[Simulation of cropland soil moisture based on an ensemble Kalman filter].

PubMed

Liu, Zhao; Zhou, Yan-Lian; Ju, Wei-Min; Gao, Ping

2011-11-01

By using an ensemble Kalman filter (EnKF) to assimilate the observed soil moisture data, the modified boreal ecosystem productivity simulator (BEPS) model was adopted to simulate the dynamics of soil moisture in winter wheat root zones at Xuzhou Agro-meteorological Station, Jiangsu Province of China during the growth seasons in 2000-2004. After the assimilation of observed data, the determination coefficient, root mean square error, and average absolute error of simulated soil moisture were in the ranges of 0.626-0.943, 0.018-0.042, and 0.021-0.041, respectively, with the simulation precision improved significantly, as compared with that before assimilation, indicating the applicability of data assimilation in improving the simulation of soil moisture. The experimental results at single point showed that the errors in the forcing data and observations and the frequency and soil depth of the assimilation of observed data all had obvious effects on the simulated soil moisture.

Monte Carlo replica-exchange based ensemble docking of protein conformations.

PubMed

Zhang, Zhe; Ehmann, Uwe; Zacharias, Martin

2017-05-01

A replica-exchange Monte Carlo (REMC) ensemble docking approach has been developed that allows efficient exploration of protein-protein docking geometries. In addition to Monte Carlo steps in translation and orientation of binding partners, possible conformational changes upon binding are included based on Monte Carlo selection of protein conformations stored as ordered pregenerated conformational ensembles. The conformational ensembles of each binding partner protein were generated by three different approaches starting from the unbound partner protein structure with a range spanning a root mean square deviation of 1-2.5 Å with respect to the unbound structure. Because MC sampling is performed to select appropriate partner conformations on the fly the approach is not limited by the number of conformations in the ensemble compared to ensemble docking of each conformer pair in ensemble cross docking. Although only a fraction of generated conformers was in closer agreement with the bound structure the REMC ensemble docking approach achieved improved docking results compared to REMC docking with only the unbound partner structures or using docking energy minimization methods. The approach has significant potential for further improvement in combination with more realistic structural ensembles and better docking scoring functions. Proteins 2017; 85:924-937. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Concrete ensemble Kalman filters with rigorous catastrophic filter divergence

PubMed Central

Kelly, David; Majda, Andrew J.; Tong, Xin T.

2015-01-01

The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature. PMID:26261335

Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.

PubMed

Kelly, David; Majda, Andrew J; Tong, Xin T

2015-08-25

The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.

Statistical fluctuations in cooperative cyclotron radiation

NASA Astrophysics Data System (ADS)

Anishchenko, S. V.; Baryshevsky, V. G.

2018-01-01

Shot noise is the cause of statistical fluctuations in cooperative cyclotron radiation generated by an ensemble of electrons oscillating in magnetic field. Autophasing time - the time required for the cooperative cyclotron radiation power to peak - is the critical parameter characterizing the dynamics of electron-oscillators interacting via the radiation field. It is shown that premodulation of charged particles leads to a considerable narrowing of the autophasing time distribution function for which the analytic expression is obtained. When the number of particles Ne exceeds a certain value that depends on the degree to which the particles have been premodulated, the relative root-mean-square deviation (RMSD) of the autophasing time δT changes from a logarithmic dependence on Ne (δT ∼ 1 / lnNe) to square-root (δT ∼ 1 /√{Ne }). A slight energy spread (∼4%) results in a twofold drop of the maximum attainable power of cooperative cyclotron radiation.

Impact of ozone observations on the structure of a tropical cyclone using coupled atmosphere-chemistry data assimilation

NASA Astrophysics Data System (ADS)

Lim, S.; Park, S. K.; Zupanski, M.

2015-04-01

Since the air quality forecast is related to both chemistry and meteorology, the coupled atmosphere-chemistry data assimilation (DA) system is essential to air quality forecasting. Ozone (O3) plays an important role in chemical reactions and is usually assimilated in chemical DA. In tropical cyclones (TCs), O3 usually shows a lower concentration inside the eyewall and an elevated concentration around the eye, impacting atmospheric as well as chemical variables. To identify the impact of O3 observations on TC structure, including atmospheric and chemical information, we employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) with an ensemble-based DA algorithm - the maximum likelihood ensemble filter (MLEF). For a TC case that occurred over the East Asia, our results indicate that the ensemble forecast is reasonable, accompanied with larger background state uncertainty over the TC, and also over eastern China. Similarly, the assimilation of O3 observations impacts atmospheric and chemical variables near the TC and over eastern China. The strongest impact on air quality in the lower troposphere was over China, likely due to the pollution advection. In the vicinity of the TC, however, the strongest impact on chemical variables adjustment was at higher levels. The impact on atmospheric variables was similar in both over China and near the TC. The analysis results are validated using several measures that include the cost function, root-mean-squared error with respect to observations, and degrees of freedom for signal (DFS). All measures indicate a positive impact of DA on the analysis - the cost function and root mean square error have decreased by 16.9 and 8.87%, respectively. In particular, the DFS indicates a strong positive impact of observations in the TC area, with a weaker maximum over northeast China.

Molecular dynamics in principal component space.

PubMed

Michielssens, Servaas; van Erp, Titus S; Kutzner, Carsten; Ceulemans, Arnout; de Groot, Bert L

2012-07-26

A molecular dynamics algorithm in principal component space is presented. It is demonstrated that sampling can be improved without changing the ensemble by assigning masses to the principal components proportional to the inverse square root of the eigenvalues. The setup of the simulation requires no prior knowledge of the system; a short initial MD simulation to extract the eigenvectors and eigenvalues suffices. Independent measures indicated a 6-7 times faster sampling compared to a regular molecular dynamics simulation.

Hybrid Data Assimilation without Ensemble Filtering

NASA Technical Reports Server (NTRS)

Todling, Ricardo; Akkraoui, Amal El

2014-01-01

The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.

An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index

NASA Astrophysics Data System (ADS)

Ali, Mumtaz; Deo, Ravinesh C.; Downs, Nathan J.; Maraseni, Tek

2018-07-01

Forecasting drought by means of the World Meteorological Organization-approved Standardized Precipitation Index (SPI) is considered to be a fundamental task to support socio-economic initiatives and effectively mitigating the climate-risk. This study aims to develop a robust drought modelling strategy to forecast multi-scalar SPI in drought-rich regions of Pakistan where statistically significant lagged combinations of antecedent SPI are used to forecast future SPI. With ensemble-Adaptive Neuro Fuzzy Inference System ('ensemble-ANFIS') executed via a 10-fold cross-validation procedure, a model is constructed by randomly partitioned input-target data. Resulting in 10-member ensemble-ANFIS outputs, judged by mean square error and correlation coefficient in the training period, the optimal forecasts are attained by the averaged simulations, and the model is benchmarked with M5 Model Tree and Minimax Probability Machine Regression (MPMR). The results show the proposed ensemble-ANFIS model's preciseness was notably better (in terms of the root mean square and mean absolute error including the Willmott's, Nash-Sutcliffe and Legates McCabe's index) for the 6- and 12- month compared to the 3-month forecasts as verified by the largest error proportions that registered in smallest error band. Applying 10-member simulations, ensemble-ANFIS model was validated for its ability to forecast severity (S), duration (D) and intensity (I) of drought (including the error bound). This enabled uncertainty between multi-models to be rationalized more efficiently, leading to a reduction in forecast error caused by stochasticity in drought behaviours. Through cross-validations at diverse sites, a geographic signature in modelled uncertainties was also calculated. Considering the superiority of ensemble-ANFIS approach and its ability to generate uncertainty-based information, the study advocates the versatility of a multi-model approach for drought-risk forecasting and its prime importance for estimating drought properties over confidence intervals to generate better information for strategic decision-making.

Skill of Ensemble Seasonal Probability Forecasts

NASA Astrophysics Data System (ADS)

Smith, Leonard A.; Binter, Roman; Du, Hailiang; Niehoerster, Falk

2010-05-01

In operational forecasting, the computational complexity of large simulation models is, ideally, justified by enhanced performance over simpler models. We will consider probability forecasts and contrast the skill of ENSEMBLES-based seasonal probability forecasts of interest to the finance sector (specifically temperature forecasts for Nino 3.4 and the Atlantic Main Development Region (MDR)). The ENSEMBLES model simulations will be contrasted against forecasts from statistical models based on the observations (climatological distributions) and empirical dynamics based on the observations but conditioned on the current state (dynamical climatology). For some start dates, individual ENSEMBLES models yield significant skill even at a lead-time of 14 months. The nature of this skill is discussed, and chances of application are noted. Questions surrounding the interpretation of probability forecasts based on these multi-model ensemble simulations are then considered; the distributions considered are formed by kernel dressing the ensemble and blending with the climatology. The sources of apparent (RMS) skill in distributions based on multi-model simulations is discussed, and it is demonstrated that the inclusion of "zero-skill" models in the long range can improve Root-Mean-Square-Error scores, casting some doubt on the common justification for the claim that all models should be included in forming an operational probability forecast. It is argued that the rational response varies with lead time.

Multiscale Macromolecular Simulation: Role of Evolving Ensembles

PubMed Central

Singharoy, A.; Joshi, H.; Ortoleva, P.J.

2013-01-01

Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin timestep is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers. PMID:22978601

A Solar Time-Based Analog Ensemble Method for Regional Solar Power Forecasting

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

Hodge, Brian S; Zhang, Xinmin; Li, Yuan

This paper presents a new analog ensemble method for day-ahead regional photovoltaic (PV) power forecasting with hourly resolution. By utilizing open weather forecast and power measurement data, this prediction method is processed within a set of historical data with similar meteorological data (temperature and irradiance), and astronomical date (solar time and earth declination angle). Further, clustering and blending strategies are applied to improve its accuracy in regional PV forecasting. The robustness of the proposed method is demonstrated with three different numerical weather prediction models, the North American Mesoscale Forecast System, the Global Forecast System, and the Short-Range Ensemble Forecast, formore » both region level and single site level PV forecasts. Using real measured data, the new forecasting approach is applied to the load zone in Southeastern Massachusetts as a case study. The normalized root mean square error (NRMSE) has been reduced by 13.80%-61.21% when compared with three tested baselines.« less

Investigation of stickiness influence in the anomalous transport and diffusion for a non-dissipative Fermi-Ulam model

NASA Astrophysics Data System (ADS)

Livorati, André L. P.; Palmero, Matheus S.; Díaz-I, Gabriel; Dettmann, Carl P.; Caldas, Iberê L.; Leonel, Edson D.

2018-02-01

We study the dynamics of an ensemble of non interacting particles constrained by two infinitely heavy walls, where one of them is moving periodically in time, while the other is fixed. The system presents mixed dynamics, where the accessible region for the particle to diffuse chaotically is bordered by an invariant spanning curve. Statistical analysis for the root mean square velocity, considering high and low velocity ensembles, leads the dynamics to the same steady state plateau for long times. A transport investigation of the dynamics via escape basins reveals that depending of the initial velocity ensemble, the decay rates of the survival probability present different shapes and bumps, in a mix of exponential, power law and stretched exponential decays. After an analysis of step-size averages, we found that the stable manifolds play the role of a preferential path for faster escape, being responsible for the bumps and different shapes of the survival probability.

An optimized ensemble local mean decomposition method for fault detection of mechanical components

NASA Astrophysics Data System (ADS)

Zhang, Chao; Li, Zhixiong; Hu, Chao; Chen, Shuai; Wang, Jianguo; Zhang, Xiaogang

2017-03-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error (Relative RMSE) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE, corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions.

Time Series Forecasting of Daily Reference Evapotranspiration by Neural Network Ensemble Learning for Irrigation System

NASA Astrophysics Data System (ADS)

Manikumari, N.; Murugappan, A.; Vinodhini, G.

2017-07-01

Time series forecasting has gained remarkable interest of researchers in the last few decades. Neural networks based time series forecasting have been employed in various application areas. Reference Evapotranspiration (ETO) is one of the most important components of the hydrologic cycle and its precise assessment is vital in water balance and crop yield estimation, water resources system design and management. This work aimed at achieving accurate time series forecast of ETO using a combination of neural network approaches. This work was carried out using data collected in the command area of VEERANAM Tank during the period 2004 - 2014 in India. In this work, the Neural Network (NN) models were combined by ensemble learning in order to improve the accuracy for forecasting Daily ETO (for the year 2015). Bagged Neural Network (Bagged-NN) and Boosted Neural Network (Boosted-NN) ensemble learning were employed. It has been proved that Bagged-NN and Boosted-NN ensemble models are better than individual NN models in terms of accuracy. Among the ensemble models, Boosted-NN reduces the forecasting errors compared to Bagged-NN and individual NNs. Regression co-efficient, Mean Absolute Deviation, Mean Absolute Percentage error and Root Mean Square Error also ascertain that Boosted-NN lead to improved ETO forecasting performance.

Effects on Physiology and Performance of Wearing the Aviator NBC ensemble While Flying the UH-60 Helicopter Flight Simulator in a Controlled Heat Environment.

DTIC Science & Technology

1992-09-01

and collecting and processing data. They were at the front line in interacting with the subjects and maintaining morale. They did an excellent job. They...second for 16 parameter channels, and the data were processed to produce a single root mean square (RMS) error value for each channel appropriate to...represented in the final analysis. Physiological data The physiological data on the VAX were processed by sampling them at 5-minute intervals throughout the

Oceanic ensemble forecasting in the Gulf of Mexico: An application to the case of the Deep Water Horizon oil spill

NASA Astrophysics Data System (ADS)

Khade, Vikram; Kurian, Jaison; Chang, Ping; Szunyogh, Istvan; Thyng, Kristen; Montuoro, Raffaele

2017-05-01

This paper demonstrates the potential of ocean ensemble forecasting in the Gulf of Mexico (GoM). The Bred Vector (BV) technique with one week rescaling frequency is implemented on a 9 km resolution version of the Regional Ocean Modelling System (ROMS). Numerical experiments are carried out by using the HYCOM analysis products to define the initial conditions and the lateral boundary conditions. The growth rates of the forecast uncertainty are estimated to be about 10% of initial amplitude per week. By carrying out ensemble forecast experiments with and without perturbed surface forcing, it is demonstrated that in the coastal regions accounting for uncertainties in the atmospheric forcing is more important than accounting for uncertainties in the ocean initial conditions. In the Loop Current region, the initial condition uncertainties, are the dominant source of the forecast uncertainty. The root-mean-square error of the Lagrangian track forecasts at the 15-day forecast lead time can be reduced by about 10 - 50 km using the ensemble mean Eulerian forecast of the oceanic flow for the computation of the tracks, instead of the single-initial-condition Eulerian forecast.

Superimposition of protein structures with dynamically weighted RMSD.

PubMed

Wu, Di; Wu, Zhijun

2010-02-01

In protein modeling, one often needs to superimpose a group of structures for a protein. A common way to do this is to translate and rotate the structures so that the square root of the sum of squares of coordinate differences of the atoms in the structures, called the root-mean-square deviation (RMSD) of the structures, is minimized. While it has provided a general way of aligning a group of structures, this approach has not taken into account the fact that different atoms may have different properties and they should be compared differently. For this reason, when superimposed with RMSD, the coordinate differences of different atoms should be evaluated with different weights. The resulting RMSD is called the weighted RMSD (wRMSD). Here we investigate the use of a special wRMSD for superimposing a group of structures with weights assigned to the atoms according to certain thermal motions of the atoms. We call such an RMSD the dynamically weighted RMSD (dRMSD). We show that the thermal motions of the atoms can be obtained from several sources such as the mean-square fluctuations that can be estimated by Gaussian network model analysis. We show that the superimposition of structures with dRMSD can successfully identify protein domains and protein motions, and that it has important implications in practice, e.g., in aligning the ensemble of structures determined by nuclear magnetic resonance.

Comparison of projection skills of deterministic ensemble methods using pseudo-simulation data generated from multivariate Gaussian distribution

NASA Astrophysics Data System (ADS)

Oh, Seok-Geun; Suh, Myoung-Seok

2017-07-01

The projection skills of five ensemble methods were analyzed according to simulation skills, training period, and ensemble members, using 198 sets of pseudo-simulation data (PSD) produced by random number generation assuming the simulated temperature of regional climate models. The PSD sets were classified into 18 categories according to the relative magnitude of bias, variance ratio, and correlation coefficient, where each category had 11 sets (including 1 truth set) with 50 samples. The ensemble methods used were as follows: equal weighted averaging without bias correction (EWA_NBC), EWA with bias correction (EWA_WBC), weighted ensemble averaging based on root mean square errors and correlation (WEA_RAC), WEA based on the Taylor score (WEA_Tay), and multivariate linear regression (Mul_Reg). The projection skills of the ensemble methods improved generally as compared with the best member for each category. However, their projection skills are significantly affected by the simulation skills of the ensemble member. The weighted ensemble methods showed better projection skills than non-weighted methods, in particular, for the PSD categories having systematic biases and various correlation coefficients. The EWA_NBC showed considerably lower projection skills than the other methods, in particular, for the PSD categories with systematic biases. Although Mul_Reg showed relatively good skills, it showed strong sensitivity to the PSD categories, training periods, and number of members. On the other hand, the WEA_Tay and WEA_RAC showed relatively superior skills in both the accuracy and reliability for all the sensitivity experiments. This indicates that WEA_Tay and WEA_RAC are applicable even for simulation data with systematic biases, a short training period, and a small number of ensemble members.

Statistical properties and condensate fluctuation of attractive Bose gas with finite number of particles

NASA Astrophysics Data System (ADS)

Bera, Sangita; Lekala, Mantile Leslie; Chakrabarti, Barnali; Bhattacharyya, Satadal; Rampho, Gaotsiwe Joel

2017-09-01

'We study the condensate fluctuation and several statistics of weakly interacting attractive Bose gas of 7 Li atoms in harmonic trap. Using exact recursion relation we calculate canonical ensemble partition function and study the thermal evolution of the condensate. As 7 Li condensate is associated with collapse, the number of condensate atom is truly finite and it facilitates to study the condensate in mesoscopic region. Being highly correlated, we utilize the two-body correlated basis function to get the many-body effective potential which is further used to calculate the energy levels. Taking van der Waals interaction as interatomic interaction we calculate several quantities like condensate fraction N, root-mean-square fluctuation δn0 and different orders of central moments. We observe the effect of finite size on the calculation of condensate fluctuations and the effect of attractive interaction over the noninteracting limit. We observe the depletion of the condensate with increase in temperature. The calculated moments nicely exhibit the mesoscopic effect. The sharp fall in the root-mean-square fluctuation near the critical point signifies the possibility of phase transition.

GPU-Q-J, a fast method for calculating root mean square deviation (RMSD) after optimal superposition

PubMed Central

2011-01-01

Background Calculation of the root mean square deviation (RMSD) between the atomic coordinates of two optimally superposed structures is a basic component of structural comparison techniques. We describe a quaternion based method, GPU-Q-J, that is stable with single precision calculations and suitable for graphics processor units (GPUs). The application was implemented on an ATI 4770 graphics card in C/C++ and Brook+ in Linux where it was 260 to 760 times faster than existing unoptimized CPU methods. Source code is available from the Compbio website http://software.compbio.washington.edu/misc/downloads/st_gpu_fit/ or from the author LHH. Findings The Nutritious Rice for the World Project (NRW) on World Community Grid predicted de novo, the structures of over 62,000 small proteins and protein domains returning a total of 10 billion candidate structures. Clustering ensembles of structures on this scale requires calculation of large similarity matrices consisting of RMSDs between each pair of structures in the set. As a real-world test, we calculated the matrices for 6 different ensembles from NRW. The GPU method was 260 times faster that the fastest existing CPU based method and over 500 times faster than the method that had been previously used. Conclusions GPU-Q-J is a significant advance over previous CPU methods. It relieves a major bottleneck in the clustering of large numbers of structures for NRW. It also has applications in structure comparison methods that involve multiple superposition and RMSD determination steps, particularly when such methods are applied on a proteome and genome wide scale. PMID:21453553

Collective strong coupling with homogeneous Rabi frequencies using a 3D lumped element microwave resonator

NASA Astrophysics Data System (ADS)

Angerer, Andreas; Astner, Thomas; Wirtitsch, Daniel; Sumiya, Hitoshi; Onoda, Shinobu; Isoya, Junichi; Putz, Stefan; Majer, Johannes

2016-07-01

We design and implement 3D-lumped element microwave cavities that spatially focus magnetic fields to a small mode volume. They allow coherent and uniform coupling to electron spins hosted by nitrogen vacancy centers in diamond. We achieve large homogeneous single spin coupling rates, with an enhancement of more than one order of magnitude compared to standard 3D cavities with a fundamental resonance at 3 GHz. Finite element simulations confirm that the magnetic field distribution is homogeneous throughout the entire sample volume, with a root mean square deviation of 1.54%. With a sample containing 1017 nitrogen vacancy electron spins, we achieve a collective coupling strength of Ω = 12 MHz, a cooperativity factor C = 27, and clearly enter the strong coupling regime. This allows to interface a macroscopic spin ensemble with microwave circuits, and the homogeneous Rabi frequency paves the way to manipulate the full ensemble population in a coherent way.

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis.

PubMed

Li, Shaobo; Liu, Guokai; Tang, Xianghong; Lu, Jianguang; Hu, Jianjun

2017-07-28

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster-Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions.

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis

PubMed Central

Li, Shaobo; Liu, Guokai; Tang, Xianghong; Lu, Jianguang

2017-01-01

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster–Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions. PMID:28788099

Examining dynamic interactions among experimental factors influencing hydrologic data assimilation with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Baetz, B. W.; Cai, X. M.; Ancell, B. C.; Fan, Y. R.

2017-11-01

The ensemble Kalman filter (EnKF) is recognized as a powerful data assimilation technique that generates an ensemble of model variables through stochastic perturbations of forcing data and observations. However, relatively little guidance exists with regard to the proper specification of the magnitude of the perturbation and the ensemble size, posing a significant challenge in optimally implementing the EnKF. This paper presents a robust data assimilation system (RDAS), in which a multi-factorial design of the EnKF experiments is first proposed for hydrologic ensemble predictions. A multi-way analysis of variance is then used to examine potential interactions among factors affecting the EnKF experiments, achieving optimality of the RDAS with maximized performance of hydrologic predictions. The RDAS is applied to the Xiangxi River watershed which is the most representative watershed in China's Three Gorges Reservoir region to demonstrate its validity and applicability. Results reveal that the pairwise interaction between perturbed precipitation and streamflow observations has the most significant impact on the performance of the EnKF system, and their interactions vary dynamically across different settings of the ensemble size and the evapotranspiration perturbation. In addition, the interactions among experimental factors vary greatly in magnitude and direction depending on different statistical metrics for model evaluation including the Nash-Sutcliffe efficiency and the Box-Cox transformed root-mean-square error. It is thus necessary to test various evaluation metrics in order to enhance the robustness of hydrologic prediction systems.

Benchmarking Commercial Conformer Ensemble Generators.

PubMed

Friedrich, Nils-Ole; de Bruyn Kops, Christina; Flachsenberg, Florian; Sommer, Kai; Rarey, Matthias; Kirchmair, Johannes

2017-11-27

We assess and compare the performance of eight commercial conformer ensemble generators (ConfGen, ConfGenX, cxcalc, iCon, MOE LowModeMD, MOE Stochastic, MOE Conformation Import, and OMEGA) and one leading free algorithm, the distance geometry algorithm implemented in RDKit. The comparative study is based on a new version of the Platinum Diverse Dataset, a high-quality benchmarking dataset of 2859 protein-bound ligand conformations extracted from the PDB. Differences in the performance of commercial algorithms are much smaller than those observed for free algorithms in our previous study (J. Chem. Inf. 2017, 57, 529-539). For commercial algorithms, the median minimum root-mean-square deviations measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers are between 0.46 and 0.61 Å. Commercial conformer ensemble generators are characterized by their high robustness, with at least 99% of all input molecules successfully processed and few or even no substantial geometrical errors detectable in their output conformations. The RDKit distance geometry algorithm (with minimization enabled) appears to be a good free alternative since its performance is comparable to that of the midranked commercial algorithms. Based on a statistical analysis, we elaborate on which algorithms to use and how to parametrize them for best performance in different application scenarios.

Molecular dynamics simulation of polyacrylamides in potassium montmorillonite clay hydrates

NASA Astrophysics Data System (ADS)

Zhang, Junfang; Rivero, Mayela; Choi, S. K.

2007-02-01

We present molecular dynamics simulation results for polyacrylamide in potassium montmorillonite clay-aqueous systems. Interlayer molecular structure and dynamics properties are investigated. The number density profile, radial distribution function, root-mean-square deviation (RMSD), mean-square displacement (MSD) and diffusion coefficient are reported. The calculations are conducted in constant NVT ensembles, at T = 300 K and with layer spacing of 40 Å. Our simulation results showed that polyacrylamides had little impact on the structure of interlayer water. Density profiles and radial distribution function indicated that hydration shells were formed. In the presence of polyacrylamides more potassium counterions move close to the clay surface while water molecules move away, indicating that potassium counterions are hydrated to a lesser extent than the system in which no polyacrylamides were added. The diffusion coefficients for potassium and water decreased when polyacrylamides were added.

Nonnegative definite EAP and ODF estimation via a unified multi-shell HARDI reconstruction.

PubMed

Cheng, Jian; Jiang, Tianzi; Deriche, Rachid

2012-01-01

In High Angular Resolution Diffusion Imaging (HARDI), Orientation Distribution Function (ODF) and Ensemble Average Propagator (EAP) are two important Probability Density Functions (PDFs) which reflect the water diffusion and fiber orientations. Spherical Polar Fourier Imaging (SPFI) is a recent model-free multi-shell HARDI method which estimates both EAP and ODF from the diffusion signals with multiple b values. As physical PDFs, ODFs and EAPs are nonnegative definite respectively in their domains S2 and R3. However, existing ODF/EAP estimation methods like SPFI seldom consider this natural constraint. Although some works considered the nonnegative constraint on the given discrete samples of ODF/EAP, the estimated ODF/EAP is not guaranteed to be nonnegative definite in the whole continuous domain. The Riemannian framework for ODFs and EAPs has been proposed via the square root parameterization based on pre-estimated ODFs and EAPs by other methods like SPFI. However, there is no work on how to estimate the square root of ODF/EAP called as the wavefuntion directly from diffusion signals. In this paper, based on the Riemannian framework for ODFs/EAPs and Spherical Polar Fourier (SPF) basis representation, we propose a unified model-free multi-shell HARDI method, named as Square Root Parameterized Estimation (SRPE), to simultaneously estimate both the wavefunction of EAPs and the nonnegative definite ODFs and EAPs from diffusion signals. The experiments on synthetic data and real data showed SRPE is more robust to noise and has better EAP reconstruction than SPFI, especially for EAP profiles at large radius.

Domain wall fermion QCD with the exact one flavor algorithm

DOE PAGES

Jung, C.; Kelly, C.; Mawhinney, R. D.; ...

2018-03-13

Lattice QCD calculations including the effects of one or more nondegenerate sea quark flavors are conventionally performed using the rational hybrid Monte Carlo (RHMC) algorithm, which computes the square root of the determinant ofmore » $${\\mathcal{D}}^{\\dagger{}}\\mathcal{D}$$, where $$\\mathcal{D}$$ is the Dirac operator. The special case of two degenerate quark flavors with the same mass is described directly by the determinant of $${\\mathcal{D}}^{\\dagger{}}\\mathcal{D}$$—in particular, no square root is necessary—enabling a variety of algorithmic developments, which have driven down the cost of simulating the light (up and down) quarks in the isospin-symmetric limit of equal masses. As a result, the relative cost of single quark flavors—such as the strange or charm—computed with RHMC has become more expensive. This problem is even more severe in the context of our measurements of the $$\\mathrm{{\\Delta}}I=1/2$$ $$K{\\rightarrow}{\\pi}{\\pi}$$ matrix elements on lattice ensembles with $G$-parity boundary conditions, since $G$-parity is associated with a doubling of the number of quark flavors described by $$\\mathcal{D}$$ , and thus RHMC is needed for the isospin-symmetric light quarks as well. In this paper we report on our implementation of the exact one flavor algorithm (EOFA) introduced by the TWQCD Collaboration for simulations including single flavors of domain wall quarks. We have developed a new preconditioner for the EOFA Dirac equation, which both reduces the cost of solving the Dirac equation and allows us to reuse the bulk of our existing high-performance code. Coupling these improvements with careful tuning of our integrator, the time per accepted trajectory in the production of our $2+1$ flavor $G$-parity ensembles with physical pion and kaon masses has been decreased by a factor of 4.2.« less

Domain wall fermion QCD with the exact one flavor algorithm

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

Jung, C.; Kelly, C.; Mawhinney, R. D.

Lattice QCD calculations including the effects of one or more nondegenerate sea quark flavors are conventionally performed using the rational hybrid Monte Carlo (RHMC) algorithm, which computes the square root of the determinant ofmore » $${\\mathcal{D}}^{\\dagger{}}\\mathcal{D}$$, where $$\\mathcal{D}$$ is the Dirac operator. The special case of two degenerate quark flavors with the same mass is described directly by the determinant of $${\\mathcal{D}}^{\\dagger{}}\\mathcal{D}$$—in particular, no square root is necessary—enabling a variety of algorithmic developments, which have driven down the cost of simulating the light (up and down) quarks in the isospin-symmetric limit of equal masses. As a result, the relative cost of single quark flavors—such as the strange or charm—computed with RHMC has become more expensive. This problem is even more severe in the context of our measurements of the $$\\mathrm{{\\Delta}}I=1/2$$ $$K{\\rightarrow}{\\pi}{\\pi}$$ matrix elements on lattice ensembles with $G$-parity boundary conditions, since $G$-parity is associated with a doubling of the number of quark flavors described by $$\\mathcal{D}$$ , and thus RHMC is needed for the isospin-symmetric light quarks as well. In this paper we report on our implementation of the exact one flavor algorithm (EOFA) introduced by the TWQCD Collaboration for simulations including single flavors of domain wall quarks. We have developed a new preconditioner for the EOFA Dirac equation, which both reduces the cost of solving the Dirac equation and allows us to reuse the bulk of our existing high-performance code. Coupling these improvements with careful tuning of our integrator, the time per accepted trajectory in the production of our $2+1$ flavor $G$-parity ensembles with physical pion and kaon masses has been decreased by a factor of 4.2.« less

Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

NASA Astrophysics Data System (ADS)

Khaki, M.; Hoteit, I.; Kuhn, M.; Awange, J.; Forootan, E.; van Dijk, A. I. J. M.; Schumacher, M.; Pattiaratchi, C.

2017-09-01

The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, for the first time, we assess the performance of the most popular data assimilation sequential techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement and test stochastic and deterministic ensemble-based Kalman filters (EnKF), as well as Particle filters (PF) using two different resampling approaches of Multinomial Resampling and Systematic Resampling. These choices provide various opportunities for weighting observations and model simulations during the assimilation and also accounting for error distributions. Particularly, the deterministic EnKF is tested to avoid perturbing observations before assimilation (that is the case in an ordinary EnKF). Gaussian-based random updates in the EnKF approaches likely do not fully represent the statistical properties of the model simulations and TWS observations. Therefore, the fully non-Gaussian PF is also applied to estimate more realistic updates. Monthly GRACE TWS are assimilated into W3RA covering the entire Australia. To evaluate the filters performances and analyze their impact on model simulations, their estimates are validated by independent in-situ measurements. Our results indicate that all implemented filters improve the estimation of water storage simulations of W3RA. The best results are obtained using two versions of deterministic EnKF, i.e. the Square Root Analysis (SQRA) scheme and the Ensemble Square Root Filter (EnSRF), respectively, improving the model groundwater estimations errors by 34% and 31% compared to a model run without assimilation. Applying the PF along with Systematic Resampling successfully decreases the model estimation error by 23%.

Domain wall fermion QCD with the exact one flavor algorithm

NASA Astrophysics Data System (ADS)

Jung, C.; Kelly, C.; Mawhinney, R. D.; Murphy, D. J.

2018-03-01

Lattice QCD calculations including the effects of one or more nondegenerate sea quark flavors are conventionally performed using the rational hybrid Monte Carlo (RHMC) algorithm, which computes the square root of the determinant of D†D , where D is the Dirac operator. The special case of two degenerate quark flavors with the same mass is described directly by the determinant of D†D —in particular, no square root is necessary—enabling a variety of algorithmic developments, which have driven down the cost of simulating the light (up and down) quarks in the isospin-symmetric limit of equal masses. As a result, the relative cost of single quark flavors—such as the strange or charm—computed with RHMC has become more expensive. This problem is even more severe in the context of our measurements of the Δ I =1 /2 K →π π matrix elements on lattice ensembles with G -parity boundary conditions, since G -parity is associated with a doubling of the number of quark flavors described by D , and thus RHMC is needed for the isospin-symmetric light quarks as well. In this paper we report on our implementation of the exact one flavor algorithm (EOFA) introduced by the TWQCD Collaboration for simulations including single flavors of domain wall quarks. We have developed a new preconditioner for the EOFA Dirac equation, which both reduces the cost of solving the Dirac equation and allows us to reuse the bulk of our existing high-performance code. Coupling these improvements with careful tuning of our integrator, the time per accepted trajectory in the production of our 2 +1 flavor G -parity ensembles with physical pion and kaon masses has been decreased by a factor of 4.2.

Interlaboratory comparison measurements of aspheres

NASA Astrophysics Data System (ADS)

Schachtschneider, R.; Fortmeier, I.; Stavridis, M.; Asfour, J.; Berger, G.; Bergmann, R. B.; Beutler, A.; Blümel, T.; Klawitter, H.; Kubo, K.; Liebl, J.; Löffler, F.; Meeß, R.; Pruss, C.; Ramm, D.; Sandner, M.; Schneider, G.; Wendel, M.; Widdershoven, I.; Schulz, M.; Elster, C.

2018-05-01

The need for high-quality aspheres is rapidly growing, necessitating increased accuracy in their measurement. A reliable uncertainty assessment of asphere form measurement techniques is difficult due to their complexity. In order to explore the accuracy of current asphere form measurement techniques, an interlaboratory comparison was carried out in which four aspheres were measured by eight laboratories using tactile measurements, optical point measurements, and optical areal measurements. Altogether, 12 different devices were employed. The measurement results were analysed after subtracting the design topography and subsequently a best-fit sphere from the measurements. The surface reduced in this way was compared to a reference topography that was obtained by taking the pointwise median across the ensemble of reduced topographies on a 1000 × 1000 Cartesian grid. The deviations of the reduced topographies from the reference topography were analysed in terms of several characteristics including peak-to-valley and root-mean-square deviations. Root-mean-square deviations of the reduced topographies from the reference topographies were found to be on the order of some tens of nanometres up to 89 nm, with most of the deviations being smaller than 20 nm. Our results give an indication of the accuracy that can currently be expected in form measurements of aspheres.

Multi-criterion model ensemble of CMIP5 surface air temperature over China

NASA Astrophysics Data System (ADS)

Yang, Tiantian; Tao, Yumeng; Li, Jingjing; Zhu, Qian; Su, Lu; He, Xiaojia; Zhang, Xiaoming

2018-05-01

The global circulation models (GCMs) are useful tools for simulating climate change, projecting future temperature changes, and therefore, supporting the preparation of national climate adaptation plans. However, different GCMs are not always in agreement with each other over various regions. The reason is that GCMs' configurations, module characteristics, and dynamic forcings vary from one to another. Model ensemble techniques are extensively used to post-process the outputs from GCMs and improve the variability of model outputs. Root-mean-square error (RMSE), correlation coefficient (CC, or R) and uncertainty are commonly used statistics for evaluating the performances of GCMs. However, the simultaneous achievements of all satisfactory statistics cannot be guaranteed in using many model ensemble techniques. In this paper, we propose a multi-model ensemble framework, using a state-of-art evolutionary multi-objective optimization algorithm (termed MOSPD), to evaluate different characteristics of ensemble candidates and to provide comprehensive trade-off information for different model ensemble solutions. A case study of optimizing the surface air temperature (SAT) ensemble solutions over different geographical regions of China is carried out. The data covers from the period of 1900 to 2100, and the projections of SAT are analyzed with regard to three different statistical indices (i.e., RMSE, CC, and uncertainty). Among the derived ensemble solutions, the trade-off information is further analyzed with a robust Pareto front with respect to different statistics. The comparison results over historical period (1900-2005) show that the optimized solutions are superior over that obtained simple model average, as well as any single GCM output. The improvements of statistics are varying for different climatic regions over China. Future projection (2006-2100) with the proposed ensemble method identifies that the largest (smallest) temperature changes will happen in the South Central China (the Inner Mongolia), the North Eastern China (the South Central China), and the North Western China (the South Central China), under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively.

Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

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

Cheung, WanYin; Zhang, Jie; Florita, Anthony

2015-12-08

Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance,more » cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.« less

Mesoscale data assimilation for a local severe rainfall event with the NHM-LETKF system

NASA Astrophysics Data System (ADS)

Kunii, M.

2013-12-01

This study aims to improve forecasts of local severe weather events through data assimilation and ensemble forecasting approaches. Here, the local ensemble transform Kalman filter (LETKF) is implemented with the Japan Meteorological Agency's nonhydrostatic model (NHM). The newly developed NHM-LETKF contains an adaptive inflation scheme and a spatial covariance localization scheme with physical distance. One-way nested analysis in which a finer-resolution LETKF is conducted by using the outputs of an outer model also becomes feasible. These new contents should enhance the potential of the LETKF for convective scale events. The NHM-LETKF is applied to a local severe rainfall event in Japan in 2012. Comparison of the root mean square errors between the model first guess and analysis reveals that the system assimilates observations appropriately. Analysis ensemble spreads indicate a significant increase around the time torrential rainfall occurred, which would imply an increase in the uncertainty of environmental fields. Forecasts initialized with LETKF analyses successfully capture intense rainfalls, suggesting that the system can work effectively for local severe weather. Investigation of probabilistic forecasts by ensemble forecasting indicates that this could become a reliable data source for decision making in the future. A one-way nested data assimilation scheme is also tested. The experiment results demonstrate that assimilation with a finer-resolution model provides an advantage in the quantitative precipitation forecasting of local severe weather conditions.

Collective strong coupling with homogeneous Rabi frequencies using a 3D lumped element microwave resonator

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

Angerer, Andreas, E-mail: andreas.angerer@tuwien.ac.at; Astner, Thomas; Wirtitsch, Daniel

We design and implement 3D-lumped element microwave cavities that spatially focus magnetic fields to a small mode volume. They allow coherent and uniform coupling to electron spins hosted by nitrogen vacancy centers in diamond. We achieve large homogeneous single spin coupling rates, with an enhancement of more than one order of magnitude compared to standard 3D cavities with a fundamental resonance at 3 GHz. Finite element simulations confirm that the magnetic field distribution is homogeneous throughout the entire sample volume, with a root mean square deviation of 1.54%. With a sample containing 10{sup 17} nitrogen vacancy electron spins, we achieve amore » collective coupling strength of Ω = 12 MHz, a cooperativity factor C = 27, and clearly enter the strong coupling regime. This allows to interface a macroscopic spin ensemble with microwave circuits, and the homogeneous Rabi frequency paves the way to manipulate the full ensemble population in a coherent way.« less

Improvement of aerosol optical properties modeling over Eastern Asia with MODIS AOD assimilation in a global non-hydrostatic icosahedral aerosol transport model.

PubMed

Dai, Tie; Schutgens, Nick A J; Goto, Daisuke; Shi, Guangyu; Nakajima, Teruyuki

2014-12-01

A new global aerosol assimilation system adopting a more complex icosahedral grid configuration is developed. Sensitivity tests for the assimilation system are performed utilizing satellite retrieved aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the results over Eastern Asia are analyzed. The assimilated results are validated through independent Aerosol Robotic Network (AERONET) observations. Our results reveal that the ensemble and local patch sizes have little effect on the assimilation performance, whereas the ensemble perturbation method has the largest effect. Assimilation leads to significantly positive effect on the simulated AOD field, improving agreement with all of the 12 AERONET sites over the Eastern Asia based on both the correlation coefficient and the root mean square difference (assimilation efficiency). Meanwhile, better agreement of the Ångström Exponent (AE) field is achieved for 8 of the 12 sites due to the assimilation of AOD only. Copyright © 2014 Elsevier Ltd. All rights reserved.

Discrete square root smoothing.

NASA Technical Reports Server (NTRS)

Kaminski, P. G.; Bryson, A. E., Jr.

