at 37°C, the corresponding glutathione conjugates were detected, but NA-DCVC was not reactive with GSH. Because NA-DCVCS exhibited a longer half-life than DCVCS and addition of rat liver cytosol enhanced GSH conjugate formation, catalysis of GSH conjugate formation by the liver could explain the lower toxicity of NA-DCVCS in comparison with DCVCS. Collectively, these results provide clear evidence that NA-DCVCS formation could play a significant role in DCVC, NA-DCVC, and trichloroethylene nephrotoxicity. They also suggest a role for hepatic metabolism in the mechanism of NA-DCVC nephrotoxicity. PMID:23253325
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Irving, Roy M; Pinkerton, Marie E; Elfarra, Adnan A
2013-02-15
N-Acetyl-S-(1,2-dichlorovinyl)-L-cysteine (NA-DCVC) has been detected in the urine of humans exposed to trichloroethylene and its related sulfoxide, N-acetyl-S-(1,2-dichlorovinyl)-L-cysteine sulfoxide (NA-DCVCS), has been detected as hemoglobin adducts in blood of rats dosed with S-(1,2-dichlorovinyl)-L-cysteine (DCVC) or S-(1,2-dichlorovinyl)-L-cysteine sulfoxide (DCVCS). Because the in vivo nephrotoxicity of NA-DCVCS was unknown, in this study, male Sprague-Dawley rats were dosed (i.p.) with 230 μmol/kg b.w. NA-DCVCS or its potential precursors, DCVCS or NA-DCVC. At 24 h post treatment, rats given NA-DCVC or NA-DCVCS exhibited kidney lesions and effects on renal function distinct from those caused by DCVCS. NA-DCVC and NA-DCVCS primarily affected the cortico-medullary proximal tubules (S(2)-S(3) segments) while DCVCS primarily affected the outer cortical proximal tubules (S(1)-S(2) segments). When NA-DCVCS or DCVCS was incubated with GSH in phosphate buffer pH 7.4 at 37°C, the corresponding glutathione conjugates were detected, but NA-DCVC was not reactive with GSH. Because NA-DCVCS exhibited a longer half-life than DCVCS and addition of rat liver cytosol enhanced GSH conjugate formation, catalysis of GSH conjugate formation by the liver could explain the lower toxicity of NA-DCVCS in comparison with DCVCS. Collectively, these results provide clear evidence that NA-DCVCS formation could play a significant role in DCVC, NA-DCVC, and trichloroethylene nephrotoxicity. They also suggest a role for hepatic metabolism in the mechanism of NA-DCVC nephrotoxicity. Copyright © 2012 Elsevier Inc. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Dargent, B.; Couraud, F.
1990-08-01
To address the issue of whether regulatory feedback exists between the electrical activity of a neuron and ion-channel density, the authors investigated the effect of Na{sup +}-channel activators (scorpion {alpha} toxin, batrachotoxin, and veratridine) on the density of Na{sup +} channels in fetal rat brain neurons in vitro. A partial but rapid (t{sub 1/2}, 15 min) disappearance of surface Na{sup +} channels was observed as measured by a decrease in the specific binding of ({sup 3}H)saxitoxin and {sup 125}I-labeled scorpion {beta} toxin and a decrease in specific {sup 22}Na{sup +} uptake. Moreover, the increase in the number of Na{sup +}more » channels that normally occurs during neuronal maturation in vitro was inhibited by chronic channel activator treatment. The induced disappearance of Na{sup +} channels was abolished by tetrodotoxin, was found to be dependent on the external Na{sup +} concentration, and was prevented when either choline (a nonpermeant ion) or Li{sup +} (a permeant ion) was substituted for Na{sup +}. Amphotericin B, a Na{sup +} ionophore, and monensin were able to mimick the effect of Na{sup +}-channel activators, while a KCl depolarization failed to do this. This feedback regulation seems to be a neuronal property since Na{sup +}-channel density in cultured astrocytes was not affected by channel activator treatment or by amphotericin B. The present evidence suggests that an increase in intracellular Na{sup +} concentration, whether elicited by Na{sup +}-channel activators or mediated by a Na{sup +} ionophore, can induce a decrease in surface Na{sup +} channels and therefore is involved in down-regulation of Na{sup +}-channel density in fetal rat brain neurons in vitro.« less
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Mushtaq, M. M. H.; Pasha, T. N.; Saima; Akram, M.; Mushtaq, T.; Parvin, R.; Farooq, U.; Mehmood, S.; Iqbal, K. J.; Hwangbo, J.
