Sample records for density mercer kernels

  1. Putting Priors in Mixture Density Mercer Kernels

    NASA Technical Reports Server (NTRS)

    Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

    2004-01-01

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

  2. Density Estimation with Mercer Kernels

    NASA Technical Reports Server (NTRS)

    Macready, William G.

    2003-01-01

    We present a new method for density estimation based on Mercer kernels. The density estimate can be understood as the density induced on a data manifold by a mixture of Gaussians fit in a feature space. As is usual, the feature space and data manifold are defined with any suitable positive-definite kernel function. We modify the standard EM algorithm for mixtures of Gaussians to infer the parameters of the density. One benefit of the approach is it's conceptual simplicity, and uniform applicability over many different types of data. Preliminary results are presented for a number of simple problems.

  3. Knowledge Driven Image Mining with Mixture Density Mercer Kernels

    NASA Technical Reports Server (NTRS)

    Srivastava, Ashok N.; Oza, Nikunj

    2004-01-01

    This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels; which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper, we present the theory of Mercer Kernels, describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

  4. An Ensemble Approach to Building Mercer Kernels with Prior Information

    NASA Technical Reports Server (NTRS)

    Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

    2005-01-01

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

  5. Knowledge Driven Image Mining with Mixture Density Mercer Kernals

    NASA Technical Reports Server (NTRS)

    Srivastava, Ashok N.; Oza, Nikunj

    2004-01-01

    This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper we present the theory of Mercer Kernels; describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

  6. Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods.

    PubMed

    Vizcaíno, Iván P; Carrera, Enrique V; Muñoz-Romero, Sergio; Cumbal, Luis H; Rojo-Álvarez, José Luis

    2017-10-16

    Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer's kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer's kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

  7. Needleboards--An exploratory study

    Treesearch

    E.T. Howard

    1974-01-01

    Medium-density hot-pressed boards were prepared from slash pine needles that had been: 1) flattened, 2) benzenesoaked, 3) flattened and then benzene-soaked, 4) mercerized, or 5) given no treatment. None of the boards had satisfactory properties for conventional uses. Mercerization improved bending strength and internal bond of the boards, but stiffness and dimensional...

  8. Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.

    PubMed

    Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K

    2016-03-01

    Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.

  9. Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing Spectra

    NASA Technical Reports Server (NTRS)

    Srivastava, Ashok N.; Oza, Nikunj; Stroeve, Julienne

    2004-01-01

    Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. These instruments are sometimes built in a phased approach, with some measurement capabilities being added in later phases. In other cases, there may not be a planned increase in measurement capability, but technology may mature to the point that it offers new measurement capabilities that were not available before. In still other cases, detailed spectral measurements may be too costly to perform on a large sample. Thus, lower resolution instruments with lower associated cost may be used to take the majority of measurements. Higher resolution instruments, with a higher associated cost may be used to take only a small fraction of the measurements in a given area. Many applied science questions that are relevant to the remote sensing community need to be addressed by analyzing enormous amounts of data that were generated from instruments with disparate measurement capability. This paper addresses this problem by demonstrating methods to produce high accuracy estimates of spectra with an associated measure of uncertainty from data that is perhaps nonlinearly correlated with the spectra. In particular, we demonstrate multi-layer perceptrons (MLPs), Support Vector Machines (SVMs) with Radial Basis Function (RBF) kernels, and SVMs with Mixture Density Mercer Kernels (MDMK). We call this type of an estimator a Virtual Sensor because it predicts, with a measure of uncertainty, unmeasured spectral phenomena.

  10. Kernel-based least squares policy iteration for reinforcement learning.

    PubMed

    Xu, Xin; Hu, Dewen; Lu, Xicheng

    2007-07-01

    In this paper, we present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. By using KLSPI, near-optimal control policies can be obtained without much a priori knowledge on dynamic models of control plants. In KLSPI, Mercer kernels are used in the policy evaluation of a policy iteration process, where a new kernel-based least squares temporal-difference algorithm called KLSTD-Q is proposed for efficient policy evaluation. To keep the sparsity and improve the generalization ability of KLSTD-Q solutions, a kernel sparsification procedure based on approximate linear dependency (ALD) is performed. Compared to the previous works on approximate RL methods, KLSPI makes two progresses to eliminate the main difficulties of existing results. One is the better convergence and (near) optimality guarantee by using the KLSTD-Q algorithm for policy evaluation with high precision. The other is the automatic feature selection using the ALD-based kernel sparsification. Therefore, the KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs). Experimental results on a typical RL task for a stochastic chain problem demonstrate that KLSPI can consistently achieve better learning efficiency and policy quality than the previous least squares policy iteration (LSPI) algorithm. Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller performance using little a priori information of uncertain dynamic systems. It is also demonstrated that KLSPI can be applied to online learning control by incorporating an initial controller to ensure online performance.

  11. Chemical and thermal studies on esterification of EDTA with raw cellulose and mercerized cellulose EFB

    NASA Astrophysics Data System (ADS)

    Azamkamal, Fatihah; Zakaria, Sarani; Gan, Sinyee; Kaco, Hatika

    2018-04-01

    Oil palm empty fruit bunch fibre (EFB) was bleached using four stages bleaching sequences (DEED) where D was a bleaching process composed of 1.7 wt% NaClO2 and buffer solution while E was composed of NaOH solution. Raw cellulose and mercerized cellulose which treated with 3.5 N sodium hydroxide were used as a raw material for esterification with ethylenediaminetetraacetic acid (EDTA) and enhancement with acetic acid. The samples of raw cellulose and mercerized cellulose were observed using optical microscope. The thermal properties of raw cellulose and mercerized cellulose esterified with EDTA were studied. The effect of mercerized cellulose on esterification process of EDTA was investigated. The studies suggested that the mercerization process affect the thermal stability of the cellulose. The transmittance of FTIR band showed that raw cellulose gave better esterification product compared to mercerized cellulose. Hence, the mercerization process of cellulose does not improve the esterification of cellulose with EDTA.

  12. A Case Study of Strategies Employed by Mercer University Leadership during Its Transformation from a Liberal Arts Institution into a Comprehensive University

    ERIC Educational Resources Information Center

    Nelson, Connie L.

    2011-01-01

    The study examined the transformation of Mercer University from a small liberal arts school into a comprehensive institution. The purpose of the study was to explore the historical transformation of Mercer University and the role of leadership throughout the process. The qualitative study was a historical case study of Mercer University based on…

  13. Mercer County (N.J.) Coordination/Consolidation Demonstration Program

    DOT National Transportation Integrated Search

    1982-03-01

    From November 1977 through June 1981, Mercer County in New Jersey, was the site of an Urban Mass Transportation Administration Service and Methods Demonstration, which coordinated human service agency transportation programs. The Mercer County Coordi...

  14. Mercerization of Cotton for Strength with Special Reference to Aircraft Cloth

    NASA Technical Reports Server (NTRS)

    Wilkie, J B

    1933-01-01

    The object of the present investigation was to determine the conditions for mercerizing cotton yarn to obtain the maximum strength for a given weight. Apparatus for controlling the variables was built and yarns were mercerized with it under systematically varied conditions of tension, time, temperature, and concentration of caustic soda. The strongest conclusion to be drawn from this work is that the strongest mercerized yarn of a given count from a given quality of cotton is obtained under the following conditions: 1. use of low-twist yarn obtained with twist multipliers from 2.2 to 3; 2. thorough pretreatment of the yarn to remove all extraneous materials; 3. mercerization at a temperature of 0 C or lower; 4. use of sufficient tension during mercerization to prevent the yarn from contracting more than 3 percent. 5. Use of caustic solution having a concentration of 10 percent or higher; 6. the time of mercerization to be 5 minutes. The resulting yarn should be 40 to 100 percent stronger than the original yarn of the same weight.

  15. A Cultural Resources Inventory of Eastern Portions of Lake Sakakawea, North Dakota (Mercer and McLean Counties).

    DTIC Science & Technology

    1982-09-15

    34esources Inventory of Eastern Portions of Lake Sakakawee, North Dakota (Mercer and McLean August - September 1982 Counties ) 6. PERFORMING ORG. REPORT...of Lake Sakakawea (Mercer and McLean Counties ), North Dakota, Identif ied 56 sites. The site types include: stone circles (36), stone cairn (1), linear...9 A CULTURAL RESOURCES INVENTORY OF EASTERN PORTIONS OF LAUE SAKAKAWRA, NORTH DAKOTA (MERCER AND XcLEAN COUNTIES

  16. 40 CFR 81.335 - North Dakota.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... McKenzie County McLean County Mercer County Morton County Mountrail County Nelson County Oliver County... County McIntosh County McKenzie County McLean County Mercer County Morton County Mountrail County Nelson... County McLean County Mercer County Morton County Mountrail County Nelson County Oliver County Pembina...

  17. 76 FR 61748 - Mercer (US), Inc., a Subsidiary of Mercer LLC, a Subsidiary of Mercer, Inc., a Subsidiary of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-05

    ... that subject worker group separations were due to a shift to India and stated that other similar firms... for Reconsideration By application received July 22, 2011, a worker requested administrative reconsideration of the negative determination regarding workers' eligibility to apply for Trade Adjustment...

  18. 78 FR 338 - CSX Transportation, Inc.; Abandonment Exemption-in Ewing Township, Mercer County, NJ

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-03

    ... DEPARTMENT OF TRANSPORTATION Surface Transportation Board [Docket No. AB 55 (Sub-No. 724X)] CSX Transportation, Inc.; Abandonment Exemption--in Ewing Township, Mercer County, NJ CSX Transportation, Inc. (CSXT... Drive, and the end of the track at milepost QAT 34.49, in Ewing Township, Mercer County, N.J. (the Line...

  19. Density separation as a strategy to reduce the enzyme load of preharvest sprouted wheat and enhance its bread making quality.

    PubMed

    Olaerts, Heleen; De Bondt, Yamina; Courtin, Christophe M

    2018-02-15

    As preharvest sprouting of wheat impairs its use in food applications, postharvest solutions for this problem are required. Due to the high kernel to kernel variability in enzyme activity in a batch of sprouted wheat, the potential of eliminating severely sprouted kernels based on density differences in NaCl solutions was evaluated. Compared to higher density kernels, lower density kernels displayed higher α-amylase, endoxylanase, and peptidase activities as well as signs of (incipient) protein, β-glucan and arabinoxylan breakdown. By discarding lower density kernels of mildly and severely sprouted wheat batches (11% and 16%, respectively), density separation increased flour FN of the batch from 280 to 345s and from 135 to 170s and increased RVA viscosity. This in turn improved dough handling, bread crumb texture and crust color. These data indicate that density separation is a powerful technique to increase the quality of a batch of sprouted wheat. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Effect of ultra-low doses, ASIR and MBIR on density and noise levels of MDCT images of dental implant sites.

    PubMed

    Widmann, Gerlig; Al-Shawaf, Reema; Schullian, Peter; Al-Sadhan, Ra'ed; Hörmann, Romed; Al-Ekrish, Asma'a A

    2017-05-01

    Differences in noise and density values in MDCT images obtained using ultra-low doses with FBP, ASIR, and MBIR may possibly affect implant site density analysis. The aim of this study was to compare density and noise measurements recorded from dental implant sites using ultra-low doses combined with FBP, ASIR, and MBIR. Cadavers were scanned using a standard protocol and four low-dose protocols. Scans were reconstructed using FBP, ASIR-50, ASIR-100, and MBIR, and either a bone or standard reconstruction kernel. Density (mean Hounsfield units [HUs]) of alveolar bone and noise levels (mean standard deviation of HUs) was recorded from all datasets and measurements were compared by paired t tests and two-way ANOVA with repeated measures. Significant differences in density and noise were found between the reference dose/FBP protocol and almost all test combinations. Maximum mean differences in HU were 178.35 (bone kernel) and 273.74 (standard kernel), and in noise, were 243.73 (bone kernel) and 153.88 (standard kernel). Decreasing radiation dose increased density and noise regardless of reconstruction technique and kernel. The effect of reconstruction technique on density and noise depends on the reconstruction kernel used. • Ultra-low-dose MDCT protocols allowed more than 90 % reductions in dose. • Decreasing the dose generally increased density and noise. • Effect of IRT on density and noise varies with reconstruction kernel. • Accuracy of low-dose protocols for interpretation of bony anatomy not known. • Effect of low doses on accuracy of computer-aided design models unknown.

  1. A comparative study of linear and nonlinear anomaly detectors for hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Goldberg, Hirsh; Nasrabadi, Nasser M.

    2007-04-01

    In this paper we implement various linear and nonlinear subspace-based anomaly detectors for hyperspectral imagery. First, a dual window technique is used to separate the local area around each pixel into two regions - an inner-window region (IWR) and an outer-window region (OWR). Pixel spectra from each region are projected onto a subspace which is defined by projection bases that can be generated in several ways. Here we use three common pattern classification techniques (Principal Component Analysis (PCA), Fisher Linear Discriminant (FLD) Analysis, and the Eigenspace Separation Transform (EST)) to generate projection vectors. In addition to these three algorithms, the well-known Reed-Xiaoli (RX) anomaly detector is also implemented. Each of the four linear methods is then implicitly defined in a high- (possibly infinite-) dimensional feature space by using a nonlinear mapping associated with a kernel function. Using a common machine-learning technique known as the kernel trick all dot products in the feature space are replaced with a Mercer kernel function defined in terms of the original input data space. To determine how anomalous a given pixel is, we then project the current test pixel spectra and the spectral mean vector of the OWR onto the linear and nonlinear projection vectors in order to exploit the statistical differences between the IWR and OWR pixels. Anomalies are detected if the separation of the projection of the current test pixel spectra and the OWR mean spectra are greater than a certain threshold. Comparisons are made using receiver operating characteristics (ROC) curves.

  2. Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation.

    PubMed

    Chen, Rongda; Wang, Ze

    2013-01-01

    Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.

  3. Curve Fitting of the Corporate Recovery Rates: The Comparison of Beta Distribution Estimation and Kernel Density Estimation

    PubMed Central

    Chen, Rongda; Wang, Ze

    2013-01-01

    Recovery rate is essential to the estimation of the portfolio’s loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody’s. However, it has a fatal defect that it can’t fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody’s new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management. PMID:23874558

  4. Strong consistency of nonparametric Bayes density estimation on compact metric spaces with applications to specific manifolds

    PubMed Central

    Bhattacharya, Abhishek; Dunson, David B.

    2012-01-01

    This article considers a broad class of kernel mixture density models on compact metric spaces and manifolds. Following a Bayesian approach with a nonparametric prior on the location mixing distribution, sufficient conditions are obtained on the kernel, prior and the underlying space for strong posterior consistency at any continuous density. The prior is also allowed to depend on the sample size n and sufficient conditions are obtained for weak and strong consistency. These conditions are verified on compact Euclidean spaces using multivariate Gaussian kernels, on the hypersphere using a von Mises-Fisher kernel and on the planar shape space using complex Watson kernels. PMID:22984295

  5. Trenton Free-Fare Demonstration Project

    DOT National Transportation Integrated Search

    1978-12-01

    The "Trenton Free-Fare Demonstration" is the first large-scale test of free transit in the U.S. The New Jersey Department of Transportation, in cooperation with UMTA, Mercer County, and Mercer County Improvement Authority, is administering an Off-Pea...

  6. 96. CENTRAL COURT. MERCER MUSEUM, FROM ENTRY LEVEL SAME VIEW ...

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

    96. CENTRAL COURT. MERCER MUSEUM, FROM ENTRY LEVEL SAME VIEW AS PA-107-67. - Moravian Pottery & Tile Works, Southwest side of State Route 313 (Swamp Road), Northwest of East Court Street, Doylestown, Bucks County, PA

  7. A feminist critique of foundational nursing research and theory on transition to motherhood.

    PubMed

    Parratt, Jenny A; Fahy, Kathleen M

    2011-08-01

    is using 'transition to motherhood theory' the best way to guide midwives in providing woman-centred care? contemporary research about changes to women's embodied sense of self during childbearing is influenced by foundational research and theory about the transition to motherhood. Rubin and Mercer are two key nursing authors whose work on transition to motherhood theory still shapes the ways in which a woman's experience of change during childbearing is understood in midwifery. using a feminist post-structural framework, Rubin and Mercer's theory and research is described, critiqued and discussed. Rubin and Mercer used pre-existing theories and concepts that had the effect of finding similarities and discarding differences between women. Rubin and Mercer's theory and research is an expression of humanistic philosophy. This philosophy creates frameworks that have an assumed, disempowered role for childbearing women. Their research used a logico-empirical, quantitative approach. Qualitative interpretive or constructivist approaches offer more appropriate ways to study the highly individualised, embodied, lived experience of a woman's changing self during childbearing. Rubin and Mercer's theory is baby-centred. Transition to motherhood theory privileges the position of experts in directing how a woman should become a mother. This has the effect of making midwives agents for the social control of women. Rubin and Mercer's transition to motherhood theory is a well-intentioned product of its time. The theory is inconsistent with contemporary midwifery philosophy which promotes a woman-centred partnership between the midwife and the woman. The usefulness of this outdated nursing theory in midwifery teaching, research or practice is debatable. Copyright © 2010 Elsevier Ltd. All rights reserved.

  8. 76 FR 18622 - Notice of Intent To Rule on Request To Release Airport Property at the Helena Regional Airport...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-04

    .... Ronald Mercer, Airport Director, Helena Regional Airport Authority (HRAA), at the following address: Mr. Ronald Mercer, Airport Director, Helena Regional Airport Authority, 2850 Skyway Drive, Helena, Montana...

  9. 3. GENERAL VIEW OF CORRIDOR AROUND TRENTON STATION. TRENTON, MERCER ...

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

    3. GENERAL VIEW OF CORRIDOR AROUND TRENTON STATION. TRENTON, MERCER CO., NJ. Sec. 1401, MP 56.70. - Northeast Railroad Corridor, Amtrak Route between Pennsylvania/New Jersey & New Jersey/New York State Lines, Newark, Essex County, NJ

  10. 97. CENTRAL COURT, MERCER MUSEUM. FROM THE THIRD FLOOR. SAME ...

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

    97. CENTRAL COURT, MERCER MUSEUM. FROM THE THIRD FLOOR. SAME VIEW AS PA-107-68. - Moravian Pottery & Tile Works, Southwest side of State Route 313 (Swamp Road), Northwest of East Court Street, Doylestown, Bucks County, PA

  11. Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data

    PubMed Central

    Zeng, Beiyan; Chen, Yiping P.; Smith, Oscar H.

    2003-01-01

    Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r2 test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed. PMID:18629292

  12. Investigation of various energy deposition kernel refinements for the convolution/superposition method

    PubMed Central

    Huang, Jessie Y.; Eklund, David; Childress, Nathan L.; Howell, Rebecca M.; Mirkovic, Dragan; Followill, David S.; Kry, Stephen F.

    2013-01-01

    Purpose: Several simplifications used in clinical implementations of the convolution/superposition (C/S) method, specifically, density scaling of water kernels for heterogeneous media and use of a single polyenergetic kernel, lead to dose calculation inaccuracies. Although these weaknesses of the C/S method are known, it is not well known which of these simplifications has the largest effect on dose calculation accuracy in clinical situations. The purpose of this study was to generate and characterize high-resolution, polyenergetic, and material-specific energy deposition kernels (EDKs), as well as to investigate the dosimetric impact of implementing spatially variant polyenergetic and material-specific kernels in a collapsed cone C/S algorithm. Methods: High-resolution, monoenergetic water EDKs and various material-specific EDKs were simulated using the EGSnrc Monte Carlo code. Polyenergetic kernels, reflecting the primary spectrum of a clinical 6 MV photon beam at different locations in a water phantom, were calculated for different depths, field sizes, and off-axis distances. To investigate the dosimetric impact of implementing spatially variant polyenergetic kernels, depth dose curves in water were calculated using two different implementations of the collapsed cone C/S method. The first method uses a single polyenergetic kernel, while the second method fully takes into account spectral changes in the convolution calculation. To investigate the dosimetric impact of implementing material-specific kernels, depth dose curves were calculated for a simplified titanium implant geometry using both a traditional C/S implementation that performs density scaling of water kernels and a novel implementation using material-specific kernels. Results: For our high-resolution kernels, we found good agreement with the Mackie et al. kernels, with some differences near the interaction site for low photon energies (<500 keV). For our spatially variant polyenergetic kernels, we found that depth was the most dominant factor affecting the pattern of energy deposition; however, the effects of field size and off-axis distance were not negligible. For the material-specific kernels, we found that as the density of the material increased, more energy was deposited laterally by charged particles, as opposed to in the forward direction. Thus, density scaling of water kernels becomes a worse approximation as the density and the effective atomic number of the material differ more from water. Implementation of spatially variant, polyenergetic kernels increased the percent depth dose value at 25 cm depth by 2.1%–5.8% depending on the field size, while implementation of titanium kernels gave 4.9% higher dose upstream of the metal cavity (i.e., higher backscatter dose) and 8.2% lower dose downstream of the cavity. Conclusions: Of the various kernel refinements investigated, inclusion of depth-dependent and metal-specific kernels into the C/S method has the greatest potential to improve dose calculation accuracy. Implementation of spatially variant polyenergetic kernels resulted in a harder depth dose curve and thus has the potential to affect beam modeling parameters obtained in the commissioning process. For metal implants, the C/S algorithms generally underestimate the dose upstream and overestimate the dose downstream of the implant. Implementation of a metal-specific kernel mitigated both of these errors. PMID:24320507

  13. Evaluation of the July 1980 Mercer Metro (Trenton, NJ) Fare Increase

    DOT National Transportation Integrated Search

    1985-12-01

    This report evaluates certain effects of a July 1980 fare increase on Mercer Metro ridership. The evaluation addresses aggregate ridership change as well as effects on individual transit user groups. The scope of this analysis was governed by a set o...

  14. The Influence of Reconstruction Kernel on Bone Mineral and Strength Estimates Using Quantitative Computed Tomography and Finite Element Analysis.

    PubMed

    Michalski, Andrew S; Edwards, W Brent; Boyd, Steven K

    2017-10-17

    Quantitative computed tomography has been posed as an alternative imaging modality to investigate osteoporosis. We examined the influence of computed tomography convolution back-projection reconstruction kernels on the analysis of bone quantity and estimated mechanical properties in the proximal femur. Eighteen computed tomography scans of the proximal femur were reconstructed using both a standard smoothing reconstruction kernel and a bone-sharpening reconstruction kernel. Following phantom-based density calibration, we calculated typical bone quantity outcomes of integral volumetric bone mineral density, bone volume, and bone mineral content. Additionally, we performed finite element analysis in a standard sideways fall on the hip loading configuration. Significant differences for all outcome measures, except integral bone volume, were observed between the 2 reconstruction kernels. Volumetric bone mineral density measured using images reconstructed by the standard kernel was significantly lower (6.7%, p < 0.001) when compared with images reconstructed using the bone-sharpening kernel. Furthermore, the whole-bone stiffness and the failure load measured in images reconstructed by the standard kernel were significantly lower (16.5%, p < 0.001, and 18.2%, p < 0.001, respectively) when compared with the image reconstructed by the bone-sharpening kernel. These data suggest that for future quantitative computed tomography studies, a standardized reconstruction kernel will maximize reproducibility, independent of the use of a quantitative calibration phantom. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

  15. Electrochemical mercerization, souring, and bleaching of textiles

    DOEpatents

    Cooper, J.F.

    1995-10-10

    Economical, pollution-free treatment of textiles occurs in a low voltage electrochemical cell that mercerizes (or scours), sours, and optionally bleaches without effluents and without the purchase of bulk caustic, neutralizing acids, or bleaches. The cell produces base in the cathodic chamber for mercerization and an equivalent amount of acid in the anodic chamber for neutralizing the fabric. Gas diffusion electrodes are used for one or both electrodes and may simultaneously generate hydrogen peroxide for bleaching. The preferred configuration is a stack of bipolar electrodes, in which one or both of the anode and cathode are gas diffusion electrodes, and where no hydrogen gas is evolved at the cathode. 5 figs.

  16. Electrochemical mercerization, souring, and bleaching of textiles

    DOEpatents

    Cooper, John F.

    1995-01-01

    Economical, pollution-free treatment of textiles occurs in a low voltage electrochemical cell that mercerizes (or scours), sours, and optionally bleaches without effluents and without the purchase of bulk caustic, neutralizing acids, or bleaches. The cell produces base in the cathodic chamber for mercerization and an equivalent amount of acid in the anodic chamber for neutralizing the fabric. Gas diffusion electrodes are used for one or both electrodes and may simultaneously generate hydrogen peroxide for bleaching. The preferred configuration is a stack of bipolar electrodes, in which one or both of the anode and cathode are gas diffusion electrodes, and where no hydrogen gas is evolved at the cathode.

  17. Mercer University's Graduate Certificate in Interactive Multimedia.

    ERIC Educational Resources Information Center

    Leonard, David C.

    Although most programs in technical communication reside in English departments where the focus is on writing, rhetoric, and exposition, the graduate certificate program in interactive multimedia at Mercer University is being developed for the Technical Communication Department within the School of Engineering. As a result, many of the…

  18. Comparative properties of cellulose nano-crystals from native and mercerized cotton fibers

    USDA-ARS?s Scientific Manuscript database

    Stable aqueous suspensions of cellulose nano-crystals (CNCs) were fabricated from both native and mercerized cotton fibers by sulfuric acid hydrolysis, followed by high-pressure homogenization. Fourier Transform Infrared Spectrometry and Wide-angle X-Ray Diffraction data showed that the fibers had b...

  19. Characterization of a maximum-likelihood nonparametric density estimator of kernel type

    NASA Technical Reports Server (NTRS)

    Geman, S.; Mcclure, D. E.

    1982-01-01

    Kernel type density estimators calculated by the method of sieves. Proofs are presented for the characterization theorem: Let x(1), x(2),...x(n) be a random sample from a population with density f(0). Let sigma 0 and consider estimators f of f(0) defined by (1).

  20. Automated skin lesion segmentation with kernel density estimation

    NASA Astrophysics Data System (ADS)

    Pardo, A.; Real, E.; Fernandez-Barreras, G.; Madruga, F. J.; López-Higuera, J. M.; Conde, O. M.

    2017-07-01

    Skin lesion segmentation is a complex step for dermoscopy pathological diagnosis. Kernel density estimation is proposed as a segmentation technique based on the statistic distribution of color intensities in the lesion and non-lesion regions.

  1. Innovative layer-by-layer processing for flame retardant behavior of cotton fabric

    USDA-ARS?s Scientific Manuscript database

    Flame retardant behavior has been prepared by the layer-by layer assemblies of kaolin/casein with inorganic chemicals on cotton fabrics. Three different kinds of cotton fabrics (print cloth, mercerized print cloth, and mercerized twill fabric) were prepared with solutions of mixture of BPEI, urea, ...

  2. Anti-flammable properties of cotton fabrics using eco friendly inorganic materials by layering self-assisted processing

    USDA-ARS?s Scientific Manuscript database

    A flame retardant surface has been prepared by the layer-by layer assemblies of branched polyethylenimine (BPEI), kaolin, urea, diammonium phosphate (dibasic) on cotton fabrics. Four different kinds of cotton fabrics (print cloth, mercerized print cloth, mercerized twill, and fleece) were prepared ...

  3. Nonparametric entropy estimation using kernel densities.

    PubMed

    Lake, Douglas E

    2009-01-01

    The entropy of experimental data from the biological and medical sciences provides additional information over summary statistics. Calculating entropy involves estimates of probability density functions, which can be effectively accomplished using kernel density methods. Kernel density estimation has been widely studied and a univariate implementation is readily available in MATLAB. The traditional definition of Shannon entropy is part of a larger family of statistics, called Renyi entropy, which are useful in applications that require a measure of the Gaussianity of data. Of particular note is the quadratic entropy which is related to the Friedman-Tukey (FT) index, a widely used measure in the statistical community. One application where quadratic entropy is very useful is the detection of abnormal cardiac rhythms, such as atrial fibrillation (AF). Asymptotic and exact small-sample results for optimal bandwidth and kernel selection to estimate the FT index are presented and lead to improved methods for entropy estimation.

  4. Discontinuous functional for linear-response time-dependent density-functional theory: The exact-exchange kernel and approximate forms

    NASA Astrophysics Data System (ADS)

    Hellgren, Maria; Gross, E. K. U.

    2013-11-01

    We present a detailed study of the exact-exchange (EXX) kernel of time-dependent density-functional theory with an emphasis on its discontinuity at integer particle numbers. It was recently found that this exact property leads to sharp peaks and step features in the kernel that diverge in the dissociation limit of diatomic systems [Hellgren and Gross, Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.85.022514 85, 022514 (2012)]. To further analyze the discontinuity of the kernel, we here make use of two different approximations to the EXX kernel: the Petersilka Gossmann Gross (PGG) approximation and a common energy denominator approximation (CEDA). It is demonstrated that whereas the PGG approximation neglects the discontinuity, the CEDA includes it explicitly. By studying model molecular systems it is shown that the so-called field-counteracting effect in the density-functional description of molecular chains can be viewed in terms of the discontinuity of the static kernel. The role of the frequency dependence is also investigated, highlighting its importance for long-range charge-transfer excitations as well as inner-shell excitations.

  5. Popular Education in Nineteenth-Century Virginia: The Efforts of Charles Fenton Mercer.

    ERIC Educational Resources Information Center

    Hunt, Thomas C.

    1981-01-01

    Although Charles Fenton Mercer's attempts to move 19th-century Virginia to a collectively supported comprehensive system of public education failed, he authored one of the first definitive plans in this country for an organized system of education under control of the state. His contributions are discussed. (RM)

  6. 33 CFR 100.1301 - Seattle seafair unlimited hydroplane race.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... Washington bounded by the Interstate 90 (Mercer Island /Lacey V. Murrow) Bridge, the western shore of Lake Washington, and the east/west line drawn tangent to Bailey Peninsula and along the shoreline of Mercer Island... hydroplane race course and then to the northerly tip of Ohlers Island in Andrews Bay. The western zone is...

  7. 76 FR 37000 - Seattle Seafair Unlimited Hydroplane Race

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-24

    ... area; the waters of Lake Washington bounded by the Interstate 90 (Mercer Island/Lacey V. Murrow) Bridge... along the shoreline of Mercer Island. The regulated area has been divided into two zones. The zones are... race course and then to the northerly tip of Ohlers Island in Andrews Bay. The western zone is...

  8. 33 CFR 100.1301 - Seattle seafair unlimited hydroplane race.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Washington bounded by the Interstate 90 (Mercer Island /Lacey V. Murrow) Bridge, the western shore of Lake Washington, and the east/west line drawn tangent to Bailey Peninsula and along the shoreline of Mercer Island... hydroplane race course and then to the northerly tip of Ohlers Island in Andrews Bay. The western zone is...

  9. 33 CFR 100.1301 - Seattle seafair unlimited hydroplane race.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... Washington bounded by the Interstate 90 (Mercer Island /Lacey V. Murrow) Bridge, the western shore of Lake Washington, and the east/west line drawn tangent to Bailey Peninsula and along the shoreline of Mercer Island... hydroplane race course and then to the northerly tip of Ohlers Island in Andrews Bay. The western zone is...

  10. 33 CFR 100.1301 - Seattle seafair unlimited hydroplane race.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Washington bounded by the Interstate 90 (Mercer Island /Lacey V. Murrow) Bridge, the western shore of Lake Washington, and the east/west line drawn tangent to Bailey Peninsula and along the shoreline of Mercer Island... hydroplane race course and then to the northerly tip of Ohlers Island in Andrews Bay. The western zone is...

  11. 33 CFR 100.1301 - Seattle seafair unlimited hydroplane race.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... Washington bounded by the Interstate 90 (Mercer Island /Lacey V. Murrow) Bridge, the western shore of Lake Washington, and the east/west line drawn tangent to Bailey Peninsula and along the shoreline of Mercer Island... hydroplane race course and then to the northerly tip of Ohlers Island in Andrews Bay. The western zone is...

  12. 77 FR 39632 - Seattle Seafair Unlimited Hydroplane Race

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-05

    ... of Lake Washington bounded by the Interstate 90 (Mercer Island/Lacey V. Murrow) Bridge, the western... shoreline of Mercer Island. The regulated area has been divided into two zones. The zones are separated by a... course and then to the northerly tip of Ohlers Island in Andrews Bay. The western zone is designated Zone...

  13. Nutrition quality of extraction mannan residue from palm kernel cake on brolier chicken

    NASA Astrophysics Data System (ADS)

    Tafsin, M.; Hanafi, N. D.; Kejora, E.; Yusraini, E.

    2018-02-01

    This study aims to find out the nutrient residue of palm kernel cake from mannan extraction on broiler chicken by evaluating physical quality (specific gravity, bulk density and compacted bulk density), chemical quality (proximate analysis and Van Soest Test) and biological test (metabolizable energy). Treatment composed of T0 : palm kernel cake extracted aquadest (control), T1 : palm kernel cake extracted acetic acid (CH3COOH) 1%, T2 : palm kernel cake extracted aquadest + mannanase enzyme 100 u/l and T3 : palm kernel cake extracted acetic acid (CH3COOH) 1% + enzyme mannanase 100 u/l. The results showed that mannan extraction had significant effect (P<0.05) in improving the quality of physical and numerically increase the value of crude protein and decrease the value of NDF (Neutral Detergent Fiber). Treatments had highly significant influence (P<0.01) on the metabolizable energy value of palm kernel cake residue in broiler chickens. It can be concluded that extraction with aquadest + enzyme mannanase 100 u/l yields the best nutrient quality of palm kernel cake residue for broiler chicken.

  14. Economic and Social Impacts of Coal Development in the 1970's for Mercer County, North Dakota.

    ERIC Educational Resources Information Center

    Carroll (Thomas E.) Associates, Washington, DC.

    In addition to providing an information base for North Dakota decision makers faced with immediate coal development plans in Mercer County, this study is also designed to serve as a prototype for similar studies incorporating the format and assumptions of the Old West Regional Commission's "Procedures Manual". The investigation is…

  15. Observed and Modeled Bio-Optical, Bioluminescent, and Physical Properties during a Coastal Upwelling Event in Monterey Bay, California

    DTIC Science & Technology

    2011-01-27

    users’ guide, report, Sequoia Sei., Inc., Mercer Island, Wash. (Available at http://www. HydroLight. info). Moblcy, C. D., and L. K. Sundman (2001b...HydroLight 4.2 technical doc- umentation, report. Sequoia Sei.. Inc., Mercer Island. Wash. (Available at http://www.HydroLight.info). Molinc, M

  16. Mercer County Community College Remedial Program Assessment, August 1988. Two Year Follow-Up of the Fall 1986 Cohort.

    ERIC Educational Resources Information Center

    Porter, Al

    This assessment of New Jersey's Mercer County Community College's (MCCC's) remedial program provides a program overview, results of a two-year follow-up of fall 1986 remedial students, and comparative data from previous years. The program overview examines policies and procedures concerning placement criteria, exit standards, program acceptance,…

  17. Proposal for an Early Retirement Incentive Program at Mercer County Community College.

    ERIC Educational Resources Information Center

    Schwartz, Arthur E.

    A project was undertaken to evaluate existing models of early retirement incentive programs (ERIPs) and recommend an ERIP for New Jersey's Mercer County Community College (MCCC). The following categories of ERIPs were reviewed: state plans for New York and Minnesota; K-12 school districts plans at the Castro Valley Unified School District and 48…

  18. A Quantitative Content Analysis of Mercer University MEd, EdS, and Doctoral Theses

    ERIC Educational Resources Information Center

    Randolph, Justus J.; Gaiek, Lura S.; White, Torian A.; Slappey, Lisa A.; Chastain, Andrea; Harris, Rose Prejean

    2010-01-01

    Quantitative content analysis of a body of research not only helps budding researchers understand the culture, language, and expectations of scholarship, it helps identify deficiencies and inform policy and practice. Because of these benefits, an analysis of a census of 980 Mercer University MEd, EdS, and doctoral theses was conducted. Each thesis…

  19. NAIplot: An opensource web tool to visualize neuraminidase inhibitor (NAI) phenotypic susceptibility results using kernel density plots.

    PubMed

    Lytras, Theodore; Kossyvakis, Athanasios; Mentis, Andreas

    2016-02-01

    The results of neuraminidase inhibitor (NAI) enzyme inhibition assays are commonly expressed as 50% inhibitory concentration (IC50) fold-change values and presented graphically in box plots (box-and-whisker plots). An alternative and more informative type of graph is the kernel density plot, which we propose should be the preferred one for this purpose. In this paper we discuss the limitations of box plots and the advantages of the kernel density plot, and we present NAIplot, an opensource web application that allows convenient creation of density plots specifically for visualizing the results of NAI enzyme inhibition assays, as well as for general purposes. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Improvement of density models of geological structures by fusion of gravity data and cosmic muon radiographies

    NASA Astrophysics Data System (ADS)

    Jourde, K.; Gibert, D.; Marteau, J.

    2015-04-01

    This paper examines how the resolution of small-scale geological density models is improved through the fusion of information provided by gravity measurements and density muon radiographies. Muon radiography aims at determining the density of geological bodies by measuring their screening effect on the natural flux of cosmic muons. Muon radiography essentially works like medical X-ray scan and integrates density information along elongated narrow conical volumes. Gravity measurements are linked to density by a 3-D integration encompassing the whole studied domain. We establish the mathematical expressions of these integration formulas - called acquisition kernels - and derive the resolving kernels that are spatial filters relating the true unknown density structure to the density distribution actually recovered from the available data. The resolving kernels approach allows to quantitatively describe the improvement of the resolution of the density models achieved by merging gravity data and muon radiographies. The method developed in this paper may be used to optimally design the geometry of the field measurements to perform in order to obtain a given spatial resolution pattern of the density model to construct. The resolving kernels derived in the joined muon/gravimetry case indicate that gravity data are almost useless to constrain the density structure in regions sampled by more than two muon tomography acquisitions. Interestingly the resolution in deeper regions not sampled by muon tomography is significantly improved by joining the two techniques. The method is illustrated with examples for La Soufrière of Guadeloupe volcano.

  1. The Image of the Community College: Faculty Perceptions at Mercer County Community College.

    ERIC Educational Resources Information Center

    Dietrich, Marilyn L.

    As part of an effort to improve the image of Mercer County Community College, in New Jersey, a faculty member conducted interviews of 15 colleagues and 4 students to determine their perceptions of the college. Participants were asked about their present attitudes towards the college, their views when they first began, what the college does best,…

  2. Mercer County Community College Workplace Skills Project. Grant Period March 1, 1991-August 31, 1992. Final Evaluation.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    This final report of an 18-month workplace literacy project (a partnership of Mercer County Community College, a large automobile components parts manufacturer, a hospital, a physics laboratory, and a chemical plant) contains the following: (1) and introduction; (2) a performance report on nine goals of the program; (3) a schedule of…

  3. 19. Photocopy of photograph (source uncertain; probably Bucks County Historical ...

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

    19. Photocopy of photograph (source uncertain; probably Bucks County Historical Society) ca. 1916, photographer unknown SHOWING CONSTRUCTION ESSENTIALLY COMPLETED. MERCER'S CAPTION READS: 'ON SATURDAY EVENING, NOVEMBER 13th AT 5: 15 P.M. THE WORKMEN HAVING AT FIVE O'CLOCK FINISHED THE CONSTRUCTION OF THE NEW BUILDING OF THE MUSEUM OF THE BUCKS COUNTY HISTORICAL SOCIETY AT DOYLESTOWN, A BAND OF TRAVELLING MUSICIANS STOPPED UNASKED AT NO. 196 GREEN STREET OPPOSITE THE SOUTHEAST GABLE OF THE BUILDING AND I HEARD THEM PLAY THE GERMAN SONG SHOWN BELOW, TRANSLATED 'WE HAD BUILT A STATELY HOUSE, AND DEDICATED IT TO GOD, AGAINST RAIN, STORM AND DISASTER' I CALLED THEM BACK TO PLAY IT AGAIN, BUT THEY MISUNDERSTOOD ME AND WENT AWAY. HENRY C. MERCER' - Mercer Museum, Pine & Ashland Streets, Doylestown, Bucks County, PA

  4. Optimized Kernel Entropy Components.

    PubMed

    Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

    2017-06-01

    This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

  5. A fast and objective multidimensional kernel density estimation method: fastKDE

    DOE PAGES

    O'Brien, Travis A.; Kashinath, Karthik; Cavanaugh, Nicholas R.; ...

    2016-03-07

    Numerous facets of scientific research implicitly or explicitly call for the estimation of probability densities. Histograms and kernel density estimates (KDEs) are two commonly used techniques for estimating such information, with the KDE generally providing a higher fidelity representation of the probability density function (PDF). Both methods require specification of either a bin width or a kernel bandwidth. While techniques exist for choosing the kernel bandwidth optimally and objectively, they are computationally intensive, since they require repeated calculation of the KDE. A solution for objectively and optimally choosing both the kernel shape and width has recently been developed by Bernacchiamore » and Pigolotti (2011). While this solution theoretically applies to multidimensional KDEs, it has not been clear how to practically do so. A method for practically extending the Bernacchia-Pigolotti KDE to multidimensions is introduced. This multidimensional extension is combined with a recently-developed computational improvement to their method that makes it computationally efficient: a 2D KDE on 10 5 samples only takes 1 s on a modern workstation. This fast and objective KDE method, called the fastKDE method, retains the excellent statistical convergence properties that have been demonstrated for univariate samples. The fastKDE method exhibits statistical accuracy that is comparable to state-of-the-science KDE methods publicly available in R, and it produces kernel density estimates several orders of magnitude faster. The fastKDE method does an excellent job of encoding covariance information for bivariate samples. This property allows for direct calculation of conditional PDFs with fastKDE. It is demonstrated how this capability might be leveraged for detecting non-trivial relationships between quantities in physical systems, such as transitional behavior.« less

  6. Improvement of density models of geological structures by fusion of gravity data and cosmic muon radiographies

    NASA Astrophysics Data System (ADS)

    Jourde, K.; Gibert, D.; Marteau, J.

    2015-08-01

    This paper examines how the resolution of small-scale geological density models is improved through the fusion of information provided by gravity measurements and density muon radiographies. Muon radiography aims at determining the density of geological bodies by measuring their screening effect on the natural flux of cosmic muons. Muon radiography essentially works like a medical X-ray scan and integrates density information along elongated narrow conical volumes. Gravity measurements are linked to density by a 3-D integration encompassing the whole studied domain. We establish the mathematical expressions of these integration formulas - called acquisition kernels - and derive the resolving kernels that are spatial filters relating the true unknown density structure to the density distribution actually recovered from the available data. The resolving kernel approach allows one to quantitatively describe the improvement of the resolution of the density models achieved by merging gravity data and muon radiographies. The method developed in this paper may be used to optimally design the geometry of the field measurements to be performed in order to obtain a given spatial resolution pattern of the density model to be constructed. The resolving kernels derived in the joined muon-gravimetry case indicate that gravity data are almost useless for constraining the density structure in regions sampled by more than two muon tomography acquisitions. Interestingly, the resolution in deeper regions not sampled by muon tomography is significantly improved by joining the two techniques. The method is illustrated with examples for the La Soufrière volcano of Guadeloupe.

  7. Symbol recognition with kernel density matching.

    PubMed

    Zhang, Wan; Wenyin, Liu; Zhang, Kun

    2006-12-01

    We propose a novel approach to similarity assessment for graphic symbols. Symbols are represented as 2D kernel densities and their similarity is measured by the Kullback-Leibler divergence. Symbol orientation is found by gradient-based angle searching or independent component analysis. Experimental results show the outstanding performance of this approach in various situations.

  8. A Comparison of Full-Time Faculty Members and Administrators with Respect to Their Perceived Impacts of Selected Societal Factors on Mercer County Community College.

    ERIC Educational Resources Information Center

    Bolge, Robert D.

    A study was conducted at Mercer County Community College (MCCC), in New Jersey, to compare the perceptions of full-time faculty and administrators of the impact of selected societal factors on the college and provide MCCC with a theoretical basis for implementing its strategic planning model. A survey inventory of 34 societal factors was…

  9. Geology and ground-water resources of northern Mercer County, Pennsylvania

    USGS Publications Warehouse

    Schiner, G.R.; Kimmel, G.E.

    1976-01-01

    The Shenango and Stoneboro 15-minute quadrangles are in northwestern Pennsylvania and are about 60 miles north of Pitts burgh. These two quadrangles comprise the following 7%-minute quadrangles: Greenville West, Greenville East, Sharpsville, Fredonia, Hadley, New Lebanon, Jackson Center, and Sandy Lake. The area covered by the two quadrangles includes the northern two thirds of Mercer County and a small amount of adjoining southern Crawford County.

  10. Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map.

    PubMed

    Kumar, Ajay; Mantovani, E E; Seetan, R; Soltani, A; Echeverry-Solarte, M; Jain, S; Simsek, S; Doehlert, D; Alamri, M S; Elias, E M; Kianian, S F; Mergoum, M

    2016-03-01

    Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools. Copyright © 2016 Crop Science Society of America.

  11. Raman microprobe analysis of single ramie fiber during mercerization

    Treesearch

    Akira Isogai; Umesh P. Agarwal; Rajai H. Atalla

    2003-01-01

    The Raman microprobe technique was applied to structural analysis of single ramie fibers during mercerization. Polarized laser beam was irradiated on a ramie fiber in 0-30 % NaOD/D2O with the electric vector at 0 or 90° to the fiber axis, and Raman spectra thus obtained were studied in relation to the concentration of NaOD in D2O. Conversion of -OH to -OD in ramie...

  12. Evaluation of various carbon blacks and dispersing agents for use in the preparation of uranium microspheres with carbon

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

    Hunt, Rodney Dale; Johnson, Jared A.; Collins, Jack Lee

    A comparison study on carbon blacks and dispersing agents was performed to determine their impacts on the final properties of uranium fuel kernels with carbon. The main target compositions in this internal gelation study were 10 and 20 mol % uranium dicarbide (UC 2), which is UC 1.86, with the balance uranium dioxide. After heat treatment at 1900 K in flowing carbon monoxide in argon for 12 h, the density of the kernels produced using a X-energy proprietary carbon suspension, which is commercially available, ranged from 96% to 100% of theoretical density (TD), with full conversion of UC to UCmore » 2 at both carbon concentrations. However, higher carbon concentrations such as a 2.5 mol ratio of carbon to uranium in the feed solutions failed to produce gel spheres with the proprietary carbon suspension. The kernels using our former baseline of Mogul L carbon black and Tamol SN were 90–92% of TD with full conversion of UC to UC 2 at a variety of carbon levels. Raven 5000 carbon black and Tamol SN were used to produce 10 mol % UC2 kernels with 95% of TD. However, an increase in the Raven 5000 concentration led to a kernel density below 90% of TD. Raven 3500 carbon black and Tamol SN were used to make very dense kernels without complete conversion to UC 2. Lastly, the selection of the carbon black and dispersing agent is highly dependent on the desired final properties of the target kernels.« less

  13. Evaluation of various carbon blacks and dispersing agents for use in the preparation of uranium microspheres with carbon

    NASA Astrophysics Data System (ADS)

    Hunt, R. D.; Johnson, J. A.; Collins, J. L.; McMurray, J. W.; Reif, T. J.; Brown, D. R.

    2018-01-01

    A comparison study on carbon blacks and dispersing agents was performed to determine their impacts on the final properties of uranium fuel kernels with carbon. The main target compositions in this internal gelation study were 10 and 20 mol % uranium dicarbide (UC2), which is UC1.86, with the balance uranium dioxide. After heat treatment at 1900 K in flowing carbon monoxide in argon for 12 h, the density of the kernels produced using a X-energy proprietary carbon suspension, which is commercially available, ranged from 96% to 100% of theoretical density (TD), with full conversion of UC to UC2 at both carbon concentrations. However, higher carbon concentrations such as a 2.5 mol ratio of carbon to uranium in the feed solutions failed to produce gel spheres with the proprietary carbon suspension. The kernels using our former baseline of Mogul L carbon black and Tamol SN were 90-92% of TD with full conversion of UC to UC2 at a variety of carbon levels. Raven 5000 carbon black and Tamol SN were used to produce 10 mol % UC2 kernels with 95% of TD. However, an increase in the Raven 5000 concentration led to a kernel density below 90% of TD. Raven 3500 carbon black and Tamol SN were used to make very dense kernels without complete conversion to UC2. The selection of the carbon black and dispersing agent is highly dependent on the desired final properties of the target kernels.