1972-01-01

The basic techniques applied in the square root least squares and square root filtering solutions are applied to the smoothing problem. Both conventional and square root solutions are obtained by computing the filtered solutions, then modifying the results to include the effect of all measurements. A comparison of computation requirements indicates that the square root information smoother (SRIS) is more efficient than conventional solutions in a large class of fixed interval smoothing problems.

Dynamical downscaling of regional climate over eastern China using RSM with multiple physics scheme ensembles

NASA Astrophysics Data System (ADS)

Peishu, Zong; Jianping, Tang; Shuyu, Wang; Lingyun, Xie; Jianwei, Yu; Yunqian, Zhu; Xiaorui, Niu; Chao, Li

2017-08-01

The parameterization of physical processes is one of the critical elements to properly simulate the regional climate over eastern China. It is essential to conduct detailed analyses on the effect of physical parameterization schemes on regional climate simulation, to provide more reliable regional climate change information. In this paper, we evaluate the 25-year (1983-2007) summer monsoon climate characteristics of precipitation and surface air temperature by using the regional spectral model (RSM) with different physical schemes. The ensemble results using the reliability ensemble averaging (REA) method are also assessed. The result shows that the RSM model has the capacity to reproduce the spatial patterns, the variations, and the temporal tendency of surface air temperature and precipitation over eastern China. And it tends to predict better climatology characteristics over the Yangtze River basin and the South China. The impact of different physical schemes on RSM simulations is also investigated. Generally, the CLD3 cloud water prediction scheme tends to produce larger precipitation because of its overestimation of the low-level moisture. The systematic biases derived from the KF2 cumulus scheme are larger than those from the RAS scheme. The scale-selective bias correction (SSBC) method improves the simulation of the temporal and spatial characteristics of surface air temperature and precipitation and advances the circulation simulation capacity. The REA ensemble results show significant improvement in simulating temperature and precipitation distribution, which have much higher correlation coefficient and lower root mean square error. The REA result of selected experiments is better than that of nonselected experiments, indicating the necessity of choosing better ensemble samples for ensemble.

Assessment of Surface Air Temperature over China Using Multi-criterion Model Ensemble Framework

NASA Astrophysics Data System (ADS)

Li, J.; Zhu, Q.; Su, L.; He, X.; Zhang, X.

2017-12-01

The General Circulation Models (GCMs) are designed to simulate the present climate and project future trends. It has been noticed that the performances of GCMs are not always in agreement with each other over different regions. Model ensemble techniques have been developed to post-process the GCMs' outputs and improve their prediction reliabilities. To evaluate the performances of GCMs, root-mean-square error, correlation coefficient, and uncertainty are commonly used statistical measures. However, the simultaneous achievements of these satisfactory statistics cannot be guaranteed when using many model ensemble techniques. Meanwhile, uncertainties and future scenarios are critical for Water-Energy management and operation. In this study, a new multi-model ensemble framework was proposed. It uses a state-of-art evolutionary multi-objective optimization algorithm, termed Multi-Objective Complex Evolution Global Optimization with Principle Component Analysis and Crowding Distance (MOSPD), to derive optimal GCM ensembles and demonstrate the trade-offs among various solutions. Such trade-off information was further analyzed with a robust Pareto front with respect to different statistical measures. A case study was conducted to optimize the surface air temperature (SAT) ensemble solutions over seven geographical regions of China for the historical period (1900-2005) and future projection (2006-2100). The results showed that the ensemble solutions derived with MOSPD algorithm are superior over the simple model average and any single model output during the historical simulation period. For the future prediction, the proposed ensemble framework identified that the largest SAT change would occur in the South Central China under RCP 2.6 scenario, North Eastern China under RCP 4.5 scenario, and North Western China under RCP 8.5 scenario, while the smallest SAT change would occur in the Inner Mongolia under RCP 2.6 scenario, South Central China under RCP 4.5 scenario, and South Central China under RCP 8.5 scenario.

Insights about data assimilation frameworks for integrating GRACE with hydrological models

NASA Astrophysics Data System (ADS)

Schumacher, Maike; Kusche, Jürgen; Van Dijk, Albert I. J. M.; Döll, Petra; Schuh, Wolf-Dieter

2016-04-01

Improving the understanding of changes in the water cycle represents a challenging objective that requires merging information from various disciplines. Debates exist on selecting an appropriate assimilation technique to integrate GRACE-derived terrestrial water storage changes (TWSC) into hydrological models in order to downscale and disaggregate GRACE TWSC, overcome model limitations, and improve monitoring and forecast skills. Yet, the effect of the specific data assimilation technique in conjunction with ill-conditioning, colored noise, resolution mismatch between GRACE and model, and other complications is still unclear. Due to its simplicity, ensemble Kalman filters or smoothers (EnKF/S) are often applied. In this study, we show that modification of the filter approach might open new avenues to improve the integration process. Particularly, we discuss an improved calibration and data assimilation (C/DA) framework (Schumacher et al., 2016), which is based on the EnKF and was extended by the square root analysis scheme (SQRA) and the singular evolutive interpolated Kalman (SEIK) filter. In addition, we discuss an off-line data blending approach (Van Dijk et al., 2014) that offers the chance to merge multi-model ensembles with GRACE observations. The investigations include: (i) a theoretical comparison, focusing on similarities and differences of the conceptual formulation of the filter algorithms, (ii) a practical comparison, for which the approaches were applied to an ensemble of runs of the WaterGAP Global Hydrology Model (WGHM), as well as (iii) an impact assessment of the GRACE error structure on C/DA results. First, a synthetic experiment over the Mississippi River Basin (USA) was used to gain insights about the C/DA set-up before applying it to real data. The results indicated promising performances when considering alternative methods, e.g. applying the SEIK algorithm improved the correlation coefficient and root mean square error (RMSE) of TWSC by 0.1 and 6 mm, with respect to the EnKF. We successfully transferred our framework to the Murray-Darling Basin (Australia), one of the largest and driest river basins over the world. Finally, we provide recommendations on an optimal C/DA strategy for real GRACE data integrations. Schumacher M, Kusche J, Döll P (2016): A Systematic Impact Assessment of GRACE Error Correlation on Data Assimilation in Hydrological Models. J Geod Van Dijk AIJM, Renzullo LJ, Wada Y, Tregoning P (2014): A global water cycle reanalysis (2003-2012) merging satellite gravimetry and altimetry observations with a hydrological multi-model ensemble. Hydrol Earth Syst Sci

An algorithm for propagating the square-root covariance matrix in triangular form

NASA Technical Reports Server (NTRS)

Tapley, B. D.; Choe, C. Y.

1976-01-01

A method for propagating the square root of the state error covariance matrix in lower triangular form is described. The algorithm can be combined with any triangular square-root measurement update algorithm to obtain a triangular square-root sequential estimation algorithm. The triangular square-root algorithm compares favorably with the conventional sequential estimation algorithm with regard to computation time.

Prediction of the distillation temperatures of crude oils using ¹H NMR and support vector regression with estimated confidence intervals.

PubMed

Filgueiras, Paulo R; Terra, Luciana A; Castro, Eustáquio V R; Oliveira, Lize M S L; Dias, Júlio C M; Poppi, Ronei J

2015-09-01

This paper aims to estimate the temperature equivalent to 10% (T10%), 50% (T50%) and 90% (T90%) of distilled volume in crude oils using (1)H NMR and support vector regression (SVR). Confidence intervals for the predicted values were calculated using a boosting-type ensemble method in a procedure called ensemble support vector regression (eSVR). The estimated confidence intervals obtained by eSVR were compared with previously accepted calculations from partial least squares (PLS) models and a boosting-type ensemble applied in the PLS method (ePLS). By using the proposed boosting strategy, it was possible to identify outliers in the T10% property dataset. The eSVR procedure improved the accuracy of the distillation temperature predictions in relation to standard PLS, ePLS and SVR. For T10%, a root mean square error of prediction (RMSEP) of 11.6°C was obtained in comparison with 15.6°C for PLS, 15.1°C for ePLS and 28.4°C for SVR. The RMSEPs for T50% were 24.2°C, 23.4°C, 22.8°C and 14.4°C for PLS, ePLS, SVR and eSVR, respectively. For T90%, the values of RMSEP were 39.0°C, 39.9°C and 39.9°C for PLS, ePLS, SVR and eSVR, respectively. The confidence intervals calculated by the proposed boosting methodology presented acceptable values for the three properties analyzed; however, they were lower than those calculated by the standard methodology for PLS. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterizing ISI and sub-threshold membrane potential distributions: Ensemble of IF neurons with random squared-noise intensity.

PubMed

Kumar, Sanjeev; Karmeshu

2018-04-01

A theoretical investigation is presented that characterizes the emerging sub-threshold membrane potential and inter-spike interval (ISI) distributions of an ensemble of IF neurons that group together and fire together. The squared-noise intensity σ 2 of the ensemble of neurons is treated as a random variable to account for the electrophysiological variations across population of nearly identical neurons. Employing superstatistical framework, both ISI distribution and sub-threshold membrane potential distribution of neuronal ensemble are obtained in terms of generalized K-distribution. The resulting distributions exhibit asymptotic behavior akin to stretched exponential family. Extensive simulations of the underlying SDE with random σ 2 are carried out. The results are found to be in excellent agreement with the analytical results. The analysis has been extended to cover the case corresponding to independent random fluctuations in drift in addition to random squared-noise intensity. The novelty of the proposed analytical investigation for the ensemble of IF neurons is that it yields closed form expressions of probability distributions in terms of generalized K-distribution. Based on a record of spiking activity of thousands of neurons, the findings of the proposed model are validated. The squared-noise intensity σ 2 of identified neurons from the data is found to follow gamma distribution. The proposed generalized K-distribution is found to be in excellent agreement with that of empirically obtained ISI distribution of neuronal ensemble. Copyright © 2018 Elsevier B.V. All rights reserved.

Ensemble averaging and stacking of ARIMA and GSTAR model for rainfall forecasting

NASA Astrophysics Data System (ADS)

Anggraeni, D.; Kurnia, I. F.; Hadi, A. F.

2018-04-01

Unpredictable rainfall changes can affect human activities, such as in agriculture, aviation, shipping which depend on weather forecasts. Therefore, we need forecasting tools with high accuracy in predicting the rainfall in the future. This research focus on local forcasting of the rainfall at Jember in 2005 until 2016, from 77 rainfall stations. The rainfall here was not only related to the occurrence of the previous of its stations, but also related to others, it’s called the spatial effect. The aim of this research is to apply the GSTAR model, to determine whether there are some correlations of spatial effect between one to another stations. The GSTAR model is an expansion of the space-time model that combines the time-related effects, the locations (stations) in a time series effects, and also the location it self. The GSTAR model will also be compared to the ARIMA model that completely ignores the independent variables. The forcested value of the ARIMA and of the GSTAR models then being combined using the ensemble forecasting technique. The averaging and stacking method of ensemble forecasting method here provide us the best model with higher acuracy model that has the smaller RMSE (Root Mean Square Error) value. Finally, with the best model we can offer a better local rainfall forecasting in Jember for the future.

Prediction of drug synergy in cancer using ensemble-based machine learning techniques

NASA Astrophysics Data System (ADS)

Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder

2018-04-01

Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

Model-based assessment of a Northwestern Tropical Pacific moored array to monitor intraseasonal variability

NASA Astrophysics Data System (ADS)

Liu, Danian; Zhu, Jiang; Shu, Yeqiang; Wang, Dongxiao; Wang, Weiqiang; Cai, Shuqun

2018-06-01

The Northwestern Tropical Pacific Ocean (NWTPO) moorings observing system, including 15 moorings, was established in 2013 to provide velocity profile data. Observing system simulation experiments (OSSEs) were carried out to assess the ability of the observation system to monitor intraseasonal variability in a pilot study, where ideal "mooring-observed" velocity was assimilated using Ensemble Optimal Interpolation (EnOI) based on the Regional Oceanic Modeling System (ROMS). Because errors between the control and "nature" runs have a mesoscale structure, a random ensemble derived from 20-90-day bandpass-filtered nine-year model outputs is proved to be more appropriate for the NWTPO mooring array assimilation than a random ensemble derived from a 30-day running mean. The simulation of the intraseasonal currents in the North Equatorial Current (NEC), North Equatorial Countercurrent (NECC), and Equatorial Undercurrent (EUC) areas can be improved by assimilating velocity profiles using a 20-90-day bandpass-filtered ensemble. The root mean square errors (RMSEs) of the intraseasonal zonal (U) and meridional velocity (V) above 500 m depth within the study area (between 0°N-18°N and 122°E-147°E) were reduced by 15.4% and 16.9%, respectively. Improvements in the downstream area of the NEC moorings transect were optimum where the RMSEs of the intraseasonal velocities above 500 m were reduced by more than 30%. Assimilating velocity profiles can have a positive impact on the simulation and forecast of thermohaline structure and sea level anomalies in the ocean.

Collective Dynamics of Specific Gene Ensembles Crucial for Neutrophil Differentiation: The Existence of Genome Vehicles Revealed

PubMed Central

Giuliani, Alessandro; Tomita, Masaru

2010-01-01

Cell fate decision remarkably generates specific cell differentiation path among the multiple possibilities that can arise through the complex interplay of high-dimensional genome activities. The coordinated action of thousands of genes to switch cell fate decision has indicated the existence of stable attractors guiding the process. However, origins of the intracellular mechanisms that create “cellular attractor” still remain unknown. Here, we examined the collective behavior of genome-wide expressions for neutrophil differentiation through two different stimuli, dimethyl sulfoxide (DMSO) and all-trans-retinoic acid (atRA). To overcome the difficulties of dealing with single gene expression noises, we grouped genes into ensembles and analyzed their expression dynamics in correlation space defined by Pearson correlation and mutual information. The standard deviation of correlation distributions of gene ensembles reduces when the ensemble size is increased following the inverse square root law, for both ensembles chosen randomly from whole genome and ranked according to expression variances across time. Choosing the ensemble size of 200 genes, we show the two probability distributions of correlations of randomly selected genes for atRA and DMSO responses overlapped after 48 hours, defining the neutrophil attractor. Next, tracking the ranked ensembles' trajectories, we noticed that only certain, not all, fall into the attractor in a fractal-like manner. The removal of these genome elements from the whole genomes, for both atRA and DMSO responses, destroys the attractor providing evidence for the existence of specific genome elements (named “genome vehicle”) responsible for the neutrophil attractor. Notably, within the genome vehicles, genes with low or moderate expression changes, which are often considered noisy and insignificant, are essential components for the creation of the neutrophil attractor. Further investigations along with our findings might provide a comprehensive mechanistic view of cell fate decision. PMID:20725638

Preservation of physical properties with Ensemble-type Kalman Filter Algorithms

NASA Astrophysics Data System (ADS)

Janjic, T.

2017-12-01

We show the behavior of the localized Ensemble Kalman filter (EnKF) with respect to preservation of positivity, conservation of mass, energy and enstrophy in toy models that conserve these properties. In order to preserve physical properties in the analysis as well as to deal with the non-Gaussianity in an EnKF framework, Janjic et al. 2014 proposed the use of physically based constraints in the analysis step to constrain the solution. In particular, constraints were used to ensure that the ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. In the study, mass and positivity were both preserved by formulating the filter update as a set of quadratic programming problems that incorporate nonnegativity constraints. Simple numerical experiments indicated that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that were more physically plausible both for individual ensemble members and for the ensemble mean. Moreover, in experiments designed to mimic the most important characteristics of convective motion, it is shown that the mass conservation- and positivity-constrained rain significantly suppresses noise seen in localized EnKF results. This is highly desirable in order to avoid spurious storms from appearing in the forecast starting from this initial condition (Lange and Craig 2014). In addition, the root mean square error is reduced for all fields and total mass of the rain is correctly simulated. Similarly, the enstrophy, divergence, as well as energy spectra can as well be strongly affected by localization radius, thinning interval, and inflation and depend on the variable that is observed (Zeng and Janjic, 2016). We constructed the ensemble data assimilation algorithm that conserves mass, total energy and enstrophy (Zeng et al., 2017). With 2D shallow water model experiments, it is found that the conservation of enstrophy within the data assimilation effectively avoids the spurious energy cascade of rotational part and thereby successfully suppresses the noise generated by the data assimilation algorithm. The 14-day deterministic and ensemble free forecast, starting from the initial condition enforced by both total energy and enstrophy constraints, produces the best prediction.

Application Bayesian Model Averaging method for ensemble system for Poland

NASA Astrophysics Data System (ADS)

Guzikowski, Jakub; Czerwinska, Agnieszka

2014-05-01

The aim of the project is to evaluate methods for generating numerical ensemble weather prediction using a meteorological data from The Weather Research & Forecasting Model and calibrating this data by means of Bayesian Model Averaging (WRF BMA) approach. We are constructing height resolution short range ensemble forecasts using meteorological data (temperature) generated by nine WRF's models. WRF models have 35 vertical levels and 2.5 km x 2.5 km horizontal resolution. The main emphasis is that the used ensemble members has a different parameterization of the physical phenomena occurring in the boundary layer. To calibrate an ensemble forecast we use Bayesian Model Averaging (BMA) approach. The BMA predictive Probability Density Function (PDF) is a weighted average of predictive PDFs associated with each individual ensemble member, with weights that reflect the member's relative skill. For test we chose a case with heat wave and convective weather conditions in Poland area from 23th July to 1st August 2013. From 23th July to 29th July 2013 temperature oscillated below or above 30 Celsius degree in many meteorology stations and new temperature records were added. During this time the growth of the hospitalized patients with cardiovascular system problems was registered. On 29th July 2013 an advection of moist tropical air masses was recorded in the area of Poland causes strong convection event with mesoscale convection system (MCS). MCS caused local flooding, damage to the transport infrastructure, destroyed buildings, trees and injuries and direct threat of life. Comparison of the meteorological data from ensemble system with the data recorded on 74 weather stations localized in Poland is made. We prepare a set of the model - observations pairs. Then, the obtained data from single ensemble members and median from WRF BMA system are evaluated on the basis of the deterministic statistical error Root Mean Square Error (RMSE), Mean Absolute Error (MAE). To evaluation probabilistic data The Brier Score (BS) and Continuous Ranked Probability Score (CRPS) were used. Finally comparison between BMA calibrated data and data from ensemble members will be displayed.

Three key residues form a critical contact network in a protein folding transition state

NASA Astrophysics Data System (ADS)

Vendruscolo, Michele; Paci, Emanuele; Dobson, Christopher M.; Karplus, Martin

2001-02-01

Determining how a protein folds is a central problem in structural biology. The rate of folding of many proteins is determined by the transition state, so that a knowledge of its structure is essential for understanding the protein folding reaction. Here we use mutation measurements-which determine the role of individual residues in stabilizing the transition state-as restraints in a Monte Carlo sampling procedure to determine the ensemble of structures that make up the transition state. We apply this approach to the experimental data for the 98-residue protein acylphosphatase, and obtain a transition-state ensemble with the native-state topology and an average root-mean-square deviation of 6Å from the native structure. Although about 20 residues with small positional fluctuations form the structural core of this transition state, the native-like contact network of only three of these residues is sufficient to determine the overall fold of the protein. This result reveals how a nucleation mechanism involving a small number of key residues can lead to folding of a polypeptide chain to its unique native-state structure.

Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

NASA Astrophysics Data System (ADS)

Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

2017-03-01

Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.

Delayed ripple counter simplifies square-root computation

NASA Technical Reports Server (NTRS)

Cliff, R.

1965-01-01

Ripple subtract technique simplifies the logic circuitry required in a binary computing device to derive the square root of a number. Successively higher numbers are subtracted from a register containing the number out of which the square root is to be extracted. The last number subtracted will be the closest integer to the square root of the number.

Discrete square root filtering - A survey of current techniques.

NASA Technical Reports Server (NTRS)

Kaminskii, P. G.; Bryson, A. E., Jr.; Schmidt, S. F.

1971-01-01

Current techniques in square root filtering are surveyed and related by applying a duality association. Four efficient square root implementations are suggested, and compared with three common conventional implementations in terms of computational complexity and precision. It is shown that the square root computational burden should not exceed the conventional by more than 50% in most practical problems. An examination of numerical conditioning predicts that the square root approach can yield twice the effective precision of the conventional filter in ill-conditioned problems. This prediction is verified in two examples.

Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C.; Ryu, D.; Western, A. W.; Su, C.-H.; Crow, W. T.; Robertson, D. E.; Leahy, C.

2014-09-01

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool. Within this context, we assimilate active and passive satellite soil moisture (SSM) retrievals using an ensemble Kalman filter to improve operational flood prediction within a large semi-arid catchment in Australia (>40 000 km2). We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM-DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation and seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided more accurate streamflow prediction (Nash-Sutcliffe efficiency, NS = 0.77) than the lumped model (NS = 0.67) at the catchment outlet. However, this did not ensure good performance at the "ungauged" inner catchments. After SM-DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 27 and 31%, respectively; the NS of the ensemble mean increased by 7 and 38%, respectively; the false alarm ratio was reduced by 15 and 25%, respectively; and the ensemble prediction spread was reduced while its reliability was maintained. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed SSM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM-DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM-DA is effective at improving streamflow ensemble prediction, however, the updated prediction is still poor since SM-DA does not address systematic errors in the model.

Evaluation of data transformations used with the square root and schoolfield models for predicting bacterial growth rate.

PubMed Central

Alber, S A; Schaffner, D W

1992-01-01

A comparison was made between mathematical variations of the square root and Schoolfield models for predicting growth rate as a function of temperature. The statistical consequences of square root and natural logarithm transformations of growth rate use in several variations of the Schoolfield and square root models were examined. Growth rate variances of Yersinia enterocolitica in brain heart infusion broth increased as a function of temperature. The ability of the two data transformations to correct for the heterogeneity of variance was evaluated. A natural logarithm transformation of growth rate was more effective than a square root transformation at correcting for the heterogeneity of variance. The square root model was more accurate than the Schoolfield model when both models used natural logarithm transformation. PMID:1444367

The Drag-based Ensemble Model (DBEM) for Coronal Mass Ejection Propagation

NASA Astrophysics Data System (ADS)

Dumbović, Mateja; Čalogović, Jaša; Vršnak, Bojan; Temmer, Manuela; Mays, M. Leila; Veronig, Astrid; Piantschitsch, Isabell

2018-02-01

The drag-based model for heliospheric propagation of coronal mass ejections (CMEs) is a widely used analytical model that can predict CME arrival time and speed at a given heliospheric location. It is based on the assumption that the propagation of CMEs in interplanetary space is solely under the influence of magnetohydrodynamical drag, where CME propagation is determined based on CME initial properties as well as the properties of the ambient solar wind. We present an upgraded version, the drag-based ensemble model (DBEM), that covers ensemble modeling to produce a distribution of possible ICME arrival times and speeds. Multiple runs using uncertainty ranges for the input values can be performed in almost real-time, within a few minutes. This allows us to define the most likely ICME arrival times and speeds, quantify prediction uncertainties, and determine forecast confidence. The performance of the DBEM is evaluated and compared to that of ensemble WSA-ENLIL+Cone model (ENLIL) using the same sample of events. It is found that the mean error is ME = ‑9.7 hr, mean absolute error MAE = 14.3 hr, and root mean square error RMSE = 16.7 hr, which is somewhat higher than, but comparable to ENLIL errors (ME = ‑6.1 hr, MAE = 12.8 hr and RMSE = 14.4 hr). Overall, DBEM and ENLIL show a similar performance. Furthermore, we find that in both models fast CMEs are predicted to arrive earlier than observed, most likely owing to the physical limitations of models, but possibly also related to an overestimation of the CME initial speed for fast CMEs.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

PubMed Central

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928–0.988,  = 0.894–0.954, RMSE = 0.002–0.412, s = 0.001–0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery. PMID:28059133

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme.

PubMed

Leong, Max K; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-06

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r 2  = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK i values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r 2  = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q 2  = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Quantifying polypeptide conformational space: sensitivity to conformation and ensemble definition.

PubMed

Sullivan, David C; Lim, Carmay

2006-08-24

Quantifying the density of conformations over phase space (the conformational distribution) is needed to model important macromolecular processes such as protein folding. In this work, we quantify the conformational distribution for a simple polypeptide (N-mer polyalanine) using the cumulative distribution function (CDF), which gives the probability that two randomly selected conformations are separated by less than a "conformational" distance and whose inverse gives conformation counts as a function of conformational radius. An important finding is that the conformation counts obtained by the CDF inverse depend critically on the assignment of a conformation's distance span and the ensemble (e.g., unfolded state model): varying ensemble and conformation definition (1 --> 2 A) varies the CDF-based conformation counts for Ala(50) from 10(11) to 10(69). In particular, relatively short molecular dynamics (MD) relaxation of Ala(50)'s random-walk ensemble reduces the number of conformers from 10(55) to 10(14) (using a 1 A root-mean-square-deviation radius conformation definition) pointing to potential disconnections in comparing the results from simplified models of unfolded proteins with those from all-atom MD simulations. Explicit waters are found to roughen the landscape considerably. Under some common conformation definitions, the results herein provide (i) an upper limit to the number of accessible conformations that compose unfolded states of proteins, (ii) the optimal clustering radius/conformation radius for counting conformations for a given energy and solvent model, (iii) a means of comparing various studies, and (iv) an assessment of the applicability of random search in protein folding.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

NASA Astrophysics Data System (ADS)

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Independent Metrics for Protein Backbone and Side-Chain Flexibility: Time Scales and Effects of Ligand Binding.

PubMed

Fuchs, Julian E; Waldner, Birgit J; Huber, Roland G; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-03-10

Conformational dynamics are central for understanding biomolecular structure and function, since biological macromolecules are inherently flexible at room temperature and in solution. Computational methods are nowadays capable of providing valuable information on the conformational ensembles of biomolecules. However, analysis tools and intuitive metrics that capture dynamic information from in silico generated structural ensembles are limited. In standard work-flows, flexibility in a conformational ensemble is represented through residue-wise root-mean-square fluctuations or B-factors following a global alignment. Consequently, these approaches relying on global alignments discard valuable information on local dynamics. Results inherently depend on global flexibility, residue size, and connectivity. In this study we present a novel approach for capturing positional fluctuations based on multiple local alignments instead of one single global alignment. The method captures local dynamics within a structural ensemble independent of residue type by splitting individual local and global degrees of freedom of protein backbone and side-chains. Dependence on residue type and size in the side-chains is removed via normalization with the B-factors of the isolated residue. As a test case, we demonstrate its application to a molecular dynamics simulation of bovine pancreatic trypsin inhibitor (BPTI) on the millisecond time scale. This allows for illustrating different time scales of backbone and side-chain flexibility. Additionally, we demonstrate the effects of ligand binding on side-chain flexibility of three serine proteases. We expect our new methodology for quantifying local flexibility to be helpful in unraveling local changes in biomolecular dynamics.

Molecular dynamic of curcumin/chitosan interaction using a computational molecular approach: Emphasis on biofilm reduction.

PubMed

Khezri, Azam; Karimi, Arsalan; Yazdian, Fatemeh; Jokar, Mahmoud; Mofradnia, Soheil Rezazadeh; Rashedi, Hamid; Tavakoli, Zahra

2018-07-15

Nanotechnology-based drug delivery systems have been used to enhance bioavailability and biological activities. Chitosan incorporating curcumin can serve as a biocompatible substitute for metallic nanoparticles in preventing biofilm formation of Streptococcus mutans and plaque on teeth. The interactions between chitosan nanoparticle as a carrier and curcumin, a natural antibacterial agent, were simulated. The binding conformation between curcumin-chitosan was obtained using the Lamarckian Genetic Algorithm in Autodock™ software in chitosan nanoparticle. The interaction stability was examined in the molecular dynamic stages, with isothermal-isobaric ensemble in the CHARMM Force Field. The results showed the root mean square deviation (RMSD) and the root mean square fluctuations (RMSF) for all complex's atoms were relaxed after 4ns (RMSD for the all-atoms was 26.81±0.1 (Å); RMSF 1.13±0.02Å). For each section, the estimation of RMSD, RMSF, radius of gyration, inter-H bond and other analysis confirmed that, during the first interval;10ns, there was a stable binding between the two sections. Although all bindings disappeared from 10 to 20ns, the curcumin was trapped inside the chitosan nanoparticles, and no release took place until 20ns, after which the curcumin began to release. This trend suggests that chitosan nanoparticle has ability to carry the curcumin. Copyright © 2018 Elsevier B.V. All rights reserved.

A study on the predictability of the transition day from the dry to the rainy season over South Korea

NASA Astrophysics Data System (ADS)

Lee, Sang-Min; Nam, Ji-Eun; Choi, Hee-Wook; Ha, Jong-Chul; Lee, Yong Hee; Kim, Yeon-Hee; Kang, Hyun-Suk; Cho, ChunHo

2016-08-01

This study was conducted to evaluate the prediction accuracies of THe Observing system Research and Predictability EXperiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data at six operational forecast centers using the root-mean square difference (RMSD) and Brier score (BS) from April to July 2012. And it was performed to test the precipitation predictability of ensemble prediction systems (EPS) on the onset of the summer rainy season, the day of withdrawal in spring drought over South Korea on 29 June 2012 with use of the ensemble mean precipitation, ensemble probability precipitation, 10-day lag ensemble forecasts (ensemble mean and probability precipitation), and effective drought index (EDI). The RMSD analysis of atmospheric variables (geopotential-height at 500 hPa, temperature at 850 hPa, sea-level pressure and specific humidity at 850 hPa) showed that the prediction accuracies of the EPS at the Meteorological Service of Canada (CMC) and China Meteorological Administration (CMA) were poor and those at the European Center for Medium-Range Weather Forecasts (ECMWF) and Korea Meteorological Administration (KMA) were good. Also, ECMWF and KMA showed better results than other EPSs for predicting precipitation in the BS distributions. It is also evaluated that the onset of the summer rainy season could be predicted using ensemble-mean precipitation from 4-day leading time at all forecast centers. In addition, the spatial distributions of predicted precipitation of the EPS at KMA and the Met Office of the United Kingdom (UKMO) were similar to those of observed precipitation; thus, the predictability showed good performance. The precipitation probability forecasts of EPS at CMA, the National Centers for Environmental Prediction (NCEP), and UKMO (ECMWF and KMA) at 1-day lead time produced over-forecasting (under-forecasting) in the reliability diagram. And all the ones at 2˜4-day lead time showed under-forecasting. Also, the precipitation on onset day of the summer rainy season could be predicted from a 4-day lead time to initial time by using the 10-day lag ensemble mean and probability forecasts. Additionally, the predictability for withdrawal day of spring drought to be ended due to precipitation on onset day of summer rainy season was evaluated using Effective Drought Index (EDI) to be calculated by ensemble mean precipitation forecasts and spreads at five EPSs.

A Continuous Square Root in Formation Filter-Swoother with Discrete Data Update

NASA Technical Reports Server (NTRS)

Miller, J. K.

1994-01-01

A differential equation for the square root information matrix is derived and adapted to the problems of filtering and smoothing. The resulting continuous square root information filter (SRIF) performs the mapping of state and process noise by numerical integration of the SRIF matrix and admits data via a discrete least square update.

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

Irrational Square Roots

ERIC Educational Resources Information Center

Misiurewicz, Michal

2013-01-01

If students are presented the standard proof of irrationality of [square root]2, can they generalize it to a proof of the irrationality of "[square root]p", "p" a prime if, instead of considering divisibility by "p", they cling to the notions of even and odd used in the standard proof?

Comprehensive evaluation of Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme over the Tibetan plateau

NASA Astrophysics Data System (ADS)

Ma, Yingzhao; Yang, Yuan; Han, Zhongying; Tang, Guoqiang; Maguire, Lane; Chu, Zhigang; Hong, Yang

2018-01-01

The objective of this study is to comprehensively evaluate the new Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme (EMSPD-DBMA) at daily and 0.25° scales from 2001 to 2015 over the Tibetan Plateau (TP). Error analysis against gauge observations revealed that EMSPD-DBMA captured the spatiotemporal pattern of daily precipitation with an acceptable Correlation Coefficient (CC) of 0.53 and a Relative Bias (RB) of -8.28%. Moreover, EMSPD-DBMA outperformed IMERG and GSMaP-MVK in almost all metrics in the summers of 2014 and 2015, with the lowest RB and Root Mean Square Error (RMSE) values of -2.88% and 8.01 mm/d, respectively. It also better reproduced the Probability Density Function (PDF) in terms of daily rainfall amount and estimated moderate and heavy rainfall better than both IMERG and GSMaP-MVK. Further, hydrological evaluation with the Coupled Routing and Excess STorage (CREST) model in the Upper Yangtze River region indicated that the EMSPD-DBMA forced simulation showed satisfying hydrological performance in terms of streamflow prediction, with Nash-Sutcliffe coefficient of Efficiency (NSE) values of 0.82 and 0.58, compared to gauge forced simulation (0.88 and 0.60) at the calibration and validation periods, respectively. EMSPD-DBMA also performed a greater fitness for peak flow simulation than a new Multi-Source Weighted-Ensemble Precipitation Version 2 (MSWEP V2) product, indicating a promising prospect of hydrological utility for the ensemble satellite precipitation data. This study belongs to early comprehensive evaluation of the blended multi-satellite precipitation data across the TP, which would be significant for improving the DBMA algorithm in regions with complex terrain.

Ensemble data assimilation of total column ozone using a coupled meteorology-chemistry model and its impact on the structure of Typhoon Nabi (2005)

NASA Astrophysics Data System (ADS)

Lim, S.; Park, S. K.; Zupanski, M.

2015-09-01

Ozone (O3) plays an important role in chemical reactions and is usually incorporated in chemical data assimilation (DA). In tropical cyclones (TCs), O3 usually shows a lower concentration inside the eyewall and an elevated concentration around the eye, impacting meteorological as well as chemical variables. To identify the impact of O3 observations on TC structure, including meteorological and chemical information, we developed a coupled meteorology-chemistry DA system by employing the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and an ensemble-based DA algorithm - the maximum likelihood ensemble filter (MLEF). For a TC case that occurred over East Asia, Typhoon Nabi (2005), our results indicate that the ensemble forecast is reasonable, accompanied with larger background state uncertainty over the TC, and also over eastern China. Similarly, the assimilation of O3 observations impacts meteorological and chemical variables near the TC and over eastern China. The strongest impact on air quality in the lower troposphere was over China, likely due to the pollution advection. In the vicinity of the TC, however, the strongest impact on chemical variables adjustment was at higher levels. The impact on meteorological variables was similar in both over China and near the TC. The analysis results are verified using several measures that include the cost function, root mean square (RMS) error with respect to observations, and degrees of freedom for signal (DFS). All measures indicate a positive impact of DA on the analysis - the cost function and RMS error have decreased by 16.9 and 8.87 %, respectively. In particular, the DFS indicates a strong positive impact of observations in the TC area, with a weaker maximum over northeastern China.

Identifying pollution sources and predicting urban air quality using ensemble learning methods

NASA Astrophysics Data System (ADS)

Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

2013-12-01

In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow (India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.

Prediction skill of rainstorm events over India in the TIGGE weather prediction models

NASA Astrophysics Data System (ADS)

Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

2017-12-01

Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

Assessment of SWE data assimilation for ensemble streamflow predictions

NASA Astrophysics Data System (ADS)

Franz, Kristie J.; Hogue, Terri S.; Barik, Muhammad; He, Minxue

2014-11-01

An assessment of data assimilation (DA) for Ensemble Streamflow Prediction (ESP) using seasonal water supply hindcasting in the North Fork of the American River Basin (NFARB) and the National Weather Service (NWS) hydrologic forecast models is undertaken. Two parameter sets, one from the California Nevada River Forecast Center (RFC) and one from the Differential Evolution Adaptive Metropolis (DREAM) algorithm, are tested. For each parameter set, hindcasts are generated using initial conditions derived with and without the inclusion of a DA scheme that integrates snow water equivalent (SWE) observations. The DREAM-DA scenario uses an Integrated Uncertainty and Ensemble-based data Assimilation (ICEA) framework that also considers model and parameter uncertainty. Hindcasts are evaluated using deterministic and probabilistic forecast verification metrics. In general, the impact of DA on the skill of the seasonal water supply predictions is mixed. For deterministic (ensemble mean) predictions, the Percent Bias (PBias) is improved with integration of the DA. DREAM-DA and the RFC-DA have the lowest biases and the RFC-DA has the lowest Root Mean Squared Error (RMSE). However, the RFC and DREAM-DA have similar RMSE scores. For the probabilistic predictions, the RFC and DREAM have the highest Continuous Ranked Probability Skill Scores (CRPSS) and the RFC has the best discrimination for low flows. Reliability results are similar between the non-DA and DA tests and the DREAM and DREAM-DA have better reliability than the RFC and RFC-DA for forecast dates February 1 and later. Despite producing improved streamflow simulations in previous studies, the hindcast analysis suggests that the DA method tested may not result in obvious improvements in streamflow forecasts. We advocate that integration of hindcasting and probabilistic metrics provides more rigorous insight on model performance for forecasting applications, such as in this study.

New method for propagating the square root covariance matrix in triangular form. [using Kalman-Bucy filter

NASA Technical Reports Server (NTRS)

Choe, C. Y.; Tapley, B. D.

1975-01-01

A method proposed by Potter of applying the Kalman-Bucy filter to the problem of estimating the state of a dynamic system is described, in which the square root of the state error covariance matrix is used to process the observations. A new technique which propagates the covariance square root matrix in lower triangular form is given for the discrete observation case. The technique is faster than previously proposed algorithms and is well-adapted for use with the Carlson square root measurement algorithm.

Microcanonical-ensemble computer simulation of the high-temperature expansion coefficients of the Helmholtz free energy of a square-well fluid

NASA Astrophysics Data System (ADS)

Sastre, Francisco; Moreno-Hilario, Elizabeth; Sotelo-Serna, Maria Guadalupe; Gil-Villegas, Alejandro

2018-02-01

The microcanonical-ensemble computer simulation method (MCE) is used to evaluate the perturbation terms Ai of the Helmholtz free energy of a square-well (SW) fluid. The MCE method offers a very efficient and accurate procedure for the determination of perturbation terms of discrete-potential systems such as the SW fluid and surpass the standard NVT canonical ensemble Monte Carlo method, allowing the calculation of the first six expansion terms. Results are presented for the case of a SW potential with attractive ranges 1.1 ≤ λ ≤ 1.8. Using semi-empirical representation of the MCE values for Ai, we also discuss the accuracy in the determination of the phase diagram of this system.

Assimilation of IASI partial tropospheric columns with an Ensemble Kalman Filter over Europe

NASA Astrophysics Data System (ADS)

Coman, A.; Foret, G.; Beekmann, M.; Eremenko, M.; Dufour, G.; Gaubert, B.; Ung, A.; Schmechtig, C.; Flaud, J.-M.; Bergametti, G.

2012-03-01

Partial lower tropospheric ozone columns provided by the IASI (Infrared Atmospheric Sounding Interferometer) instrument have been assimilated into a chemistry-transport model at continental scale (CHIMERE) using an Ensemble Square Root Kalman Filter (EnSRF). Analyses are made for the month of July 2007 over the European domain. Launched in 2006, aboard the MetOp-A satellite, IASI shows high sensitivity for ozone in the free troposphere and low sensitivity at the ground; therefore it is important to evaluate if assimilation of these observations can improve free tropospheric ozone, and possibly surface ozone. The analyses are validated against independent ozone observations from sondes, MOZAIC1 aircraft and ground based stations (AIRBASE - the European Air quality dataBase) and compared with respect to the free run of CHIMERE. These comparisons show a decrease in error of 6 parts-per-billion (ppb) in the free troposphere over the Frankfurt area, and also a reduction of the root mean square error (respectively bias) at the surface of 19% (33%) for more than 90% of existing ground stations. This provides evidence of the potential of data assimilation of tropospheric IASI columns to better describe the tropospheric ozone distribution, including surface ozone, despite the lower sensitivity. The changes in concentration resulting from the observational constraints were quantified and several geophysical explanations for the findings of this study were drawn. The corrections were most pronounced over Italy and the Mediterranean region, we noted an average reduction of 8-9 ppb in the free troposphere with respect to the free run, and still a reduction of 5.5 ppb at ground, likely due to a longer residence time of air masses in this part associated to the general circulation pattern (i.e. dominant western circulation) and to persistent anticyclonic conditions over the Mediterranean basin. This is an important geophysical result, since the ozone burden is large over this area, with impact on the radiative balance and air quality. 1 Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by in-service AIrbus airCraft (http://mozaic.aero.obs-mip.fr/web/).