2013-01-01
A basal diet (0.8 g/kg dNa) was formulated in which each of the two sources (NaHCO3 and Na2SO4) were supplemented in such a way to attain four levels (1.7, 2.6, 3.5, and 4.4 g/kg) of total dNa, respectively, under 4×2 factorial arrangement. Eight dietary treatments were replicated four times, with 40 birds in each replicate (n = 1,280). The diets supplemented with Na2SO4 to attain higher levels of dNa showed highest BW gain and feed intake (FI) during d 1 to 10 (interaction effects) while 2.6 g/kg dNa exhibited improved BW gain and gain:feed (FG) during d 11 to 20. Linear rise in daily water intake (DWI) was associated with diets containing increasing dNa during d 1 to 42 (p≤0.036). During the first 10 d, DWI:FI was found highest in NaHCO3 diets while Na2SO4 diets showed highest DWI:FI during last 10 d of the experiment (p≤0.036). Increasing dNa and changing Na2SO4 with NaHCO3 salt increased pH and resulted in poor growth performance. Dressing weight (p≤0.001) and abdominal fat (p≤0.001; quadratic effect) were reduced, whereas breast (p≤0.001) and thigh (p<0.001) weights were aggravated with increasing dNa (linear effects). Present findings suggested higher levels of dNa from Na2SO4 as the supplemental salt in broiler diets would produce better growth performance, especially in first ten days of life, and improve carcass and body organ characteristics. PMID:25049765
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A computational study of Na behavior on graphene
NASA Astrophysics Data System (ADS)
Malyi, Oleksandr I.; Sopiha, Kostiantyn; Kulish, Vadym V.; Tan, Teck L.; Manzhos, Sergei; Persson, Clas
2015-04-01
We present the first ab initio and molecular dynamics study of Na adsorption and diffusion on ideal graphene that considers Na-Na interaction and dispersion forces. From density functional theory (DFT) calculations using the generalized gradient approximation (GGA), the binding energy (vs. the vacuum reference state) of -0.75 eV is higher than the cohesive energy of Na metal (E
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How far can sodium substitute for potassium in red beet?
NASA Technical Reports Server (NTRS)
Subbarao, G. V.; Wheeler, R. M.; Stutte, G. W.; Levine, L. H.; Sager, J. C. (Principal Investigator)
1999-01-01
Sodium (Na) movement between plants and humans is one of the more critical aspects of bioregenerative systems of life support, which NASA is studying for the establishment of long-term bases on the Lunar or Martian surface. This study was conducted to determine the extent to which Na can replace potassium (K) in red beet (Beta vulgaris L. ssp vulgaris) without adversely affecting metabolic functions such as water relations, photosynthetic rates, and thus growth. Two cultivars, Ruby Queen and Klein Bol, were grown for 42 days at 1200 micromoles mol-1 CO2 in a growth chamber using a re-circulating nutrient film technique with 0%, 75%, 95%, and 98% Na substitution for K in a modified half-strength Hoagland solution. Total biomass of Ruby Queen was greatest at 95% Na substitution and equal at 0% and 98% Na substitution. For Klein Bol, there was a 75% reduction in total biomass at 98% Na substitution. Nearly 95% of the total plant K was replaced with Na at 98% Na substitution in both cultivars. Potassium concentrations in leaves decreased from 120 g kg-1 dwt in 0% Na substitution to 3.5 g kg-1 dwt at 98% Na substitution. Leaf chlorophyll concentration, photosynthetic rate, and osmotic potential were not affected in either cultivar by Na substitution for K. Leaf glycinebetaine levels were doubled at 75% Na substitution in Klein Bol, but decreased at higher levels of Na substitution. For Ruby Queen, glycinebetaine levels in leaf increased with the first increase of Na levels and were maintained at the higher Na levels. These results indicate that in some cultivars of red beet, 95% of the normal tissue K can be replaced by Na without a reduction in growth.