  14. Evaluation of various carbon blacks and dispersing agents for use in the preparation of uranium microspheres with carbon

    DOE PAGES

    Hunt, Rodney Dale; Johnson, Jared A.; Collins, Jack Lee; ...

    2017-10-12

    A comparison study on carbon blacks and dispersing agents was performed to determine their impacts on the final properties of uranium fuel kernels with carbon. The main target compositions in this internal gelation study were 10 and 20 mol % uranium dicarbide (UC 2), which is UC 1.86, with the balance uranium dioxide. After heat treatment at 1900 K in flowing carbon monoxide in argon for 12 h, the density of the kernels produced using a X-energy proprietary carbon suspension, which is commercially available, ranged from 96% to 100% of theoretical density (TD), with full conversion of UC to UCmore » 2 at both carbon concentrations. However, higher carbon concentrations such as a 2.5 mol ratio of carbon to uranium in the feed solutions failed to produce gel spheres with the proprietary carbon suspension. The kernels using our former baseline of Mogul L carbon black and Tamol SN were 90–92% of TD with full conversion of UC to UC 2 at a variety of carbon levels. Raven 5000 carbon black and Tamol SN were used to produce 10 mol % UC2 kernels with 95% of TD. However, an increase in the Raven 5000 concentration led to a kernel density below 90% of TD. Raven 3500 carbon black and Tamol SN were used to make very dense kernels without complete conversion to UC 2. Lastly, the selection of the carbon black and dispersing agent is highly dependent on the desired final properties of the target kernels.« less

  15. The Library Work Order Processing System: A New Approach to Motivate Employees and to Increase Production in the Technical Service Department of Mercer County Community College Library. Applied Educational Research and Evaluation.

    ERIC Educational Resources Information Center

    Sim, Yong Sup

    After reviewing the current movement toward job enrichment, a system was designed for the technical services department of the Mercer County Community College Library. The Library Work Order Processing System, as tried between January and March, 1974, was designed to permit each worker more variety of jobs. The technical services department was…

  16. Resolvability of regional density structure

    NASA Astrophysics Data System (ADS)

    Plonka, A.; Fichtner, A.

    2016-12-01

    Lateral density variations are the source of mass transport in the Earth at all scales, acting as drivers of convectivemotion. However, the density structure of the Earth remains largely unknown since classic seismic observables and gravityprovide only weak constraints with strong trade-offs. Current density models are therefore often based on velocity scaling,making strong assumptions on the origin of structural heterogeneities, which may not necessarily be correct. Our goal is to assessif 3D density structure may be resolvable with emerging full-waveform inversion techniques. We have previously quantified the impact of regional-scale crustal density structure on seismic waveforms with the conclusion that reasonably sized density variations within thecrust can leave a strong imprint on both travel times and amplitudes, and, while this can produce significant biases in velocity and Q estimates, the seismic waveform inversion for density may become feasible. In this study we performprincipal component analyses of sensitivity kernels for P velocity, S velocity, and density. This is intended to establish theextent to which these kernels are linearly independent, i.e. the extent to which the different parameters may be constrainedindependently. Since the density imprint we observe is not exclusively linked to travel times and amplitudes of specific phases,we consider waveform differences between complete seismograms. We test the method using a known smooth model of the crust and seismograms with clear Love and Rayleigh waves, showing that - as expected - the first principal kernel maximizes sensitivity to SH and SV velocity structure, respectively, and that the leakage between S velocity, P velocity and density parameter spaces is minimal in the chosen setup. Next, we apply the method to data from 81 events around the Iberian Penninsula, registered in total by 492 stations. The objective is to find a principal kernel which would maximize the sensitivity to density, potentially allowing for independent density resolution, and, as the final goal, for direct density inversion.

  17. Dissection of genetic factors underlying wheat kernel shape and size in an elite x nonadapted cross using a high density SNP linkage map

    USDA-ARS?s Scientific Manuscript database

    Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414...

  18. How bandwidth selection algorithms impact exploratory data analysis using kernel density estimation.

    PubMed

    Harpole, Jared K; Woods, Carol M; Rodebaugh, Thomas L; Levinson, Cheri A; Lenze, Eric J

    2014-09-01

    Exploratory data analysis (EDA) can reveal important features of underlying distributions, and these features often have an impact on inferences and conclusions drawn from data. Graphical analysis is central to EDA, and graphical representations of distributions often benefit from smoothing. A viable method of estimating and graphing the underlying density in EDA is kernel density estimation (KDE). This article provides an introduction to KDE and examines alternative methods for specifying the smoothing bandwidth in terms of their ability to recover the true density. We also illustrate the comparison and use of KDE methods with 2 empirical examples. Simulations were carried out in which we compared 8 bandwidth selection methods (Sheather-Jones plug-in [SJDP], normal rule of thumb, Silverman's rule of thumb, least squares cross-validation, biased cross-validation, and 3 adaptive kernel estimators) using 5 true density shapes (standard normal, positively skewed, bimodal, skewed bimodal, and standard lognormal) and 9 sample sizes (15, 25, 50, 75, 100, 250, 500, 1,000, 2,000). Results indicate that, overall, SJDP outperformed all methods. However, for smaller sample sizes (25 to 100) either biased cross-validation or Silverman's rule of thumb was recommended, and for larger sample sizes the adaptive kernel estimator with SJDP was recommended. Information is provided about implementing the recommendations in the R computing language. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  19. Characteristics of uranium carbonitride microparticles synthesized using different reaction conditions

    NASA Astrophysics Data System (ADS)

    Silva, Chinthaka M.; Lindemer, Terrence B.; Voit, Stewart R.; Hunt, Rodney D.; Besmann, Theodore M.; Terrani, Kurt A.; Snead, Lance L.

    2014-11-01

    Three sets of experimental conditions were tested to synthesize uranium carbonitride (UC1-xNx) kernels from gel-derived urania-carbon microspheres. Primarily, three sequences of gases were used, N2 to N2-4%H2 to Ar, Ar to N2 to Ar, and Ar-4%H2 to N2-4%H2 to Ar-4%H2. Physical and chemical characteristics such as geometrical density, phase purity, and chemical compositions of the synthesized UC1-xNx were measured. Single-phase kernels were commonly obtained with densities generally ranging from 85% to 93% TD and values of x as high as 0.99. In-depth analysis of the microstrutures of UC1-xNx has been carried out and is discussed with the objective of large batch fabrication of high density UC1-xNx kernels.

  20. Approximation of the breast height diameter distribution of two-cohort stands by mixture models III Kernel density estimators vs mixture models

    Treesearch

    Rafal Podlaski; Francis A. Roesch

    2014-01-01

    Two-component mixtures of either the Weibull distribution or the gamma distribution and the kernel density estimator were used for describing the diameter at breast height (dbh) empirical distributions of two-cohort stands. The data consisted of study plots from the Å wietokrzyski National Park (central Poland) and areas close to and including the North Carolina section...

  1. Effect of operating conditions on the performances of multichannel ceramic UF membranes for textile mercerization wastewater treatment.

    PubMed

    Zebić Avdičević, Maja; Košutić, Krešimir; Dobrović, Slaven

    2017-01-01

    Textile wastewaters are rated as one of the most polluting in all industrial sectors, and membrane separation is the most promising technology for their treatment and reuse of auxiliary chemicals. This study evaluates the performance of three types of tubular ceramic ultrafiltration membranes differing by mean pore size (1, 2 and 500 kDa) treating textile mercerization wastewater from a textile mill at different operating conditions: cross-flow velocity (CFV) and temperature. Acceptable results were obtained with 1 kDa ceramic membrane, with rejection efficiencies 92% for suspended solids, 98% for turbidity, 98% for color and 53% for total organic carbon at 20°C and 3 m s -1 CFV. Highest fouling effect was observed for 500 kDa membrane and lowest CFV. According to the observed results, 1 kDa membrane could be used for the treatment of wastewater from the textile mercerization process in terms of permeate quality.

  2. Nonparametric probability density estimation by optimization theoretic techniques

    NASA Technical Reports Server (NTRS)

    Scott, D. W.

    1976-01-01

    Two nonparametric probability density estimators are considered. The first is the kernel estimator. The problem of choosing the kernel scaling factor based solely on a random sample is addressed. An interactive mode is discussed and an algorithm proposed to choose the scaling factor automatically. The second nonparametric probability estimate uses penalty function techniques with the maximum likelihood criterion. A discrete maximum penalized likelihood estimator is proposed and is shown to be consistent in the mean square error. A numerical implementation technique for the discrete solution is discussed and examples displayed. An extensive simulation study compares the integrated mean square error of the discrete and kernel estimators. The robustness of the discrete estimator is demonstrated graphically.

  3. Some physical properties of ginkgo nuts and kernels

    NASA Astrophysics Data System (ADS)

    Ch'ng, P. E.; Abdullah, M. H. R. O.; Mathai, E. J.; Yunus, N. A.

    2013-12-01

    Some data of the physical properties of ginkgo nuts at a moisture content of 45.53% (±2.07) (wet basis) and of their kernels at 60.13% (± 2.00) (wet basis) are presented in this paper. It consists of the estimation of the mean length, width, thickness, the geometric mean diameter, sphericity, aspect ratio, unit mass, surface area, volume, true density, bulk density, and porosity measures. The coefficient of static friction for nuts and kernels was determined by using plywood, glass, rubber, and galvanized steel sheet. The data are essential in the field of food engineering especially dealing with design and development of machines, and equipment for processing and handling agriculture products.

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

    Jolly, Brian C.; Helmreich, Grant; Cooley, Kevin M.

    In support of fully ceramic microencapsulated (FCM) fuel development, coating development work is ongoing at Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with both UN kernels and surrogate (uranium-free) kernels. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere. The surrogate TRISO particles are necessary for separate effects testing and for utilization in the consolidation process development. This report focuses on the fabrication and characterization of surrogate TRISO particles which use 800μm in diameter ZrO 2 microspheres as the kernel.

  5. A shock-capturing SPH scheme based on adaptive kernel estimation

    NASA Astrophysics Data System (ADS)

    Sigalotti, Leonardo Di G.; López, Hender; Donoso, Arnaldo; Sira, Eloy; Klapp, Jaime

    2006-02-01

    Here we report a method that converts standard smoothed particle hydrodynamics (SPH) into a working shock-capturing scheme without relying on solutions to the Riemann problem. Unlike existing adaptive SPH simulations, the present scheme is based on an adaptive kernel estimation of the density, which combines intrinsic features of both the kernel and nearest neighbor approaches in a way that the amount of smoothing required in low-density regions is effectively controlled. Symmetrized SPH representations of the gas dynamic equations along with the usual kernel summation for the density are used to guarantee variational consistency. Implementation of the adaptive kernel estimation involves a very simple procedure and allows for a unique scheme that handles strong shocks and rarefactions the same way. Since it represents a general improvement of the integral interpolation on scattered data, it is also applicable to other fluid-dynamic models. When the method is applied to supersonic compressible flows with sharp discontinuities, as in the classical one-dimensional shock-tube problem and its variants, the accuracy of the results is comparable, and in most cases superior, to that obtained from high quality Godunov-type methods and SPH formulations based on Riemann solutions. The extension of the method to two- and three-space dimensions is straightforward. In particular, for the two-dimensional cylindrical Noh's shock implosion and Sedov point explosion problems the present scheme produces much better results than those obtained with conventional SPH codes.

  6. Adiabatic-connection fluctuation-dissipation DFT for the structural properties of solids—The renormalized ALDA and electron gas kernels

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

    Patrick, Christopher E., E-mail: chripa@fysik.dtu.dk; Thygesen, Kristian S., E-mail: thygesen@fysik.dtu.dk

    2015-09-14

    We present calculations of the correlation energies of crystalline solids and isolated systems within the adiabatic-connection fluctuation-dissipation formulation of density-functional theory. We perform a quantitative comparison of a set of model exchange-correlation kernels originally derived for the homogeneous electron gas (HEG), including the recently introduced renormalized adiabatic local-density approximation (rALDA) and also kernels which (a) satisfy known exact limits of the HEG, (b) carry a frequency dependence, or (c) display a 1/k{sup 2} divergence for small wavevectors. After generalizing the kernels to inhomogeneous systems through a reciprocal-space averaging procedure, we calculate the lattice constants and bulk moduli of a testmore » set of 10 solids consisting of tetrahedrally bonded semiconductors (C, Si, SiC), ionic compounds (MgO, LiCl, LiF), and metals (Al, Na, Cu, Pd). We also consider the atomization energy of the H{sub 2} molecule. We compare the results calculated with different kernels to those obtained from the random-phase approximation (RPA) and to experimental measurements. We demonstrate that the model kernels correct the RPA’s tendency to overestimate the magnitude of the correlation energy whilst maintaining a high-accuracy description of structural properties.« less

  7. Triso coating development progress for uranium nitride kernels

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

    Jolly, Brian C.; Lindemer, Terrence; Terrani, Kurt A.

    2015-08-01

    In support of fully ceramic matrix (FCM) fuel development [1-2], coating development work is ongoing at the Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with UN kernels [3]. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere [4]. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO2 and UCx) kernels [5]. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions weremore » required to maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels (Table 1).« less

  8. New library building: Mercer University School of Medicine, Macon, Georgia.

    PubMed Central

    Rankin, J A; Bernard, G R

    1984-01-01

    The Mercer University School of Medicine (MUSM) enrolled its charter class in 1982. The curriculum is problem-based and adaptable to the learning needs of each student. MUSM is housed in a new building designed to support this unique educational program. Its library is an example of a comparatively small, but fully functional, medical school library. The planning process, design, and layout of the new library facility are described. Among its unique features are an integrated print and non-print collection, current periodical display space, and extensive use of task lighting. PMID:6733330

  9. The quantitative properties of three soft X-ray flare kernels observed with the AS&E X-ray telescope on Skylab

    NASA Technical Reports Server (NTRS)

    Kahler, S. W.; Petrasso, R. D.; Kane, S. R.

    1976-01-01

    The physical parameters for the kernels of three solar X-ray flare events have been deduced using photographic data from the S-054 X-ray telescope on Skylab as the primary data source and 1-8 and 8-20 A fluxes from Solrad 9 as the secondary data source. The kernels had diameters of about 5-7 seconds of arc and in two cases electron densities at least as high as 0.3 trillion per cu cm. The lifetimes of the kernels were 5-10 min. The presence of thermal conduction during the decay phases is used to argue: (1) that kernels are entire, not small portions of, coronal loop structures, and (2) that flare heating must continue during the decay phase. We suggest a simple geometric model to explain the role of kernels in flares in which kernels are identified with emerging flux regions.

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

    Jolly, Brian C.; Lindemer, Terrence; Terrani, Kurt A.

    In support of fully ceramic matrix (FCM) fuel development, coating development work has begun at the Oak Ridge National Laboratory (ORNL) to produce tri-isotropic (TRISO) coated fuel particles with UN kernels. The nitride kernels are used to increase heavy metal density in these SiC-matrix fuel pellets with details described elsewhere. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO 2 and UC x) kernels. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions were required tomore » maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels.« less

  11. Distributed Noise Generation for Density Estimation Based Clustering without Trusted Third Party

    NASA Astrophysics Data System (ADS)

    Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi

    The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suffer from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

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

    O'Brien, Travis A.; Kashinath, Karthik; Cavanaugh, Nicholas R.

    Numerous facets of scientific research implicitly or explicitly call for the estimation of probability densities. Histograms and kernel density estimates (KDEs) are two commonly used techniques for estimating such information, with the KDE generally providing a higher fidelity representation of the probability density function (PDF). Both methods require specification of either a bin width or a kernel bandwidth. While techniques exist for choosing the kernel bandwidth optimally and objectively, they are computationally intensive, since they require repeated calculation of the KDE. A solution for objectively and optimally choosing both the kernel shape and width has recently been developed by Bernacchiamore » and Pigolotti (2011). While this solution theoretically applies to multidimensional KDEs, it has not been clear how to practically do so. A method for practically extending the Bernacchia-Pigolotti KDE to multidimensions is introduced. This multidimensional extension is combined with a recently-developed computational improvement to their method that makes it computationally efficient: a 2D KDE on 10 5 samples only takes 1 s on a modern workstation. This fast and objective KDE method, called the fastKDE method, retains the excellent statistical convergence properties that have been demonstrated for univariate samples. The fastKDE method exhibits statistical accuracy that is comparable to state-of-the-science KDE methods publicly available in R, and it produces kernel density estimates several orders of magnitude faster. The fastKDE method does an excellent job of encoding covariance information for bivariate samples. This property allows for direct calculation of conditional PDFs with fastKDE. It is demonstrated how this capability might be leveraged for detecting non-trivial relationships between quantities in physical systems, such as transitional behavior.« less

  13. Probing the Dragonfish star-forming complex: the ionizing population of the young massive cluster Mercer 30

    NASA Astrophysics Data System (ADS)

    de la Fuente, D.; Najarro, F.; Borissova, J.; Ramírez Alegría, S.; Hanson, M. M.; Trombley, C.; Figer, D. F.; Davies, B.; Garcia, M.; Kurtev, R.; Urbaneja, M. A.; Smith, L. C.; Lucas, P. W.; Herrero, A.

    2016-05-01

    It has recently been claimed that the nebula, Dragonfish, is powered by a superluminous but elusive OB association. However, systematic searches in near-infrared photometric surveys have found many other cluster candidates in this region of the sky. Among these, the first confirmed young massive cluster was Mercer 30, where Wolf-Rayet stars were found.We perform a new characterization of Mercer 30 with unprecedented accuracy, combining NICMOS/HST and VVV photometric data with multi-epoch ISAAC/VLT H- and K-band spectra. Stellar parameters for most of spectroscopically observed cluster members are found through precise non-LTE atmosphere modeling with the CMFGEN code. Our spectrophotometric study for this cluster yields a new, revised distance of d = (12.4 ± 1.7) kpc and a total of QHMc30 ≈ 6.70 × 1050 s-1 Lyman ionizing photons. A cluster age of (4.0 ± 0.8) Myr is found through isochrone fitting, and a total mass of (1.6 ± 0.6) × 104M⊙ is estimated, thanks to our extensive knowledge of the post-main-sequence population. As a consequence, membership of Mercer 30 to the Dragonfish star-forming complex is confirmed, allowing us to use this cluster as a probe for the whole complex, which turns out to be extremely large (~400 pc across) and located at the outer edge of the Sagittarius-Carina spiral arm (~11 kpc from the Galactic center). The Dragonfish complex hosts 19 young clusters or cluster candidates (including Mercer 30 and a new candidate presented in this work) and an estimated minimum of nine field Wolf-Rayet stars. All these contributions account for, at least 73% of the ionization of the Dragonfish nebula and leaves little or no room for the alleged superluminous OB association; alternative explanations are discussed. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile, under programs IDs 179.B-2002, 081.D-0471, 083.D-0765, 087.D-0957, and 089.D-0989.

  14. Handling Density Conversion in TPS.

    PubMed

    Isobe, Tomonori; Mori, Yutaro; Takei, Hideyuki; Sato, Eisuke; Tadano, Kiichi; Kobayashi, Daisuke; Tomita, Tetsuya; Sakae, Takeji

    2016-01-01

    Conversion from CT value to density is essential to a radiation treatment planning system. Generally CT value is converted to the electron density in photon therapy. In the energy range of therapeutic photon, interactions between photons and materials are dominated with Compton scattering which the cross-section depends on the electron density. The dose distribution is obtained by calculating TERMA and kernel using electron density where TERMA is the energy transferred from primary photons and kernel is a volume considering spread electrons. Recently, a new method was introduced which uses the physical density. This method is expected to be faster and more accurate than that using the electron density. As for particle therapy, dose can be calculated with CT-to-stopping power conversion since the stopping power depends on the electron density. CT-to-stopping power conversion table is also called as CT-to-water-equivalent range and is an essential concept for the particle therapy.

  15. GPU Acceleration of Mean Free Path Based Kernel Density Estimators for Monte Carlo Neutronics Simulations

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

    Burke, TImothy P.; Kiedrowski, Brian C.; Martin, William R.

    Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics formore » one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.« less

  16. Three-dimensional holoscopic image coding scheme using high-efficiency video coding with kernel-based minimum mean-square-error estimation

    NASA Astrophysics Data System (ADS)

    Liu, Deyang; An, Ping; Ma, Ran; Yang, Chao; Shen, Liquan; Li, Kai

    2016-07-01

    Three-dimensional (3-D) holoscopic imaging, also known as integral imaging, light field imaging, or plenoptic imaging, can provide natural and fatigue-free 3-D visualization. However, a large amount of data is required to represent the 3-D holoscopic content. Therefore, efficient coding schemes for this particular type of image are needed. A 3-D holoscopic image coding scheme with kernel-based minimum mean square error (MMSE) estimation is proposed. In the proposed scheme, the coding block is predicted by an MMSE estimator under statistical modeling. In order to obtain the signal statistical behavior, kernel density estimation (KDE) is utilized to estimate the probability density function of the statistical modeling. As bandwidth estimation (BE) is a key issue in the KDE problem, we also propose a BE method based on kernel trick. The experimental results demonstrate that the proposed scheme can achieve a better rate-distortion performance and a better visual rendering quality.

  17. Density-Aware Clustering Based on Aggregated Heat Kernel and Its Transformation

    DOE PAGES

    Huang, Hao; Yoo, Shinjae; Yu, Dantong; ...

    2015-06-01

    Current spectral clustering algorithms suffer from the sensitivity to existing noise, and parameter scaling, and may not be aware of different density distributions across clusters. If these problems are left untreated, the consequent clustering results cannot accurately represent true data patterns, in particular, for complex real world datasets with heterogeneous densities. This paper aims to solve these problems by proposing a diffusion-based Aggregated Heat Kernel (AHK) to improve the clustering stability, and a Local Density Affinity Transformation (LDAT) to correct the bias originating from different cluster densities. AHK statistically\\ models the heat diffusion traces along the entire time scale, somore » it ensures robustness during clustering process, while LDAT probabilistically reveals local density of each instance and suppresses the local density bias in the affinity matrix. Our proposed framework integrates these two techniques systematically. As a result, not only does it provide an advanced noise-resisting and density-aware spectral mapping to the original dataset, but also demonstrates the stability during the processing of tuning the scaling parameter (which usually controls the range of neighborhood). Furthermore, our framework works well with the majority of similarity kernels, which ensures its applicability to many types of data and problem domains. The systematic experiments on different applications show that our proposed algorithms outperform state-of-the-art clustering algorithms for the data with heterogeneous density distributions, and achieve robust clustering performance with respect to tuning the scaling parameter and handling various levels and types of noise.« less

  18. The distal portion of the short arm of wheat (Triticum aestivum L.) chromosome 5D controls endosperm vitreosity and grain hardness.

    PubMed

    Morris, Craig F; Beecher, Brian S

    2012-07-01

    Kernel vitreosity is an important trait of wheat grain, but its developmental control is not completely known. We developed back-cross seven (BC(7)) near-isogenic lines in the soft white spring wheat cultivar Alpowa that lack the distal portion of chromosome 5D short arm. From the final back-cross, 46 BC(7)F(2) plants were isolated. These plants exhibited a complete and perfect association between kernel vitreosity (i.e. vitreous, non-vitreous or mixed) and Single Kernel Characterization System (SKCS) hardness. Observed segregation of 10:28:7 fit a 1:2:1 Chi-square. BC(7)F(2) plants classified as heterozygous for both SKCS hardness and kernel vitreosity (n = 29) were selected and a single vitreous and non-vitreous kernel were selected, and grown to maturity and subjected to SKCS analysis. The resultant phenotypic ratios were, from non-vitreous kernels, 23:6:0, and from vitreous kernels, 0:1:28, soft:heterozygous:hard, respectively. Three of these BC(7)F(2) heterozygous plants were selected and 40 kernels each drawn at random, grown to maturity and subjected to SKCS analysis. Phenotypic segregation ratios were 7:27:6, 11:20:9, and 3:28:9, soft:heterozygous:hard. Chi-square analysis supported a 1:2:1 segregation for one plant but not the other two, in which cases the two homozygous classes were under-represented. Twenty-two paired BC(7)F(2):F(3) full sibs were compared for kernel hardness, weight, size, density and protein content. SKCS hardness index differed markedly, 29.4 for the lines with a complete 5DS, and 88.6 for the lines possessing the deletion. The soft non-vitreous kernels were on average significantly heavier, by nearly 20%, and were slightly larger. Density and protein contents were similar, however. The results provide strong genetic evidence that gene(s) on distal 5DS control not only kernel hardness but also the manner in which the endosperm develops, viz. whether it is vitreous or non-vitreous.

  19. Nonlocal kinetic energy functional from the jellium-with-gap model: Applications to orbital-free density functional theory

    NASA Astrophysics Data System (ADS)

    Constantin, Lucian A.; Fabiano, Eduardo; Della Sala, Fabio

    2018-05-01

    Orbital-free density functional theory (OF-DFT) promises to describe the electronic structure of very large quantum systems, being its computational cost linear with the system size. However, the OF-DFT accuracy strongly depends on the approximation made for the kinetic energy (KE) functional. To date, the most accurate KE functionals are nonlocal functionals based on the linear-response kernel of the homogeneous electron gas, i.e., the jellium model. Here, we use the linear-response kernel of the jellium-with-gap model to construct a simple nonlocal KE functional (named KGAP) which depends on the band-gap energy. In the limit of vanishing energy gap (i.e., in the case of metals), the KGAP is equivalent to the Smargiassi-Madden (SM) functional, which is accurate for metals. For a series of semiconductors (with different energy gaps), the KGAP performs much better than SM, and results are close to the state-of-the-art functionals with sophisticated density-dependent kernels.

  20. Spatiotemporal Domain Decomposition for Massive Parallel Computation of Space-Time Kernel Density

    NASA Astrophysics Data System (ADS)

    Hohl, A.; Delmelle, E. M.; Tang, W.

    2015-07-01

    Accelerated processing capabilities are deemed critical when conducting analysis on spatiotemporal datasets of increasing size, diversity and availability. High-performance parallel computing offers the capacity to solve computationally demanding problems in a limited timeframe, but likewise poses the challenge of preventing processing inefficiency due to workload imbalance between computing resources. Therefore, when designing new algorithms capable of implementing parallel strategies, careful spatiotemporal domain decomposition is necessary to account for heterogeneity in the data. In this study, we perform octtree-based adaptive decomposition of the spatiotemporal domain for parallel computation of space-time kernel density. In order to avoid edge effects near subdomain boundaries, we establish spatiotemporal buffers to include adjacent data-points that are within the spatial and temporal kernel bandwidths. Then, we quantify computational intensity of each subdomain to balance workloads among processors. We illustrate the benefits of our methodology using a space-time epidemiological dataset of Dengue fever, an infectious vector-borne disease that poses a severe threat to communities in tropical climates. Our parallel implementation of kernel density reaches substantial speedup compared to sequential processing, and achieves high levels of workload balance among processors due to great accuracy in quantifying computational intensity. Our approach is portable of other space-time analytical tests.

  1. Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

    PubMed

    Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

    2018-02-13

    Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  2. Resolvability of regional density structure and the road to direct density inversion - a principal-component approach to resolution analysis

    NASA Astrophysics Data System (ADS)

    Płonka, Agnieszka; Fichtner, Andreas

    2017-04-01

    Lateral density variations are the source of mass transport in the Earth at all scales, acting as drivers of convective motion. However, the density structure of the Earth remains largely unknown since classic seismic observables and gravity provide only weak constraints with strong trade-offs. Current density models are therefore often based on velocity scaling, making strong assumptions on the origin of structural heterogeneities, which may not necessarily be correct. Our goal is to assess if 3D density structure may be resolvable with emerging full-waveform inversion techniques. We have previously quantified the impact of regional-scale crustal density structure on seismic waveforms with the conclusion that reasonably sized density variations within the crust can leave a strong imprint on both travel times and amplitudes, and, while this can produce significant biases in velocity and Q estimates, the seismic waveform inversion for density may become feasible. In this study we perform principal component analyses of sensitivity kernels for P velocity, S velocity, and density. This is intended to establish the extent to which these kernels are linearly independent, i.e. the extent to which the different parameters may be constrained independently. We apply the method to data from 81 events around the Iberian Penninsula, registered in total by 492 stations. The objective is to find a principal kernel which would maximize the sensitivity to density, potentially allowing for as independent as possible density resolution. We find that surface (mosty Rayleigh) waves have significant sensitivity to density, and that the trade-off with velocity is negligible. We also show the preliminary results of the inversion.

  3. Water quality, hydrology, and simulated response to changes in phosphorus loading of Mercer Lake, Iron County, Wisconsin, with special emphasis on the effects of wastewater discharges

    USGS Publications Warehouse

    Robertson, Dale M.; Garn, Herbert S.; Rose, William J.; Juckem, Paul F.; Reneau, Paul C.

    2012-01-01

    Mercer Lake is a relatively shallow drainage lake in north-central Wisconsin. The area near the lake has gone through many changes over the past century, including urbanization and industrial development. To try to improve the water quality of the lake, actions have been taken, such as removal of the lumber mill and diversion of all effluent from the sewage treatment plant away from the lake; however, it is uncertain how these actions have affected water quality. Mercer Lake area residents and authorities would like to continue to try to improve the water quality of the lake; however, they would like to place their efforts in the actions that will have the most beneficial effects. To provide a better understanding of the factors affecting the water quality of Mercer Lake, a detailed study of the lake and its watershed was conducted by the U.S. Geological Survey in collaboration with the Mercer Lake Association. The purposes of the study were to describe the water quality of the lake and the composition of its sediments; quantify the sources of water and phosphorus loading to the lake, including sources associated with wastewater discharges; and evaluate the effects of past and future changes in phosphorus inputs on the water quality of the lake using eutrophication models (models that simulate changes in phosphorus and algae concentrations and water clarity in the lake). Based on analyses of sediment cores and monitoring data collected from the lake, the water quality of Mercer Lake appears to have degraded as a result of the activities in its watershed over the past 100 years. The water quality appears to have improved, however, since a sewage treatment plant was constructed in 1965 and its effluent was routed away from the lake in 1995. Since 2000, when a more consistent monitoring program began, the water quality of the lake appears to have changed very little. During the two monitoring years (MY) 2008-09, the average summer near-surface concentration of total phosphorus was 0.023 mg/L, indicating the lake is borderline mesotrophic-eutrophic, or has moderate to high concentrations of phosphorus, whereas the average summer chlorophyll a concentration was 3.3 mg/L and water clarity, as measured with a Secchi depth, was 10.4 ft, both indicating mesotrophic conditions or that the lake has a moderate amount of algae and water clarity. Although actions have been taken to eliminate the wastewater discharges, the bottom sediment still has slightly elevated concentrations of several pollutants from wastewater discharges, lumber operations, and roadway drainage, and a few naturally occurring metals (such as iron). None of the concentrations, however, were high enough above the defined thresholds to be of concern. Based on nitrogen to phosphorus ratios, the productivity (algal growth) in Mercer Lake should typically be limited by phosphorus; therefore, understanding the phosphorus input to the lake is important when management efforts to improve or prevent degradation of the lake water quality are considered. Total inputs of phosphorus to Mercer Lake were directly estimated for MY 2008-09 at about 340 lb/yr and for a recent year with more typical hydrology at about 475 lb/yr. During these years, the largest sources of phosphorus were from Little Turtle Inlet, which contributed about 45 percent, and the drainage area near the lake containing the adjacent urban and residential developments, which contributed about 24 percent. Prior to 1965, when there was no sewage treatment plant and septic systems and other untreated systems contributed nutrients to the watershed, phosphorus loadings were estimated to be about 71 percent higher than during around 2009. In 1965, a sewage treatment plant was built, but its effluent was released in the downstream end of the lake. Depending on various assumptions on how much effluent was retained in the lake, phosphorus inputs from wastewater may have ranged from 0 to 342 lb. Future highway and stormwater improvements have been identified in the Mercer Infrastructure Improvement Project, and if they are done with the proposed best management practices, then phosphorus inputs to the lake may decrease by about 40 lb. Eutrophication models [Canfield and Bachman model (1981) and Carlson Trophic State Index equations (1977)] were used to predict how the water quality of Mercer Lake should respond to changes in phosphorus loading. A relatively linear response was found between phosphorus loading and phosphorus and chlorophyll a concentrations in the lake, with changes in phosphorus concentrations being slightly less (about 80 percent) and changes in chlorophyll a concentrations being slightly more (about 120 percent) than the changes in phosphorus loadings to the lake. Water clarity, indicated by Secchi depths, responded more to decreases in phosphorus loading than to increases in loading. Results from the eutrophication models indicated that the lake should have been negatively affected by the wastewater discharges. Prior to 1965, when there was no sewage treatment plant effluent and inputs from the septic systems and other untreated systems were thought to be high, the lake should have been eutrophic; near the surface, average phosphorus concentrations were almost 0.035 mg/L, chlorophyll a concentrations were about 7 μg/L, and Secchi depths were about 6 ft, which agreed with the shallower Secchi depths during this time estimated from the sediment-core analysis. The models indicated that between 1965 and 1995, when the lake retained some of the effluent from the new sewage treatment plant, water quality should have been between the conditions estimated prior to 1965 and what was expected during typical hydrologic conditions around MY 2008-09. The models also indicated that if the future Mercer Infrastructure Improvement Project is conducted with the best management practices as proposed, the water quality in the lake could improve slightly from that measured during 2006-10. Because of the small amount of phosphorus that is presently input into Mercer Lake any additional phosphorus added to the lake could degrade water quality; therefore, management actions can usefully focus on minimizing future phosphorus inputs. Phosphorus released from the sediments of a degraded lake often delays its response to decreases in external phosphorus loading, especially in shallow, frequently mixed systems. Mercer Lake, however, remains stratified throughout most of the summer, and phosphorus released from the sediments represents only about 6 percent, or a small fraction, of the total phosphorus load to the lake. Therefore, the phosphorus trapped in the sediments should minimally affect the long-term water quality of the lake and should not delay the response in its productivity to future changes in nutrient loading from its watershed.

  4. Linked-cluster formulation of electron-hole interaction kernel in real-space representation without using unoccupied states.

    PubMed

    Bayne, Michael G; Scher, Jeremy A; Ellis, Benjamin H; Chakraborty, Arindam

    2018-05-21

    Electron-hole or quasiparticle representation plays a central role in describing electronic excitations in many-electron systems. For charge-neutral excitation, the electron-hole interaction kernel is the quantity of interest for calculating important excitation properties such as optical gap, optical spectra, electron-hole recombination and electron-hole binding energies. The electron-hole interaction kernel can be formally derived from the density-density correlation function using both Green's function and TDDFT formalism. The accurate determination of the electron-hole interaction kernel remains a significant challenge for precise calculations of optical properties in the GW+BSE formalism. From the TDDFT perspective, the electron-hole interaction kernel has been viewed as a path to systematic development of frequency-dependent exchange-correlation functionals. Traditional approaches, such as MBPT formalism, use unoccupied states (which are defined with respect to Fermi vacuum) to construct the electron-hole interaction kernel. However, the inclusion of unoccupied states has long been recognized as the leading computational bottleneck that limits the application of this approach for larger finite systems. In this work, an alternative derivation that avoids using unoccupied states to construct the electron-hole interaction kernel is presented. The central idea of this approach is to use explicitly correlated geminal functions for treating electron-electron correlation for both ground and excited state wave functions. Using this ansatz, it is derived using both diagrammatic and algebraic techniques that the electron-hole interaction kernel can be expressed only in terms of linked closed-loop diagrams. It is proved that the cancellation of unlinked diagrams is a consequence of linked-cluster theorem in real-space representation. The electron-hole interaction kernel derived in this work was used to calculate excitation energies in many-electron systems and results were found to be in good agreement with the EOM-CCSD and GW+BSE methods. The numerical results highlight the effectiveness of the developed method for overcoming the computational barrier of accurately determining the electron-hole interaction kernel to applications of large finite systems such as quantum dots and nanorods.

  5. Pattern formation of microtubules and motors: inelastic interaction of polar rods.

    PubMed

    Aranson, Igor S; Tsimring, Lev S

    2005-05-01

    We derive a model describing spatiotemporal organization of an array of microtubules interacting via molecular motors. Starting from a stochastic model of inelastic polar rods with a generic anisotropic interaction kernel we obtain a set of equations for the local rods concentration and orientation. At large enough mean density of rods and concentration of motors, the model describes orientational instability. We demonstrate that the orientational instability leads to the formation of vortices and (for large density and/or kernel anisotropy) asters seen in recent experiments.

  6. On the polymorphic and morphological changes of cellulose nanocrystals (CNC-I) upon mercerization and conversion to CNC-II.

    PubMed

    Jin, Ersuo; Guo, Jiaqi; Yang, Fang; Zhu, Yangyang; Song, Junlong; Jin, Yongcan; Rojas, Orlando J

    2016-06-05

    Polymorphic and morphological transformations of cellulosic materials are strongly associated to their properties and applications, especially in the case of emerging nanocelluloses. Related changes that take place upon treatment of cellulose nanocrystals (CNC) in alkaline conditions are studied here by XRD, TEM, AFM, and other techniques. The results indicate polymorphic transformation of CNC proceeds gradually in a certain range of alkali concentrations, i.e. from about 8% to 12.5% NaOH. In such transition alkali concentration, cellulose I and II allomorphs coexists. Such value and range of the transition concentration is strongly interdependent with the crystallite size of CNCs. In addition, it is distinctively lower than that for macroscopic fibers (12-15% NaOH). Transmission electron microscopy and particle sizing reveals that after mercerization CNCs tend to associate. Furthermore, TEMPO-oxidized mercerized CNC reveals the morphology of individual nanocrystal of the cellulose II type, which is composed of some interconnected granular structures. Overall, this work reveals how the polymorphism and morphology of individual CNC change in alkali conditions and sheds light onto the polymorphic transition from cellulose I to II. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Do we really need a large number of particles to simulate bimolecular reactive transport with random walk methods? A kernel density estimation approach

    NASA Astrophysics Data System (ADS)

    Rahbaralam, Maryam; Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier

    2015-12-01

    Random walk particle tracking methods are a computationally efficient family of methods to solve reactive transport problems. While the number of particles in most realistic applications is in the order of 106-109, the number of reactive molecules even in diluted systems might be in the order of fractions of the Avogadro number. Thus, each particle actually represents a group of potentially reactive molecules. The use of a low number of particles may result not only in loss of accuracy, but also may lead to an improper reproduction of the mixing process, limited by diffusion. Recent works have used this effect as a proxy to model incomplete mixing in porous media. In this work, we propose using a Kernel Density Estimation (KDE) of the concentrations that allows getting the expected results for a well-mixed solution with a limited number of particles. The idea consists of treating each particle as a sample drawn from the pool of molecules that it represents; this way, the actual location of a tracked particle is seen as a sample drawn from the density function of the location of molecules represented by that given particle, rigorously represented by a kernel density function. The probability of reaction can be obtained by combining the kernels associated to two potentially reactive particles. We demonstrate that the observed deviation in the reaction vs time curves in numerical experiments reported in the literature could be attributed to the statistical method used to reconstruct concentrations (fixed particle support) from discrete particle distributions, and not to the occurrence of true incomplete mixing. We further explore the evolution of the kernel size with time, linking it to the diffusion process. Our results show that KDEs are powerful tools to improve computational efficiency and robustness in reactive transport simulations, and indicates that incomplete mixing in diluted systems should be modeled based on alternative mechanistic models and not on a limited number of particles.

  8. Using Adjoint Methods to Improve 3-D Velocity Models of Southern California

    NASA Astrophysics Data System (ADS)

    Liu, Q.; Tape, C.; Maggi, A.; Tromp, J.

    2006-12-01

    We use adjoint methods popular in climate and ocean dynamics to calculate Fréchet derivatives for tomographic inversions in southern California. The Fréchet derivative of an objective function χ(m), where m denotes the Earth model, may be written in the generic form δχ=int Km(x) δln m(x) d3x, where δln m=δ m/m denotes the relative model perturbation. For illustrative purposes, we construct the 3-D finite-frequency banana-doughnut kernel Km, corresponding to the misfit of a single traveltime measurement, by simultaneously computing the 'adjoint' wave field s† forward in time and reconstructing the regular wave field s backward in time. The adjoint wave field is produced by using the time-reversed velocity at the receiver as a fictitious source, while the regular wave field is reconstructed on the fly by propagating the last frame of the wave field saved by a previous forward simulation backward in time. The approach is based upon the spectral-element method, and only two simulations are needed to produce density, shear-wave, and compressional-wave sensitivity kernels. This method is applied to the SCEC southern California velocity model. Various density, shear-wave, and compressional-wave sensitivity kernels are presented for different phases in the seismograms. We also generate 'event' kernels for Pnl, S and surface waves, which are the Fréchet kernels of misfit functions that measure the P, S or surface wave traveltime residuals at all the receivers simultaneously for one particular event. Effectively, an event kernel is a sum of weighted Fréchet kernels, with weights determined by the associated traveltime anomalies. By the nature of the 3-D simulation, every event kernel is also computed based upon just two simulations, i.e., its construction costs the same amount of computation time as an individual banana-doughnut kernel. One can think of the sum of the event kernels for all available earthquakes, called the 'misfit' kernel, as a graphical representation of the gradient of the misfit function. With the capability of computing both the value of the misfit function and its gradient, which assimilates the traveltime anomalies, we are ready to use a non-linear conjugate gradient algorithm to iteratively improve velocity models of southern California.

  9. New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

    PubMed

    Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

    2017-06-21

    We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

  10. Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

    PubMed

    Cid, Jaime A; von Davier, Alina A

    2015-05-01

    Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

  11. Magnetic field influences on the lateral dose response functions of photon-beam detectors: MC study of wall-less water-filled detectors with various densities.

    PubMed

    Looe, Hui Khee; Delfs, Björn; Poppinga, Daniela; Harder, Dietrich; Poppe, Björn

    2017-06-21

    The distortion of detector reading profiles across photon beams in the presence of magnetic fields is a developing subject of clinical photon-beam dosimetry. The underlying modification by the Lorentz force of a detector's lateral dose response function-the convolution kernel transforming the true cross-beam dose profile in water into the detector reading profile-is here studied for the first time. The three basic convolution kernels, the photon fluence response function, the dose deposition kernel, and the lateral dose response function, of wall-less cylindrical detectors filled with water of low, normal and enhanced density are shown by Monte Carlo simulation to be distorted in the prevailing direction of the Lorentz force. The asymmetric shape changes of these convolution kernels in a water medium and in magnetic fields of up to 1.5 T are confined to the lower millimetre range, and they depend on the photon beam quality, the magnetic flux density and the detector's density. The impact of this distortion on detector reading profiles is demonstrated using a narrow photon beam profile. For clinical applications it appears as favourable that the magnetic flux density dependent distortion of the lateral dose response function, as far as secondary electron transport is concerned, vanishes in the case of water-equivalent detectors of normal water density. By means of secondary electron history backtracing, the spatial distribution of the photon interactions giving rise either directly to secondary electrons or to scattered photons further downstream producing secondary electrons which contribute to the detector's signal, and their lateral shift due to the Lorentz force is elucidated. Electron history backtracing also serves to illustrate the correct treatment of the influences of the Lorentz force in the EGSnrc Monte Carlo code applied in this study.

  12. Reproductive sink of sweet corn in response to plant density and hybrid

    USDA-ARS?s Scientific Manuscript database

    Improvements in plant density tolerance have played an essential role in grain corn yield gains for ~80 years; however, plant density effects on sweet corn biomass allocation to the ear (the reproductive ‘sink’) is poorly quantified. Moreover, optimal plant densities for modern white-kernel shrunke...

  13. Reservoir area of influence and implications for fisheries management

    USGS Publications Warehouse

    Martin, Dustin R.; Chizinski, Christopher J.; Pope, Kevin L.

    2015-01-01

    Understanding the spatial area that a reservoir draws anglers from, defined as the reservoir's area of influence, and the potential overlap of that area of influence between reservoirs is important for fishery managers. Our objective was to define the area of influence for reservoirs of the Salt Valley regional fishery in southeastern Nebraska using kernel density estimation. We used angler survey data obtained from in-person interviews at 17 reservoirs during 2009–2012. The area of influence, defined by the 95% kernel density, for reservoirs within the Salt Valley regional fishery varied, indicating that anglers use reservoirs differently across the regional fishery. Areas of influence reveal angler preferences in a regional context, indicating preferred reservoirs with a greater area of influence. Further, differences in areas of influences across time and among reservoirs can be used as an assessment following management changes on an individual reservoir or within a regional fishery. Kernel density estimation provided a clear method for creating spatial maps of areas of influence and provided a two-dimensional view of angler travel, as opposed to the traditional mean travel distance assessment.

  14. A heat kernel proof of the index theorem for deformation quantization

    NASA Astrophysics Data System (ADS)

    Karabegov, Alexander

    2017-11-01

    We give a heat kernel proof of the algebraic index theorem for deformation quantization with separation of variables on a pseudo-Kähler manifold. We use normalizations of the canonical trace density of a star product and of the characteristic classes involved in the index formula for which this formula contains no extra constant factors.

  15. Diversity of maize kernels from a breeding program for protein quality III: Ionome profiling

    USDA-ARS?s Scientific Manuscript database

    Densities of single and multiple macro- and micronutrients have been estimated in mature kernels of 1,348 accessions in 13 maize genotypes. The germplasm belonged to stiff stalk (SS) and non-stiff stalk (NS) heterotic groups (HG) with one (S1) to four (S4) years of inbreeding (IB), or open pollinati...

  16. Efficient 3D movement-based kernel density estimator and application to wildlife ecology

    USGS Publications Warehouse

    Tracey-PR, Jeff; Sheppard, James K.; Lockwood, Glenn K.; Chourasia, Amit; Tatineni, Mahidhar; Fisher, Robert N.; Sinkovits, Robert S.

    2014-01-01

    We describe an efficient implementation of a 3D movement-based kernel density estimator for determining animal space use from discrete GPS measurements. This new method provides more accurate results, particularly for species that make large excursions in the vertical dimension. The downside of this approach is that it is much more computationally expensive than simpler, lower-dimensional models. Through a combination of code restructuring, parallelization and performance optimization, we were able to reduce the time to solution by up to a factor of 1000x, thereby greatly improving the applicability of the method.

  17. Calculation of the time resolution of the J-PET tomograph using kernel density estimation

    NASA Astrophysics Data System (ADS)

    Raczyński, L.; Wiślicki, W.; Krzemień, W.; Kowalski, P.; Alfs, D.; Bednarski, T.; Białas, P.; Curceanu, C.; Czerwiński, E.; Dulski, K.; Gajos, A.; Głowacz, B.; Gorgol, M.; Hiesmayr, B.; Jasińska, B.; Kamińska, D.; Korcyl, G.; Kozik, T.; Krawczyk, N.; Kubicz, E.; Mohammed, M.; Pawlik-Niedźwiecka, M.; Niedźwiecki, S.; Pałka, M.; Rudy, Z.; Rundel, O.; Sharma, N. G.; Silarski, M.; Smyrski, J.; Strzelecki, A.; Wieczorek, A.; Zgardzińska, B.; Zieliński, M.; Moskal, P.

    2017-06-01

    In this paper we estimate the time resolution of the J-PET scanner built from plastic scintillators. We incorporate the method of signal processing using the Tikhonov regularization framework and the kernel density estimation method. We obtain simple, closed-form analytical formulae for time resolution. The proposed method is validated using signals registered by means of the single detection unit of the J-PET tomograph built from a 30 cm long plastic scintillator strip. It is shown that the experimental and theoretical results obtained for the J-PET scanner equipped with vacuum tube photomultipliers are consistent.