Contribution Of The SWOT Mission To Large-Scale Hydrological Modeling Using Data Assimilation

NASA Astrophysics Data System (ADS)

Emery, C. M.; Biancamaria, S.; Boone, A. A.; Ricci, S. M.; Rochoux, M. C.; Garambois, P. A.; Paris, A.; Calmant, S.

2016-12-01

The purpose of this work is to improve water fluxes estimation on the continental surfaces, at interanual and interseasonal scale (from few years to decennial time period). More specifically, it studies contribution of the incoming SWOT satellite mission to improve hydrology model at global scale, and using the land surface model ISBA-TRIP. This model corresponds to the continental component of the CNRM (French meteorological research center)'s climatic model. This study explores the potential of satellite data to correct either input parameters of the river routing scheme TRIP or its state variables. To do so, a data assimilation platform (using an Ensemble Kalman Filter, EnKF) has been implemented to assimilate SWOT virtual observations as well as discharges estimated from real nadir altimetry data. A series of twin experiments is used to test and validate the parameter estimation module of the platform. SWOT virtual-observations of water heights along SWOT tracks (with a 10 cm white noise model error) are assimilated to correct the river routing model parameters. To begin with, we chose to focus exclusively on the river manning coefficient, with the possibility to easily extend to other parameters such as the river widths. First results show that the platform is able to recover the "true" Manning distribution assimilating SWOT-like water heights. The error on the coefficients goes from 35 % before assimilation to 9 % after four SWOT orbit repeat period of 21 days. In the state estimation mode, daily assimilation cycles are realized to correct TRIP river water storage initial state by assimilating ENVISAT-based discharge. Those observations are derived from ENVISAT water elevation measures, using rating curves from the MGB-IPH hydrological model (calibrated over the Amazon using in situ gages discharge). Using such kind of observation allows going beyond idealized twin experiments and also to test contribution of a remotely-sensed discharge product, which could prefigure the SWOT discharge product. The results show that discharge after assimilation are globally improved : the root-mean-square error between the analysis discharge ensemble mean and in situ discharges is reduced by 30 %, compared to the root-mean-square error between the free run and in situ discharges.

The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

NASA Astrophysics Data System (ADS)

Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

2015-05-01

A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

Ensemble learning for spatial interpolation of soil potassium content based on environmental information.

PubMed

Liu, Wei; Du, Peijun; Wang, Dongchen

2015-01-01

One important method to obtain the continuous surfaces of soil properties from point samples is spatial interpolation. In this paper, we propose a method that combines ensemble learning with ancillary environmental information for improved interpolation of soil properties (hereafter, EL-SP). First, we calculated the trend value for soil potassium contents at the Qinghai Lake region in China based on measured values. Then, based on soil types, geology types, land use types, and slope data, the remaining residual was simulated with the ensemble learning model. Next, the EL-SP method was applied to interpolate soil potassium contents at the study site. To evaluate the utility of the EL-SP method, we compared its performance with other interpolation methods including universal kriging, inverse distance weighting, ordinary kriging, and ordinary kriging combined geographic information. Results show that EL-SP had a lower mean absolute error and root mean square error than the data produced by the other models tested in this paper. Notably, the EL-SP maps can describe more locally detailed information and more accurate spatial patterns for soil potassium content than the other methods because of the combined use of different types of environmental information; these maps are capable of showing abrupt boundary information for soil potassium content. Furthermore, the EL-SP method not only reduces prediction errors, but it also compliments other environmental information, which makes the spatial interpolation of soil potassium content more reasonable and useful.

Downscaling Satellite Data for Predicting Catchment-scale Root Zone Soil Moisture with Ground-based Sensors and an Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Lin, H.; Baldwin, D. C.; Smithwick, E. A. H.

2015-12-01

Predicting root zone (0-100 cm) soil moisture (RZSM) content at a catchment-scale is essential for drought and flood predictions, irrigation planning, weather forecasting, and many other applications. Satellites, such as the NASA Soil Moisture Active Passive (SMAP), can estimate near-surface (0-5 cm) soil moisture content globally at coarse spatial resolutions. We develop a hierarchical Ensemble Kalman Filter (EnKF) data assimilation modeling system to downscale satellite-based near-surface soil moisture and to estimate RZSM content across the Shale Hills Critical Zone Observatory at a 1-m resolution in combination with ground-based soil moisture sensor data. In this example, a simple infiltration model within the EnKF-model has been parameterized for 6 soil-terrain units to forecast daily RZSM content in the catchment from 2009 - 2012 based on AMSRE. LiDAR-derived terrain variables define intra-unit RZSM variability using a novel covariance localization technique. This method also allows the mapping of uncertainty with our RZSM estimates for each time-step. A catchment-wide satellite-to-surface downscaling parameter, which nudges the satellite measurement closer to in situ near-surface data, is also calculated for each time-step. We find significant differences in predicted root zone moisture storage for different terrain units across the experimental time-period. Root mean square error from a cross-validation analysis of RZSM predictions using an independent dataset of catchment-wide in situ Time-Domain Reflectometry (TDR) measurements ranges from 0.060-0.096 cm3 cm-3, and the RZSM predictions are significantly (p < 0.05) correlated with TDR measurements [r = 0.47-0.68]. The predictive skill of this data assimilation system is similar to the Penn State Integrated Hydrologic Modeling (PIHM) system. Uncertainty estimates are significantly (p < 0.05) correlated to cross validation error during wet and dry conditions, but more so in dry summer seasons. Developing an EnKF-model system that downscales satellite data and predicts catchment-scale RZSM content is especially timely, given the anticipated release of SMAP surface moisture data in 2015.

Analog ensemble and Bayesian regression techniques to improve the wind speed prediction during extreme storms in the NE U.S.

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Delle Monache, L.; Alessandrini, S.

2016-12-01

Accuracy of weather forecasts in Northeast U.S. has become very important in recent years, given the serious and devastating effects of extreme weather events. Despite the use of evolved forecasting tools and techniques strengthened by increased super-computing resources, the weather forecasting systems still have their limitations in predicting extreme events. In this study, we examine the combination of analog ensemble and Bayesian regression techniques to improve the prediction of storms that have impacted NE U.S., mostly defined by the occurrence of high wind speeds (i.e. blizzards, winter storms, hurricanes and thunderstorms). The predicted wind speed, wind direction and temperature by two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) are combined using the mentioned techniques, exploring various ways that those variables influence the minimization of the prediction error (systematic and random). This study is focused on retrospective simulations of 146 storms that affected the NE U.S. in the period 2005-2016. In order to evaluate the techniques, leave-one-out cross validation procedure was implemented regarding 145 storms as the training dataset. The analog ensemble method selects a set of past observations that corresponded to the best analogs of the numerical weather prediction and provides a set of ensemble members of the selected observation dataset. The set of ensemble members can then be used in a deterministic or probabilistic way. In the Bayesian regression framework, optimal variances are estimated for the training partition by minimizing the root mean square error and are applied to the out-of-sample storm. The preliminary results indicate a significant improvement in the statistical metrics of 10-m wind speed for 146 storms using both techniques (20-30% bias and error reduction in all observation-model pairs). In this presentation, we discuss the various combinations of atmospheric predictors and techniques and illustrate how the long record of predicted storms is valuable in the improvement of wind speed prediction.

On the Denesting of Nested Square Roots

ERIC Educational Resources Information Center

Gkioulekas, Eleftherios

2017-01-01

We present the basic theory of denesting nested square roots, from an elementary point of view, suitable for lower level coursework. Necessary and sufficient conditions are given for direct denesting, where the nested expression is rewritten as a sum of square roots of rational numbers, and for indirect denesting, where the nested expression is…

Multi-model ensemble hydrologic prediction using Bayesian model averaging

NASA Astrophysics Data System (ADS)

Duan, Qingyun; Ajami, Newsha K.; Gao, Xiaogang; Sorooshian, Soroosh

2007-05-01

Multi-model ensemble strategy is a means to exploit the diversity of skillful predictions from different models. This paper studies the use of Bayesian model averaging (BMA) scheme to develop more skillful and reliable probabilistic hydrologic predictions from multiple competing predictions made by several hydrologic models. BMA is a statistical procedure that infers consensus predictions by weighing individual predictions based on their probabilistic likelihood measures, with the better performing predictions receiving higher weights than the worse performing ones. Furthermore, BMA provides a more reliable description of the total predictive uncertainty than the original ensemble, leading to a sharper and better calibrated probability density function (PDF) for the probabilistic predictions. In this study, a nine-member ensemble of hydrologic predictions was used to test and evaluate the BMA scheme. This ensemble was generated by calibrating three different hydrologic models using three distinct objective functions. These objective functions were chosen in a way that forces the models to capture certain aspects of the hydrograph well (e.g., peaks, mid-flows and low flows). Two sets of numerical experiments were carried out on three test basins in the US to explore the best way of using the BMA scheme. In the first set, a single set of BMA weights was computed to obtain BMA predictions, while the second set employed multiple sets of weights, with distinct sets corresponding to different flow intervals. In both sets, the streamflow values were transformed using Box-Cox transformation to ensure that the probability distribution of the prediction errors is approximately Gaussian. A split sample approach was used to obtain and validate the BMA predictions. The test results showed that BMA scheme has the advantage of generating more skillful and equally reliable probabilistic predictions than original ensemble. The performance of the expected BMA predictions in terms of daily root mean square error (DRMS) and daily absolute mean error (DABS) is generally superior to that of the best individual predictions. Furthermore, the BMA predictions employing multiple sets of weights are generally better than those using single set of weights.

Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems.

PubMed

Liu, Xi; Qu, Hua; Zhao, Jihong; Yue, Pengcheng

2018-05-31

For a nonlinear system, the cubature Kalman filter (CKF) and its square-root version are useful methods to solve the state estimation problems, and both can obtain good performance in Gaussian noises. However, their performances often degrade significantly in the face of non-Gaussian noises, particularly when the measurements are contaminated by some heavy-tailed impulsive noises. By utilizing the maximum correntropy criterion (MCC) to improve the robust performance instead of traditional minimum mean square error (MMSE) criterion, a new square-root nonlinear filter is proposed in this study, named as the maximum correntropy square-root cubature Kalman filter (MCSCKF). The new filter not only retains the advantage of square-root cubature Kalman filter (SCKF), but also exhibits robust performance against heavy-tailed non-Gaussian noises. A judgment condition that avoids numerical problem is also given. The results of two illustrative examples, especially the SINS/GPS integrated systems, demonstrate the desirable performance of the proposed filter. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Markov state models of protein misfolding

NASA Astrophysics Data System (ADS)

Sirur, Anshul; De Sancho, David; Best, Robert B.

2016-02-01

Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity.

Enhancing Students' Understanding of Square Roots

ERIC Educational Resources Information Center

Wiesman, Jeff L.

2015-01-01

Students enrolled in a middle school prealgebra or algebra course often struggle to conceptualize and understand the meaning of radical notation when it is introduced. For example, although it is important for students to approximate the decimal value of a number such as [square root of] 30 and estimate the value of a square root in the form of…

On roots and squares - estimation, intuition and creativity

NASA Astrophysics Data System (ADS)

Patkin, Dorit; Gazit, Avikam

2013-12-01

The paper presents findings of a small scale study of a few items related to problem solving with squares and roots, for different teacher groups (pre-service and in-service mathematics teachers: elementary and junior high school). The research participants were asked to explain what would be the units digit of a natural number to be squared in order to obtain a certain units digit as a result. They were also asked to formulate a rule - an algorithm for calculating the square of a 2-digit number which is a multiple of 5. Based on this knowledge and estimation capability, they were required to find, without using calculators, the square roots of given natural numbers. The findings show that most of the participants had only partial intuition regarding the units' digit of a number which is squared when the units' digit of the square is known. At the same time, the participants manifested some evidence of creativity and flow of ideas in identifying the rule for calculating the square of a natural number whose units digit is 5. However, when asked to identify, by means of estimation and based on knowledge from previous items, the square roots of three natural numbers, only few of them managed to find the three roots by estimation.

In the eye of the beholder: Inhomogeneous distribution of high-resolution shapes within the random-walk ensemble

NASA Astrophysics Data System (ADS)

Müller, Christian L.; Sbalzarini, Ivo F.; van Gunsteren, Wilfred F.; Žagrović, Bojan; Hünenberger, Philippe H.

2009-06-01

The concept of high-resolution shapes (also referred to as folds or states, depending on the context) of a polymer chain plays a central role in polymer science, structural biology, bioinformatics, and biopolymer dynamics. However, although the idea of shape is intuitively very useful, there is no unambiguous mathematical definition for this concept. In the present work, the distributions of high-resolution shapes within the ideal random-walk ensembles with N =3,…,6 beads (or up to N =10 for some properties) are investigated using a systematic (grid-based) approach based on a simple working definition of shapes relying on the root-mean-square atomic positional deviation as a metric (i.e., to define the distance between pairs of structures) and a single cutoff criterion for the shape assignment. Although the random-walk ensemble appears to represent the paramount of homogeneity and randomness, this analysis reveals that the distribution of shapes within this ensemble, i.e., in the total absence of interatomic interactions characteristic of a specific polymer (beyond the generic connectivity constraint), is significantly inhomogeneous. In particular, a specific (densest) shape occurs with a local probability that is 1.28, 1.79, 2.94, and 10.05 times (N =3,…,6) higher than the corresponding average over all possible shapes (these results can tentatively be extrapolated to a factor as large as about 1028 for N =100). The qualitative results of this analysis lead to a few rather counterintuitive suggestions, namely, that, e.g., (i) a fold classification analysis applied to the random-walk ensemble would lead to the identification of random-walk "folds;" (ii) a clustering analysis applied to the random-walk ensemble would also lead to the identification random-walk "states" and associated relative free energies; and (iii) a random-walk ensemble of polymer chains could lead to well-defined diffraction patterns in hypothetical fiber or crystal diffraction experiments. The inhomogeneous nature of the shape probability distribution identified here for random walks may represent a significant underlying baseline effect in the analysis of real polymer chain ensembles (i.e., in the presence of specific interatomic interactions). As a consequence, a part of what is called a polymer shape may actually reside just "in the eye of the beholder" rather than in the nature of the interactions between the constituting atoms, and the corresponding observation-related bias should be taken into account when drawing conclusions from shape analyses as applied to real structural ensembles.

In the eye of the beholder: Inhomogeneous distribution of high-resolution shapes within the random-walk ensemble.

PubMed

Müller, Christian L; Sbalzarini, Ivo F; van Gunsteren, Wilfred F; Zagrović, Bojan; Hünenberger, Philippe H

2009-06-07

The concept of high-resolution shapes (also referred to as folds or states, depending on the context) of a polymer chain plays a central role in polymer science, structural biology, bioinformatics, and biopolymer dynamics. However, although the idea of shape is intuitively very useful, there is no unambiguous mathematical definition for this concept. In the present work, the distributions of high-resolution shapes within the ideal random-walk ensembles with N=3,...,6 beads (or up to N=10 for some properties) are investigated using a systematic (grid-based) approach based on a simple working definition of shapes relying on the root-mean-square atomic positional deviation as a metric (i.e., to define the distance between pairs of structures) and a single cutoff criterion for the shape assignment. Although the random-walk ensemble appears to represent the paramount of homogeneity and randomness, this analysis reveals that the distribution of shapes within this ensemble, i.e., in the total absence of interatomic interactions characteristic of a specific polymer (beyond the generic connectivity constraint), is significantly inhomogeneous. In particular, a specific (densest) shape occurs with a local probability that is 1.28, 1.79, 2.94, and 10.05 times (N=3,...,6) higher than the corresponding average over all possible shapes (these results can tentatively be extrapolated to a factor as large as about 10(28) for N=100). The qualitative results of this analysis lead to a few rather counterintuitive suggestions, namely, that, e.g., (i) a fold classification analysis applied to the random-walk ensemble would lead to the identification of random-walk "folds;" (ii) a clustering analysis applied to the random-walk ensemble would also lead to the identification random-walk "states" and associated relative free energies; and (iii) a random-walk ensemble of polymer chains could lead to well-defined diffraction patterns in hypothetical fiber or crystal diffraction experiments. The inhomogeneous nature of the shape probability distribution identified here for random walks may represent a significant underlying baseline effect in the analysis of real polymer chain ensembles (i.e., in the presence of specific interatomic interactions). As a consequence, a part of what is called a polymer shape may actually reside just "in the eye of the beholder" rather than in the nature of the interactions between the constituting atoms, and the corresponding observation-related bias should be taken into account when drawing conclusions from shape analyses as applied to real structural ensembles.

47 CFR 15.115 - TV interface devices, including cable system terminal devices.

Code of Federal Regulations, 2014 CFR

2014-10-01

... times the square root of (R) for the video signal and 155 times the square root of (R) for the audio... and 77.5 times the square root of (R) for the audio signal. (2) At any RF output terminal, the maximum... video cassette recorders continue to be subject to the provisions for general TV interface devices. (c...

47 CFR 15.115 - TV interface devices, including cable system terminal devices.

Code of Federal Regulations, 2012 CFR

2012-10-01

... times the square root of (R) for the video signal and 155 times the square root of (R) for the audio... and 77.5 times the square root of (R) for the audio signal. (2) At any RF output terminal, the maximum... video cassette recorders continue to be subject to the provisions for general TV interface devices. (c...

47 CFR 15.115 - TV interface devices, including cable system terminal devices.

Code of Federal Regulations, 2013 CFR

2013-10-01

... times the square root of (R) for the video signal and 155 times the square root of (R) for the audio... and 77.5 times the square root of (R) for the audio signal. (2) At any RF output terminal, the maximum... video cassette recorders continue to be subject to the provisions for general TV interface devices. (c...

Three filters for visualization of phase objects with large variations of phase gradients

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

Sagan, Arkadiusz; Antosiewicz, Tomasz J.; Szoplik, Tomasz

2009-02-20

We propose three amplitude filters for visualization of phase objects. They interact with the spectra of pure-phase objects in the frequency plane and are based on tangent and error functions as well as antisymmetric combination of square roots. The error function is a normalized form of the Gaussian function. The antisymmetric square-root filter is composed of two square-root filters to widen its spatial frequency spectral range. Their advantage over other known amplitude frequency-domain filters, such as linear or square-root graded ones, is that they allow high-contrast visualization of objects with large variations of phase gradients.

Improving Weather Forecasts Through Reduced Precision Data Assimilation

NASA Astrophysics Data System (ADS)

Hatfield, Samuel; Düben, Peter; Palmer, Tim

2017-04-01

We present a new approach for improving the efficiency of data assimilation, by trading numerical precision for computational speed. Future supercomputers will allow a greater choice of precision, so that models can use a level of precision that is commensurate with the model uncertainty. Previous studies have already indicated that the quality of climate and weather forecasts is not significantly degraded when using a precision less than double precision [1,2], but so far these studies have not considered data assimilation. Data assimilation is inherently uncertain due to the use of relatively long assimilation windows, noisy observations and imperfect models. Thus, the larger rounding errors incurred from reducing precision may be within the tolerance of the system. Lower precision arithmetic is cheaper, and so by reducing precision in ensemble data assimilation, we can redistribute computational resources towards, for example, a larger ensemble size. Because larger ensembles provide a better estimate of the underlying distribution and are less reliant on covariance inflation and localisation, lowering precision could actually allow us to improve the accuracy of weather forecasts. We will present results on how lowering numerical precision affects the performance of an ensemble data assimilation system, consisting of the Lorenz '96 toy atmospheric model and the ensemble square root filter. We run the system at half precision (using an emulation tool), and compare the results with simulations at single and double precision. We estimate that half precision assimilation with a larger ensemble can reduce assimilation error by 30%, with respect to double precision assimilation with a smaller ensemble, for no extra computational cost. This results in around half a day extra of skillful weather forecasts, if the error-doubling characteristics of the Lorenz '96 model are mapped to those of the real atmosphere. Additionally, we investigate the sensitivity of these results to observational error and assimilation window length. Half precision hardware will become available very shortly, with the introduction of Nvidia's Pascal GPU architecture and the Intel Knights Mill coprocessor. We hope that the results presented here will encourage the uptake of this hardware. References [1] Peter D. Düben and T. N. Palmer, 2014: Benchmark Tests for Numerical Weather Forecasts on Inexact Hardware, Mon. Weather Rev., 142, 3809-3829 [2] Peter D. Düben, Hugh McNamara and T. N. Palmer, 2014: The use of imprecise processing to improve accuracy in weather & climate prediction, J. Comput. Phys., 271, 2-18

Turbulence intensity in a region of interest 2cm distal to the carotid bifurcation in a family of seven anthropomorphic flow phantoms

NASA Astrophysics Data System (ADS)

Powell, Janet L.; Poepping, Tamie L.

2011-03-01

An in vitro flow system has been used to assess the flow disturbances downstream of the stenosis in a family of seven carotid bifurcation phantoms modelling varying plaque build-up both axially symmetrically (concentrically) and asymmetrically (eccentrically). Radio frequency data were collected for 10 s at each of over 1000 sites within each model, and a sliding 1024-point FFT is applied to the data to extract the Doppler spectrum every 12 ms. From this, the ensemble average over 10 cardiac cycles of the spectral mean velocity, and the root mean square over these same 10 cardiac cycles - the turbulence intensity (TI), can be obtained as a function of an ensemble averaged cardiac cycle at each spatial point in all phantoms. TI was investigated by looking at the average over a 25 mm2 square region of interest in the ICA centered 2 cm distal to the apex of the bifurcation. TI in the region of interest increased with stenosis severity; at 23ms following peak systole, the time point when TI was maximal for the majority of models, this ranged from 2.4+/-0.1 cm/s in the non-diseased model to 6.6+/-0.3, 16.0+/-1.4 and 26.1+/-1.3 cm/s in the 30, 50 and 70% concentrically stenosed (by NASCET criteria) models, respectively. Similarly, TI was 8.3+/-0.7, 19.9+/-1.1, and 26.2+/-1.2 cm/s in the 30, 50 and 70% eccentrically stenosed models, respectively. Differences in TI between models, both in increasing stenosis severity and between eccentricities, were statistically different except between the 70% concentric and eccentric models.

Visualizing the Sample Standard Deviation

ERIC Educational Resources Information Center

Sarkar, Jyotirmoy; Rashid, Mamunur

2017-01-01

The standard deviation (SD) of a random sample is defined as the square-root of the sample variance, which is the "mean" squared deviation of the sample observations from the sample mean. Here, we interpret the sample SD as the square-root of twice the mean square of all pairwise half deviations between any two sample observations. This…

Molecular docking and molecular dynamics simulation analyses of urea with ammoniated and ammoxidized lignin.

PubMed

Li, Wenzhuo; Zhang, Song; Zhao, Yingying; Huang, Shuaiyu; Zhao, Jiangshan

2017-01-01

Ammoniated lignin, prepared through the Mannich reaction of lignin, has more advantages as a slow-release carrier of urea molecules than ammoxidized lignin and lignin. The advantages of the ammoniated lignin include its amine groups added and its high molecular mass kept as similar as that of lignin. Three organic molecules including guaiacyl, 2-hydroxybenzylamine and 5-carbamoylpentanoic acid are monomers respectively in lignin, ammoniated lignin and ammoxidized lignin. We studied the difference between the interactions of lignin, ammoniated lignin and ammoxidized lignin with respect to urea, based on radial distribution functions (RDFs) results from molecular dynamics (MD) simulations. Glass transition temperature (T g ) and solubility parameter (δ) of ammoniated and ammoxidized lignin have been calculated by MD simulations in the constant-temperature and constant-pressure ensemble (NPT). Molecular docking results showed the interaction sites of the urea onto the ammoniated and ammoxidized lignin and three different interaction modes were identified. Root mean square deviation (RMSD) values could indicate the mobilities of the urea molecule affected by the three different interaction modes. A series of MD simulations in the constant-temperature and constant-volume ensemble (NVT) helped us to calculate the diffusivity of urea which was affected by the content of urea in ammoniated and ammoxidized lignin. Copyright © 2016 Elsevier Inc. All rights reserved.

Improving particle filters in rainfall-runoff models: application of the resample-move step and development of the ensemble Gaussian particle filter

NASA Astrophysics Data System (ADS)

Plaza Guingla, D. A.; Pauwels, V. R.; De Lannoy, G. J.; Matgen, P.; Giustarini, L.; De Keyser, R.

2012-12-01

The objective of this work is to analyze the improvement in the performance of the particle filter by including a resample-move step or by using a modified Gaussian particle filter. Specifically, the standard particle filter structure is altered by the inclusion of the Markov chain Monte Carlo move step. The second choice adopted in this study uses the moments of an ensemble Kalman filter analysis to define the importance density function within the Gaussian particle filter structure. Both variants of the standard particle filter are used in the assimilation of densely sampled discharge records into a conceptual rainfall-runoff model. In order to quantify the obtained improvement, discharge root mean square errors are compared for different particle filters, as well as for the ensemble Kalman filter. First, a synthetic experiment is carried out. The results indicate that the performance of the standard particle filter can be improved by the inclusion of the resample-move step, but its effectiveness is limited to situations with limited particle impoverishment. The results also show that the modified Gaussian particle filter outperforms the rest of the filters. Second, a real experiment is carried out in order to validate the findings from the synthetic experiment. The addition of the resample-move step does not show a considerable improvement due to performance limitations in the standard particle filter with real data. On the other hand, when an optimal importance density function is used in the Gaussian particle filter, the results show a considerably improved performance of the particle filter.

Exploring the future change space for fire weather in southeast Australia

NASA Astrophysics Data System (ADS)

Clarke, Hamish; Evans, Jason P.

2018-05-01

High-resolution projections of climate change impacts on fire weather conditions in southeast Australia out to 2080 are presented. Fire weather is represented by the McArthur Forest Fire Danger Index (FFDI), calculated from an objectively designed regional climate model ensemble. Changes in annual cumulative FFDI vary widely, from - 337 (- 21%) to + 657 (+ 24%) in coastal areas and - 237 (- 12%) to + 1143 (+ 26%) in inland areas. A similar spread is projected in extreme FFDI values. In coastal regions, the number of prescribed burning days is projected to change from - 11 to + 10 in autumn and - 10 to + 3 in spring. Across the ensemble, the most significant increases in fire weather and decreases in prescribed burn windows are projected to take place in spring. Partial bias correction of FFDI leads to similar projections but with a greater spread, particularly in extreme values. The partially bias-corrected FFDI performs similarly to uncorrected FFDI compared to the observed annual cumulative FFDI (ensemble root mean square error spans 540 to 1583 for uncorrected output and 695 to 1398 for corrected) but is generally worse for FFDI values above 50. This emphasizes the need to consider inter-variable relationships when bias-correcting for complex phenomena such as fire weather. There is considerable uncertainty in the future trajectory of fire weather in southeast Australia, including the potential for less prescribed burning days and substantially greater fire danger in spring. Selecting climate models on the basis of multiple criteria can lead to more informative projections and allow an explicit exploration of uncertainty.

Probabilistic regional climate projection in Japan using a regression model with CMIP5 multi-model ensemble experiments

NASA Astrophysics Data System (ADS)

Ishizaki, N. N.; Dairaku, K.; Ueno, G.

2016-12-01

We have developed a statistical downscaling method for estimating probabilistic climate projection using CMIP5 multi general circulation models (GCMs). A regression model was established so that the combination of weights of GCMs reflects the characteristics of the variation of observations at each grid point. Cross validations were conducted to select GCMs and to evaluate the regression model to avoid multicollinearity. By using spatially high resolution observation system, we conducted statistically downscaled probabilistic climate projections with 20-km horizontal grid spacing. Root mean squared errors for monthly mean air surface temperature and precipitation estimated by the regression method were the smallest compared with the results derived from a simple ensemble mean of GCMs and a cumulative distribution function based bias correction method. Projected changes in the mean temperature and precipitation were basically similar to those of the simple ensemble mean of GCMs. Mean precipitation was generally projected to increase associated with increased temperature and consequent increased moisture content in the air. Weakening of the winter monsoon may affect precipitation decrease in some areas. Temperature increase in excess of 4 K was expected in most areas of Japan in the end of 21st century under RCP8.5 scenario. The estimated probability of monthly precipitation exceeding 300 mm would increase around the Pacific side during the summer and the Japan Sea side during the winter season. This probabilistic climate projection based on the statistical method can be expected to bring useful information to the impact studies and risk assessments.

Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Tao, Wei-Kuo; Wu, Di; Peters-Lidard, Christa; Santanello, Joseph A.; Kemp, Eric; Tian, Yudong; Case, Jonathan; Wang, Weile; Ferraro, Robert;

The construction of general basis functions in reweighting ensemble dynamics simulations: Reproduce equilibrium distribution in complex systems from multiple short simulation trajectories

NASA Astrophysics Data System (ADS)

Zhang, Chuan-Biao; Ming, Li; Xin, Zhou

2015-12-01

Ensemble simulations, which use multiple short independent trajectories from dispersive initial conformations, rather than a single long trajectory as used in traditional simulations, are expected to sample complex systems such as biomolecules much more efficiently. The re-weighted ensemble dynamics (RED) is designed to combine these short trajectories to reconstruct the global equilibrium distribution. In the RED, a number of conformational functions, named as basis functions, are applied to relate these trajectories to each other, then a detailed-balance-based linear equation is built, whose solution provides the weights of these trajectories in equilibrium distribution. Thus, the sufficient and efficient selection of basis functions is critical to the practical application of RED. Here, we review and present a few possible ways to generally construct basis functions for applying the RED in complex molecular systems. Especially, for systems with less priori knowledge, we could generally use the root mean squared deviation (RMSD) among conformations to split the whole conformational space into a set of cells, then use the RMSD-based-cell functions as basis functions. We demonstrate the application of the RED in typical systems, including a two-dimensional toy model, the lattice Potts model, and a short peptide system. The results indicate that the RED with the constructions of basis functions not only more efficiently sample the complex systems, but also provide a general way to understand the metastable structure of conformational space. Project supported by the National Natural Science Foundation of China (Grant No. 11175250).

Bayesian Hierarchical Model Characterization of Model Error in Ocean Data Assimilation and Forecasts

DTIC Science & Technology

2013-09-30

proof-of-concept results comparing a BHM surface wind ensemble with the increments in the surface momentum flux control vector in a four-dimensional...Surface   Momentum  Flux  Ensembles  from  Summaries  of  BHM  Winds  (Mediterranean)   include  ocean  current  effect   Td...Bayesian Hierarchical Model to provide surface momentum flux ensembles. 3 Figure 2: Domain of interest : squares indicate spatial locations where

A Model Comparison for Characterizing Protein Motions from Structure

NASA Astrophysics Data System (ADS)

David, Charles; Jacobs, Donald

2011-10-01

A comparative study is made using three computational models that characterize native state dynamics starting from known protein structures taken from four distinct SCOP classifications. A geometrical simulation is performed, and the results are compared to the elastic network model and molecular dynamics. The essential dynamics is quantified by a direct analysis of a mode subspace constructed from ANM and a principal component analysis on both the FRODA and MD trajectories using root mean square inner product and principal angles. Relative subspace sizes and overlaps are visualized using the projection of displacement vectors on the model modes. Additionally, a mode subspace is constructed from PCA on an exemplar set of X-ray crystal structures in order to determine similarly with respect to the generated ensembles. Quantitative analysis reveals there is significant overlap across the three model subspaces and the model independent subspace. These results indicate that structure is the key determinant for native state dynamics.

Tourism forecasting using modified empirical mode decomposition and group method of data handling

NASA Astrophysics Data System (ADS)

Yahya, N. A.; Samsudin, R.; Shabri, A.

2017-09-01

In this study, a hybrid model using modified Empirical Mode Decomposition (EMD) and Group Method of Data Handling (GMDH) model is proposed for tourism forecasting. This approach reconstructs intrinsic mode functions (IMFs) produced by EMD using trial and error method. The new component and the remaining IMFs is then predicted respectively using GMDH model. Finally, the forecasted results for each component are aggregated to construct an ensemble forecast. The data used in this experiment are monthly time series data of tourist arrivals from China, Thailand and India to Malaysia from year 2000 to 2016. The performance of the model is evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) where conventional GMDH model and EMD-GMDH model are used as benchmark models. Empirical results proved that the proposed model performed better forecasts than the benchmarked models.

Fluctuation Pressure Assisted Ejection of DNA From Bacteriophage

NASA Astrophysics Data System (ADS)

Harrison, Michael J.

2011-03-01

The role of thermal pressure fluctuations excited within tightly packaged DNA while it is ejected from protein capsid shells is discussed in a model calculation. At equilibrium before ejection we assume the DNA is folded many times into a bundle of parallel segments that forms an equilibrium conformation at minimum free energy, which presses tightly against capsid walls. Using a canonical ensemble at temperature T we calculate internal pressure fluctuations against a slowly moving or static capsid mantle for an elastic continuum model of the folded DNA bundle. It is found that fluctuating pressures on the capsid from thermal excitation of longitudinal acoustic vibrations in the bundle whose wavelengths are exceeded by the bend persistence length may have root-mean-square values that are several tens of atmospheres for typically small phage dimensions. Comparisons are given with measured data on three mutants of lambda phage with different base pair lengths and total genome ejection pressures.

Unusual square roots in the ghost-free theory of massive gravity

NASA Astrophysics Data System (ADS)

Golovnev, Alexey; Smirnov, Fedor

2017-06-01

A crucial building block of the ghost free massive gravity is the square root function of a matrix. This is a problematic entity from the viewpoint of existence and uniqueness properties. We accurately describe the freedom of choosing a square root of a (non-degenerate) matrix. It has discrete and (in special cases) continuous parts. When continuous freedom is present, the usual perturbation theory in terms of matrices can be critically ill defined for some choices of the square root. We consider the new formulation of massive and bimetric gravity which deals directly with eigenvalues (in disguise of elementary symmetric polynomials) instead of matrices. It allows for a meaningful discussion of perturbation theory in such cases, even though certain non-analytic features arise.

Monthly ENSO Forecast Skill and Lagged Ensemble Size

PubMed Central

DelSole, T.; Tippett, M.K.; Pegion, K.

2018-01-01

Abstract The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real‐time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real‐time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8–10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities. PMID:29937973

Monthly ENSO Forecast Skill and Lagged Ensemble Size

NASA Astrophysics Data System (ADS)

Trenary, L.; DelSole, T.; Tippett, M. K.; Pegion, K.

2018-04-01

The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real-time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real-time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8-10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities.

Classifying Physical Morphology of Cocoa Beans Digital Images using Multiclass Ensemble Least-Squares Support Vector Machine

NASA Astrophysics Data System (ADS)

Lawi, Armin; Adhitya, Yudhi

2018-03-01

The objective of this research is to determine the quality of cocoa beans through morphology of their digital images. Samples of cocoa beans were scattered on a bright white paper under a controlled lighting condition. A compact digital camera was used to capture the images. The images were then processed to extract their morphological parameters. Classification process begins with an analysis of cocoa beans image based on morphological feature extraction. Parameters for extraction of morphological or physical feature parameters, i.e., Area, Perimeter, Major Axis Length, Minor Axis Length, Aspect Ratio, Circularity, Roundness, Ferret Diameter. The cocoa beans are classified into 4 groups, i.e.: Normal Beans, Broken Beans, Fractured Beans, and Skin Damaged Beans. The model of classification used in this paper is the Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM), a proposed improvement model of SVM using ensemble method in which the separate hyperplanes are obtained by least square approach and the multiclass procedure uses One-Against- All method. The result of our proposed model showed that the classification with morphological feature input parameters were accurately as 99.705% for the four classes, respectively.

Bringing the Outside In: Blending Formal and Informal through Acts Hospitality

ERIC Educational Resources Information Center

West, Chad; Cremata, Radio

2016-01-01

Through the lens of hospitality, we explored the meanings that members constructed about their experiences within a blended formal/informal college music ensemble. The focus in this ensemble was not on competition and musical excellence but on independent musicianship and praxis. The bandleader had his roots in tradition but his heart in socially…

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

PubMed

Zhai, Binxu; Chen, Jianguo

2018-04-18

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

Initial conditions and ENSO prediction using a coupled ocean-atmosphere model

NASA Astrophysics Data System (ADS)

Larow, T. E.; Krishnamurti, T. N.

1998-01-01

A coupled ocean-atmosphere initialization scheme using Newtonian relaxation has been developed for the Florida State University coupled ocean-atmosphere global general circulation model. The initialization scheme is used to initialize the coupled model for seasonal forecasting the boreal summers of 1987 and 1988. The atmosphere model is a modified version of the Florida State University global spectral model, resolution T-42. The ocean general circulation model consists of a slightly modified version of the Hamburg's climate group model described in Latif (1987) and Latif et al. (1993). The coupling is synchronous with information exchanged every two model hours. Using ECMWF atmospheric daily analysis and observed monthly mean SSTs, two, 1-year, time-dependent, Newtonian relaxation were performed using the coupled model prior to conducting the seasonal forecasts. The coupled initializations were conducted from 1 June 1986 to 1 June 1987 and from 1 June 1987 to 1 June 1988. Newtonian relaxation was applied to the prognostic atmospheric vorticity, divergence, temperature and dew point depression equations. In the ocean model the relaxation was applied to the surface temperature. Two, 10-member ensemble integrations were conducted to examine the impact of the coupled initialization on the seasonal forecasts. The initial conditions used for the ensembles are the ocean's final state after the initialization and the atmospheric initial conditions are ECMWF analysis. Examination of the SST root mean square error and anomaly correlations between observed and forecasted SSTs in the Niño-3 and Niño-4 regions for the 2 seasonal forecasts, show closer agreement between the initialized forecast than two, 10-member non-initialized ensemble forecasts. The main conclusion here is that a single forecast with the coupled initialization outperforms, in SST anomaly prediction, against each of the control forecasts (members of the ensemble) which do not include such an initialization, indicating possible importance for the inclusion of the atmosphere during the coupled initialization.

Equilibrium Ensembles for Insulin Folding from Bias-Exchange Metadynamics.

PubMed

Singh, Richa; Bansal, Rohit; Rathore, Anurag Singh; Goel, Gaurav

2017-04-25

Earliest events in the aggregation process, such as single molecule reconfiguration, are extremely important and the most difficult to characterize in experiments. To this end, we have used well-tempered bias exchange metadynamics simulations to determine the equilibrium ensembles of an insulin molecule under amyloidogenic conditions of low pH and high temperature. A bin-based clustering method that uses statistics accumulated in bias exchange metadynamics trajectories was employed to construct a detailed thermodynamic and kinetic model of insulin folding. The highest lifetime, lowest free-energy ensemble identified consisted of native conformations adopted by a folded insulin monomer in solution, namely, the R-, the R f -, and the T-states of insulin. The lowest free-energy structure had a root mean square deviation of only 0.15 nm from native x-ray structure. The second longest-lived metastable state was an unfolded, compact monomer with little similarity to the native structure. We have identified three additional long-lived, metastable states from the bin-based model. We then carried out an exhaustive structural characterization of metastable states on the basis of tertiary contact maps and per-residue accessible surface areas. We have also determined the lowest free-energy path between two longest-lived metastable states and confirm earlier findings of non-two-state folding for insulin through a folding intermediate. The ensemble containing the monomeric intermediate retained 58% of native hydrophobic contacts, however, accompanied by a complete loss of native secondary structure. We have discussed the relative importance of nativelike versus nonnative tertiary contacts for the folding transition. We also provide a simple measure to determine the importance of an individual residue for folding transition. Finally, we have compared and contrasted this intermediate with experimental data obtained in spectroscopic, crystallographic, and calorimetric measurements during early stages of insulin aggregation. We have also determined stability of monomeric insulin by incubation at a very low concentration to isolate protein-protein interaction effects. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Dynamic clustering threshold reduces conformer ensemble size while maintaining a biologically relevant ensemble

NASA Astrophysics Data System (ADS)

Yongye, Austin B.; Bender, Andreas; Martínez-Mayorga, Karina

2010-08-01

Representing the 3D structures of ligands in virtual screenings via multi-conformer ensembles can be computationally intensive, especially for compounds with a large number of rotatable bonds. Thus, reducing the size of multi-conformer databases and the number of query conformers, while simultaneously reproducing the bioactive conformer with good accuracy, is of crucial interest. While clustering and RMSD filtering methods are employed in existing conformer generators, the novelty of this work is the inclusion of a clustering scheme (NMRCLUST) that does not require a user-defined cut-off value. This algorithm simultaneously optimizes the number and the average spread of the clusters. Here we describe and test four inter-dependent approaches for selecting computer-generated conformers, namely: OMEGA, NMRCLUST, RMS filtering and averaged- RMS filtering. The bioactive conformations of 65 selected ligands were extracted from the corresponding protein:ligand complexes from the Protein Data Bank, including eight ligands that adopted dissimilar bound conformations within different receptors. We show that NMRCLUST can be employed to further filter OMEGA-generated conformers while maintaining biological relevance of the ensemble. It was observed that NMRCLUST (containing on average 10 times fewer conformers per compound) performed nearly as well as OMEGA, and both outperformed RMS filtering and averaged- RMS filtering in terms of identifying the bioactive conformations with excellent and good matches (0.5 < RMSD < 1.0 Å). Furthermore, we propose thresholds for OMEGA root-mean square filtering depending on the number of rotors in a compound: 0.8, 1.0 and 1.4 for structures with low (1-4), medium (5-9) and high (10-15) numbers of rotatable bonds, respectively. The protocol employed is general and can be applied to reduce the number of conformers in multi-conformer compound collections and alleviate the complexity of downstream data processing in virtual screening experiments.