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Strong climate and tectonic control on plagioclase weathering in granitic terrain
Rasmussen, C.; Brantley, S.; Richter, D.D.B.; Blum, A.; Dixon, J.; White, A.F.
2011-01-01
Investigations to understand linkages among climate, erosion and weathering are central to quantifying landscape evolution. We approach these linkages through synthesis of regolith data for granitic terrain compiled with respect to climate, geochemistry, and denudation rates for low sloping upland profiles. Focusing on Na as a proxy for plagioclase weathering, we quantified regolith Na depletion, Na mass loss, and the relative partitioning of denudation to physical and chemical contributions. The depth and magnitude of regolith Na depletion increased continuously with increasing water availability, except for locations with mean annual temperature <5??C that exhibited little Na depletion, and locations with physical erosion rates <20gm-2yr-1 that exhibited deep and complete regolith Na depletion. Surface Na depletion also tended to decrease with increasing physical erosion. Depth-integrated Na mass loss and regolith depth were both three orders of magnitude greater in the fully depleted, low erosion rate sites relative to other locations. These locations exhibited strong erosion-limitation of Na chemical weathering rates based on correlation of Na chemical weathering rate to total Na denudation. Sodium weathering rates in cool locations with positive annual water balance were strongly correlated to total Na denudation and precipitation, and exhibited an average apparent activation energy (Ea) of 69kJmol-1 Na. The remaining water-limited locations exhibited kinetic limitation of Na weathering rates with an Ea of 136kJmol-1 Na, roughly equivalent to the sum of laboratory measures of Ea and dissolution reaction enthalpy for albite. Water availability is suggested as the dominant factor limiting rate kinetics in the water-limited systems. Together, these data demonstrate marked transitions and nonlinearity in how climate and tectonics correlate to plagioclase chemical weathering and Na mass loss. ?? 2010 Elsevier B.V.
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Wu, H; Zhang, Z X; Zhao, H P; Wu, D C; Wu, B L; Cong, R
2004-12-01
Sodium fluoride-loaded gelatin microspheres (NaF-GMS) were prepared using double-phase emulsified condensation polymerization. The average diameter of microspheres was (11.33+/-5.56) microm. The drug content and encapsulation efficiency were 8.80% and 76.73%, respectively. The fluoride releasing profiles of NaF-GMS in physiological saline and artificial saliva (pH 4.5, pH 6.8) showed that NaF-GMS had a sustained-release property and fluoride release rate was increased in pH 4.5 artificial saliva. Experiments conducted in rabbits' oral cavity using NaF-GMS and NaF solution as control revealed NaF-GMS could maintain oral fluoride retention longer than NaF solution. Cariostatic abilities of NaF-GMS including demineralization prohibition in vitro, fluoride deposition in artificial dental plaque and the ability of targeting to cariogenic bacteria were investigated in artificial dental plaque. The results indicated NaF-GMS with lower fluoride concentrations could achieve equivalent cariostatic effect to the concentrated NaF solution, at the same time, could prolong fluoride retention in dental plaque. Microscopic observation showed that NaF-GMS carrying fusion protein of glucan-binding domain could adhere more bacteria than NaF-GMS and this might indicate the possibility of targeting to cariogenic bacteria when NaF-GMS were properly modified.
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Reactions occurring during the sulfation of sodium chloride deposited on alumina substrates
NASA Technical Reports Server (NTRS)
Wu, C. S.; Birks, N.
1986-01-01
The reaction between solid NaCl and air containing 1 pct SO2 has been studied between 500 and 700 C. The reaction product, Na2SO4, forms not only on the surface of the NaCl but also on surrounding areas of the substrate due to the volatility of the NaCl at these temperatures. At the higher temperatures, the vapor pressure of NaCl is so high that the majority of the reaction product is distributed on the substrate. Above 625 C, the reaction product is a liquid solution of NaCl and Na2SO4 that exists only so long as NaCl is supplied from the original crystal source. Eventually, the liquid solidifies by constitutional solidification as the NaCl is converted to Na2SO4. While it exists, the liquid NaCl-Na2SO4 solution is shown to be highly corrosive to Al2O3 and, on a scale of Al2O3 growing on alloy HOS 875, particularly attacks the grain boundaries of the scale at preferred sites where chromium and iron oxides and sulfides rapidly develop. This is proposed as one mechanism by which NaCl deposition contributes to the initiation of low temperature hot corrosion.