  18. Nonlocal and Nonadiabatic Effects in the Charge-Density Response of Solids: A Time-Dependent Density-Functional Approach

    NASA Astrophysics Data System (ADS)

    Panholzer, Martin; Gatti, Matteo; Reining, Lucia

    2018-04-01

    The charge-density response of extended materials is usually dominated by the collective oscillation of electrons, the plasmons. Beyond this feature, however, intriguing many-body effects are observed. They cannot be described by one of the most widely used approaches for the calculation of dielectric functions, which is time-dependent density functional theory (TDDFT) in the adiabatic local density approximation (ALDA). Here, we propose an approximation to the TDDFT exchange-correlation kernel which is nonadiabatic and nonlocal. It is extracted from correlated calculations in the homogeneous electron gas, where we have tabulated it for a wide range of wave vectors and frequencies. A simple mean density approximation allows one to use it in inhomogeneous materials where the density varies on a scale of 1.6 rs or faster. This kernel contains effects that are completely absent in the ALDA; in particular, it correctly describes the double plasmon in the dynamic structure factor of sodium, and it shows the characteristic low-energy peak that appears in systems with low electronic density. It also leads to an overall quantitative improvement of spectra.

  19. Nonlocal and Nonadiabatic Effects in the Charge-Density Response of Solids: A Time-Dependent Density-Functional Approach.

    PubMed

    Panholzer, Martin; Gatti, Matteo; Reining, Lucia

    2018-04-20

    The charge-density response of extended materials is usually dominated by the collective oscillation of electrons, the plasmons. Beyond this feature, however, intriguing many-body effects are observed. They cannot be described by one of the most widely used approaches for the calculation of dielectric functions, which is time-dependent density functional theory (TDDFT) in the adiabatic local density approximation (ALDA). Here, we propose an approximation to the TDDFT exchange-correlation kernel which is nonadiabatic and nonlocal. It is extracted from correlated calculations in the homogeneous electron gas, where we have tabulated it for a wide range of wave vectors and frequencies. A simple mean density approximation allows one to use it in inhomogeneous materials where the density varies on a scale of 1.6 r_{s} or faster. This kernel contains effects that are completely absent in the ALDA; in particular, it correctly describes the double plasmon in the dynamic structure factor of sodium, and it shows the characteristic low-energy peak that appears in systems with low electronic density. It also leads to an overall quantitative improvement of spectra.

  20. SOME ENGINEERING PROPERTIES OF SHELLED AND KERNEL TEA (Camellia sinensis) SEEDS.

    PubMed

    Altuntas, Ebubekir; Yildiz, Merve

    2017-01-01

    Camellia sinensis is the source of tea leaves and it is an economic crop now grown around the World. Tea seed oil has been used for cooking in China and other Asian countries for more than a thousand years. Tea is the most widely consumed beverages after water in the world. It is mainly produced in Asia, central Africa, and exported throughout the World. Some engineering properties (size dimensions, sphericity, volume, bulk and true densities, friction coefficient, colour characteristics and mechanical behaviour as rupture force of shelled and kernel tea ( Camellia sinensis ) seeds were determined in this study. This research was carried out for shelled and kernel tea seeds. The shelled tea seeds used in this study were obtained from East-Black Sea Tea Cooperative Institution in Rize city of Turkey. Shelled and kernel tea seeds were characterized as large and small sizes. The average geometric mean diameter and seed mass of the shelled tea seeds were 15.8 mm, 10.7 mm (large size); 1.47 g, 0.49 g (small size); while the average geometric mean diameter and seed mass of the kernel tea seeds were 11.8 mm, 8 mm for large size; 0.97 g, 0.31 g for small size, respectively. The sphericity, surface area and volume values were found to be higher in a larger size than small size for the shelled and kernel tea samples. The shelled tea seed's colour intensity (Chroma) were found between 59.31 and 64.22 for large size, while the kernel tea seed's chroma values were found between 56.04 68.34 for large size, respectively. The rupture force values of kernel tea seeds were higher than shelled tea seeds for the large size along X axis; whereas, the rupture force values of along X axis were higher than Y axis for large size of shelled tea seeds. The static coefficients of friction of shelled and kernel tea seeds for the large and small sizes higher values for rubber than the other friction surfaces. Some engineering properties, such as geometric mean diameter, sphericity, volume, bulk and true densities, the coefficient of friction, L*, a*, b* colour characteristics and rupture force of shelled and kernel tea ( Camellia sinensis ) seeds will serve to design the equipment used in postharvest treatments.

  1. A Non-Local, Energy-Optimized Kernel: Recovering Second-Order Exchange and Beyond in Extended Systems

    NASA Astrophysics Data System (ADS)

    Bates, Jefferson; Laricchia, Savio; Ruzsinszky, Adrienn

    The Random Phase Approximation (RPA) is quickly becoming a standard method beyond semi-local Density Functional Theory that naturally incorporates weak interactions and eliminates self-interaction error. RPA is not perfect, however, and suffers from self-correlation error as well as an incorrect description of short-ranged correlation typically leading to underbinding. To improve upon RPA we introduce a short-ranged, exchange-like kernel that is one-electron self-correlation free for one and two electron systems in the high-density limit. By tuning the one free parameter in our model to recover an exact limit of the homogeneous electron gas correlation energy we obtain a non-local, energy-optimized kernel that reduces the errors of RPA for both homogeneous and inhomogeneous solids. To reduce the computational cost of the standard kernel-corrected RPA, we also implement RPA renormalized perturbation theory for extended systems, and demonstrate its capability to describe the dominant correlation effects with a low-order expansion in both metallic and non-metallic systems. Furthermore we stress that for norm-conserving implementations the accuracy of RPA and beyond RPA structural properties compared to experiment is inherently limited by the choice of pseudopotential. Current affiliation: King's College London.

  2. Spatial Variability of Organic Carbon in a Fractured Mudstone and Its Effect on the Retention and Release of Trichloroethene (TCE)

    NASA Astrophysics Data System (ADS)

    Sole-Mari, G.; Fernandez-Garcia, D.

    2016-12-01

    Random Walk Particle Tracking (RWPT) coupled with Kernel Density Estimation (KDE) has been recently proposed to simulate reactive transport in porous media. KDE provides an optimal estimation of the area of influence of particles which is a key element to simulate nonlinear chemical reactions. However, several important drawbacks can be identified: (1) the optimal KDE method is computationally intensive and thereby cannot be used at each time step of the simulation; (2) it does not take advantage of the prior information about the physical system and the previous history of the solute plume; (3) even if the kernel is optimal, the relative error in RWPT simulations typically increases over time as the particle density diminishes by dilution. To overcome these problems, we propose an adaptive branching random walk methodology that incorporates the physics, the particle history and maintains accuracy with time. The method allows particles to efficiently split and merge when necessary as well as to optimally adapt their local kernel shape without having to recalculate the kernel size. We illustrate the advantage of the method by simulating complex reactive transport problems in randomly heterogeneous porous media.

  3. Screening of the aerodynamic and biophysical properties of barley malt

    NASA Astrophysics Data System (ADS)

    Ghodsvali, Alireza; Farzaneh, Vahid; Bakhshabadi, Hamid; Zare, Zahra; Karami, Zahra; Mokhtarian, Mohsen; Carvalho, Isabel. S.

    2016-10-01

    An understanding of the aerodynamic and biophysical properties of barley malt is necessary for the appropriate design of equipment for the handling, shipping, dehydration, grading, sorting and warehousing of this strategic crop. Malting is a complex biotechnological process that includes steeping; germination and finally, the dehydration of cereal grains under controlled temperature and humidity conditions. In this investigation, the biophysical properties of barley malt were predicted using two models of artificial neural networks as well as response surface methodology. Stepping time and germination time were selected as the independent variables and 1 000 kernel weight, kernel density and terminal velocity were selected as the dependent variables (responses). The obtained outcomes showed that the artificial neural network model, with a logarithmic sigmoid activation function, presents more precise results than the response surface model in the prediction of the aerodynamic and biophysical properties of produced barley malt. This model presented the best result with 8 nodes in the hidden layer and significant correlation coefficient values of 0.783, 0.767 and 0.991 were obtained for responses one thousand kernel weight, kernel density, and terminal velocity, respectively. The outcomes indicated that this novel technique could be successfully applied in quantitative and qualitative monitoring within the malting process.

  4. Locally adaptive methods for KDE-based random walk models of reactive transport in porous media

    NASA Astrophysics Data System (ADS)

    Sole-Mari, G.; Fernandez-Garcia, D.

    2017-12-01

    Random Walk Particle Tracking (RWPT) coupled with Kernel Density Estimation (KDE) has been recently proposed to simulate reactive transport in porous media. KDE provides an optimal estimation of the area of influence of particles which is a key element to simulate nonlinear chemical reactions. However, several important drawbacks can be identified: (1) the optimal KDE method is computationally intensive and thereby cannot be used at each time step of the simulation; (2) it does not take advantage of the prior information about the physical system and the previous history of the solute plume; (3) even if the kernel is optimal, the relative error in RWPT simulations typically increases over time as the particle density diminishes by dilution. To overcome these problems, we propose an adaptive branching random walk methodology that incorporates the physics, the particle history and maintains accuracy with time. The method allows particles to efficiently split and merge when necessary as well as to optimally adapt their local kernel shape without having to recalculate the kernel size. We illustrate the advantage of the method by simulating complex reactive transport problems in randomly heterogeneous porous media.

  5. Abiotic stress growth conditions induce different responses in kernel iron concentration across genotypically distinct maize inbred varieties

    PubMed Central

    Kandianis, Catherine B.; Michenfelder, Abigail S.; Simmons, Susan J.; Grusak, Michael A.; Stapleton, Ann E.

    2013-01-01

    The improvement of grain nutrient profiles for essential minerals and vitamins through breeding strategies is a target important for agricultural regions where nutrient poor crops like maize contribute a large proportion of the daily caloric intake. Kernel iron concentration in maize exhibits a broad range. However, the magnitude of genotype by environment (GxE) effects on this trait reduces the efficacy and predictability of selection programs, particularly when challenged with abiotic stress such as water and nitrogen limitations. Selection has also been limited by an inverse correlation between kernel iron concentration and the yield component of kernel size in target environments. Using 25 maize inbred lines for which extensive genome sequence data is publicly available, we evaluated the response of kernel iron density and kernel mass to water and nitrogen limitation in a managed field stress experiment using a factorial design. To further understand GxE interactions we used partition analysis to characterize response of kernel iron and weight to abiotic stressors among all genotypes, and observed two patterns: one characterized by higher kernel iron concentrations in control over stress conditions, and another with higher kernel iron concentration under drought and combined stress conditions. Breeding efforts for this nutritional trait could exploit these complementary responses through combinations of favorable allelic variation from these already well-characterized genetic stocks. PMID:24363659

  6. Kernel and divergence techniques in high energy physics separations

    NASA Astrophysics Data System (ADS)

    Bouř, Petr; Kůs, Václav; Franc, Jiří

    2017-10-01

    Binary decision trees under the Bayesian decision technique are used for supervised classification of high-dimensional data. We present a great potential of adaptive kernel density estimation as the nested separation method of the supervised binary divergence decision tree. Also, we provide a proof of alternative computing approach for kernel estimates utilizing Fourier transform. Further, we apply our method to Monte Carlo data set from the particle accelerator Tevatron at DØ experiment in Fermilab and provide final top-antitop signal separation results. We have achieved up to 82 % AUC while using the restricted feature selection entering the signal separation procedure.

  7. Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

    PubMed

    Zhang, Zhanhui; Wu, Xiangyuan; Shi, Chaonan; Wang, Rongna; Li, Shengfei; Wang, Zhaohui; Liu, Zonghua; Xue, Yadong; Tang, Guiliang; Tang, Jihua

    2016-02-01

    Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

  8. On supervised graph Laplacian embedding CA model & kernel construction and its application

    NASA Astrophysics Data System (ADS)

    Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

    2017-01-01

    There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

  9. Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012

    PubMed Central

    Carvalho, Silvia; Magalhães, Mônica de Avelar Figueiredo Mafra; Medronho, Roberto de Andrade

    2017-01-01

    ABSTRACT OBJECTIVE Analyze the spatial distribution of classical dengue and severe dengue cases in the city of Rio de Janeiro. METHODS Exploratory study, considering cases of classical dengue and severe dengue with laboratory confirmation of the infection in the city of Rio de Janeiro during the years 2011/2012. The georeferencing technique was applied for the cases notified in the Notification Increase Information System in the period of 2011 and 2012. For this process, the fields “street” and “number” were used. The ArcGis10 program’s Geocoding tool’s automatic process was performed. The spatial analysis was done through the kernel density estimator. RESULTS Kernel density pointed out hotspots for classic dengue that did not coincide geographically with severe dengue and were in or near favelas. The kernel ratio did not show a notable change in the spatial distribution pattern observed in the kernel density analysis. The georeferencing process showed a loss of 41% of classic dengue registries and 17% of severe dengue registries due to the address in the Notification Increase Information System form. CONCLUSIONS The hotspots near the favelas suggest that the social vulnerability of these localities can be an influencing factor for the occurrence of this aggravation since there is a deficiency of the supply and access to essential goods and services for the population. To reduce this vulnerability, interventions must be related to macroeconomic policies. PMID:28832752

  10. Carbothermic synthesis of 820 μm uranium nitride kernels: Literature review, thermodynamics, analysis, and related experiments

    NASA Astrophysics Data System (ADS)

    Lindemer, T. B.; Voit, S. L.; Silva, C. M.; Besmann, T. M.; Hunt, R. D.

    2014-05-01

    The US Department of Energy is developing a new nuclear fuel that would be less susceptible to ruptures during a loss-of-coolant accident. The fuel would consist of tristructural isotropic coated particles with uranium nitride (UN) kernels with diameters near 825 μm. This effort explores factors involved in the conversion of uranium oxide-carbon microspheres into UN kernels. An analysis of previous studies with sufficient experimental details is provided. Thermodynamic calculations were made to predict pressures of carbon monoxide and other relevant gases for several reactions that can be involved in the conversion of uranium oxides and carbides into UN. Uranium oxide-carbon microspheres were heated in a microbalance with an attached mass spectrometer to determine details of calcining and carbothermic conversion in argon, nitrogen, and vacuum. A model was derived from experiments on the vacuum conversion to uranium oxide-carbide kernels. UN-containing kernels were fabricated using this vacuum conversion as part of the overall process. Carbonitride kernels of ∼89% of theoretical density were produced along with several observations concerning the different stages of the process.

  11. Analytical Plug-In Method for Kernel Density Estimator Applied to Genetic Neutrality Study

    NASA Astrophysics Data System (ADS)

    Troudi, Molka; Alimi, Adel M.; Saoudi, Samir

    2008-12-01

    The plug-in method enables optimization of the bandwidth of the kernel density estimator in order to estimate probability density functions (pdfs). Here, a faster procedure than that of the common plug-in method is proposed. The mean integrated square error (MISE) depends directly upon [InlineEquation not available: see fulltext.] which is linked to the second-order derivative of the pdf. As we intend to introduce an analytical approximation of [InlineEquation not available: see fulltext.], the pdf is estimated only once, at the end of iterations. These two kinds of algorithm are tested on different random variables having distributions known for their difficult estimation. Finally, they are applied to genetic data in order to provide a better characterisation in the mean of neutrality of Tunisian Berber populations.

  12. Production of near-full density uranium nitride microspheres with a hot isostatic press

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

    McMurray, Jacob W.; Kiggans, Jr., Jim O.; Helmreich, Grant W.

    Depleted uranium nitride (UN) kernels with diameters ranging from 420 to 858 microns and theoretical densities (TD) between 87 and 91 percent were postprocessed using a hot isostatic press (HIP) in an argon gas media. This treatment was shown to increase the TD up to above 97%. Uranium nitride is highly reactive with oxygen. Therefore, a novel crucible design was implemented to remove impurities in the argon gas via in situ gettering to avoid oxidation of the UN kernels. The density before and after each HIP procedure was calculated from average weight, volume, and ellipticity determined with established characterization techniquesmore » for particle. Furthermore, micrographs confirmed the nearly full densification of the particles using the gettering approach and HIP processing parameters investigated in this work.« less

  13. A Kernel-Free Particle-Finite Element Method for Hypervelocity Impact Simulation. Chapter 4

    NASA Technical Reports Server (NTRS)

    Park, Young-Keun; Fahrenthold, Eric P.

    2004-01-01

    An improved hybrid particle-finite element method has been developed for the simulation of hypervelocity impact problems. Unlike alternative methods, the revised formulation computes the density without reference to any kernel or interpolation functions, for either the density or the rate of dilatation. This simplifies the state space model and leads to a significant reduction in computational cost. The improved method introduces internal energy variables as generalized coordinates in a new formulation of the thermomechanical Lagrange equations. Example problems show good agreement with exact solutions in one dimension and good agreement with experimental data in a three dimensional simulation.

  14. Modeling utilization distributions in space and time

    USGS Publications Warehouse

    Keating, K.A.; Cherry, S.

    2009-01-01

    W. Van Winkle defined the utilization distribution (UD) as a probability density that gives an animal's relative frequency of occurrence in a two-dimensional (x, y) plane. We extend Van Winkle's work by redefining the UD as the relative frequency distribution of an animal's occurrence in all four dimensions of space and time. We then describe a product kernel model estimation method, devising a novel kernel from the wrapped Cauchy distribution to handle circularly distributed temporal covariates, such as day of year. Using Monte Carlo simulations of animal movements in space and time, we assess estimator performance. Although not unbiased, the product kernel method yields models highly correlated (Pearson's r - 0.975) with true probabilities of occurrence and successfully captures temporal variations in density of occurrence. In an empirical example, we estimate the expected UD in three dimensions (x, y, and t) for animals belonging to each of two distinct bighorn sheep {Ovis canadensis) social groups in Glacier National Park, Montana, USA. Results show the method can yield ecologically informative models that successfully depict temporal variations in density of occurrence for a seasonally migratory species. Some implications of this new approach to UD modeling are discussed. ?? 2009 by the Ecological Society of America.

  15. 7 CFR 246.27 - Program information.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ..., New Jersey, Pennsylvania, Puerto Rico, Virginia, Virgin Islands, West Virginia: U.S. Department of Agriculture, FNS, Mid-Atlantic Region, Mercer Corporate Park, 300 Corporate Boulevard, Robbinsville, New...

  16. On- and off-axis spectral emission features from laser-produced gas breakdown plasmas

    NASA Astrophysics Data System (ADS)

    Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.; Brumfield, B. E.; Phillips, M. C.; Miloshevsky, G.

    2017-06-01

    Laser-heated gas breakdown plasmas or sparks emit profoundly in the ultraviolet and visible region of the electromagnetic spectrum with contributions from ionic, atomic, and molecular species. Laser created kernels expand into a cold ambient with high velocities during their early lifetime followed by confinement of the plasma kernel and eventually collapse. However, the plasma kernels produced during laser breakdown of gases are also capable of exciting and ionizing the surrounding ambient medium. Two mechanisms can be responsible for excitation and ionization of the surrounding ambient: photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early times of their creation and/or heating by strong shocks generated by the kernel during its expansion into the ambient. In this study, an investigation is made on the spectral features of on- and off-axis emission of laser-induced plasma breakdown kernels generated in atmospheric pressure conditions with an aim to elucidate the mechanisms leading to ambient excitation and emission. Pulses from an Nd:YAG laser emitting at 1064 nm with a pulse duration of 6 ns are used to generate plasma kernels. Laser sparks were generated in air, argon, and helium gases to provide different physical properties of expansion dynamics and plasma chemistry considering the differences in laser absorption properties, mass density, and speciation. Point shadowgraphy and time-resolved imaging were used to evaluate the shock wave and spark self-emission morphology at early and late times, while space and time resolved spectroscopy is used for evaluating the emission features and for inferring plasma physical conditions at on- and off-axis positions. The structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using the computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms, and molecules are separated in time with early time temperatures and densities in excess of 35 000 K and 4 × 1018/cm3 with an existence of thermal equilibrium. However, the emission from the off-kernel positions from the breakdown plasmas showed enhanced ultraviolet radiation with the presence of N2 bands and is represented by non-local thermodynamic equilibrium (non-LTE) conditions. Our results also highlight that the ultraviolet radiation emitted during the early time of spark evolution is the predominant source of the photo-excitation of the surrounding medium.

  17. On- and off-axis spectral emission features from laser-produced gas breakdown plasmas

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

    Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.

    Laser-heated gas breakdown plasmas or sparks emit profoundly in the ultraviolet and visible region of the electromagnetic spectrum with contributions from ionic, atomic, and molecular species. Laser created kernels expand into a cold ambient with high velocities during its early lifetime followed by confinement of the plasma kernel and eventually collapse. However, the plasma kernels produced during laser breakdown of gases are also capable of exciting and ionizing the surrounding ambient medium. Two mechanisms can be responsible for excitation and ionization of surrounding ambient: viz. photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early timesmore » of its creation and/or heating by strong shocks generated by the kernel during its expansion into the ambient. In this study, an investigation is made on the spectral features of on- and off-axis emission features of laser-induced plasma breakdown kernels generated in atmospheric pressure conditions with an aim to elucidate the mechanisms leading to ambient excitation and emission. Pulses from an Nd:YAG laser emitting at 1064 nm with 6 ns pulse duration are used to generate plasma kernels. Laser sparks were generated in air, argon, and helium gases to provide different physical properties of expansion dynamics and plasma chemistry considering the differences in laser absorption properties, mass density and speciation. Point shadowgraphy and time-resolved imaging were used to evaluate the shock wave and spark self-emission morphology at early and late times while space and time resolved spectroscopy is used for evaluating the emission features as well as for inferring plasma fundaments at on- and off-axis. Structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms and molecules are separated in time with an early time temperatures and densities in excess of 35000 K and 4×10 18 /cm 3 with an existence of thermal equilibrium. However, the emission from the off-kernel positions from the breakdown plasmas showed enhanced ultraviolet radiation with the presence of N 2 bands and represented by non-LTE conditions. Finally, our results also highlight that the ultraviolet radiation emitted during early time of spark evolution is the predominant source of the photo-excitation of the surrounding medium.« less

  18. On- and off-axis spectral emission features from laser-produced gas breakdown plasmas

    DOE PAGES

    Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.; ...

    2017-06-01

    Laser-heated gas breakdown plasmas or sparks emit profoundly in the ultraviolet and visible region of the electromagnetic spectrum with contributions from ionic, atomic, and molecular species. Laser created kernels expand into a cold ambient with high velocities during its early lifetime followed by confinement of the plasma kernel and eventually collapse. However, the plasma kernels produced during laser breakdown of gases are also capable of exciting and ionizing the surrounding ambient medium. Two mechanisms can be responsible for excitation and ionization of surrounding ambient: viz. photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early timesmore » of its creation and/or heating by strong shocks generated by the kernel during its expansion into the ambient. In this study, an investigation is made on the spectral features of on- and off-axis emission features of laser-induced plasma breakdown kernels generated in atmospheric pressure conditions with an aim to elucidate the mechanisms leading to ambient excitation and emission. Pulses from an Nd:YAG laser emitting at 1064 nm with 6 ns pulse duration are used to generate plasma kernels. Laser sparks were generated in air, argon, and helium gases to provide different physical properties of expansion dynamics and plasma chemistry considering the differences in laser absorption properties, mass density and speciation. Point shadowgraphy and time-resolved imaging were used to evaluate the shock wave and spark self-emission morphology at early and late times while space and time resolved spectroscopy is used for evaluating the emission features as well as for inferring plasma fundaments at on- and off-axis. Structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms and molecules are separated in time with an early time temperatures and densities in excess of 35000 K and 4×1018 /cm3 with an existence of thermal equilibrium. However, the emission from the off-kernel positions from the breakdown plasmas showed enhanced ultraviolet radiation with the presence of N2 bands and represented by non-LTE conditions. Our results also highlight that the ultraviolet radiation emitted during early time of spark evolution is the predominant source of the photo-excitation of the surrounding medium.« less

  19. A method of smoothed particle hydrodynamics using spheroidal kernels

    NASA Technical Reports Server (NTRS)

    Fulbright, Michael S.; Benz, Willy; Davies, Melvyn B.

    1995-01-01

    We present a new method of three-dimensional smoothed particle hydrodynamics (SPH) designed to model systems dominated by deformation along a preferential axis. These systems cause severe problems for SPH codes using spherical kernels, which are best suited for modeling systems which retain rough spherical symmetry. Our method allows the smoothing length in the direction of the deformation to evolve independently of the smoothing length in the perpendicular plane, resulting in a kernel with a spheroidal shape. As a result the spatial resolution in the direction of deformation is significantly improved. As a test case we present the one-dimensional homologous collapse of a zero-temperature, uniform-density cloud, which serves to demonstrate the advantages of spheroidal kernels. We also present new results on the problem of the tidal disruption of a star by a massive black hole.

  20. Transient and asymptotic behaviour of the binary breakage problem

    NASA Astrophysics Data System (ADS)

    Mantzaris, Nikos V.

    2005-06-01

    The general binary breakage problem with power-law breakage functions and two families of symmetric and asymmetric breakage kernels is studied in this work. A useful transformation leads to an equation that predicts self-similar solutions in its asymptotic limit and offers explicit knowledge of the mean size and particle density at each point in dimensionless time. A novel moving boundary algorithm in the transformed coordinate system is developed, allowing the accurate prediction of the full transient behaviour of the system from the initial condition up to the point where self-similarity is achieved, and beyond if necessary. The numerical algorithm is very rapid and its results are in excellent agreement with known analytical solutions. In the case of the symmetric breakage kernels only unimodal, self-similar number density functions are obtained asymptotically for all parameter values and independent of the initial conditions, while in the case of asymmetric breakage kernels, bimodality appears for high degrees of asymmetry and sharp breakage functions. For symmetric and discrete breakage kernels, self-similarity is not achieved. The solution exhibits sustained oscillations with amplitude that depends on the initial condition and the sharpness of the breakage mechanism, while the period is always fixed and equal to ln 2 with respect to dimensionless time.

  1. Quantification of process variables for carbothermic synthesis of UC 1-xN x fuel microspheres

    DOE PAGES

    Lindemer, Terrance B.; Silva, Chinthaka M.; Henry, Jr, John James; ...

    2016-11-05

    This report details the continued investigation of process variables involved in converting sol-gel-derived, urania-carbon microspheres to ~820-μm-dia. UC 1-xN x fuel kernels in flow-through, vertical Mo and W crucibles at temperatures up to 2123 K. Experiments included calcining of air-dried UO 3-H 2O-C microspheres in Ar and H 2-containing gases, conversion of the resulting UO 2-C kernels to dense UO2:2UC in the same gases and vacuum, and its conversion in N 2 to UC 1-xN x (x = ~0.85). The thermodynamics of the relevant reactions were applied extensively to interpret and control the process variables. Producing the precursor UO 2:2UCmore » kernel of ~96% theoretical density was required, but its subsequent conversion to UC 1-xN x at 2123 K was not accompanied by sintering and resulted in ~83-86% of theoretical density. Increasing the UC 1-xN x kernel nitride component to ~0.98 in flowing N 2-H 2 mixtures to evolve HCN was shown to be quantitatively consistent with present and past experiments and the only useful application of H 2 in the entire process.« less

  2. Quantification of process variables for carbothermic synthesis of UC1-xNx fuel microspheres

    NASA Astrophysics Data System (ADS)

    Lindemer, T. B.; Silva, C. M.; Henry, J. J.; McMurray, J. W.; Voit, S. L.; Collins, J. L.; Hunt, R. D.

    2017-01-01

    This report details the continued investigation of process variables involved in converting sol-gel-derived, urania-carbon microspheres to ∼820-μm-dia. UC1-xNx fuel kernels in flow-through, vertical Mo and W crucibles at temperatures up to 2123 K. Experiments included calcining of air-dried UO3-H2O-C microspheres in Ar and H2-containing gases, conversion of the resulting UO2-C kernels to dense UO2:2UC in the same gases and vacuum, and its conversion in N2 to UC1-xNx (x = ∼0.85). The thermodynamics of the relevant reactions were applied extensively to interpret and control the process variables. Producing the precursor UO2:2UC kernel of ∼96% theoretical density was required, but its subsequent conversion to UC1-xNx at 2123 K was not accompanied by sintering and resulted in ∼83-86% of theoretical density. Increasing the UC1-xNx kernel nitride component to ∼0.98 in flowing N2-H2 mixtures to evolve HCN was shown to be quantitatively consistent with present and past experiments and the only useful application of H2 in the entire process.

  3. Using kernel density estimation to understand the influence of neighbourhood destinations on BMI

    PubMed Central

    King, Tania L; Bentley, Rebecca J; Thornton, Lukar E; Kavanagh, Anne M

    2016-01-01

    Objectives Little is known about how the distribution of destinations in the local neighbourhood is related to body mass index (BMI). Kernel density estimation (KDE) is a spatial analysis technique that accounts for the location of features relative to each other. Using KDE, this study investigated whether individuals living near destinations (shops and service facilities) that are more intensely distributed rather than dispersed, have lower BMIs. Study design and setting A cross-sectional study of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Methods Destinations were geocoded, and kernel density estimates of destination intensity were created using kernels of 400, 800 and 1200 m. Using multilevel linear regression, the association between destination intensity (classified in quintiles Q1(least)–Q5(most)) and BMI was estimated in models that adjusted for the following confounders: age, sex, country of birth, education, dominant household occupation, household type, disability/injury and area disadvantage. Separate models included a physical activity variable. Results For kernels of 800 and 1200 m, there was an inverse relationship between BMI and more intensely distributed destinations (compared to areas with least destination intensity). Effects were significant at 1200 m: Q4, β −0.86, 95% CI −1.58 to −0.13, p=0.022; Q5, β −1.03 95% CI −1.65 to −0.41, p=0.001. Inclusion of physical activity in the models attenuated effects, although effects remained marginally significant for Q5 at 1200 m: β −0.77 95% CI −1.52, −0.02, p=0.045. Conclusions This study conducted within urban Melbourne, Australia, found that participants living in areas of greater destination intensity within 1200 m of home had lower BMIs. Effects were partly explained by physical activity. The results suggest that increasing the intensity of destination distribution could reduce BMI levels by encouraging higher levels of physical activity. PMID:26883235

  4. EFFECTS OF FLUID AND COMPUTED TOMOGRAPHIC TECHNICAL FACTORS ON CONSPICUITY OF CANINE AND FELINE NASAL TURBINATES

    PubMed Central

    Uosyte, Raimonda; Shaw, Darren J; Gunn-Moore, Danielle A; Fraga-Manteiga, Eduardo; Schwarz, Tobias

    2015-01-01

    Turbinate destruction is an important diagnostic criterion in canine and feline nasal computed tomography (CT). However decreased turbinate visibility may also be caused by technical CT settings and nasal fluid. The purpose of this experimental, crossover study was to determine whether fluid reduces conspicuity of canine and feline nasal turbinates in CT and if so, whether CT settings can maximize conspicuity. Three canine and three feline cadaver heads were used. Nasal slabs were CT-scanned before and after submerging them in a water bath; using sequential, helical, and ultrahigh resolution modes; with images in low, medium, and high frequency image reconstruction kernels; and with application of additional posterior fossa optimization and high contrast enhancing filters. Visible turbinate length was measured by a single observer using manual tracing. Nasal density heterogeneity was measured using the standard deviation (SD) of mean nasal density from a region of interest in each nasal cavity. Linear mixed-effect models using the R package ‘nlme’, multivariable models and standard post hoc Tukey pair-wise comparisons were performed to investigate the effect of several variables (nasal content, scanning mode, image reconstruction kernel, application of post reconstruction filters) on measured visible total turbinate length and SD of mean nasal density. All canine and feline water-filled nasal slabs showed significantly decreased visibility of nasal turbinates (P < 0.001). High frequency kernels provided the best turbinate visibility and highest SD of aerated nasal slabs, whereas medium frequency kernels were optimal for water-filled nasal slabs. Scanning mode and filter application had no effect on turbinate visibility. PMID:25867935

  5. SOMKE: kernel density estimation over data streams by sequences of self-organizing maps.

    PubMed

    Cao, Yuan; He, Haibo; Man, Hong

    2012-08-01

    In this paper, we propose a novel method SOMKE, for kernel density estimation (KDE) over data streams based on sequences of self-organizing map (SOM). In many stream data mining applications, the traditional KDE methods are infeasible because of the high computational cost, processing time, and memory requirement. To reduce the time and space complexity, we propose a SOM structure in this paper to obtain well-defined data clusters to estimate the underlying probability distributions of incoming data streams. The main idea of this paper is to build a series of SOMs over the data streams via two operations, that is, creating and merging the SOM sequences. The creation phase produces the SOM sequence entries for windows of the data, which obtains clustering information of the incoming data streams. The size of the SOM sequences can be further reduced by combining the consecutive entries in the sequence based on the measure of Kullback-Leibler divergence. Finally, the probability density functions over arbitrary time periods along the data streams can be estimated using such SOM sequences. We compare SOMKE with two other KDE methods for data streams, the M-kernel approach and the cluster kernel approach, in terms of accuracy and processing time for various stationary data streams. Furthermore, we also investigate the use of SOMKE over nonstationary (evolving) data streams, including a synthetic nonstationary data stream, a real-world financial data stream and a group of network traffic data streams. The simulation results illustrate the effectiveness and efficiency of the proposed approach.

  6. Synthesis and characterization of carboxylic cation exchange bio-resin for heavy metal remediation.

    PubMed

    Kulkarni, Vihangraj V; Golder, Animes Kumar; Ghosh, Pranab Kumar

    2018-01-05

    A new carboxylic bio-resin was synthesized from raw arecanut husk through mercerization and ethylenediaminetetraacetic dianhydride (EDTAD) carboxylation. The synthesized bio-resin was characterized using thermogravimetric analysis, field emission scanning electron microscopy, proximate & ultimate analyses, mass percent gain/loss, potentiometric titrations, and Fourier transform infrared spectroscopy. Mercerization extracted lignin from the vesicles on the husk and EDTAD was ridged in to, through an acylation reaction in dimethylformamide media. The reaction induced carboxylic groups as high as 0.735mM/g and a cation exchange capacity of 2.01meq/g functionalized mercerized husk (FMH). Potentiometric titration data were fitted to a newly developed single-site proton adsorption model (PAM) that gave pKa of 3.29 and carboxylic groups concentration of 0.741mM/g. FMH showed 99% efficiency in Pb(II) removal from synthetic wastewater (initial concentration 0.157mM), for which the Pb(II) binding constant was 1.73×10 3 L/mol as estimated from modified PAM. The exhaustion capacity was estimated to be 18.7mg/g of FMH. Desorption efficiency of Pb(II) from exhausted FMH was found to be about 97% with 0.1N HCl. The FMH simultaneously removed lead and cadmium below detection limit from a real lead acid battery wastewater along with the removal of Fe, Mg, Ni, and Co. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. 19 CFR 102.22 - Rules of origin for textile and apparel products of Israel.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ...: bleaching, shrinking, fulling, napping, decating, permanent stiffening, weighting, permanent embossing, or... as showerproofing, superwashing, bleaching, decating, fulling, shrinking, mercerizing, or similar...

  8. 19 CFR 102.22 - Rules of origin for textile and apparel products of Israel.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ...: bleaching, shrinking, fulling, napping, decating, permanent stiffening, weighting, permanent embossing, or... as showerproofing, superwashing, bleaching, decating, fulling, shrinking, mercerizing, or similar...

  9. 19 CFR 102.22 - Rules of origin for textile and apparel products of Israel.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ...: bleaching, shrinking, fulling, napping, decating, permanent stiffening, weighting, permanent embossing, or... as showerproofing, superwashing, bleaching, decating, fulling, shrinking, mercerizing, or similar...

  10. 19 CFR 102.22 - Rules of origin for textile and apparel products of Israel.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ...: bleaching, shrinking, fulling, napping, decating, permanent stiffening, weighting, permanent embossing, or... as showerproofing, superwashing, bleaching, decating, fulling, shrinking, mercerizing, or similar...

  11. 19 CFR 102.22 - Rules of origin for textile and apparel products of Israel.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ...: bleaching, shrinking, fulling, napping, decating, permanent stiffening, weighting, permanent embossing, or... as showerproofing, superwashing, bleaching, decating, fulling, shrinking, mercerizing, or similar...

  12. Under Control

    PubMed Central

    Payne, John

    1971-01-01

    The new film of David Mercer's Family life poses some hard questions for psychiatry to answer and puts the Laingian case for 'schizophrenia' being an illness created within the family unit. PMID:27670980

  13. Boundary conditions for gas flow problems from anisotropic scattering kernels

    NASA Astrophysics Data System (ADS)

    To, Quy-Dong; Vu, Van-Huyen; Lauriat, Guy; Léonard, Céline

    2015-10-01

    The paper presents an interface model for gas flowing through a channel constituted of anisotropic wall surfaces. Using anisotropic scattering kernels and Chapman Enskog phase density, the boundary conditions (BCs) for velocity, temperature, and discontinuities including velocity slip and temperature jump at the wall are obtained. Two scattering kernels, Dadzie and Méolans (DM) kernel, and generalized anisotropic Cercignani-Lampis (ACL) are examined in the present paper, yielding simple BCs at the wall fluid interface. With these two kernels, we rigorously recover the analytical expression for orientation dependent slip shown in our previous works [Pham et al., Phys. Rev. E 86, 051201 (2012) and To et al., J. Heat Transfer 137, 091002 (2015)] which is in good agreement with molecular dynamics simulation results. More important, our models include both thermal transpiration effect and new equations for the temperature jump. While the same expression depending on the two tangential accommodation coefficients is obtained for slip velocity, the DM and ACL temperature equations are significantly different. The derived BC equations associated with these two kernels are of interest for the gas simulations since they are able to capture the direction dependent slip behavior of anisotropic interfaces.

  14. Three-Dimensional Sensitivity Kernels of Z/H Amplitude Ratios of Surface and Body Waves

    NASA Astrophysics Data System (ADS)

    Bao, X.; Shen, Y.

    2017-12-01

    The ellipticity of Rayleigh wave particle motion, or Z/H amplitude ratio, has received increasing attention in inversion for shallow Earth structures. Previous studies of the Z/H ratio assumed one-dimensional (1D) velocity structures beneath the receiver, ignoring the effects of three-dimensional (3D) heterogeneities on wave amplitudes. This simplification may introduce bias in the resulting models. Here we present 3D sensitivity kernels of the Z/H ratio to Vs, Vp, and density perturbations, based on finite-difference modeling of wave propagation in 3D structures and the scattering-integral method. Our full-wave approach overcomes two main issues in previous studies of Rayleigh wave ellipticity: (1) the finite-frequency effects of wave propagation in 3D Earth structures, and (2) isolation of the fundamental mode Rayleigh waves from Rayleigh wave overtones and converted Love waves. In contrast to the 1D depth sensitivity kernels in previous studies, our 3D sensitivity kernels exhibit patterns that vary with azimuths and distances to the receiver. The laterally-summed 3D sensitivity kernels and 1D depth sensitivity kernels, based on the same homogeneous reference model, are nearly identical with small differences that are attributable to the single period of the 1D kernels and a finite period range of the 3D kernels. We further verify the 3D sensitivity kernels by comparing the predictions from the kernels with the measurements from numerical simulations of wave propagation for models with various small-scale perturbations. We also calculate and verify the amplitude kernels for P waves. This study shows that both Rayleigh and body wave Z/H ratios provide vertical and lateral constraints on the structure near the receiver. With seismic arrays, the 3D kernels afford a powerful tool to use the Z/H ratios to obtain accurate and high-resolution Earth models.

  15. 7 CFR 225.19 - Regional office addresses.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ..., District of Columbia, Maryland, New Jersey, Pennsylvania, Puerto Rico, Virginia, Virgin Islands, and West Virginia: Mid-Atlantic Regional Office, FNS, U.S. Department of Agriculture, Mercer Corporate Park, 300...

  16. Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng58 × SK maize population.

    PubMed

    Raihan, Mohammad Sharif; Liu, Jie; Huang, Juan; Guo, Huan; Pan, Qingchun; Yan, Jianbing

    2016-08-01

    Sixteen major QTLs regulating maize kernel traits were mapped in multiple environments and one of them, qKW - 9.2 , was restricted to 630 Kb, harboring 28 putative gene models. To elucidate the genetic basis of kernel traits, a quantitative trait locus (QTL) analysis was conducted in a maize recombinant inbred line population derived from a cross between two diverse parents Zheng58 and SK, evaluated across eight environments. Construction of a high-density linkage map was based on 13,703 single-nucleotide polymorphism markers, covering 1860.9 cM of the whole genome. In total, 18, 26, 23, and 19 QTLs for kernel length, width, thickness, and 100-kernel weight, respectively, were detected on the basis of a single-environment analysis, and each QTL explained 3.2-23.7 % of the phenotypic variance. Sixteen major QTLs, which could explain greater than 10 % of the phenotypic variation, were mapped in multiple environments, implying that kernel traits might be controlled by many minor and multiple major QTLs. The major QTL qKW-9.2 with physical confidence interval of 1.68 Mbp, affecting kernel width, was then selected for fine mapping using heterogeneous inbred families. At final, the location of the underlying gene was narrowed down to 630 Kb, harboring 28 putative candidate-gene models. This information will enhance molecular breeding for kernel traits and simultaneously assist the gene cloning underlying this QTL, helping to reveal the genetic basis of kernel development in maize.

  17. Mapping and validation of major quantitative trait loci for kernel length in wild barley (Hordeum vulgare ssp. spontaneum).

    PubMed

    Zhou, Hong; Liu, Shihang; Liu, Yujiao; Liu, Yaxi; You, Jing; Deng, Mei; Ma, Jian; Chen, Guangdeng; Wei, Yuming; Liu, Chunji; Zheng, Youliang

    2016-09-13

    Kernel length is an important target trait in barley (Hordeum vulgare L.) breeding programs. However, the number of known quantitative trait loci (QTLs) controlling kernel length is limited. In the present study, we aimed to identify major QTLs for kernel length, as well as putative candidate genes that might influence kernel length in wild barley. A recombinant inbred line (RIL) population derived from the barley cultivar Baudin (H. vulgare ssp. vulgare) and the long-kernel wild barley genotype Awcs276 (H.vulgare ssp. spontaneum) was evaluated at one location over three years. A high-density genetic linkage map was constructed using 1,832 genome-wide diversity array technology (DArT) markers, spanning a total of 927.07 cM with an average interval of approximately 0.49 cM. Two major QTLs for kernel length, LEN-3H and LEN-4H, were detected across environments and further validated in a second RIL population derived from Fleet (H. vulgare ssp. vulgare) and Awcs276. In addition, a systematic search of public databases identified four candidate genes and four categories of proteins related to LEN-3H and LEN-4H. This study establishes a fundamental research platform for genomic studies and marker-assisted selection, since LEN-3H and LEN-4H could be used for accelerating progress in barley breeding programs that aim to improve kernel length.

  18. Sensitivity Kernels for the Cross-Convolution Measure: Eliminate the Source in Waveform Tomography

    NASA Astrophysics Data System (ADS)

    Menke, W. H.

    2017-12-01

    We use the adjoint method to derive sensitivity kernels for the cross-convolution measure, a goodness-of-fit criterion that is applicable to seismic data containing closely-spaced multiple arrivals, such as reverberating compressional waves and split shear waves. In addition to a general formulation, specific expressions for sensitivity with respect to density, Lamé parameter and shear modulus are derived for a isotropic elastic solid. As is typical of adjoint methods, the kernels depend upon an adjoint field, the source of which, in this case, is the reference displacement field, pre-multiplied by a matrix of cross-correlations of components of the observed field. We use a numerical simulation to evaluate the resolving power of a topographic inversion that employs the cross-convolution measure. The estimated resolving kernel shows is point-like, indicating that the cross-convolution measure will perform well in waveform tomography settings.

  19. Analysis of Drude model using fractional derivatives without singular kernels

    NASA Astrophysics Data System (ADS)

    Jiménez, Leonardo Martínez; García, J. Juan Rosales; Contreras, Abraham Ortega; Baleanu, Dumitru

    2017-11-01

    We report study exploring the fractional Drude model in the time domain, using fractional derivatives without singular kernels, Caputo-Fabrizio (CF), and fractional derivatives with a stretched Mittag-Leffler function. It is shown that the velocity and current density of electrons moving through a metal depend on both the time and the fractional order 0 < γ ≤ 1. Due to non-singular fractional kernels, it is possible to consider complete memory effects in the model, which appear neither in the ordinary model, nor in the fractional Drude model with Caputo fractional derivative. A comparison is also made between these two representations of the fractional derivatives, resulting a considered difference when γ < 0.8.

  20. [Spatial analysis of road traffic accidents with fatalities in Spain, 2008-2011].

    PubMed

    Gómez-Barroso, Diana; López-Cuadrado, Teresa; Llácer, Alicia; Palmera Suárez, Rocío; Fernández-Cuenca, Rafael

    2015-09-01

    To estimate the areas of greatest density of road traffic accidents with fatalities at 24 hours per km(2)/year in Spain from 2008 to 2011, using a geographic information system. Accidents were geocodified using the road and kilometer points where they occurred. The average nearest neighbor was calculated to detect possible clusters and to obtain the bandwidth for kernel density estimation. A total of 4775 accidents were analyzed, of which 73.3% occurred on conventional roads. The estimated average distance between accidents was 1,242 meters, and the average expected distance was 10,738 meters. The nearest neighbor index was 0.11, indicating that there were aggregations of accidents in space. A map showing the kernel density was obtained with a resolution of 1 km(2), which identified the areas of highest density. This methodology allowed a better approximation to locating accident risks by taking into account kilometer points. The map shows areas where there was a greater density of accidents. This could be an advantage in decision-making by the relevant authorities. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

  1. The construction of a two-dimensional reproducing kernel function and its application in a biomedical model.

    PubMed

    Guo, Qi; Shen, Shu-Ting

    2016-04-29

    There are two major classes of cardiac tissue models: the ionic model and the FitzHugh-Nagumo model. During computer simulation, each model entails solving a system of complex ordinary differential equations and a partial differential equation with non-flux boundary conditions. The reproducing kernel method possesses significant applications in solving partial differential equations. The derivative of the reproducing kernel function is a wavelet function, which has local properties and sensitivities to singularity. Therefore, study on the application of reproducing kernel would be advantageous. Applying new mathematical theory to the numerical solution of the ventricular muscle model so as to improve its precision in comparison with other methods at present. A two-dimensional reproducing kernel function inspace is constructed and applied in computing the solution of two-dimensional cardiac tissue model by means of the difference method through time and the reproducing kernel method through space. Compared with other methods, this method holds several advantages such as high accuracy in computing solutions, insensitivity to different time steps and a slow propagation speed of error. It is suitable for disorderly scattered node systems without meshing, and can arbitrarily change the location and density of the solution on different time layers. The reproducing kernel method has higher solution accuracy and stability in the solutions of the two-dimensional cardiac tissue model.

  2. Zika virus disease, microcephaly and Guillain-Barré syndrome in Colombia: epidemiological situation during 21 months of the Zika virus outbreak, 2015-2017.

    PubMed

    Méndez, Nelson; Oviedo-Pastrana, Misael; Mattar, Salim; Caicedo-Castro, Isaac; Arrieta, German

    2017-01-01

    The Zika virus disease (ZVD) has had a huge impact on public health in Colombia for the numbers of people affected and the presentation of Guillain-Barre syndrome (GBS) and microcephaly cases associated to ZVD. A retrospective descriptive study was carried out, we analyze the epidemiological situation of ZVD and its association with microcephaly and GBS during a 21-month period, from October 2015 to June 2017. The variables studied were: (i) ZVD cases, (ii) ZVD cases in pregnant women, (iii) laboratory-confirmed ZVD in pregnant women, (iv) ZVD cases associated with microcephaly, (v) laboratory-confirmed ZVD associated with microcephaly, and (vi) ZVD associated to GBS cases. Average number of cases, attack rates (AR) and proportions were also calculated. The studied variables were plotted by epidemiological weeks and months. The distribution of ZVD cases in Colombia was mapped across the time using Kernel density estimator and QGIS software; we adopted Kernel Ridge Regression (KRR) and the Gaussian Kernel to estimate the number of Guillain Barre cases given the number of ZVD cases. One hundred eight thousand eighty-seven ZVD cases had been reported in Colombia, including 19,963 (18.5%) in pregnant women, 710 (0.66%) associated with microcephaly (AR, 4.87 cases per 10,000 live births) and 453 (0.42%) ZVD associated to GBS cases (AR, 41.9 GBS cases per 10,000 ZVD cases). It appears the cases of GBS increased in parallel with the cases of ZVD, cases of microcephaly appeared 5 months after recognition of the outbreak. The kernel density map shows that throughout the study period, the states most affected by the Zika outbreak in Colombia were mainly San Andrés and Providencia islands, Casanare, Norte de Santander, Arauca and Huila. The KRR shows that there is no proportional relationship between the number of GBS and ZVD cases. During the cross validation, the RMSE achieved for the second order polynomial kernel, the linear kernel, the sigmoid kernel, and the Gaussian kernel are 9.15, 9.2, 10.7, and 7.2 respectively. This study updates the epidemiological analysis of the ZVD situation in Colombia describes the geographical distribution of ZVD and shows the functional relationship between ZVD cases and GBS.