An Effective Approach for Clustering InhA Molecular Dynamics Trajectory Using Substrate-Binding Cavity Features

PubMed Central

Ruiz, Duncan D. A.; Norberto de Souza, Osmar

2015-01-01

Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward’s, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes. PMID:26218832

An Effective Approach for Clustering InhA Molecular Dynamics Trajectory Using Substrate-Binding Cavity Features.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D A; Norberto de Souza, Osmar

2015-01-01

Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward's, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes.

A Collection of Numbers Whose Proof of Irrationality Is Like that of the Number "e"

ERIC Educational Resources Information Center

Osler, Thomas J.; Stugard, Nicholas

2006-01-01

In some elementary courses, it is shown that square root of 2 is irrational. It is also shown that the roots like square root of 3, cube root of 2, etc., are irrational. Much less often, it is shown that the number "e," the base of the natural logarithm, is irrational, even though a proof is available that uses only elementary calculus. In this…

An Assessment of Multimodel Simulations for the Variability of Western North Pacific Tropical Cyclones and Its Association with ENSO

NASA Technical Reports Server (NTRS)

Han, Rongqing; Wang, Hui; Hu, Zeng-Zhen; Kumar, Arun; Li, Weijing; Long, Lindsey N.; Schemm, Jae-Kyung E.; Peng, Peitao; Wang, Wanqiu; Si, Dong;

Modeling causes of death: an integrated approach using CODEm

PubMed Central

2012-01-01

Background Data on causes of death by age and sex are a critical input into health decision-making. Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them. However, cause of death data are often not available or are subject to substantial problems of comparability. We propose five general principles for cause of death model development, validation, and reporting. Methods We detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death. Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes. The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates. All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance. Results Ensemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval. We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers. Conclusions CODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification. We demonstrate the utility of CODEm for the estimation of several major causes of death. PMID:22226226

Non-stationary Bias Correction of Monthly CMIP5 Temperature Projections over China using a Residual-based Bagging Tree Model

NASA Astrophysics Data System (ADS)

Yang, T.; Lee, C.

2017-12-01

The biases in the Global Circulation Models (GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias correction model, termed Residual-based Bagging Tree (RBT) model, to reduce simulation biases and to quantify the contributions of single models. Specifically, the proposed model estimates the residuals between individual models and observations, and takes the differences between observations and the ensemble mean into consideration during the model training process. A case study is conducted for 10 major river basins in Mainland China during different seasons. Results show that the proposed model is capable of providing accurate and stable predictions while including the non-stationarities into the modeling framework. Significant reductions in both bias and root mean squared error are achieved with the proposed RBT model, especially for the central and western parts of China. The proposed RBT model has consistently better performance in reducing biases when compared to the raw ensemble mean, the ensemble mean with simple additive bias correction, and the single best model for different seasons. Furthermore, the contribution of each single GCM in reducing the overall bias is quantified. The single model importance varies between 3.1% and 7.2%. For different future scenarios (RCP 2.6, RCP 4.5, and RCP 8.5), the results from RBT model suggest temperature increases of 1.44 ºC, 2.59 ºC, and 4.71 ºC by the end of the century, respectively, when compared to the average temperature during 1970 - 1999.

Ensemble-based characterization of unbound and bound states on protein energy landscape

PubMed Central

Ruvinsky, Anatoly M; Kirys, Tatsiana; Tuzikov, Alexander V; Vakser, Ilya A

2013-01-01

Physicochemical description of numerous cell processes is fundamentally based on the energy landscapes of protein molecules involved. Although the whole energy landscape is difficult to reconstruct, increased attention to particular targets has provided enough structures for mapping functionally important subspaces associated with the unbound and bound protein structures. The subspace mapping produces a discrete representation of the landscape, further called energy spectrum. We compiled and characterized ensembles of bound and unbound conformations of six small proteins and explored their spectra in implicit solvent. First, the analysis of the unbound-to-bound changes points to conformational selection as the binding mechanism for four proteins. Second, results show that bound and unbound spectra often significantly overlap. Moreover, the larger the overlap the smaller the root mean square deviation (RMSD) between the bound and unbound conformational ensembles. Third, the center of the unbound spectrum has a higher energy than the center of the corresponding bound spectrum of the dimeric and multimeric states for most of the proteins. This suggests that the unbound states often have larger entropy than the bound states. Fourth, the exhaustively long minimization, making small intrarotamer adjustments (all-atom RMSD ≤ 0.7 Å), dramatically reduces the distance between the centers of the bound and unbound spectra as well as the spectra extent. It condenses unbound and bound energy levels into a thin layer at the bottom of the energy landscape with the energy spacing that varies between 0.8–4.6 and 3.5–10.5 kcal/mol for the unbound and bound states correspondingly. Finally, the analysis of protein energy fluctuations showed that protein vibrations itself can excite the interstate transitions, including the unbound-to-bound ones. PMID:23526684

Sequential data assimilation for a distributed hydrologic model considering different time scale of internal processes

NASA Astrophysics Data System (ADS)

Noh, S.; Tachikawa, Y.; Shiiba, M.; Kim, S.

2011-12-01

Applications of the sequential data assimilation methods have been increasing in hydrology to reduce uncertainty in the model prediction. In a distributed hydrologic model, there are many types of state variables and each variable interacts with each other based on different time scales. However, the framework to deal with the delayed response, which originates from different time scale of hydrologic processes, has not been thoroughly addressed in the hydrologic data assimilation. In this study, we propose the lagged filtering scheme to consider the lagged response of internal states in a distributed hydrologic model using two filtering schemes; particle filtering (PF) and ensemble Kalman filtering (EnKF). The EnKF is one of the widely used sub-optimal filters implementing an efficient computation with limited number of ensemble members, however, still based on Gaussian approximation. PF can be an alternative in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions involved. In case of PF, advanced particle regularization scheme is implemented together to preserve the diversity of the particle system. In case of EnKF, the ensemble square root filter (EnSRF) are implemented. Each filtering method is parallelized and implemented in the high performance computing system. A distributed hydrologic model, the water and energy transfer processes (WEP) model, is applied for the Katsura River catchment, Japan to demonstrate the applicability of proposed approaches. Forecasted results via PF and EnKF are compared and analyzed in terms of the prediction accuracy and the probabilistic adequacy. Discussions are focused on the prospects and limitations of each data assimilation method.

Using an ensemble smoother to evaluate parameter uncertainty of an integrated hydrological model of Yanqi basin

NASA Astrophysics Data System (ADS)

Li, Ning; McLaughlin, Dennis; Kinzelbach, Wolfgang; Li, WenPeng; Dong, XinGuang

2015-10-01

Model uncertainty needs to be quantified to provide objective assessments of the reliability of model predictions and of the risk associated with management decisions that rely on these predictions. This is particularly true in water resource studies that depend on model-based assessments of alternative management strategies. In recent decades, Bayesian data assimilation methods have been widely used in hydrology to assess uncertain model parameters and predictions. In this case study, a particular data assimilation algorithm, the Ensemble Smoother with Multiple Data Assimilation (ESMDA) (Emerick and Reynolds, 2012), is used to derive posterior samples of uncertain model parameters and forecasts for a distributed hydrological model of Yanqi basin, China. This model is constructed using MIKESHE/MIKE11software, which provides for coupling between surface and subsurface processes (DHI, 2011a-d). The random samples in the posterior parameter ensemble are obtained by using measurements to update 50 prior parameter samples generated with a Latin Hypercube Sampling (LHS) procedure. The posterior forecast samples are obtained from model runs that use the corresponding posterior parameter samples. Two iterative sample update methods are considered: one based on an a perturbed observation Kalman filter update and one based on a square root Kalman filter update. These alternatives give nearly the same results and converge in only two iterations. The uncertain parameters considered include hydraulic conductivities, drainage and river leakage factors, van Genuchten soil property parameters, and dispersion coefficients. The results show that the uncertainty in many of the parameters is reduced during the smoother updating process, reflecting information obtained from the observations. Some of the parameters are insensitive and do not benefit from measurement information. The correlation coefficients among certain parameters increase in each iteration, although they generally stay below 0.50.

Determination of a transient heat transfer property of acrylic using thermochromic liquid crystals

NASA Technical Reports Server (NTRS)

Heidmann, James D.

1994-01-01

An experiment was performed to determine a transient heat transfer property of acrylic. The experiment took advantage of the known analytical solution for heat conduction in a homogeneous semi-infinite solid with a constant surface heat flux. Thermochromic liquid crystals were used to measure the temperature nonintrusively. The relevant property in this experiment was the transient thermal conduction coefficient h(sub t), which is the square root of the product of density p, specific heat c(sub p), and thermal conductivity k (i.e., square root of pc(sub p)k). A value of 595.6 W square root of s/sq m K was obtained for h(sub t), with a standard deviation of 5.1 W square root of s/sq m K. Although there is no generally accepted value for h(sub t), a commonly used one is 580 W square root of s/sq m K, which is almost 3 percent less than the h(sub t) value obtained in this experiment. Since these results were highly repeatable and since there is no definitive value for h(sub t), the new value is recommended for future use.

On Roots and Squares--Estimation, Intuition and Creativity

ERIC Educational Resources Information Center

Patkin, Dorit; Gazit, Avikam

2013-01-01

The paper presents findings of a small scale study of a few items related to problem solving with squares and roots, for different teacher groups (pre-service and in-service mathematics teachers: elementary and junior high school). The research participants were asked to explain what would be the units digit of a natural number to be squared in…

Remote sensing of key grassland nutrients using hyperspectral techniques in KwaZulu-Natal, South Africa

NASA Astrophysics Data System (ADS)

Singh, Leeth; Mutanga, Onisimo; Mafongoya, Paramu; Peerbhay, Kabir

2017-07-01

The concentration of forage fiber content is critical in explaining the palatability of forage quality for livestock grazers in tropical grasslands. Traditional methods of determining forage fiber content are usually time consuming, costly, and require specialized laboratory analysis. With the potential of remote sensing technologies, determination of key fiber attributes can be made more accurately. This study aims to determine the effectiveness of known absorption wavelengths for detecting forage fiber biochemicals, neutral detergent fiber, acid detergent fiber, and lignin using hyperspectral data. Hyperspectral reflectance spectral measurements (350 to 2500 nm) of grass were collected and implemented within the random forest (RF) ensemble. Results show successful correlations between the known absorption features and the biochemicals with coefficients of determination (R2) ranging from 0.57 to 0.81 and root mean square errors ranging from 6.97 to 3.03 g/kg. In comparison, using the entire dataset, the study identified additional wavelengths for detecting fiber biochemicals, which contributes to the accurate determination of forage quality in a grassland environment. Overall, the results showed that hyperspectral remote sensing in conjunction with the competent RF ensemble could discriminate each key biochemical evaluated. This study shows the potential to upscale the methodology to a space-borne multispectral platform with similar spectral configurations for an accurate and cost effective mapping analysis of forage quality.

Fitting a function to time-dependent ensemble averaged data.

PubMed

Fogelmark, Karl; Lomholt, Michael A; Irbäck, Anders; Ambjörnsson, Tobias

2018-05-03

Time-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these averages (for instance, squared displacements) with a function and extract parameters (such as diffusion constants). A commonly overlooked challenge in such function fitting procedures is that fluctuations around mean values, by construction, exhibit temporal correlations. We show that the only available general purpose function fitting methods, correlated chi-square method and the weighted least squares method (which neglects correlation), fail at either robust parameter estimation or accurate error estimation. We remedy this by deriving a new closed-form error estimation formula for weighted least square fitting. The new formula uses the full covariance matrix, i.e., rigorously includes temporal correlations, but is free of the robustness issues, inherent to the correlated chi-square method. We demonstrate its accuracy in four examples of importance in many fields: Brownian motion, damped harmonic oscillation, fractional Brownian motion and continuous time random walks. We also successfully apply our method, weighted least squares including correlation in error estimation (WLS-ICE), to particle tracking data. The WLS-ICE method is applicable to arbitrary fit functions, and we provide a publically available WLS-ICE software.

Explicit Formulae for the Continued Fraction Convergents of "Square Root of D"

ERIC Educational Resources Information Center

Braza, Peter A.

2010-01-01

The formulae for the convergents of continued fractions are always given recursively rather than in explicit form. This article derives explicit formulae for the convergents of the continued fraction expansions for square roots.

Liquid fuel spray processes in high-pressure gas flow

NASA Technical Reports Server (NTRS)

Ingebo, R. D.

1985-01-01

Atomization of single liquid jets injected downstream in high pressure and high velocity airflow was investigated to determine the effect of airstream pressure on mean drop size as measured with a scanning radiometer. For aerodynamic - wave breakup of liquid jets, the ratio of orifice diameter D sub o to measured mean drop diameter D sub m which is assumed equal to D sub 32 or Sauter mean diameter, was correlated with the product of the Weber and Reynolds numbers WeRe and the dimensionless group G1/square root of c, where G is the gravitational acceleration, 1 the mean free molecular path, and square root of C the root mean square velocity, as follows; D sub o/D sub 32 = 1.2 (WeRe) to the 0.4 (G1/square root of c) to the 0.15 for values of WeRe 1 million and an airstream pressure range of 0.10 to 2.10 MPa.

Liquid fuel spray processes in high-pressure gas flow

NASA Technical Reports Server (NTRS)

Ingebo, R. D.

1986-01-01

Atomization of single liquid jets injected downstream in high pressure and high velocity airflow was investigated to determine the effect of airstream pressure on mean drop size as measured with a scanning radiometer. For aerodynamic - wave breakup of liquid jets, the ratio of orifice diameter D sub o to measured mean drop diameter D sub m which is assumed equal to D sub 32 or Sauter mean diameter, was correlated with the product of the Weber and Reynolds numbers WeRe and the dimensionless group G1/square root of c, where G is the gravitational acceleration, 1 the mean free molecular path, and square root of C the root mean square velocity, as follows; D sub o/D sub 32 = 1.2 (WeRe) to the 0.4 (G1/square root of c) to the 0.15 for values of WeRe 1 million and an airstream pressure range of 0.10 to 2.10 MPa.

Performance of statistical models to predict mental health and substance abuse cost.

PubMed

Montez-Rath, Maria; Christiansen, Cindy L; Ettner, Susan L; Loveland, Susan; Rosen, Amy K

2006-10-26

Providers use risk-adjustment systems to help manage healthcare costs. Typically, ordinary least squares (OLS) models on either untransformed or log-transformed cost are used. We examine the predictive ability of several statistical models, demonstrate how model choice depends on the goal for the predictive model, and examine whether building models on samples of the data affects model choice. Our sample consisted of 525,620 Veterans Health Administration patients with mental health (MH) or substance abuse (SA) diagnoses who incurred costs during fiscal year 1999. We tested two models on a transformation of cost: a Log Normal model and a Square-root Normal model, and three generalized linear models on untransformed cost, defined by distributional assumption and link function: Normal with identity link (OLS); Gamma with log link; and Gamma with square-root link. Risk-adjusters included age, sex, and 12 MH/SA categories. To determine the best model among the entire dataset, predictive ability was evaluated using root mean square error (RMSE), mean absolute prediction error (MAPE), and predictive ratios of predicted to observed cost (PR) among deciles of predicted cost, by comparing point estimates and 95% bias-corrected bootstrap confidence intervals. To study the effect of analyzing a random sample of the population on model choice, we re-computed these statistics using random samples beginning with 5,000 patients and ending with the entire sample. The Square-root Normal model had the lowest estimates of the RMSE and MAPE, with bootstrap confidence intervals that were always lower than those for the other models. The Gamma with square-root link was best as measured by the PRs. The choice of best model could vary if smaller samples were used and the Gamma with square-root link model had convergence problems with small samples. Models with square-root transformation or link fit the data best. This function (whether used as transformation or as a link) seems to help deal with the high comorbidity of this population by introducing a form of interaction. The Gamma distribution helps with the long tail of the distribution. However, the Normal distribution is suitable if the correct transformation of the outcome is used.

Fracture behavior of thick, laminated graphite/epoxy composites

NASA Technical Reports Server (NTRS)

Harris, C. E.; Morris, D. H.

1984-01-01

The effect of laminate thickness on the fracture behavior of laminated graphite epoxy (T300/5208) composites was studied. The predominantly experimental research program included the study of the 0/+ or - 45/90 sub ns and 0/90 sub ns laminates with thickness of 8, 32, 64, 96 and 120 plies and the 0/+ or - 45 sub ns laminate with thickness of 6, 30, 60, 90 and 120 plies. The research concentrated on the measurement of fracture toughness utilizing the center-cracked tension, compact tension and three point bend specimen configurations. The development of subcritical damage at the crack tip was studied nondestructively using enhanced X-ray radiography and destructively using the laminate deply technique. The test results showed fracture toughness to be a function of laminate thickness. The fracture toughness of the 0 + or - 45/90 sub ns and 0/90 sub ns laminates decreased with increasing thickness and asymptotically approached lower bound values of 30 ksi square root of in. (1043 MPa square root of mm and 25 ksi square root of in (869 MPa square root of mm respectively. In contrast to the other two laminates, the fracture toughness of the 0/+ or - 45 sub ns laminate increased sharply with increasing thickness but reached an upper plateau value of 40 ksi square root of in (1390 MPa square root of mm) at 30 plies. Fracture toughness was independent of crack size for both thin and thick laminates for all three laminate types except for the 0/90 sub 2s laminate which spilt extensively. The center cracked tension, three point bend and compact tension specimens gave comparable results.

Probabilistic precipitation nowcasting based on an extrapolation of radar reflectivity and an ensemble approach

NASA Astrophysics Data System (ADS)

Sokol, Zbyněk; Mejsnar, Jan; Pop, Lukáš; Bližňák, Vojtěch

2017-09-01

A new method for the probabilistic nowcasting of instantaneous rain rates (ENS) based on the ensemble technique and extrapolation along Lagrangian trajectories of current radar reflectivity is presented. Assuming inaccurate forecasts of the trajectories, an ensemble of precipitation forecasts is calculated and used to estimate the probability that rain rates will exceed a given threshold in a given grid point. Although the extrapolation neglects the growth and decay of precipitation, their impact on the probability forecast is taken into account by the calibration of forecasts using the reliability component of the Brier score (BS). ENS forecasts the probability that the rain rates will exceed thresholds of 0.1, 1.0 and 3.0 mm/h in squares of 3 km by 3 km. The lead times were up to 60 min, and the forecast accuracy was measured by the BS. The ENS forecasts were compared with two other methods: combined method (COM) and neighbourhood method (NEI). NEI considered the extrapolated values in the square neighbourhood of 5 by 5 grid points of the point of interest as ensemble members, and the COM ensemble was comprised of united ensemble members of ENS and NEI. The results showed that the calibration technique significantly improves bias of the probability forecasts by including additional uncertainties that correspond to neglected processes during the extrapolation. In addition, the calibration can also be used for finding the limits of maximum lead times for which the forecasting method is useful. We found that ENS is useful for lead times up to 60 min for thresholds of 0.1 and 1 mm/h and approximately 30 to 40 min for a threshold of 3 mm/h. We also found that a reasonable size of the ensemble is 100 members, which provided better scores than ensembles with 10, 25 and 50 members. In terms of the BS, the best results were obtained by ENS and COM, which are comparable. However, ENS is better calibrated and thus preferable.

Comparison of initial perturbation methods for the mesoscale ensemble prediction system of the Meteorological Research Institute for the WWRP Beijing 2008 Olympics Research and Development Project (B08RDP)

NASA Astrophysics Data System (ADS)

Saito, Kazuo; Hara, Masahiro; Kunii, Masaru; Seko, Hiromu; Yamaguchi, Munehiko

2011-05-01

Different initial perturbation methods for the mesoscale ensemble prediction were compared by the Meteorological Research Institute (MRI) as a part of the intercomparison of mesoscale ensemble prediction systems (EPSs) of the World Weather Research Programme (WWRP) Beijing 2008 Olympics Research and Development Project (B08RDP). Five initial perturbation methods for mesoscale ensemble prediction were developed for B08RDP and compared at MRI: (1) a downscaling method of the Japan Meteorological Agency (JMA)'s operational one-week EPS (WEP), (2) a targeted global model singular vector (GSV) method, (3) a mesoscale model singular vector (MSV) method based on the adjoint model of the JMA non-hydrostatic model (NHM), (4) a mesoscale breeding growing mode (MBD) method based on the NHM forecast and (5) a local ensemble transform (LET) method based on the local ensemble transform Kalman filter (LETKF) using NHM. These perturbation methods were applied to the preliminary experiments of the B08RDP Tier-1 mesoscale ensemble prediction with a horizontal resolution of 15 km. To make the comparison easier, the same horizontal resolution (40 km) was employed for the three mesoscale model-based initial perturbation methods (MSV, MBD and LET). The GSV method completely outperformed the WEP method, confirming the advantage of targeting in mesoscale EPS. The GSV method generally performed well with regard to root mean square errors of the ensemble mean, large growth rates of ensemble spreads throughout the 36-h forecast period, and high detection rates and high Brier skill scores (BSSs) for weak rains. On the other hand, the mesoscale model-based initial perturbation methods showed good detection rates and BSSs for intense rains. The MSV method showed a rapid growth in the ensemble spread of precipitation up to a forecast time of 6 h, which suggests suitability of the mesoscale SV for short-range EPSs, but the initial large growth of the perturbation did not last long. The performance of the MBD method was good for ensemble prediction of intense rain with a relatively small computing cost. The LET method showed similar characteristics to the MBD method, but the spread and growth rate were slightly smaller and the relative operating characteristic area skill score and BSS did not surpass those of MBD. These characteristic features of the five methods were confirmed by checking the evolution of the total energy norms and their growth rates. Characteristics of the initial perturbations obtained by four methods (GSV, MSV, MBD and LET) were examined for the case of a synoptic low-pressure system passing over eastern China. With GSV and MSV, the regions of large spread were near the low-pressure system, but with MSV, the distribution was more concentrated on the mesoscale disturbance. On the other hand, large-spread areas were observed southwest of the disturbance in MBD and LET. The horizontal pattern of LET perturbation was similar to that of MBD, but the amplitude of the LET perturbation reflected the observation density.

Repeatability of paired counts.

PubMed

Alexander, Neal; Bethony, Jeff; Corrêa-Oliveira, Rodrigo; Rodrigues, Laura C; Hotez, Peter; Brooker, Simon

2007-08-30

The Bland and Altman technique is widely used to assess the variation between replicates of a method of clinical measurement. It yields the repeatability, i.e. the value within which 95 per cent of repeat measurements lie. The valid use of the technique requires that the variance is constant over the data range. This is not usually the case for counts of items such as CD4 cells or parasites, nor is the log transformation applicable to zero counts. We investigate the properties of generalized differences based on Box-Cox transformations. For an example, in a data set of hookworm eggs counted by the Kato-Katz method, the square root transformation is found to stabilize the variance. We show how to back-transform the repeatability on the square root scale to the repeatability of the counts themselves, as an increasing function of the square mean root egg count, i.e. the square of the average of square roots. As well as being more easily interpretable, the back-transformed results highlight the dependence of the repeatability on the sample volume used.

Tantalum films with well-controlled roughness grown by oblique incidence deposition

NASA Astrophysics Data System (ADS)

Rechendorff, K.; Hovgaard, M. B.; Chevallier, J.; Foss, M.; Besenbacher, F.

2005-08-01

We have investigated how tantalum films with well-controlled surface roughness can be grown by e-gun evaporation with oblique angle of incidence between the evaporation flux and the surface normal. Due to a more pronounced shadowing effect the root-mean-square roughness increases from about 2 to 33 nm as grazing incidence is approached. The exponent, characterizing the scaling of the root-mean-square roughness with length scale (α), varies from 0.75 to 0.93, and a clear correlation is found between the angle of incidence and root-mean-square roughness.

Facial Expression Recognition using Multiclass Ensemble Least-Square Support Vector Machine

NASA Astrophysics Data System (ADS)

Lawi, Armin; Sya'Rani Machrizzandi, M.

2018-03-01

Facial expression is one of behavior characteristics of human-being. The use of biometrics technology system with facial expression characteristics makes it possible to recognize a person’s mood or emotion. The basic components of facial expression analysis system are face detection, face image extraction, facial classification and facial expressions recognition. This paper uses Principal Component Analysis (PCA) algorithm to extract facial features with expression parameters, i.e., happy, sad, neutral, angry, fear, and disgusted. Then Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM) is used for the classification process of facial expression. The result of MELS-SVM model obtained from our 185 different expression images of 10 persons showed high accuracy level of 99.998% using RBF kernel.

Scale-invariant Green-Kubo relation for time-averaged diffusivity

NASA Astrophysics Data System (ADS)

Meyer, Philipp; Barkai, Eli; Kantz, Holger

2017-12-01

In recent years it was shown both theoretically and experimentally that in certain systems exhibiting anomalous diffusion the time- and ensemble-averaged mean-squared displacement are remarkably different. The ensemble-averaged diffusivity is obtained from a scaling Green-Kubo relation, which connects the scale-invariant nonstationary velocity correlation function with the transport coefficient. Here we obtain the relation between time-averaged diffusivity, usually recorded in single-particle tracking experiments, and the underlying scale-invariant velocity correlation function. The time-averaged mean-squared displacement is given by 〈δ2¯〉 ˜2 DνtβΔν -β , where t is the total measurement time and Δ is the lag time. Here ν is the anomalous diffusion exponent obtained from ensemble-averaged measurements 〈x2〉 ˜tν , while β ≥-1 marks the growth or decline of the kinetic energy 〈v2〉 ˜tβ . Thus, we establish a connection between exponents that can be read off the asymptotic properties of the velocity correlation function and similarly for the transport constant Dν. We demonstrate our results with nonstationary scale-invariant stochastic and deterministic models, thereby highlighting that systems with equivalent behavior in the ensemble average can differ strongly in their time average. If the averaged kinetic energy is finite, β =0 , the time scaling of 〈δ2¯〉 and 〈x2〉 are identical; however, the time-averaged transport coefficient Dν is not identical to the corresponding ensemble-averaged diffusion constant.

Predicting Real-Valued Protein Residue Fluctuation Using FlexPred.

PubMed

Peterson, Lenna; Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2017-01-01

The conventional view of a protein structure as static provides only a limited picture. There is increasing evidence that protein dynamics are often vital to protein function including interaction with partners such as other proteins, nucleic acids, and small molecules. Considering flexibility is also important in applications such as computational protein docking and protein design. While residue flexibility is partially indicated by experimental measures such as the B-factor from X-ray crystallography and ensemble fluctuation from nuclear magnetic resonance (NMR) spectroscopy as well as computational molecular dynamics (MD) simulation, these techniques are resource-intensive. In this chapter, we describe the web server and stand-alone version of FlexPred, which rapidly predicts absolute per-residue fluctuation from a three-dimensional protein structure. On a set of 592 nonredundant structures, comparing the fluctuations predicted by FlexPred to the observed fluctuations in MD simulations showed an average correlation coefficient of 0.669 and an average root mean square error of 1.07 Å. FlexPred is available at http://kiharalab.org/flexPred/ .

Statistical behavior of post-shock overpressure past grid turbulence

NASA Astrophysics Data System (ADS)

Sasoh, Akihiro; Harasaki, Tatsuya; Kitamura, Takuya; Takagi, Daisuke; Ito, Shigeyoshi; Matsuda, Atsushi; Nagata, Kouji; Sakai, Yasuhiko

2014-09-01

When a shock wave ejected from the exit of a 5.4-mm inner diameter, stainless steel tube propagated through grid turbulence across a distance of 215 mm, which is 5-15 times larger than its integral length scale , and was normally incident onto a flat surface; the peak value of post-shock overpressure, , at a shock Mach number of 1.0009 on the flat surface experienced a standard deviation of up to about 9 % of its ensemble average. This value was more than 40 times larger than the dynamic pressure fluctuation corresponding to the maximum value of the root-mean-square velocity fluctuation, . By varying and , the statistical behavior of was obtained after at least 500 runs were performed for each condition. The standard deviation of due to the turbulence was almost proportional to . Although the overpressure modulations at two points 200 mm apart were independent of each other, we observed a weak positive correlation between the peak overpressure difference and the relative arrival time difference.

Flow disturbance due to presence of the vane anemometer

NASA Astrophysics Data System (ADS)

Bujalski, M.; Gawor, M.; Sobczyk, J.

2014-08-01

This paper presents the results of the preliminary experimental investigations of the disturbance of velocity field resulting from placing a vane anemometer in the analyzed air flow. Experiments were conducted in a wind tunnel with a closed loop. For the measurement process, Particle Image Velocimetry (PIV) method was used to visualize the flow structure and evaluate the instantaneous, two-dimensional velocity vector fields. Regions of inflow on the vane anemometer as well as flow behind it were examined. Ensemble averaged velocity distribution and root-mean-square (RMS) velocity fluctuations were determined. The results below are presented in the form of contour-velocity maps and profile plots. In order to investigate velocity fluctuations in the wake of vane anemometer with high temporal resolution hot-wire anemometry (HWA) technique was used. Frequency analysis by means of Fast Fourier Transform was carried out. The obtained results give evidence to a significant spatially and temporally complex flow disturbance in the vicinity of analyzed instrument.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps.

PubMed

Singharoy, Abhishek; Teo, Ivan; McGreevy, Ryan; Stone, John E; Zhao, Jianhua; Schulten, Klaus

2016-07-07

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

Creating a Satellite-Based Record of Tropospheric Ozone

NASA Technical Reports Server (NTRS)

Oetjen, Hilke; Payne, Vivienne H.; Kulawik, Susan S.; Eldering, Annmarie; Worden, John; Edwards, David P.; Francis, Gene L.; Worden, Helen M.

2013-01-01

The TES retrieval algorithm has been applied to IASI radiances. We compare the retrieved ozone profiles with ozone sonde profiles for mid-latitudes for the year 2008. We find a positive bias in the IASI ozone profiles in the UTLS region of up to 22 %. The spatial coverage of the IASI instrument allows sampling of effectively the same air mass with several IASI scenes simultaneously. Comparisons of the root-mean-square of an ensemble of IASI profiles to theoretical errors indicate that the measurement noise and the interference of temperature and water vapour on the retrieval together mostly explain the empirically derived random errors. The total degrees of freedom for signal of the retrieval for ozone are 3.1 +/- 0.2 and the tropospheric degrees of freedom are 1.0 +/- 0.2 for the described cases. IASI ozone profiles agree within the error bars with coincident ozone profiles derived from a TES stare sequence for the ozone sonde station at Bratt's Lake (50.2 deg N, 104.7 deg W).

The Influence of Dimensionality on Estimation in the Partial Credit Model.

ERIC Educational Resources Information Center

De Ayala, R. J.

1995-01-01

The effect of multidimensionality on partial credit model parameter estimation was studied with noncompensatory and compensatory data. Analysis results, consisting of root mean square error bias, Pearson product-moment corrections, standardized root mean squared differences, standardized differences between means, and descriptive statistics…

MgB2 Thin-Film Bolometer for Applications in Far-Infrared Instruments on Future Planetary Missions

NASA Technical Reports Server (NTRS)

Lakew, B.; Aslam, S.; Brasunas, J.; Cao, N.; Costen, N.; La, A.; Stevenson, T.; Waczynski, A.

2012-01-01

A SiN membrane based MgB2 thin-film bolometer, with a non-optimized absorber, has been fabricated that shows an electrical noise equivalent power of 256 fW/square root Hz operating at 30 Hz in the 8.5 - 12.35 micron spectral bandpass. This value corresponds to an electrical specific detectivity of 7.6 x 10(exp 10) cm square root Hz/W. The bolometer shows a measured blackbody (optical) specific detectivity of 8.8 x 10(exp 9) cm square root Hz/W, with a responsivity of 701.5 kV/W and a first-order time constant of 5.2 ms. It is predicted that with the inclusion of a gold black absorber that a blackbody specific detectivity of 6.4 x 10(exp 10) cm/square root Hz/W at an operational frequency of 10 Hz, can be realized for integration into future planetary exploration instrumentation where high sensitivity is required in the 17 - 250 micron spectral wavelength range.

Analysis of tractable distortion metrics for EEG compression applications.

PubMed

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cárdenas-Barrera, Julián; Cruz-Roldán, Fernando

2012-07-01

Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio.

Blending of Radial HF Radar Surface Current and Model Using ETKF Scheme For The Sunda Strait

NASA Astrophysics Data System (ADS)

Mujiasih, Subekti; Riyadi, Mochammad; Wandono, Dr; Wayan Suardana, I.; Nyoman Gede Wiryajaya, I.; Nyoman Suarsa, I.; Hartanto, Dwi; Barth, Alexander; Beckers, Jean-Marie

2017-04-01

Preliminary study of data blending of surface current for Sunda Strait-Indonesia has been done using the analysis scheme of the Ensemble Transform Kalman Filter (ETKF). The method is utilized to combine radial velocity from HF Radar and u and v component of velocity from Global Copernicus - Marine environment monitoring service (CMEMS) model. The initial ensemble is based on the time variability of the CMEMS model result. Data tested are from 2 CODAR Seasonde radar sites in Sunda Strait and 2 dates such as 09 September 2013 and 08 February 2016 at 12.00 UTC. The radial HF Radar data has a hourly temporal resolution, 20-60 km of spatial range, 3 km of range resolution, 5 degree of angular resolution and spatial resolution and 11.5-14 MHz of frequency range. The u and v component of the model velocity represents a daily mean with 1/12 degree spatial resolution. The radial data from one HF radar site is analyzed and the result compared to the equivalent radial velocity from CMEMS for the second HF radar site. Error checking is calculated by root mean squared error (RMSE). Calculation of ensemble analysis and ensemble mean is using Sangoma software package. The tested R which represents observation error covariance matrix, is a diagonal matrix with diagonal elements equal 0.05, 0.5 or 1.0 m2/s2. The initial ensemble members comes from a model simulation spanning a month (September 2013 or February 2016), one year (2013) or 4 years (2013-2016). The spatial distribution of the radial current are analyzed and the RMSE values obtained from independent HF radar station are optimized. It was verified that the analysis reproduces well the structure included in the analyzed HF radar data. More importantly, the analysis was also improved relative to the second independent HF radar site. RMSE of the improved analysis is better than first HF Radar site Analysis. The best result of the blending exercise was obtained for observation error variance equal to 0.05 m2/s2. This study is still preliminary step, but it gives promising result for bigger size of data, combining other model and further development. Keyword: HF Radar, Sunda Strait, ETKF, CMEMS

A study of autonomous satellite navigation methods using the global positioning satellite system

NASA Technical Reports Server (NTRS)

Tapley, B. D.

1980-01-01

Special orbit determination algorithms were developed to accommodate the size and speed limitations of on-board computer systems of the NAVSTAR Global Positioning System. The algorithms use square root sequential filtering methods. A new method for the time update of the square root covariance matrix was also developed. In addition, the time update method was compared with another square root convariance propagation method to determine relative performance characteristics. Comparisions were based on the results of computer simulations of the LANDSAT-D satellite processing pseudo range and pseudo range-rate measurements from the phase one GPS. A summary of the comparison results is presented.

Application of Data Assimilation with the Root Zone Water Quality Model for Soil Moisture Profile Estimation

USDA-ARS?s Scientific Manuscript database

The Ensemble Kalman Filter (EnKF), a popular data assimilation technique for non-linear systems was applied to the Root Zone Water Quality Model. Measured soil moisture data at four different depths (5cm, 20cm, 40cm and 60cm) from two agricultural fields (AS1 and AS2) in northeastern Indiana were us...

Thermal Aging of Oceanic Asthenosphere

NASA Astrophysics Data System (ADS)

Paulson, E.; Jordan, T. H.

2013-12-01

To investigate the depth extent of mantle thermal aging beneath ocean basins, we project 3D Voigt-averaged S-velocity variations from an ensemble of global tomographic models onto a 1x1 degree age-based regionalization and average over bins delineated by equal increments in the square-root of crustal age. From comparisons among the bin-averaged S-wave profiles, we estimate age-dependent convergence depths (minimum depths where the age variations become statistically insignificant) as well as S travel times from these depths to a shallow reference surface. Using recently published techniques (Jordan & Paulson, JGR, doi:10.1002/jgrb.50263, 2013), we account for the aleatory variability in the bin-averaged S-wave profiles using the angular correlation functions of the individual tomographic models, we correct the convergence depths for vertical-smearing bias using their radial correlation functions, and we account for epistemic uncertainties through Bayesian averaging over the tomographic model ensemble. From this probabilistic analysis, we can assert with 90% confidence that the age-correlated variations in Voigt-averaged S velocities persist to depths greater than 170 km; i.e., more than 100 km below the mean depth of the G discontinuity (~70 km). Moreover, the S travel time above the convergence depth decays almost linearly with the square-root of crustal age out to 200 Ma, consistent with a half-space cooling model. Given the strong evidence that the G discontinuity approximates the lithosphere-asthenosphere boundary (LAB) beneath ocean basins, we conclude that the upper (and probably weakest) part of the oceanic asthenosphere, like the oceanic lithosphere, participates in the cooling that forms the kinematic plates, or tectosphere. In other words, the thermal boundary layer of a mature oceanic plate appears to be more than twice the thickness of its mechanical boundary layer. We do not discount the possibility that small-scale convection creates heterogeneities in the oceanic upper mantle; however, the large-scale flow evidently advects these small-scale heterogeneities along with the plates, allowing the upper part of the asthenosphere to continue cooling with lithospheric age. The dominance of this large-scale horizontal flow may be related to the high stresses associated with its channelization in a thin (~100 km) asthenosphere, as well as the possible focusing of the subtectospheric strain in a low-viscosity channel immediately above the 410-km discontinuity. These speculations aside, the observed thermal aging of oceanic asthenosphere is inconsistent with a tenet of plate tectonics, the LAB hypothesis, which states that lithospheric plates are decoupled from deeper mantle flow by a shear zone in the upper part of the asthenosphere.

Decadal prediction skill in the ocean with surface nudging in the IPSL-CM5A-LR climate model

NASA Astrophysics Data System (ADS)

Mignot, Juliette; García-Serrano, Javier; Swingedouw, Didier; Germe, Agathe; Nguyen, Sébastien; Ortega, Pablo; Guilyardi, Eric; Ray, Sulagna

2016-08-01

Two decadal prediction ensembles, based on the same climate model (IPSL-CM5A-LR) and the same surface nudging initialization strategy are analyzed and compared with a focus on upper-ocean variables in different regions of the globe. One ensemble consists of 3-member hindcasts launched every year since 1961 while the other ensemble benefits from 9 members but with start dates only every 5 years. Analysis includes anomaly correlation coefficients and root mean square errors computed against several reanalysis and gridded observational fields, as well as against the nudged simulation used to produce the hindcasts initial conditions. The last skill measure gives an upper limit of the predictability horizon one can expect in the forecast system, while the comparison with different datasets highlights uncertainty when assessing the actual skill. Results provide a potential prediction skill (verification against the nudged simulation) beyond the linear trend of the order of 10 years ahead at the global scale, but essentially associated with non-linear radiative forcings, in particular from volcanoes. At regional scale, we obtain 1 year in the tropical band, 10 years at midlatitudes in the North Atlantic and North Pacific, and 5 years at tropical latitudes in the North Atlantic, for both sea surface temperature (SST) and upper-ocean heat content. Actual prediction skill (verified against observational or reanalysis data) is overall more limited and less robust. Even so, large actual skill is found in the extratropical North Atlantic for SST and in the tropical to subtropical North Pacific for upper-ocean heat content. Results are analyzed with respect to the specific dynamics of the model and the way it is influenced by the nudging. The interplay between initialization and internal modes of variability is also analyzed for sea surface salinity. The study illustrates the importance of two key ingredients both necessary for the success of future coordinated decadal prediction exercises, a high frequency of start dates is needed to achieve robust statistical significance, and a large ensemble size is required to increase the signal to noise ratio.