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2015-01-01
medics’ aid bags? 8% 92% N/A TCCC Pain Management Are you using TCCC guidelines pain medications?4 42% 12% 46% Fentanyl 69% 31% N/A Ketamine 50% 50% N...A Wound (Combat) Pill Pack 4% 96% N/A What pain medication do your medics carry? Morphine5 92% 8% N/A Fentanyl 35% 65% N/A Ketamine 12% 88% N/A TCCC
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Logistics and the Fight -- Lessons from Napoleon
2011-04-07
Napoleon N/A Sb. GRANT NUMBER N/A Sc. PROGRAM ELEMENT NUMBER N/A 6. AUTHOR( S ) 5d. PROJECT NUMBER LCDR Sean W. Toole, SC, USN N/A Se. TASK NUMBER N...A Sf. WORK UNIT NUMBER N/A 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION USMC Command and Staff College REPORT...NUMBER Marine Corps University N/A 2076 South Street Quantico, VA 22134-5068 9. SPONSORING/MONITORING AGENCY NAME( S ) AND ADDRESS(ES) 10. SPONSOR
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Applicability of Tenets of Operational Art in Low Intensity Conflict Operations (LICO) in India
2013-04-04
Major, Indian Army N/A N/A N/A USMC Command and Staff College Marine Corps University 2076 South Street Quantico, VA 22134-5068 N/A N/A N/A N/A...Approved for public release; distribution is unlimited N/A The identification and application of the tenets of operational art in LICO in the Indian ...and the security forces in particular. A thorough and deep understanding of the tenets of operational art as applicable to LICO in the Indian context
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Yohannan, Jinu P.; Vidyasagar, Kanamaluru, E-mail: kvsagar@iitm.ac.in
Seven new non-centrosymmetric Na{sub 2}M{sub 2}M’S{sub 6} sulfides, namely, Na{sub 2}Sn{sub 2}ZnS{sub 6}(1){sub ,} Na{sub 2}Ga{sub 2}GeS{sub 6}(2), Na{sub 2}Ga{sub 2}SnS{sub 6}(3-α), Na{sub 2}Ga{sub 2}SnS{sub 6}(3-β){sub ,} Na{sub 2}Ge{sub 2}ZnS{sub 6}(4){sub ,} Na{sub 2}Ge{sub 2}CdS{sub 6}(5){sub ,} Na{sub 2}In{sub 2}SiS{sub 6}(6) and Na{sub 2}In{sub 2}GeS{sub 6}(7), were synthesized by high temperature solid state reactions and structurally characterized by single crystal X-ray diffraction. They crystallize in non-centrosymmetric Fdd2 and Cc space groups and their three-dimensional [M{sub 2}M′S{sub 6}]{sup 2-}framework structures consist of MS{sub 4} and M′S{sub 4} tetrahedra corner-connected to one another in either orderly or disordered fashion. Sodium ions residemore » in the tunnels of the anionic framework. Compounds 1, 2 and 3-α have the structure of known Li{sub 2}Ga{sub 2}GeS{sub 6}, whereas compounds 6 and 7 are isostructural with known Li{sub 2}In{sub 2}GeS{sub 6} compound. Isostructural compounds 4 and 5 represent a new structural variant. Compounds 3-α and its new monoclinic structural variant 3-β have disordered structural framework. All of them are wide band gap semiconductors. Na{sub 2}Ga{sub 2}GeS{sub 6}(2), Na{sub 2}Ga{sub 2}SnS{sub 6}(3), Na{sub 2}Ge{sub 2}ZnS{sub 6}(4) and Na{sub 2}In{sub 2}GeS{sub 6}(7) compounds are found to be second-harmonic generation (SHG) active. Compounds 1, 2 and 3-α melt congruently. - Graphical abstract: Na{sub 2}Ga{sub 2}GeS{sub 6}, Na{sub 2}Ga{sub 2}SnS{sub 6}, Na{sub 2}Ge{sub 2}ZnS{sub 6}, Na{sub 2}In{sub 2}GeS{sub 6}, Na{sub 2}Sn{sub 2}ZnS{sub 6}, Na{sub 2}Ge{sub 2}CdS{sub 6} and Na{sub 2}In{sub 2}SiS{sub 6} have non-centrosymmetric structures and the first four compounds are SHG active. Display Omitted - Highlights: • Seven new Na{sub 2}M{sub 2}M′S{sub 6} compounds with non-centrosymmetric structures were synthesized. • They are wide band gap semiconductors. • Na{sub 2}Ga{sub 2}GeS{sub 6}, Na{sub 2}Ga{sub 2}SnS{sub 6}, Na{sub 2}Ge{sub 2}ZnS{sub 6} and Na{sub 2}In{sub 2}GeS{sub 6} are SHG active.« less
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Na+/H+ Exchange Activity in the Plasma Membrane of Arabidopsis1
Qiu, Quan-Sheng; Barkla, Bronwyn J.; Vera-Estrella, Rosario; Zhu, Jian-Kang; Schumaker, Karen S.