  3. Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale.

    PubMed

    Buck, Christoph; Kneib, Thomas; Tkaczick, Tobias; Konstabel, Kenn; Pigeot, Iris

    2015-12-22

    Built environment studies provide broad evidence that urban characteristics influence physical activity (PA). However, findings are still difficult to compare, due to inconsistent measures assessing urban point characteristics and varying definitions of spatial scale. Both were found to influence the strength of the association between the built environment and PA. We simultaneously evaluated the effect of kernel approaches and network-distances to investigate the association between urban characteristics and physical activity depending on spatial scale and intensity measure. We assessed urban measures of point characteristics such as intersections, public transit stations, and public open spaces in ego-centered network-dependent neighborhoods based on geographical data of one German study region of the IDEFICS study. We calculated point intensities using the simple intensity and kernel approaches based on fixed bandwidths, cross-validated bandwidths including isotropic and anisotropic kernel functions and considering adaptive bandwidths that adjust for residential density. We distinguished six network-distances from 500 m up to 2 km to calculate each intensity measure. A log-gamma regression model was used to investigate the effect of each urban measure on moderate-to-vigorous physical activity (MVPA) of 400 2- to 9.9-year old children who participated in the IDEFICS study. Models were stratified by sex and age groups, i.e. pre-school children (2 to <6 years) and school children (6-9.9 years), and were adjusted for age, body mass index (BMI), education and safety concerns of parents, season and valid weartime of accelerometers. Association between intensity measures and MVPA strongly differed by network-distance, with stronger effects found for larger network-distances. Simple intensity revealed smaller effect estimates and smaller goodness-of-fit compared to kernel approaches. Smallest variation in effect estimates over network-distances was found for kernel intensity measures based on isotropic and anisotropic cross-validated bandwidth selection. We found a strong variation in the association between the built environment and PA of children based on the choice of intensity measure and network-distance. Kernel intensity measures provided stable results over various scales and improved the assessment compared to the simple intensity measure. Considering different spatial scales and kernel intensity methods might reduce methodological limitations in assessing opportunities for PA in the built environment.

  4. Permissible Home Range Estimation (PHRE) in restricted habitats: A new algorithm and an evaluation for sea otters

    USGS Publications Warehouse

    Tarjan, Lily M; Tinker, M. Tim

    2016-01-01

    Parametric and nonparametric kernel methods dominate studies of animal home ranges and space use. Most existing methods are unable to incorporate information about the underlying physical environment, leading to poor performance in excluding areas that are not used. Using radio-telemetry data from sea otters, we developed and evaluated a new algorithm for estimating home ranges (hereafter Permissible Home Range Estimation, or “PHRE”) that reflects habitat suitability. We began by transforming sighting locations into relevant landscape features (for sea otters, coastal position and distance from shore). Then, we generated a bivariate kernel probability density function in landscape space and back-transformed this to geographic space in order to define a permissible home range. Compared to two commonly used home range estimation methods, kernel densities and local convex hulls, PHRE better excluded unused areas and required a smaller sample size. Our PHRE method is applicable to species whose ranges are restricted by complex physical boundaries or environmental gradients and will improve understanding of habitat-use requirements and, ultimately, aid in conservation efforts.

  5. Resummed memory kernels in generalized system-bath master equations

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

    Mavros, Michael G.; Van Voorhis, Troy, E-mail: tvan@mit.edu

    2014-08-07

    Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between themore » two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the “Landau-Zener resummation” of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics.« less

  6. 44. LOCK, ELECTRICAL SYSTEM, HAULAGE ENGINES, ELECTRICAL DETAILS AND LOCATION. ...

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

    44. LOCK, ELECTRICAL SYSTEM, HAULAGE ENGINES, ELECTRICAL DETAILS AND LOCATION. February 1938 - Mississippi River 9-Foot Channel Project, Lock & Dam No. 17, Upper Mississippi River, New Boston, Mercer County, IL

  7. 5. VIEW OF POWER SUPPLY EQUIPMENT SHOWING ELECTRIC MOTER AND ...

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

    5. VIEW OF POWER SUPPLY EQUIPMENT SHOWING ELECTRIC MOTER AND DRIVE & FLYWHEELS WITH BELT TRANSMISSION. ORIGINALLY STEAM DRIVEN - Anchor (Stangl) Pottery Company, 940 New York Avenue, Trenton, Mercer County, NJ

  8. Proceedings of the third workshop on the energy development board of Mercer County, North Dakota

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

    None

    Two earlier workshops concerned with managing growth in Mercer County, North Dakota focused on the activities of the Energy Development Board (EDB) and were held in 1977 and 1978, respectively. This third workshop, Energy Development in Rural Areas - Local Implementation of National Priorities addresses the transferability of the EDB as an organization approach for managing energy-related rapid growth; the potential for developing integrated energy resource conservation/economic plans in rural energy development areas; and Federal policy and initiatives regarding energy-impact assistance. Panel discussions on these subjects were conducted and the comments are presented. The introductory address by Wayne Sanstead, Lt.more » Gov. of North Dakota and the keynote address by Edward Helminski, White House Management Task Force on Energy Shortages, are included.« less

  9. Microwave sensing of moisture content and bulk density in flowing grain

    USDA-ARS?s Scientific Manuscript database

    Moisture content and bulk density were determined from measurement of the dielectric properties of flowing wheat kernels at a single microwave frequency (5.8 GHz). The measuring system consisted of two high-gain microwave patch antennas mounted on opposite sides of rectangular chute and connected to...

  10. Shell cracking strength in almond (Prunus dulcis [Mill.] D.A. Webb.) and its implication in uses as a value-added product.

    PubMed

    Ledbetter, C A

    2008-09-01

    Researchers are currently developing new value-added uses for almond shells, an abundant agricultural by-product. Almond varieties are distinguished by processors as being either hard or soft shelled, but these two broad classes of almond also exhibit varietal diversity in shell morphology and physical characters. By defining more precisely the physical and chemical characteristics of almond shells from different varieties, researchers will better understand which specific shell types are best suited for specific industrial processes. Eight diverse almond accessions were evaluated in two consecutive harvest seasons for nut and kernel weight, kernel percentage and shell cracking strength. Shell bulk density was evaluated in a separate year. Harvest year by almond accession interactions were highly significant (p0.01) for each of the analyzed variables. Significant (p0.01) correlations were noted for average nut weight with kernel weight, kernel percentage and shell cracking strength. A significant (p0.01) negative correlation for shell cracking strength with kernel percentage was noted. In some cases shell cracking strength was independent of the kernel percentage which suggests that either variety compositional differences or shell morphology affect the shell cracking strength. The varietal characterization of almond shell materials will assist in determining the best value-added uses for this abundant agricultural by-product.

  11. New Families of Skewed Higher-Order Kernel Estimators to Solve the BSS/ICA Problem for Multimodal Sources Mixtures.

    PubMed

    Jabbar, Ahmed Najah

    2018-04-13

    This letter suggests two new types of asymmetrical higher-order kernels (HOK) that are generated using the orthogonal polynomials Laguerre (positive or right skew) and Bessel (negative or left skew). These skewed HOK are implemented in the blind source separation/independent component analysis (BSS/ICA) algorithm. The tests for these proposed HOK are accomplished using three scenarios to simulate a real environment using actual sound sources, an environment of mixtures of multimodal fast-changing probability density function (pdf) sources that represent a challenge to the symmetrical HOK, and an environment of an adverse case (near gaussian). The separation is performed by minimizing the mutual information (MI) among the mixed sources. The performance of the skewed kernels is compared to the performance of the standard kernels such as Epanechnikov, bisquare, trisquare, and gaussian and the performance of the symmetrical HOK generated using the polynomials Chebyshev1, Chebyshev2, Gegenbauer, Jacobi, and Legendre to the tenth order. The gaussian HOK are generated using the Hermite polynomial and the Wand and Schucany procedure. The comparison among the 96 kernels is based on the average intersymbol interference ratio (AISIR) and the time needed to complete the separation. In terms of AISIR, the skewed kernels' performance is better than that of the standard kernels and rivals most of the symmetrical kernels' performance. The importance of these new skewed HOK is manifested in the environment of the multimodal pdf mixtures. In such an environment, the skewed HOK come in first place compared with the symmetrical HOK. These new families can substitute for symmetrical HOKs in such applications.

  12. StreamMap: Smooth Dynamic Visualization of High-Density Streaming Points.

    PubMed

    Li, Chenhui; Baciu, George; Han, Yu

    2018-03-01

    Interactive visualization of streaming points for real-time scatterplots and linear blending of correlation patterns is increasingly becoming the dominant mode of visual analytics for both big data and streaming data from active sensors and broadcasting media. To better visualize and interact with inter-stream patterns, it is generally necessary to smooth out gaps or distortions in the streaming data. Previous approaches either animate the points directly or present a sampled static heat-map. We propose a new approach, called StreamMap, to smoothly blend high-density streaming points and create a visual flow that emphasizes the density pattern distributions. In essence, we present three new contributions for the visualization of high-density streaming points. The first contribution is a density-based method called super kernel density estimation that aggregates streaming points using an adaptive kernel to solve the overlapping problem. The second contribution is a robust density morphing algorithm that generates several smooth intermediate frames for a given pair of frames. The third contribution is a trend representation design that can help convey the flow directions of the streaming points. The experimental results on three datasets demonstrate the effectiveness of StreamMap when dynamic visualization and visual analysis of trend patterns on streaming points are required.

  13. Earth Structure, Ice Mass Changes, and the Local Dynamic Geoid

    NASA Astrophysics Data System (ADS)

    Harig, C.; Simons, F. J.

    2014-12-01

    Spherical Slepian localization functions are a useful method for studying regional mass changes observed by satellite gravimetry. By projecting data onto a sparse basis set, the local field can be estimated more easily than with the full spherical harmonic basis. We have used this method previously to estimate the ice mass change in Greenland from GRACE data, and it can also be applied to other planetary problems such as global magnetic fields. Earth's static geoid, in contrast to the time-variable field, is in large part related to the internal density and rheological structure of the Earth. Past studies have used dynamic geoid kernels to relate this density structure and the internal deformation it induces to the surface geopotential at large scales. These now classical studies of the eighties and nineties were able to estimate the mantle's radial rheological profile, placing constraints on the ratio between upper and lower mantle viscosity. By combining these two methods, spherical Slepian localization and dynamic geoid kernels, we have created local dynamic geoid kernels which are sensitive only to density variations within an area of interest. With these kernels we can estimate the approximate local radial rheological structure that best explains the locally observed geoid on a regional basis. First-order differences of the regional mantle viscosity structure are accessible to this technique. In this contribution we present our latest, as yet unpublished results on the geographical and temporal pattern of ice mass changes in Antarctica over the past decade, and we introduce a new approach to extract regional information about the internal structure of the Earth from the static global gravity field. Both sets of results are linked in terms of the relevant physics, but also in being developed from the marriage of Slepian functions and geoid kernels. We make predictions on the utility of our approach to derive fully three-dimensional rheological Earth models, to be used for corrections for glacio-isostatic adjustment, as necessary for the interpretation of time-variable gravity observations in terms of ice sheet mass-balance studies.

  14. 18. AERIAL VIEW OF PRISON COMPLEX, CIRCA 1930s Photographer unknown; ...

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

    18. AERIAL VIEW OF PRISON COMPLEX, CIRCA 1930s Photographer unknown; National Archives and Records Administration photograph No. 18-AN-31716. - New Jersey State Prison, Second & Federal Streets, Trenton, Mercer County, NJ

  15. Seismic Imaging of VTI, HTI and TTI based on Adjoint Methods

    NASA Astrophysics Data System (ADS)

    Rusmanugroho, H.; Tromp, J.

    2014-12-01

    Recent studies show that isotropic seismic imaging based on adjoint method reduces low-frequency artifact caused by diving waves, which commonly occur in two-wave wave-equation migration, such as Reverse Time Migration (RTM). Here, we derive new expressions of sensitivity kernels for Vertical Transverse Isotropy (VTI) using the Thomsen parameters (ɛ, δ, γ) plus the P-, and S-wave speeds (α, β) as well as via the Chen & Tromp (GJI 2005) parameters (A, C, N, L, F). For Horizontal Transverse Isotropy (HTI), these parameters depend on an azimuthal angle φ, where the tilt angle θ is equivalent to 90°, and for Tilted Transverse Isotropy (TTI), these parameters depend on both the azimuth and tilt angles. We calculate sensitivity kernels for each of these two approaches. Individual kernels ("images") are numerically constructed based on the interaction between the regular and adjoint wavefields in smoothed models which are in practice estimated through Full-Waveform Inversion (FWI). The final image is obtained as a result of summing all shots, which are well distributed to sample the target model properly. The impedance kernel, which is a sum of sensitivity kernels of density and the Thomsen or Chen & Tromp parameters, looks crisp and promising for seismic imaging. The other kernels suffer from low-frequency artifacts, similar to traditional seismic imaging conditions. However, all sensitivity kernels are important for estimating the gradient of the misfit function, which, in combination with a standard gradient-based inversion algorithm, is used to minimize the objective function in FWI.

  16. Influence of moisture content on physical properties of minor millets.

    PubMed

    Balasubramanian, S; Viswanathan, R

    2010-06-01

    Physical properties including 1000 kernel weight, bulk density, true density, porosity, angle of repose, coefficient of static friction, coefficient of internal friction and grain hardness were determined for foxtail millet, little millet, kodo millet, common millet, barnyard millet and finger millet in the moisture content range of 11.1 to 25% db. Thousand kernel weight increased from 2.3 to 6.1 g and angle of repose increased from 25.0 to 38.2°. Bulk density decreased from 868.1 to 477.1 kg/m(3) and true density from 1988.7 to 884.4 kg/m(3) for all minor millets when observed in the moisture range of 11.1 to 25%. Porosity decreased from 63.7 to 32.5%. Coefficient of static friction of minor millets against mild steel surface increased from 0.253 to 0.728 and coefficient of internal friction was in the range of 1.217 and 1.964 in the moisture range studied. Grain hardness decreased from 30.7 to 12.4 for all minor millets when moisture content was increased from 11.1 to 25% db.

  17. Carbothermic Synthesis of ~820- m UN Kernels. Investigation of Process Variables

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

    Lindemer, Terrence; Silva, Chinthaka M; Henry, Jr, John James

    2015-06-01

    This report details the continued investigation of process variables involved in converting sol-gel-derived, urainia-carbon microspheres to ~820-μm-dia. UN fuel kernels in flow-through, vertical refractory-metal crucibles at temperatures up to 2123 K. Experiments included calcining of air-dried UO 3-H 2O-C microspheres in Ar and H 2-containing gases, conversion of the resulting UO 2-C kernels to dense UO 2:2UC in the same gases and vacuum, and its conversion in N 2 to in UC 1-xN x. The thermodynamics of the relevant reactions were applied extensively to interpret and control the process variables. Producing the precursor UO 2:2UC kernel of ~96% theoretical densitymore » was required, but its subsequent conversion to UC 1-xN x at 2123 K was not accompanied by sintering and resulted in ~83-86% of theoretical density. Decreasing the UC 1-xN x kernel carbide component via HCN evolution was shown to be quantitatively consistent with present and past experiments and the only useful application of H2 in the entire process.« less

  18. Rockfaced, coursed ashlar wing wall on the southwest corner of ...

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

    Rock-faced, coursed ashlar wing wall on the southwest corner of the bridge, facing west. - Oakland Avenue Viaduct, Oakland Avenue spanning U.S. Route 62 (State Route 2302) & Pine Run, Sharon, Mercer County, PA

  19. Exploring crystalline-structural variations of cellulose during alkaline pretreatment for enhanced enzymatic hydrolysis.

    PubMed

    Ling, Zhe; Chen, Sheng; Zhang, Xun; Xu, Feng

    2017-01-01

    The study aimed to explore the crystallinity and crystalline structure of alkaline pretreated cellulose. The enzymatic hydrolysis followed by pretreatment was conducted for measuring the efficiency of sugar conversion. For cellulose Iβ dominated samples, alkaline pretreatment (<8wt%) caused increased cellulose crystallinity and depolymerized hemicelluloses, that were superimposed to affect the enzymatic conversion to glucose. Varying crystallite sizes and lattice spacings indicated the separation of cellulose crystals during mercerization (8-12wt% NaOH). Completion of mercerization was proved under higher alkaline concentration (14-18wt% NaOH), leading to distortion of crystalline cellulose to some extent. Cellulose II crystallinity showed a stimulative impact on enzymatic hydrolysis due to the weakened hydrophobic interactions within cellulose chains. The current study may provide innovative explanations for enhanced enzymatic digestibility of alkaline pretreated lignocellulosic materials. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Detonability of turbulent white dwarf plasma: Hydrodynamical models at low densities

    NASA Astrophysics Data System (ADS)

    Fenn, Daniel

    The origins of Type Ia supernovae (SNe Ia) remain an unsolved problem of contemporary astrophysics. Decades of research indicate that these supernovae arise from thermonuclear runaway in the degenerate material of white dwarf stars; however, the mechanism of these explosions is unknown. Also, it is unclear what are the progenitors of these objects. These missing elements are vital components of the initial conditions of supernova explosions, and are essential to understanding these events. A requirement of any successful SN Ia model is that a sufficient portion of the white dwarf plasma must be brought under conditions conducive to explosive burning. Our aim is to identify the conditions required to trigger detonations in turbulent, carbon-rich degenerate plasma at low densities. We study this problem by modeling the hydrodynamic evolution of a turbulent region filled with a carbon/oxygen mixture at a density, temperature, and Mach number characteristic of conditions found in the 0.8+1.2 solar mass (CO0812) model discussed by Fenn et al. (2016). We probe the ignition conditions for different degrees of compressibility in turbulent driving. We assess the probability of successful detonations based on characteristics of the identified ignition kernels, using Eulerian and Lagrangian statistics of turbulent flow. We found that material with very short ignition times is abundant in the case that turbulence is driven compressively. This material forms contiguous structures that persist over many ignition time scales, and that we identify as prospective detonation kernels. Detailed analysis of the kernels revealed that their central regions are densely filled with material characterized by short ignition times and contain the minimum mass required for self-sustained detonations to form. It is conceivable that ignition kernels will be formed for lower compressibility in the turbulent driving. However, we found no detonation kernels in models driven 87.5 percent compressively. We indirectly confirmed the existence of the lower limit of the degree of compressibility of the turbulent drive for the formation of detonation kernels by analyzing simulation results of the He0609 model of Fenn et al. (2016), which produces a detonation in a helium-rich boundary layer. We found that the amount of energy in the compressible component of the kinetic energy in this model corresponds to about 96 percent compressibility in the turbulent drive. The fact that no detonation was found in the original CO0812 model for nominally the same problem conditions suggests that models with carbon-rich boundary layers may require higher resolution in order to adequately represent the mass distributions in terms of ignition times.

  1. A density-adaptive SPH method with kernel gradient correction for modeling explosive welding

    NASA Astrophysics Data System (ADS)

    Liu, M. B.; Zhang, Z. L.; Feng, D. L.

    2017-09-01

    Explosive welding involves processes like the detonation of explosive, impact of metal structures and strong fluid-structure interaction, while the whole process of explosive welding has not been well modeled before. In this paper, a novel smoothed particle hydrodynamics (SPH) model is developed to simulate explosive welding. In the SPH model, a kernel gradient correction algorithm is used to achieve better computational accuracy. A density adapting technique which can effectively treat large density ratio is also proposed. The developed SPH model is firstly validated by simulating a benchmark problem of one-dimensional TNT detonation and an impact welding problem. The SPH model is then successfully applied to simulate the whole process of explosive welding. It is demonstrated that the presented SPH method can capture typical physics in explosive welding including explosion wave, welding surface morphology, jet flow and acceleration of the flyer plate. The welding angle obtained from the SPH simulation agrees well with that from a kinematic analysis.

  2. Characteristics of uranium carbonitride microparticles synthesized using different reaction conditions

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

    Silva, Chinthaka M; Lindemer, Terrence; Voit, Stewart L

    2014-11-01

    Three sets of different experimental conditions by changing the cover gases during the sample preparation were tested to synthesize uranium carbonitride (UC1-xNx) microparticles. In the first two sets of experiments using (N2 to N2-4%H2 to Ar) and (Ar to N2 to Ar) environments, single phase UC1-xNx was synthesized. When reducing environments (Ar-4%H2 to N2-4%H2 to Ar-4%H2) were utilized, theoretical densities up to 97% of single phase UC1-xNx kernels were obtained. Physical and chemical characteristics such as density, phase purity, and chemical compositions of the synthesized UC1-xNx materials for the diferent experimental conditions used are provided. In-depth analysis of the microstruturesmore » of UC1-xNx has been carried out and is discussed with the objective of large batch fabrication of high density UC1-xNx kernels.« less

  3. 40 CFR 80.510 - What are the standards and marker requirements for NRLM diesel fuel and ECA marine fuel?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... following areas: (1) Northeast/Mid-Atlantic Area, which includes the following States and counties, through..., Elk, Jefferson, Clarion, Forest, Venango, Mercer, Crawford, Lawrence, Beaver, Washington, and Greene...

  4. Communication gap exacerbates health care crisis.

    PubMed

    Cordero, C E

    1993-03-01

    Mercer-B&H survey shows employers, doctors, insurers, and workers do not understand each other's most basic concerns. For example, respondents disagree on such issues as how to define quality care and whether freedom to choose a doctor is important.

  5. Principles of Systems Biology, No. 29.

    PubMed

    2018-05-23

    This month: in silico labeling of microscopy images (Christiansen/Finkbeiner), single-cell lineage trees and data integration (Rajewsky, Satija), gene expression (Weinberger/Simpson, Tavazoie, Ameres/Zuber), and signalling networks (Mercer/Wollscheid, Fussenegger). Copyright © 2018. Published by Elsevier Inc.

  6. Off-Peak Fare-Free Transit : Mercer County, New Jersey

    DOT National Transportation Integrated Search

    1982-03-01

    The evaluation was designed to explore the effects of the fare elimination on the transit operator, the riding public, the general populace, and the local business community. Evaluation issues were concerned with impacts on ridership volumes, passeng...

  7. VIEW EASTLEFTBUILDING 2 PHYSICAL TESTING HOUSE (1928) RIGHTBUILDING 7 MACHINE ...

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

    VIEW EAST-LEFT-BUILDING 2 PHYSICAL TESTING HOUSE (1928) RIGHT-BUILDING 7 MACHINE SHOP (1901 SECTION) - John A. Roebling's Sons Company & American Steel & Wire Company, South Broad, Clark, Elmer, Mott & Hudson Streets, Trenton, Mercer County, NJ

  8. 4. First floor interior. Camera facing west. Mirrored interior supports ...

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

    4. First floor interior. Camera facing west. Mirrored interior supports mark the former division between 11 and 13 North Broad Street. - 11-15 North Broad Street (Commercial Building), 11-15 North Broad Street, Trenton, Mercer County, NJ

  9. 77 FR 45373 - National Register of Historic Places; Notification of Pending Nominations and Related Actions

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-31

    ..., 12000527 Mercer County Roebling's, John A., Sons Company, Trenton, N.J., Block 3, Bounded by Hamilton Ave... St., Yankton, 12000536 VIRGINIA Arlington County Georgetown Pike, From DC/VA boundary at Chain Bridge...

  10. 10. Historic American Buildings Survey Lester Jones, Photographer August 24, ...

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

    10. Historic American Buildings Survey Lester Jones, Photographer August 24, 1940 INTERESTING ARCHES, SECOND FLOOR - Shaker Centre Family Dwelling House (Third), North side of Village Road, North of Route 68 & State Route 33, Shakertown, Mercer County, KY

  11. Graphical and Numerical Descriptive Analysis: Exploratory Tools Applied to Vietnamese Data

    ERIC Educational Resources Information Center

    Haughton, Dominique; Phong, Nguyen

    2004-01-01

    This case study covers several exploratory data analysis ideas, the histogram and boxplot, kernel density estimates, the recently introduced bagplot--a two-dimensional extension of the boxplot--as well as the violin plot, which combines a boxplot with a density shape plot. We apply these ideas and demonstrate how to interpret the output from these…

  12. Accuracy of lung nodule density on HRCT: analysis by PSF-based image simulation.

    PubMed

    Ohno, Ken; Ohkubo, Masaki; Marasinghe, Janaka C; Murao, Kohei; Matsumoto, Toru; Wada, Shinichi

    2012-11-08

    A computed tomography (CT) image simulation technique based on the point spread function (PSF) was applied to analyze the accuracy of CT-based clinical evaluations of lung nodule density. The PSF of the CT system was measured and used to perform the lung nodule image simulation. Then, the simulated image was resampled at intervals equal to the pixel size and the slice interval found in clinical high-resolution CT (HRCT) images. On those images, the nodule density was measured by placing a region of interest (ROI) commonly used for routine clinical practice, and comparing the measured value with the true value (a known density of object function used in the image simulation). It was quantitatively determined that the measured nodule density depended on the nodule diameter and the image reconstruction parameters (kernel and slice thickness). In addition, the measured density fluctuated, depending on the offset between the nodule center and the image voxel center. This fluctuation was reduced by decreasing the slice interval (i.e., with the use of overlapping reconstruction), leading to a stable density evaluation. Our proposed method of PSF-based image simulation accompanied with resampling enables a quantitative analysis of the accuracy of CT-based evaluations of lung nodule density. These results could potentially reveal clinical misreadings in diagnosis, and lead to more accurate and precise density evaluations. They would also be of value for determining the optimum scan and reconstruction parameters, such as image reconstruction kernels and slice thicknesses/intervals.

  13. Efficient exact-exchange time-dependent density-functional theory methods and their relation to time-dependent Hartree-Fock.

    PubMed

    Hesselmann, Andreas; Görling, Andreas

    2011-01-21

    A recently introduced time-dependent exact-exchange (TDEXX) method, i.e., a response method based on time-dependent density-functional theory that treats the frequency-dependent exchange kernel exactly, is reformulated. In the reformulated version of the TDEXX method electronic excitation energies can be calculated by solving a linear generalized eigenvalue problem while in the original version of the TDEXX method a laborious frequency iteration is required in the calculation of each excitation energy. The lowest eigenvalues of the new TDEXX eigenvalue equation corresponding to the lowest excitation energies can be efficiently obtained by, e.g., a version of the Davidson algorithm appropriate for generalized eigenvalue problems. Alternatively, with the help of a series expansion of the new TDEXX eigenvalue equation, standard eigensolvers for large regular eigenvalue problems, e.g., the standard Davidson algorithm, can be used to efficiently calculate the lowest excitation energies. With the help of the series expansion as well, the relation between the TDEXX method and time-dependent Hartree-Fock is analyzed. Several ways to take into account correlation in addition to the exact treatment of exchange in the TDEXX method are discussed, e.g., a scaling of the Kohn-Sham eigenvalues, the inclusion of (semi)local approximate correlation potentials, or hybrids of the exact-exchange kernel with kernels within the adiabatic local density approximation. The lowest lying excitations of the molecules ethylene, acetaldehyde, and pyridine are considered as examples.

  14. Celebrating Leadership in Public Health and Medicine Friends of the National Library of Medicine (FNLM) | NIH ...

    MedlinePlus

    ... Michael E. DeBakey Medical Librarian Award Rita B. Smith, MLIS, AHIP, Outreach and Education Coordinator, Mercer University Medical Library and LRC Ms. Smith was honored for her outstanding service to the ...

  15. A Modeling and Data Analysis of Laser Beam Propagation in the Maritime Domain

    DTIC Science & Technology

    2015-05-18

    approach to computing pdfs is the Kernel Density Method (Reference [9] has an intro - duction to the method), which we will apply to compute the pdf of our...The project has two parts to it: 1) we present a computational analysis of different probability density function approximation techniques; and 2) we... computational analysis of different probability density function approximation techniques; and 2) we introduce preliminary steps towards developing a

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

    Pavlou, A. T.; Betzler, B. R.; Burke, T. P.

    Uncertainties in the composition and fabrication of fuel compacts for the Fort St. Vrain (FSV) high temperature gas reactor have been studied by performing eigenvalue sensitivity studies that represent the key uncertainties for the FSV neutronic analysis. The uncertainties for the TRISO fuel kernels were addressed by developing a suite of models for an 'average' FSV fuel compact that models the fuel as (1) a mixture of two different TRISO fuel particles representing fissile and fertile kernels, (2) a mixture of four different TRISO fuel particles representing small and large fissile kernels and small and large fertile kernels and (3)more » a stochastic mixture of the four types of fuel particles where every kernel has its diameter sampled from a continuous probability density function. All of the discrete diameter and continuous diameter fuel models were constrained to have the same fuel loadings and packing fractions. For the non-stochastic discrete diameter cases, the MCNP compact model arranged the TRISO fuel particles on a hexagonal honeycomb lattice. This lattice-based fuel compact was compared to a stochastic compact where the locations (and kernel diameters for the continuous diameter cases) of the fuel particles were randomly sampled. Partial core configurations were modeled by stacking compacts into fuel columns containing graphite. The differences in eigenvalues between the lattice-based and stochastic models were small but the runtime of the lattice-based fuel model was roughly 20 times shorter than with the stochastic-based fuel model. (authors)« less

  17. 77 FR 73394 - Proposed Flood Elevation Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-10

    ... and modified elevations, and communities affected for Mercer County, Pennsylvania (All Jurisdictions... determinations of Base (1% annual-chance) Flood Elevations (BFEs) and modified BFEs for communities participating... not be construed to mean that the community must change any existing ordinances that are more...

  18. 78 FR 22222 - Proposed Flood Elevation Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-15

    ... of referenced elevations, effective and modified elevations, and communities affected for Mercer...) and modified BFEs for communities participating in the National Flood Insurance Program (NFIP), in... CFR 60.3, are minimum requirements. They should not be construed to mean that the community must...

  19. Unlocking Minds

    ERIC Educational Resources Information Center

    Greene, Jenny; Knapp, Jill

    2012-01-01

    The Princeton Teaching Initiative at Princeton University is an all-volunteer group formed to teach for-credit college courses in the New Jersey state prison system. The courses are coordinated with the Mercer County Community College (MCCC), which accredits the courses and maintains the students' transcripts. Volunteer professors, postdoctoral…

  20. 16. VIEW OF THE CONCRETE MIXER THAT WAS USED AT ...

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

    16. VIEW OF THE CONCRETE MIXER THAT WAS USED AT THE MERCER MUSEUM AND ON THE INDIAN HOUSE TOWER. - Moravian Pottery & Tile Works, Southwest side of State Route 313 (Swamp Road), Northwest of East Court Street, Doylestown, Bucks County, PA

  1. Genetics Home Reference: 1q21.1 microdeletion

    MedlinePlus

    ... Baralle D, Collins A, Mercer C, Norga K, de Ravel T, Devriendt K, Bongers EM, de Leeuw N, Reardon W, Gimelli S, Bena F, Hennekam ... Lilley C, Armengol L, Spysschaert Y, Verloo P, De Coene A, Goossens L, Mortier G, Speleman F, ...

  2. Genetics Home Reference: 1q21.1 microduplication

    MedlinePlus

    ... Baralle D, Collins A, Mercer C, Norga K, de Ravel T, Devriendt K, Bongers EM, de Leeuw N, Reardon W, Gimelli S, Bena F, Hennekam ... Lilley C, Armengol L, Spysschaert Y, Verloo P, De Coene A, Goossens L, Mortier G, Speleman F, ...

  3. An atomistic fingerprint algorithm for learning ab initio molecular force fields

    NASA Astrophysics Data System (ADS)

    Tang, Yu-Hang; Zhang, Dongkun; Karniadakis, George Em

    2018-01-01

    Molecular fingerprints, i.e., feature vectors describing atomistic neighborhood configurations, is an important abstraction and a key ingredient for data-driven modeling of potential energy surface and interatomic force. In this paper, we present the density-encoded canonically aligned fingerprint algorithm, which is robust and efficient, for fitting per-atom scalar and vector quantities. The fingerprint is essentially a continuous density field formed through the superimposition of smoothing kernels centered on the atoms. Rotational invariance of the fingerprint is achieved by aligning, for each fingerprint instance, the neighboring atoms onto a local canonical coordinate frame computed from a kernel minisum optimization procedure. We show that this approach is superior over principal components analysis-based methods especially when the atomistic neighborhood is sparse and/or contains symmetry. We propose that the "distance" between the density fields be measured using a volume integral of their pointwise difference. This can be efficiently computed using optimal quadrature rules, which only require discrete sampling at a small number of grid points. We also experiment on the choice of weight functions for constructing the density fields and characterize their performance for fitting interatomic potentials. The applicability of the fingerprint is demonstrated through a set of benchmark problems.

  4. Nonparametric Fine Tuning of Mixtures: Application to Non-Life Insurance Claims Distribution Estimation

    NASA Astrophysics Data System (ADS)

    Sardet, Laure; Patilea, Valentin

    When pricing a specific insurance premium, actuary needs to evaluate the claims cost distribution for the warranty. Traditional actuarial methods use parametric specifications to model claims distribution, like lognormal, Weibull and Pareto laws. Mixtures of such distributions allow to improve the flexibility of the parametric approach and seem to be quite well-adapted to capture the skewness, the long tails as well as the unobserved heterogeneity among the claims. In this paper, instead of looking for a finely tuned mixture with many components, we choose a parsimonious mixture modeling, typically a two or three-component mixture. Next, we use the mixture cumulative distribution function (CDF) to transform data into the unit interval where we apply a beta-kernel smoothing procedure. A bandwidth rule adapted to our methodology is proposed. Finally, the beta-kernel density estimate is back-transformed to recover an estimate of the original claims density. The beta-kernel smoothing provides an automatic fine-tuning of the parsimonious mixture and thus avoids inference in more complex mixture models with many parameters. We investigate the empirical performance of the new method in the estimation of the quantiles with simulated nonnegative data and the quantiles of the individual claims distribution in a non-life insurance application.

  5. Correction of scatter in megavoltage cone-beam CT

    NASA Astrophysics Data System (ADS)

    Spies, L.; Ebert, M.; Groh, B. A.; Hesse, B. M.; Bortfeld, T.

    2001-03-01

    The role of scatter in a cone-beam computed tomography system using the therapeutic beam of a medical linear accelerator and a commercial electronic portal imaging device (EPID) is investigated. A scatter correction method is presented which is based on a superposition of Monte Carlo generated scatter kernels. The kernels are adapted to both the spectral response of the EPID and the dimensions of the phantom being scanned. The method is part of a calibration procedure which converts the measured transmission data acquired for each projection angle into water-equivalent thicknesses. Tomographic reconstruction of the projections then yields an estimate of the electron density distribution of the phantom. It is found that scatter produces cupping artefacts in the reconstructed tomograms. Furthermore, reconstructed electron densities deviate greatly (by about 30%) from their expected values. The scatter correction method removes the cupping artefacts and decreases the deviations from 30% down to about 8%.

  6. Urban Transmission of American Cutaneous Leishmaniasis in Argentina: Spatial Analysis Study

    PubMed Central

    Gil, José F.; Nasser, Julio R.; Cajal, Silvana P.; Juarez, Marisa; Acosta, Norma; Cimino, Rubén O.; Diosque, Patricio; Krolewiecki, Alejandro J.

    2010-01-01

    We used kernel density and scan statistics to examine the spatial distribution of cases of pediatric and adult American cutaneous leishmaniasis in an urban disease-endemic area in Salta Province, Argentina. Spatial analysis was used for the whole population and stratified by women > 14 years of age (n = 159), men > 14 years of age (n = 667), and children < 15 years of age (n = 213). Although kernel density for adults encompassed nearly the entire city, distribution in children was most prevalent in the peripheral areas of the city. Scan statistic analysis for adult males, adult females, and children found 11, 2, and 8 clusters, respectively. Clusters for children had the highest odds ratios (P < 0.05) and were located in proximity of plantations and secondary vegetation. The data from this study provide further evidence of the potential urban transmission of American cutaneous leishmaniasis in northern Argentina. PMID:20207869

  7. Basic Science.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    Instructional materials are provided for a course that covers basic concepts of physics and chemistry. Designed for use in a workplace literacy project developed by Mercer County Community College (New Jersey) and its partners, the course describes applications of these concepts to real-life situations, with an emphasis on applications of…

  8. 75 FR 65696 - Ohio Disaster #OH-00025 Declaration of Economic Injury

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-26

    ... Counties: Auglaize, Mercer. Contiguous Counties: Ohio: Allen, Darke, Hardin, Logan, Shelby, Van Wert... SMALL BUSINESS ADMINISTRATION [Disaster Declaration 12359] Ohio Disaster OH-00025 Declaration of... Economic Injury Disaster Loan (EIDL) declaration for the State of Ohio, dated 10/19/2010. Incident: Toxic...

  9. Basic Math I.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    This document offers instructional materials for a 60-hour course on basic math operations involving decimals, fractions, and proportions as applied in the workplace. The course, part of a workplace literacy project developed by Mercer County Community College (New Jersey) and its partners, contains the following: course outline; 17 lesson…

  10. Medical Terminology.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    This document is one of a series of student workbooks developed for workplace skill development courses or workshops by Mercer County Community College (New Jersey) and its partners. Designed to help employees of medical establishments learn medical terminology, this course provides information on basic word structure, body parts, suffixes and…

  11. Flood of July 21, 1975 in Mercer County, New Jersey

    USGS Publications Warehouse

    Stankowski, Stephen J.; Schopp, Robert D.; Velnich, Anthony J.

    1975-01-01

    Intense rainfall during the evening of July 20 and early morning hours of July 21, 1975 caused flooding of unprecedented magnitude in highly urbanized Mercer County, New Jersey. Over 6 inches (152 millimetres) of rainfall was recorded during a 10-hour period at Trenton, the capital of New Jersey. No lives were lost but damages to highways and bridges, to industrial, business, and residential buildings, to farmlands and crops, and to water supply systems were severe. This report illustrates the magnitude of the flood and provides hydrologic data needed for planning and design to control or lessen damages from future floods. It includes discussions of the antecedent conditions and meteorological aspects of the storm; a description of the flood and comparison to previous floods; a summary of flood stages and discharges; a discussion of flood frequency; and photomosaics which show inundated areas. More than 200 high-water marks are described as to location and elevation above mean sea level.

  12. KERNELHR: A program for estimating animal home ranges

    USGS Publications Warehouse

    Seaman, D.E.; Griffith, B.; Powell, R.A.

    1998-01-01

    Kernel methods are state of the art for estimating animal home-range area and utilization distribution (UD). The KERNELHR program was developed to provide researchers and managers a tool to implement this extremely flexible set of methods with many variants. KERNELHR runs interactively or from the command line on any personal computer (PC) running DOS. KERNELHR provides output of fixed and adaptive kernel home-range estimates, as well as density values in a format suitable for in-depth statistical and spatial analyses. An additional package of programs creates contour files for plotting in geographic information systems (GIS) and estimates core areas of ranges.

  13. Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012.

    PubMed

    Carvalho, Silvia; Magalhães, Mônica de Avelar Figueiredo Mafra; Medronho, Roberto de Andrade

    2017-08-17

    Analyze the spatial distribution of classical dengue and severe dengue cases in the city of Rio de Janeiro. Exploratory study, considering cases of classical dengue and severe dengue with laboratory confirmation of the infection in the city of Rio de Janeiro during the years 2011/2012. The georeferencing technique was applied for the cases notified in the Notification Increase Information System in the period of 2011 and 2012. For this process, the fields "street" and "number" were used. The ArcGis10 program's Geocoding tool's automatic process was performed. The spatial analysis was done through the kernel density estimator. Kernel density pointed out hotspots for classic dengue that did not coincide geographically with severe dengue and were in or near favelas. The kernel ratio did not show a notable change in the spatial distribution pattern observed in the kernel density analysis. The georeferencing process showed a loss of 41% of classic dengue registries and 17% of severe dengue registries due to the address in the Notification Increase Information System form. The hotspots near the favelas suggest that the social vulnerability of these localities can be an influencing factor for the occurrence of this aggravation since there is a deficiency of the supply and access to essential goods and services for the population. To reduce this vulnerability, interventions must be related to macroeconomic policies. Analisar a distribuição espacial dos casos de dengue clássico e dengue grave no município do Rio de Janeiro. Estudo exploratório, considerando casos de dengue clássico e de dengue grave com comprovação laboratorial da infecção, ocorridos no município do Rio de Janeiro nos anos de 2011/2012. Foi aplicada a técnica de georreferenciamento dos casos notificados no Sistema de Informação de Agravos de Notificação, no período de 2011 e 2012. Para esse processo, utilizaram-se os campos "logradouro" e "número". Foi realizado o processo automático da ferramenta Geocoding do programa ArcGis10. A análise espacial foi feita a partir do estimador de densidade Kernel. A densidade de Kernel apontou áreas quentes para dengue clássico não coincidente geograficamente a dengue grave, estando localizadas dentro ou próximas de favelas. O cálculo da razão de Kernel não apresentou modificação significativa no padrão de distribuição espacial observados na análise da densidade de Kernel. O processo de georreferenciamento mostrou perda de 41% dos registros de dengue clássico e 17% de dengue grave devido ao endereçamento da ficha do Sistema de Informação de Agravos de Notificação. As áreas quentes próximas às favelas sugerem que a vulnerabilidade social existente nessas localidades pode ser um fator de influência para a ocorrência desse agravo, uma vez que há deficiência da oferta e acesso a bens e serviços essenciais para a população. Para diminuir essa vulnerabilidade, as intervenções devem estar relacionadas a políticas macroeconômicas.

  14. 3D local feature BKD to extract road information from mobile laser scanning point clouds

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang

    2017-08-01

    Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.

  15. Benchmarks for detecting 'breakthroughs' in clinical trials: empirical assessment of the probability of large treatment effects using kernel density estimation.

    PubMed

    Miladinovic, Branko; Kumar, Ambuj; Mhaskar, Rahul; Djulbegovic, Benjamin

    2014-10-21

    To understand how often 'breakthroughs,' that is, treatments that significantly improve health outcomes, can be developed. We applied weighted adaptive kernel density estimation to construct the probability density function for observed treatment effects from five publicly funded cohorts and one privately funded group. 820 trials involving 1064 comparisons and enrolling 331,004 patients were conducted by five publicly funded cooperative groups. 40 cancer trials involving 50 comparisons and enrolling a total of 19,889 patients were conducted by GlaxoSmithKline. We calculated that the probability of detecting treatment with large effects is 10% (5-25%), and that the probability of detecting treatment with very large treatment effects is 2% (0.3-10%). Researchers themselves judged that they discovered a new, breakthrough intervention in 16% of trials. We propose these figures as the benchmarks against which future development of 'breakthrough' treatments should be measured. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  16. On the solution of integral equations with a generalized cauchy kernel

    NASA Technical Reports Server (NTRS)

    Kaya, A. C.; Erdogan, F.

    1986-01-01

    In this paper a certain class of singular integral equations that may arise from the mixed boundary value problems in nonhomogeneous materials is considered. The distinguishing feature of these equations is that in addition to the Cauchy singularity, the kernels contain terms that are singular only at the end points. In the form of the singular integral equations adopted, the density function is a potential or a displacement and consequently the kernel has strong singularities of the form (t-x) sup-2, x sup n-2 (t+x) sup n, (n or = 2, 0x,tb). The complex function theory is used to determine the fundamental function of the problem for the general case and a simple numerical technique is described to solve the integral equation. Two examples from the theory of elasticity are then considered to show the application of the technique.

  17. Thermal Density Functional Theory: Time-Dependent Linear Response and Approximate Functionals from the Fluctuation-Dissipation Theorem

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

    Pribram-Jones, Aurora; Grabowski, Paul E.; Burke, Kieron

    We present that the van Leeuwen proof of linear-response time-dependent density functional theory (TDDFT) is generalized to thermal ensembles. This allows generalization to finite temperatures of the Gross-Kohn relation, the exchange-correlation kernel of TDDFT, and fluctuation dissipation theorem for DFT. Finally, this produces a natural method for generating new thermal exchange-correlation approximations.

  18. Thermal Density Functional Theory: Time-Dependent Linear Response and Approximate Functionals from the Fluctuation-Dissipation Theorem

    DOE PAGES

    Pribram-Jones, Aurora; Grabowski, Paul E.; Burke, Kieron

    2016-06-08

    We present that the van Leeuwen proof of linear-response time-dependent density functional theory (TDDFT) is generalized to thermal ensembles. This allows generalization to finite temperatures of the Gross-Kohn relation, the exchange-correlation kernel of TDDFT, and fluctuation dissipation theorem for DFT. Finally, this produces a natural method for generating new thermal exchange-correlation approximations.

  19. City Life: Rankings (Livability) versus Perceptions (Satisfaction)

    ERIC Educational Resources Information Center

    Okulicz-Kozaryn, Adam

    2013-01-01

    I investigate the relationship between the popular Mercer city ranking (livability) and survey data (satisfactions). Livability aims to capture "objective" quality of life such as infrastructure. Survey items capture "subjective" quality of life such as satisfaction with city. The relationship between objective measures of quality of life and…

  20. VIEW NORTH OF PRESTRESS TRACK CENTERHEMP STORAGE BUILDING 77 (1920) ...

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

    VIEW NORTH OF PRE-STRESS TRACK CENTER-HEMP STORAGE BUILDING 77 (1920) ROPE WAREHOUSE 43 (1941) BEHIND IT STORAGE SHED 44 (1953) IN FRONT - John A. Roebling's Sons Company & American Steel & Wire Company, South Broad, Clark, Elmer, Mott & Hudson Streets, Trenton, Mercer County, NJ

  1. 40 CFR 410.50 - Applicability; description of the knit fabric finishing subcategory.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 28 2010-07-01 2010-07-01 true Applicability; description of the knit fabric finishing subcategory. 410.50 Section 410.50 Protection of Environment ENVIRONMENTAL PROTECTION... operations: Bleaching, mercerizing, dyeing, printing, resin treatment, water proofing, flame proofing, soil...

  2. 40 CFR 81.314 - Illinois.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...: Carroll County X Henry County X Mercer County X Rock Island County X Whiteside County X AQCR 70: Madison... X AQCR 72: Massac County X Alexander County X Johnson County X Pope County X Pulaski County X Union... Unclassifiable/Attainment Johnson County Unclassifiable/Attainment Kane County Unclassifiable/Attainment Kankakee...

  3. 75 FR 11900 - North Dakota; Major Disaster and Related Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-12

    ..., Billings, Bowman, Burke, Dickey, Dunn, Emmons, Golden Valley, Grant, Hettinger, Logan, McIntosh, McKenzie, Mercer, Morton, Mountrail, Oliver, Ransom, Renville, Sioux, Slope, Stark, Steele, and Walsh Counties and the Standing Rock Indian Reservation for Public Assistance. All counties and Tribes within the State...