Predictive Skill of Meteorological Drought Based on Multi-Model Ensemble Forecasts: A Real-Time Assessment

NASA Astrophysics Data System (ADS)

Chen, L. C.; Mo, K. C.; Zhang, Q.; Huang, J.

2014-12-01

Drought prediction from monthly to seasonal time scales is of critical importance to disaster mitigation, agricultural planning, and multi-purpose reservoir management. Starting in December 2012, NOAA Climate Prediction Center (CPC) has been providing operational Standardized Precipitation Index (SPI) Outlooks using the North American Multi-Model Ensemble (NMME) forecasts, to support CPC's monthly drought outlooks and briefing activities. The current NMME system consists of six model forecasts from U.S. and Canada modeling centers, including the CFSv2, CM2.1, GEOS-5, CCSM3.0, CanCM3, and CanCM4 models. In this study, we conduct an assessment of the predictive skill of meteorological drought using real-time NMME forecasts for the period from May 2012 to May 2014. The ensemble SPI forecasts are the equally weighted mean of the six model forecasts. Two performance measures, the anomaly correlation coefficient and root-mean-square errors against the observations, are used to evaluate forecast skill.Similar to the assessment based on NMME retrospective forecasts, predictive skill of monthly-mean precipitation (P) forecasts is generally low after the second month and errors vary among models. Although P forecast skill is not large, SPI predictive skill is high and the differences among models are small. The skill mainly comes from the P observations appended to the model forecasts. This factor also contributes to the similarity of SPI prediction among the six models. Still, NMME SPI ensemble forecasts have higher skill than those based on individual models or persistence, and the 6-month SPI forecasts are skillful out to four months. The three major drought events occurred during the 2012-2014 period, the 2012 Central Great Plains drought, the 2013 Upper Midwest flash drought, and 2013-2014 California drought, are used as examples to illustrate the system's strength and limitations. For precipitation-driven drought events, such as the 2012 Central Great Plains drought, NMME SPI forecasts perform well in predicting drought severity and spatial patterns. For fast-developing drought events, such as the 2013 Upper Midwest flash drought, the system failed to capture the onset of the drought.

Assimilation of MODIS Snow Cover Through the Data Assimilation Research Testbed and the Community Land Model Version 4

NASA Technical Reports Server (NTRS)

Zhang, Yong-Fei; Hoar, Tim J.; Yang, Zong-Liang; Anderson, Jeffrey L.; Toure, Ally M.; Rodell, Matthew

2014-01-01

To improve snowpack estimates in Community Land Model version 4 (CLM4), the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) was assimilated into the Community Land Model version 4 (CLM4) via the Data Assimilation Research Testbed (DART). The interface between CLM4 and DART is a flexible, extensible approach to land surface data assimilation. This data assimilation system has a large ensemble (80-member) atmospheric forcing that facilitates ensemble-based land data assimilation. We use 40 randomly chosen forcing members to drive 40 CLM members as a compromise between computational cost and the data assimilation performance. The localization distance, a parameter in DART, was tuned to optimize the data assimilation performance at the global scale. Snow water equivalent (SWE) and snow depth are adjusted via the ensemble adjustment Kalman filter, particularly in regions with large SCF variability. The root-mean-square error of the forecast SCF against MODIS SCF is largely reduced. In DJF (December-January-February), the discrepancy between MODIS and CLM4 is broadly ameliorated in the lower-middle latitudes (2345N). Only minimal modifications are made in the higher-middle (4566N) and high latitudes, part of which is due to the agreement between model and observation when snow cover is nearly 100. In some regions it also reveals that CLM4-modeled snow cover lacks heterogeneous features compared to MODIS. In MAM (March-April-May), adjustments to snowmove poleward mainly due to the northward movement of the snowline (i.e., where largest SCF uncertainty is and SCF assimilation has the greatest impact). The effectiveness of data assimilation also varies with vegetation types, with mixed performance over forest regions and consistently good performance over grass, which can partly be explained by the linearity of the relationship between SCF and SWE in the model ensembles. The updated snow depth was compared to the Canadian Meteorological Center (CMC) data. Differences between CMC and CLM4 are generally reduced in densely monitored regions.

Seasonal simulations using a coupled ocean-atmosphere model with data assimilation

NASA Astrophysics Data System (ADS)

Larow, Timothy Edward

1997-10-01

A coupled ocean-atmosphere initialization scheme using Newtonian relaxation has been developed for the Florida State University coupled ocean-atmosphere global general circulation model. The coupled model is used for seasonal predictions of the boreal summers of 1987 and 1988. The atmosphere model is a modified version of the Florida State University global spectral model, resolution triangular truncation 42 waves. The ocean general circulation model consists of a slightly modified version developed by Latif (1987). Coupling is synchronous with exchange of information every two model hours. Using daily analysis from ECMWF and observed monthly mean SSTs from NCEP, two - one year, time dependent, Newtonian relaxation were conducted using the coupled model prior to the seasonal forecasts. Relaxation was selectively applied to the atmospheric vorticity, divergence, temperature, and dew point depression equations, and to the ocean's surface temperature equation. The ocean's initial conditions are from a six year ocean-only simulation which used observed wind stresses and a relaxation towards observed SSTs for forcings. Coupled initialization was conducted from 1 June 1986 to 1 June 1987 for the 1987 boreal forecast and from 1 June 1987 to 1 June 1988 for the 1988 boreal forecast. Examination of annual means of net heat flux, freshwater flux and wind stress obtained by from the initialization show close agreement with Oberhuber (1988) climatology and the Florida State University pseudo wind stress analysis. Sensitivity of the initialization/assimilation scheme was tested by conducting two - ten member ensemble integrations. Each member was integrated for 90 days (June-August) of the respective year. Initial conditions for the ensembles consisted of the same ocean state as used by the initialize forecasts, while the atmospheric initial conditions were from ECMWF analysis centered on 1 June of the respective year. Root mean square error and anomaly correlations between observed and forecasted SSTs in the Nino 3 and Nino 4 regions show greater skill between the initialized forecasts than the ensemble forecasts. It is hypothesized that differences in the specific humidity within the planetary boundary layer are responsible for the large SST errors noted with the ensembles.

NOAA HRD's HEDAS Data Assimilation System's performance for the 2010 Atlantic Hurricane Season

NASA Astrophysics Data System (ADS)

Sellwood, K.; Aksoy, A.; Vukicevic, T.; Lorsolo, S.

2010-12-01

The Hurricane Ensemble Data Assimilation System (HEDAS) was developed at the Hurricane Research Division (HRD) of NOAA, in conjunction with an experimental version of the Hurricane Weather and Research Forecast model (HWRFx), in an effort to improve the initial representation of the hurricane vortex by utilizing high resolution in-situ data collected during NOAA’s Hurricane Field Program. HEDAS implements the “ensemble square root “ filter of Whitaker and Hamill (2002) using a 30 member ensemble obtained from NOAA/ESRL’s ensemble Kalman filter (EnKF) system and the assimilation is performed on a 3-km nest centered on the hurricane vortex. As part of NOAA’s Hurricane Forecast Improvement Program (HFIP), HEDAS will be run in a semi-operational mode for the first time during the 2010 Atlantic hurricane season and will assimilate airborne Doppler radar winds, dropwindsonde and flight level wind, temperature, pressure and relative humidity, and Stepped Frequency Microwave Radiometer surface wind observations as they become available. HEDAS has been implemented in an experimental mode for the cases of Hurricane Bill, 2009 and Paloma, 2008 to confirm functionality and determine the optimal configuration of the system. This test case demonstrates the importance of assimilating thermodynamic data in addition to wind observations and the benefit of increasing the quantity and distribution of observations. Applying HEDAS to a larger sample of storm forecasts would provide further insight into the behavior of the model when inner core aircraft observations are assimilated. The main focus of this talk will be to present a summary of HEDAS performance in the HWRFx model for the inaugural season. The HEDAS analyses and the resulting HWRFx forecasts will be compared with HWRFx analyses and forecasts produced concurrently using the HRD modeling group’s vortex initialization which does not employ data assimilation. The initial vortex and subsequent forecasts will be evaluated based on the thermodynamic structure, wind field, track and intensity. Related HEDAS research to be presented by HRD’s data assimilation group include evaluations of the geostrophic wind balance and covariance structures for the Bill experiments, and Observation System Simulation experiments (OSSEs) for the case of hurricane Paloma using both model generated and real observations.

Dynamic clustering threshold reduces conformer ensemble size while maintaining a biologically relevant ensemble

PubMed Central

Yongye, Austin B.; Bender, Andreas

2010-01-01

Representing the 3D structures of ligands in virtual screenings via multi-conformer ensembles can be computationally intensive, especially for compounds with a large number of rotatable bonds. Thus, reducing the size of multi-conformer databases and the number of query conformers, while simultaneously reproducing the bioactive conformer with good accuracy, is of crucial interest. While clustering and RMSD filtering methods are employed in existing conformer generators, the novelty of this work is the inclusion of a clustering scheme (NMRCLUST) that does not require a user-defined cut-off value. This algorithm simultaneously optimizes the number and the average spread of the clusters. Here we describe and test four inter-dependent approaches for selecting computer-generated conformers, namely: OMEGA, NMRCLUST, RMS filtering and averaged-RMS filtering. The bioactive conformations of 65 selected ligands were extracted from the corresponding protein:ligand complexes from the Protein Data Bank, including eight ligands that adopted dissimilar bound conformations within different receptors. We show that NMRCLUST can be employed to further filter OMEGA-generated conformers while maintaining biological relevance of the ensemble. It was observed that NMRCLUST (containing on average 10 times fewer conformers per compound) performed nearly as well as OMEGA, and both outperformed RMS filtering and averaged-RMS filtering in terms of identifying the bioactive conformations with excellent and good matches (0.5 < RMSD < 1.0 Å). Furthermore, we propose thresholds for OMEGA root-mean square filtering depending on the number of rotors in a compound: 0.8, 1.0 and 1.4 for structures with low (1–4), medium (5–9) and high (10–15) numbers of rotatable bonds, respectively. The protocol employed is general and can be applied to reduce the number of conformers in multi-conformer compound collections and alleviate the complexity of downstream data processing in virtual screening experiments. Electronic supplementary material The online version of this article (doi:10.1007/s10822-010-9365-1) contains supplementary material, which is available to authorized users. PMID:20499135

The Menousa

ERIC Educational Resources Information Center

Mason, John; Watson, Anne

2009-01-01

While Socrates and Meno are discussing the nature of knowledge through considering the square-root of two with one of Meno's slaves, their wives are discussing the nature of knowledge through considering the square-root of three with one of the slave girls, using a diagram based on Raphael's "The School of Athens" being contemplated by Euclid.

Local ensemble transform Kalman filter for ionospheric data assimilation: Observation influence analysis during a geomagnetic storm event

NASA Astrophysics Data System (ADS)

Durazo, Juan A.; Kostelich, Eric J.; Mahalov, Alex

2017-09-01

We propose a targeted observation strategy, based on the influence matrix diagnostic, that optimally selects where additional observations may be placed to improve ionospheric forecasts. This strategy is applied in data assimilation observing system experiments, where synthetic electron density vertical profiles, which represent those of Constellation Observing System for Meteorology, Ionosphere, and Climate/Formosa satellite 3, are assimilated into the Thermosphere-Ionosphere-Electrodynamics General Circulation Model using the local ensemble transform Kalman filter during the 26 September 2011 geomagnetic storm. During each analysis step, the observation vector is augmented with five synthetic vertical profiles optimally placed to target electron density errors, using our targeted observation strategy. Forecast improvement due to assimilation of augmented vertical profiles is measured with the root-mean-square error (RMSE) of analyzed electron density, averaged over 600 km regions centered around the augmented vertical profile locations. Assimilating vertical profiles with targeted locations yields about 60%-80% reduction in electron density RMSE, compared to a 15% average reduction when assimilating randomly placed vertical profiles. Assimilating vertical profiles whose locations target the zonal component of neutral winds (Un) yields on average a 25% RMSE reduction in Un estimates, compared to a 2% average improvement obtained with randomly placed vertical profiles. These results demonstrate that our targeted strategy can improve data assimilation efforts during extreme events by detecting regions where additional observations would provide the largest benefit to the forecast.

The quasi-biennial vertical oscillations at global GPS stations: identification by ensemble empirical mode decomposition.

PubMed

Pan, Yuanjin; Shen, Wen-Bin; Ding, Hao; Hwang, Cheinway; Li, Jin; Zhang, Tengxu

2015-10-14

Modeling nonlinear vertical components of a GPS time series is critical to separating sources contributing to mass displacements. Improved vertical precision in GPS positioning at stations for velocity fields is key to resolving the mechanism of certain geophysical phenomena. In this paper, we use ensemble empirical mode decomposition (EEMD) to analyze the daily GPS time series at 89 continuous GPS stations, spanning from 2002 to 2013. EEMD decomposes a GPS time series into different intrinsic mode functions (IMFs), which are used to identify different kinds of signals and secular terms. Our study suggests that the GPS records contain not only the well-known signals (such as semi-annual and annual signals) but also the seldom-noted quasi-biennial oscillations (QBS). The quasi-biennial signals are explained by modeled loadings of atmosphere, non-tidal and hydrology that deform the surface around the GPS stations. In addition, the loadings derived from GRACE gravity changes are also consistent with the quasi-biennial deformations derived from the GPS observations. By removing the modeled components, the weighted root-mean-square (WRMS) variation of the GPS time series is reduced by 7.1% to 42.3%, and especially, after removing the seasonal and QBO signals, the average improvement percentages for seasonal and QBO signals are 25.6% and 7.5%, respectively, suggesting that it is significant to consider the QBS signals in the GPS records to improve the observed vertical deformations.

The Quasi-Biennial Vertical Oscillations at Global GPS Stations: Identification by Ensemble Empirical Mode Decomposition

PubMed Central

Pan, Yuanjin; Shen, Wen-Bin; Ding, Hao; Hwang, Cheinway; Li, Jin; Zhang, Tengxu

2015-01-01

Modeling nonlinear vertical components of a GPS time series is critical to separating sources contributing to mass displacements. Improved vertical precision in GPS positioning at stations for velocity fields is key to resolving the mechanism of certain geophysical phenomena. In this paper, we use ensemble empirical mode decomposition (EEMD) to analyze the daily GPS time series at 89 continuous GPS stations, spanning from 2002 to 2013. EEMD decomposes a GPS time series into different intrinsic mode functions (IMFs), which are used to identify different kinds of signals and secular terms. Our study suggests that the GPS records contain not only the well-known signals (such as semi-annual and annual signals) but also the seldom-noted quasi-biennial oscillations (QBS). The quasi-biennial signals are explained by modeled loadings of atmosphere, non-tidal and hydrology that deform the surface around the GPS stations. In addition, the loadings derived from GRACE gravity changes are also consistent with the quasi-biennial deformations derived from the GPS observations. By removing the modeled components, the weighted root-mean-square (WRMS) variation of the GPS time series is reduced by 7.1% to 42.3%, and especially, after removing the seasonal and QBO signals, the average improvement percentages for seasonal and QBO signals are 25.6% and 7.5%, respectively, suggesting that it is significant to consider the QBS signals in the GPS records to improve the observed vertical deformations. PMID:26473882

Comparison of MM/GBSA calculations based on explicit and implicit solvent simulations.

PubMed

Godschalk, Frithjof; Genheden, Samuel; Söderhjelm, Pär; Ryde, Ulf

2013-05-28

Molecular mechanics with generalised Born and surface area solvation (MM/GBSA) is a popular method to calculate the free energy of the binding of ligands to proteins. It involves molecular dynamics (MD) simulations with an explicit solvent of the protein-ligand complex to give a set of snapshots for which energies are calculated with an implicit solvent. This change in the solvation method (explicit → implicit) would strictly require that the energies are reweighted with the implicit-solvent energies, which is normally not done. In this paper we calculate MM/GBSA energies with two generalised Born models for snapshots generated by the same methods or by explicit-solvent simulations for five synthetic N-acetyllactosamine derivatives binding to galectin-3. We show that the resulting energies are very different both in absolute and relative terms, showing that the change in the solvent model is far from innocent and that standard MM/GBSA is not a consistent method. The ensembles generated with the various solvent models are quite different with root-mean-square deviations of 1.2-1.4 Å. The ensembles can be converted to each other by performing short MD simulations with the new method, but the convergence is slow, showing mean absolute differences in the calculated energies of 6-7 kJ mol(-1) after 2 ps simulations. Minimisations show even slower convergence and there are strong indications that the energies obtained from minimised structures are different from those obtained by MD.

Ratio of jet cross sections at square root of s = 630 GeV and 1800 GeV.

PubMed

Abbott, B; Abolins, M; Abramov, V; Acharya, B S; Adams, D L; Adams, M; Alves, G A; Amos, N; Anderson, E W; Baarmand, M M; Babintsev, V V; Babukhadia, L; Baden, A; Baldin, B; Balm, P W; Banerjee, S; Bantly, J; Barberis, E; Baringer, P; Bartlett, J F; Bassler, U; Bean, A; Begel, M; Belyaev, A; Beri, S B; Bernardi, G; Bertram, I; Besson, A; Bezzubov, V A; Bhat, P C; Bhatnagar, V; Bhattacharjee, M; Blazey, G; Blessing, S; Boehnlein, A; Bojko, N I; Borcherding, F; Brandt, A; Breedon, R; Briskin, G; Brock, R; Brooijmans, G; Bross, A; Buchholz, D; Buehler, M; Buescher, V; Burtovoi, V S; Butler, J M; Canelli, F; Carvalho, W; Casey, D; Casilum, Z; Castilla-Valdez, H; Chakraborty, D; Chan, K M; Chekulaev, S V; Cho, D K; Choi, S; Chopra, S; Christenson, J H; Chung, M; Claes, D; Clark, A R; Cochran, J; Coney, L; Connolly, B; Cooper, W E; Coppage, D; Cummings, M A; Cutts, D; Dahl, O I; Davis, G A; Davis, K; De, K; Del Signore, K; Demarteau, M; Demina, R; Demine, P; Denisov, D; Denisov, S P; Desai, S; Diehl, H T; Diesburg, M; Di Loreto, G; Doulas, S; Draper, P; Ducros, Y; Dudko, L V; Duensing, S; Dugad, S R; Dyshkant, A; Edmunds, D; Ellison, J; Elvira, V D; Engelmann, R; Eno, S; Eppley, G; Ermolov, P; Eroshin, O V; Estrada, J; Evans, H; Evdokimov, V N; Fahland, T; Feher, S; Fein, D; Ferbel, T; Fisk, H E; Fisyak, Y; Flattum, E; Fleuret, F; Fortner, M; Frame, K C; Fuess, S; Gallas, E; Galyaev, A N; Gartung, P; Gavrilov, V; Genik, R J; Genser, K; Gerber, C E; Gershtein, Y; Gibbard, B; Gilmartin, R; Ginther, G; Gómez, B; Gómez, G; Goncharov, P I; González Solís, J L; Gordon, H; Goss, L T; Gounder, K; Goussiou, A; Graf, N; Graham, G; Grannis, P D; Green, J A; Greenlee, H; Grinstein, S; Groer, L; Grudberg, P; Grünendahl, S; Gupta, A; Gurzhiev, S N; Gutierrez, G; Gutierrez, P; Hadley, N J; Haggerty, H; Hagopian, S; Hagopian, V; Hahn, K S; Hall, R E; Hanlet, P; Hansen, S; Hauptman, J M; Hays, C; Hebert, C; Hedin, D; Heinson, A P; Heintz, U; Heuring, T; Hirosky, R; Hobbs, J D; Hoeneisen, B; Hoftun, J S; Hou, S; Huang, Y; Ito, A S; Jerger, S A; Jesik, R; Johns, K; Johnson, M; Jonckheere, A; Jones, M; Jöstlein, H; Juste, A; Kahn, S; Kajfasz, E; Karmanov, D; Karmgard, D; Kehoe, R; Kim, S K; Klima, B; Klopfenstein, C; Knuteson, B; Ko, W; Kohli, J M; Kostritskiy, A V; Kotcher, J; Kotwal, A V; Kozelov, A V; Kozlovsky, E A; Krane, J; Krishnaswamy, M R; Krzywdzinski, S; Kubantsev, M; Kuleshov, S; Kulik, Y; Kunori, S; Kuznetsov, V E; Landsberg, G; Leflat, A; Lehner, F; Li, J; Li, Q Z; Lima, J G; Lincoln, D; Linn, S L; Linnemann, J; Lipton, R; Lucotte, A; Lueking, L; Lundstedt, C; Maciel, A K; Madaras, R J; Manankov, V; Mao, H S; Marshall, T; Martin, M I; Martin, R D; Mauritz, K M; May, B; Mayorov, A A; McCarthy, R; McDonald, J; McMahon, T; Melanson, H L; Meng, X C; Merkin, M; Merritt, K W; Miao, C; Miettinen, H; Mihalcea, D; Mincer, A; Mishra, C S; Mokhov, N; Mondal, N K; Montgomery, H E; Moore, R W; Mostafa, M; da Motta, H; Nagy, E; Nang, F; Narain, M; Narasimham, V S; Neal, H A; Negret, J P; Negroni, S; Norman, D; Oesch, L; Oguri, V; Olivier, B; Oshima, N; Padley, P; Pan, L J; Para, A; Parashar, N; Partridge, R; Parua, N; Paterno, M; Patwa, A; Pawlik, B; Perkins, J; Peters, M; Peters, O; Piegaia, R; Piekarz, H; Pope, B G; Popkov, E; Prosper, H B; Protopopescu, S; Qian, J; Quintas, P Z; Raja, R; Rajagopalan, S; Ramberg, E; Rapidis, P A; Reay, N W; Reucroft, S; Rha, J; Rijssenbeek, M; Rockwell, T; Roco, M; Rubinov, P; Ruchti, R; Rutherfoord, J; Santoro, A; Sawyer, L; Schamberger, R D; Schellman, H; Schwartzman, A; Sculli, J; Sen, N; Shabalina, E; Shankar, H C; Shivpuri, R K; Shpakov, D; Shupe, M; Sidwell, R A; Simak, V; Singh, H; Singh, J B; Sirotenko, V; Slattery, P; Smith, E; Smith, R P; Snihur, R; Snow, G R; Snow, J; Snyder, S; Solomon, J; Sorín, V; Sosebee, M; Sotnikova, N; Soustruznik, K; Souza, M; Stanton, N R; Steinbrück, G; Stephens, R W; Stevenson, M L; Stichelbaut, F; Stoker, D; Stolin, V; Stoyanova, D A; Strauss, M; Streets, K; Strovink, M; Stutte, L; Sznajder, A; Taylor, W; Tentindo-Repond, S; Thompson, J; Toback, D; Tripathi, S M; Trippe, T G; Turcot, A S; Tuts, P M; van Gemmeren, P; Vaniev, V; Van Kooten, R; Varelas, N; Volkov, A A; Vorobiev, A P; Wahl, H D; Wang, H; Wang, Z M; Warchol, J; Watts, G; Wayne, M; Weerts, H; White, A; White, J T; Whiteson, D; Wightman, J A; Wijngaarden, D A; Willis, S; Wimpenny, S J; Wirjawan, J V; Womersley, J; Wood, D R; Yamada, R; Yamin, P; Yasuda, T; Yip, K; Youssef, S; Yu, J; Yu, Z; Zanabria, M; Zheng, H; Zhou, Z; Zhu, Z H; Zielinski, M; Zieminska, D; Zieminski, A; Zutshi, V; Zverev, E G; Zylberstejn, A

2001-03-19

The D0 Collaboration has measured the inclusive jet cross section in barpp collisions at square root of s = 630 GeV. The results for pseudorapidities (eta)<0.5 are combined with our previous results at square root of s = 1800 GeV to form a ratio of cross sections with smaller uncertainties than either individual measurement. Next-to-leading-order QCD predictions show excellent agreement with the measurement at 630 GeV; agreement is also satisfactory for the ratio. Specifically, despite a 10% to 15% difference in the absolute magnitude, the dependence of the ratio on jet transverse momentum is very similar for data and theory.

Fracture toughness of CIP-HIP (cold isostatic pressed - hot isostatic pressed) beryllium at elevated temperatures. Final report, 13 May 1980-13 February 1981

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

Barker, L.M.; Jones, A.H.

1986-04-01

The fracture toughness of CIP-HIP (cold isostatic pressed-hot isostatic pressed) beryllium was determined using the short-bar fracture-toughness (K/sub IcSB/) method. The K/sub IcSB/ value measured was 10.96 MPa x the square root of m at room temperature. This falls well within the expected range of 9 to 12 MPa x the square root of m as observed from previous fracture toughness measurements of beryllium. Toughness increased rapidly between 400 F and 500 F reaching a value of 16.7 MPa x the square root of m at 500 F.

Application of Partial Least Square (PLS) Analysis on Fluorescence Data of 8-Anilinonaphthalene-1-Sulfonic Acid, a Polarity Dye, for Monitoring Water Adulteration in Ethanol Fuel.

PubMed

Kumar, Keshav; Mishra, Ashok Kumar

2015-07-01

Fluorescence characteristic of 8-anilinonaphthalene-1-sulfonic acid (ANS) in ethanol-water mixture in combination with partial least square (PLS) analysis was used to propose a simple and sensitive analytical procedure for monitoring the adulteration of ethanol by water. The proposed analytical procedure was found to be capable of detecting even small adulteration level of ethanol by water. The robustness of the procedure is evident from the statistical parameters such as square of correlation coefficient (R(2)), root mean square of calibration (RMSEC) and root mean square of prediction (RMSEP) that were found to be well with in the acceptable limits.

An Algorithm for Computing Matrix Square Roots with Application to Riccati Equation Implementation,

DTIC Science & Technology

1977-01-01

pansion is compared to Euclid’s method. The apriori by Aerospace Medical Research Laboratory, Aero— upper and lower bounds are also calculated. The third ... space Medical Division , Air Force Systems Command , part of this paper extends the scalar square root al— Wright—Patterson Air Force Base, Ohio 45433

Fast and stable algorithms for computing the principal square root of a complex matrix

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Lian, Sui R.; Mcinnis, Bayliss C.

1987-01-01

This note presents recursive algorithms that are rapidly convergent and more stable for finding the principal square root of a complex matrix. Also, the developed algorithms are utilized to derive the fast and stable matrix sign algorithms which are useful in developing applications to control system problems.

Sub-Femto-g Free Fall for Space-Based Gravitational Wave Observatories: LISA Pathfinder Results

NASA Technical Reports Server (NTRS)

Armano, M.; Audley, H.; Auger, G.; Baird, J. T.; Bassan, M.; Binetruy, P.; Born, M.; Bortoluzzi, D.; Brandt, N.; Thorpe, J. I.

2016-01-01

We report the first results of the LISA Pathfinder in-flight experiment. The results demonstrate that two free-falling reference test masses, such as those needed for a space-based gravitational wave observatory like LISA, can be put in free fall with a relative acceleration noise with a square root of the power spectral density of 5.2 +/- 0.1 fm s(exp -2)/square root of Hz, or (0.54 +/- 0.01) x 10(exp -15) g/square root of Hz, with g the standard gravity, for frequencies between 0.7 and 20 mHz. This value is lower than the LISA Pathfinder requirement by more than a factor 5 and within a factor 1.25 of the requirement for the LISA mission, and is compatible with Brownian noise from viscous damping due to the residual gas surrounding the test masses. Above 60 mHz the acceleration noise is dominated by interferometer displacement readout noise at a level of (34.8 +/- 0.3) fm square root of Hz, about 2 orders of magnitude better than requirements. At f less than or equal to 0.5 mHz we observe a low-frequency tail that stays below 12 fm s(exp -2)/square root of Hz down to 0.1 mHz. This performance would allow for a space-based gravitational wave observatory with a sensitivity close to what was originally foreseen for LISA.

Fast algorithm for computing a primitive /2 to power p + 1/p-th root of unity in GF/q squared/

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.; Miller, R. L.

1978-01-01

A quick method is described for finding the primitive (2 to power p + 1)p-th root of unity in the Galois field GF(q squared), where q = (2 to power p) - 1 and is known as a Mersenne prime. Determination of this root is necessary to implement complex integer transforms of length (2 to power k) times p over the Galois field, with k varying between 3 and p + 1.

Structural Variation of Alpha-synuclein with Temperature by a Coarse-grained Approach with Knowledge-based Interactions (Postprint)

DTIC Science & Technology

2015-07-01

the radius of gyration in detail as a function FIG. 5. Variation of the root mean square (RMS) displacement of the center of mass of the protein with...depends on the temperature. The global motion can be examined by analyzing the variation of the root mean square displacement (RMS) of the center of...and global physical quantities during the course of simula- tion, including the energy of each residue, its mobility, mean square displacement of the

Development Towards a Space Qualified Laser Stabilization System in Support of Space-Based Optical Interferometers

NASA Technical Reports Server (NTRS)

Seidel, David J.; Dubovitsky, Serge

2000-01-01

We report on the development, functional performance and space-qualification status of a laser stabilization system supporting a space-based metrology source used to measure changes in optical path lengths in space-based stellar interferometers. The Space Interferometry Mission (SIM) and Deep Space 3 (DS-3) are two missions currently funded by the National Aeronautics and Space Administration (NASA) that are space-based optical interferometers. In order to properly recombine the starlight received at each telescope of the interferometer it is necessary to perform high resolution laser metrology to stabilize the interferometer. A potentially significant error source in performing high resolution metrology length measurements is the potential for fluctuations in the laser gauge itself. If the laser frequency or wavelength is changing over time it will be misinterpreted as a length change in one of the legs of the interferometer. An analysis of the frequency stability requirement for SIM resulted in a fractional frequency stability requirement of square root (S(sub y)(f)) = <2 x 10(exp -12)/square root(Hz) at Fourier frequencies between 10 Hz and 1000 Hz. The DS-3 mission stability requirement is further increased to square root (S(sub y)(f)) = <5 x 10(exp -14)/Square root(Hz) at Fourier frequencies between 0.2 Hz and 10 kHz with a goal of extending the low frequency range to 0.05 Hz. The free running performance of the Lightwave Electronics NPRO lasers, which are the baseline laser for both SIM and DS-3 vary in stability and we have measured them to perform as follows (9 x l0(exp -11)/ f(Hz))(Hz)/square root(Hz)) = <( square root (S(sub y)(f)) = <(1.3 x l0(exp -8)/ f(Hz))/Square root(Hz). In order to improve the frequency stability of the laser we stabilize the laser to a high finesse optical cavity by locking the optical frequency of the laser to one of the transmission modes of the cavity. At JPL we have built a prototype space-qualifiable system meeting the stability requirements of SIM, which has been delivered to one of the SIM testbeds. We have also started on the development of a system to meet the stability needs of DS-3.

The Weighted-Average Lagged Ensemble.

PubMed

DelSole, T; Trenary, L; Tippett, M K

2017-11-01

A lagged ensemble is an ensemble of forecasts from the same model initialized at different times but verifying at the same time. The skill of a lagged ensemble mean can be improved by assigning weights to different forecasts in such a way as to maximize skill. If the forecasts are bias corrected, then an unbiased weighted lagged ensemble requires the weights to sum to one. Such a scheme is called a weighted-average lagged ensemble. In the limit of uncorrelated errors, the optimal weights are positive and decay monotonically with lead time, so that the least skillful forecasts have the least weight. In more realistic applications, the optimal weights do not always behave this way. This paper presents a series of analytic examples designed to illuminate conditions under which the weights of an optimal weighted-average lagged ensemble become negative or depend nonmonotonically on lead time. It is shown that negative weights are most likely to occur when the errors grow rapidly and are highly correlated across lead time. The weights are most likely to behave nonmonotonically when the mean square error is approximately constant over the range forecasts included in the lagged ensemble. An extreme example of the latter behavior is presented in which the optimal weights vanish everywhere except at the shortest and longest lead times.

The Relationship between Root Mean Square Error of Approximation and Model Misspecification in Confirmatory Factor Analysis Models

ERIC Educational Resources Information Center

Savalei, Victoria

2012-01-01

The fit index root mean square error of approximation (RMSEA) is extremely popular in structural equation modeling. However, its behavior under different scenarios remains poorly understood. The present study generates continuous curves where possible to capture the full relationship between RMSEA and various "incidental parameters," such as…

Optimization of one-way wave equations.

USGS Publications Warehouse

Lee, M.W.; Suh, S.Y.

1985-01-01

The theory of wave extrapolation is based on the square-root equation or one-way equation. The full wave equation represents waves which propagate in both directions. On the contrary, the square-root equation represents waves propagating in one direction only. A new optimization method presented here improves the dispersion relation of the one-way wave equation. -from Authors

A reaction-diffusion model for market fluctuations - A relation between price change and traded volumes

NASA Astrophysics Data System (ADS)

Yuvan, Steven; Bier, Martin

2018-02-01

Two decades ago Bak et al. (1997) [3] proposed a reaction-diffusion model to describe market fluctuations. In the model buyers and sellers diffuse from opposite ends of a 1D interval that represents a price range. Trades occur when buyers and sellers meet. We show analytically and numerically that the model well reproduces the square-root relation between traded volumes and price changes that is observed in real-life markets. The result is remarkable as this relation has commonly been explained in terms of more elaborate trader strategies. We furthermore explain why the square-root relation is robust under model modifications and we show how real-life bond market data exhibit the square-root relation.

Aging scaled Brownian motion

NASA Astrophysics Data System (ADS)

Safdari, Hadiseh; Chechkin, Aleksei V.; Jafari, Gholamreza R.; Metzler, Ralf

2015-04-01

Scaled Brownian motion (SBM) is widely used to model anomalous diffusion of passive tracers in complex and biological systems. It is a highly nonstationary process governed by the Langevin equation for Brownian motion, however, with a power-law time dependence of the noise strength. Here we study the aging properties of SBM for both unconfined and confined motion. Specifically, we derive the ensemble and time averaged mean squared displacements and analyze their behavior in the regimes of weak, intermediate, and strong aging. A very rich behavior is revealed for confined aging SBM depending on different aging times and whether the process is sub- or superdiffusive. We demonstrate that the information on the aging factorizes with respect to the lag time and exhibits a functional form that is identical to the aging behavior of scale-free continuous time random walk processes. While SBM exhibits a disparity between ensemble and time averaged observables and is thus weakly nonergodic, strong aging is shown to effect a convergence of the ensemble and time averaged mean squared displacement. Finally, we derive the density of first passage times in the semi-infinite domain that features a crossover defined by the aging time.

Aging scaled Brownian motion.

PubMed

Safdari, Hadiseh; Chechkin, Aleksei V; Jafari, Gholamreza R; Metzler, Ralf

2015-04-01

Scaled Brownian motion (SBM) is widely used to model anomalous diffusion of passive tracers in complex and biological systems. It is a highly nonstationary process governed by the Langevin equation for Brownian motion, however, with a power-law time dependence of the noise strength. Here we study the aging properties of SBM for both unconfined and confined motion. Specifically, we derive the ensemble and time averaged mean squared displacements and analyze their behavior in the regimes of weak, intermediate, and strong aging. A very rich behavior is revealed for confined aging SBM depending on different aging times and whether the process is sub- or superdiffusive. We demonstrate that the information on the aging factorizes with respect to the lag time and exhibits a functional form that is identical to the aging behavior of scale-free continuous time random walk processes. While SBM exhibits a disparity between ensemble and time averaged observables and is thus weakly nonergodic, strong aging is shown to effect a convergence of the ensemble and time averaged mean squared displacement. Finally, we derive the density of first passage times in the semi-infinite domain that features a crossover defined by the aging time.

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Gui-Long

2001-01-01

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Two ways to solve, using Lie group analysis, the fundamental valuation equation in the double-square-root model of the term structure

NASA Astrophysics Data System (ADS)

Sinkala, W.

2011-01-01

Two approaches based on Lie group analysis are employed to obtain the closed-form solution of a partial differential equation derived by Francis A. Longstaff [J Financial Econom 1989;23:195-224] for the price of a discount bond in the double-square-root model of the term structure.

14 CFR Appendix G to Part 25 - Continuous Gust Design Criteria

Code of Federal Regulations, 2014 CFR

2014-01-01

...) Values of Ā (ratio of root-mean-square incremental load root-mean-square gust velocity) must be... gust velocity, ft./sec. Ω=reduced frequency, radians per foot. L=2,500 ft. (3) The limit loads must be... velocity Uσ: (i) At speed Vc: Uσ=85 fps true gust velocity in the interval 0 to 30,000 ft. altitude and is...

14 CFR Appendix G to Part 25 - Continuous Gust Design Criteria

Code of Federal Regulations, 2013 CFR

2013-01-01

...) Values of Ā (ratio of root-mean-square incremental load root-mean-square gust velocity) must be... gust velocity, ft./sec. Ω=reduced frequency, radians per foot. L=2,500 ft. (3) The limit loads must be... velocity Uσ: (i) At speed Vc: Uσ=85 fps true gust velocity in the interval 0 to 30,000 ft. altitude and is...

14 CFR Appendix G to Part 25 - Continuous Gust Design Criteria

Code of Federal Regulations, 2012 CFR

2012-01-01

...) Values of Ā (ratio of root-mean-square incremental load root-mean-square gust velocity) must be... gust velocity, ft./sec. Ω=reduced frequency, radians per foot. L=2,500 ft. (3) The limit loads must be... velocity Uσ: (i) At speed Vc: Uσ=85 fps true gust velocity in the interval 0 to 30,000 ft. altitude and is...

Reification in the Learning of Square Roots in a Ninth Grade Classroom: Combining Semiotic and Discursive Approaches

ERIC Educational Resources Information Center

Shinno, Yusuke

2018-01-01

This paper reports on combining semiotic and discursive approaches to reification in classroom interactions. It focuses on the discursive characteristics and semiotic processes involved in the teaching and learning of square roots in a ninth grade classroom in Japan. The purpose of this study is to characterize the development of mathematical…

A highly accurate analytical solution for the surface fields of a short vertical wire antenna lying on a multilayer ground

NASA Astrophysics Data System (ADS)

Parise, M.

2018-01-01

A highly accurate analytical solution is derived to the electromagnetic problem of a short vertical wire antenna located on a stratified ground. The derivation consists of three steps. First, the integration path of the integrals describing the fields of the dipole is deformed and wrapped around the pole singularities and the two vertical branch cuts of the integrands located in the upper half of the complex plane. This allows to decompose the radiated field into its three contributions, namely the above-surface ground wave, the lateral wave, and the trapped surface waves. Next, the square root terms responsible for the branch cuts are extracted from the integrands of the branch-cut integrals. Finally, the extracted square roots are replaced with their rational representations according to Newton's square root algorithm, and residue theorem is applied to give explicit expressions, in series form, for the fields. The rigorous integration procedure and the convergence of square root algorithm ensure that the obtained formulas converge to the exact solution. Numerical simulations are performed to show the validity and robustness of the developed formulation, as well as its advantages in terms of time cost over standard numerical integration procedures.

Microwave Photonic Architecture for Direction Finding of LPI Emitters: Post-Processing for Angle of Arrival Estimation

DTIC Science & Technology

2016-09-01

mean- square (RMS) error of 0.29° at ə° resolution. For a P4 coded signal, the RMS error in estimating the AOA is 0.32° at 1° resolution. 14...FMCW signal, it was demonstrated that the system is capable of estimating the AOA with a root-mean- square (RMS) error of 0.29° at ə° resolution. For a...Modulator PCB printed circuit board PD photodetector RF radio frequency RMS root-mean- square xvi THIS PAGE INTENTIONALLY LEFT BLANK xvii

A root-mean-square approach for predicting fatigue crack growth under random loading

NASA Technical Reports Server (NTRS)

Hudson, C. M.

1981-01-01

A method for predicting fatigue crack growth under random loading which employs the concept of Barsom (1976) is presented. In accordance with this method, the loading history for each specimen is analyzed to determine the root-mean-square maximum and minimum stresses, and the predictions are made by assuming the tests have been conducted under constant-amplitude loading at the root-mean-square maximum and minimum levels. The procedure requires a simple computer program and a desk-top computer. For the eleven predictions made, the ratios of the predicted lives to the test lives ranged from 2.13 to 0.82, which is a good result, considering that the normal scatter in the fatigue-crack-growth rates may range from a factor of two to four under identical loading conditions.

Storage and computationally efficient permutations of factorized covariance and square-root information matrices

NASA Technical Reports Server (NTRS)

Muellerschoen, R. J.