2003-01-01
In plants, Na+/H+ exchangers in the plasma membrane are critical for growth in high levels of salt, removing toxic Na+ from the cytoplasm by transport out of the cell. The molecular identity of a plasma membrane Na+/H+ exchanger in Arabidopsis (SOS1) has recently been determined. In this study, immunological analysis provided evidence that SOS1 localizes to the plasma membrane of leaves and roots. To characterize the transport activity of this protein, purified plasma membrane vesicles were isolated from leaves of Arabidopsis. Na+/H+ exchange activity, monitored as the ability of Na to dissipate an established pH gradient, was absent in plants grown without salt. However, exchange activity was induced when plants were grown in 250 mm NaCl and increased with prolonged salt exposure up to 8 d. H+-coupled exchange was specific for Na, because chloride salts of other monovalent cations did not dissipate the pH gradient. Na+/H+ exchange activity was dependent on Na (substrate) concentration, and kinetic analysis indicated that the affinity (apparent Km) of the transporter for Na+ is 22.8 mm. Data from two experimental approaches supports electroneutral exchange (one Na+ exchanged for one proton): (a) no change in membrane potential was measured during the exchange reaction, and (b) Na+/H+ exchange was unaffected by the presence or absence of a membrane potential. Results from this research provide a framework for future studies into the regulation of the plant plasma membrane Na+/H+ exchanger and its relative contribution to the maintenance of cellular Na+ homeostasis during plant growth in salt. PMID:12805632
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Na+/H+ exchange activity in the plasma membrane of Arabidopsis.
Qiu, Quan-Sheng; Barkla, Bronwyn J; Vera-Estrella, Rosario; Zhu, Jian-Kang; Schumaker, Karen S
2003-06-01
In plants, Na+/H+ exchangers in the plasma membrane are critical for growth in high levels of salt, removing toxic Na+ from the cytoplasm by transport out of the cell. The molecular identity of a plasma membrane Na+/H+ exchanger in Arabidopsis (SOS1) has recently been determined. In this study, immunological analysis provided evidence that SOS1 localizes to the plasma membrane of leaves and roots. To characterize the transport activity of this protein, purified plasma membrane vesicles were isolated from leaves of Arabidopsis. Na+/H+ exchange activity, monitored as the ability of Na to dissipate an established pH gradient, was absent in plants grown without salt. However, exchange activity was induced when plants were grown in 250 mm NaCl and increased with prolonged salt exposure up to 8 d. H+-coupled exchange was specific for Na, because chloride salts of other monovalent cations did not dissipate the pH gradient. Na+/H+ exchange activity was dependent on Na (substrate) concentration, and kinetic analysis indicated that the affinity (apparent Km) of the transporter for Na+ is 22.8 mm. Data from two experimental approaches supports electroneutral exchange (one Na+ exchanged for one proton): (a) no change in membrane potential was measured during the exchange reaction, and (b) Na+/H+ exchange was unaffected by the presence or absence of a membrane potential. Results from this research provide a framework for future studies into the regulation of the plant plasma membrane Na+/H+ exchanger and its relative contribution to the maintenance of cellular Na+ homeostasis during plant growth in salt.