  4. Work Survival Skills.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    Instructional materials are provided for a course that deals with improving assertiveness and attitude at work. Designed for use in a workplace literacy project, the course, developed by Mercer County Community College (New Jersey) and its partners, is also intended to teach students techniques of dealing with difficult people and effective…

  5. Academic Branch Libraries: Assessment and Collection Development

    ERIC Educational Resources Information Center

    Poole, Julie

    2009-01-01

    An ongoing project at Mercer University's Regional Academic Center Libraries illustrates how utilizing established assessment guidelines, stakeholder input, and a clear understanding of audience and curriculum needs may all be used to optimize a collection. Academic branch libraries often have clear collection development limitations in terms of…

  6. Selection and properties of alternative forming fluids for TRISO fuel kernel production

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

    Baker, M. P.; King, J. C.; Gorman, B. P.

    2013-01-01

    Current Very High Temperature Reactor (VHTR) designs incorporate TRi-structural ISOtropic (TRISO) fuel, which consists of a spherical fissile fuel kernel surrounded by layers of pyrolytic carbon and silicon carbide. An internal sol-gel process forms the fuel kernel using wet chemistry to produce uranium oxyhydroxide gel spheres by dropping a cold precursor solution into a hot column of trichloroethylene (TCE). Over time, gelation byproducts inhibit complete gelation, and the TCE must be purified or discarded. The resulting TCE waste stream contains both radioactive and hazardous materials and is thus considered a mixed hazardous waste. Changing the forming fluid to a non-hazardousmore » alternative could greatly improve the economics of TRISO fuel kernel production. Selection criteria for a replacement forming fluid narrowed a list of ~10,800 chemicals to yield ten potential replacement forming fluids: 1-bromododecane, 1- bromotetradecane, 1-bromoundecane, 1-chlorooctadecane, 1-chlorotetradecane, 1-iododecane, 1-iodododecane, 1-iodohexadecane, 1-iodooctadecane, and squalane. The density, viscosity, and surface tension for each potential replacement forming fluid were measured as a function of temperature between 25 °C and 80 °C. Calculated settling velocities and heat transfer rates give an overall column height approximation. 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane show the greatest promise as replacements, and future tests will verify their ability to form satisfactory fuel kernels.« less

  7. Selection and properties of alternative forming fluids for TRISO fuel kernel production

    NASA Astrophysics Data System (ADS)

    Baker, M. P.; King, J. C.; Gorman, B. P.; Marshall, D. W.

    2013-01-01

    Current Very High Temperature Reactor (VHTR) designs incorporate TRi-structural ISOtropic (TRISO) fuel, which consists of a spherical fissile fuel kernel surrounded by layers of pyrolytic carbon and silicon carbide. An internal sol-gel process forms the fuel kernel using wet chemistry to produce uranium oxyhydroxide gel spheres by dropping a cold precursor solution into a hot column of trichloroethylene (TCE). Over time, gelation byproducts inhibit complete gelation, and the TCE must be purified or discarded. The resulting TCE waste stream contains both radioactive and hazardous materials and is thus considered a mixed hazardous waste. Changing the forming fluid to a non-hazardous alternative could greatly improve the economics of TRISO fuel kernel production. Selection criteria for a replacement forming fluid narrowed a list of ˜10,800 chemicals to yield ten potential replacement forming fluids: 1-bromododecane, 1-bromotetradecane, 1-bromoundecane, 1-chlorooctadecane, 1-chlorotetradecane, 1-iododecane, 1-iodododecane, 1-iodohexadecane, 1-iodooctadecane, and squalane. The density, viscosity, and surface tension for each potential replacement forming fluid were measured as a function of temperature between 25 °C and 80 °C. Calculated settling velocities and heat transfer rates give an overall column height approximation. 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane show the greatest promise as replacements, and future tests will verify their ability to form satisfactory fuel kernels.

  8. Channeling Your Donna Reed Syndrome.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    This document offers materials on stress management used in a workplace literacy project developed by Mercer County Community College (New Jersey) and its partners. The document contains handouts on the following topics: (1) description of learners' typical days and identification of their stress points; (2) what stress is and is not; (3) a…

  9. Extraction and characterization of cellulose nanowhiskers from Mandacaru (Cereus jamacaru DC.) spines

    USDA-ARS?s Scientific Manuscript database

    Cellulose nanowhiskers were extracted from the spines of Mandacaru (Cereus jamacaru DC.) spines, a cactus native to the Caatinga biome of in northeastern Brazil, using sulfuric acid hydrolysis preceeded by mercerization and bleaching. Nanowhisker size decreased from about 400 to 260 nm when extracti...

  10. Postgraduate Research Supervision: Transforming (R)Elations. Eruptions: New Feminism across the Disciplines, Volume 11.

    ERIC Educational Resources Information Center

    Bartlett, Alison, Ed.; Mercer, Gina, Ed.

    This anthology explores the relationships between postgraduate research candidates and their supervisors. Through stories from candidates and supervisors, the collection proposes alternatives to the prevailing models of postgraduate research supervision. The chapters are: (1) "Introduction" (Alison Bartlett and Gina Mercer); (2) "Dirty Work: 'A…

  11. 78 FR 36010 - Illinois Disaster #IL-00042

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-14

    ..., Mason, Mchenry, Mercer, Ogle, Pike, Putnam, Rock Island, Stark, Warren, Woodford. The Interest Rates are... AGENCY: U.S. Small Business Administration. ACTION: Notice. SUMMARY: This is a Notice of the Presidential declaration of a major disaster for Public Assistance Only for the State of Illinois (FEMA- 4116-DR), dated 06...

  12. Exploring biosensor applications with cotton cellulose nanocrystalline protein and peptide conjugates

    USDA-ARS?s Scientific Manuscript database

    Sensor I: Nano-crystalline preparations were produced through acid hydrolysis and mechanical breakage of the cotton fibers from a scoured and bleached cotton fabric and a scoured and bleached, mercerized fabric, which was shown to produce cellulose I (NCI) and cellulose II (NCII) crystals respective...

  13. The Art of Active Listening.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    This document is one of a series of student workbooks developed for workplace skill development courses or workshops by Mercer County Community College (New Jersey) and its partners. Designed to help employees empathize with others' points of view, the course is intended to teach employees to listen effectively, ask the right questions, and give…

  14. 75 FR 39460 - Prevailing Rate Systems; Redefinition of the Chicago, IL; Fort Wayne-Marion, IN; Indianapolis, IN...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-09

    .... Joseph Steuben Wabash White Whitley Ohio: Allen Defiance Fulton Henry Mercer Paulding Putnam Van Wert Williams INDIANAPOLIS Survey Area Indiana: Boone Hamilton Hancock Hendricks Johnson Marion Morgan Shelby... Vermillion Vigo Warren * * * * * OHIO * * * * * Cleveland Survey Area Ohio: Cuyahoga Geauga Lake Medina Area...

  15. Effect of fiber treatments on tensile and thermal properties of starch/ethylene vinyl alcohol copolymers/coir biocomposites

    USDA-ARS?s Scientific Manuscript database

    The effects of different fiber treatments, namely washing with water, alkali treatment (mercerization) and bleaching, on mechanical and thermal properties of starch/EVA/coir biocomposites were evaluated by tensile tests and thermogravimetry (TG), respectively. Additionally, the fiber/matrix interfac...

  16. English Language for the Chemical Plant.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    This document is one of a series of student workbooks developed for workplace skill development courses or workshops by Mercer County Community College (New Jersey) and its partners. Designed for chemical plant employees, the course covers basic English speaking and writing skills needed to communicate effectively at work and outside the…

  17. 76 FR 17967 - Meeting of the Advisory Committee; Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-31

    ... Joint Board examinations in actuarial mathematics, pension law and methodology referred to in 29 U.S.C... closed meeting of the Advisory Committee on Actuarial Examinations. DATES: The meeting will be held on... INFORMATION: Notice is hereby given that the Advisory Committee on Actuarial Examinations will meet at Mercer...

  18. 88. VIEW OF THE CONCRETE MIXER THAT WAS USED AT ...

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

    88. VIEW OF THE CONCRETE MIXER THAT WAS USED AT THE MERCER MUSEUM AND ON THE INDIAN HOUSE TOWER. SAME VIEW AS PA-107-16. - Moravian Pottery & Tile Works, Southwest side of State Route 313 (Swamp Road), Northwest of East Court Street, Doylestown, Bucks County, PA

  19. VIEW WESTBUILDING 23WIRE MILL & PATENTING (c.1853 & c.1900)CENTER BUILDING ...

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

    VIEW WEST-BUILDING 23-WIRE MILL & PATENTING (c.1853 & c.1900)-CENTER BUILDING 25- NO 2 WIRE MILL (c.1853) BEHIND 23 TO RIGHT - John A. Roebling's Sons Company & American Steel & Wire Company, South Broad, Clark, Elmer, Mott & Hudson Streets, Trenton, Mercer County, NJ

  20. 75 FR 18408 - Suspension of Community Eligibility

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-12

    ... 330122 March 1, 1976, ......do Do. County. Emerg; May 17, 1977, Reg; April 19, 2010, Susp. [[Page 18410..., 170883 March 24, 1998, ......do Do. Mercer and Rock Island Emerg; October Counties. 18, 2002, Reg; April..., 1976, ......do Do. Merrimack County. Emerg; April 2, 1986, Reg; April 19, 2010, Susp. Boscawen, Town of...

  1. 75 FR 14356 - Suspension of Community Eligibility

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-25

    ... 170587 March 5, 1976, ......do Do. Island County. Emerg; October 15, 1982, Reg; April 5, 2010, Susp..., Susp.. Reynolds, Village of, Rock 170883 March 24, 1998, ......do Do. Island and Mercer Counties. Emerg... Do. County. Emerg; May 5, 1981, Reg; April 5, 2010, Susp.. Chandler, City of, 480326 March 5, 1976...

  2. ARC-2011-ACD11-0012-012

    NASA Image and Video Library

    2011-01-26

    Technology Partnerships awards: Federal Laboratory Consortium Far West Region Award for Outstanding Technology Development for Multi-Aircraft Control System. In particular order are Connie Brasil, Todd Callantine, Al Globus, Jeff Homola, Rich Jacoby, George Lawton, Paul Lee, Matt Mainini, Joey Mercer, Ev Palmer, Tom Prevot, Nancy Smith, Easter Wang, James Wong.

  3. 40 CFR 81.331 - New Jersey.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Area Somerset County (part) Borough of Somerville 2/5/96 Attainment Toms River Area Ocean County (part) City of Toms River 2/5/96 Attainment Trenton Area Mercer County (part) City of Trenton 2/5/96... Ocean County (part) Area outside Toms River AQCR 151 NE PA—Upper Delaware Valley Unclassifiable...

  4. Writing for Manufacturing Personnel.

    ERIC Educational Resources Information Center

    Mercer County Community Coll., Trenton, NJ.

    This document, developed by Mercer County Community College (New Jersey) and its partners, offers lists of topics covered in each day of a 24-day course designed to teach General Motors employees the following skills: document information; write clear directions and instructions; outline and organize thoughts and ideas; write memos and business…

  5. Evaluating and interpreting the chemical relevance of the linear response kernel for atoms II: open shell.

    PubMed

    Boisdenghien, Zino; Fias, Stijn; Van Alsenoy, Christian; De Proft, Frank; Geerlings, Paul

    2014-07-28

    Most of the work done on the linear response kernel χ(r,r') has focussed on its atom-atom condensed form χAB. Our previous work [Boisdenghien et al., J. Chem. Theory Comput., 2013, 9, 1007] was the first effort to truly focus on the non-condensed form of this function for closed (sub)shell atoms in a systematic fashion. In this work, we extend our method to the open shell case. To simplify the plotting of our results, we average our results to a symmetrical quantity χ(r,r'). This allows us to plot the linear response kernel for all elements up to and including argon and to investigate the periodicity throughout the first three rows in the periodic table and in the different representations of χ(r,r'). Within the context of Spin Polarized Conceptual Density Functional Theory, the first two-dimensional plots of spin polarized linear response functions are presented and commented on for some selected cases on the basis of the atomic ground state electronic configurations. Using the relation between the linear response kernel and the polarizability we compare the values of the polarizability tensor calculated using our method to high-level values.

  6. Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions

    PubMed Central

    Ruan, Peiying; Hayashida, Morihiro; Maruyama, Osamu; Akutsu, Tatsuya

    2013-01-01

    Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes. PMID:23776458

  7. Enriched reproducing kernel particle method for fractional advection-diffusion equation

    NASA Astrophysics Data System (ADS)

    Ying, Yuping; Lian, Yanping; Tang, Shaoqiang; Liu, Wing Kam

    2018-06-01

    The reproducing kernel particle method (RKPM) has been efficiently applied to problems with large deformations, high gradients and high modal density. In this paper, it is extended to solve a nonlocal problem modeled by a fractional advection-diffusion equation (FADE), which exhibits a boundary layer with low regularity. We formulate this method on a moving least-square approach. Via the enrichment of fractional-order power functions to the traditional integer-order basis for RKPM, leading terms of the solution to the FADE can be exactly reproduced, which guarantees a good approximation to the boundary layer. Numerical tests are performed to verify the proposed approach.

  8. Maternal and child mortality indicators across 187 countries of the world: converging or diverging.

    PubMed

    Goli, Srinivas; Arokiasamy, Perianayagam

    2014-01-01

    This study reassessed the progress achieved since 1990 in maternal and child mortality indicators to test whether the progress is converging or diverging across countries worldwide. The convergence process is examined using standard parametric and non-parametric econometric models of convergence. The results of absolute convergence estimates reveal that progress in maternal and child mortality indicators is diverging for the entire period of 1990-2010 [maternal mortality ratio (MMR) - β = .00033, p < .574; neonatal mortality rate (NNMR) - β = .04367, p < .000; post-neonatal mortality rate (PNMR) - β = .02677, p < .000; under-five mortality rate (U5MR) - β = .00828, p < .000)]. In the recent period, such divergence is replaced with convergence for MMR but diverged for all the child mortality indicators. The results of Kernel density estimate reveal considerable reduction in divergence of MMR for the recent period; however, the Kernel density distribution plots show more than one 'peak' which indicates the emergence of convergence clubs based on their mortality levels. For child mortality indicators, the Kernel estimates suggest that divergence is in progress across the countries worldwide but tended to converge for countries with low mortality levels. A mere progress in global averages of maternal and child mortality indicators among a global cross-section of countries does not warranty convergence unless there is a considerable reduction in variance, skewness and range of change.

  9. MODELING LEACHING OF VIRUSES BY THE MONTE CARLO METHOD

    EPA Science Inventory

    A predictive screening model was developed for fate and transport
    of viruses in the unsaturated zone. A database of input parameters
    allowed Monte Carlo analysis with the model. The resulting kernel
    densities of predicted attenuation during percolation indicated very ...

  10. SPHYNX: an accurate density-based SPH method for astrophysical applications

    NASA Astrophysics Data System (ADS)

    Cabezón, R. M.; García-Senz, D.; Figueira, J.

    2017-10-01

    Aims: Hydrodynamical instabilities and shocks are ubiquitous in astrophysical scenarios. Therefore, an accurate numerical simulation of these phenomena is mandatory to correctly model and understand many astrophysical events, such as supernovas, stellar collisions, or planetary formation. In this work, we attempt to address many of the problems that a commonly used technique, smoothed particle hydrodynamics (SPH), has when dealing with subsonic hydrodynamical instabilities or shocks. To that aim we built a new SPH code named SPHYNX, that includes many of the recent advances in the SPH technique and some other new ones, which we present here. Methods: SPHYNX is of Newtonian type and grounded in the Euler-Lagrange formulation of the smoothed-particle hydrodynamics technique. Its distinctive features are: the use of an integral approach to estimating the gradients; the use of a flexible family of interpolators called sinc kernels, which suppress pairing instability; and the incorporation of a new type of volume element which provides a better partition of the unity. Unlike other modern formulations, which consider volume elements linked to pressure, our volume element choice relies on density. SPHYNX is, therefore, a density-based SPH code. Results: A novel computational hydrodynamic code oriented to Astrophysical applications is described, discussed, and validated in the following pages. The ensuing code conserves mass, linear and angular momentum, energy, entropy, and preserves kernel normalization even in strong shocks. In our proposal, the estimation of gradients is enhanced using an integral approach. Additionally, we introduce a new family of volume elements which reduce the so-called tensile instability. Both features help to suppress the damp which often prevents the growth of hydrodynamic instabilities in regular SPH codes. Conclusions: On the whole, SPHYNX has passed the verification tests described below. For identical particle setting and initial conditions the results were similar (or better in some particular cases) than those obtained with other SPH schemes such as GADGET-2, PSPH or with the recent density-independent formulation (DISPH) and conservative reproducing kernel (CRKSPH) techniques.

  11. Suspended liquid particle disturbance on laser-induced blast wave and low density distribution

    NASA Astrophysics Data System (ADS)

    Ukai, Takahiro; Zare-Behtash, Hossein; Kontis, Konstantinos

    2017-12-01

    The impurity effect of suspended liquid particles on the laser-induced gas breakdown was experimentally investigated in quiescent gas. The focus of this study is the investigation of the influence of the impurities on the shock wave structure as well as the low density distribution. A 532 nm Nd:YAG laser beam with an 188 mJ/pulse was focused on the chamber filled with suspended liquid particles 0.9 ± 0.63 μm in diameter. Several shock waves are generated by multiple gas breakdowns along the beam path in the breakdown with particles. Four types of shock wave structures can be observed: (1) the dual blast waves with a similar shock radius, (2) the dual blast waves with a large shock radius at the lower breakdown, (3) the dual blast waves with a large shock radius at the upper breakdown, and (4) the triple blast waves. The independent blast waves interact with each other and enhance the shock strength behind the shock front in the lateral direction. The triple blast waves lead to the strongest shock wave in all cases. The shock wave front that propagates toward the opposite laser focal spot impinges on one another, and thereafter a transmitted shock wave (TSW) appears. The TSW interacts with the low density core called a kernel; the kernel then longitudinally expands quickly due to a Richtmyer-Meshkov-like instability. The laser-particle interaction causes an increase in the kernel volume which is approximately five times as large as that in the gas breakdown without particles. In addition, the laser-particle interaction can improve the laser energy efficiency.

  12. Evaluation of Statistical Downscaling Skill at Reproducing Extreme Events

    NASA Astrophysics Data System (ADS)

    McGinnis, S. A.; Tye, M. R.; Nychka, D. W.; Mearns, L. O.

    2015-12-01

    Climate model outputs usually have much coarser spatial resolution than is needed by impacts models. Although higher resolution can be achieved using regional climate models for dynamical downscaling, further downscaling is often required. The final resolution gap is often closed with a combination of spatial interpolation and bias correction, which constitutes a form of statistical downscaling. We use this technique to downscale regional climate model data and evaluate its skill in reproducing extreme events. We downscale output from the North American Regional Climate Change Assessment Program (NARCCAP) dataset from its native 50-km spatial resolution to the 4-km resolution of University of Idaho's METDATA gridded surface meterological dataset, which derives from the PRISM and NLDAS-2 observational datasets. We operate on the major variables used in impacts analysis at a daily timescale: daily minimum and maximum temperature, precipitation, humidity, pressure, solar radiation, and winds. To interpolate the data, we use the patch recovery method from the Earth System Modeling Framework (ESMF) regridding package. We then bias correct the data using Kernel Density Distribution Mapping (KDDM), which has been shown to exhibit superior overall performance across multiple metrics. Finally, we evaluate the skill of this technique in reproducing extreme events by comparing raw and downscaled output with meterological station data in different bioclimatic regions according to the the skill scores defined by Perkins et al in 2013 for evaluation of AR4 climate models. We also investigate techniques for improving bias correction of values in the tails of the distributions. These techniques include binned kernel density estimation, logspline kernel density estimation, and transfer functions constructed by fitting the tails with a generalized pareto distribution.

  13. Spatiotemporal characteristics of elderly population’s traffic accidents in Seoul using space-time cube and space-time kernel density estimation

    PubMed Central

    Cho, Nahye; Son, Serin

    2018-01-01

    The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people’s traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. In addition, we analyzed elderly people’s traffic accidents by dividing cases into those in which the drivers were elderly people and those in which elderly people were victims of traffic accidents, and used the traffic accidents data in Seoul for 2013 for analysis. The main findings were as follows: (1) the hotspots for elderly people’s traffic accidents differed according to whether they were drivers or victims. (2) The hourly analysis showed that the hotspots for elderly drivers’ traffic accidents are in specific areas north of the Han River during the period from morning to afternoon, whereas the hotspots for elderly victims are distributed over a wide area from daytime to evening. (3) Monthly analysis showed that the hotspots are weak during winter and summer, whereas they are strong in the hiking and climbing areas in Seoul during spring and fall. Further, elderly victims’ hotspots are more sporadic than elderly drivers’ hotspots. (4) The analysis for the entire period of 2013 indicates that traffic accidents involving elderly people are increasing in specific areas on the north side of the Han River. We expect the results of this study to aid in reducing the number of traffic accidents involving elderly people in the future. PMID:29768453

  14. Spatiotemporal characteristics of elderly population's traffic accidents in Seoul using space-time cube and space-time kernel density estimation.

    PubMed

    Kang, Youngok; Cho, Nahye; Son, Serin

    2018-01-01

    The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people's traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. In addition, we analyzed elderly people's traffic accidents by dividing cases into those in which the drivers were elderly people and those in which elderly people were victims of traffic accidents, and used the traffic accidents data in Seoul for 2013 for analysis. The main findings were as follows: (1) the hotspots for elderly people's traffic accidents differed according to whether they were drivers or victims. (2) The hourly analysis showed that the hotspots for elderly drivers' traffic accidents are in specific areas north of the Han River during the period from morning to afternoon, whereas the hotspots for elderly victims are distributed over a wide area from daytime to evening. (3) Monthly analysis showed that the hotspots are weak during winter and summer, whereas they are strong in the hiking and climbing areas in Seoul during spring and fall. Further, elderly victims' hotspots are more sporadic than elderly drivers' hotspots. (4) The analysis for the entire period of 2013 indicates that traffic accidents involving elderly people are increasing in specific areas on the north side of the Han River. We expect the results of this study to aid in reducing the number of traffic accidents involving elderly people in the future.

  15. A comparison of explosive cyclone characteristics in recent reanalyses: NCEP CFSR, JRA-55, and ERA-Interim

    NASA Astrophysics Data System (ADS)

    Kita, Y.; Waseda, T.

    2016-12-01

    Explosive cyclones (EXPCs) were investigated in three recent reanalyses. Their tracking methods is diverse among researchers, and additionally reanalysis data they use are various. Reanalysis data are essential as initial conditions to implement a downscale simulation with high accuracy. In this study, characteristics of EXPCs in three recent reanalyses were investigated from several perspectives: track densities, minimum MSLP (Mean Sea Level Pressure), and radius of EXPCs. The tracking method of extratropical cyclones (ECs) is to track local minimum of MSLP. The domain is limited to Eastern Asia and the North Pacific Ocean (lat20°:70°, lon100°:200°), and target period is 2000-2014. Fig.1 shows that the frequencies of EXPCs, which is defined as ECs whose MSLP drops by over 12hPa in 12hours, are greatly different, noting that extracted EXPCs are those whose most deepening phases were located around Japan (lat20°:60°, lon110°:160°). In addition, they are dissimilar to those in a previous EXPCs database (Kawamura et al.) and results in weather map analyses. The differences between each frequency might be caused by MSLP at their centers: there were sometimes small gaps of a few hPa. The minimum MSLP and effective radius were also investigated, but distributions of effective radii of EXPCs did not show significant difference (Fig.2). Thus, the gaps of central MSLP just matter in the differences of their trends. To evaluate the path density of EXPCs, two-dimensional kernel density estimation was conducted. The kernel densities of EXPCs' tracks in three reanalyses seem similar: they accumulated apparently above ocean (not shown). Two-dimensional kernel densities of EXPCs' most deepening points accumulated above Sea of Japan, Kuroshio and Extension. Therefore, it is proved that there are considerable differences in numbers of EXPCs depending on reanalyses, while the general characteristics of EXPCs just have little difference. It is worthwhile to say that careful attention should be paid when researchers investigate an individual EXPC with reanalysis data.

  16. Tobacco Retail Environments and Social Inequalities in Individual-Level Smoking and Cessation Among Scottish Adults.

    PubMed

    Pearce, Jamie; Rind, Esther; Shortt, Niamh; Tisch, Catherine; Mitchell, Richard

    2016-02-01

    Many neighborhood characteristics may constrain or enable smoking. This study investigated whether the neighborhood tobacco retail environment was associated with individual-level smoking and cessation in Scottish adults, and whether inequalities in smoking status were related to tobacco retailing. Tobacco outlet density measures were developed for neighborhoods across Scotland using the September 2012 Scottish Tobacco Retailers Register. The outlet data were cleaned and geocoded (n = 10,161) using a Geographic Information System. Kernel density estimation was used to calculate an outlet density measure for each postcode. The kernel density estimation measures were then appended to data on individuals included in the 2008-2011 Scottish Health Surveys (n = 28,751 adults aged ≥16), via their postcode. Two-level logistic regression models examined whether neighborhood density of tobacco retailing was associated with current smoking status and smoking cessation and whether there were differences in the relationship between household income and smoking status, by tobacco outlet density. After adjustment for individual- and area-level confounders, compared to residents of areas with the lowest outlet densities, those living in areas with the highest outlet densities had a 6% higher chance of being a current smoker, and a 5% lower chance of being an ex-smoker. There was little evidence to suggest that inequalities in either current smoking or cessation were narrower in areas with lower availability of tobacco retailing. The findings suggest that residents of environments with a greater availability of tobacco outlets are more likely to start and/or sustain smoking, and less likely to quit. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. Non-Gaussian probabilistic MEG source localisation based on kernel density estimation☆

    PubMed Central

    Mohseni, Hamid R.; Kringelbach, Morten L.; Woolrich, Mark W.; Baker, Adam; Aziz, Tipu Z.; Probert-Smith, Penny

    2014-01-01

    There is strong evidence to suggest that data recorded from magnetoencephalography (MEG) follows a non-Gaussian distribution. However, existing standard methods for source localisation model the data using only second order statistics, and therefore use the inherent assumption of a Gaussian distribution. In this paper, we present a new general method for non-Gaussian source estimation of stationary signals for localising brain activity from MEG data. By providing a Bayesian formulation for MEG source localisation, we show that the source probability density function (pdf), which is not necessarily Gaussian, can be estimated using multivariate kernel density estimators. In the case of Gaussian data, the solution of the method is equivalent to that of widely used linearly constrained minimum variance (LCMV) beamformer. The method is also extended to handle data with highly correlated sources using the marginal distribution of the estimated joint distribution, which, in the case of Gaussian measurements, corresponds to the null-beamformer. The proposed non-Gaussian source localisation approach is shown to give better spatial estimates than the LCMV beamformer, both in simulations incorporating non-Gaussian signals, and in real MEG measurements of auditory and visual evoked responses, where the highly correlated sources are known to be difficult to estimate. PMID:24055702

  18. 78 FR 26354 - Transcontinental Gas Pipeline Company, LLC; Notice of Intent to Prepare an Environmental Impact...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-05-06

    ... compressor stations located in York County, Pennsylvania and Mercer and Middlesex Counties, New Jersey to... Connector Project would be constructed on lands owned by Transco within existing compressor station sites... proposes to: Add an incremental 6,540 horsepower (hp) of compression at its existing Compressor Station 195...

  19. The Negotiation and Co-Construction of Meaning and Understanding within a Postgraduate Online Learning Community

    ERIC Educational Resources Information Center

    Littleton, Karen; Whitelock, Denise

    2005-01-01

    There is an increasing development of courses and course components taught through teaching and learning dialogues online yet there is little secure knowledge regarding the educational quality of these dialogues. Drawing on contemporary sociocultural research, this paper adapts a well-established analytical framework (see Mercer, 1995) that has…

  20. Willingness-to-pay for an area-wide integrated Pest Managment Program to control the Asian Tiger Mosquito in New Jersey.

    USDA-ARS?s Scientific Manuscript database

    Using contingent valuation, the perceived value of an area-wide, integrated pest management program for the Asian tiger mosquito, Aedes albopictus, implemented in Monmouth and Mercer Counties, New Jersey, was estimated. The residents’ maximum willingness-to-pay (WTP) and payment modality was estimat...

  1. 76 FR 11529 - Gregory Desobry, Ph.D.; Order Requiring Notification of Involvement in NRC-Licensed Activities

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-02

    ... the reported medical events, the VA National Health Physics Program (NHPP) conducted onsite... Radiology in 1989 and subsequent practice in the field of Medical Physics, Mr. Desobry's actions at the... medical physicist, but had been employed at the Capital Health System--Mercer Campus, in Trenton, New...

  2. Topic Models in Information Retrieval

    DTIC Science & Technology

    2007-08-01

    Information Processing Systems, Cambridge, MA, MIT Press, 2004. Brown, P.F., Della Pietra, V.J., deSouza, P.V., Lai, J.C. and Mercer, R.L., Class-based...2003. http://www.wkap.nl/prod/b/1-4020-1216-0. Croft, W.B., Lucia , T.J., Cringean, J., and Willett, P., Retrieving Documents By Plausible Inference

  3. Advanced Learners' Foreign Language-Related Emotions across the Four Skills

    ERIC Educational Resources Information Center

    Piniel, Katalin; Albert, Ágnes

    2018-01-01

    Individual differences researchers have recently begun to investigate the concept of emotions and their role in language learning (MacIntyre, Gregersen, & Mercer, 2016). Our aim is to report on a project exploring English majors' feelings related to their use of foreign languages. Using a qualitative research design, participants were asked to…

  4. 19. RUSSIAN STOVE IN THE INDIAN HOUSE. FIREBOX IS AT ...

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

    19. RUSSIAN STOVE IN THE INDIAN HOUSE. FIREBOX IS AT THE LOWER RIGHT. THE FOOT-POWERED POTTER'S WHEEL IN THE BACKGROUND WAS COLLECTED BY HENRY MERCER, BUT WAS NOT USED IN PRODUCTION. - Moravian Pottery & Tile Works, Southwest side of State Route 313 (Swamp Road), Northwest of East Court Street, Doylestown, Bucks County, PA

  5. 78 FR 44119 - Circle Environmental #1 Superfund Site; Dawson, Terrell County, Georgia; Notice of Settlement

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-23

    ... ENVIRONMENTAL PROTECTION AGENCY [FRL-9837-3; CERCLA-04-2013-3760] Circle Environmental 1 Superfund... settlement with Walter G. Mercer, Jr. concerning the Circle Environmental 1 Superfund Site located in Dawson... methods: Internet: www.epa.gov/region4/superfund/programs/enforcement/enforcement.html U.S. Mail: U.S...

  6. Using Puppets to Provide Opportunities for Dialogue and Scientific Inquiry

    ERIC Educational Resources Information Center

    Liston, Maeve

    2015-01-01

    Talk, peer collaboration and exchanging ideas significantly contribute to a child's conceptual understanding in science (Howe, McWilliam and Cross, 2005). Dialogue helps children to clarify their thinking and to develop their capacity to reason, which are crucial scientific process skills (Mercer et al., 2004). One very effective way of supporting…

  7. 78 FR 20090 - Reorganization of Foreign-Trade Zone 133 Under Alternative Site Framework; Quad-Cities, Iowa...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-03

    ... area of Henderson, Henry, Mercer, Rock Island and Warren Counties, Illinois and Cedar, Clinton, Des Moines, Dubuque, Henry, Jackson, Johnson, Jones, Lee, Louisa, Muscatine, Scott and Washington Counties, Iowa, within and adjacent to the Davenport, Iowa- Moline and Rock Island, Illinois Customs and Border...

  8. English as a Second Language for Automotive Component Parts Line Operators.

    ERIC Educational Resources Information Center

    Lewandowski, Carol

    This document is one of a series of student workbooks developed for workplace skill development courses or workshops by Mercer County Community College (New Jersey) and its partners. Designed to improve the English speaking and reading skills of non-English-speaking automotive component parts line operators, the course covers oral, written,…

  9. Literature Discussion as Positioning: Examining Positions in Dialogic Discussions in a Third-Grade Classroom

    ERIC Educational Resources Information Center

    Wee, Jongsun

    2010-01-01

    The purpose of the study is to examine positions of students and a teacher in dialogic discussion. In this study, dialogic discussion was defined with Bakhtin's (1981) dialogism, Nystrand's (1997) explanation of dialogically organized instruction, and Mercer's (1995) explanation of Exploratory Talk. Studies about literature discussion in…

  10. Automatic vigilance for negative words in lexical decision and naming: comment on Larsen, Mercer, and Balota (2006).

    PubMed

    Estes, Zachary; Adelman, James S

    2008-08-01

    An automatic vigilance hypothesis states that humans preferentially attend to negative stimuli, and this attention to negative valence disrupts the processing of other stimulus properties. Thus, negative words typically elicit slower color naming, word naming, and lexical decisions than neutral or positive words. Larsen, Mercer, and Balota analyzed the stimuli from 32 published studies, and they found that word valence was confounded with several lexical factors known to affect word recognition. Indeed, with these lexical factors covaried out, Larsen et al. found no evidence of automatic vigilance. The authors report a more sensitive analysis of 1011 words. Results revealed a small but reliable valence effect, such that negative words (e.g., "shark") elicit slower lexical decisions and naming than positive words (e.g., "beach"). Moreover, the relation between valence and recognition was categorical rather than linear; the extremity of a word's valence did not affect its recognition. This valence effect was not attributable to word length, frequency, orthographic neighborhood size, contextual diversity, first phoneme, or arousal. Thus, the present analysis provides the most powerful demonstration of automatic vigilance to date.

  11. Segmentation of the Speaker's Face Region with Audiovisual Correlation

    NASA Astrophysics Data System (ADS)

    Liu, Yuyu; Sato, Yoichi

    The ability to find the speaker's face region in a video is useful for various applications. In this work, we develop a novel technique to find this region within different time windows, which is robust against the changes of view, scale, and background. The main thrust of our technique is to integrate audiovisual correlation analysis into a video segmentation framework. We analyze the audiovisual correlation locally by computing quadratic mutual information between our audiovisual features. The computation of quadratic mutual information is based on the probability density functions estimated by kernel density estimation with adaptive kernel bandwidth. The results of this audiovisual correlation analysis are incorporated into graph cut-based video segmentation to resolve a globally optimum extraction of the speaker's face region. The setting of any heuristic threshold in this segmentation is avoided by learning the correlation distributions of speaker and background by expectation maximization. Experimental results demonstrate that our method can detect the speaker's face region accurately and robustly for different views, scales, and backgrounds.

  12. Computational investigation of intense short-wavelength laser interaction with rare gas clusters

    NASA Astrophysics Data System (ADS)

    Bigaouette, Nicolas

    Current Very High Temperature Reactor designs incorporate TRi-structural ISOtropic (TRISO) particle fuel, which consists of a spherical fissile fuel kernel surrounded by layers of pyrolytic carbon and silicon carbide. An internal sol-gel process forms the fuel kernel by dropping a cold precursor solution into a column of hot trichloroethylene (TCE). The temperature difference drives the liquid precursor solution to precipitate the metal solution into gel spheres before reaching the bottom of a production column. Over time, gelation byproducts inhibit complete gelation and the TCE must be purified or discarded. The resulting mixed-waste stream is expensive to dispose of or recycle, and changing the forming fluid to a non-hazardous alternative could greatly improve the economics of kernel production. Selection criteria for a replacement forming fluid narrowed a list of ~10,800 chemicals to yield ten potential replacements. The physical properties of the alternatives were measured as a function of temperature between 25 °C and 80 °C. Calculated terminal velocities and heat transfer rates provided an overall column height approximation. 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane were selected for further testing, and surrogate yttria-stabilized zirconia (YSZ) kernels were produced using these selected fluids. The kernels were characterized for density, geometry, composition, and crystallinity and compared to a control group of kernels produced in silicone oil. Production in 1-bromotetradecane showed positive results, producing dense (93.8 %TD) and spherical (1.03 aspect ratio) kernels, but proper gelation did not occur in the other alternative forming fluids. With many of the YSZ kernels not properly gelling within the length of the column, this project further investigated the heat transfer properties of the forming fluids and precursor solution. A sensitivity study revealed that the heat transfer properties of the precursor solution have the strongest impact on gelation time. A COMSOL heat transfer model estimated an effective thermal diffusivity range for the YSZ precursor solution as 1.13x10 -8 m2/s to 3.35x10-8 m 2/s, which is an order of magnitude smaller than the value used in previous studies. 1-bromotetradecane is recommended for further investigation with the production of uranium-based kernels.

  13. Optimization of soxhlet extraction and physicochemical analysis of crop oil from seed kernel of Feun Kase (Thevetia peruviana)

    NASA Astrophysics Data System (ADS)

    Suwari, Kotta, Herry Z.; Buang, Yohanes

    2017-12-01

    Optimizing the soxhlet extraction of oil from seed kernel of Feun Kase (Thevetia peruviana) for biodiesel production was carried out in this study. The solvent used was petroleum ether and methanol, as well as their combinations. The effect of three factors namely different solvent combinations (polarity), extraction time and extraction temperature were investigated for achieving maximum oil yield. Each experiment was conducted in 250 mL soxhlet apparatus. The physicochemical properties of the oil yield (density, kinematic viscosity, acid value, iodine value, saponification value, and water content) were also analyzed. The optimum conditions were found after 4.5 h with extraction time, extraction temperature at 65 oC and petroleum ether to methanol ratio of 90 : 10 (polarity index 0.6). The oil extract was found to be 51.88 ± 3.18%. These results revealed that the crop oil from seed kernel of Feun Kase (Thevetia peruviana) is a potential feedstock for biodiesel production.

  14. The Feasibility of Palm Kernel Shell as a Replacement for Coarse Aggregate in Lightweight Concrete

    NASA Astrophysics Data System (ADS)

    Itam, Zarina; Beddu, Salmia; Liyana Mohd Kamal, Nur; Ashraful Alam, Md; Issa Ayash, Usama

    2016-03-01

    Implementing sustainable materials into the construction industry is fast becoming a trend nowadays. Palm Kernel Shell is a by-product of Malaysia’s palm oil industry, generating waste as much as 4 million tons per annum. As a means of producing a sustainable, environmental-friendly, and affordable alternative in the lightweight concrete industry, the exploration of the potential of Palm Kernel Shell to be used as an aggregate replacement was conducted which may give a positive impact to the Malaysian construction industry as well as worldwide concrete usage. This research investigates the feasibility of PKS as an aggregate replacement in lightweight concrete in terms of compressive strength, slump test, water absorption, and density. Results indicate that by using PKS for aggregate replacement, it increases the water absorption but decreases the concrete workability and strength. Results however, fall into the range acceptable for lightweight aggregates, hence it can be concluded that there is potential to use PKS as aggregate replacement for lightweight concrete.

  15. Lyman continuum observations of solar flares

    NASA Technical Reports Server (NTRS)

    Machado, M. E.; Noyes, R. W.

    1978-01-01

    A study is made of Lyman continuum observations of solar flares, using data obtained by the EUV spectroheliometer on the Apollo Telescope Mount. It is found that there are two main types of flare regions: an overall 'mean' flare coincident with the H-alpha flare region, and transient Lyman continuum kernels which can be identified with the H-alpha and X-ray kernels observed by other authors. It is found that the ground level hydrogen population in flares is closer to LTE than in the quiet sun and active regions, and that the level of Lyman continuum formation is lowered in the atmosphere from a mass column density .000005 g/sq cm in the quiet sun to .0003 g/sq cm in the mean flare, and to .001 g/sq cm in kernels. From these results the amount of chromospheric material 'evaporated' into the high temperature region is derived, which is found to be approximately 10 to the 15th g, in agreement with observations of X-ray emission measures.

  16. Geoboard and Balance Activities for the Gifted Child.

    ERIC Educational Resources Information Center

    Bondy, Kay W.

    1979-01-01

    The author describes mathematics activities for gifted children which make use of the geoboard and balance. The problem, solutions, and theoretical backing are provided for determining areas of squares, areas of irregular shapes, the weight of popped and unpopped popcorn, kernels, and liquid mass and density. (SBH)

  17. Beyond electronegativity and local hardness: Higher-order equalization criteria for determination of a ground-state electron density.

    PubMed

    Ayers, Paul W; Parr, Robert G

    2008-08-07

    Higher-order global softnesses, local softnesses, and softness kernels are defined along with their hardness inverses. The local hardness equalization principle recently derived by the authors is extended to arbitrary order. The resulting hierarchy of equalization principles indicates that the electronegativity/chemical potential, local hardness, and local hyperhardnesses all are constant when evaluated for the ground-state electron density. The new equalization principles can be used to test whether a trial electron density is an accurate approximation to the true ground-state density and to discover molecules with desired reactive properties, as encapsulated by their chemical reactivity indicators.

  18. Developmental Differences in the Naming of Contextually Non-Categorical Objects

    ERIC Educational Resources Information Center

    Ozcan, Mehmet

    2012-01-01

    This study investigates the naming process of contextually non-categorical objects in children from 3 to 9 plus 13-year-olds. 112 children participated in the study. Children were asked to narrate a story individually while looking at Mercer Mayer's textless, picture book "Frog, where are you?" The narratives were audio recorded and transcribed.…

  19. Species Profiles: Life Histories and Environmental Requirements of Coastal Fishes and Invertebrates (Mid-Atlantic): Weakfish

    DTIC Science & Technology

    1989-08-01

    Linda P. Mercer North Carolina Division of Marine Fisheries Morehead City, NC 28557 Project Officer David Moran U.S. Fish and Wildlife Service National...of the nomenclature, taxonomy, morphology, distribution, life history, population structure and dynamics, and the fishery of the blue crab...AND RECREATIONAL FISHERIES .. ............. ........ ECOLOGICAL ROLE. .... ................... .......... 9 Food habits

  20. National Dam Safety Program. Whitehead Dam (NJ00559), Delaware River Basin, Assunpink Creek, Mercer County, New Jersey. Phase I Inspection Report.

    DTIC Science & Technology

    1980-03-01

    Magothy and Raritan Formations. These marine formations are comprised of alternating beds of clay and sand. Assunpink Creek is near the westerly extent...of the Magothy and Raritan formations and their overall thickness may be as little as twenty five feet. Precambrian bedrock underlies these

  1. VIEW SOUTH FROM HAMILTON AVENUE BUILDING 25 LEFT; BUILDING 32 ...

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

    VIEW SOUTH FROM HAMILTON AVENUE BUILDING 25 LEFT; BUILDING 32 MACHINE SHOP (1890) LEFT CENTER BUILDING 31 RIGGER'S SHOP (1890) CENTER BUILDING 28 BLACKSMITH SHOP (1885) RIGHT CENTER; BUILDING 27 PATTERN SHOP (1853) RIGHT - John A. Roebling's Sons Company & American Steel & Wire Company, South Broad, Clark, Elmer, Mott & Hudson Streets, Trenton, Mercer County, NJ

  2. VIEW NORTH EXTREME LEFTBUILDING 32; MACHINE SHOP (1890) SECOND LEFTBUILDING ...

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

    VIEW NORTH- EXTREME LEFT-BUILDING 32; MACHINE SHOP (1890) SECOND LEFT-BUILDING 31; RIGGER SHOP (1890) CENTER- BUILDING 28; BLACKSMITH SHOP (1885) CENTER RIGHT-BUILDING 27; PATTERN SHOP (C.1853) RIGHT-BUILDING 40; WIRE WAREHOUSE (1915) - John A. Roebling's Sons Company & American Steel & Wire Company, South Broad, Clark, Elmer, Mott & Hudson Streets, Trenton, Mercer County, NJ

  3. Ground Rules for Talk: The Acceptable Face of Prescription

    ERIC Educational Resources Information Center

    Lambirth, Andrew

    2009-01-01

    In this second article on the theory of "ground rules for talk" I extend a debate between myself and Professor Neil Mercer over the introduction of "ground rules" into classrooms. I critique ground rules through the use of sociological theory and argue that advocates of the ground rules perspective need to recognise the ideological nature of their…

  4. Forests and People in the Mid-Atlantic Region

    Treesearch

    Stephanie Fulton; Evan Mercer; M. Patricia Bradley

    2012-01-01

    Human populations in the Mid-Atlantic region over the last 250 years have increased nearly 100-fold, from an estimated few hundred thousand people to over 30 million people (Mercer and Murthy 2000). Increased population growth usually results in the conversion of forestland to nonforest uses, particularly agriculture, pastureland, and urban development. Not only is the...

  5. 77 FR 48959 - Foreign-Trade Zone 133-Quad-Cities, Iowa/Illinois Application for Reorganization Under...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-15

    ... Cities Industrial Center, 200 East 90th Street, Davenport, Iowa; Site 2 (33 acres)--Rock Island Arsenal, 1775 East Street, Rock Island, Illinois; Site 3 (55 acres)--Modern Warehousing, 801 1st Street East..., Mercer, Rock Island and Warren Counties, Illinois as well as Cedar, Clinton, Des Moines, Dubuque, Henry...

  6. Effects of a Computerized Program on Use of the Test-Taking Strategy by Secondary Students with Disabilities

    ERIC Educational Resources Information Center

    Lancaster, Paula E.; Schumaker, Jean B.; Lancaster, Sean J. C.; Deshler, Donald D.

    2009-01-01

    Students with disabilities must meet many testing demands, given the current emphasis on accountability and state competency testing. The purpose of this project was to develop and field test a computerized program to teach the Test-Taking Strategy (Hughes, Schumaker, Deshler, & Mercer, 1988) to secondary-level students with disabilities. The…

  7. Creating and Analyzing the Effectiveness of a Mathematics Placement Policy for New Freshmen

    ERIC Educational Resources Information Center

    Denny, Jeffrey K.; Nelson, David G.; Zhao, Martin Q.

    2012-01-01

    In the mid-1990s, Mercer University's undergraduate schools placed incoming freshmen in their first mathematics course, using only their scores on the mathematics portion of the SAT (SATM). This placement policy was strongly supported by the admissions office because it did not require additional testing of the freshmen in their on-campus summer…

  8. High School/College Collaboration that Promotes High School Success.

    ERIC Educational Resources Information Center

    Conklin, David

    Over the past few years, Mercer County Community College (MCCC) in Trenton, New Jersey, has developed several programs and activities to promote a closer relationship between the college and local junior high and high schools. The programs are built on the premise that well-prepared students are more likely to persist through high school and…

  9. Effectiveness of the Area-wide Pest Management Program to Control Asian Tiger Mosquito in New Jersey: Evidence from a Household Survey

    USDA-ARS?s Scientific Manuscript database

    Households’ behaviors can both mitigate and measure the spread of urban mosquitos. Beginning in 2009, a comprehensive area-wide pest management (AWPM) project to control Aedes albopictus was implemented in 4 areas in Monmouth and Mercer Counties, New Jersey. Including other activities, the project f...

  10. Effectiveness of the area wide pest management program to control asian tiger mosquito in New Jersey: evidence from a household survey

    USDA-ARS?s Scientific Manuscript database

    Households’ behaviors can both mitigate and measure the spread of urban mosquito species. Beginning in 2009, an area-wide pest management (AWPM) project to control Ae. Albopictus was implemented in 6 areas in Monmouth and Mercer counties, NJ. Including other activities, the project focused on increa...

  11. Economic evaluation of an area-wide integrated pest management program to control the Asian tiger mosquito in New Jersey

    USDA-ARS?s Scientific Manuscript database

    Aedes albopictus is the most invasive mosquito in the world, an important disease vector, and a biting nuisance that limits outdoor activities. Area-wide integrated pest management (AW-IPM) is the recommended control strategy. We conducted an economic evaluation of the AW-IPM project in Mercer and ...

  12. Cost-benefit analysis of an area-wide pest management program to control Asian tiger mosquito in New Jersey

    USDA-ARS?s Scientific Manuscript database

    Area-wide pest management (AWPM) is recommended to control urban mosquitoes, such as Aedes albopictus (Asian tiger mosquito), which limit outdoor activities. We conducted a cost-benefit analysis for an AWPM in Mercer and Monmouth counties, New Jersey, as part of a controlled design with matched area...