1988-01-01

A unified method to permute vector-stored upper-triangular diagonal factorized covariance (UD) and vector stored upper-triangular square-root information filter (SRIF) arrays is presented. The method involves cyclical permutation of the rows and columns of the arrays and retriangularization with appropriate square-root-free fast Givens rotations or elementary slow Givens reflections. A minimal amount of computation is performed and only one scratch vector of size N is required, where N is the column dimension of the arrays. To make the method efficient for large SRIF arrays on a virtual memory machine, three additional scratch vectors each of size N are used to avoid expensive paging faults. The method discussed is compared with the methods and routines of Bierman's Estimation Subroutine Library (ESL).

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy

PubMed Central

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system. PMID:27835638

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PubMed

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

Relationship between neighbor number and vibrational spectra in disordered colloidal clusters with attractive interactions

NASA Astrophysics Data System (ADS)

Yunker, Peter J.; Zhang, Zexin; Gratale, Matthew; Chen, Ke; Yodh, A. G.

2013-03-01

We study connections between vibrational spectra and average nearest neighbor number in disordered clusters of colloidal particles with attractive interactions. Measurements of displacement covariances between particles in each cluster permit calculation of the stiffness matrix, which contains effective spring constants linking pairs of particles. From the cluster stiffness matrix, we derive vibrational properties of corresponding "shadow" glassy clusters, with the same geometric configuration and interactions as the "source" cluster but without damping. Here, we investigate the stiffness matrix to elucidate the origin of the correlations between the median frequency of cluster vibrational modes and average number of nearest neighbors in the cluster. We find that the mean confining stiffness of particles in a cluster, i.e., the ensemble-averaged sum of nearest neighbor spring constants, correlates strongly with average nearest neighbor number, and even more strongly with median frequency. Further, we find that the average oscillation frequency of an individual particle is set by the total stiffness of its nearest neighbor bonds; this average frequency increases as the square root of the nearest neighbor bond stiffness, in a manner similar to the simple harmonic oscillator.

A comparison of the stochastic and machine learning approaches in hydrologic time series forecasting

NASA Astrophysics Data System (ADS)

Kim, T.; Joo, K.; Seo, J.; Heo, J. H.

2016-12-01

Hydrologic time series forecasting is an essential task in water resources management and it becomes more difficult due to the complexity of runoff process. Traditional stochastic models such as ARIMA family has been used as a standard approach in time series modeling and forecasting of hydrological variables. Due to the nonlinearity in hydrologic time series data, machine learning approaches has been studied with the advantage of discovering relevant features in a nonlinear relation among variables. This study aims to compare the predictability between the traditional stochastic model and the machine learning approach. Seasonal ARIMA model was used as the traditional time series model, and Random Forest model which consists of decision tree and ensemble method using multiple predictor approach was applied as the machine learning approach. In the application, monthly inflow data from 1986 to 2015 of Chungju dam in South Korea were used for modeling and forecasting. In order to evaluate the performances of the used models, one step ahead and multi-step ahead forecasting was applied. Root mean squared error and mean absolute error of two models were compared.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps

PubMed Central

Singharoy, Abhishek; Teo, Ivan; McGreevy, Ryan; Stone, John E; Zhao, Jianhua; Schulten, Klaus

2016-01-01

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services. DOI: http://dx.doi.org/10.7554/eLife.16105.001 PMID:27383269

Rate Constant and Reaction Coordinate of Trp-Cage Folding in Explicit Water

PubMed Central

Juraszek, Jarek; Bolhuis, Peter G.

2008-01-01

We report rate constant calculations and a reaction coordinate analysis of the rate-limiting folding and unfolding process of the Trp-cage mini-protein in explicit solvent using transition interface sampling. Previous transition path sampling simulations revealed that in this (un)folding process the protein maintains its compact configuration, while a (de)increase of secondary structure is observed. The calculated folding rate agrees reasonably with experiment, while the unfolding rate is 10 times higher. We discuss possible origins for this mismatch. We recomputed the rates with the forward flux sampling method, and found a discrepancy of four orders of magnitude, probably caused by the method's higher sensitivity to the choice of order parameter with respect to transition interface sampling. Finally, we used the previously computed transition path-sampling ensemble to screen combinations of many order parameters for the best model of the reaction coordinate by employing likelihood maximization. We found that a combination of the root mean-square deviation of the helix and of the entire protein was, of the set of tried order parameters, the one that best describes the reaction coordination. PMID:18676648

Comparison of machine-learning methods for above-ground biomass estimation based on Landsat imagery

NASA Astrophysics Data System (ADS)

Wu, Chaofan; Shen, Huanhuan; Shen, Aihua; Deng, Jinsong; Gan, Muye; Zhu, Jinxia; Xu, Hongwei; Wang, Ke

2016-07-01

Biomass is one significant biophysical parameter of a forest ecosystem, and accurate biomass estimation on the regional scale provides important information for carbon-cycle investigation and sustainable forest management. In this study, Landsat satellite imagery data combined with field-based measurements were integrated through comparisons of five regression approaches [stepwise linear regression, K-nearest neighbor, support vector regression, random forest (RF), and stochastic gradient boosting] with two different candidate variable strategies to implement the optimal spatial above-ground biomass (AGB) estimation. The results suggested that RF algorithm exhibited the best performance by 10-fold cross-validation with respect to R2 (0.63) and root-mean-square error (26.44 ton/ha). Consequently, the map of estimated AGB was generated with a mean value of 89.34 ton/ha in northwestern Zhejiang Province, China, with a similar pattern to the distribution mode of local forest species. This research indicates that machine-learning approaches associated with Landsat imagery provide an economical way for biomass estimation. Moreover, ensemble methods using all candidate variables, especially for Landsat images, provide an alternative for regional biomass simulation.

A Lagrangian stochastic model for aerial spray transport above an oak forest

USGS Publications Warehouse

Wang, Yansen; Miller, David R.; Anderson, Dean E.; McManus, Michael L.

1995-01-01

An aerial spray droplets' transport model has been developed by applying recent advances in Lagrangian stochastic simulation of heavy particles. A two-dimensional Lagrangian stochastic model was adopted to simulate the spray droplet dispersion in atmospheric turbulence by adjusting the Lagrangian integral time scale along the drop trajectory. The other major physical processes affecting the transport of spray droplets above a forest canopy, the aircraft wingtip vortices and the droplet evaporation, were also included in each time step of the droplets' transport.The model was evaluated using data from an aerial spray field experiment. In generally neutral stability conditions, the accuracy of the model predictions varied from run-to-run as expected. The average root-mean-square error was 24.61 IU cm−2, and the average relative error was 15%. The model prediction was adequate in two-dimensional steady wind conditions, but was less accurate in variable wind condition. The results indicated that the model can simulate successfully the ensemble; average transport of aerial spray droplets under neutral, steady atmospheric wind conditions.

Search for Randall-Sundrum gravitons in the dielectron and diphoton final states with 5.4  fb(-1) of data from pp collisions at square root(s) = 1.96  TeV.

PubMed

Abazov, V M; Abbott, B; Abolins, M; Acharya, B S; Adams, M; Adams, T; Aguilo, E; Alexeev, G D; Alkhazov, G; Alton, A; Alverson, G; Alves, G A; Ancu, L S; Aoki, M; Arnoud, Y; Arov, M; Askew, A; Asman, B; Atramentov, O; Avila, C; Backus Mayes, J; Badaud, F; Bagby, L; Baldin, B; Bandurin, D V; Banerjee, S; Barberis, E; Barfuss, A-F; Baringer, P; Barreto, J; Bartlett, J F; Bassler, U; Beale, S; Bean, A; Begalli, M; Begel, M; Belanger-Champagne, C; Bellantoni, L; Benitez, J A; Beri, S B; Bernardi, G; Bernhard, R; Bertram, I; Besançon, M; Beuselinck, R; Bezzubov, V A; Bhat, P C; Bhatnagar, V; Blazey, G; Blessing, S; Bloom, K; Boehnlein, A; Boline, D; Bolton, T A; Boos, E E; Borissov, G; Bose, T; Brandt, A; Brock, R; Brooijmans, G; Bross, A; Brown, D; Bu, X B; Buchholz, D; Buehler, M; Buescher, V; Bunichev, V; Burdin, S; Burnett, T H; Buszello, C P; Calfayan, P; Calpas, B; Calvet, S; Camacho-Pérez, E; Cammin, J; Carrasco-Lizarraga, M A; Carrera, E; Casey, B C K; Castilla-Valdez, H; Chakrabarti, S; Chakraborty, D; Chan, K M; Chandra, A; Chen, G; Chevalier-Théry, S; Cho, D K; Cho, S W; Choi, S; Choudhary, B; Christoudias, T; Cihangir, S; Claes, D; Clutter, J; Cooke, M S; Cooke, M; Cooper, W E; Corcoran, M; Couderc, F; Cousinou, M-C; Croc, A; Cutts, D; Cwiok, M; Das, A; Davies, G; De, K; de Jong, S J; De la Cruz-Burelo, E; DeVaughan, K; Déliot, F; Demarteau, M; Demina, R; Denisov, D; Denisov, S P; Desai, S; Diehl, H T; Diesburg, M; Dominguez, A; Dorland, T; Dubey, A; Dudko, L V; Duggan, D; Duperrin, A; Dutt, S; Dyshkant, A; Eads, M; Edmunds, D; Ellison, J; Elvira, V D; Enari, Y; Eno, S; Evans, H; Evdokimov, A; Evdokimov, V N; Facini, G; Ferapontov, A V; Ferbel, T; Fiedler, F; Filthaut, F; Fisher, W; Fisk, H E; Fortner, M; Fox, H; Fuess, S; Gadfort, T; Garcia-Bellido, A; Gavrilov, V; Gay, P; Geist, W; Geng, W; Gerbaudo, D; Gerber, C E; Gershtein, Y; Gillberg, D; Ginther, G; Golovanov, G; Goussiou, A; Grannis, P D; Greder, S; Greenlee, H; Greenwood, Z D; Gregores, E M; Grenier, G; Gris, Ph; Grivaz, J-F; Grohsjean, A; Grünendahl, S; Grünewald, M W; Guo, F; Guo, J; Gutierrez, G; Gutierrez, P; Haas, A; Haefner, P; Hagopian, S; Haley, J; Hall, I; Han, L; Harder, K; Harel, A; Hauptman, J M; Hays, J; Hebbeker, T; Hedin, D; Heinson, A P; Heintz, U; Hensel, C; Heredia-De la Cruz, I; Herner, K; Hesketh, G; Hildreth, M D; Hirosky, R; Hoang, T; Hobbs, J D; Hoeneisen, B; Hohlfeld, M; Hossain, S; Houben, P; Hu, Y; Hubacek, Z; Huske, N; Hynek, V; Iashvili, I; Illingworth, R; Ito, A S; Jabeen, S; Jaffré, M; Jain, S; Jamin, D; Jesik, R; Johns, K; Johnson, C; Johnson, M; Johnston, D; Jonckheere, A; Jonsson, P; Juste, A; Kaadze, K; Kajfasz, E; Karmanov, D; Kasper, P A; Katsanos, I; Kehoe, R; Kermiche, S; Khalatyan, N; Khanov, A; Kharchilava, A; Kharzheev, Y N; Khatidze, D; Kirby, M H; Kirsch, M; Kohli, J M; Kozelov, A V; Kraus, J; Kumar, A; Kupco, A; Kurca, T; Kuzmin, V A; Kvita, J; Lammers, S; Landsberg, G; Lebrun, P; Lee, H S; Lee, W M; Lellouch, J; Li, L; Li, Q Z; Lietti, S M; Lim, J K; Lincoln, D; Linnemann, J; Lipaev, V V; Lipton, R; Liu, Y; Liu, Z; Lobodenko, A; Lokajicek, M; Love, P; Lubatti, H J; Luna-Garcia, R; Lyon, A L; Maciel, A K A; Mackin, D; Madar, R; Magaña-Villalba, R; Mal, P K; Malik, S; Malyshev, V L; Maravin, Y; Martínez-Ortega, J; McCarthy, R; McGivern, C L; Meijer, M M; Melnitchouk, A; Menezes, D; Mercadante, P G; Merkin, M; Meyer, A; Meyer, J; Mondal, N K; Moulik, T; Muanza, G S; Mulhearn, M; Nagy, E; Naimuddin, M; Narain, M; Nayyar, R; Neal, H A; Negret, J P; Neustroev, P; Nilsen, H; Novaes, S F; Nunnemann, T; Obrant, G; Onoprienko, D; Orduna, J; Osman, N; Osta, J; Otero y Garzón, G J; Owen, M; Padilla, M; Pangilinan, M; Parashar, N; Parihar, V; Park, S-J; Park, S K; Parsons, J; Partridge, R; Parua, N; Patwa, A; Penning, B; Perfilov, M; Peters, K; Peters, Y; Petrillo, G; Pétroff, P; Piegaia, R; Piper, J; Pleier, M-A; Podesta-Lerma, P L M; Podstavkov, V M; Pol, M-E; Polozov, P; Popov, A V; Prewitt, M; Price, D; Protopopescu, S; Qian, J; Quadt, A; Quinn, B; Rangel, M S; Ranjan, K; Ratoff, P N; Razumov, I; Renkel, P; Rich, P; Rijssenbeek, M; Ripp-Baudot, I; Rizatdinova, F; Rominsky, M; Royon, C; Rubinov, P; Ruchti, R; Safronov, G; Sajot, G; Sánchez-Hernández, A; Sanders, M P; Sanghi, B; Savage, G; Sawyer, L; Scanlon, T; Schaile, D; Schamberger, R D; Scheglov, Y; Schellman, H; Schliephake, T; Schlobohm, S; Schwanenberger, C; Schwienhorst, R; Sekaric, J; Severini, H; Shabalina, E; Shary, V; Shchukin, A A; Shivpuri, R K; Simak, V; Sirotenko, V; Skubic, P; Slattery, P; Smirnov, D; Snow, G R; Snow, J; Snyder, S; Söldner-Rembold, S; Sonnenschein, L; Sopczak, A; Sosebee, M; Soustruznik, K; Spurlock, B; Stark, J; Stolin, V; Stoyanova, D A; Strang, M A; Strauss, E; Strauss, M; Ströhmer, R; Strom, D; Stutte, L; Svoisky, P; Takahashi, M; Tanasijczuk, A; Taylor, W; Tiller, B; Titov, M; Tokmenin, V V; Tsybychev, D; Tuchming, B; Tully, C; Tuts, P M; Unalan, R; Uvarov, L; Uvarov, S; Uzunyan, S; Van Kooten, R; van Leeuwen, W M; Varelas, N; Varnes, E W; Vasilyev, I A; Verdier, P; Vertogradov, L S; Verzocchi, M; Vesterinen, M; Vilanova, D; Vint, P; Vokac, P; Wahl, H D; Wang, M H L S; Warchol, J; Watts, G; Wayne, M; Weber, G; Weber, M; Wetstein, M; White, A; Wicke, D; Williams, M R J; Wilson, G W; Wimpenny, S J; Wobisch, M; Wood, D R; Wyatt, T R; Xie, Y; Xu, C; Yacoob, S; Yamada, R; Yang, W-C; Yasuda, T; Yatsunenko, Y A; Ye, Z; Yin, H; Yip, K; Yoo, H D; Youn, S W; Yu, J; Zelitch, S; Zhao, T; Zhou, B; Zhou, N; Zhu, J; Zielinski, M; Zieminska, D; Zivkovic, L

2010-06-18

Using 5.4  fb(-1) of integrated luminosity from pp collisions at square root(s)=1.96  TeV collected by the D0 detector at the Fermilab Tevatron Collider, we search for decays of the lightest Kaluza-Klein mode of the graviton in the Randall-Sundrum model to ee and γγ. We set 95% C.L. lower limits on the mass of the lightest graviton between 560 and 1050 GeV for values of the coupling k/M(Pl) between 0.01 and 0.1.

Calibration and parameterization of a semi-distributed hydrological model to support sub-daily ensemble flood forecasting; a watershed in southeast Brazil

NASA Astrophysics Data System (ADS)

de Almeida Bressiani, D.; Srinivasan, R.; Mendiondo, E. M.

2013-12-01

The use of distributed or semi-distributed models to represent the processes and dynamics of a watershed in the last few years has increased. These models are important tools to predict and forecast the hydrological responses of the watersheds, and they can subside disaster risk management and planning. However they usually have a lot of parameters, of which, due to the spatial and temporal variability of the processes, are not known, specially in developing countries; therefore a robust and sensible calibration is very important. This study conduced a sub-daily calibration and parameterization of the Soil & Water Assessment Tool (SWAT) for a 12,600 km2 watershed in southeast Brazil, and uses ensemble forecasts to evaluate if the model can be used as a tool for flood forecasting. The Piracicaba Watershed, in São Paulo State, is mainly rural, but has about 4 million of population in highly relevant urban areas, and three cities in the list of critical cities of the National Center for Natural Disasters Monitoring and Alerts. For calibration: the watershed was divided in areas with similar hydrological characteristics, for each of these areas one gauge station was chosen for calibration; this procedure was performed to evaluate the effectiveness of calibrating in fewer places, since areas with the same group of groundwater, soil, land use and slope characteristics should have similar parameters; making calibration a less time-consuming task. The sensibility analysis and calibration were performed on the software SWAT-CUP with the optimization algorithm: Sequential Uncertainly Fitting Version 2 (SUFI-2), which uses Latin hypercube sampling scheme in an iterative process. The performance of the models to evaluate the calibration and validation was done with: Nash-Sutcliffe efficiency coefficient (NSE), determination coefficient (r2), root mean square error (RMSE), and percent bias (PBIAS), with monthly average values of NSE around 0.70, r2 of 0.9, normalized RMSE of 0.01, and PBIAS of 10. Past events were analysed to evaluate the possibility of using the SWAT developed model for Piracicaba watershed as a tool for ensemble flood forecasting. For the ensemble evaluation members from the numerical model Eta were used. Eta is an atmospheric model used for research and operational purposes, with 5km resolution, and is updated twice a day (00 e 12 UTC) for a ten day horizon, with precipitation and weather estimates for each hour. The parameterized SWAT model performed overall well for ensemble flood forecasting.

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

Multi-model ensemble projections of future extreme heat stress on rice across southern China

NASA Astrophysics Data System (ADS)

He, Liang; Cleverly, James; Wang, Bin; Jin, Ning; Mi, Chunrong; Liu, De Li; Yu, Qiang

2017-08-01

Extreme heat events have become more frequent and intense with climate warming, and these heatwaves are a threat to rice production in southern China. Projected changes in heat stress in rice provide an assessment of the potential impact on crop production and can direct measures for adaptation to climate change. In this study, we calculated heat stress indices using statistical scaling techniques, which can efficiently downscale output from general circulation models (GCMs). Data across the rice belt in southern China were obtained from 28 GCMs in the Coupled Model Intercomparison Project phase 5 (CMIP5) with two emissions scenarios (RCP4.5 for current emissions and RCP8.5 for increasing emissions). Multi-model ensemble projections over the historical period (1960-2010) reproduced the trend of observations in heat stress indices (root-mean-square error RMSE = 6.5 days) better than multi-model arithmetic mean (RMSE 8.9 days) and any individual GCM (RMSE 11.4 days). The frequency of heat stress events was projected to increase by 2061-2100 in both scenarios (up to 185 and 319% for RCP4.5 and RCP8.5, respectively), especially in the middle and lower reaches of the Yangtze River. This increasing risk of exposure to heat stress above 30 °C during flowering and grain filling is predicted to impact rice production. The results of our study suggest the importance of specific adaption or mitigation strategies, such as selection of heat-tolerant cultivars and adjustment of planting date in a warmer future world.

New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

NASA Astrophysics Data System (ADS)

Cane, D.; Milelli, M.

2009-09-01

The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

From Alpha To Omega

NASA Astrophysics Data System (ADS)

Castellano, Doc

2002-08-01

Galileo, the Father of Modern Science, put forth the first significant Modern Scientific Era/Philosophy. Best represented per: x' = x (+/-) vt. Locating/defining the dynamic x' in an Euclidean, fixed frame Universe. Einstein, the popularized relativist, utilizing Lorentz's transformation equations: x' = (x - vt)/square root [ 1- (v squared/c squared)], c the velocity of light. Arbitrarily decreed that c must be the ultimate, universal velocity. Thus, Reporters, the general Public and Scientists consider/considered, Einstein's OPINION of our Universe, 'The Omega Concept'. Castellano, since 1954, has PROVEN the "C Transformation Equations": X' = (X - vt)/square root [ 1 - (v squared/C squared)], Capital C = or greater than c; IS THE OMEGA CONCEPT. And "MAPHICS", combining the Philosophy of Mathematics with the Philosophy of Physics is "THE OMEGA PHILOSOPHY". Sufficient PROOFS & details are at: http://hometown.aol.com/phdco/myhomepage/index/html ----- Thank you for your interest. My sincere appreciation for deserved acknowledgements.

Quantified Choice of Root-Mean-Square Errors of Approximation for Evaluation and Power Analysis of Small Differences between Structural Equation Models

ERIC Educational Resources Information Center

Li, Libo; Bentler, Peter M.

2011-01-01

MacCallum, Browne, and Cai (2006) proposed a new framework for evaluation and power analysis of small differences between nested structural equation models (SEMs). In their framework, the null and alternative hypotheses for testing a small difference in fit and its related power analyses were defined by some chosen root-mean-square error of…

Quantum cryptography: Security criteria reexamined

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

Kaszlikowski, Dagomir; Liang, Y.C.; Englert, Berthold-Georg

2004-09-01

We find that the generally accepted security criteria are flawed for a whole class of protocols for quantum cryptography. This is so because a standard assumption of the security analysis, namely that the so-called square-root measurement is optimal for eavesdropping purposes, is not true in general. There are rather large parameter regimes in which the optimal measurement extracts substantially more information than the square-root measurement.

Verification of forecast ensembles in complex terrain including observation uncertainty

NASA Astrophysics Data System (ADS)

Dorninger, Manfred; Kloiber, Simon

2017-04-01

Traditionally, verification means to verify a forecast (ensemble) with the truth represented by observations. The observation errors are quite often neglected arguing that they are small when compared to the forecast error. In this study as part of the MesoVICT (Mesoscale Verification Inter-comparison over Complex Terrain) project it will be shown, that observation errors have to be taken into account for verification purposes. The observation uncertainty is estimated from the VERA (Vienna Enhanced Resolution Analysis) and represented via two analysis ensembles which are compared to the forecast ensemble. For the whole study results from COSMO-LEPS provided by Arpae-SIMC Emilia-Romagna are used as forecast ensemble. The time period covers the MesoVICT core case from 20-22 June 2007. In a first step, all ensembles are investigated concerning their distribution. Several tests have been executed (Kolmogorov-Smirnov-Test, Finkelstein-Schafer Test, Chi-Square Test etc.) showing no exact mathematical distribution. So the main focus is on non-parametric statistics (e.g. Kernel density estimation, Boxplots etc.) and also the deviation between "forced" normal distributed data and the kernel density estimations. In a next step the observational deviations due to the analysis ensembles are analysed. In a first approach scores are multiple times calculated with every single ensemble member from the analysis ensemble regarded as "true" observation. The results are presented as boxplots for the different scores and parameters. Additionally, the bootstrapping method is also applied to the ensembles. These possible approaches to incorporating observational uncertainty into the computation of statistics will be discussed in the talk.

Exact Results for the Nonergodicity of d -Dimensional Generalized Lévy Walks

NASA Astrophysics Data System (ADS)

Albers, Tony; Radons, Günter

2018-03-01

We provide analytical results for the ensemble-averaged and time-averaged squared displacement, and the randomness of the latter, in the full two-dimensional parameter space of the d -dimensional generalized Lévy walk introduced by Shlesinger et al. [Phys. Rev. Lett. 58, 1100 (1987), 10.1103/PhysRevLett.58.1100]. In certain regions of the parameter plane, we obtain surprising results such as the divergence of the mean-squared displacements, the divergence of the ergodicity breaking parameter despite a finite mean-squared displacement, and subdiffusion which appears superdiffusive when one only considers time averages.

Characterization and Scaling of Black Carbon Aerosol Concentration with City Population Based on In-Situ Measurements and Analysis

NASA Astrophysics Data System (ADS)

Paredes-Miranda, G.; Arnott, W. P.; Moosmuller, H.

2010-12-01

The global trend toward urbanization and the resulting increase in city population has directed attention toward air pollution in megacities. A closely related question of importance for urban planning and attainment of air quality standards is how pollutant concentrations scale with city population. In this study, we use measurements of light absorption and light scattering coefficients as proxies for primary (i.e., black carbon; BC) and total (i.e., particulate matter; PM) pollutant concentration, to start addressing the following questions: What patterns and generalizations are emerging from our expanding data sets on urban air pollution? How does the per-capita air pollution vary with economic, geographic, and meteorological conditions of an urban area? Does air pollution provide an upper limit on city size? Diurnal analysis of black carbon concentration measurements in suburban Mexico City, Mexico, Las Vegas, NV, USA, and Reno, NV, USA for similar seasons suggests that commonly emitted primary air pollutant concentrations scale approximately as the square root of the urban population N, consistent with a simple 2-d box model. The measured absorption coefficient Babs is approximately proportional to the BC concentration (primary pollution) and thus scales with the square root of population (N). Since secondary pollutants form through photochemical reactions involving primary pollutants, they scale also with square root of N. Therefore the scattering coefficient Bsca, a proxy for PM concentration is also expected to scale with square root of N. Here we present light absorption and scattering measurements and data on meteorological conditions and compare the population scaling of these pollutant measurements with predictions from the simple 2-d box model. We find that these basin cities are connected by the square root of N dependence. Data from other cities will be discussed as time permits.

An Ensemble System Based on Hybrid EGARCH-ANN with Different Distributional Assumptions to Predict S&P 500 Intraday Volatility

NASA Astrophysics Data System (ADS)

Lahmiri, S.; Boukadoum, M.

2015-10-01

Accurate forecasting of stock market volatility is an important issue in portfolio risk management. In this paper, an ensemble system for stock market volatility is presented. It is composed of three different models that hybridize the exponential generalized autoregressive conditional heteroscedasticity (GARCH) process and the artificial neural network trained with the backpropagation algorithm (BPNN) to forecast stock market volatility under normal, t-Student, and generalized error distribution (GED) assumption separately. The goal is to design an ensemble system where each single hybrid model is capable to capture normality, excess skewness, or excess kurtosis in the data to achieve complementarity. The performance of each EGARCH-BPNN and the ensemble system is evaluated by the closeness of the volatility forecasts to realized volatility. Based on mean absolute error and mean of squared errors, the experimental results show that proposed ensemble model used to capture normality, skewness, and kurtosis in data is more accurate than the individual EGARCH-BPNN models in forecasting the S&P 500 intra-day volatility based on one and five-minute time horizons data.

A decentralized square root information filter/smoother

NASA Technical Reports Server (NTRS)

Bierman, G. J.; Belzer, M. R.

1985-01-01

A number of developments has recently led to a considerable interest in the decentralization of linear least squares estimators. The developments are partly related to the impending emergence of VLSI technology, the realization of parallel processing, and the need for algorithmic ways to speed the solution of dynamically decoupled, high dimensional estimation problems. A new method is presented for combining Square Root Information Filters (SRIF) estimates obtained from independent data sets. The new method involves an orthogonal transformation, and an information matrix filter 'homework' problem discussed by Schweppe (1973) is generalized. The employed SRIF orthogonal transformation methodology has been described by Bierman (1977).

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

NASA Astrophysics Data System (ADS)

Aalstad, Kristoffer; Westermann, Sebastian; Vikhamar Schuler, Thomas; Boike, Julia; Bertino, Laurent

2018-01-01

With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least nearly matches the performance of other ensemble-based batch smoother schemes with regards to various evaluation metrics. Given the modularity of the method, it could prove valuable for a range of satellite-era hydrometeorological reanalyses.

Verification of an ensemble prediction system for storm surge forecast in the Adriatic Sea

NASA Astrophysics Data System (ADS)

Mel, Riccardo; Lionello, Piero

2014-12-01

In the Adriatic Sea, storm surges present a significant threat to Venice and to the flat coastal areas of the northern coast of the basin. Sea level forecast is of paramount importance for the management of daily activities and for operating the movable barriers that are presently being built for the protection of the city. In this paper, an EPS (ensemble prediction system) for operational forecasting of storm surge in the northern Adriatic Sea is presented and applied to a 3-month-long period (October-December 2010). The sea level EPS is based on the HYPSE (hydrostatic Padua Sea elevation) model, which is a standard single-layer nonlinear shallow water model, whose forcings (mean sea level pressure and surface wind fields) are provided by the ensemble members of the ECMWF (European Center for Medium-Range Weather Forecasts) EPS. Results are verified against observations at five tide gauges located along the Croatian and Italian coasts of the Adriatic Sea. Forecast uncertainty increases with the predicted value of the storm surge and with the forecast lead time. The EMF (ensemble mean forecast) provided by the EPS has a rms (root mean square) error lower than the DF (deterministic forecast), especially for short (up to 3 days) lead times. Uncertainty for short lead times of the forecast and for small storm surges is mainly caused by uncertainty of the initial condition of the hydrodynamical model. Uncertainty for large lead times and large storm surges is mainly caused by uncertainty in the meteorological forcings. The EPS spread increases with the rms error of the forecast. For large lead times the EPS spread and the forecast error substantially coincide. However, the EPS spread in this study, which does not account for uncertainty in the initial condition, underestimates the error during the early part of the forecast and for small storm surge values. On the contrary, it overestimates the rms error for large surge values. The PF (probability forecast) of the EPS has a clear skill in predicting the actual probability distribution of sea level, and it outperforms simple "dressed" PF methods. A probability estimate based on the single DF is shown to be inadequate. However, a PF obtained with a prescribed Gaussian distribution and centered on the DF value performs very similarly to the EPS-based PF.

Applying Ensemble Kalman Filter to Regional Ocean Circulation Model in the East Asian Marginal Sea

NASA Astrophysics Data System (ADS)

Pak, Gyun-Do; Kim, Young Ho; Chang, Kyung-Il

2010-05-01

We successfully apply the ensemble Kalman filter (EnKF) data assimilation scheme to the East Sea Regional Ocean Model (ESROM). The ESROM solves the three dimensional ocean primitive equations with the hydrostatic and Boussinesq approximations. The domain of ESROM fully covers East Sea with grid intervals of approximately 0.1˚. The ESROM has one inflow port, the Korea Strait, and two outflow ports, the Tsugaru and Soya straits. High resolution bathymetry of 1/60˚ (Choi et al., 2002) is adopted for the model topography. The ESROM is initialized using hydrographic data from World Ocean Atlas (WOA), and forced by monthly mean surface and open boundary conditions supplied from European Centre for Medium-Range Weather Forecast data, WOA and so on. The EnKF system is composed of 16 ensembles and thousands of observation data are assimilated at every assimilation step into its parallel version, which significantly reduces the required memory and computational time more than 3-fold compared with its serial version. To prevent the collapse of ensembles due to rank deficiency, we employ various schemes such as localization and inflation of the background error covariance and disturbance of observations. Sea surface temperature from the Advanced Very High Resolution Radiometer and in-situ temperature profiles from various sources including Argo floats have been assimilated into the EnKF system. For cyclonic circulation in the northern East Sea and paths of the East Korean Warm Current and the Nearshore Branch, the EnKF system reproduces the mean surface circulation more realistically than that in the case without data assimilation. Simulated area-averaged vertical temperature profiles also agrees well with the Generalized Digital Environmental Model data, which indicates that the EnKF system corrects the warming of subsurface temperature and the erosion of the permanent thermocline that are usually observed in numerical models without data assimilation. We also quantitatively validate the EnKF system by comparing its results with observed temperatures at 100 m for two years in the southwestern East Sea. We find that spatial and temporal correlations are higher and root-mean-square errors are lower in the EnKF system as compared with those systems without data assimilation.

Search for Higgs boson production in dilepton and missing energy final states with 5.4 fb(-1) of pp collisions at square root(s) = 1.96 TeV.

PubMed

Abazov, V M; Abbott, B; Abolins, M; Acharya, B S; Adams, M; Adams, T; Aguilo, E; Alexeev, G D; Alkhazov, G; Alton, A; Alverson, G; Alves, G A; Ancu, L S; Aoki, M; Arnoud, Y; Arov, M; Askew, A; Asman, B; Atramentov, O; Avila, C; BackusMayes, J; Badaud, F; Bagby, L; Baldin, B; Bandurin, D V; Banerjee, S; Barberis, E; Barfuss, A-F; Baringer, P; Barreto, J; Bartlett, J F; Bassler, U; Bauer, D; Beale, S; Bean, A; Begalli, M; Begel, M; Belanger-Champagne, C; Bellantoni, L; Benitez, J A; Beri, S B; Bernardi, G; Bernhard, R; Bertram, I; Besançon, M; Beuselinck, R; Bezzubov, V A; Bhat, P C; Bhatnagar, V; Blazey, G; Blessing, S; Bloom, K; Boehnlein, A; Boline, D; Bolton, T A; Boos, E E; Borissov, G; Bose, T; Brandt, A; Brock, R; Brooijmans, G; Bross, A; Brown, D; Bu, X B; Buchholz, D; Buehler, M; Buescher, V; Bunichev, V; Burdin, S; Burnett, T H; Buszello, C P; Calfayan, P; Calpas, B; Calvet, S; Camacho-Pérez, E; Cammin, J; Carrasco-Lizarraga, M A; Carrera, E; Casey, B C K; Castilla-Valdez, H; Chakrabarti, S; Chakraborty, D; Chan, K M; Chandra, A; Cheu, E; Chevalier-Théry, S; Cho, D K; Cho, S W; Choi, S; Choudhary, B; Christoudias, T; Cihangir, S; Claes, D; Clutter, J; Cooke, M; Cooper, W E; Corcoran, M; Couderc, F; Cousinou, M-C; Cutts, D; Cwiok, M; Das, A; Davies, G; De, K; de Jong, S J; De la Cruz-Burelo, E; DeVaughan, K; Déliot, F; Demarteau, M; Demina, R; Denisov, D; Denisov, S P; Desai, S; Diehl, H T; Diesburg, M; Dominguez, A; Dorland, T; Dubey, A; Dudko, L V; Duflot, L; Duggan, D; Duperrin, A; Dutt, S; Dyshkant, A; Eads, M; Edmunds, D; Ellison, J; Elvira, V D; Enari, Y; Eno, S; Evans, H; Evdokimov, A; Evdokimov, V N; Facini, G; Ferapontov, A V; Ferbel, T; Fiedler, F; Filthaut, F; Fisher, W; Fisk, H E; Fortner, M; Fox, H; Fuess, S; Gadfort, T; Galea, C F; Garcia-Bellido, A; Gavrilov, V; Gay, P; Geist, W; Geng, W; Gerbaudo, D; Gerber, C E; Gershtein, Y; Gillberg, D; Ginther, G; Golovanov, G; Gómez, B; Goussiou, A; Grannis, P D; Greder, S; Greenlee, H; Greenwood, Z D; Gregores, E M; Grenier, G; Gris, Ph; Grivaz, J-F; Grohsjean, A; Grünendahl, S; Grünewald, M W; Guo, F; Guo, J; Gutierrez, G; Gutierrez, P; Haas, A; Haefner, P; Hagopian, S; Haley, J; Hall, I; Han, L; Harder, K; Harel, A; Hauptman, J M; Hays, J; Hebbeker, T; Hedin, D; Hegeman, J G; Heinson, A P; Heintz, U; Hensel, C; Heredia-De la Cruz, I; Herner, K; Hesketh, G; Hildreth, M D; Hirosky, R; Hoang, T; Hobbs, J D; Hoeneisen, B; Hohlfeld, M; Hossain, S; Houben, P; Hu, Y; Hubacek, Z; Huske, N; Hynek, V; Iashvili, I; Illingworth, R; Ito, A S; Jabeen, S; Jaffré, M; Jain, S; Jamin, D; Jesik, R; Johns, K; Johnson, C; Johnson, M; Johnston, D; Jonckheere, A; Jonsson, P; Juste, A; Kajfasz, E; Karmanov, D; Kasper, P A; Katsanos, I; Kaushik, V; Kehoe, R; Kermiche, S; Khalatyan, N; Khanov, A; Kharchilava, A; Kharzheev, Y N; Khatidze, D; Kirby, M H; Kirsch, M; Kohli, J M; Kozelov, A V; Kraus, J; Kumar, A; Kupco, A; Kurca, T; Kuzmin, V A; Kvita, J; Lam, D; Lammers, S; Landsberg, G; Lebrun, P; Lee, H S; Lee, W M; Leflat, A; Lellouch, J; Li, L; Li, Q Z; Lietti, S M; Lim, J K; Lincoln, D; Linnemann, J; Lipaev, V V; Lipton, R; Liu, Y; Liu, Z; Lobodenko, A; Lokajicek, M; Love, P; Lubatti, H J; Luna-Garcia, R; Lyon, A L; Maciel, A K A; Mackin, D; Mättig, P; Magaña-Villalba, R; Mal, P K; Malik, S; Malyshev, V L; Maravin, Y; Martínez-Ortega, J; McCarthy, R; McGivern, C L; Meijer, M M; Melnitchouk, A; Mendoza, L; Menezes, D; Mercadante, P G; Merkin, M; Meyer, A; Meyer, J; Mondal, N K; Moulik, T; Muanza, G S; Mulhearn, M; Mundal, O; Mundim, L; Nagy, E; Naimuddin, M; Narain, M; Nayyar, R; Neal, H A; Negret, J P; Neustroev, P; Nilsen, H; Nogima, H; Novaes, S F; Nunnemann, T; Obrant, G; Onoprienko, D; Orduna, J; Osman, N; Osta, J; Otec, R; Otero y Garzón, G J; Owen, M; Padilla, M; Padley, P; Pangilinan, M; Parashar, N; Parihar, V; Park, S-J; Park, S K; Parsons, J; Partridge, R; Parua, N; Patwa, A; Penning, B; Perfilov, M; Peters, K; Peters, Y; Pétroff, P; Piegaia, R; Piper, J; Pleier, M-A; Podesta-Lerma, P L M; Podstavkov, V M; Pol, M-E; Polozov, P; Popov, A V; Prewitt, M; Price, D; Protopopescu, S; Qian, J; Quadt, A; Quinn, B; Rangel, M S; Ranjan, K; Ratoff, P N; Razumov, I; Renkel, P; Rich, P; Rijssenbeek, M; Ripp-Baudot, I; Rizatdinova, F; Robinson, S; Rominsky, M; Royon, C; Rubinov, P; Ruchti, R; Safronov, G; Sajot, G; Sánchez-Hernández, A; Sanders, M P; Sanghi, B; Savage, G; Sawyer, L; Scanlon, T; Schaile, D; Schamberger, R D; Scheglov, Y; Schellman, H; Schliephake, T; Schlobohm, S; Schwanenberger, C; Schwienhorst, R; Sekaric, J; Severini, H; Shabalina, E; Shary, V; Shchukin, A A; Shivpuri, R K; Simak, V; Sirotenko, V; Skubic, P; Slattery, P; Smirnov, D; Snow, G R; Snow, J; Snyder, S; Söldner-Rembold, S; Sonnenschein, L; Sopczak, A; Sosebee, M; Soustruznik, K; Spurlock, B; Stark, J; Stolin, V; Stoyanova, D A; Strandberg, J; Strang, M A; Strauss, E; Strauss, M; Ströhmer, R; Strom, D; Stutte, L; Svoisky, P; Takahashi, M; Tanasijczuk, A; Taylor, W; Tiller, B; Titov, M; Tokmenin, V V; Tsybychev, D; Tuchming, B; Tully, C; Tuts, P M; Unalan, R; Uvarov, L; Uvarov, S; Uzunyan, S; van den Berg, P J; Van Kooten, R; van Leeuwen, W M; Varelas, N; Varnes, E W; Vasilyev, I A; Verdier, P; Vertogradov, L S; Verzocchi, M; Vesterinen, M; Vilanova, D; Vint, P; Vokac, P; Wahl, H D; Wang, M H L S; Warchol, J; Watts, G; Wayne, M; Weber, G; Weber, M; Wetstein, M; White, A; Wicke, D; Williams, M R J; Wilson, G W; Wimpenny, S J; Wobisch, M; Wood, D R; Wyatt, T R; Xie, Y; Xu, C; Yacoob, S; Yamada, R; Yang, W-C; Yasuda, T; Yatsunenko, Y A; Ye, Z; Yin, H; Yip, K; Yoo, H D; Youn, S W; Yu, J; Zeitnitz, C; Zelitch, S; Zhao, T; Zhou, B; Zhu, J; Zielinski, M; Zieminska, D; Zivkovic, L; Zutshi, V; Zverev, E G

2010-02-12

A search for the standard model Higgs boson is presented using events with two charged leptons and large missing transverse energy selected from 5.4 fb(-1) of integrated luminosity in pp collisions at square root(s) = 1.96 TeV collected with the D0 detector at the Fermilab Tevatron collider. No significant excess of events above background predictions is found, and observed (expected) upper limits at 95% confidence level on the rate of Higgs boson production are derived that are a factor of 1.55 (1.36) above the predicted standard model cross section at m(H) = 165 GeV.