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Nutritional Relationships in Schistosomiasis.
1978-07-01
to presence of ou~bain, phlorizin, phloretin . 1lexose mediated accumulation is Na coupled. Accession For NTIS GREA&I DDC TAB Unannounced...mediat,!d system is apparently Na + dependent and sensitive to presence of ouabain, phlorizin, phloretin . Hexose mediated accumulation is Na+ coupled. i...decreased Na+, ouabain, phiorizin phloretin and other sugars. Studies with Na22 suggest that the accumulation of 2-deoxyglucose and Na+ were coupled
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Acidosis Differentially Modulates Inactivation in NaV1.2, NaV1.4, and NaV1.5 Channels
Vilin, Yury Y.; Peters, Colin H.; Ruben, Peter C.
2012-01-01
NaV channels play a crucial role in neuronal and muscle excitability. Using whole-cell recordings we studied effects of low extracellular pH on the biophysical properties of NaV1.2, NaV1.4, and NaV1.5, expressed in cultured mammalian cells. Low pH produced different effects on different channel subtypes. Whereas NaV1.4 exhibited very low sensitivity to acidosis, primarily limited to partial block of macroscopic currents, the effects of low pH on gating in NaV1.2 and NaV1.5 were profound. In NaV1.2 low pH reduced apparent valence of steady-state fast inactivation, shifted the τ(V) to depolarizing potentials and decreased channels availability during onset to slow and use-dependent inactivation (UDI). In contrast, low pH delayed open-state inactivation in NaV1.5, right-shifted the voltage-dependence of window current, and increased channel availability during onset to slow and UDI. These results suggest that protons affect channel availability in an isoform-specific manner. A computer model incorporating these results demonstrates their effects on membrane excitability. PMID:22701426
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NASA Astrophysics Data System (ADS)
Thangaraju, Dheivasigamani; Santhana, Vedi; Matsuda, Satoshi; Hayakawa, Yasuhiro
2018-05-01
Hexagonal NaYF4:Yb:Er:Tm@NaGdF4 core-shell nanocrystals were synthesized using a seed mediated hot injection method, and monodispersed Fe3O4 (4 nm) nanoparticles were prepared from iron(II) actylacetonate by a precursor thermal decomposition method. Structural and morphology verified NaYF4:Yb:Er:Tm@NaGdF4 and Fe3O4 nanoparticles were utilized for the preparation of NaYF4:Yb:Er:Tm@NaGdF4/Fe3O4@SiO2 nanocomposite using a micro-emulsion method. Existence of Fe3O4 in NaYF4:Yb:Er:Tm@NaGdF4 in SiO2 nano-spheres were confirmed with transmission electron microscopy. Luminescence measurement revealed that NaYF4:Yb:Er:Tm@NaGdF4 exhibited strong emissions at green and red regions, in addition to a weak blue emission also observed under 980 nm excitation. Up-conversion emission of the nanoparticle-embedded silica nanocomposite showed that the up-conversion emission was not affected by Fe3O4 nanoparticles.
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Structure-based assessment of disease-related mutations in human voltage-gated sodium channels.
Huang, Weiyun; Liu, Minhao; Yan, S Frank; Yan, Nieng
2017-06-01
Voltage-gated sodium (Na v ) channels are essential for the rapid upstroke of action potentials and the propagation of electrical signals in nerves and muscles. Defects of Na v channels are associated with a variety of channelopathies. More than 1000 disease-related mutations have been identified in Na v channels, with Na v 1.1 and Na v 1.5 each harboring more than 400 mutations. Na v channels represent major targets for a wide array of neurotoxins and drugs. Atomic structures of Na v channels are required to understand their function and disease mechanisms. The recently determined atomic structure of the rabbit voltage-gated calcium (Ca v ) channel Ca v 1.1 provides a template for homology-based structural modeling of the evolutionarily related Na v channels. In this Resource article, we summarized all the reported disease-related mutations in human Na v channels, generated a homologous model of human Na v 1.7, and structurally mapped disease-associated mutations. Before the determination of structures of human Na v channels, the analysis presented here serves as the base framework for mechanistic investigation of Na v channelopathies and for potential structure-based drug discovery.