  13. Does the Effect of Enjoyment Outweigh That of Anxiety in Foreign Language Performance?

    ERIC Educational Resources Information Center

    Dewaele, Jean-Marc; Alfawzan, Mateb

    2018-01-01

    Interest in the effect of positive and negative emotions in foreign language acquisition has soared recently because of the positive psychology movement (Dewaele & MacIntyre, 2014, 2016; MacIntyre, Gregersen & Mercer, 2016). No work so far has been carried out on the differential effect of positive and negative emotions on foreign language…

  14. VIEW EASTLEFTBUILDING 4NO 1 WIRE MILL (1871) RIGHTBUILDING 25NO 2 ...

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

    VIEW EAST-LEFT-BUILDING 4-NO 1 WIRE MILL (1871) RIGHT-BUILDING 25-NO 2 WIRE MILL (c.1853) RIGHT-BUILDING 23 WIRE MILL & PATENTING (1853 & 1900)-BEHIND 25 CENTER-PEDESTRIAN BRIDGE (C.1873) - John A. Roebling's Sons Company & American Steel & Wire Company, South Broad, Clark, Elmer, Mott & Hudson Streets, Trenton, Mercer County, NJ

  15. Estimating peer density effects on oral health for community-based older adults.

    PubMed

    Chakraborty, Bibhas; Widener, Michael J; Mirzaei Salehabadi, Sedigheh; Northridge, Mary E; Kum, Susan S; Jin, Zhu; Kunzel, Carol; Palmer, Harvey D; Metcalf, Sara S

    2017-12-29

    As part of a long-standing line of research regarding how peer density affects health, researchers have sought to understand the multifaceted ways that the density of contemporaries living and interacting in proximity to one another influence social networks and knowledge diffusion, and subsequently health and well-being. This study examined peer density effects on oral health for racial/ethnic minority older adults living in northern Manhattan and the Bronx, New York, NY. Peer age-group density was estimated by smoothing US Census data with 4 kernel bandwidths ranging from 0.25 to 1.50 mile. Logistic regression models were developed using these spatial measures and data from the ElderSmile oral and general health screening program that serves predominantly racial/ethnic minority older adults at community centers in northern Manhattan and the Bronx. The oral health outcomes modeled as dependent variables were ordinal dentition status and binary self-rated oral health. After construction of kernel density surfaces and multiple imputation of missing data, logistic regression analyses were performed to estimate the effects of peer density and other sociodemographic characteristics on the oral health outcomes of dentition status and self-rated oral health. Overall, higher peer density was associated with better oral health for older adults when estimated using smaller bandwidths (0.25 and 0.50 mile). That is, statistically significant relationships (p < 0.01) between peer density and improved dentition status were found when peer density was measured assuming a more local social network. As with dentition status, a positive significant association was found between peer density and fair or better self-rated oral health when peer density was measured assuming a more local social network. This study provides novel evidence that the oral health of community-based older adults is affected by peer density in an urban environment. To the extent that peer density signifies the potential for social interaction and support, the positive significant effects of peer density on improved oral health point to the importance of place in promoting social interaction as a component of healthy aging. Proximity to peers and their knowledge of local resources may facilitate utilization of community-based oral health care.

  16. Nonparametric model validations for hidden Markov models with applications in financial econometrics.

    PubMed

    Zhao, Zhibiao

    2011-06-01

    We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise.

  17. Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers.

    PubMed

    Li, Faji; Wen, Weie; He, Zhonghu; Liu, Jindong; Jin, Hui; Cao, Shuanghe; Geng, Hongwei; Yan, Jun; Zhang, Pingzhi; Wan, Yingxiu; Xia, Xianchun

    2018-06-01

    We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

  18. Performance of fly ash based geopolymer incorporating palm kernel shell for lightweight concrete

    NASA Astrophysics Data System (ADS)

    Razak, Rafiza Abd; Abdullah, Mohd Mustafa Al Bakri; Yahya, Zarina; Jian, Ang Zhi; Nasri, Armia

    2017-09-01

    A concrete which cement is totally replaced by source material such as fly ash and activated by highly alkaline solutions is known as geopolymer concrete. Fly ash is the most common source material for geopolymer because it is a by-product material, so it can get easily from all around the world. An investigation has been carried out to select the most suitable ingredients of geopolymer concrete so that the geopolymer concrete can achieve the desire compressive strength. The samples were prepared to determine the suitable percentage of palm kernel shell used in geopolymer concrete and cured for 7 days in oven. After that, other samples were prepared by using the suitable percentage of palm kernel shell and cured for 3, 14, 21 and 28 days in oven. The control sample consisting of ordinary Portland cement and palm kernel shell and cured for 28 days were prepared too. The NaOH concentration of 12M, ratio Na2SiO3 to NaOH of 2.5, ratio fly ash to alkaline activator solution of 2.0 and ratio water to geopolymer of 0.35 were fixed throughout the research. The density obtained for the samples were 1.78 kg/m3, water absorption of 20.41% and the compressive strength of 14.20 MPa. The compressive strength of geopolymer concrete is still acceptable as lightweight concrete although the compressive strength is lower than OPC concrete. Therefore, the proposed method by using fly ash mixed with 10% of palm kernel shell can be used to design geopolymer concrete.

  19. Kernel machine SNP set analysis provides new insight into the association between obesity and polymorphisms located on the chromosomal 16q.12.2 region: Tehran Lipid and Glucose Study.

    PubMed

    Javanrouh, Niloufar; Daneshpour, Maryam S; Soltanian, Ali Reza; Tapak, Leili

    2018-06-05

    Obesity is a serious health problem that leads to low quality of life and early mortality. To the purpose of prevention and gene therapy for such a worldwide disease, genome wide association study is a powerful tool for finding SNPs associated with increased risk of obesity. To conduct an association analysis, kernel machine regression is a generalized regression method, has an advantage of considering the epistasis effects as well as the correlation between individuals due to unknown factors. In this study, information of the people who participated in Tehran cardio-metabolic genetic study was used. They were genotyped for the chromosomal region, evaluation 986 variations located at 16q12.2; build 38hg. Kernel machine regression and single SNP analysis were used to assess the association between obesity and SNPs genotyped data. We found that associated SNP sets with obesity, were almost in the FTO (P = 0.01), AIKTIP (P = 0.02) and MMP2 (P = 0.02) genes. Moreover, two SNPs, i.e., rs10521296 and rs11647470, showed significant association with obesity using kernel regression (P = 0.02). In conclusion, significant sets were randomly distributed throughout the region with more density around the FTO, AIKTIP and MMP2 genes. Furthermore, two intergenic SNPs showed significant association after using kernel machine regression. Therefore, more studies have to be conducted to assess their functionality or precise mechanism. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Electron correlation in Hooke's law atom in the high-density limit.

    PubMed

    Gill, P M W; O'Neill, D P

    2005-03-01

    Closed-form expressions for the first three terms in the perturbation expansion of the exact energy and Hartree-Fock energy of the lowest singlet and triplet states of the Hooke's law atom are found. These yield elementary formulas for the exact correlation energies (-49.7028 and -5.807 65 mE(h)) of the two states in the high-density limit and lead to a pair of necessary conditions on the exact correlation kernel G(w) in Hartree-Fock-Wigner theory.

  1. Space Use and Movement of a Neotropical Top Predator: The Endangered Jaguar

    PubMed Central

    Stabach, Jared A.; Fleming, Chris H.; Calabrese, Justin M.; De Paula, Rogério C.; Ferraz, Kátia M. P. M.; Kantek, Daniel L. Z.; Miyazaki, Selma S.; Pereira, Thadeu D. C.; Araujo, Gediendson R.; Paviolo, Agustin; De Angelo, Carlos; Di Bitetti, Mario S.; Cruz, Paula; Lima, Fernando; Cullen, Laury; Sana, Denis A.; Ramalho, Emiliano E.; Carvalho, Marina M.; Soares, Fábio H. S.; Zimbres, Barbara; Silva, Marina X.; Moraes, Marcela D. F.; Vogliotti, Alexandre; May, Joares A.; Haberfeld, Mario; Rampim, Lilian; Sartorello, Leonardo; Ribeiro, Milton C.; Leimgruber, Peter

    2016-01-01

    Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kernel density estimator (AKDE), we investigated range residency of forty-four jaguars fit with GPS collars across five biomes in Brazil and Argentina. We assessed home range and movement parameters of range resident animals and compared AKDE estimates with kernel density estimates (KDE). We accounted for differential space use and movement among individuals, sex, region, and habitat quality. Thirty-three (80%) of collared jaguars were range resident. Home range estimates using AKDE were 1.02 to 4.80 times larger than KDE estimates that did not consider autocorrelation. Males exhibited larger home ranges, more directional movement paths, and a trend towards larger distances traveled per day. Jaguars with the largest home ranges occupied the Atlantic Forest, a biome with high levels of deforestation and high human population density. Our results fill a gap in the knowledge of the species’ ecology with an aim towards better conservation of this endangered/critically endangered carnivore—the top predator in the Neotropics. PMID:28030568

  2. An improved numerical method for the kernel density functional estimation of disperse flow

    NASA Astrophysics Data System (ADS)

    Smith, Timothy; Ranjan, Reetesh; Pantano, Carlos

    2014-11-01

    We present an improved numerical method to solve the transport equation for the one-point particle density function (pdf), which can be used to model disperse flows. The transport equation, a hyperbolic partial differential equation (PDE) with a source term, is derived from the Lagrangian equations for a dilute particle system by treating position and velocity as state-space variables. The method approximates the pdf by a discrete mixture of kernel density functions (KDFs) with space and time varying parameters and performs a global Rayleigh-Ritz like least-square minimization on the state-space of velocity. Such an approximation leads to a hyperbolic system of PDEs for the KDF parameters that cannot be written completely in conservation form. This system is solved using a numerical method that is path-consistent, according to the theory of non-conservative hyperbolic equations. The resulting formulation is a Roe-like update that utilizes the local eigensystem information of the linearized system of PDEs. We will present the formulation of the base method, its higher-order extension and further regularization to demonstrate that the method can predict statistics of disperse flows in an accurate, consistent and efficient manner. This project was funded by NSF Project NSF-DMS 1318161.

  3. Space Use and Movement of a Neotropical Top Predator: The Endangered Jaguar.

    PubMed

    Morato, Ronaldo G; Stabach, Jared A; Fleming, Chris H; Calabrese, Justin M; De Paula, Rogério C; Ferraz, Kátia M P M; Kantek, Daniel L Z; Miyazaki, Selma S; Pereira, Thadeu D C; Araujo, Gediendson R; Paviolo, Agustin; De Angelo, Carlos; Di Bitetti, Mario S; Cruz, Paula; Lima, Fernando; Cullen, Laury; Sana, Denis A; Ramalho, Emiliano E; Carvalho, Marina M; Soares, Fábio H S; Zimbres, Barbara; Silva, Marina X; Moraes, Marcela D F; Vogliotti, Alexandre; May, Joares A; Haberfeld, Mario; Rampim, Lilian; Sartorello, Leonardo; Ribeiro, Milton C; Leimgruber, Peter

    2016-01-01

    Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kernel density estimator (AKDE), we investigated range residency of forty-four jaguars fit with GPS collars across five biomes in Brazil and Argentina. We assessed home range and movement parameters of range resident animals and compared AKDE estimates with kernel density estimates (KDE). We accounted for differential space use and movement among individuals, sex, region, and habitat quality. Thirty-three (80%) of collared jaguars were range resident. Home range estimates using AKDE were 1.02 to 4.80 times larger than KDE estimates that did not consider autocorrelation. Males exhibited larger home ranges, more directional movement paths, and a trend towards larger distances traveled per day. Jaguars with the largest home ranges occupied the Atlantic Forest, a biome with high levels of deforestation and high human population density. Our results fill a gap in the knowledge of the species' ecology with an aim towards better conservation of this endangered/critically endangered carnivore-the top predator in the Neotropics.

  4. An alternative covariance estimator to investigate genetic heterogeneity in populations.

    PubMed

    Heslot, Nicolas; Jannink, Jean-Luc

    2015-11-26

    For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative covariance estimator can be used to gain insight into trait-specific genetic heterogeneity by identifying relevant sub-populations that lack genetic correlation between them. Genetic correlation can be 0 between identified sub-populations by performing automatic selection of relevant sets of individuals to be included in the training population. It may also increase statistical power in GWAS.

  5. Evaluation of human exposure to single electromagnetic pulses of arbitrary shape.

    PubMed

    Jelínek, Lukás; Pekárek, Ludĕk

    2006-03-01

    Transient current density J(t) induced in the body of a person exposed to a single magnetic pulse of arbitrary shape or to a magnetic jump is filtered by a convolution integral containing in its kernel the frequency and phase dependence of the basic limit value adopted in a way similar to that used for reference values in the International Commission on Non-lonising Radiation Protection statement. From the obtained time-dependent dimensionless impact function W(J)(t) can immediately be determined whether the exposure to the analysed single event complies with the basic limit. For very slowly varying field, the integral kernel is extended to include the softened ICNIRP basic limit for frequencies lower than 4 Hz.

  6. A comparison of spatial analysis methods for the construction of topographic maps of retinal cell density.

    PubMed

    Garza-Gisholt, Eduardo; Hemmi, Jan M; Hart, Nathan S; Collin, Shaun P

    2014-01-01

    Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed 'by eye'. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation 'respects' the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the 'noise' caused by artefacts and permits a clearer representation of the dominant, 'real' distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome.

  7. 77 FR 1674 - Tennessee Gas Pipeline Company, L.L.C.; Notice of Intent To Prepare an Environmental Assessment...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-11

    ... stations to provide bi-directional natural gas flow: a. Station 219, in Mercer County; b. Station 303, in Venango County; c. Station 310, in McKean County; and d. Station 313, in Potter County. The general... yards, compressor stations, and access roads). Our EA for this project will document our findings on the...

  8. Species Profiles: Life Histories and Environmental Requirements of Coastal Fishes and Invertebrates (South Atlantic). Black Sea Bass

    DTIC Science & Technology

    1989-07-01

    Environmental Requirements of Coastal Fishes and Invertebrates (South Atlantic) BLACK SEA BASS BY Linda P. Mercer North Carolina Division of Marine Fisheries ...CHARACTERISTICS. .. ....... ....... ...... ..... 6 FISHERY .. .. ....... ...... ....... ....... ..... 7 Commnercial Harvest...Manooch, III, Gene Huntsman, and R.O. Parker, Jr., of the National Marine Fisheries Service, Beaufort Laboratory, and C. Wayne Waltz of the South

  9. QCCM Center for Quantum Algorithms

    DTIC Science & Technology

    2008-10-17

    algorithms (e.g., quantum walks and adiabatic computing ), as well as theoretical advances relating algorithms to physical implementations (e.g...Park, NC 27709-2211 15. SUBJECT TERMS Quantum algorithms, quantum computing , fault-tolerant error correction Richard Cleve MITACS East Academic...0511200 Algebraic results on quantum automata A. Ambainis, M. Beaudry, M. Golovkins, A. Kikusts, M. Mercer, D. Thrien Theory of Computing Systems 39(2006

  10. A Pilot Study on Concurrent Learning/Teaching Model (CLTM) for Online and In-Class Informatics Students

    ERIC Educational Resources Information Center

    Liu, Feng; Stapleton, Colleen; Stephen, Jacqueline

    2017-01-01

    The Informatics program at Mercer University is offered at four regional academic centers located throughout the state of Georgia. We serve non-traditional students who have primary responsibilities such as caring for family, working, and participating in their communities. We aim to offer availability and access to all required courses, access to…

  11. Course Completion Rates: Volume and Efficiency Measures, and Grade Distributions, 1982-1983. Technical Report 84-03.

    ERIC Educational Resources Information Center

    McMaster, Anne

    Available statistical data on student completion of courses at Mercer County Community College (MCCC) were compiled and analyzed for the 2-year period, summer 1981 to spring 1982, and summer 1982 to spring 1983. Two different measures of student enrollment were used: volume measures such as student headcount enrollment, student credit hours…

  12. Results of coal bed methane drilling, Mylan Park, Monongalia County, West Virginia

    USGS Publications Warehouse

    Ruppert, Leslie F.; Fedorko, Nick; Warwick, Peter D.; Grady, William C.; Crangle, Robert D.; Britton, James Q.

    2004-01-01

    The Department of Energy National Energy Technology Laboratory funded drilling of a borehole (39.64378 deg E , -80.04376 deg N) to evaluate the potential for coal bed methane and carbon dioxide sequestration at Mylan Park, Monongalia County, West Virginia. The drilling commenced on September 23, 2002 and was completed on November 14, 2002. The 2,525 ft deep hole contained 1,483.41 ft of Pennsylvanian coal-bearing strata, 739.67 feet of Mississippian strata, and 301.93 ft. of Devonian strata. The drill site was located directly over abandoned Pittsburgh and Sewickley coal mines. Coal cores from remaining mine pillars were cut and retrieved for desorption from both mines. In addition, coals were cored and desorbed from the Pittsburgh Roof, Little Pittsburgh, Elk Lick, Brush Creek, Upper Kittanning, Middle Kittanning, Clarion, Upper Mercer, Lower Mercer, and Quakertown coal beds. All coals are Pennsylvanian in age and are high-volatile-A bituminous in rank. A total of 34.75 ft of coal was desorbed over a maximum period of 662 days, although most of the coal was desorbed for about 275 days. This report is provided in Adobe Acrobat format. Appendix 3 is provided in Excel format.

  13. Evaluation of borehole geophysical logs at the Sharon Steel Farrell Works Superfund site, Mercer County, Pennsylvania

    USGS Publications Warehouse

    McAuley, Steven D.

    2004-01-01

    On April 14?15, 2003, geophysical logging was conducted in five open-borehole wells in and adjacent to the Sharon Steel Farrell Works Superfund Site, Mercer County, Pa. Geophysical-logging tools used included caliper, natural gamma, single-point resistance, fluid temperature, and heatpulse flowmeter. The logs were used to determine casing depth, locate subsurface fractures, identify water-bearing fractures, and identify and measure direction and rate of vertical flow within the borehole. The results of the geophysical logging were used to determine the placement of borehole screens, which allows monitoring of water levels and sampling of water-bearing zones so that the U.S. Environmental Protection Agency can conduct an investigation of contaminant movement in the fractured bedrock. Water-bearing zones were identified in three of five boreholes at depths ranging from 46 to 119 feet below land surface. Borehole MR-3310 (MW03D) showed upward vertical flow from 71 to 74 feet below land surface to a receiving zone at 63-68 feet below land surface, permitting potential movement of ground water, and possibly contaminants, from deep to shallow zones. No vertical flow was measured in the other four boreholes.

  14. Data-based diffraction kernels for surface waves from convolution and correlation processes through active seismic interferometry

    NASA Astrophysics Data System (ADS)

    Chmiel, Malgorzata; Roux, Philippe; Herrmann, Philippe; Rondeleux, Baptiste; Wathelet, Marc

    2018-05-01

    We investigated the construction of diffraction kernels for surface waves using two-point convolution and/or correlation from land active seismic data recorded in the context of exploration geophysics. The high density of controlled sources and receivers, combined with the application of the reciprocity principle, allows us to retrieve two-dimensional phase-oscillation diffraction kernels (DKs) of surface waves between any two source or receiver points in the medium at each frequency (up to 15 Hz, at least). These DKs are purely data-based as no model calculations and no synthetic data are needed. They naturally emerge from the interference patterns of the recorded wavefields projected on the dense array of sources and/or receivers. The DKs are used to obtain multi-mode dispersion relations of Rayleigh waves, from which near-surface shear velocity can be extracted. Using convolution versus correlation with a grid of active sources is an important step in understanding the physics of the retrieval of surface wave Green's functions. This provides the foundation for future studies based on noise sources or active sources with a sparse spatial distribution.

  15. Spectral-element simulations of wave propagation in complex exploration-industry models: Imaging and adjoint tomography

    NASA Astrophysics Data System (ADS)

    Luo, Y.; Nissen-Meyer, T.; Morency, C.; Tromp, J.

    2008-12-01

    Seismic imaging in the exploration industry is often based upon ray-theoretical migration techniques (e.g., Kirchhoff) or other ideas which neglect some fraction of the seismic wavefield (e.g., wavefield continuation for acoustic-wave first arrivals) in the inversion process. In a companion paper we discuss the possibility of solving the full physical forward problem (i.e., including visco- and poroelastic, anisotropic media) using the spectral-element method. With such a tool at hand, we can readily apply the adjoint method to tomographic inversions, i.e., iteratively improving an initial 3D background model to fit the data. In the context of this inversion process, we draw connections between kernels in adjoint tomography and basic imaging principles in migration. We show that the images obtained by migration are nothing but particular kinds of adjoint kernels (mainly density kernels). Migration is basically a first step in the iterative inversion process of adjoint tomography. We apply the approach to basic 2D problems involving layered structures, overthrusting faults, topography, salt domes, and poroelastic regions.

  16. Spatial Relative Risk Patterns of Autism Spectrum Disorders in Utah

    ERIC Educational Resources Information Center

    Bakian, Amanda V.; Bilder, Deborah A.; Coon, Hilary; McMahon, William M.

    2015-01-01

    Heightened areas of spatial relative risk for autism spectrum disorders (ASD), or ASD hotspots, in Utah were identified using adaptive kernel density functions. Children ages four, six, and eight with ASD from multiple birth cohorts were identified by the Utah Registry of Autism and Developmental Disabilities. Each ASD case was gender-matched to…

  17. Boundary Kernel Estimation of the Two Sample Comparison Density Function

    DTIC Science & Technology

    1989-05-01

    not for the understand- ing, love, and steadfast support of my wife, Catheryn . She supported my move to statistics a mere fortnight after we were...school one learns things of a narrow and technical nature; 0 Catheryn has shown me much of what is fundamentally true and important in this world. To her

  18. Left ventricle segmentation via graph cut distribution matching.

    PubMed

    Ben Ayed, Ismail; Punithakumar, Kumaradevan; Li, Shuo; Islam, Ali; Chong, Jaron

    2009-01-01

    We present a discrete kernel density matching energy for segmenting the left ventricle cavity in cardiac magnetic resonance sequences. The energy and its graph cut optimization based on an original first-order approximation of the Bhattacharyya measure have not been proposed previously, and yield competitive results in nearly real-time. The algorithm seeks a region within each frame by optimization of two priors, one geometric (distance-based) and the other photometric, each measuring a distribution similarity between the region and a model learned from the first frame. Based on global rather than pixelwise information, the proposed algorithm does not require complex training and optimization with respect to geometric transformations. Unlike related active contour methods, it does not compute iterative updates of computationally expensive kernel densities. Furthermore, the proposed first-order analysis can be used for other intractable energies and, therefore, can lead to segmentation algorithms which share the flexibility of active contours and computational advantages of graph cuts. Quantitative evaluations over 2280 images acquired from 20 subjects demonstrated that the results correlate well with independent manual segmentations by an expert.

  19. Visualization of spatial patterns and temporal trends for aerial surveillance of illegal oil discharges in western Canadian marine waters.

    PubMed

    Serra-Sogas, Norma; O'Hara, Patrick D; Canessa, Rosaline; Keller, Peter; Pelot, Ronald

    2008-05-01

    This paper examines the use of exploratory spatial analysis for identifying hotspots of shipping-based oil pollution in the Pacific Region of Canada's Exclusive Economic Zone. It makes use of data collected from fiscal years 1997/1998 to 2005/2006 by the National Aerial Surveillance Program, the primary tool for monitoring and enforcing the provisions imposed by MARPOL 73/78. First, we present oil spill data as points in a "dot map" relative to coastlines, harbors and the aerial surveillance distribution. Then, we explore the intensity of oil spill events using the Quadrat Count method, and the Kernel Density Estimation methods with both fixed and adaptive bandwidths. We found that oil spill hotspots where more clearly defined using Kernel Density Estimation with an adaptive bandwidth, probably because of the "clustered" distribution of oil spill occurrences. Finally, we discuss the importance of standardizing oil spill data by controlling for surveillance effort to provide a better understanding of the distribution of illegal oil spills, and how these results can ultimately benefit a monitoring program.

  20. Predicting spatial patterns of plant recruitment using animal-displacement kernels.

    PubMed

    Santamaría, Luis; Rodríguez-Pérez, Javier; Larrinaga, Asier R; Pias, Beatriz

    2007-10-10

    For plants dispersed by frugivores, spatial patterns of recruitment are primarily influenced by the spatial arrangement and characteristics of parent plants, the digestive characteristics, feeding behaviour and movement patterns of animal dispersers, and the structure of the habitat matrix. We used an individual-based, spatially-explicit framework to characterize seed dispersal and seedling fate in an endangered, insular plant-disperser system: the endemic shrub Daphne rodriguezii and its exclusive disperser, the endemic lizard Podarcis lilfordi. Plant recruitment kernels were chiefly determined by the disperser's patterns of space utilization (i.e. the lizard's displacement kernels), the position of the various plant individuals in relation to them, and habitat structure (vegetation cover vs. bare soil). In contrast to our expectations, seed gut-passage rate and its effects on germination, and lizard speed-of-movement, habitat choice and activity rhythm were of minor importance. Predicted plant recruitment kernels were strongly anisotropic and fine-grained, preventing their description using one-dimensional, frequency-distance curves. We found a general trade-off between recruitment probability and dispersal distance; however, optimal recruitment sites were not necessarily associated to sites of maximal adult-plant density. Conservation efforts aimed at enhancing the regeneration of endangered plant-disperser systems may gain in efficacy by manipulating the spatial distribution of dispersers (e.g. through the creation of refuges and feeding sites) to create areas favourable to plant recruitment.

  1. Exchange and correlation effects on plasmon dispersions and Coulomb drag in low-density electron bilayers

    NASA Astrophysics Data System (ADS)

    Badalyan, S. M.; Kim, C. S.; Vignale, G.; Senatore, G.

    2007-03-01

    We investigate the effect of exchange and correlation (XC) on the plasmon spectrum and the Coulomb drag between spatially separated low-density two-dimensional electron layers. We adopt a different approach, which employs dynamic XC kernels in the calculation of the bilayer plasmon spectra and of the plasmon-mediated drag, and static many-body local field factors in the calculation of the particle-hole contribution to the drag. The spectrum of bilayer plasmons and the drag resistivity are calculated in a broad range of temperatures taking into account both intra- and interlayer correlation effects. We observe that both plasmon modes are strongly affected by XC corrections. After the inclusion of the complex dynamic XC kernels, a decrease of the electron density induces shifts of the plasmon branches in opposite directions. This is in stark contrast with the tendency observed within random phase approximation that both optical and acoustical plasmons move away from the boundary of the particle-hole continuum with a decrease in the electron density. We find that the introduction of XC corrections results in a significant enhancement of the transresistivity and qualitative changes in its temperature dependence. In particular, the large high-temperature plasmon peak that is present in the random phase approximation is found to disappear when the XC corrections are included. Our numerical results at low temperatures are in good agreement with the results of recent experiments by Kellogg [Solid State Commun. 123, 515 (2002)].

  2. Nonparametric model validations for hidden Markov models with applications in financial econometrics

    PubMed Central

    Zhao, Zhibiao

    2011-01-01

    We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise. PMID:21750601

  3. Fracture analysis of a transversely isotropic high temperature superconductor strip based on real fundamental solutions

    NASA Astrophysics Data System (ADS)

    Gao, Zhiwen; Zhou, Youhe

    2015-04-01

    Real fundamental solution for fracture problem of transversely isotropic high temperature superconductor (HTS) strip is obtained. The superconductor E-J constitutive law is characterized by the Bean model where the critical current density is independent of the flux density. Fracture analysis is performed by the methods of singular integral equations which are solved numerically by Gauss-Lobatto-Chybeshev (GSL) collocation method. To guarantee a satisfactory accuracy, the convergence behavior of the kernel function is investigated. Numerical results of fracture parameters are obtained and the effects of the geometric characteristics, applied magnetic field and critical current density on the stress intensity factors (SIF) are discussed.

  4. Measurement of vascular wall attenuation: comparison of CT angiography using model-based iterative reconstruction with standard filtered back-projection algorithm CT in vitro.

    PubMed

    Suzuki, Shigeru; Machida, Haruhiko; Tanaka, Isao; Ueno, Eiko

    2012-11-01

    To compare the performance of model-based iterative reconstruction (MBIR) with that of standard filtered back projection (FBP) for measuring vascular wall attenuation. After subjecting 9 vascular models (actual attenuation value of wall, 89 HU) with wall thickness of 0.5, 1.0, or 1.5 mm that we filled with contrast material of 275, 396, or 542 HU to scanning using 64-detector computed tomography (CT), we reconstructed images using MBIR and FBP (Bone, Detail kernels) and measured wall attenuation at the center of the wall for each model. We performed attenuation measurements for each model and additional supportive measurements by a differentiation curve. We analyzed statistics using analyzes of variance with repeated measures. Using the Bone kernel, standard deviation of the measurement exceeded 30 HU in most conditions. In measurements at the wall center, the attenuation values obtained using MBIR were comparable to or significantly closer to the actual wall attenuation than those acquired using Detail kernel. Using differentiation curves, we could measure attenuation for models with walls of 1.0- or 1.5-mm thickness using MBIR but only those of 1.5-mm thickness using Detail kernel. We detected no significant differences among the attenuation values of the vascular walls of either thickness (MBIR, P=0.1606) or among the 3 densities of intravascular contrast material (MBIR, P=0.8185; Detail kernel, P=0.0802). Compared with FBP, MBIR reduces both reconstruction blur and image noise simultaneously, facilitates recognition of vascular wall boundaries, and can improve accuracy in measuring wall attenuation. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  5. Home range and space use patterns of flathead catfish during the summer-fall period in two Missouri streams

    USGS Publications Warehouse

    Vokoun, Jason C.; Rabeni, Charles F.

    2005-01-01

    Flathead catfish Pylodictis olivaris were radio-tracked in the Grand River and Cuivre River, Missouri, from late July until they moved to overwintering habitats in late October. Fish moved within a definable area, and although occasional long-distance movements occurred, the fish typically returned to the previously occupied area. Seasonal home range was calculated with the use of kernel density estimation, which can be interpreted as a probabilistic utilization distribution that documents the internal structure of the estimate by delineating portions of the range that was used a specified percentage of the time. A traditional linear range also was reported. Most flathead catfish (89%) had one 50% kernel-estimated core area, whereas 11% of the fish split their time between two core areas. Core areas were typically in the middle of the 90% kernel-estimated home range (58%), although several had core areas in upstream (26%) and downstream (16%) portions of the home range. Home-range size did not differ based on river, sex, or size and was highly variable among individuals. The median 95% kernel estimate was 1,085 m (range, 70– 69,090 m) for all fish. The median 50% kernel-estimated core area was 135 m (10–2,260 m). The median linear range was 3,510 m (150–50,400 m). Fish pairs with core areas in the same and neighboring pools had static joint space use values of up to 49% (area of intersection index), indicating substantial overlap and use of the same area. However, all fish pairs had low dynamic joint space use values (<0.07; coefficient of association), indicating that fish pairs were temporally segregated, rarely occurring in the same location at the same time.

  6. Policy-Making Boards and Religious-Affiliated Colleges: The Experiences of Two Baptist Institutions

    ERIC Educational Resources Information Center

    Jenkins, J. Kevin; Allen, Loyd; Elkins, Penny L.

    2008-01-01

    Over the last decades of the 20th century, and the first few years of the 21st, the conflict within the life of the Baptist church has often focused on control of Baptist-affiliated institutions of higher education. During this time, two such institutions in Georgia, Mercer University and Shorter College, were engaged in a struggle for power with…

  7. North Pacific Acoustic Laboratory and Deep Water Acoustics

    DTIC Science & Technology

    2015-09-30

    range acoustic systems, whether for acoustic surveillance, communication, or remote sensing of the ocean interior . The data from the NPAL network, and...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. North Pacific Acoustic Laboratory and Deep Water... Acoustics PI James A. Mercer Applied Physics Laboratory, University of Washington 1013 NE 40th Street Seattle, WA 98105 phone: (206) 543-1361 fax

  8. Institutional Research: New Challenges to an Evolving Role. Proceedings of the North East Association for Institutional Research Annual Conference (13th, Philadelphia, Pennsylvania, October 26-28, 1986).

    ERIC Educational Resources Information Center

    Baylis, Bayard, Comp.

    New challenges facing the institutional research profession are covered in these 1986 conference proceedings of the North East Association for Institutional Research. Paper titles and authors include: "Institutional Research at Mercer County Community College: The Changing Role in the Eighties" (F. L. Edwards); "Course Placement and Academic…

  9. 75 FR 60004 - Relocation of Standard Time Zone Boundary in the State of North Dakota: Mercer County

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-29

    ... children going to school in the dark. A high school teacher explained that she does not want to walk to school in the dark. Several individuals said they found living and working in different time zones to be... the matter be put to a vote, such as an advisory referendum on the November 2010 ballot. As a Federal...

  10. Towards effective partnerships in a collaborative problem-solving task.

    PubMed

    Schmitz, Megan J; Winskel, Heather

    2008-12-01

    Collaborative learning is recognized as an effective learning tool in the classroom. In order to optimize the collaborative learning experience for children within a collaborative partnership, it is important to understand how to match the children by ability level, and whether assigning roles within these dyads is beneficial or not. The current study investigated the effect of partnering children with different task-specific abilities and assigning or not assigning helping roles within the dyads on the quality of talk used in a collaborative learning task. The participants in this study comprised 54 year 6 pupils from a Western Sydney government primary school (boys=26, girls=28). The ages ranged from 10 years 10 months to 12 years 4 months with a mean age of 11 years 4 months. The children were formed into 27 single sex dyads of low-middle- and low-high-ability partnerships. In half of each of these dyads the higher ability partner was asked to help the lower ability partner, which was compared with just asking partners to work together. The quality of talk used by the dyads while working collaboratively on the problem-solving task was analysed using a language analysis framework developed by Mercer and colleagues (e.g. Littleton et al., 2005; Mercer, 1994, 1996). Results of this study found that children who worked collaboratively in the low-middle-ability dyad condition demonstrated significantly more high-quality exploratory talk than those in the low-high-ability dyad condition. Although there was no significant difference between dyads who were assigned roles and those who were asked to work together, there was an interaction trend which suggests that low-high-ability dyads, who were given the roles of helper and learner, showed more exploratory talk than dyads who were asked just to work together. Mercer's re-conceptualization of Vygotsky's Zone of Proximal Development (ZPD) in terms of the Intermental Development Zone (IDZ), which is reliant on constructive challenging discourse, can potentially provide a platform upon which all learners in the classroom can benefit from collaborative learning experiences.

  11. Exact analytic solution for non-linear density fluctuation in a ΛCDM universe

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

    Yoo, Jaiyul; Gong, Jinn-Ouk, E-mail: jyoo@physik.uzh.ch, E-mail: jinn-ouk.gong@apctp.org

    We derive the exact third-order analytic solution of the matter density fluctuation in the proper-time hypersurface in a ΛCDM universe, accounting for the explicit time-dependence and clarifying the relation to the initial condition. Furthermore, we compare our analytic solution to the previous calculation in the comoving gauge, and to the standard Newtonian perturbation theory by providing Fourier kernels for the relativistic effects. Our results provide an essential ingredient for a complete description of galaxy bias in the relativistic context.

  12. A sparse matrix-vector multiplication based algorithm for accurate density matrix computations on systems of millions of atoms

    NASA Astrophysics Data System (ADS)

    Ghale, Purnima; Johnson, Harley T.

    2018-06-01

    We present an efficient sparse matrix-vector (SpMV) based method to compute the density matrix P from a given Hamiltonian in electronic structure computations. Our method is a hybrid approach based on Chebyshev-Jackson approximation theory and matrix purification methods like the second order spectral projection purification (SP2). Recent methods to compute the density matrix scale as O(N) in the number of floating point operations but are accompanied by large memory and communication overhead, and they are based on iterative use of the sparse matrix-matrix multiplication kernel (SpGEMM), which is known to be computationally irregular. In addition to irregularity in the sparse Hamiltonian H, the nonzero structure of intermediate estimates of P depends on products of H and evolves over the course of computation. On the other hand, an expansion of the density matrix P in terms of Chebyshev polynomials is straightforward and SpMV based; however, the resulting density matrix may not satisfy the required constraints exactly. In this paper, we analyze the strengths and weaknesses of the Chebyshev-Jackson polynomials and the second order spectral projection purification (SP2) method, and propose to combine them so that the accurate density matrix can be computed using the SpMV computational kernel only, and without having to store the density matrix P. Our method accomplishes these objectives by using the Chebyshev polynomial estimate as the initial guess for SP2, which is followed by using sparse matrix-vector multiplications (SpMVs) to replicate the behavior of the SP2 algorithm for purification. We demonstrate the method on a tight-binding model system of an oxide material containing more than 3 million atoms. In addition, we also present the predicted behavior of our method when applied to near-metallic Hamiltonians with a wide energy spectrum.

  13. Testosterone and androstanediol glucuronide among men in NHANES III.

    PubMed

    Duan, Chuan Wei; Xu, Lin

    2018-03-09

    Most of the androgen replacement therapies were based on serum testosterone and without measurements of total androgen activities. Whether those with low testosterone also have low levels of androgen activity is largely unknown. We hence examined the association between testosterone and androstanediol glucuronide (AG), a reliable measure of androgen activity, in a nationally representative sample of US men. Cross-sectional analysis was based on 1493 men from the Third National Health and Nutrition examination Survey (NHANES III) conducted from 1988 to 1991. Serum testosterone and AG were measured by immunoassay. Kernel density was used to estimate the average density of serum AG concentrations by quartiles of testosterone. Testosterone was weakly and positively correlated with AG (correlation coefficient = 0.18). The kernel density estimates show that the distributions are quite similar between the quartiles of testosterone. After adjustment for age, the distributions of AG in quartiles of testosterone did not change. The correlation between testosterone and AG was stronger in men with younger age, lower body mass index, non-smoking and good self-rated health and health status. Serum testosterone is weakly correlated with total androgen activities, and the correlation is even weaker for those with poor self-rated health. Our results suggest that measurement of total androgen activity in addition to testosterone is necessary in clinical practice, especially before administration of androgen replacement therapy.

  14. Congested Aggregation via Newtonian Interaction

    NASA Astrophysics Data System (ADS)

    Craig, Katy; Kim, Inwon; Yao, Yao

    2018-01-01

    We consider a congested aggregation model that describes the evolution of a density through the competing effects of nonlocal Newtonian attraction and a hard height constraint. This provides a counterpoint to existing literature on repulsive-attractive nonlocal interaction models, where the repulsive effects instead arise from an interaction kernel or the addition of diffusion. We formulate our model as the Wasserstein gradient flow of an interaction energy, with a penalization to enforce the constraint on the height of the density. From this perspective, the problem can be seen as a singular limit of the Keller-Segel equation with degenerate diffusion. Two key properties distinguish our problem from previous work on height constrained equations: nonconvexity of the interaction kernel (which places the model outside the scope of classical gradient flow theory) and nonlocal dependence of the velocity field on the density (which causes the problem to lack a comparison principle). To overcome these obstacles, we combine recent results on gradient flows of nonconvex energies with viscosity solution theory. We characterize the dynamics of patch solutions in terms of a Hele-Shaw type free boundary problem and, using this characterization, show that in two dimensions patch solutions converge to a characteristic function of a disk in the long-time limit, with an explicit rate on the decay of the energy. We believe that a key contribution of the present work is our blended approach, combining energy methods with viscosity solution theory.

  15. Production of LEU Fully Ceramic Microencapsulated Fuel for Irradiation Testing

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

    Terrani, Kurt A; Kiggans Jr, James O; McMurray, Jake W

    2016-01-01

    Fully Ceramic Microencapsulated (FCM) fuel consists of tristructural isotropic (TRISO) fuel particles embedded inside a SiC matrix. This fuel inherently possesses multiple barriers to fission product release, namely the various coating layers in the TRISO fuel particle as well as the dense SiC matrix that hosts these particles. This coupled with the excellent oxidation resistance of the SiC matrix and the SiC coating layer in the TRISO particle designate this concept as an accident tolerant fuel (ATF). The FCM fuel takes advantage of uranium nitride kernels instead of oxide or oxide-carbide kernels used in high temperature gas reactors to enhancemore » heavy metal loading in the highly moderated LWRs. Production of these kernels with appropriate density, coating layer development to produce UN TRISO particles, and consolidation of these particles inside a SiC matrix have been codified thanks to significant R&D supported by US DOE Fuel Cycle R&D program. Also, surrogate FCM pellets (pellets with zirconia instead of uranium-bearing kernels) have been neutron irradiated and the stability of the matrix and coating layer under LWR irradiation conditions have been established. Currently the focus is on production of LEU (7.3% U-235 enrichment) FCM pellets to be utilized for irradiation testing. The irradiation is planned at INL s Advanced Test Reactor (ATR). This is a critical step in development of this fuel concept to establish the ability of this fuel to retain fission products under prototypical irradiation conditions.« less

  16. QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

    NASA Astrophysics Data System (ADS)

    Bartolini, S.; Cappello, A.; Martí, J.; Del Negro, C.

    2013-08-01

    One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision-making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps, i.e. the spatial probability of a future vent opening given the past eruptive activity of a volcano. This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source Geographic Information System Quantum GIS, that is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows to select an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input datasets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

  17. Comparative analysis of genetic architectures for nine developmental traits of rye.

    PubMed

    Masojć, Piotr; Milczarski, P; Kruszona, P

    2017-08-01

    Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1-3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1-5 loci of the epistatic D class and 10-28 loci of the hypostatic, mostly R and E classes controlling traits variation through D-E or D-R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2-8 traits. Detection of considerable numbers of the reversed (D', E' and R') classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies.

  18. Small-scale modification to the lensing kernel

    NASA Astrophysics Data System (ADS)

    Hadzhiyska, Boryana; Spergel, David; Dunkley, Joanna

    2018-02-01

    Calculations of the cosmic microwave background (CMB) lensing power implemented into the standard cosmological codes such as camb and class usually treat the surface of last scatter as an infinitely thin screen. However, since the CMB anisotropies are smoothed out on scales smaller than the diffusion length due to the effect of Silk damping, the photons which carry information about the small-scale density distribution come from slightly earlier times than the standard recombination time. The dominant effect is the scale dependence of the mean redshift associated with the fluctuations during recombination. We find that fluctuations at k =0.01 Mpc-1 come from a characteristic redshift of z ≈1090 , while fluctuations at k =0.3 Mpc-1 come from a characteristic redshift of z ≈1130 . We then estimate the corrections to the lensing kernel and the related power spectra due to this effect. We conclude that neglecting it would result in a deviation from the true value of the lensing kernel at the half percent level at small CMB scales. For an all-sky, noise-free experiment, this corresponds to a ˜0.1 σ shift in the observed temperature power spectrum on small scales (2500 ≲l ≲4000 ).

  19. The Predictability of Large-Scale, Short-Period Ocean Variability in the Philippine Sea and the Influence of Such Variability on Long-Range Acoustic Propagation

    DTIC Science & Technology

    2014-09-30

    for the various ray arrivals on this path, with the black line indicating an average of these travel times. Altimetry data from 2000- 2007 were used...D.E. & Stammer , D., Eds., ESA Publication WPP-306. Dushaw, B. D., P. F. Worcester, W. H. Munk, R. C. Spindel, J. A. Mercer, B. M. Howe, K. Metzger

  20. Hydrology Section Executive Committee Minutes

    NASA Astrophysics Data System (ADS)

    Mercer, James W.

    The AGU Hydrology Section Executive Committee Meeting was called to order at approximately 4 P.M. on Monday, May 18, 1987, by Hydrology Section President Marshall Moss. In attendance were President-Elect George Pinder, Secretary Jim Mercer, Ron Cummings, Helen Joyce Peters, Peter Eagleson, Stephen Burges, Jim Wallis, Jurate Landwehr, Don Nielson, Ken Bencala, Pete Loucks, Jery Stedinger, Dennis Lettenmaier, Lenny Konikow, Ken Potter, John Wilson, Ivan Johnson, and Judy Holoviak.

  1. ASW Research at WHOI and SIO

    DTIC Science & Technology

    2016-06-07

    North Pacific targeting ocean-acoustic bottom interaction, deep seafloor arri vals and bottom diffracted surface refl ected acoustic paths. We...These arrivals were named Deep Sea Floor Arrivals (DSF As). SIO (Worcester) and WHOI (Kemp) provided the near-seafloor DVLA. The OBSJP (Ocean...Andrew, R. K. , Mercer, J . A. , Colosi, J. A. , and Howe, B. M. (2012). "Analysis of Deep Seafloor Arrivals Observed on NPAL04," WHO! Technical Report

  2. Experimental Investigation and Analysis of Mercerized and Citric Acid Surface Treated Bamboo Fiber Reinforced Composite

    NASA Astrophysics Data System (ADS)

    De, Jyotiraman; Baxi, R. N., Dr.

    2017-08-01

    Mercerization or NaOH fiber surface treatment is one of the most popular surface treatment processes to make the natural fibers such as bamboo fibers compatible for use as reinforcing material in composites. But NaOH being a chemical is hazardous and polluting to the nature. This paper explores the possibility of use of naturally derived citric acid for bamboo fiber surface treatment and its comparison with NaOH treated Bamboo Fiber Composites. Untreated, 2.5 wt% NaOH treated and 5 wt% citric acid treated Bamboo Fiber Composites with 5 wt% fiber content were developed by Hand Lay process. Bamboo mats made of bamboo slivers were used as reinforcing material. Mechanical and physical characterization was done to compare the effects of NaOH and citric acid bamboo fiber surface treatment on mechanical and physical properties of Bamboo Fiber Composite. The experiment data reveals that the tensile and flexural strength was found to be highest for citric acid and NaOH treated Bamboo Fiber Composite respectively. Water absorption tendency was found more than the NaOH treated Bamboo Fiber Composites. SEM micrographs used to analyze the morphology of fracture surface of tensile test specimens confirm improvement in fiber-matrix interface bonding due to surface treatment of bamboo fibers.

  3. Analysis of mercerization process based on the intensity change of deconvoluted resonances of (13)C CP/MAS NMR: Cellulose mercerized under cooling and non-cooling conditions.

    PubMed

    Miura, Kento; Nakano, Takato

    2015-08-01

    The area intensity change of C1, C4, and C6 in spectrum obtained by (13)C CP/MAS NMR and the mutual relationship between their changes were examined for cellulose samples treated with various concentrations of aqueous NaOH solutions under non-cooling and cooling conditions. The area intensity of C1-up and C6-down changed cooperatively with that of C4-down which corresponds to the crystallinity of samples: "-up" and "-down" are the up- and down- field component in a splitting peak of NMR spectrum, respectively. The intensity change of C1-up starts to decrease with decreasing in that of C4-down after that of C6-down is almost complete. These changes were more clearly observed for samples treated under cooling condition. It can be suggested that their characteristic change relates closely to the change in conformation of cellulose chains by induced decrystallization and the subsequent crystallization of cellulose II, and presumed that their changes at microscopic level relate to the macroscopic morphological changes such as contraction along the length of cellulose chains and recovery along the length. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Snake River Plain Geothermal Play Fairway Analysis - Phase 1 Raster Files

    DOE Data Explorer

    John Shervais

    2015-10-09

    Snake River Plain Play Fairway Analysis - Phase 1 CRS Raster Files. This dataset contains raster files created in ArcGIS. These raster images depict Common Risk Segment (CRS) maps for HEAT, PERMEABILITY, AND SEAL, as well as selected maps of Evidence Layers. These evidence layers consist of either Bayesian krige functions or kernel density functions, and include: (1) HEAT: Heat flow (Bayesian krige map), Heat flow standard error on the krige function (data confidence), volcanic vent distribution as function of age and size, groundwater temperature (equivalue interval and natural breaks bins), and groundwater T standard error. (2) PERMEABILTY: Fault and lineament maps, both as mapped and as kernel density functions, processed for both dilational tendency (TD) and slip tendency (ST), along with data confidence maps for each data type. Data types include mapped surface faults from USGS and Idaho Geological Survey data bases, as well as unpublished mapping; lineations derived from maximum gradients in magnetic, deep gravity, and intermediate depth gravity anomalies. (3) SEAL: Seal maps based on presence and thickness of lacustrine sediments and base of SRP aquifer. Raster size is 2 km. All files generated in ArcGIS.