The Wording of a Proof: Hardy's Second "Elegant" Proof--The Pythagorean School's Irrationality of Square Root of 2

ERIC Educational Resources Information Center

Padula, Janice

2006-01-01

One of the most interesting and important proofs in the history of mathematics is the Pythagorean school's proof of the "irrationality" of the square root of 2. After a brief look at G. H. Hardy (1941) thoughts regarding it, two versions of the classic Pythagorean proof are examined and discussed in this article, one written by an American…

Comments on real tachyon vacuum solution without square roots

NASA Astrophysics Data System (ADS)

Arroyo, E. Aldo

2018-01-01

We analyze the consistency of a recently proposed real tachyon vacuum solution without square roots in open bosonic string field theory. We show that the equation of motion contracted with the solution itself is satisfied. Additionally, by expanding the solution in the basis of the curly ℒ0 and the traditional L 0 eigenstates, we evaluate numerically the vacuum energy and obtain a result in agreement with Sen's conjecture.

Accelerometer Data Analysis and Presentation Techniques

NASA Technical Reports Server (NTRS)

Rogers, Melissa J. B.; Hrovat, Kenneth; McPherson, Kevin; Moskowitz, Milton E.; Reckart, Timothy

1997-01-01

The NASA Lewis Research Center's Principal Investigator Microgravity Services project analyzes Orbital Acceleration Research Experiment and Space Acceleration Measurement System data for principal investigators of microgravity experiments. Principal investigators need a thorough understanding of data analysis techniques so that they can request appropriate analyses to best interpret accelerometer data. Accelerometer data sampling and filtering is introduced along with the related topics of resolution and aliasing. Specific information about the Orbital Acceleration Research Experiment and Space Acceleration Measurement System data sampling and filtering is given. Time domain data analysis techniques are discussed and example environment interpretations are made using plots of acceleration versus time, interval average acceleration versus time, interval root-mean-square acceleration versus time, trimmean acceleration versus time, quasi-steady three dimensional histograms, and prediction of quasi-steady levels at different locations. An introduction to Fourier transform theory and windowing is provided along with specific analysis techniques and data interpretations. The frequency domain analyses discussed are power spectral density versus frequency, cumulative root-mean-square acceleration versus frequency, root-mean-square acceleration versus frequency, one-third octave band root-mean-square acceleration versus frequency, and power spectral density versus frequency versus time (spectrogram). Instructions for accessing NASA Lewis Research Center accelerometer data and related information using the internet are provided.

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

In vitro evaluation of the sealing ability of three newly developed root canal sealers: A bacterial microleakage study

PubMed Central

Sobhani, Ehsan; Samadi-Kafil, Hossein; Pirzadeh, Ahmad; Jafari, Sanaz

2016-01-01

Background The purpose of this study was to compare the sealing ability of MTA Fillapex, Apatite Root Canal Sealer and AH26 sealers. Material and Methods The present in vitro study was carried out on 142 extracted single-rooted human mature teeth. The teeth were randomly divided into three experimental groups (n=44) and two control groups (n=5). Three root canal sealers were MTA Fillapex, Apatite Root Canal Sealer and AH26. The teeth in the control groups were either filled with no sealer or made completely impermeable. The root canals were prepared and obturated with gutta-percha and one of the sealers. The teeth were sterilized with ethylene oxide gas prior to the bacterial leakage assessment using Enterococcus faecalis. Leakage was evaluated every 24 hours for 90 days. Data were analyzed with descriptive statistical methods and chi-squared test. If the data were significant, a proper post hoc test was used. Statistical significance was set at P<0.05. Results The positive control specimens exhibited total bacterial penetration whilst the negative control specimens showed no evidence of bacterial penetration. At the end of the study, the analysis of microleakage with chi-squared test showed no significant differences between the experimental groups (P<0.05). The results of chi-squared test analyzing the pair-wise differences between the groups considering the numerical values for leakage day indicated the lowest leakage with AH26 and the highest with Apatite root sealer. Conclusions According to the results of the present study, sealing ability of AH26 was significantly higher than that of MTA Fillapex and Apatite Root Canal Sealer. Key words:Mineral Trioxide aggregate, root canal obturation, dental seal. PMID:27957271

A new method for determining the optimal lagged ensemble

PubMed Central

DelSole, T.; Tippett, M. K.; Pegion, K.

2017-01-01

Abstract We propose a general methodology for determining the lagged ensemble that minimizes the mean square forecast error. The MSE of a lagged ensemble is shown to depend only on a quantity called the cross‐lead error covariance matrix, which can be estimated from a short hindcast data set and parameterized in terms of analytic functions of time. The resulting parameterization allows the skill of forecasts to be evaluated for an arbitrary ensemble size and initialization frequency. Remarkably, the parameterization also can estimate the MSE of a burst ensemble simply by taking the limit of an infinitely small interval between initialization times. This methodology is applied to forecasts of the Madden Julian Oscillation (MJO) from version 2 of the Climate Forecast System version 2 (CFSv2). For leads greater than a week, little improvement is found in the MJO forecast skill when ensembles larger than 5 days are used or initializations greater than 4 times per day. We find that if the initialization frequency is too infrequent, important structures of the lagged error covariance matrix are lost. Lastly, we demonstrate that the forecast error at leads ≥10 days can be reduced by optimally weighting the lagged ensemble members. The weights are shown to depend only on the cross‐lead error covariance matrix. While the methodology developed here is applied to CFSv2, the technique can be easily adapted to other forecast systems. PMID:28580050

Advances of the smooth variable structure filter: square-root and two-pass formulations

NASA Astrophysics Data System (ADS)

Gadsden, S. Andrew; Lee, Andrew S.

2017-01-01

The smooth variable structure filter (SVSF) has seen significant development and research activity in recent years. It is based on sliding mode concepts, which utilize a switching gain that brings an inherent amount of stability to the estimation process. In an effort to improve upon the numerical stability of the SVSF, a square-root formulation is derived. The square-root SVSF is based on Potter's algorithm. The proposed formulation is computationally more efficient and reduces the risks of failure due to numerical instability. The new strategy is applied on target tracking scenarios for the purposes of state estimation, and the results are compared with the popular Kalman filter. In addition, the SVSF is reformulated to present a two-pass smoother based on the SVSF gain. The proposed method is applied on an aerospace flight surface actuator, and the results are compared with the Kalman-based two-pass smoother.

Dictionary Learning on the Manifold of Square Root Densities and Application to Reconstruction of Diffusion Propagator Fields*

PubMed Central

Sun, Jiaqi; Xie, Yuchen; Ye, Wenxing; Ho, Jeffrey; Entezari, Alireza; Blackband, Stephen J.

2013-01-01

In this paper, we present a novel dictionary learning framework for data lying on the manifold of square root densities and apply it to the reconstruction of diffusion propagator (DP) fields given a multi-shell diffusion MRI data set. Unlike most of the existing dictionary learning algorithms which rely on the assumption that the data points are vectors in some Euclidean space, our dictionary learning algorithm is designed to incorporate the intrinsic geometric structure of manifolds and performs better than traditional dictionary learning approaches when applied to data lying on the manifold of square root densities. Non-negativity as well as smoothness across the whole field of the reconstructed DPs is guaranteed in our approach. We demonstrate the advantage of our approach by comparing it with an existing dictionary based reconstruction method on synthetic and real multi-shell MRI data. PMID:24684004

Two Comments on Bond Angles

NASA Astrophysics Data System (ADS)

Glaister, P.

1997-09-01

Tetrahedral Bond Angle from Elementary Trigonometry The alternative approach of using the scalar (or dot) product of vectors enables the determination of the bond angle in a tetrahedral molecule in a simple way. There is, of course, an even more straightforward derivation suitable for students who are unfamiliar with vectors, or products thereof, but who do know some elementary trigonometry. The starting point is the figure showing triangle OAB. The point O is the center of a cube, and A and B are at opposite corners of a face of that cube in which fits a regular tetrahedron. The required bond angle alpha = AÔB; and using Pythagoras' theorem, AB = 2(square root 2) is the diagonal of a face of the cube. Hence from right-angled triangle OEB, tan(alpha/2) = (square root 2) and therefore alpha = 2tan-1(square root 2) is approx. 109° 28' (see Fig. 1).

Spiral tracing on a touchscreen is influenced by age, hand, implement, and friction.

PubMed

Heintz, Brittany D; Keenan, Kevin G

2018-01-01

Dexterity impairments are well documented in older adults, though it is unclear how these influence touchscreen manipulation. This study examined age-related differences while tracing on high- and low-friction touchscreens using the finger or stylus. 26 young and 24 older adults completed an Archimedes spiral tracing task on a touchscreen mounted on a force sensor. Root mean square error was calculated to quantify performance. Root mean square error increased by 29.9% for older vs. young adults using the fingertip, but was similar to young adults when using the stylus. Although other variables (e.g., touchscreen usage, sensation, and reaction time) differed between age groups, these variables were not related to increased error in older adults while using their fingertip. Root mean square error also increased on the low-friction surface for all subjects. These findings suggest that utilizing a stylus and increasing surface friction may improve touchscreen use in older adults.

Using Least Squares for Error Propagation

ERIC Educational Resources Information Center

Tellinghuisen, Joel

2015-01-01

The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…

Cross-Shore Exchange on Natural Beaches

DTIC Science & Technology

2014-09-01

87   Figure 2.   Wave conditions measured by the ADCP in 13 m water depth of (a) root- mean-square wave height Hrms...horizontal velocity, Umean, measured in the reference level, ∑Tsig,pulse T3−hour ∑Tsig,pulse T3−hour xi (e) local water depth, h, and (f) local root...mean-square wave height normalized by the local water depth, Hrms/h, measured by ADCPin (blue) and ADCPout (red) during the 3HRLTs. Colored lines

Flight Measurement of Wall-Pressure Fluctuations and Boundary-Layer Turbulence

NASA Technical Reports Server (NTRS)

Mull, Harold R.; Algranti, Joseph S.

1960-01-01

The results are presented for a flight test program using a fighter type jet aircraft flying at pressure altitudes of 10,000, 20,000, and 30,000 feet at Mach numbers from 0.3 to 0.8. Specially designed apparatus was used to measure and record the output of microphones and hot-wire anemometers mounted on the forward-fuselage section and wing of the airplane. Mean-velocity profiles in the boundary layers were obtained from total-pressure measurements. The ratio of the root-mean-square fluctuating wall pressure to the free-stream dynamic pressure is presented as a function of Reynolds number and Mach number. The longitudinal component of the turbulent-velocity fluctuations was measured, and the turbulence-intensity profiles are presented for the wing and forward-fuselage section. In general, the results are in agreement with wind-tunnel measurements which have been-reported in the literature. For example, the variation the square root of p(sup 2)/q times the square root of p(sup 2) is the root mean square of the wall-pressure fluctuation, and q is the free-stream dynamic pressure) with Reynolds number was found to be essentially constant for the forward-fuselage-section boundary layer, while variations at the wing station were probably unduly affected by the microphone diameter (5/8 in.), which was large compared with the boundary-layer thickness.

Narrowing the surface temperature range in CMIP5 simulations over the Arctic

NASA Astrophysics Data System (ADS)

Hao, Mingju; Huang, Jianbin; Luo, Yong; Chen, Xin; Lin, Yanluan; Zhao, Zongci; Xu, Ying

2018-05-01

Much uncertainty exists in reproducing Arctic temperature using different general circulation models (GCMs). Therefore, evaluating the performance of GCMs in reproducing Arctic temperature is critically important. In our study, 32 GCMs in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) during the period 1900-2005 are used, and several metrics, i.e., bias, correlation coefficient ( R), and root mean square error (RMSE), are applied. The Cowtan data set is adopted as the reference data. The results suggest that the GCMs used can reasonably reproduce the Arctic warming trend during the period 1900-2005, as observed in the observational data, whereas a large variation of inter-model differences exists in modeling the Arctic warming magnitude. With respect to the reference data, most GCMs have large cold biases, whereas others have weak warm biases. Additionally, based on statistical thresholds, the models MIROC-ESM, CSIRO-Mk3-6-0, HadGEM2-AO, and MIROC-ESM-CHEM (bias ≤ ±0.10 °C, R ≥ 0.50, and RMSE ≤ 0.60 °C) are identified as well-performing GCMs. The ensemble of the four best-performing GCMs (ES4), with bias, R, and RMSE values of -0.03 °C, 0.72, and 0.39 °C, respectively, performs better than the ensemble with all 32 members, with bias, R, and RMSE values of -0.04 °C, 0.64, and 0.43 °C, respectively. Finally, ES4 is used to produce projections for the next century under the scenarios of RCP2.6, RCP4.5, and RCP8.0. The uncertainty in the projected temperature is greater in the higher emissions scenarios. Additionally, the projected temperature in the cold half year has larger variations than that in the warm half year.

Global Genetic Response in a Cancer Cell: Self-Organized Coherent Expression Dynamics

PubMed Central

Tsuchiya, Masa; Hashimoto, Midori; Takenaka, Yoshiko; Motoike, Ikuko N.; Yoshikawa, Kenichi

2014-01-01

Understanding the basic mechanism of the spatio-temporal self-control of genome-wide gene expression engaged with the complex epigenetic molecular assembly is one of major challenges in current biological science. In this study, the genome-wide dynamical profile of gene expression was analyzed for MCF-7 breast cancer cells induced by two distinct ErbB receptor ligands: epidermal growth factor (EGF) and heregulin (HRG), which drive cell proliferation and differentiation, respectively. We focused our attention to elucidate how global genetic responses emerge and to decipher what is an underlying principle for dynamic self-control of genome-wide gene expression. The whole mRNA expression was classified into about a hundred groups according to the root mean square fluctuation (rmsf). These expression groups showed characteristic time-dependent correlations, indicating the existence of collective behaviors on the ensemble of genes with respect to mRNA expression and also to temporal changes in expression. All-or-none responses were observed for HRG and EGF (biphasic statistics) at around 10–20 min. The emergence of time-dependent collective behaviors of expression occurred through bifurcation of a coherent expression state (CES). In the ensemble of mRNA expression, the self-organized CESs reveals distinct characteristic expression domains for biphasic statistics, which exhibits notably the presence of criticality in the expression profile as a route for genomic transition. In time-dependent changes in the expression domains, the dynamics of CES reveals that the temporal development of the characteristic domains is characterized as autonomous bistable switch, which exhibits dynamic criticality (the temporal development of criticality) in the genome-wide coherent expression dynamics. It is expected that elucidation of the biophysical origin for such critical behavior sheds light on the underlying mechanism of the control of whole genome. PMID:24831017

The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

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

Wilczak, James M.; Finley, Cathy; Freedman, Jeff

The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collectionmore » of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.« less

Building alternate protein structures using the elastic network model.

PubMed

Yang, Qingyi; Sharp, Kim A

2009-02-15

We describe a method for efficiently generating ensembles of alternate, all-atom protein structures that (a) differ significantly from the starting structure, (b) have good stereochemistry (bonded geometry), and (c) have good steric properties (absence of atomic overlap). The method uses reconstruction from a series of backbone framework structures that are obtained from a modified elastic network model (ENM) by perturbation along low-frequency normal modes. To ensure good quality backbone frameworks, the single force parameter ENM is modified by introducing two more force parameters to characterize the interaction between the consecutive carbon alphas and those within the same secondary structure domain. The relative stiffness of the three parameters is parameterized to reproduce B-factors, while maintaining good bonded geometry. After parameterization, violations of experimental Calpha-Calpha distances and Calpha-Calpha-Calpha pseudo angles along the backbone are reduced to less than 1%. Simultaneously, the average B-factor correlation coefficient improves to R = 0.77. Two applications illustrate the potential of the approach. (1) 102,051 protein backbones spanning a conformational space of 15 A root mean square deviation were generated from 148 nonredundant proteins in the PDB database, and all-atom models with minimal bonded and nonbonded violations were produced from this ensemble of backbone structures using the SCWRL side chain building program. (2) Improved backbone templates for homology modeling. Fifteen query sequences were each modeled on two targets. For each of the 30 target frameworks, dozens of improved templates could be produced In all cases, improved full atom homology models resulted, of which 50% could be identified blind using the D-Fire statistical potential. (c) 2008 Wiley-Liss, Inc.

Hydrologic data assimilation with a hillslope-scale-resolving model and L band radar observations: Synthetic experiments with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara

2012-08-01

Soil moisture information is critical for applications like landslide susceptibility analysis and military trafficability assessment. Existing technologies cannot observe soil moisture at spatial scales of hillslopes (e.g., 100 to 102 m) and over large areas (e.g., 102 to 105 km2) with sufficiently high temporal coverage (e.g., days). Physics-based hydrologic models can simulate soil moisture at the necessary spatial and temporal scales, albeit with error. We develop and test a data assimilation framework based on the ensemble Kalman filter for constraining uncertain simulated high-resolution soil moisture fields to anticipated remote sensing products, specifically NASA's Soil Moisture Active-Passive (SMAP) mission, which will provide global L band microwave observation approximately every 2-3 days. The framework directly assimilates SMAP synthetic 3 km radar backscatter observations to update hillslope-scale bare soil moisture estimates from a physics-based model. Downscaling from 3 km observations to hillslope scales is achieved through the data assimilation algorithm. Assimilation reduces bias in near-surface soil moisture (e.g., top 10 cm) by approximately 0.05 m3/m3and expected root-mean-square errors by at least 60% in much of the watershed, relative to an open loop simulation. However, near-surface moisture estimates in channel and valley bottoms do not improve, and estimates of profile-integrated moisture throughout the watershed do not substantially improve. We discuss the implications of this work, focusing on ongoing efforts to improve soil moisture estimation in the entire soil profile through joint assimilation of other satellite (e.g., vegetation) and in situ soil moisture measurements.

Assimilating MODIS-based albedo and snow cover fraction into the Common Land Model to improve snow depth simulation with direct insertion and deterministic ensemble Kalman filter methods

NASA Astrophysics Data System (ADS)

Xu, Jianhui; Shu, Hong

2014-09-01

This study assesses the analysis performance of assimilating the Moderate Resolution Imaging Spectroradiometer (MODIS)-based albedo and snow cover fraction (SCF) separately or jointly into the physically based Common Land Model (CoLM). A direct insertion method (DI) is proposed to assimilate the black and white-sky albedos into the CoLM. The MODIS-based albedo is calculated with the MODIS bidirectional reflectance distribution function (BRDF) model parameters product (MCD43B1) and the solar zenith angle as estimated in the CoLM for each time step. Meanwhile, the MODIS SCF (MOD10A1) is assimilated into the CoLM using the deterministic ensemble Kalman filter (DEnKF) method. A new DEnKF-albedo assimilation scheme for integrating the DI and DEnKF assimilation schemes is proposed. Our assimilation results are validated against in situ snow depth observations from November 2008 to March 2009 at five sites in the Altay region of China. The experimental results show that all three data assimilation schemes can improve snow depth simulations. But overall, the DEnKF-albedo assimilation shows the best analysis performance as it significantly reduces the bias and root-mean-square error (RMSE) during the snow accumulation and ablation periods at all sites except for the Fuyun site. The SCF assimilation via DEnKF produces better results than the albedo assimilation via DI, implying that the albedo assimilation that indirectly updates the snow depth state variable is less efficient than the direct SCF assimilation. For the Fuyun site, the DEnKF-albedo scheme tends to overestimate the snow depth accumulation with the maximum bias and RMSE values because of the large positive innovation (observation minus forecast).

The fast-folding HP35 double mutant has a substantially reduced primary folding free energy barrier

NASA Astrophysics Data System (ADS)

Lei, Hongxing; Deng, Xiaojian; Wang, Zhixiang; Duan, Yong

2008-10-01

The LYS24/29NLE double mutant of villin headpiece subdomain (HP35) is the fastest folding protein known so far with a folding time constant of 0.6μs. In this work, the folding mechanism of the mutant has been investigated by both conventional and replica exchange molecular dynamics (CMD and REMD) simulations with AMBER FF03 force field and a generalized-Born solvation model. Direct comparison to the ab initio folding of the wild type HP35 enabled a close examination on the mutational effect on the folding process. The mutant folded to the native state, as demonstrated by the 0.50Å Cα-root mean square deviation (RMSD) sampled in both CMD and REMD simulations and the high population of the folded conformation compared with the denatured conformations. Consistent with experiments, the significantly reduced primary folding free energy barrier makes the mutant closer to a downhill folder than the wild type HP35 that directly leads to the faster transition and higher melting temperature. However, unlike the proposed downhill folding which envisages a smooth shift between unfolded and folded states without transition barrier, we observed a well-defined folding transition that was consistent with experiments. Further examination of the secondary structures revealed that the two mutated residues have higher intrinsic helical preference that facilitated the formation of both helix III and the intermediate state which contains the folded segment helix II/III. Other factors contributing to the faster folding include the more favorable electrostatic interactions in the transition state with the removal of the charged NH3+ groups from LYS. In addition, both transition state ensemble and denatured state ensemble are shifted in the mutant.

Investigation of flow and transport processes at the MADE site using ensemble Kalman filter

USGS Publications Warehouse

Liu, Gaisheng; Chen, Y.; Zhang, Dongxiao

2008-01-01

In this work the ensemble Kalman filter (EnKF) is applied to investigate the flow and transport processes at the macro-dispersion experiment (MADE) site in Columbus, MS. The EnKF is a sequential data assimilation approach that adjusts the unknown model parameter values based on the observed data with time. The classic advection-dispersion (AD) and the dual-domain mass transfer (DDMT) models are employed to analyze the tritium plume during the second MADE tracer experiment. The hydraulic conductivity (K), longitudinal dispersivity in the AD model, and mass transfer rate coefficient and mobile porosity ratio in the DDMT model, are estimated in this investigation. Because of its sequential feature, the EnKF allows for the temporal scaling of transport parameters during the tritium concentration analysis. Inverse simulation results indicate that for the AD model to reproduce the extensive spatial spreading of the tritium observed in the field, the K in the downgradient area needs to be increased significantly. The estimated K in the AD model becomes an order of magnitude higher than the in situ flowmeter measurements over a large portion of media. On the other hand, the DDMT model gives an estimation of K that is much more comparable with the flowmeter values. In addition, the simulated concentrations by the DDMT model show a better agreement with the observed values. The root mean square (RMS) between the observed and simulated tritium plumes is 0.77 for the AD model and 0.45 for the DDMT model at 328 days. Unlike the AD model, which gives inconsistent K estimates at different times, the DDMT model is able to invert the K values that consistently reproduce the observed tritium concentrations through all times. ?? 2008 Elsevier Ltd. All rights reserved.

Evaluating Snow Data Assimilation Framework for Streamflow Forecasting Applications Using Hindcast Verification

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2012-12-01

Snow water equivalent (SWE) estimation is a key factor in producing reliable streamflow simulations and forecasts in snow dominated areas. However, measuring or predicting SWE has significant uncertainty. Sequential data assimilation, which updates states using both observed and modeled data based on error estimation, has been shown to reduce streamflow simulation errors but has had limited testing for forecasting applications. In the current study, a snow data assimilation framework integrated with the National Weather System River Forecasting System (NWSRFS) is evaluated for use in ensemble streamflow prediction (ESP). Seasonal water supply ESP hindcasts are generated for the North Fork of the American River Basin (NFARB) in northern California. Parameter sets from the California Nevada River Forecast Center (CNRFC), the Differential Evolution Adaptive Metropolis (DREAM) algorithm and the Multistep Automated Calibration Scheme (MACS) are tested both with and without sequential data assimilation. The traditional ESP method considers uncertainty in future climate conditions using historical temperature and precipitation time series to generate future streamflow scenarios conditioned on the current basin state. We include data uncertainty analysis in the forecasting framework through the DREAM-based parameter set which is part of a recently developed Integrated Uncertainty and Ensemble-based data Assimilation framework (ICEA). Extensive verification of all tested approaches is undertaken using traditional forecast verification measures, including root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), volumetric bias, joint distribution, rank probability score (RPS), and discrimination and reliability plots. In comparison to the RFC parameters, the DREAM and MACS sets show significant improvement in volumetric bias in flow. Use of assimilation improves hindcasts of higher flows but does not significantly improve performance in the mid flow and low flow categories.

State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements

PubMed Central

Mollazadeh, Mohsen; Davidson, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

2013-01-01

The performance of brain-machine interfaces (BMIs) that continuously control upper limb neuroprostheses may benefit from distinguishing periods of posture and movement so as to prevent inappropriate movement of the prosthesis. Few studies, however, have investigated how decoding behavioral states and detecting the transitions between posture and movement could be used autonomously to trigger a kinematic decoder. We recorded simultaneous neuronal ensemble and local field potential (LFP) activity from microelectrode arrays in primary motor cortex (M1) and dorsal (PMd) and ventral (PMv) premotor areas of two male rhesus monkeys performing a center-out reach-and-grasp task, while upper limb kinematics were tracked with a motion capture system with markers on the dorsal aspect of the forearm, hand, and fingers. A state decoder was trained to distinguish four behavioral states (baseline, reaction, movement, hold), while a kinematic decoder was trained to continuously decode hand end point position and 18 joint angles of the wrist and fingers. LFP amplitude most accurately predicted transition into the reaction (62%) and movement (73%) states, while spikes most accurately decoded arm, hand, and finger kinematics during movement. Using an LFP-based state decoder to trigger a spike-based kinematic decoder [r = 0.72, root mean squared error (RMSE) = 0.15] significantly improved decoding of reach-to-grasp movements from baseline to final hold, compared with either a spike-based state decoder combined with a spike-based kinematic decoder (r = 0.70, RMSE = 0.17) or a spike-based kinematic decoder alone (r = 0.67, RMSE = 0.17). Combining LFP-based state decoding with spike-based kinematic decoding may be a valuable step toward the realization of BMI control of a multifingered neuroprosthesis performing dexterous manipulation. PMID:23536714

Improving Flood Prediction By the Assimilation of Satellite Soil Moisture in Poorly Monitored Catchments.

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C. D.; Ryu, D.; Western, A. W.; Crow, W. T.; Su, C. H.; Robertson, D. E.

2014-12-01

Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particular, is the assimilation of satellite soil moisture (SM-DA) into rainfall-runoff models. The rationale is that satellite soil moisture (SSM) can be used to correct model soil water states, enabling more accurate prediction of catchment response to precipitation and thus better streamflow. However, there is still no consensus on the most effective SM-DA scheme and how this might depend on catchment scale, climate characteristics, runoff mechanisms, model and SSM products used, etc. In this work, an operational SM-DA scheme was set up in the poorly monitored, large (>40,000 km2), semi-arid Warrego catchment situated in eastern Australia. We assimilated passive and active SSM products into the probability distributed model (PDM) using an ensemble Kalman filter. We explored factors influencing the SM-DA framework, including relatively new techniques to remove model-observation bias, estimate observation errors and represent model errors. Furthermore, we explored the advantages of accounting for the spatial distribution of forcing and channel routing processes within the catchment by implementing and comparing lumped and semi-distributed model setups. Flood prediction is improved by SM-DA (Figure), with a 30% reduction of the average root-mean-squared difference of the ensemble prediction, a 20% reduction of the false alarm ratio and a 40% increase of the ensemble mean Nash-Sutcliffe efficiency. SM-DA skill does not significantly change with different observation error assumptions, but the skill strongly depends on the observational bias correction technique used, and more importantly, on the performance of the open-loop model before assimilation. Our findings imply that proper pre-processing of SSM is important for the efficacy of the SM-DA and assimilation performance is critically affected by the quality of model calibration. We therefore recommend focusing efforts on these two factors, while further evaluating the trade-offs between model complexity and data availability.

A regional neural network model for predicting mean daily river water temperature

USGS Publications Warehouse

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate and land use changes, thereby providing information that is valuable to management of river ecosystems and biota such as brook trout.

Prediction of lung cancer patient survival via supervised machine learning classification techniques.

PubMed

Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

2017-12-01

Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time with the ultimate goal to inform patient care decisions, and that the performance of these techniques with this particular dataset may be on par with that of classical methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Particle-Based Simulations of Microscopic Thermal Properties of Confined Systems

DTIC Science & Technology

2014-11-01

velocity versus electric field in gallium arsenide (GaAs) computed with the original CMC table structure (squares) at temperature T=150K, and the new...computer-aided design Cellular Monte Carlo Ensemble Monte Carlo gallium arsenide Heat Transport Equation DARPA Defense Advanced Research Projects

Dem Generation with WORLDVIEW-2 Images

NASA Astrophysics Data System (ADS)

Büyüksalih, G.; Baz, I.; Alkan, M.; Jacobsen, K.

2012-07-01

For planning purposes 42 km coast line of the Black Sea, starting at the Bosporus going in West direction, with a width of approximately 5 km, was imaged by WorldView-2. Three stereo scenes have been oriented at first by 3D-affine transformation and later by bias corrected RPC solution. The result is nearly the same, but it is limited by identification of the control points in the images. Nevertheless after blunder elimination by data snooping root mean square discrepancies below 1 pixel have been reached. The root mean square discrepancy at control point height reached 0.5 m up to 1.3 m with a base to height relation between 1:1.26 and 1:1.80. Digital Surface models (DSM) with 4 m spacing have been generated by least squares matching with region growing, supported by image pyramids. A higher percentage of the mountainous area is covered by forest, requiring the approximation based on image pyramids. In the forest area the approximation just by region growing leads to larger gaps in the DSM. Caused by the good image quality of WorldView-2 the correlation coefficients reached by least squares matching are high and even in most forest areas a satisfying density of accepted points was reached. Two stereo models have an overlapping area of 1.6 km times 6.7 km allowing an accuracy evaluation. Small, but nevertheless significant differences in scene orientation have been eliminated by least squares shift of both overlapping height models to each other. The root mean square differences of both independent DSM are 1.06m or as a function of terrain inclination 0.74 m + 0.55 m  tangent (slope). The terrain inclination in the average is 7° with 12% exceeding 17°. The frequency distribution of height discrepancies is not far away from normal distribution, but as usual, larger discrepancies are more often available as corresponding to normal distribution. This also can be seen by the normalized medium absolute deviation (NMAS) related to 68% probability level of 0.83m being significant smaller as the root mean square differences. Nevertheless the results indicate a standard deviation of the single height models of 0.75 m or 0.52 m + 0.39* tangent (slope), corresponding to approximately 0.6 pixels for the x-parallax in flat terrain, being very satisfying for the available land cover. An interpolation over 10 m enlarged the root mean square differences of both height models nearly by 50%.

Anomalous Impact in Reaction-Diffusion Financial Models

NASA Astrophysics Data System (ADS)

Mastromatteo, I.; Tóth, B.; Bouchaud, J.-P.

2014-12-01

We generalize the reaction-diffusion model A +B → /0 in order to study the impact of an excess of A (or B ) at the reaction front. We provide an exact solution of the model, which shows that the linear response breaks down: the average displacement of the reaction front grows as the square root of the imbalance. We argue that this model provides a highly simplified but generic framework to understand the square-root impact of large orders in financial markets.

Identified particle distributions in pp and Au+Au collisions at square root of (sNN)=200 GeV.

PubMed

Adams, J; Adler, C; Aggarwal, M M; Ahammed, Z; Amonett, J; Anderson, B D; Anderson, M; Arkhipkin, D; Averichev, G S; Badyal, S K; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Bekele, S; Belaga, V V; Bellwied, R; Berger, J; Bezverkhny, B I; Bhardwaj, S; Bhaskar, P; Bhati, A K; Bichsel, H; Billmeier, A; Bland, L C; Blyth, C O; Bonner, B E; Botje, M; Boucham, A; Brandin, A; Bravar, A; Cadman, R V; Cai, X Z; Caines, H; Calderón de la Barca Sánchez, M; Carroll, J; Castillo, J; Castro, M; Cebra, D; Chaloupka, P; Chattopadhyay, S; Chen, H F; Chen, Y; Chernenko, S P; Cherney, M; Chikanian, A; Choi, B; Christie, W; Coffin, J P; Cormier, T M; Cramer, J G; Crawford, H J; Das, D; Das, S; Derevschikov, A A; Didenko, L; Dietel, T; Dong, X; Draper, J E; Du, F; Dubey, A K; Dunin, V B; Dunlop, J C; Dutta Majumdar, M R; Eckardt, V; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Estienne, M; Fachini, P; Faine, V; Faivre, J; Fatemi, R; Filimonov, K; Filip, P; Finch, E; Fisyak, Y; Flierl, D; Foley, K J; Fu, J; Gagliardi, C A; Ganti, M S; Gutierrez, T D; Gagunashvili, N; Gans, J; Gaudichet, L; Germain, M; Geurts, F; Ghazikhanian, V; Ghosh, P; Gonzalez, J E; Grachov, O; Grigoriev, V; Gronstal, S; Grosnick, D; Guedon, M; Guertin, S M; Gupta, A; Gushin, E; Hallman, T J; Hardtke, D; Harris, J W; Heinz, M; Henry, T W; Heppelmann, S; Herston, T; Hippolyte, B; Hirsch, A; Hjort, E; Hoffmann, G W; Horsley, M; Huang, H Z; Huang, S L; Humanic, T J; Igo, G; Ishihara, A; Jacobs, P; Jacobs, W W; Janik, M; Johnson, I; Jones, P G; Judd, E G; Kabana, S; Kaneta, M; Kaplan, M; Keane, D; Kiryluk, J; Kisiel, A; Klay, J; Klein, S R; Klyachko, A; Koetke, D D; Kollegger, T; Konstantinov, A S; Kopytine, M; Kotchenda, L; Kovalenko, A D; Kramer, M; Kravtsov, P; Krueger, K; Kuhn, C; Kulikov, A I; Kumar, A; Kunde, G J; Kunz, C L; Kutuev, R Kh; Kuznetsov, A A; Lamont, M A C; Landgraf, J M; Lange, S; Lansdell, C P; Lasiuk, B; Laue, F; Lauret, J; Lebedev, A; Lednický, R; Leontiev, V M; LeVine, M J; Li, C; Li, Q; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, L; Liu, Z; Liu, Q J; Ljubicic, T; Llope, W J; Long, H; Longacre, R S; Lopez-Noriega, M; Love, W A; Ludlam, T; Lynn, D; Ma, J; Ma, Y G; Magestro, D; Mahajan, S; Mangotra, L K; Mahapatra, D P; Majka, R; Manweiler, R; Margetis, S; Markert, C; Martin, L; Marx, J; Matis, H S; Matulenko, Yu A; McShane, T S; Meissner, F; Melnick, Yu; Meschanin, A; Messer, M; Miller, M L; Milosevich, Z; Minaev, N G; Mironov, C; Mishra, D; Mitchell, J; Mohanty, B; Molnar, L; Moore, C F; Mora-Corral, M J; Morozov, V; de Moura, M M; Munhoz, M G; Nandi, B K; Nayak, S K; Nayak, T K; Nelson, J M; Nevski, P; Nikitin, V A; Nogach, L V; Norman, B; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Paic, G; Pandey, S U; Pal, S K; Panebratsev, Y; Panitkin, S Y; Pavlinov, A I; Pawlak, T; Perevoztchikov, V; Peryt, W; Petrov, V A; Phatak, S C; Picha, R; Planinic, M; Pluta, J; Porile, N; Porter, J; Poskanzer, A M; Potekhin, M; Potrebenikova, E; Potukuchi, B V K S; Prindle, D; Pruneau, C; Putschke, J; Rai, G; Rakness, G; Raniwala, R; Raniwala, S; Ravel, O; Ray, R L; Razin, S V; Reichhold, D; Reid, J G; Renault, G; Retiere, F; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevski, O V; Romero, J L; Rose, A; Roy, C; Ruan, L J; Sahoo, R; Sakrejda, I; Salur, S; Sandweiss, J; Savin, I; Schambach, J; Scharenberg, R P; Schmitz, N; Schroeder, L S; Schweda, K; Seger, J; Seliverstov, D; Seyboth, P; Shahaliev, E; Shao, M; Sharma, M; Shestermanov, K E; Shimanskii, S S; Singaraju, R N; Simon, F; Skoro, G; Smirnov, N; Snellings, R; Sood, G; Sorensen, P; Sowinski, J; Spinka, H M; Srivastava, B; Stanislaus, S; Stock, R; Stolpovsky, A; Strikhanov, M; Stringfellow, B; Struck, C; Suaide, A A P; Sugarbaker, E; Suire, C; Sumbera, M; Surrow, B; Symons, T J M; de Toledo, A Szanto; Szarwas, P; Tai, A; Takahashi, J; Tang, A H; Thein, D; Thomas, J H; Tikhomirov, V; Tokarev, M; Tonjes, M B; Trainor, T A; Trentalange, S; Tribble, R E; Trivedi, M D; Trofimov, V; Tsai, O; Ullrich, T; Underwood, D G; Van Buren, G; VanderMolen, A M; Vasiliev, A N; Vasiliev, M; Vigdor, S E; Viyogi, Y P; Voloshin, S A; Waggoner, W; Wang, F; Wang, G; Wang, X L; Wang, Z M; Ward, H; Watson, J W; Wells, R; Westfall, G D; Whitten, C; Wieman, H; Willson, R; Wissink, S W; Witt, R; Wood, J; Wu, J; Xu, N; Xu, Z; Xu, Z Z; Yakutin, A E; Yamamoto, E; Yang, J; Yepes, P; Yurevich, V I; Zanevski, Y V; Zborovský, I; Zhang, H; Zhang, H Y; Zhang, W M; Zhang, Z P; Zołnierczuk, P A; Zoulkarneev, R; Zoulkarneeva, J; Zubarev, A N

2004-03-19

Transverse mass and rapidity distributions for charged pions, charged kaons, protons, and antiprotons are reported for square root of [sNN]=200 GeV pp and Au+Au collisions at Relativistic Heary Ion Collider (RHIC). Chemical and kinetic equilibrium model fits to our data reveal strong radial flow and long duration from chemical to kinetic freeze-out in central Au+Au collisions. The chemical freeze-out temperature appears to be independent of initial conditions at RHIC energies.

Ponce de Leon Inlet, FL: An Integrated Hydrodynamic and Morphologic Assessment of Design Alternatives using the U.S. Army Corps of Engineers’ Coastal Modeling System

DTIC Science & Technology

2009-07-01

produce a configuration parallel to, and longitudinally aligned with, the north jetty, but the rebuilt structure essentially cuts off the inner south...Normalized Root Mean Square Deviation PMAB Prototype Measurement and Analysis Branch RGB Red, Green, Blue RMSD Root Mean Square Deviation SHOALS...intended height of the rubble mound off the seafloor (submergent). The latter method is used for a variety of structural assignments besides a

Simple Forest Canopy Thermal Exitance Model

NASA Technical Reports Server (NTRS)

Smith J. A.; Goltz, S. M.

1999-01-01

We describe a model to calculate brightness temperature and surface energy balance for a forest canopy system. The model is an extension of an earlier vegetation only model by inclusion of a simple soil layer. The root mean square error in brightness temperature for a dense forest canopy was 2.5 C. Surface energy balance predictions were also in good agreement. The corresponding root mean square errors for net radiation, latent, and sensible heat were 38.9, 30.7, and 41.4 W/sq m respectively.

A higher-order split-step Fourier parabolic-equation sound propagation solution scheme.

PubMed

Lin, Ying-Tsong; Duda, Timothy F

2012-08-01

A three-dimensional Cartesian parabolic-equation model with a higher-order approximation to the square-root Helmholtz operator is presented for simulating underwater sound propagation in ocean waveguides. The higher-order approximation includes cross terms with the free-space square-root Helmholtz operator and the medium phase speed anomaly. It can be implemented with a split-step Fourier algorithm to solve for sound pressure in the model. Two idealized ocean waveguide examples are presented to demonstrate the performance of this numerical technique.

An Efficient Metadynamics-Based Protocol To Model the Binding Affinity and the Transition State Ensemble of G-Protein-Coupled Receptor Ligands.