  5. Segmentation of 3D microPET images of the rat brain via the hybrid gaussian mixture method with kernel density estimation.

    PubMed

    Chen, Tai-Been; Chen, Jyh-Cheng; Lu, Henry Horng-Shing

    2012-01-01

    Segmentation of positron emission tomography (PET) is typically achieved using the K-Means method or other approaches. In preclinical and clinical applications, the K-Means method needs a prior estimation of parameters such as the number of clusters and appropriate initialized values. This work segments microPET images using a hybrid method combining the Gaussian mixture model (GMM) with kernel density estimation. Segmentation is crucial to registration of disordered 2-deoxy-2-fluoro-D-glucose (FDG) accumulation locations with functional diagnosis and to estimate standardized uptake values (SUVs) of region of interests (ROIs) in PET images. Therefore, simulation studies are conducted to apply spherical targets to evaluate segmentation accuracy based on Tanimoto's definition of similarity. The proposed method generates a higher degree of similarity than the K-Means method. The PET images of a rat brain are used to compare the segmented shape and area of the cerebral cortex by the K-Means method and the proposed method by volume rendering. The proposed method provides clearer and more detailed activity structures of an FDG accumulation location in the cerebral cortex than those by the K-Means method.

  6. Applications of the line-of-response probability density function resolution model in PET list mode reconstruction.

    PubMed

    Jian, Y; Yao, R; Mulnix, T; Jin, X; Carson, R E

    2015-01-07

    Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners-the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [(11)C]AFM rats imaged on the HRRT and [(11)C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods.

  7. Applications of the line-of-response probability density function resolution model in PET list mode reconstruction

    PubMed Central

    Jian, Y; Yao, R; Mulnix, T; Jin, X; Carson, R E

    2016-01-01

    Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners - the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [11C]AFM rats imaged on the HRRT and [11C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods. PMID:25490063

  8. On processed splitting methods and high-order actions in path-integral Monte Carlo simulations.

    PubMed

    Casas, Fernando

    2010-10-21

    Processed splitting methods are particularly well adapted to carry out path-integral Monte Carlo (PIMC) simulations: since one is mainly interested in estimating traces of operators, only the kernel of the method is necessary to approximate the thermal density matrix. Unfortunately, they suffer the same drawback as standard, nonprocessed integrators: kernels of effective order greater than two necessarily involve some negative coefficients. This problem can be circumvented, however, by incorporating modified potentials into the composition, thus rendering schemes of higher effective order. In this work we analyze a family of fourth-order schemes recently proposed in the PIMC setting, paying special attention to their linear stability properties, and justify their observed behavior in practice. We also propose a new fourth-order scheme requiring the same computational cost but with an enlarged stability interval.

  9. Power Series Approximation for the Correlation Kernel Leading to Kohn-Sham Methods Combining Accuracy, Computational Efficiency, and General Applicability

    NASA Astrophysics Data System (ADS)

    Erhard, Jannis; Bleiziffer, Patrick; Görling, Andreas

    2016-09-01

    A power series approximation for the correlation kernel of time-dependent density-functional theory is presented. Using this approximation in the adiabatic-connection fluctuation-dissipation (ACFD) theorem leads to a new family of Kohn-Sham methods. The new methods yield reaction energies and barriers of unprecedented accuracy and enable a treatment of static (strong) correlation with an accuracy of high-level multireference configuration interaction methods but are single-reference methods allowing for a black-box-like handling of static correlation. The new methods exhibit a better scaling of the computational effort with the system size than rivaling wave-function-based electronic structure methods. Moreover, the new methods do not suffer from the problem of singularities in response functions plaguing previous ACFD methods and therefore are applicable to any type of electronic system.

  10. A Comparison of Spatial Analysis Methods for the Construction of Topographic Maps of Retinal Cell Density

    PubMed Central

    Garza-Gisholt, Eduardo; Hemmi, Jan M.; Hart, Nathan S.; Collin, Shaun P.

    2014-01-01

    Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed ‘by eye’. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation ‘respects’ the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the ‘noise’ caused by artefacts and permits a clearer representation of the dominant, ‘real’ distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome. PMID:24747568

  11. Kernel abortion in maize : I. Carbohydrate concentration patterns and Acid invertase activity of maize kernels induced to abort in vitro.

    PubMed

    Hanft, J M; Jones, R J

    1986-06-01

    Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.

  12. 7 CFR 810.602 - Definition of other terms.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...) Damaged kernels. Kernels and pieces of flaxseed kernels that are badly ground-damaged, badly weather... instructions. Also, underdeveloped, shriveled, and small pieces of flaxseed kernels removed in properly... recleaning. (c) Heat-damaged kernels. Kernels and pieces of flaxseed kernels that are materially discolored...

  13. Kernel Abortion in Maize 1

    PubMed Central

    Hanft, Jonathan M.; Jones, Robert J.

    1986-01-01

    Kernels cultured in vitro were induced to abort by high temperature (35°C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35°C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth. PMID:16664846

  14. UTM Technical Capabilities Level 2 (TLC2) Test at Reno-Stead Airport.

    NASA Image and Video Library

    2016-10-06

    Test of Unmanned Aircraft Systems Traffic Management (UTM) technical capability Level 2 (TCL2) at Reno-Stead Airport, Nevada. During the test, five drones simultaneously crossed paths, separated by altitude. Two drones flew beyond visual line-of-sight and three flew within line-of-sight of their operators. Engineer Joey Mercer reviews flight paths using the UAS traffic management research platform UTM coordinator app to verify and validate flight paths.

  15. Current Issues in Mental Retardation and Human Development: Selected Papers from the 1970 Staff Development Conferences of the President's Committee on Mental Retardation (Washington, D.C., 1971).

    ERIC Educational Resources Information Center

    Stedman, Donald J., Ed.

    Six papers discuss some of the current issues in the field of mental retardation and human development. Epidemiology of mental retardation from a sociological and clinical point of view is analyzed by Jane R. Mercer, based on studies of mental retardation in the community in Pomona, California. The role of genetics and intra-uterine diagnosis of…

  16. 66. FONTHILL GARAGE (1913) AND TERRACE PAVILION (192628), FROM SOUTH. ...

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

    66. FONTHILL GARAGE (1913) AND TERRACE PAVILION (1926-28), FROM SOUTH. POURED ATOP AN EARLIER STONE BARN. THE FIRST FLOOR OF THIS STRUCTURE SERVERD AS A GARAGE FOR FONTHILL. IN 1926, MERCER BEGAN CONVERTING THE SECOND FLOOR INTO AND ELABORATELY DECORATED MEETING HOUSE FOR THE DOYLESTOWN NATURE CLUB, CALLED THE TERRACE PAVILION. - Moravian Pottery & Tile Works, Southwest side of State Route 313 (Swamp Road), Northwest of East Court Street, Doylestown, Bucks County, PA

  17. Time Effects on Morphology and Bonding Ability in Mercerized Natural Fibers for Composite Reinforcement

    DTIC Science & Technology

    2011-01-01

    such as lignin , are not favored for interaction with most hydrophilic resins. Lignin , being mostly hydrophobic, shows poor adhe- sion between the...cellulose, hemicelluloses, and lignin , are shown in Figures 1, 2, 3, and 4, respectively. Chemical treatment has been a well-known method em- ployed...to clean the surfaces of fibers and remove unwanted components, such as waxes, pectin, hemicellulose, and lignin . The removal of these materials has

  18. The Freedmen’s Bureau, Politics, and Stability Operations during Reconstruction in the South

    DTIC Science & Technology

    2009-06-12

    Movement in the 1960s. 15. SUBJECT TERMS Freedmen‘s Bureau, Stability Operations, Andrew Johnson, Reconstruction 16. SECURITY CLASSIFICATION OF...Mercer Langston (1829-1897) [on-line]; available from http://www. oberlin.edu /external/ EOG /OYTT-images/JMLangston.html; Internet; accessed 26 March...by sentiment more in line with the South‘s old ruling class view of labor, society, and governance. 53 Democratic victories of 1874 signaled a

  19. Group Centric Networking: Large Scale Over the Air Testing of Group Centric Networking

    DTIC Science & Technology

    2016-11-01

    protocol designed to support groups of devices in a local region [4]. It attempts to use the wireless medium to broadcast minimal control information...1) Group Discovery: The goal of the group discovery algo- rithm is to find group nodes without globally flooding control messages. To facilitate this...Large Scale Over-the-Air Testing of Group Centric Networking Logan Mercer, Greg Kuperman, Andrew Hunter, Brian Proulx MIT Lincoln Laboratory

  20. 75 FR 9568 - Standard Time Zone Boundary in the State of North Dakota: Proposed Change for Mercer County...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-03

    ... hearing on this issue from 7-10 p.m. (Mountain Daylight Time) on Friday, May 14, 2010, in the ``Large Room... referendum favored changing to central time by a vote of 1,180 to 1038. However, a majority of written... middle of the Missouri River. * * * * * [FR Doc. 2010-4372 Filed 3-2-10; 8:45 am] BILLING CODE 4910-9X-P ...

  1. QCDNUM: Fast QCD evolution and convolution

    NASA Astrophysics Data System (ADS)

    Botje, M.

    2011-02-01

    The QCDNUM program numerically solves the evolution equations for parton densities and fragmentation functions in perturbative QCD. Un-polarised parton densities can be evolved up to next-to-next-to-leading order in powers of the strong coupling constant, while polarised densities or fragmentation functions can be evolved up to next-to-leading order. Other types of evolution can be accessed by feeding alternative sets of evolution kernels into the program. A versatile convolution engine provides tools to compute parton luminosities, cross-sections in hadron-hadron scattering, and deep inelastic structure functions in the zero-mass scheme or in generalised mass schemes. Input to these calculations are either the QCDNUM evolved densities, or those read in from an external parton density repository. Included in the software distribution are packages to calculate zero-mass structure functions in un-polarised deep inelastic scattering, and heavy flavour contributions to these structure functions in the fixed flavour number scheme. Program summaryProgram title: QCDNUM version: 17.00 Catalogue identifier: AEHV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU Public Licence No. of lines in distributed program, including test data, etc.: 45 736 No. of bytes in distributed program, including test data, etc.: 911 569 Distribution format: tar.gz Programming language: Fortran-77 Computer: All Operating system: All RAM: Typically 3 Mbytes Classification: 11.5 Nature of problem: Evolution of the strong coupling constant and parton densities, up to next-to-next-to-leading order in perturbative QCD. Computation of observable quantities by Mellin convolution of the evolved densities with partonic cross-sections. Solution method: Parametrisation of the parton densities as linear or quadratic splines on a discrete grid, and evolution of the spline coefficients by solving (coupled) triangular matrix equations with a forward substitution algorithm. Fast computation of convolution integrals as weighted sums of spline coefficients, with weights derived from user-given convolution kernels. Restrictions: Accuracy and speed are determined by the density of the evolution grid. Running time: Less than 10 ms on a 2 GHz Intel Core 2 Duo processor to evolve the gluon density and 12 quark densities at next-to-next-to-leading order over a large kinematic range.

  2. Out-of-Sample Extensions for Non-Parametric Kernel Methods.

    PubMed

    Pan, Binbin; Chen, Wen-Sheng; Chen, Bo; Xu, Chen; Lai, Jianhuang

    2017-02-01

    Choosing suitable kernels plays an important role in the performance of kernel methods. Recently, a number of studies were devoted to developing nonparametric kernels. Without assuming any parametric form of the target kernel, nonparametric kernel learning offers a flexible scheme to utilize the information of the data, which may potentially characterize the data similarity better. The kernel methods using nonparametric kernels are referred to as nonparametric kernel methods. However, many nonparametric kernel methods are restricted to transductive learning, where the prediction function is defined only over the data points given beforehand. They have no straightforward extension for the out-of-sample data points, and thus cannot be applied to inductive learning. In this paper, we show how to make the nonparametric kernel methods applicable to inductive learning. The key problem of out-of-sample extension is how to extend the nonparametric kernel matrix to the corresponding kernel function. A regression approach in the hyper reproducing kernel Hilbert space is proposed to solve this problem. Empirical results indicate that the out-of-sample performance is comparable to the in-sample performance in most cases. Experiments on face recognition demonstrate the superiority of our nonparametric kernel method over the state-of-the-art parametric kernel methods.

  3. 7 CFR 810.1202 - Definition of other terms.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... kernels. Kernels, pieces of rye kernels, and other grains that are badly ground-damaged, badly weather.... Also, underdeveloped, shriveled, and small pieces of rye kernels removed in properly separating the...-damaged kernels. Kernels, pieces of rye kernels, and other grains that are materially discolored and...

  4. The Genetic Basis of Natural Variation in Kernel Size and Related Traits Using a Four-Way Cross Population in Maize.

    PubMed

    Chen, Jiafa; Zhang, Luyan; Liu, Songtao; Li, Zhimin; Huang, Rongrong; Li, Yongming; Cheng, Hongliang; Li, Xiantang; Zhou, Bo; Wu, Suowei; Chen, Wei; Wu, Jianyu; Ding, Junqiang

    2016-01-01

    Kernel size is an important component of grain yield in maize breeding programs. To extend the understanding on the genetic basis of kernel size traits (i.e., kernel length, kernel width and kernel thickness), we developed a set of four-way cross mapping population derived from four maize inbred lines with varied kernel sizes. In the present study, we investigated the genetic basis of natural variation in seed size and other components of maize yield (e.g., hundred kernel weight, number of rows per ear, number of kernels per row). In total, ten QTL affecting kernel size were identified, three of which (two for kernel length and one for kernel width) had stable expression in other components of maize yield. The possible genetic mechanism behind the trade-off of kernel size and yield components was discussed.

  5. The Genetic Basis of Natural Variation in Kernel Size and Related Traits Using a Four-Way Cross Population in Maize

    PubMed Central

    Liu, Songtao; Li, Zhimin; Huang, Rongrong; Li, Yongming; Cheng, Hongliang; Li, Xiantang; Zhou, Bo; Wu, Suowei; Chen, Wei; Wu, Jianyu; Ding, Junqiang

    2016-01-01

    Kernel size is an important component of grain yield in maize breeding programs. To extend the understanding on the genetic basis of kernel size traits (i.e., kernel length, kernel width and kernel thickness), we developed a set of four-way cross mapping population derived from four maize inbred lines with varied kernel sizes. In the present study, we investigated the genetic basis of natural variation in seed size and other components of maize yield (e.g., hundred kernel weight, number of rows per ear, number of kernels per row). In total, ten QTL affecting kernel size were identified, three of which (two for kernel length and one for kernel width) had stable expression in other components of maize yield. The possible genetic mechanism behind the trade-off of kernel size and yield components was discussed. PMID:27070143

  6. Statistics of primordial density perturbations from discrete seed masses

    NASA Technical Reports Server (NTRS)

    Scherrer, Robert J.; Bertschinger, Edmund

    1991-01-01

    The statistics of density perturbations for general distributions of seed masses with arbitrary matter accretion is examined. Formal expressions for the power spectrum, the N-point correlation functions, and the density distribution function are derived. These results are applied to the case of uncorrelated seed masses, and power spectra are derived for accretion of both hot and cold dark matter plus baryons. The reduced moments (cumulants) of the density distribution are computed and used to obtain a series expansion for the density distribution function. Analytic results are obtained for the density distribution function in the case of a distribution of seed masses with a spherical top-hat accretion pattern. More generally, the formalism makes it possible to give a complete characterization of the statistical properties of any random field generated from a discrete linear superposition of kernels. In particular, the results can be applied to density fields derived by smoothing a discrete set of points with a window function.

  7. Two-Component Noncollinear Time-Dependent Spin Density Functional Theory for Excited State Calculations.

    PubMed

    Egidi, Franco; Sun, Shichao; Goings, Joshua J; Scalmani, Giovanni; Frisch, Michael J; Li, Xiaosong

    2017-06-13

    We present a linear response formalism for the description of the electronic excitations of a noncollinear reference defined via Kohn-Sham spin density functional methods. A set of auxiliary variables, defined using the density and noncollinear magnetization density vector, allows the generalization of spin density functional kernels commonly used in collinear DFT to noncollinear cases, including local density, GGA, meta-GGA and hybrid functionals. Working equations and derivations of functional second derivatives with respect to the noncollinear density, required in the linear response noncollinear TDDFT formalism, are presented in this work. This formalism takes all components of the spin magnetization into account independent of the type of reference state (open or closed shell). As a result, the method introduced here is able to afford a nonzero local xc torque on the spin magnetization while still satisfying the zero-torque theorem globally. The formalism is applied to a few test cases using the variational exact-two-component reference including spin-orbit coupling to illustrate the capabilities of the method.

  8. Density Deconvolution With EPI Splines

    DTIC Science & Technology

    2015-09-01

    effects of various substances on test subjects [11], [12]. Whereas in geophysics, a shot may be fired into the ground, in pharmacokinetics, a signal is...be significant, including medicine, bioinformatics, chemistry, as- tronomy, and econometrics , as well as an extensive review of kernel based methods...demonstrate the effectiveness of our model in simulations motivated by test instances in [32]. We consider an additive measurement model scenario where

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

    Rao, N.S.V.

    The classical Nadaraya-Watson estimator is shown to solve a generic sensor fusion problem where the underlying sensor error densities are not known but a sample is available. By employing Haar kernels this estimator is shown to yield finite sample guarantees and also to be efficiently computable. Two simulation examples, and a robotics example involving the detection of a door using arrays of ultrasonic and infrared sensors, are presented to illustrate the performance.

  10. Nowcasting Cloud Fields for U.S. Air Force Special Operations

    DTIC Science & Technology

    2017-03-01

    application of Bayes’ Rule offers many advantages over Kernel Density Estimation (KDE) and other commonly used statistical post-processing methods...reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past...nowcasting, low cloud forecasting, cloud reflectance, ISR, Bayesian estimation, statistical post-processing, machine learning 15. NUMBER OF PAGES

  11. Using kernel density estimates to investigate lymphatic filariasis in northeast Brazil

    PubMed Central

    Medeiros, Zulma; Bonfim, Cristine; Brandão, Eduardo; Netto, Maria José Evangelista; Vasconcellos, Lucia; Ribeiro, Liany; Portugal, José Luiz

    2012-01-01

    After more than 10 years of the Global Program to Eliminate Lymphatic Filariasis (GPELF) in Brazil, advances have been seen, but the endemic disease persists as a public health problem. The aim of this study was to describe the spatial distribution of lymphatic filariasis in the municipality of Jaboatão dos Guararapes, Pernambuco, Brazil. An epidemiological survey was conducted in the municipality, and positive filariasis cases identified in this survey were georeferenced in point form, using the GPS. A kernel intensity estimator was applied to identify clusters with greater intensity of cases. We examined 23 673 individuals and 323 individuals with microfilaremia were identified, representing a mean prevalence rate of 1.4%. Around 88% of the districts surveyed presented cases of filarial infection, with prevalences of 0–5.6%. The male population was more affected by the infection, with 63.8% of the cases (P<0.005). Positive cases were found in all age groups examined. The kernel intensity estimator identified the areas of greatest intensity and least intensity of filarial infection cases. The case distribution was heterogeneous across the municipality. The kernel estimator identified spatial clusters of cases, thus indicating locations with greater intensity of transmission. The main advantage of this type of analysis lies in its ability to rapidly and easily show areas with the highest concentration of cases, thereby contributing towards planning, monitoring, and surveillance of filariasis elimination actions. Incorporation of geoprocessing and spatial analysis techniques constitutes an important tool for use within the GPELF. PMID:22943547

  12. QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

    NASA Astrophysics Data System (ADS)

    Bartolini, S.; Cappello, A.; Martí, J.; Del Negro, C.

    2013-11-01

    One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps (i.e., the spatial probability of a future vent opening given the past eruptive activity of a volcano). This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source geographic information system Quantum GIS, which is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows the selection of an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input data sets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

  13. MO-G-17A-06: Kernel Based Dosimetry for 90Y Microsphere Liver Therapy Using 90Y Bremsstrahlung SPECT/CT

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

    Mikell, J; Siman, W; Kappadath, S

    2014-06-15

    Purpose: 90Y microsphere therapy in liver presents a situation where beta transport is dominant and the tissue is relatively homogenous. We compare voxel-based absorbed doses from a 90Y kernel to Monte Carlo (MC) using quantitative 90Y bremsstrahlung SPECT/CT as source distribution. Methods: Liver, normal liver, and tumors were delineated by an interventional radiologist using contrast-enhanced CT registered with 90Y SPECT/CT scans for 14 therapies. Right lung was segmented via region growing. The kernel was generated with 1.04 g/cc soft tissue for 4.8 mm voxel matching the SPECT. MC simulation materials included air, lung, soft tissue, and bone with varying densities.more » We report percent difference between kernel and MC (%Δ(K,MC)) for mean absorbed dose, D70, and V20Gy in total liver, normal liver, tumors, and right lung. We also report %Δ(K,MC) for heterogeneity metrics: coefficient of variation (COV) and D10/D90. The impact of spatial resolution (0, 10, 20 mm FWHM) and lung shunt fraction (LSF) (1,5,10,20%) on the accuracy of MC and kernel doses near the liver-lung interface was modeled in 1D. We report the distance from the interface where errors become <10% of unblurred MC as d10(side of interface, dose calculation, FWHM blurring, LSF). Results: The %Δ(K,MC) for mean, D70, and V20Gy in tumor and liver was <7% while right lung differences varied from 60–90%. The %Δ(K,MC) for COV was <4.8% for tumor and liver and <54% for the right lung. The %Δ(K,MC) for D10/D90 was <5% for 22/23 tumors. d10(liver,MC,10,1–20) awere <9mm and d10(liver,MC,20,1–20) awere <15mm; both agreed within 3mm to the kernel. d10(lung,MC,10,20), d10(lung,MC,10,1), d10(lung,MC,20,20), and d10(lung,MC,20,1) awere 6, 25, 15, and 34mm, respectively. Kernel calculations on blurred distributions in lung had errors > 10%. Conclusions: Liver and tumor voxel doses with 90Y kernel and MC agree within 7%. Large differences exist between the two methods in right lung. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA138986. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less

  14. Inferring probabilistic stellar rotation periods using Gaussian processes

    NASA Astrophysics Data System (ADS)

    Angus, Ruth; Morton, Timothy; Aigrain, Suzanne; Foreman-Mackey, Daniel; Rajpaul, Vinesh

    2018-02-01

    Variability in the light curves of spotted, rotating stars is often non-sinusoidal and quasi-periodic - spots move on the stellar surface and have finite lifetimes, causing stellar flux variations to slowly shift in phase. A strictly periodic sinusoid therefore cannot accurately model a rotationally modulated stellar light curve. Physical models of stellar surfaces have many drawbacks preventing effective inference, such as highly degenerate or high-dimensional parameter spaces. In this work, we test an appropriate effective model: a Gaussian Process with a quasi-periodic covariance kernel function. This highly flexible model allows sampling of the posterior probability density function of the periodic parameter, marginalizing over the other kernel hyperparameters using a Markov Chain Monte Carlo approach. To test the effectiveness of this method, we infer rotation periods from 333 simulated stellar light curves, demonstrating that the Gaussian process method produces periods that are more accurate than both a sine-fitting periodogram and an autocorrelation function method. We also demonstrate that it works well on real data, by inferring rotation periods for 275 Kepler stars with previously measured periods. We provide a table of rotation periods for these and many more, altogether 1102 Kepler objects of interest, and their posterior probability density function samples. Because this method delivers posterior probability density functions, it will enable hierarchical studies involving stellar rotation, particularly those involving population modelling, such as inferring stellar ages, obliquities in exoplanet systems, or characterizing star-planet interactions. The code used to implement this method is available online.

  15. THREE-POINT PHASE CORRELATIONS: A NEW MEASURE OF NONLINEAR LARGE-SCALE STRUCTURE

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

    Wolstenhulme, Richard; Bonvin, Camille; Obreschkow, Danail

    2015-05-10

    We derive an analytical expression for a novel large-scale structure observable: the line correlation function. The line correlation function, which is constructed from the three-point correlation function of the phase of the density field, is a robust statistical measure allowing the extraction of information in the nonlinear and non-Gaussian regime. We show that, in perturbation theory, the line correlation is sensitive to the coupling kernel F{sub 2}, which governs the nonlinear gravitational evolution of the density field. We compare our analytical expression with results from numerical simulations and find a 1σ agreement for separations r ≳ 30 h{sup −1} Mpc.more » Fitting formulae for the power spectrum and the nonlinear coupling kernel at small scales allow us to extend our prediction into the strongly nonlinear regime, where we find a 1σ agreement with the simulations for r ≳ 2 h{sup −1} Mpc. We discuss the advantages of the line correlation relative to standard statistical measures like the bispectrum. Unlike the latter, the line correlation is independent of the bias, in the regime where the bias is local and linear. Furthermore, the variance of the line correlation is independent of the Gaussian variance on the modulus of the density field. This suggests that the line correlation can probe more precisely the nonlinear regime of gravity, with less contamination from the power spectrum variance.« less

  16. 7 CFR 810.802 - Definition of other terms.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...) Damaged kernels. Kernels and pieces of grain kernels for which standards have been established under the.... (d) Heat-damaged kernels. Kernels and pieces of grain kernels for which standards have been...

  17. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  18. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  19. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  20. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  1. A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

    PubMed

    Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

    2017-06-19

    A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

  2. Crop Loss Relationships and Economic Injury Levels for Ferrisia gilli (Hemiptera: Pseudococcidae) Infesting Pistachio in California.

    PubMed

    Haviland, David R; Beede, Robert H; Daane, Kent M

    2015-12-01

    Ferrisia gilli Gullan (Hemiptera: Pseudococcidae) is a new pest in California pistachios, Pistacea vera L. We conducted a 3-yr field study to determine the type and amount of damage caused by F. gilli. Using pesticides, we established gradients of F. gilli densities in a commercial pistachio orchard near Tipton, CA, from 2005 to 2007. Each year, mealybug densities on pistachio clusters were recorded from May through September and cumulative mealybug-days were determined. At harvest time, nut yield per tree (5% dried weight) was determined, and subsamples of nuts were evaluated for market quality. Linear regression analysis of cumulative mealybug-days against fruit yield and nut quality measurements showed no relationships in 2005 and 2006, when mealybug densities were moderate. However, in 2007, when mealybug densities were very high, there was a negative correlation with yield (for every 1,000 mealybug-days, there was a decrease in total dry weight per tree of 0.105 kg) and percentage of split unstained nuts (for every 1,000 mealybug-days, there was a decrease in the percentage of split unstained of 0.560%), and a positive correlation between the percentage of closed kernel and closed blank nuts (for every 1,000 mealybug-days, there is an increase in the percentage of closed kernel and closed blank of 0.176 and 0.283%, respectively). The data were used to determine economic injury levels, showing that for each mealybug per cluster in May there was a 4.73% reduction in crop value associated with quality and a 0.866 kg reduction in yield per tree (4.75%). © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. Classification With Truncated Distance Kernel.

    PubMed

    Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

    2018-05-01

    This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

  4. Production of Low Enriched Uranium Nitride Kernels for TRISO Particle Irradiation Testing

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

    McMurray, J. W.; Silva, C. M.; Helmreich, G. W.

    2016-06-01

    A large batch of UN microspheres to be used as kernels for TRISO particle fuel was produced using carbothermic reduction and nitriding of a sol-gel feedstock bearing tailored amounts of low-enriched uranium (LEU) oxide and carbon. The process parameters, established in a previous study, produced phasepure NaCl structure UN with dissolved C on the N sublattice. The composition, calculated by refinement of the lattice parameter from X-ray diffraction, was determined to be UC 0.27N 0.73. The final accepted product weighed 197.4 g. The microspheres had an average diameter of 797±1.35 μm and a composite mean theoretical density of 89.9±0.5% formore » a solid solution of UC and UN with the same atomic ratio; both values are reported with their corresponding calculated standard error.« less

  5. Is there a single best estimator? selection of home range estimators using area- under- the-curve

    USGS Publications Warehouse

    Walter, W. David; Onorato, Dave P.; Fischer, Justin W.

    2015-01-01

    Comparisons of fit of home range contours with locations collected would suggest that use of VHF technology is not as accurate as GPS technology to estimate size of home range for large mammals. Estimators of home range collected with GPS technology performed better than those estimated with VHF technology regardless of estimator used. Furthermore, estimators that incorporate a temporal component (third-generation estimators) appeared to be the most reliable regardless of whether kernel-based or Brownian bridge-based algorithms were used and in comparison to first- and second-generation estimators. We defined third-generation estimators of home range as any estimator that incorporates time, space, animal-specific parameters, and habitat. Such estimators would include movement-based kernel density, Brownian bridge movement models, and dynamic Brownian bridge movement models among others that have yet to be evaluated.

  6. Survival analysis for the missing censoring indicator model using kernel density estimation techniques

    PubMed Central

    Subramanian, Sundarraman

    2008-01-01

    This article concerns asymptotic theory for a new estimator of a survival function in the missing censoring indicator model of random censorship. Specifically, the large sample results for an inverse probability-of-non-missingness weighted estimator of the cumulative hazard function, so far not available, are derived, including an almost sure representation with rate for a remainder term, and uniform strong consistency with rate of convergence. The estimator is based on a kernel estimate for the conditional probability of non-missingness of the censoring indicator. Expressions for its bias and variance, in turn leading to an expression for the mean squared error as a function of the bandwidth, are also obtained. The corresponding estimator of the survival function, whose weak convergence is derived, is asymptotically efficient. A numerical study, comparing the performances of the proposed and two other currently existing efficient estimators, is presented. PMID:18953423

  7. Survival analysis for the missing censoring indicator model using kernel density estimation techniques.

    PubMed

    Subramanian, Sundarraman

    2006-01-01

    This article concerns asymptotic theory for a new estimator of a survival function in the missing censoring indicator model of random censorship. Specifically, the large sample results for an inverse probability-of-non-missingness weighted estimator of the cumulative hazard function, so far not available, are derived, including an almost sure representation with rate for a remainder term, and uniform strong consistency with rate of convergence. The estimator is based on a kernel estimate for the conditional probability of non-missingness of the censoring indicator. Expressions for its bias and variance, in turn leading to an expression for the mean squared error as a function of the bandwidth, are also obtained. The corresponding estimator of the survival function, whose weak convergence is derived, is asymptotically efficient. A numerical study, comparing the performances of the proposed and two other currently existing efficient estimators, is presented.

  8. A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

    PubMed Central

    Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

    2017-01-01

    A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. PMID:28629202

  9. Linkage disequilibrium, SNP frequency change due to selection, and association mapping in popcorn chromosome regions containing QTLs for quality traits

    PubMed Central

    Paes, Geísa Pinheiro; Viana, José Marcelo Soriano; Silva, Fabyano Fonseca e; Mundim, Gabriel Borges

    2016-01-01

    Abstract The objectives of this study were to assess linkage disequilibrium (LD) and selection-induced changes in single nucleotide polymorphism (SNP) frequency, and to perform association mapping in popcorn chromosome regions containing quantitative trait loci (QTLs) for quality traits. Seven tropical and two temperate popcorn populations were genotyped for 96 SNPs chosen in chromosome regions containing QTLs for quality traits. The populations were phenotyped for expansion volume, 100-kernel weight, kernel sphericity, and kernel density. The LD statistics were the difference between the observed and expected haplotype frequencies (D), the proportion of D relative to the expected maximum value in the population, and the square of the correlation between the values of alleles at two loci. Association mapping was based on least squares and Bayesian approaches. In the tropical populations, D-values greater than 0.10 were observed for SNPs separated by 100-150 Mb, while most of the D-values in the temperate populations were less than 0.05. Selection for expansion volume indirectly led to increase in LD values, population differentiation, and significant changes in SNP frequency. Some associations were observed for expansion volume and the other quality traits. The candidate genes are involved with starch, storage protein, lipid, and cell wall polysaccharides synthesis. PMID:27007903

  10. Linkage disequilibrium, SNP frequency change due to selection, and association mapping in popcorn chromosome regions containing QTLs for quality traits.

    PubMed

    Paes, Geísa Pinheiro; Viana, José Marcelo Soriano; Silva, Fabyano Fonseca E; Mundim, Gabriel Borges

    2016-03-01

    The objectives of this study were to assess linkage disequilibrium (LD) and selection-induced changes in single nucleotide polymorphism (SNP) frequency, and to perform association mapping in popcorn chromosome regions containing quantitative trait loci (QTLs) for quality traits. Seven tropical and two temperate popcorn populations were genotyped for 96 SNPs chosen in chromosome regions containing QTLs for quality traits. The populations were phenotyped for expansion volume, 100-kernel weight, kernel sphericity, and kernel density. The LD statistics were the difference between the observed and expected haplotype frequencies (D), the proportion of D relative to the expected maximum value in the population, and the square of the correlation between the values of alleles at two loci. Association mapping was based on least squares and Bayesian approaches. In the tropical populations, D-values greater than 0.10 were observed for SNPs separated by 100-150 Mb, while most of the D-values in the temperate populations were less than 0.05. Selection for expansion volume indirectly led to increase in LD values, population differentiation, and significant changes in SNP frequency. Some associations were observed for expansion volume and the other quality traits. The candidate genes are involved with starch, storage protein, lipid, and cell wall polysaccharides synthesis.

  11. Gabor-based kernel PCA with fractional power polynomial models for face recognition.

    PubMed

    Liu, Chengjun

    2004-05-01

    This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

  12. A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

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

    Sun, Ning; Yearsley, John; Voisin, Nathalie

    2015-05-15

    Stream temperatures in urban watersheds are influenced to a high degree by anthropogenic impacts related to changes in landscape, stream channel morphology, and climate. These impacts can occur at small time and length scales, hence require analytical tools that consider the influence of the hydrologic regime, energy fluxes, topography, channel morphology, and near-stream vegetation distribution. Here we describe a modeling system that integrates the Distributed Hydrologic Soil Vegetation Model, DHSVM, with the semi-Lagrangian stream temperature model RBM, which has the capability to simulate the hydrology and water temperature of urban streams at high time and space resolutions, as well asmore » a representation of the effects of riparian shading on stream energetics. We demonstrate the modeling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model is able both to produce realistic streamflow predictions at fine temporal and spatial scales, and to provide spatially distributed water temperature predictions that are consistent with observations throughout a complex stream network. We use the modeling construct to characterize impacts of land use change and near-stream vegetation change on stream temperature throughout the Mercer Creek system. We then explore the sensitivity of stream temperature to land use changes and modifications in vegetation along the riparian corridor.« less

  13. A multi-label learning based kernel automatic recommendation method for support vector machine.

    PubMed

    Zhang, Xueying; Song, Qinbao

    2015-01-01

    Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

  14. A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

    PubMed Central

    Zhang, Xueying; Song, Qinbao

    2015-01-01

    Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance. PMID:25893896

  15. 7 CFR 981.7 - Edible kernel.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible. [41 FR 26852, June 30, 1976] ...

  16. Kernel K-Means Sampling for Nyström Approximation.

    PubMed

    He, Li; Zhang, Hong

    2018-05-01

    A fundamental problem in Nyström-based kernel matrix approximation is the sampling method by which training set is built. In this paper, we suggest to use kernel -means sampling, which is shown in our works to minimize the upper bound of a matrix approximation error. We first propose a unified kernel matrix approximation framework, which is able to describe most existing Nyström approximations under many popular kernels, including Gaussian kernel and polynomial kernel. We then show that, the matrix approximation error upper bound, in terms of the Frobenius norm, is equal to the -means error of data points in kernel space plus a constant. Thus, the -means centers of data in kernel space, or the kernel -means centers, are the optimal representative points with respect to the Frobenius norm error upper bound. Experimental results, with both Gaussian kernel and polynomial kernel, on real-world data sets and image segmentation tasks show the superiority of the proposed method over the state-of-the-art methods.

  17. Resource-Constrained Spatial Hot Spot Identification

    DTIC Science & Technology

    2011-01-01

    into three categories ( Cameron and Leitner, 2005):2 Thematic Mapping. Concentrations of events are color-coded in discrete geo- graphic areas that...of Boston burglary events in 1999 and provided by Cameron and Leitner (2005). The first map reflects burglary rates per 100,000 residents by Census...Burglary Rates, 1999 RAND A8567-22 1 0 1 2 Miles Thematic mapping Kernel density interpolation Hierarchical clustering Source: Cameron and Leitner, 2005. For

  18. Kernel-density estimation and approximate Bayesian computation for flexible epidemiological model fitting in Python.

    PubMed

    Irvine, Michael A; Hollingsworth, T Déirdre

    2018-05-26

    Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  19. An Experimental Study of Briquetting Process of Torrefied Rubber Seed Kernel and Palm Oil Shell.

    PubMed

    Hamid, M Fadzli; Idroas, M Yusof; Ishak, M Zulfikar; Zainal Alauddin, Z Alimuddin; Miskam, M Azman; Abdullah, M Khalil

    2016-01-01

    Torrefaction process of biomass material is essential in converting them into biofuel with improved calorific value and physical strength. However, the production of torrefied biomass is loose, powdery, and nonuniform. One method of upgrading this material to improve their handling and combustion properties is by densification into briquettes of higher density than the original bulk density of the material. The effects of critical parameters of briquetting process that includes the type of biomass material used for torrefaction and briquetting, densification temperature, and composition of binder for torrefied biomass are studied and characterized. Starch is used as a binder in the study. The results showed that the briquette of torrefied rubber seed kernel (RSK) is better than torrefied palm oil shell (POS) in both calorific value and compressive strength. The best quality of briquettes is yielded from torrefied RSK at the ambient temperature of briquetting process with the composition of 60% water and 5% binder. The maximum compressive load for the briquettes of torrefied RSK is 141 N and the calorific value is 16 MJ/kg. Based on the economic evaluation analysis, the return of investment (ROI) for the mass production of both RSK and POS briquettes is estimated in 2-year period and the annual profit after payback was approximately 107,428.6 USD.

  20. Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process

    PubMed Central

    Galindo, I.; Romero, M. C.; Sánchez, N.; Morales, J. M.

    2016-01-01

    Risk management stakeholders in high-populated volcanic islands should be provided with the latest high-quality volcanic information. We present here the first volcanic susceptibility map of Lanzarote and Chinijo Islands and their submarine flanks based on updated chronostratigraphical and volcano structural data, as well as on the geomorphological analysis of the bathymetric data of the submarine flanks. The role of the structural elements in the volcanic susceptibility analysis has been reviewed: vents have been considered since they indicate where previous eruptions took place; eruptive fissures provide information about the stress field as they are the superficial expression of the dyke conduit; eroded dykes have been discarded since they are single non-feeder dykes intruded in deep parts of Miocene-Pliocene volcanic edifices; main faults have been taken into account only in those cases where they could modified the superficial movement of magma. The application of kernel density estimation via a linear diffusion process for the volcanic susceptibility assessment has been applied successfully to Lanzarote and could be applied to other fissure volcanic fields worldwide since the results provide information about the probable area where an eruption could take place but also about the main direction of the probable volcanic fissures. PMID:27265878

  1. Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process.

    PubMed

    Galindo, I; Romero, M C; Sánchez, N; Morales, J M

    2016-06-06

    Risk management stakeholders in high-populated volcanic islands should be provided with the latest high-quality volcanic information. We present here the first volcanic susceptibility map of Lanzarote and Chinijo Islands and their submarine flanks based on updated chronostratigraphical and volcano structural data, as well as on the geomorphological analysis of the bathymetric data of the submarine flanks. The role of the structural elements in the volcanic susceptibility analysis has been reviewed: vents have been considered since they indicate where previous eruptions took place; eruptive fissures provide information about the stress field as they are the superficial expression of the dyke conduit; eroded dykes have been discarded since they are single non-feeder dykes intruded in deep parts of Miocene-Pliocene volcanic edifices; main faults have been taken into account only in those cases where they could modified the superficial movement of magma. The application of kernel density estimation via a linear diffusion process for the volcanic susceptibility assessment has been applied successfully to Lanzarote and could be applied to other fissure volcanic fields worldwide since the results provide information about the probable area where an eruption could take place but also about the main direction of the probable volcanic fissures.

  2. Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process

    NASA Astrophysics Data System (ADS)

    Galindo, I.; Romero, M. C.; Sánchez, N.; Morales, J. M.

    2016-06-01

    Risk management stakeholders in high-populated volcanic islands should be provided with the latest high-quality volcanic information. We present here the first volcanic susceptibility map of Lanzarote and Chinijo Islands and their submarine flanks based on updated chronostratigraphical and volcano structural data, as well as on the geomorphological analysis of the bathymetric data of the submarine flanks. The role of the structural elements in the volcanic susceptibility analysis has been reviewed: vents have been considered since they indicate where previous eruptions took place; eruptive fissures provide information about the stress field as they are the superficial expression of the dyke conduit; eroded dykes have been discarded since they are single non-feeder dykes intruded in deep parts of Miocene-Pliocene volcanic edifices; main faults have been taken into account only in those cases where they could modified the superficial movement of magma. The application of kernel density estimation via a linear diffusion process for the volcanic susceptibility assessment has been applied successfully to Lanzarote and could be applied to other fissure volcanic fields worldwide since the results provide information about the probable area where an eruption could take place but also about the main direction of the probable volcanic fissures.

  3. Effect of Aspergillus niger xylanase on dough characteristics and bread quality attributes.

    PubMed

    Ahmad, Zulfiqar; Butt, Masood Sadiq; Ahmed, Anwaar; Riaz, Muhammad; Sabir, Syed Mubashar; Farooq, Umar; Rehman, Fazal Ur

    2014-10-01

    The present study was conducted to investigate the impact of various treatments of xylanase produced by Aspergillus niger applied in bread making processes like during tempering of wheat kernels and dough mixing on the dough quality characteristics i.e. dryness, stiffness, elasticity, extensibility, coherency and bread quality parameters i.e. volume, specific volume, density, moisture retention and sensory attributes. Different doses (200, 400, 600, 800 and 1,000 IU) of purified enzyme were applied to 1 kg of wheat grains during tempering and 1 kg of flour (straight grade flour) during mixing of dough in parallel. The samples of wheat kernels were agitated at different intervals for uniformity in tempering. After milling and dough making of both types of flour (having enzyme treatment during tempering and flour mixing) showed improved dough characteristics but the improvement was more prominent in the samples receiving enzyme treatment during tempering. Moreover, xylanase decreased dryness and stiffness of the dough whereas, resulted in increased elasticity, extensibility and coherency and increase in volume & decrease in bread density. Xylanase treatments also resulted in higher moisture retention and improvement of sensory attributes of bread. From the results, it is concluded that dough characteristics and bread quality improved significantly in response to enzyme treatments during tempering as compared to application during mixing.

  4. Food Environment and Weight Change: Does Residential Mobility Matter?

    PubMed Central

    Laraia, Barbara A.; Downing, Janelle M.; Zhang, Y. Tara; Dow, William H.; Kelly, Maggi; Blanchard, Samuel D.; Adler, Nancy; Schillinger, Dean; Moffet, Howard; Warton, E. Margaret; Karter, Andrew J.

    2017-01-01

    Abstract Associations between neighborhood food environment and adult body mass index (BMI; weight (kg)/height (m)2) derived using cross-sectional or longitudinal random-effects models may be biased due to unmeasured confounding and measurement and methodological limitations. In this study, we assessed the within-individual association between change in food environment from 2006 to 2011 and change in BMI among adults with type 2 diabetes using clinical data from the Kaiser Permanente Diabetes Registry collected from 2007 to 2011. Healthy food environment was measured using the kernel density of healthful food venues. Fixed-effects models with a 1-year-lagged BMI were estimated. Separate models were fitted for persons who moved and those who did not. Sensitivity analysis using different lag times and kernel density bandwidths were tested to establish the consistency of findings. On average, patients lost 1 pound (0.45 kg) for each standard-deviation improvement in their food environment. This relationship held for persons who remained in the same location throughout the 5-year study period but not among persons who moved. Proximity to food venues that promote nutritious foods alone may not translate into clinically meaningful diet-related health changes. Community-level policies for improving the food environment need multifaceted strategies to invoke clinically meaningful change in BMI among adult patients with diabetes. PMID:28387785

  5. Exploiting graph kernels for high performance biomedical relation extraction.

    PubMed

    Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

    2018-01-30

    Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM performed better than APG kernel for the BioInfer dataset, in the Area Under Curve (AUC) measure (74% vs 69%). However, for all the other PPI datasets, namely AIMed, HPRD50, IEPA and LLL, ASM is substantially outperformed by the APG kernel in F-score and AUC measures. We demonstrate a high performance Chemical Induced Disease relation extraction, without employing external knowledge sources or task specific heuristics. Our work shows that graph kernels are effective in extracting relations that are expressed in multiple sentences. We also show that the graph kernels, namely the ASM and APG kernels, substantially outperform the tree kernels. Among the graph kernels, we showed the ASM kernel as effective for biomedical relation extraction, with comparable performance to the APG kernel for datasets such as the CID-sentence level relation extraction and BioInfer in PPI. Overall, the APG kernel is shown to be significantly more accurate than the ASM kernel, achieving better performance on most datasets.

  6. Brownian motion of a nano-colloidal particle: the role of the solvent.

    PubMed

    Torres-Carbajal, Alexis; Herrera-Velarde, Salvador; Castañeda-Priego, Ramón

    2015-07-15

    Brownian motion is a feature of colloidal particles immersed in a liquid-like environment. Usually, it can be described by means of the generalised Langevin equation (GLE) within the framework of the Mori theory. In principle, all quantities that appear in the GLE can be calculated from the molecular information of the whole system, i.e., colloids and solvent molecules. In this work, by means of extensive Molecular Dynamics simulations, we study the effects of the microscopic details and the thermodynamic state of the solvent on the movement of a single nano-colloid. In particular, we consider a two-dimensional model system in which the mass and size of the colloid are two and one orders of magnitude, respectively, larger than the ones associated with the solvent molecules. The latter ones interact via a Lennard-Jones-type potential to tune the nature of the solvent, i.e., it can be either repulsive or attractive. We choose the linear momentum of the Brownian particle as the observable of interest in order to fully describe the Brownian motion within the Mori framework. We particularly focus on the colloid diffusion at different solvent densities and two temperature regimes: high and low (near the critical point) temperatures. To reach our goal, we have rewritten the GLE as a second kind Volterra integral in order to compute the memory kernel in real space. With this kernel, we evaluate the momentum-fluctuating force correlation function, which is of particular relevance since it allows us to establish when the stationarity condition has been reached. Our findings show that even at high temperatures, the details of the attractive interaction potential among solvent molecules induce important changes in the colloid dynamics. Additionally, near the critical point, the dynamical scenario becomes more complex; all the correlation functions decay slowly in an extended time window, however, the memory kernel seems to be only a function of the solvent density. Thus, the explicit inclusion of the solvent in the description of Brownian motion allows us to better understand the behaviour of the memory kernel at those thermodynamic states near the critical region without any further approximation. This information is useful to elaborate more realistic descriptions of Brownian motion that take into account the particular details of the host medium.

  7. 7 CFR 810.2202 - Definition of other terms.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... kernels, foreign material, and shrunken and broken kernels. The sum of these three factors may not exceed... the removal of dockage and shrunken and broken kernels. (g) Heat-damaged kernels. Kernels, pieces of... sample after the removal of dockage and shrunken and broken kernels. (h) Other grains. Barley, corn...

  8. 7 CFR 981.8 - Inedible kernel.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel, or...

  9. 7 CFR 51.1415 - Inedible kernels.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Inedible kernels. 51.1415 Section 51.1415 Agriculture... Standards for Grades of Pecans in the Shell 1 Definitions § 51.1415 Inedible kernels. Inedible kernels means that the kernel or pieces of kernels are rancid, moldy, decayed, injured by insects or otherwise...

  10. An Approximate Approach to Automatic Kernel Selection.

    PubMed

    Ding, Lizhong; Liao, Shizhong

    2016-02-02

    Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

  11. Unconventional protein sources: apricot seed kernels.

    PubMed

    Gabrial, G N; El-Nahry, F I; Awadalla, M Z; Girgis, S M

    1981-09-01

    Hamawy apricot seed kernels (sweet), Amar apricot seed kernels (bitter) and treated Amar apricot kernels (bitterness removed) were evaluated biochemically. All kernels were found to be high in fat (42.2--50.91%), protein (23.74--25.70%) and fiber (15.08--18.02%). Phosphorus, calcium, and iron were determined in all experimental samples. The three different apricot seed kernels were used for extensive study including the qualitative determination of the amino acid constituents by acid hydrolysis, quantitative determination of some amino acids, and biological evaluation of the kernel proteins in order to use them as new protein sources. Weanling albino rats failed to grow on diets containing the Amar apricot seed kernels due to low food consumption because of its bitterness. There was no loss in weight in that case. The Protein Efficiency Ratio data and blood analysis results showed the Hamawy apricot seed kernels to be higher in biological value than treated apricot seed kernels. The Net Protein Ratio data which accounts for both weight, maintenance and growth showed the treated apricot seed kernels to be higher in biological value than both Hamawy and Amar kernels. The Net Protein Ratio for the last two kernels were nearly equal.

  12. An introduction to kernel-based learning algorithms.

    PubMed

    Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

    2001-01-01

    This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

  13. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as...

  14. Design of CT reconstruction kernel specifically for clinical lung imaging

    NASA Astrophysics Data System (ADS)

    Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

    2005-04-01

    In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

  15. Quality changes in macadamia kernel between harvest and farm-gate.

    PubMed

    Walton, David A; Wallace, Helen M

    2011-02-01

    Macadamia integrifolia, Macadamia tetraphylla and their hybrids are cultivated for their edible kernels. After harvest, nuts-in-shell are partially dried on-farm and sorted to eliminate poor-quality kernels before consignment to a processor. During these operations, kernel quality may be lost. In this study, macadamia nuts-in-shell were sampled at five points of an on-farm postharvest handling chain from dehusking to the final storage silo to assess quality loss prior to consignment. Shoulder damage, weight of pieces and unsound kernel were assessed for raw kernels, and colour, mottled colour and surface damage for roasted kernels. Shoulder damage, weight of pieces and unsound kernel for raw kernels increased significantly between the dehusker and the final silo. Roasted kernels displayed a significant increase in dark colour, mottled colour and surface damage during on-farm handling. Significant loss of macadamia kernel quality occurred on a commercial farm during sorting and storage of nuts-in-shell before nuts were consigned to a processor. Nuts-in-shell should be dried as quickly as possible and on-farm handling minimised to maintain optimum kernel quality. 2010 Society of Chemical Industry.

  16. Effect of fat replacement by inulin or lupin-kernel fibre on sausage patty acceptability, post-meal perceptions of satiety and food intake in men.

    PubMed

    Archer, Bridie J; Johnson, Stuart K; Devereux, Helen M; Baxter, Amynta L

    2004-04-01

    The present study examined whether replacing fat with inulin or lupin-kernel fibre influenced palatability, perceptions of satiety, and food intake in thirty-three healthy men (mean age 52 years, BMI 27.4 kg/m(2)), using a within-subject design. On separate occasions, after fasting overnight, the participants consumed a breakfast consisting primarily of either a full-fat sausage patty (FFP) or a reduced-fat patty containing inulin (INP) or lupin-kernel fibre (LKP). Breakfast variants were alike in mass, protein and carbohydrate content; however the INP and LKP breakfasts were 36 and 37 % lower in fat and 15 and 17 % lower in energy density respectively compared with the FFP breakfast. The participants rated their satiety before breakfast then evaluated patty acceptability. Satiety was rated immediately after consuming the breakfast, then over the subsequent 4.5 h whilst fasting. Food consumed until the end of the following day was recorded. All patties were rated above 'neither acceptable or unacceptable', however the INP rated lower for general acceptability (P=0.039) and the LKP lower for flavour (P=0.023) than the FFP. The LKP breakfast rated more satiating than the INP (P=0.010) and FFP (P=0.016) breakfasts. Total fat intake was 18 g lower on the day of the INP (P=0.035) and 26 g lower on the day of the LKP breakfast (P=0.013) than the FFP breakfast day. Energy intake was lower (1521 kJ) only on the day of the INP breakfast (P=0.039). Both inulin and lupin-kernel fibre appear to have potential as fat replacers in meat products and for reducing fat and energy intake in men.

  17. Ultralow dose dentomaxillofacial CT imaging and iterative reconstruction techniques: variability of Hounsfield units and contrast-to-noise ratio

    PubMed Central

    Bischel, Alexander; Stratis, Andreas; Kakar, Apoorv; Bosmans, Hilde; Jacobs, Reinhilde; Gassner, Eva-Maria; Puelacher, Wolfgang; Pauwels, Ruben

    2016-01-01

    Objective: The aim of this study was to evaluate whether application of ultralow dose protocols and iterative reconstruction technology (IRT) influence quantitative Hounsfield units (HUs) and contrast-to-noise ratio (CNR) in dentomaxillofacial CT imaging. Methods: A phantom with inserts of five types of materials was scanned using protocols for (a) a clinical reference for navigated surgery (CT dose index volume 36.58 mGy), (b) low-dose sinus imaging (18.28 mGy) and (c) four ultralow dose imaging (4.14, 2.63, 0.99 and 0.53 mGy). All images were reconstructed using: (i) filtered back projection (FBP); (ii) IRT: adaptive statistical iterative reconstruction-50 (ASIR-50), ASIR-100 and model-based iterative reconstruction (MBIR); and (iii) standard (std) and bone kernel. Mean HU, CNR and average HU error after recalibration were determined. Each combination of protocols was compared using Friedman analysis of variance, followed by Dunn's multiple comparison test. Results: Pearson's sample correlation coefficients were all >0.99. Ultralow dose protocols using FBP showed errors of up to 273 HU. Std kernels had less HU variability than bone kernels. MBIR reduced the error value for the lowest dose protocol to 138 HU and retained the highest relative CNR. ASIR could not demonstrate significant advantages over FBP. Conclusions: Considering a potential dose reduction as low as 1.5% of a std protocol, ultralow dose protocols and IRT should be further tested for clinical dentomaxillofacial CT imaging. Advances in knowledge: HU as a surrogate for bone density may vary significantly in CT ultralow dose imaging. However, use of std kernels and MBIR technology reduce HU error values and may retain the highest CNR. PMID:26859336

  18. A new discriminative kernel from probabilistic models.

    PubMed

    Tsuda, Koji; Kawanabe, Motoaki; Rätsch, Gunnar; Sonnenburg, Sören; Müller, Klaus-Robert

    2002-10-01

    Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived; from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

  19. Fast and accurate Voronoi density gridding from Lagrangian hydrodynamics data

    NASA Astrophysics Data System (ADS)

    Petkova, Maya A.; Laibe, Guillaume; Bonnell, Ian A.

    2018-01-01

    Voronoi grids have been successfully used to represent density structures of gas in astronomical hydrodynamics simulations. While some codes are explicitly built around using a Voronoi grid, others, such as Smoothed Particle Hydrodynamics (SPH), use particle-based representations and can benefit from constructing a Voronoi grid for post-processing their output. So far, calculating the density of each Voronoi cell from SPH data has been done numerically, which is both slow and potentially inaccurate. This paper proposes an alternative analytic method, which is fast and accurate. We derive an expression for the integral of a cubic spline kernel over the volume of a Voronoi cell and link it to the density of the cell. Mass conservation is ensured rigorously by the procedure. The method can be applied more broadly to integrate a spherically symmetric polynomial function over the volume of a random polyhedron.

  20. Habitat suitability criteria via parametric distributions: estimation, model selection and uncertainty

    USGS Publications Warehouse

    Som, Nicholas A.; Goodman, Damon H.; Perry, Russell W.; Hardy, Thomas B.

    2016-01-01

    Previous methods for constructing univariate habitat suitability criteria (HSC) curves have ranged from professional judgement to kernel-smoothed density functions or combinations thereof. We present a new method of generating HSC curves that applies probability density functions as the mathematical representation of the curves. Compared with previous approaches, benefits of our method include (1) estimation of probability density function parameters directly from raw data, (2) quantitative methods for selecting among several candidate probability density functions, and (3) concise methods for expressing estimation uncertainty in the HSC curves. We demonstrate our method with a thorough example using data collected on the depth of water used by juvenile Chinook salmon (Oncorhynchus tschawytscha) in the Klamath River of northern California and southern Oregon. All R code needed to implement our example is provided in the appendix. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  1. Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

    PubMed

    Kwak, Nojun

    2016-05-20

    Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

  2. Increasing accuracy of dispersal kernels in grid-based population models

    USGS Publications Warehouse

    Slone, D.H.

    2011-01-01

    Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels (σ > 10 cells), the total kernel error was <10 &sup-11; compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10-11 and invasion time error to <5%.

  3. UTM Technical Capabilities Level 2 (TLC2) Test at Reno-Stead Airport.

    NASA Image and Video Library

    2016-10-06

    Test of Unmanned Aircraft Systems Traffic Management (UTM) technical capability Level 2 (TCL2) at Reno-Stead Airport, Nevada. During the test, five drones simultaneously crossed paths, separated by altitude. Two drones flew beyond visual line-of-sight and three flew within line-of-sight of their operators. Engineers Priya Venkatesan and Joey Mercer review flight paths using the UAS traffic management research platform at flight operations mission control at NASA’s UTM TCL2 test.

  4. 8. Historic view of the building: 'Warren Street from State ...

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

    8. Historic view of the building: 'Warren Street from State Street' ca. 1890. Courtesy of the Trenton Free Public Library. This shows the building before the True American's renovations of 1893. It is the three-story buildings, flanked by lower ones in the middle of the block. At the time of the photograph, the brick exterior was painted a light color and dark-colored louvered shutters flanked all the upper story windows. - 14 North Warren Street (Commercial Building), True American Building, Trenton, Mercer County, NJ

  5. KPMG Peat Marwick LLP Corporation of Mercer University Fiscal Year Ended June 30, 1995

    DTIC Science & Technology

    1997-06-11

    The objective of a quality control review is to ensure that the audit was conducted in accordance with applicable standards and meets the auditing...requirements of the OMB Circular A-133. We conducted a quality control review of the audit working papers. We focused our review on the following...qualitative aspects of the audit : due professional care, planning, supervision, independence, quality control, internal controls, substantive testing, general and specific compliance testing, and the Schedule of Federal Awards.

  6. National Dam Safety Program. Stony Brook Watershed Dam Site Number 7 (NJ00344), Raritan River Basin, Stony Brook, Mercer County, New Jersey. Phase 1 Inspection Report.

    DTIC Science & Technology

    1980-02-01

    for Permit for Construction and Repair of Dam" filed on March 16, 1959. f. Design and Construction History Design data on file with NJDEP include: 1...LAr- Us a-2. hr’s. LA9~ WATF=R? SiQ_~~- SL- !E q VOL ( YFv - mcA>-) (Acmr-- =T.) 2o4~ 2-Ito STORCH ENGINEERS shootL... of 11. Project FmnnK Wmr=X---A-1

  7. 10. Historic view of the building: 'Warren Street from State ...

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

    10. Historic view of the building: 'Warren Street from State Street' ca. 1893. Courtesy of Trenton Free Public Library. 2-6 East State Street is to the right of the image, with the sign for a dentist prominent on the corner. The mass of wires entering the fourth floor window suggests the location of the Western Union Telegraph Office in the building. - 2-6 East State Street (Commercial Building), 2-6 East State Street, Trenton, Mercer County, NJ

  8. Summary of Federal Aviation Administration Responses to National Transportation Safety Board Safety Recommendations.

    DTIC Science & Technology

    1981-10-01

    Company never was a supplier of engine air inlet system for their company and was not an * approved vendor for Cessna. However, owners/operators can and...Citation, N501GP, accident 65 at Mercer County Airport, Bluefield West Virginia on January 21, 1981 A-81-69 Continental Oil Company Lear 72 Model 25...The switches are located in an area where they can be damaged by service carts or accidently activated by a flight attendant while trying to remove a

  9. Anthraquinones isolated from the browned Chinese chestnut kernels (Castanea mollissima blume)

    NASA Astrophysics Data System (ADS)

    Zhang, Y. L.; Qi, J. H.; Qin, L.; Wang, F.; Pang, M. X.

    2016-08-01

    Anthraquinones (AQS) represent a group of secondary metallic products in plants. AQS are often naturally occurring in plants and microorganisms. In a previous study, we found that AQS were produced by enzymatic browning reaction in Chinese chestnut kernels. To find out whether non-enzymatic browning reaction in the kernels could produce AQS too, AQS were extracted from three groups of chestnut kernels: fresh kernels, non-enzymatic browned kernels, and browned kernels, and the contents of AQS were determined. High performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) methods were used to identify two compounds of AQS, rehein(1) and emodin(2). AQS were barely exists in the fresh kernels, while both browned kernel groups sample contained a high amount of AQS. Thus, we comfirmed that AQS could be produced during both enzymatic and non-enzymatic browning process. Rhein and emodin were the main components of AQS in the browned kernels.

  10. Broken rice kernels and the kinetics of rice hydration and texture during cooking.

    PubMed

    Saleh, Mohammed; Meullenet, Jean-Francois

    2013-05-01

    During rice milling and processing, broken kernels are inevitably present, although to date it has been unclear as to how the presence of broken kernels affects rice hydration and cooked rice texture. Therefore, this work intended to study the effect of broken kernels in a rice sample on rice hydration and texture during cooking. Two medium-grain and two long-grain rice cultivars were harvested, dried and milled, and the broken kernels were separated from unbroken kernels. Broken rice kernels were subsequently combined with unbroken rice kernels forming treatments of 0, 40, 150, 350 or 1000 g kg(-1) broken kernels ratio. Rice samples were then cooked and the moisture content of the cooked rice, the moisture uptake rate, and rice hardness and stickiness were measured. As the amount of broken rice kernels increased, rice sample texture became increasingly softer (P < 0.05) but the unbroken kernels became significantly harder. Moisture content and moisture uptake rate were positively correlated, and cooked rice hardness was negatively correlated to the percentage of broken kernels in rice samples. Differences in the proportions of broken rice in a milled rice sample play a major role in determining the texture properties of cooked rice. Variations in the moisture migration kinetics between broken and unbroken kernels caused faster hydration of the cores of broken rice kernels, with greater starch leach-out during cooking affecting the texture of the cooked rice. The texture of cooked rice can be controlled, to some extent, by varying the proportion of broken kernels in milled rice. © 2012 Society of Chemical Industry.

  11. Local and linear chemical reactivity response functions at finite temperature in density functional theory

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

    Franco-Pérez, Marco, E-mail: francopj@mcmaster.ca, E-mail: ayers@mcmaster.ca, E-mail: jlgm@xanum.uam.mx, E-mail: avela@cinvestav.mx; Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, Av. San Rafael Atlixco 186, México, D.F. 09340; Ayers, Paul W., E-mail: francopj@mcmaster.ca, E-mail: ayers@mcmaster.ca, E-mail: jlgm@xanum.uam.mx, E-mail: avela@cinvestav.mx

    2015-12-28

    We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dualmore » descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model.« less

  12. Local and linear chemical reactivity response functions at finite temperature in density functional theory.

    PubMed

    Franco-Pérez, Marco; Ayers, Paul W; Gázquez, José L; Vela, Alberto

    2015-12-28

    We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dual descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model.

  13. A climatological model of North Indian Ocean tropical cyclone genesis, tracks and landfall

    NASA Astrophysics Data System (ADS)

    Wahiduzzaman, Mohammad; Oliver, Eric C. J.; Wotherspoon, Simon J.; Holbrook, Neil J.

    2017-10-01

    Extensive damage and loss of life can be caused by tropical cyclones (TCs) that make landfall. Modelling of TC landfall probability is beneficial to insurance/re-insurance companies, decision makers, government policy and planning, and residents in coastal areas. In this study, we develop a climatological model of tropical cyclone genesis, tracks and landfall for North Indian Ocean (NIO) rim countries based on kernel density estimation, a generalised additive model (GAM) including an Euler integration step, and landfall detection using a country mask approach. Using a 35-year record (1979-2013) of tropical cyclone track observations from the Joint Typhoon Warning Centre (part of the International Best Track Archive Climate Stewardship Version 6), the GAM is fitted to the observed cyclone track velocities as a smooth function of location in each season. The distribution of cyclone genesis points is approximated by kernel density estimation. The model simulated TCs are randomly selected from the fitted kernel (TC genesis), and the cyclone paths (TC tracks), represented by the GAM together with the application of stochastic innovations at each step, are simulated to generate a suite of NIO rim landfall statistics. Three hindcast validation methods are applied to evaluate the integrity of the model. First, leave-one-out cross validation is applied whereby the country of landfall is determined by the majority vote (considering the location by only highest percentage of landfall) from the simulated tracks. Second, the probability distribution of simulated landfall is evaluated against the observed landfall. Third, the distances between the point of observed landfall and simulated landfall are compared and quantified. Overall, the model shows very good cross-validated hindcast skill of modelled landfalling cyclones against observations in each of the NIO tropical cyclone seasons and for most NIO rim countries, with only a relatively small difference in the percentage of predicted landfall locations compared with observations.

  14. EnviroAtlas - New York, NY - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  15. EnviroAtlas - Paterson, NJ - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  16. EnviroAtlas - Fresno, CA - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  17. EnviroAtlas - Green Bay, WI - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  18. EnviroAtlas - Des Moines, IA - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  19. EnviroAtlas - Minneapolis/St. Paul, MN - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  20. EnviroAtlas - Woodbine, IA - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  1. EnviroAtlas - Phoenix, AZ - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  2. EnviroAtlas - Pittsburgh, PA - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  3. EnviroAtlas - New Bedford, MA - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  4. EnviroAtlas - Milwaukee, WI - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  5. EnviroAtlas - Austin, TX - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  6. Nonparametric Density Estimation Based on Self-Organizing Incremental Neural Network for Large Noisy Data.

    PubMed

    Nakamura, Yoshihiro; Hasegawa, Osamu

    2017-01-01

    With the ongoing development and expansion of communication networks and sensors, massive amounts of data are continuously generated in real time from real environments. Beforehand, prediction of a distribution underlying such data is difficult; furthermore, the data include substantial amounts of noise. These factors make it difficult to estimate probability densities. To handle these issues and massive amounts of data, we propose a nonparametric density estimator that rapidly learns data online and has high robustness. Our approach is an extension of both kernel density estimation (KDE) and a self-organizing incremental neural network (SOINN); therefore, we call our approach KDESOINN. An SOINN provides a clustering method that learns about the given data as networks of prototype of data; more specifically, an SOINN can learn the distribution underlying the given data. Using this information, KDESOINN estimates the probability density function. The results of our experiments show that KDESOINN outperforms or achieves performance comparable to the current state-of-the-art approaches in terms of robustness, learning time, and accuracy.

  7. EnviroAtlas - Cleveland, OH - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  8. EnviroAtlas - Portland, ME - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  9. EnviroAtlas - Portland, OR - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  10. EnviroAtlas - Durham, NC - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  11. EnviroAtlas - Tampa, FL - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  12. EnviroAtlas - Memphis, TN - Estimated Intersection Density of Walkable Roads

    EPA Pesticide Factsheets

    This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  13. Nonlinear Deep Kernel Learning for Image Annotation.

    PubMed

    Jiu, Mingyuan; Sahbi, Hichem

    2017-02-08

    Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

  14. Multineuron spike train analysis with R-convolution linear combination kernel.

    PubMed

    Tezuka, Taro

    2018-06-01

    A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Study on Energy Productivity Ratio (EPR) at palm kernel oil processing factory: case study on PT-X at Sumatera Utara Plantation

    NASA Astrophysics Data System (ADS)

    Haryanto, B.; Bukit, R. Br; Situmeang, E. M.; Christina, E. P.; Pandiangan, F.

    2018-02-01

    The purpose of this study was to determine the performance, productivity and feasibility of the operation of palm kernel processing plant based on Energy Productivity Ratio (EPR). EPR is expressed as the ratio of output to input energy and by-product. Palm Kernel plan is process in palm kernel to become palm kernel oil. The procedure started from collecting data needed as energy input such as: palm kernel prices, energy demand and depreciation of the factory. The energy output and its by-product comprise the whole production price such as: palm kernel oil price and the remaining products such as shells and pulp price. Calculation the equality of energy of palm kernel oil is to analyze the value of Energy Productivity Ratio (EPR) bases on processing capacity per year. The investigation has been done in Kernel Oil Processing Plant PT-X at Sumatera Utara plantation. The value of EPR was 1.54 (EPR > 1), which indicated that the processing of palm kernel into palm kernel oil is feasible to be operated based on the energy productivity.

  16. Rain Splash Dispersal of Gibberella zeae Within Wheat Canopies in Ohio.

    PubMed

    Paul, P A; El-Allaf, S M; Lipps, P E; Madden, L V

    2004-12-01

    ABSTRACT Rain splash dispersal of Gibberella zeae, causal agent of Fusarium head blight of wheat, was investigated in field studies in Ohio between 2001 and 2003. Samplers placed at 0, 30, and 100 cm above the soil surface were used to collect rain splash in wheat fields with maize residue on the surface and fields with G. zeae-infested maize kernels. Rain splash was collected during separate rain episodes throughout the wheat-growing seasons. Aliquots of splashed rain were transferred to petri dishes containing Komada's selective medium, and G. zeae was identified based on colony and spore morphology. Dispersed spores were measured in CFU/ml. Intensity of splashed rain was highest at 100 cm and ranged from 0.2 to 10.2 mm h(-1), depending on incident rain intensity and sampler height. Spores were recovered from splash samples at all heights in both locations for all sampled rain events. Both macroconidia and ascospores were found based on microscopic examination of random samples of splashed rain. Spore density and spore flux density per rain episode ranged from 0.4 to 40.9 CFU cm(-2) and 0.4 to 84.8 CFU cm(-2) h(-1), respectively. Spore flux density was higher in fields with G. zeae-infested maize kernels than in fields with maize debris, and generally was higher at 0 and 30 cm than at 100 cm at both locations. However, on average, spore flux density was only 30% lower at 100 cm (height of wheat spikes) than at the other heights. The log of spore flux density was linearly related to the log of splashed rain intensity and the log of incident rain intensity. The regression slopes were not significantly affected by year, location, height, and their interactions, but the intercepts were significantly affected by both sampler height and location. Thus, our results show that spores of G. zeae were consistently splash dispersed to spike heights within wheat canopies, and splashed rain intensity and spore flux density could be predicted based on incident rain intensity in order to estimate inoculum dispersal within the wheat canopy.

  17. Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

    PubMed Central

    2013-01-01

    Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

  18. 7 CFR 981.9 - Kernel weight.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels, including...

  19. An SVM model with hybrid kernels for hydrological time series

    NASA Astrophysics Data System (ADS)

    Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

    2017-12-01

    Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

  20. Norm overlap between many-body states: Uncorrelated overlap between arbitrary Bogoliubov product states

    NASA Astrophysics Data System (ADS)

    Bally, B.; Duguet, T.

    2018-02-01

    Background: State-of-the-art multi-reference energy density functional calculations require the computation of norm overlaps between different Bogoliubov quasiparticle many-body states. It is only recently that the efficient and unambiguous calculation of such norm kernels has become available under the form of Pfaffians [L. M. Robledo, Phys. Rev. C 79, 021302 (2009), 10.1103/PhysRevC.79.021302]. Recently developed particle-number-restored Bogoliubov coupled-cluster (PNR-BCC) and particle-number-restored Bogoliubov many-body perturbation (PNR-BMBPT) ab initio theories [T. Duguet and A. Signoracci, J. Phys. G 44, 015103 (2017), 10.1088/0954-3899/44/1/015103] make use of generalized norm kernels incorporating explicit many-body correlations. In PNR-BCC and PNR-BMBPT, the Bogoliubov states involved in the norm kernels differ specifically via a global gauge rotation. Purpose: The goal of this work is threefold. We wish (i) to propose and implement an alternative to the Pfaffian method to compute unambiguously the norm overlap between arbitrary Bogoliubov quasiparticle states, (ii) to extend the first point to explicitly correlated norm kernels, and (iii) to scrutinize the analytical content of the correlated norm kernels employed in PNR-BMBPT. Point (i) constitutes the purpose of the present paper while points (ii) and (iii) are addressed in a forthcoming paper. Methods: We generalize the method used in another work [T. Duguet and A. Signoracci, J. Phys. G 44, 015103 (2017), 10.1088/0954-3899/44/1/015103] in such a way that it is applicable to kernels involving arbitrary pairs of Bogoliubov states. The formalism is presently explicated in detail in the case of the uncorrelated overlap between arbitrary Bogoliubov states. The power of the method is numerically illustrated and benchmarked against known results on the basis of toy models of increasing complexity. Results: The norm overlap between arbitrary Bogoliubov product states is obtained under a closed-form expression allowing its computation without any phase ambiguity. The formula is physically intuitive, accurate, and versatile. It equally applies to norm overlaps between Bogoliubov states of even or odd number parity. Numerical applications illustrate these features and provide a transparent representation of the content of the norm overlaps. Conclusions: The complex norm overlap between arbitrary Bogoliubov states is computed, without any phase ambiguity, via elementary linear algebra operations. The method can be used in any configuration mixing of orthogonal and non-orthogonal product states. Furthermore, the closed-form expression extends naturally to correlated overlaps at play in PNR-BCC and PNR-BMBPT. As such, the straight overlap between Bogoliubov states is the zero-order reduction of more involved norm kernels to be studied in a forthcoming paper.

  1. Approximate kernel competitive learning.

    PubMed

    Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

    2015-03-01

    Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Multiple kernels learning-based biological entity relationship extraction method.

    PubMed

    Dongliang, Xu; Jingchang, Pan; Bailing, Wang

    2017-09-20

    Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the most authoritative textual database in the field of biomedicine, and follow an exponential growth over time. This frantic expansion of the biomedical literature can often be difficult to absorb or manually analyze. Thus efficient and automated search engines are necessary to efficiently explore the biomedical literature using text mining techniques. The P, R, and F value of tag graph method in Aimed corpus are 50.82, 69.76, and 58.61%, respectively. The P, R, and F value of tag graph kernel method in other four evaluation corpuses are 2-5% higher than that of all-paths graph kernel. And The P, R and F value of feature kernel and tag graph kernel fuse methods is 53.43, 71.62 and 61.30%, respectively. The P, R and F value of feature kernel and tag graph kernel fuse methods is 55.47, 70.29 and 60.37%, respectively. It indicated that the performance of the two kinds of kernel fusion methods is better than that of simple kernel. In comparison with the all-paths graph kernel method, the tag graph kernel method is superior in terms of overall performance. Experiments show that the performance of the multi-kernels method is better than that of the three separate single-kernel method and the dual-mutually fused kernel method used hereof in five corpus sets.

  3. Modeling the spread and control of foot-and-mouth disease in Pennsylvania following its discovery and options for control

    PubMed Central

    Tildesley, Michael J.; Smith, Gary; Keeling, Matt J.

    2013-01-01

    In this paper, we simulate outbreaks of foot-and-mouth disease in the Commonwealth of Pennsylvania, USA – after the introduction of a state-wide movement ban – as they might unfold in the presence of mitigation strategies. We have adapted a model previously used to investigate FMD control policies in the UK to examine the potential for disease spread given an infection seeded in each county in Pennsylvania. The results are highly dependent upon the county of introduction and the spatial scale of transmission. Should the transmission kernel be identical to that for the UK, the epidemic impact is limited to fewer than 20 premises, regardless of the county of introduction. However, for wider kernels where infection can spread further, outbreaks seeded in or near the county with highest density of premises and animals result in large epidemics (>150 premises). Ring culling and vaccination reduce epidemic size, with the optimal radius of the rings being dependent upon the county of introduction. Should the kernel width exceed a given county-dependent threshold, ring culling is unable to control the epidemic. We find that a vaccinate-to-live policy is generally preferred to ring culling (in terms of reducing the overall number of premises culled), indicating that well-targeted control can dramatically reduce the risk of large scale outbreaks of foot-and-mouth disease occurring in Pennsylvania. PMID:22169708

  4. Pollen flow in the wildservice tree, Sorbus torminalis (L.) Crantz. II. Pollen dispersal and heterogeneity in mating success inferred from parent-offspring analysis.

    PubMed

    Oddou-Muratorio, Sylvie; Klein, Etienne K; Austerlitz, Frédéric

    2005-12-01

    Knowing the extent of gene movements from parents to offspring is essential to understand the potential of a species to adapt rapidly to a changing environment, and to design appropriate conservation strategies. In this study, we develop a nonlinear statistical model to jointly estimate the pollen dispersal kernel and the heterogeneity in fecundity among phenotypically or environmentally defined groups of males. This model uses genotype data from a sample of fruiting plants, a sample of seeds harvested on each of these plants, and all males within a circumscribed area. We apply this model to a scattered, entomophilous woody species, Sorbus torminalis (L.) Crantz, within a natural population covering more than 470 ha. We estimate a high heterogeneity in male fecundity among ecological groups, both due to phenotype (size of the trees and flowering intensity) and landscape factors (stand density within the neighbourhood). We also show that fat-tailed kernels are the most appropriate to depict the important abilities of long-distance pollen dispersal for this species. Finally, our results reveal that the spatial position of a male with respect to females affects as much its mating success as ecological determinants of male fecundity. Our study thus stresses the interest to account for the dispersal kernel when estimating heterogeneity in male fecundity, and reciprocally.

  5. 7 CFR 51.2295 - Half kernel.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...

  6. 7 CFR 810.206 - Grades and grade requirements for barley.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... weight per bushel (pounds) Sound barley (percent) Maximum Limits of— Damaged kernels 1 (percent) Heat damaged kernels (percent) Foreign material (percent) Broken kernels (percent) Thin barley (percent) U.S... or otherwise of distinctly low quality. 1 Includes heat-damaged kernels. Injured-by-frost kernels and...

  7. 7 CFR 51.1449 - Damage.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ...) Kernel which is “dark amber” or darker color; (e) Kernel having more than one dark kernel spot, or one dark kernel spot more than one-eighth inch in greatest dimension; (f) Shriveling when the surface of the kernel is very conspicuously wrinkled; (g) Internal flesh discoloration of a medium shade of gray...

  8. 7 CFR 51.1449 - Damage.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ...) Kernel which is “dark amber” or darker color; (e) Kernel having more than one dark kernel spot, or one dark kernel spot more than one-eighth inch in greatest dimension; (f) Shriveling when the surface of the kernel is very conspicuously wrinkled; (g) Internal flesh discoloration of a medium shade of gray...

  9. 7 CFR 51.2125 - Split or broken kernels.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Split or broken kernels. 51.2125 Section 51.2125 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards... kernels. Split or broken kernels means seven-eighths or less of complete whole kernels but which will not...

  10. 7 CFR 51.2296 - Three-fourths half kernel.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...

  11. The Classification of Diabetes Mellitus Using Kernel k-means

    NASA Astrophysics Data System (ADS)

    Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

    2018-01-01

    Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

  12. UNICOS Kernel Internals Application Development

    NASA Technical Reports Server (NTRS)

    Caredo, Nicholas; Craw, James M. (Technical Monitor)

    1995-01-01

    Having an understanding of UNICOS Kernel Internals is valuable information. However, having the knowledge is only half the value. The second half comes with knowing how to use this information and apply it to the development of tools. The kernel contains vast amounts of useful information that can be utilized. This paper discusses the intricacies of developing utilities that utilize kernel information. In addition, algorithms, logic, and code will be discussed for accessing kernel information. Code segments will be provided that demonstrate how to locate and read kernel structures. Types of applications that can utilize kernel information will also be discussed.

  13. Detection of maize kernels breakage rate based on K-means clustering

    NASA Astrophysics Data System (ADS)

    Yang, Liang; Wang, Zhuo; Gao, Lei; Bai, Xiaoping

    2017-04-01

    In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means clustering algorithm. First, the collected RGB images are converted into Lab images, then the original images clarity evaluation are evaluated by the energy function of Sobel 8 gradient. Finally, the detection of maize kernels breakage using different pixel acquisition equipments and different shooting angles. In this paper, the broken maize kernels are identified by the color difference between integrity kernels and broken kernels. The original images clarity evaluation and different shooting angles are taken to verify that the clarity and shooting angles of the images have a direct influence on the feature extraction. The results show that K-means clustering algorithm can distinguish the broken maize kernels effectively.

  14. Modeling adaptive kernels from probabilistic phylogenetic trees.

    PubMed

    Nicotra, Luca; Micheli, Alessio

    2009-01-01

    Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species. We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel. The new kernels are used in the context of support vector machine learning. The kernels adaptivity is obtained through the estimation of the parameters of a tree structured model of evolution using as observed data phylogenetic profiles encoding the presence or absence of specific genes in a set of fully sequenced genomes. We report results obtained in the prediction of the functional class of the proteins of the budding yeast Saccharomyces cerevisae which favorably compare to a standard vector based kernel and to a non-adaptive tree kernel function. A further comparative analysis is performed in order to assess the impact of the different components of the proposed approach. We show that the key features of the proposed kernels are the adaptivity to the input domain and the ability to deal with structured data interpreted through a graphical model representation.

  15. Aflatoxin and nutrient contents of peanut collected from local market and their processed foods

    NASA Astrophysics Data System (ADS)

    Ginting, E.; Rahmianna, A. A.; Yusnawan, E.

    2018-01-01

    Peanut is succeptable to aflatoxin contamination and the sources of peanut as well as processing methods considerably affect aflatoxin content of the products. Therefore, the study on aflatoxin and nutrient contents of peanut collected from local market and their processed foods were performed. Good kernels of peanut were prepared into fried peanut, pressed-fried peanut, peanut sauce, peanut press cake, fermented peanut press cake (tempe) and fried tempe, while blended kernels (good and poor kernels) were processed into peanut sauce and tempe and poor kernels were only processed into tempe. The results showed that good and blended kernels which had high number of sound/intact kernels (82,46% and 62,09%), contained 9.8-9.9 ppb of aflatoxin B1, while slightly higher level was seen in poor kernels (12.1 ppb). However, the moisture, ash, protein, and fat contents of the kernels were similar as well as the products. Peanut tempe and fried tempe showed the highest increase in protein content, while decreased fat contents were seen in all products. The increase in aflatoxin B1 of peanut tempe prepared from poor kernels > blended kernels > good kernels. However, it averagely decreased by 61.2% after deep-fried. Excluding peanut tempe and fried tempe, aflatoxin B1 levels in all products derived from good kernels were below the permitted level (15 ppb). This suggests that sorting peanut kernels as ingredients and followed by heat processing would decrease the aflatoxin content in the products.

  16. Partial Deconvolution with Inaccurate Blur Kernel.

    PubMed

    Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

    2017-10-17

    Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.

  17. Mercerized mesoporous date pit activated carbon—A novel adsorbent to sequester potentially toxic divalent heavy metals from water

    PubMed Central

    Aldawsari, Abdullah; Hameed, B. H.; Alqadami, Ayoub Abdullah; Siddiqui, Masoom Raza; Alothman, Zeid Abdullah; Ahmed, A. Yacine Badjah Hadj

    2017-01-01

    A substantive approach converting waste date pits to mercerized mesoporous date pit activated carbon (DPAC) and utilizing it in the removal of Cd(II), Cu(II), Pb(II), and Zn(II) was reported. In general, rapid heavy metals adsorption kinetics for Co range: 25–100 mg/L was observed, accomplishing 77–97% adsorption within 15 min, finally, attaining equilibrium in 360 min. Linear and non-linear isotherm studies revealed Langmuir model applicability for Cd(II) and Pb(II) adsorption, while Freundlich model was fitted to Zn(II) and Cu(II) adsorption. Maximum monolayer adsorption capacities (qm) for Cd(II), Pb(II), Cu(II), and Zn(II) obtained by non-linear isotherm model at 298 K were 212.1, 133.5, 194.4, and 111 mg/g, respectively. Kinetics modeling parameters showed the applicability of pseudo-second-order model. The activation energy (Ea) magnitude revealed physical nature of adsorption. Maximum elution of Cu(II) (81.6%), Zn(II) (70.1%), Pb(II) (96%), and Cd(II) (78.2%) were observed with 0.1 M HCl. Thermogravimetric analysis of DPAC showed a total weight loss (in two-stages) of 28.3%. Infra-red spectral analysis showed the presence of carboxyl and hydroxyl groups over DPAC surface. The peaks at 820, 825, 845 and 885 cm-1 attributed to Zn–O, Pb–O, Cd–O, and Cu–O appeared on heavy metals saturated DPAC, confirmed their binding on DPAC during the adsorption. PMID:28910368

  18. Mercerized mesoporous date pit activated carbon-A novel adsorbent to sequester potentially toxic divalent heavy metals from water.

    PubMed

    Aldawsari, Abdullah; Khan, Moonis Ali; Hameed, B H; Alqadami, Ayoub Abdullah; Siddiqui, Masoom Raza; Alothman, Zeid Abdullah; Ahmed, A Yacine Badjah Hadj

    2017-01-01

    A substantive approach converting waste date pits to mercerized mesoporous date pit activated carbon (DPAC) and utilizing it in the removal of Cd(II), Cu(II), Pb(II), and Zn(II) was reported. In general, rapid heavy metals adsorption kinetics for Co range: 25-100 mg/L was observed, accomplishing 77-97% adsorption within 15 min, finally, attaining equilibrium in 360 min. Linear and non-linear isotherm studies revealed Langmuir model applicability for Cd(II) and Pb(II) adsorption, while Freundlich model was fitted to Zn(II) and Cu(II) adsorption. Maximum monolayer adsorption capacities (qm) for Cd(II), Pb(II), Cu(II), and Zn(II) obtained by non-linear isotherm model at 298 K were 212.1, 133.5, 194.4, and 111 mg/g, respectively. Kinetics modeling parameters showed the applicability of pseudo-second-order model. The activation energy (Ea) magnitude revealed physical nature of adsorption. Maximum elution of Cu(II) (81.6%), Zn(II) (70.1%), Pb(II) (96%), and Cd(II) (78.2%) were observed with 0.1 M HCl. Thermogravimetric analysis of DPAC showed a total weight loss (in two-stages) of 28.3%. Infra-red spectral analysis showed the presence of carboxyl and hydroxyl groups over DPAC surface. The peaks at 820, 825, 845 and 885 cm-1 attributed to Zn-O, Pb-O, Cd-O, and Cu-O appeared on heavy metals saturated DPAC, confirmed their binding on DPAC during the adsorption.

  19. Is low frequency ocean sound increasing globally?

    PubMed

    Miksis-Olds, Jennifer L; Nichols, Stephen M

    2016-01-01

    Low frequency sound has increased in the Northeast Pacific Ocean over the past 60 yr [Ross (1993) Acoust. Bull. 18, 5-8; (2005) IEEE J. Ocean. Eng. 30, 257-261; Andrew, Howe, Mercer, and Dzieciuch (2002) J. Acoust. Soc. Am. 129, 642-651; McDonald, Hildebrand, and Wiggins (2006) J. Acoust. Soc. Am. 120, 711-717; Chapman and Price (2011) J. Acoust. Soc. Am. 129, EL161-EL165] and in the Indian Ocean over the past decade, [Miksis-Olds, Bradley, and Niu (2013) J. Acoust. Soc. Am. 134, 3464-3475]. More recently, Andrew, Howe, and Mercer's [(2011) J. Acoust. Soc. Am. 129, 642-651] observations in the Northeast Pacific show a level or slightly decreasing trend in low frequency noise. It remains unclear what the low frequency trends are in other regions of the world. In this work, data from the Comprehensive Nuclear-Test Ban Treaty Organization International Monitoring System was used to examine the rate and magnitude of change in low frequency sound (5-115 Hz) over the past decade in the South Atlantic and Equatorial Pacific Oceans. The dominant source observed in the South Atlantic was seismic air gun signals, while shipping and biologic sources contributed more to the acoustic environment at the Equatorial Pacific location. Sound levels over the past 5-6 yr in the Equatorial Pacific have decreased. Decreases were also observed in the ambient sound floor in the South Atlantic Ocean. Based on these observations, it does not appear that low frequency sound levels are increasing globally.

  20. Regression-assisted deconvolution.

    PubMed

    McIntyre, Julie; Stefanski, Leonard A

    2011-06-30

    We present a semi-parametric deconvolution estimator for the density function of a random variable biX that is measured with error, a common challenge in many epidemiological studies. Traditional deconvolution estimators rely only on assumptions about the distribution of X and the error in its measurement, and ignore information available in auxiliary variables. Our method assumes the availability of a covariate vector statistically related to X by a mean-variance function regression model, where regression errors are normally distributed and independent of the measurement errors. Simulations suggest that the estimator achieves a much lower integrated squared error than the observed-data kernel density estimator when models are correctly specified and the assumption of normal regression errors is met. We illustrate the method using anthropometric measurements of newborns to estimate the density function of newborn length. Copyright © 2011 John Wiley & Sons, Ltd.

  1. Equalizing resolution in smoothed-particle hydrodynamics calculations using self-adaptive sinc kernels

    NASA Astrophysics Data System (ADS)

    García-Senz, Domingo; Cabezón, Rubén M.; Escartín, José A.; Ebinger, Kevin

    2014-10-01

    Context. The smoothed-particle hydrodynamics (SPH) technique is a numerical method for solving gas-dynamical problems. It has been applied to simulate the evolution of a wide variety of astrophysical systems. The method has a second-order accuracy, with a resolution that is usually much higher in the compressed regions than in the diluted zones of the fluid. Aims: We propose and check a method to balance and equalize the resolution of SPH between high- and low-density regions. This method relies on the versatility of a family of interpolators called sinc kernels, which allows increasing the interpolation quality by varying only a single parameter (the exponent of the sinc function). Methods: The proposed method was checked and validated through a number of numerical tests, from standard one-dimensional Riemann problems in shock tubes, to multidimensional simulations of explosions, hydrodynamic instabilities, and the collapse of a Sun-like polytrope. Results: The analysis of the hydrodynamical simulations suggests that the scheme devised to equalize the accuracy improves the treatment of the post-shock regions and, in general, of the rarefacted zones of fluids while causing no harm to the growth of hydrodynamic instabilities. The method is robust and easy to implement with a low computational overload. It conserves mass, energy, and momentum and reduces to the standard SPH scheme in regions of the fluid that have smooth density gradients.

  2. A comparative study of outlier detection for large-scale traffic data by one-class SVM and kernel density estimation

    NASA Astrophysics Data System (ADS)

    Ngan, Henry Y. T.; Yung, Nelson H. C.; Yeh, Anthony G. O.

    2015-02-01

    This paper aims at presenting a comparative study of outlier detection (OD) for large-scale traffic data. The traffic data nowadays are massive in scale and collected in every second throughout any modern city. In this research, the traffic flow dynamic is collected from one of the busiest 4-armed junction in Hong Kong in a 31-day sampling period (with 764,027 vehicles in total). The traffic flow dynamic is expressed in a high dimension spatial-temporal (ST) signal format (i.e. 80 cycles) which has a high degree of similarities among the same signal and across different signals in one direction. A total of 19 traffic directions are identified in this junction and lots of ST signals are collected in the 31-day period (i.e. 874 signals). In order to reduce its dimension, the ST signals are firstly undergone a principal component analysis (PCA) to represent as (x,y)-coordinates. Then, these PCA (x,y)-coordinates are assumed to be conformed as Gaussian distributed. With this assumption, the data points are further to be evaluated by (a) a correlation study with three variant coefficients, (b) one-class support vector machine (SVM) and (c) kernel density estimation (KDE). The correlation study could not give any explicit OD result while the one-class SVM and KDE provide average 59.61% and 95.20% DSRs, respectively.

  3. Local Renyi entropic profiles of DNA sequences.

    PubMed

    Vinga, Susana; Almeida, Jonas S

    2007-10-16

    In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs. The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at http://kdbio.inesc-id.pt/~svinga/ep/. The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures.

  4. Local Renyi entropic profiles of DNA sequences

    PubMed Central

    Vinga, Susana; Almeida, Jonas S

    2007-01-01

    Background In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs. Results The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at . Conclusion The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures. PMID:17939871

  5. An evaluation of potential sampling locations in a reservoir with emphasis on conserved spatial correlation structure.

    PubMed

    Yenilmez, Firdes; Düzgün, Sebnem; Aksoy, Aysegül

    2015-01-01

    In this study, kernel density estimation (KDE) was coupled with ordinary two-dimensional kriging (OK) to reduce the number of sampling locations in measurement and kriging of dissolved oxygen (DO) concentrations in Porsuk Dam Reservoir (PDR). Conservation of the spatial correlation structure in the DO distribution was a target. KDE was used as a tool to aid in identification of the sampling locations that would be removed from the sampling network in order to decrease the total number of samples. Accordingly, several networks were generated in which sampling locations were reduced from 65 to 10 in increments of 4 or 5 points at a time based on kernel density maps. DO variograms were constructed, and DO values in PDR were kriged. Performance of the networks in DO estimations were evaluated through various error metrics, standard error maps (SEM), and whether the spatial correlation structure was conserved or not. Results indicated that smaller number of sampling points resulted in loss of information in regard to spatial correlation structure in DO. The minimum representative sampling points for PDR was 35. Efficacy of the sampling location selection method was tested against the networks generated by experts. It was shown that the evaluation approach proposed in this study provided a better sampling network design in which the spatial correlation structure of DO was sustained for kriging.

  6. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  7. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  8. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  9. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  10. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  11. 7 CFR 51.1441 - Half-kernel.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume missing...

  12. 7 CFR 51.1403 - Kernel color classification.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

  13. 7 CFR 51.1450 - Serious damage.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...; (c) Decay affecting any portion of the kernel; (d) Insects, web, or frass or any distinct evidence of insect feeding on the kernel; (e) Internal discoloration which is dark gray, dark brown, or black and...) Dark kernel spots when more than three are on the kernel, or when any dark kernel spot or the aggregate...

  14. 7 CFR 51.1450 - Serious damage.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ...; (c) Decay affecting any portion of the kernel; (d) Insects, web, or frass or any distinct evidence of insect feeding on the kernel; (e) Internal discoloration which is dark gray, dark brown, or black and...) Dark kernel spots when more than three are on the kernel, or when any dark kernel spot or the aggregate...

  15. 7 CFR 51.1450 - Serious damage.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ...; (c) Decay affecting any portion of the kernel; (d) Insects, web, or frass or any distinct evidence of insect feeding on the kernel; (e) Internal discoloration which is dark gray, dark brown, or black and...) Dark kernel spots when more than three are on the kernel, or when any dark kernel spot or the aggregate...

  16. Wavelet SVM in Reproducing Kernel Hilbert Space for hyperspectral remote sensing image classification

    NASA Astrophysics Data System (ADS)

    Du, Peijun; Tan, Kun; Xing, Xiaoshi

    2010-12-01

    Combining Support Vector Machine (SVM) with wavelet analysis, we constructed wavelet SVM (WSVM) classifier based on wavelet kernel functions in Reproducing Kernel Hilbert Space (RKHS). In conventional kernel theory, SVM is faced with the bottleneck of kernel parameter selection which further results in time-consuming and low classification accuracy. The wavelet kernel in RKHS is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. Implications on semiparametric estimation are proposed in this paper. Airborne Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing image with 64 bands and Reflective Optics System Imaging Spectrometer (ROSIS) data with 115 bands were used to experiment the performance and accuracy of the proposed WSVM classifier. The experimental results indicate that the WSVM classifier can obtain the highest accuracy when using the Coiflet Kernel function in wavelet transform. In contrast with some traditional classifiers, including Spectral Angle Mapping (SAM) and Minimum Distance Classification (MDC), and SVM classifier using Radial Basis Function kernel, the proposed wavelet SVM classifier using the wavelet kernel function in Reproducing Kernel Hilbert Space is capable of improving classification accuracy obviously.

  17. A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

    PubMed

    Jiang, Wenhao; Chung, Fu-lai

    2014-01-01

    Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

    PubMed Central

    Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

    2017-01-01

    Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

  19. Hadamard Kernel SVM with applications for breast cancer outcome predictions.

    PubMed

    Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

    2017-12-21

    Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

  20. Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

    PubMed

    Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

    2017-01-01

    Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

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