PubMed

Saleh, Noureldin; Ibrahim, Passainte; Saladino, Giorgio; Gervasio, Francesco Luigi; Clark, Timothy

2017-05-22

A generally applicable metadynamics scheme for predicting the free energy profile of ligand binding to G-protein-coupled receptors (GPCRs) is described. A common and effective collective variable (CV) has been defined using the ideally placed and highly conserved Trp6.48 as a reference point for ligand-GPCR distance measurement and the common orientation of GPCRs in the cell membrane. Using this single CV together with well-tempered multiple-walker metadynamics with a funnel-like boundary allows an efficient exploration of the entire ligand binding path from the extracellular medium to the orthosteric binding site, including vestibule and intermediate sites. The protocol can be used with X-ray structures or high-quality homology models (based on a high-quality template and after thorough refinement) for the receptor and is universally applicable to agonists, antagonists, and partial and reverse agonists. The root-mean-square error (RMSE) in predicted binding free energies for 12 diverse ligands in five receptors (a total of 23 data points) is surprisingly small (less than 1 kcal mol -1 ). The RMSEs for simulations that use receptor X-ray structures and homology models are very similar.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-02-16

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less

Gaussian Elimination-Based Novel Canonical Correlation Analysis Method for EEG Motion Artifact Removal.

PubMed

Roy, Vandana; Shukla, Shailja; Shukla, Piyush Kumar; Rawat, Paresh

2017-01-01

The motion generated at the capturing time of electro-encephalography (EEG) signal leads to the artifacts, which may reduce the quality of obtained information. Existing artifact removal methods use canonical correlation analysis (CCA) for removing artifacts along with ensemble empirical mode decomposition (EEMD) and wavelet transform (WT). A new approach is proposed to further analyse and improve the filtering performance and reduce the filter computation time under highly noisy environment. This new approach of CCA is based on Gaussian elimination method which is used for calculating the correlation coefficients using backslash operation and is designed for EEG signal motion artifact removal. Gaussian elimination is used for solving linear equation to calculate Eigen values which reduces the computation cost of the CCA method. This novel proposed method is tested against currently available artifact removal techniques using EEMD-CCA and wavelet transform. The performance is tested on synthetic and real EEG signal data. The proposed artifact removal technique is evaluated using efficiency matrices such as del signal to noise ratio (DSNR), lambda ( λ ), root mean square error (RMSE), elapsed time, and ROC parameters. The results indicate suitablity of the proposed algorithm for use as a supplement to algorithms currently in use.

Coupling of c  =  ‑2 and c =\\frac{1}{2} and c  =  0 conformal field theories: the geometrical point of view

NASA Astrophysics Data System (ADS)

Najafi, M. N.

2018-04-01

The coupling of the c  =  ‑2, c=\\frac{1}{2} and c  =  0 conformal field theories are numerically considered in this paper. As the prototypes of the couplings, (c_1=-2)\\oplus (c_2=0) and (c_1=-2)\\oplus (c_2=\\frac{1}{2}) , we consider the Bak–Tang–Weisenfeld (BTW) model on the 2D square critical site-percolation and the BTW model on Ising-correlated percolation lattices respectively. Some geometrical techniques are used to characterize the presumable conformal symmetry of the resultant systems. Based on the numerical analysis of the diffusivity parameter (κ) in the Schramm–Loewner evolution (SLE) theory we propose that the algebra of the central charges of the coupled models is closed. This result is based on the analysis of the conformal loop ensemble (CLE) analysis. The diffusivity parameter in each case is obtained by calculating the fractal dimension of loops (and the corresponding exponent of mean-square root distance), the direct SLE mapping method, the left passage probability and the winding angle analysis. More precisely we numerically show that the coupling (c_1=-2)\\oplus (c_2=\\frac{1}{2}) results to 2D self-avoiding walk (SAW) fixed point corresponding to c  =  0 conformal field theory, whereas the coupling (c_1=-2)\\oplus (c_2=0) results to the 2D critical Ising fixed point corresponding to the c=\\frac{1}{2} conformal field theory.

Comparison of Nonlinear Filtering Techniques for Lunar Surface Roving Navigation

NASA Technical Reports Server (NTRS)

Kimber, Lemon; Welch, Bryan W.

2008-01-01

Leading up to the Apollo missions the Extended Kalman Filter, a modified version of the Kalman Filter, was developed to estimate the state of a nonlinear system. Throughout the Apollo missions, Potter's Square Root Filter was used for lunar navigation. Now that NASA is returning to the Moon, the filters used during the Apollo missions must be compared to the filters that have been developed since that time, the Bierman-Thornton Filter (UD) and the Unscented Kalman Filter (UKF). The UD Filter involves factoring the covariance matrix into UDUT and has similar accuracy to the Square Root Filter; however it requires less computation time. Conversely, the UKF, which uses sigma points, is much more computationally intensive than any of the filters; however it produces the most accurate results. The Extended Kalman Filter, Potter's Square Root Filter, the Bierman-Thornton UD Filter, and the Unscented Kalman Filter each prove to be the most accurate filter depending on the specific conditions of the navigation system.

Transverse-momentum and pseudorapidity distributions of charged hadrons in pp collisions at square root of s = 7 TeV.

PubMed

Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Bergauer, T; Dragicevic, M; Erö, J; Fabjan, C; Friedl, M; Frühwirth, R; Ghete, V M; Hammer, J; Hänsel, S; Hoch, M; Hörmann, N; Hrubec, J; Jeitler, M; Kasieczka, G; Kiesenhofer, W; Krammer, M; Liko, D; Mikulec, I; Pernicka, M; Rohringer, H; Schöfbeck, R; Strauss, J; Taurok, A; Teischinger, F; Waltenberger, W; Walzel, G; Widl, E; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Benucci, L; Ceard, L; De Wolf, E A; Hashemi, M; Janssen, X; Maes, T; Mucibello, L; Ochesanu, S; Roland, B; Rougny, R; Selvaggi, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Adler, V; Beauceron, S; Blyweert, S; D'Hondt, J; Devroede, O; Kalogeropoulos, A; Maes, J; Maes, M; Tavernier, S; Van Doninck, W; Van Mulders, P; Villella, I; Chabert, E C; Charaf, O; Clerbaux, B; De Lentdecker, G; Dero, V; Gay, A P R; Hammad, G H; Marage, P E; Vander Velde, C; Vanlaer, P; Wickens, J; Costantini, S; Grunewald, M; Klein, B; Marinov, A; Ryckbosch, D; Thyssen, F; Tytgat, M; Vanelderen, L; Verwilligen, P; Walsh, S; Zaganidis, N; Basegmez, S; Bruno, G; Caudron, J; De Favereau De Jeneret, J; Delaere, C; Demin, P; Favart, D; Giammanco, A; Grégoire, G; Hollar, J; Lemaitre, V; Militaru, O; Ovyn, S; Pagano, D; Pin, A; Piotrzkowski, K; Quertenmont, L; Schul, N; Beliy, N; Caebergs, T; Daubie, E; Alves, G A; Pol, M E; Souza, M H G; Carvalho, W; Da Costa, E M; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Mundim, L; Oguri, V; Santoro, A; Silva Do Amaral, S M; Sznajder, A; Torres Da Silva De Araujo, F; Dias, F A; Dias, M A F; Fernandez Perez Tomei, T R; Gregores, E M; Marinho, F; Novaes, S F; Padula, Sandra S; Darmenov, N; Dimitrov, L; Genchev, V; Iaydjiev, P; Piperov, S; Stoykova, S; Sultanov, G; Trayanov, R; Vankov, I; Dyulendarova, M; Hadjiiska, R; Kozhuharov, V; Litov, L; Marinova, E; Mateev, M; Pavlov, B; Petkov, P; Bian, J G; Chen, G M; Chen, H S; Jiang, C H; Liang, D; Liang, S; Wang, J; Wang, J; Wang, X; Wang, Z; Yang, M; Zang, J; Zhang, Z; Ban, Y; Guo, S; Hu, Z; Mao, Y; Qian, S J; Teng, H; Zhu, B; Cabrera, A; Carrillo Montoya, C A; Gomez Moreno, B; Ocampo Rios, A A; Osorio Oliveros, A F; Sanabria, J C; Godinovic, N; Lelas, D; Lelas, K; Plestina, R; Polic, D; Puljak, I; Antunovic, Z; Dzelalija, M; Brigljevic, V; Duric, S; Kadija, K; Morovic, S; Attikis, A; Fereos, R; Galanti, M; Mousa, J; Nicolaou, C; Papadakis, A; Ptochos, F; Razis, P A; Rykaczewski, H; Tsiakkouri, D; Zinonos, Z; Mahmoud, M; Hektor, A; Kadastik, M; Kannike, K; Müntel, M; Raidal, M; Rebane, L; Azzolini, V; Eerola, P; Czellar, S; Härkönen, J; Heikkinen, A; Karimäki, V; Kinnunen, R; Klem, J; Kortelainen, M J; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Tuominen, E; Tuominiemi, J; Tuovinen, E; Ungaro, D; Wendland, L; Banzuzi, K; Korpela, A; Tuuva, T; Sillou, D; Besancon, M; Dejardin, M; Denegri, D; Descamps, J; Fabbro, B; Faure, J L; Ferri, F; Ganjour, S; Gentit, F X; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; 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Goncharov, M; Hahn, K A; Harris, P; Kim, Y; Klute, M; Lee, Y-J; Li, W; Loizides, C; Luckey, P D; Ma, T; Nahn, S; Paus, C; Roland, C; Roland, G; Rudolph, M; Stephans, G S F; Sumorok, K; Sung, K; Wenger, E A; Wyslouch, B; Xie, S; Yilmaz, Y; Yoon, A S; Zanetti, M; Cole, P; Cooper, S I; Cushman, P; Dahmes, B; De Benedetti, A; Dudero, P R; Franzoni, G; Haupt, J; Klapoetke, K; Kubota, Y; Mans, J; Petyt, D; Rekovic, V; Rusack, R; Sasseville, M; Singovsky, A; Cremaldi, L M; Godang, R; Kroeger, R; Perera, L; Rahmat, R; Sanders, D A; Sonnek, P; Summers, D; Bloom, K; Bose, S; Butt, J; Claes, D R; Dominguez, A; Eads, M; Keller, J; Kelly, T; Kravchenko, I; Lazo-Flores, J; Lundstedt, C; Malbouisson, H; Malik, S; Snow, G R; Baur, U; Iashvili, I; Kharchilava, A; Kumar, A; Smith, K; Strang, M; Zennamo, J; Alverson, G; Barberis, E; Baumgartel, D; Boeriu, O; Reucroft, S; Swain, J; Wood, D; Zhang, J; Anastassov, A; Kubik, A; Ofierzynski, R A; Pozdnyakov, A; Schmitt, M; Stoynev, S; Velasco, M; Won, S; Antonelli, L; Berry, D; Hildreth, M; Jessop, C; Karmgard, D J; Kolb, J; Kolberg, T; Lannon, K; Lynch, S; Marinelli, N; Morse, D M; Ruchti, R; Slaunwhite, J; Valls, N; Warchol, J; Wayne, M; Ziegler, J; Bylsma, B; Durkin, L S; Gu, J; Killewald, P; Ling, T Y; Williams, G; Adam, N; Berry, E; Elmer, P; Gerbaudo, D; Halyo, V; Hunt, A; Jones, J; Laird, E; Lopes Pegna, D; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Piroué, P; Stickland, D; Tully, C; Werner, J S; Zuranski, A; Acosta, J G; Huang, X T; Lopez, A; Mendez, H; Oliveros, S; Ramirez Vargas, J E; Zatzerklyaniy, A; Alagoz, E; Barnes, V E; Bolla, G; Borrello, L; Bortoletto, D; Everett, A; Garfinkel, A F; Gecse, Z; Gutay, L; Jones, M; Koybasi, O; Laasanen, A T; Leonardo, N; Liu, C; Maroussov, V; Merkel, P; Miller, D H; Neumeister, N; Potamianos, K; Shipsey, I; Silvers, D; Yoo, H D; Zablocki, J; Zheng, Y; Jindal, P; Parashar, N; Cuplov, V; Ecklund, K M; Geurts, F J M; Liu, J H; Morales, J; Padley, B P; Redjimi, R; Roberts, J; Betchart, B; Bodek, A; Chung, Y S; de Barbaro, P; Demina, R; Flacher, H; Garcia-Bellido, A; Gotra, Y; Han, J; Harel, A; Miner, D C; Orbaker, D; Petrillo, G; Vishnevskiy, D; Zielinski, M; Bhatti, A; Demortier, L; Goulianos, K; Hatakeyama, K; Lungu, G; Mesropian, C; Yan, M; Atramentov, O; Gershtein, Y; Gray, R; Halkiadakis, E; Hidas, D; Hits, D; Lath, A; Rose, K; Schnetzer, S; Somalwar, S; Stone, R; Thomas, S; Cerizza, G; Hollingsworth, M; Spanier, S; Yang, Z C; York, A; Asaadi, J; Eusebi, R; Gilmore, J; Gurrola, A; Kamon, T; Khotilovich, V; Montalvo, R; Nguyen, C N; Pivarski, J; Safonov, A; Sengupta, S; Toback, D; Weinberger, M; Akchurin, N; Bardak, C; Damgov, J; Jeong, C; Kovitanggoon, K; Lee, S W; Mane, P; Roh, Y; Sill, A; Volobouev, I; Wigmans, R; Yazgan, E; Appelt, E; Brownson, E; Engh, D; Florez, C; Gabella, W; Johns, W; Kurt, P; Maguire, C; Melo, A; Sheldon, P; Velkovska, J; Arenton, M W; Balazs, M; Buehler, M; Conetti, S; Cox, B; Hirosky, R; Ledovskoy, A; Neu, C; Yohay, R; Gollapinni, S; Gunthoti, K; Harr, R; Karchin, P E; Mattson, M; Milstène, C; Sakharov, A; Anderson, M; Bachtis, M; Bellinger, J N; Carlsmith, D; Dasu, S; Dutta, S; Efron, J; Gray, L; Grogg, K S; Grothe, M; Hall-Wilton, R; Herndon, M; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Leonard, J; Lomidze, D; Loveless, R; Mohapatra, A; Polese, G; Reeder, D; Savin, A; Smith, W H; Swanson, J; Weinberg, M

2010-07-09

Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at square root of s = 7  TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity dN(ch)/dη|(|η|<0.5) = 5.78 ± 0.01(stat) ± 0.23(syst) for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from square root of s = 0.9 to 7 TeV is [66.1 ± 1.0(stat) ± 4.2(syst)]%. The mean transverse momentum is measured to be 0.545 ± 0.005(stat) ± 0.015(syst)  GeV/c. The results are compared with similar measurements at lower energies.

The structure and dynamics of rat apo-cellular retinol-binding protein II in solution: comparison with the X-ray structure.

PubMed

Lu, J; Lin, C L; Tang, C; Ponder, J W; Kao, J L; Cistola, D P; Li, E

1999-03-05

The structure and dynamics of rat apo-cellular retinol binding protein II (apo-CRBP II) in solution has been determined by multidimensional NMR analysis of uniformly enriched recombinant rat 13C, 15N-apo-CRBP II and 15N-apo-CRBP II. The final ensemble of 24 NMR structures has been calculated from 3274 conformational restraints or 24.4 restraints/residue. The average root-mean-square deviation of the backbone atoms for the final 24 structures relative to their mean structure is 1.06 A. Although the average solution structure is very similar to the crystal structure, it differs at the putative entrance to the binding cavity, which is formed by the helix-turn-helix motif, the betaC-betaD turn and the betaE-betaF turn. The mean coordinates of the main-chain atoms of amino acid residues 28-38 are displaced in the solution structure relative to the crystal structure. The side-chain of F58, located on the betaC-betaD turn, is reoriented such that it interacts with L37 and no longer blocks entry into the ligand-binding pocket. Residues 28-35, which form the second helix of the helix-turn-helix motif in the crystal structure, do not exhibit a helical conformation in the solution structure. The solution structure of apo-CRBP II exhibits discrete regions of backbone disorder which are most pronounced at residues 28-32, 37-38 and 73-76 in the betaE-betaF turn as evaluated by the consensus chemical shift index, the root-mean-square deviation, amide 1H exchange rates and 15N relaxation studies. These studies indicate that fluctuations in protein conformation occur on the microseconds to ms time-scale in these regions of the protein. Some of these exchange processes can be directly observed in the three-dimensional 15N-resolved NOESY spectrum. These results suggest that in solution, apo-CRBP II undergoes conformational changes on the microseconds to ms time-scale which result in increased access to the binding cavity. Copyright 1999 Academic Press.

Determining the Uncertainty of X-Ray Absorption Measurements

PubMed Central

Wojcik, Gary S.

2004-01-01

X-ray absorption (or more properly, x-ray attenuation) techniques have been applied to study the moisture movement in and moisture content of materials like cement paste, mortar, and wood. An increase in the number of x-ray counts with time at a location in a specimen may indicate a decrease in moisture content. The uncertainty of measurements from an x-ray absorption system, which must be known to properly interpret the data, is often assumed to be the square root of the number of counts, as in a Poisson process. No detailed studies have heretofore been conducted to determine the uncertainty of x-ray absorption measurements or the effect of averaging data on the uncertainty. In this study, the Poisson estimate was found to adequately approximate normalized root mean square errors (a measure of uncertainty) of counts for point measurements and profile measurements of water specimens. The Poisson estimate, however, was not reliable in approximating the magnitude of the uncertainty when averaging data from paste and mortar specimens. Changes in uncertainty from differing averaging procedures were well-approximated by a Poisson process. The normalized root mean square errors decreased when the x-ray source intensity, integration time, collimator size, and number of scanning repetitions increased. Uncertainties in mean paste and mortar count profiles were kept below 2 % by averaging vertical profiles at horizontal spacings of 1 mm or larger with counts per point above 4000. Maximum normalized root mean square errors did not exceed 10 % in any of the tests conducted. PMID:27366627

Chaos and complexity by design

DOE PAGES

Roberts, Daniel A.; Yoshida, Beni

2017-04-20

We study the relationship between quantum chaos and pseudorandomness by developing probes of unitary design. A natural probe of randomness is the “frame poten-tial,” which is minimized by unitary k-designs and measures the 2-norm distance between the Haar random unitary ensemble and another ensemble. A natural probe of quantum chaos is out-of-time-order (OTO) four-point correlation functions. We also show that the norm squared of a generalization of out-of-time-order 2k-point correlators is proportional to the kth frame potential, providing a quantitative connection between chaos and pseudorandomness. In addition, we prove that these 2k-point correlators for Pauli operators completely determine the k-foldmore » channel of an ensemble of unitary operators. Finally, we use a counting argument to obtain a lower bound on the quantum circuit complexity in terms of the frame potential. This provides a direct link between chaos, complexity, and randomness.« less

Laser transit anemometer software development program

NASA Technical Reports Server (NTRS)

Abbiss, John B.

1989-01-01

Algorithms were developed for the extraction of two components of mean velocity, standard deviation, and the associated correlation coefficient from laser transit anemometry (LTA) data ensembles. The solution method is based on an assumed two-dimensional Gaussian probability density function (PDF) model of the flow field under investigation. The procedure consists of transforming the data ensembles from the data acquisition domain (consisting of time and angle information) to the velocity space domain (consisting of velocity component information). The mean velocity results are obtained from the data ensemble centroid. Through a least squares fitting of the transformed data to an ellipse representing the intersection of a plane with the PDF, the standard deviations and correlation coefficient are obtained. A data set simulation method is presented to test the data reduction process. Results of using the simulation system with a limited test matrix of input values is also given.

Weak ergodicity breaking, irreproducibility, and ageing in anomalous diffusion processes

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

Metzler, Ralf

2014-01-14

Single particle traces are standardly evaluated in terms of time averages of the second moment of the position time series r(t). For ergodic processes, one can interpret such results in terms of the known theories for the corresponding ensemble averaged quantities. In anomalous diffusion processes, that are widely observed in nature over many orders of magnitude, the equivalence between (long) time and ensemble averages may be broken (weak ergodicity breaking), and these time averages may no longer be interpreted in terms of ensemble theories. Here we detail some recent results on weakly non-ergodic systems with respect to the time averagedmore » mean squared displacement, the inherent irreproducibility of individual measurements, and methods to determine the exact underlying stochastic process. We also address the phenomenon of ageing, the dependence of physical observables on the time span between initial preparation of the system and the start of the measurement.« less

First measurement of the ratio of central-electron to forward-electron W partial cross sections in pp[over] collisions at (square root)s =1.96 TeV.

PubMed

Abulencia, A; Adelman, J; Affolder, T; Akimoto, T; Albrow, M G; Amerio, S; Amidei, D; Anastassov, A; Anikeev, K; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carillo, S; Carlsmith, D; Carosi, R; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, I; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Cilijak, M; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Coca, M; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Almenar, C Cuenca; Cuevas, J; Culbertson, R; Cully, J C; DaRonco, S; Datta, M; D'Auria, S; Davies, T; Dagenhart, D; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; De Lorenzo, G; Dell'Orso, M; Delli Paoli, F; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Giovanni, G P Di; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Dörr, C; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, I; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Forrest, R; Forrester, S; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garcia, J E; Garberson, F; Garfinkel, A F; Gay, C; Gerberich, H; Gerdes, D; Giagu, S; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Goldstein, J; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Hamilton, A; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Holloway, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; Iyutin, B; James, E; Jang, D; Jayatilaka, B; Jeans, D; Jeon, E J; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Karchin, P E; Kato, Y; Kemp, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraan, A C; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lu, R-S; Lucchesi, D; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis, A; Margaroli, F; Marginean, R; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Matsunaga, H; Mattson, M E; Mazini, R; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyamoto, A; Moed, S; Moggi, N; Mohr, B; Moon, C S; Moore, R; Morello, M; Fernandez, P Movilla; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Pagliarone, C; Palencia, E; Papadimitriou, V; 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Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zhou, J; Zucchelli, S

2007-06-22

We present a measurement of sigma(pp[over] --> W) x B(W --> e nu) at (square root)s = 1.96 TeV, using electrons identified in the forward region (1.2 < |eta| < 2.8) of the CDF II detector, in 223 pb(-1) of data. We measure sigma x B = 2796 +/- 13(stat)(-90)(+95)(syst) +/- 162(lum) pb. Combining this result with a previous CDF measurement obtained using electrons in the central region (|eta| approximately < 1), we present the first measurement of the ratio of central-electron to forward-electron W partial cross sections R(exp) = 0.925 +/- 0.006(stat) +/- 0.032(syst), consistent with theoretical predictions using Coordinated Theoretical-Experimental Project on QCD (CTEQ) and Martin-Roberts-Stirling-Thorne (MRST) parton distribution functions.

Search for gluinos and scalar quarks in pp collisions at square root[s] = 1.8 TeV using the missing energy plus multijets signature.

PubMed

Affolder, T; Akimoto, H; Akopian, A; Albrow, M G; Amaral, P; Amidei, D; Anikeev, K; Antos, J; Apollinari, G; Arisawa, T; Artikov, A; Asakawa, T; Ashmanskas, W; Azfar, F; Azzi-Bacchetta, P; Bacchetta, N; Bachacou, H; Bailey, S; de Barbaro, P; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Barone, M; Bauer, G; Bedeschi, F; Belforte, S; Bell, W H; Bellettini, G; Bellinger, J; Benjamin, D; Bensinger, J; Beretvas, A; Berge, J P; Berryhill, J; Bhatti, A; Binkley, M; Bisello, D; Bishai, M; Blair, R E; Blocker, C; Bloom, K; Blumenfeld, B; Blusk, S R; Bocci, A; Bodek, A; Bokhari, W; Bolla, G; Bonushkin, Y; Bortoletto, D; Boudreau, J; Brandl, A; van den Brink, S; Bromberg, C; Brozovic, M; Brubaker, E; Bruner, N; Buckley-Geer, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Byon-Wagner, A; Byrum, K L; Cabrera, S; Calafiura, P; Campbell, M; Carithers, W; Carlson, J; Carlsmith, D; Caskey, W; Castro, A; Cauz, D; Cerri, A; Chan, A W; Chang, P S; Chang, P T; Chapman, J; Chen, C; Chen, Y C; Cheng, M-T; Chertok, M; Chiarelli, G; Chirikov-Zorin, I; Chlachidze, G; Chlebana, F; Christofek, L; Chu, M L; Chung, Y S; Ciobanu, C I; Clark, A G; Connolly, A; Conway, J; Cordelli, M; Cranshaw, J; Cropp, R; Culbertson, R; Dagenhart, D; D'Auria, S; DeJongh, F; Dell'Agnello, S; Dell'Orso, M; Demortier, L; Deninno, M; Derwent, P F; Devlin, T; Dittmann, J R; Dominguez, A; Donati, S; Done, J; D'Onofrio, M; Dorigo, T; Eddy, N; Einsweiler, K; Elias, J E; Engels, E; Erbacher, R; Errede, D; Errede, S; Fan, Q; Feild, R G; Fernandez, J P; Ferretti, C; Field, R D; Fiori, I; Flaugher, B; Foster, G W; Franklin, M; Freeman, J; Friedman, J; Frisch, H J; Fukui, Y; Furic, I; Galeotti, S; Gallas, A; Gallinaro, M; Gao, T; Garcia-Sciveres, M; Garfinkel, A F; Gatti, P; Gay, C; Gerdes, D W; Giannetti, P; Giromini, P; Glagolev, V; Glenzinski, D; Gold, M; Goldstein, J; Gorelov, I; Goshaw, A T; Gotra, Y; Goulianos, K; Green, C; Grim, G; Gris, P; Groer, L; Grosso-Pilcher, C; Guenther, M; Guillian, G; Guimaraes da Costa, J; Haas, R M; Haber, C; Hahn, S R; Hall, C; Handa, T; Handler, R; Hao, W; Happacher, F; Hara, K; Hardman, A D; Harris, R M; Hartmann, F; Hatakeyama, K; Hauser, J; Heinrich, J; Heiss, A; Herndon, M; Hill, C; Hoffman, K D; Holck, C; Hollebeek, R; Holloway, L; Hughes, R; Huston, J; Huth, J; Ikeda, H; Incandela, J; Introzzi, G; Iwai, J; Iwata, Y; James, E; Jones, M; Joshi, U; Kambara, H; Kamon, T; Kaneko, T; Karr, K; Kasha, H; Kato, Y; Keaffaber, T A; Kelley, K; Kelly, M; Kennedy, R D; Kephart, R; Khazins, D; Kikuchi, T; Kilminster, B; Kim, B J; Kim, D H; Kim, H S; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kirby, M; Kirk, M; Kirsch, L; Klimenko, S; Koehn, P; Kondo, K; Konigsberg, J; Korn, A; Korytov, A; Kovacs, E; Kroll, J; Kruse, M; Kuhlmann, S E; Kurino, K; Kuwabara, T; Laasanen, A T; Lai, N; Lami, S; Lammel, S; Lancaster, J; Lancaster, M; Lander, R; Lath, A; Latino, G; LeCompte, T; Lee, A M; Lee, K; Leone, S; Lewis, J D; Lindgren, M; Liss, T M; Liu, J B; Liu, Y C; Litvintsev, D O; Lobban, O; Lockyer, N; Loken, J; Loreti, M; Lucchesi, D; Lukens, P; Lusin, S; Lyons, L; Lys, J; Madrak, R; Maeshima, K; Maksimovic, P; Malferrari, L; Mangano, M; Mariotti, M; Martignon, G; Martin, A; Matthews, J A J; Mayer, J; Mazzanti, P; McFarland, K S; McIntyre, P; McKigney, E; Menguzzato, M; Menzione, A; Mesropian, C; Meyer, A; Miao, T; Miller, R; Miller, J S; Minato, H; Miscetti, S; Mishina, M; Mitselmakher, G; Moggi, N; Moore, E; Moore, R; Morita, Y; Moulik, T; Mulhearn, M; Mukherjee, A; Muller, T; Munar, A; Murat, P; Murgia, S; Nachtman, J; Nagaslaev, V; Nahn, S; Nakada, H; Nakano, I; Nelson, C; Nelson, T; Neu, C; Neuberger, D; Newman-Holmes, C; Ngan, C-Y P; Niu, H; Nodulman, L; Nomerotski, A; Oh, S H; Oh, Y D; Ohmoto, T; Ohsugi, T; Oishi, R; Okusawa, T; Olsen, J; Orejudos, W; Pagliarone, C; Palmonari, F; Paoletti, R; Papadimitriou, V; Partos, D; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pescara, L; Phillips, T J; Piacentino, G; Pitts, K T; Pompos, A; Pondrom, L; Pope, G; Popovic, M; Prokoshin, F; Proudfoot, J; Ptohos, F; Pukhov, O; Punzi, G; Rakitine, A; Ratnikov, F; Reher, D; Reichold, A; Ribon, A; Riegler, W; Rimondi, F; Ristori, L; Riveline, M; Robertson, W J; Robinson, A; Rodrigo, T; Rolli, S; Rosenson, L; Roser, R; Rossin, R; Roy, A; Ruiz, A; Safonov, A; St Denis, R; Sakumoto, W K; Saltzberg, D; Sanchez, C; Sansoni, A; Santi, L; Sato, H; Savard, P; Schlabach, P; Schmidt, E E; Schmidt, M P; Schmitt, M; Scodellaro, L; Scott, A; Scribano, A; Segler, S; Seidel, S; Seiya, Y; Semenov, A; Semeria, F; Shah, T; Shapiro, M D; Shepard, P F; Shibayama, T; Shimojima, M; Shochet, M; Sidoti, A; Siegrist, J; Sill, A; Sinervo, P; Singh, P; Slaughter, A J; Sliwa, K; Smith, C; Snider, F D; Solodsky, A; Spalding, J; Speer, T; Sphicas, P; Spinella, F; Spiropulu, M; Spiegel, L; Steele, J; Stefanini, A; Strologas, J; Strumia, F; Stuart, D; Sumorok, K; Suzuki, T; Takano, T; Takashima, R; Takikawa, K; Tamburello, P; Tanaka, M; Tannenbaum, B; Tecchio, M; Tesarek, R; Teng, P K; Terashi, K; Tether, S; Thompson, A S; Thurman-Keup, R; Tipton, P; Tkaczyk, S; Toback, D; Tollefson, K; Tollestrup, A; Tonelli, D; Toyoda, H; Trischuk, W; de Troconiz, J F; Tseng, J; Turini, N; Ukegawa, F; Vaiciulis, T; Valls, J; Vejcik, S; Velev, G; Veramendi, G; Vidal, R; Vila, I; Vilar, R; Volobouev, I; von der Mey, M; Vucinic, D; Wagner, R G; Wagner, R L; Wallace, N B; Wan, Z; Wang, C; Wang, M J; Ward, B; Waschke, S; Watanabe, T; Waters, D; Watts, T; Webb, R; Wenzel, H; Wester, W C; Wicklund, A B; Wicklund, E; Wilkes, T; Williams, H H; Wilson, P; Winer, B L; Winn, D; Wolbers, S; Wolinski, D; Wolinski, J; Wolinski, S; Worm, S; Wu, X; Wyss, J; Yao, W; Yagil, A; Yeh, G P; Yoh, J; Yosef, C; Yoshida, T; Yu, I; Yu, S; Yu, Z; Zanetti, A; Zetti, F; Zucchelli, S

2002-01-28

We have performed a search for gluinos (g) and scalar quarks (q) in a data sample of 84 pb(-1) of pp collisions at square root[s] = 1.8 TeV, recorded by the Collider Detector at Fermilab. We investigate the final state of large missing transverse energy and three or more jets, a characteristic signature in R-parity-conserving supersymmetric models. The analysis has been performed "blind," in that the inspection of the signal region is made only after the predictions from standard model backgrounds have been calculated. Comparing the data with predictions of constrained supersymmetric models, we exclude gluino masses below 195 GeV/c2 (95% C.L.), independent of the squark mass. For the case m(q) approximately m(g), gluino masses below 300 GeV/c2 are excluded.

Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Reichle, Rolf H.

2016-01-01

Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval assimilation.

Light-regulated gravitropism in seedling roots of maize

NASA Technical Reports Server (NTRS)

Feldman, L. J.; Briggs, W. R.

1987-01-01

Red light-induced changes in the gravitropism of roots of Zea mays variety Merit is a very low fluence response with a threshold of 10(-9) moles per square meter and is not reversible by far red light. Blue light also affects root gravitropism but the sensitivity of roots to blue is 50 to 100 times less than to an equal fluence of red. In Z. mays Merit we conclude that phytochrome is the sole pigment associated with light-induced changes in root gravitropism.

[NIR Assignment of Magnolol by 2D-COS Technology and Model Application Huoxiangzhengqi Oral Liduid].

PubMed

Pei, Yan-ling; Wu, Zhi-sheng; Shi, Xin-yuan; Pan, Xiao-ning; Peng, Yan-fang; Qiao, Yan-jiang

2015-08-01

Near infrared (NIR) spectroscopy assignment of Magnolol was performed using deuterated chloroform solvent and two-dimensional correlation spectroscopy (2D-COS) technology. According to the synchronous spectra of deuterated chloroform solvent and Magnolol, 1365~1455, 1600~1720, 2000~2181 and 2275~2465 nm were the characteristic absorption of Magnolol. Connected with the structure of Magnolol, 1440 nm was the stretching vibration of phenolic group O-H, 1679 nm was the stretching vibration of aryl and methyl which connected with aryl, 2117, 2304, 2339 and 2370 nm were the combination of the stretching vibration, bending vibration and deformation vibration for aryl C-H, 2445 nm were the bending vibration of methyl which linked with aryl group, these bands attribut to the characteristics of Magnolol. Huoxiangzhengqi Oral Liduid was adopted to study the Magnolol, the characteristic band by spectral assignment and the band by interval Partial Least Squares (iPLS) and Synergy interval Partial Least Squares (SiPLS) were used to establish Partial Least Squares (PLS) quantitative model, the coefficient of determination Rcal(2) and Rpre(2) were greater than 0.99, the Root Mean of Square Error of Calibration (RM-SEC), Root Mean of Square Error of Cross Validation (RMSECV) and Root Mean of Square Error of Prediction (RMSEP) were very small. It indicated that the characteristic band by spectral assignment has the same results with the Chemometrics in PLS model. It provided a reference for NIR spectral assignment of chemical compositions in Chinese Materia Medica, and the band filters of NIR were interpreted.

Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Kumar, Sujay V.; Wang, Shugong; Mocko, David M.; Peters-Lidard, Christa D.; Xia, Youlong

2017-11-01

Multimodel ensembles are often used to produce ensemble mean estimates that tend to have increased simulation skill over any individual model output. If multimodel outputs are too similar, an individual LSM would add little additional information to the multimodel ensemble, whereas if the models are too dissimilar, it may be indicative of systematic errors in their formulations or configurations. The article presents a formal similarity assessment of the North American Land Data Assimilation System (NLDAS) multimodel ensemble outputs to assess their utility to the ensemble, using a confirmatory factor analysis. Outputs from four NLDAS Phase 2 models currently running in operations at NOAA/NCEP and four new/upgraded models that are under consideration for the next phase of NLDAS are employed in this study. The results show that the runoff estimates from the LSMs were most dissimilar whereas the models showed greater similarity for root zone soil moisture, snow water equivalent, and terrestrial water storage. Generally, the NLDAS operational models showed weaker association with the common factor of the ensemble and the newer versions of the LSMs showed stronger association with the common factor, with the model similarity increasing at longer time scales. Trade-offs between the similarity metrics and accuracy measures indicated that the NLDAS operational models demonstrate a larger span in the similarity-accuracy space compared to the new LSMs. The results of the article indicate that simultaneous consideration of model similarity and accuracy at the relevant time scales is necessary in the development of multimodel ensemble.

Theoretical study of the transfer integral and density of states in spiro-linked triphenylamine derivatives.

PubMed

Kirkpatrick, James; Nelson, Jenny

2005-08-22

We present a method for calculating the parameters that control hopping transport in disordered molecular solids, i.e., the transfer integrals and the distribution of transport site energies. Average values of these parameters are obtained by performing quantum-chemical calculations on a large ensemble of bimolecular complexes in random relative orientations. The method is applied to triphenylamine (TPA) and three differently substituted spiro-linked phenylamine compounds, 2,2',7,7'-tetrakis-(N,N-di-4-methoxyphenylamino)-9,9'-spirobifluorene (spiro-MeOTAD), 2,2'7,7'-tetrakis-(N,N-diphenylhenylamino)-9,9'-spirobifluorene (spiro-TAD), and 2,2',7,7'-tetrakis-(N,N-di-m-methylphenylamino)-9,9'-spirobifluorene (spiro-m-TTB). In the case of TPA, the dependence of the root-mean-square hole transfer integral J on intermolecular separation r for the ensemble of relative orientations is compared with that obtained by performing the same calculations for a fixed, approximately cofacial, orientation of the two TPA molecules. The calculation for the disordered geometry predicts a larger localization radius r0, where J approximately exp(-r/r0), than the calculation for the fixed orientation and is in better agreement with experiment. In the case of the spiro-linked compounds, results from our method are compared with parameters extracted from time-of-flight mobility measurements analyzed with the Gaussian disorder model (GDM). We find that the highest occupied molecular-orbital (HOMO) energies of the bimolecular complexes are distributed on an asymmetric peak, whose width varies in qualitative agreement with the value of the energetic disorder sigma obtained from experimental data using the GDM. The mean-square hole transfer integral varies in accordance with the experimentally determined value of the mobility prefactor micro0. The differences between the differently substituted compounds are interpreted in terms of differences in the spatial extent of the wave function. Spiro-MeOTAD was found to have a greater localization radius, which leads to both a larger transfer integral and a broader distribution of HOMO energies than either of the other compounds. For these compounds, differences in energetic disorder could not be explained in terms of differences in the permanent dipole moment. Our method is proposed as an approximate means of predicting the effect of chemical structure on the values of transport parameters in disordered molecular films.

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition

PubMed Central

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-01-01

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijiang stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five models. The scatterplots of the predicted results of the six models versus the original daily LST data series show that the hybrid EEMD-LSTM model is superior to the other five models. It is concluded that the proposed hybrid EEMD-LSTM model in this study is a suitable tool for temperature forecasting. PMID:29883381

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.

PubMed

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-05-21

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijaing stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five models. The scatterplots of the predicted results of the six models versus the original daily LST data series show that the hybrid EEMD-LSTM model is superior to the other five models. It is concluded that the proposed hybrid EEMD-LSTM model in this study is a suitable tool for temperature forecasting.

A root-mean-square pressure fluctuations model for internal flow applications

NASA Technical Reports Server (NTRS)

Chen, Y. S.

1985-01-01

A transport equation for the root-mean-square pressure fluctuations of turbulent flow is derived from the time-dependent momentum equation for incompressible flow. Approximate modeling of this transport equation is included to relate terms with higher order correlations to the mean quantities of turbulent flow. Three empirical constants are introduced in the model. Two of the empirical constants are estimated from homogeneous turbulence data and wall pressure fluctuations measurements. The third constant is determined by comparing the results of large eddy simulations for a plane channel flow and an annulus flow.

Vectorization of linear discrete filtering algorithms

NASA Technical Reports Server (NTRS)

Schiess, J. R.

1977-01-01

Linear filters, including the conventional Kalman filter and versions of square root filters devised by Potter and Carlson, are studied for potential application on streaming computers. The square root filters are known to maintain a positive definite covariance matrix in cases in which the Kalman filter diverges due to ill-conditioning of the matrix. Vectorization of the filters is discussed, and comparisons are made of the number of operations and storage locations required by each filter. The Carlson filter is shown to be the most efficient of the filters on the Control Data STAR-100 computer.

Symmetric factorization of the conformation tensor in viscoelastic fluid models

NASA Astrophysics Data System (ADS)

Thomases, Becca; Balci, Nusret; Renardy, Michael; Doering, Charles

2010-11-01

The positive definite symmetric polymer conformation tensor possesses a unique symmetric square root that satisfies a closed evolution equation in the Oldroyd-B and FENE-P models of viscoelastic fluid flow. When expressed in terms of the velocity field and the symmetric square root of the conformation tensor, these models' equations of motion formally constitute an evolution in a Hilbert space with a total energy functional that defines a norm. Moreover, this formulation is easily implemented in direct numerical simulations resulting in significant practical advantages in terms of both accuracy and stability.

Application of Data Assimilation with the Root Zone Water Quality Model for Soil Moisture Profile Estimation

USDA-ARS?s Scientific Manuscript database

Estimation of soil moisture has received considerable attention in the areas of hydrology, agriculture, meteorology and environmental studies because of its role in the partitioning water and energy at the land surface. In this study, the Ensemble Kalman Filter (EnKF), a popular data assimilation te...

Transient aging in fractional Brownian and Langevin-equation motion.

PubMed

Kursawe, Jochen; Schulz, Johannes; Metzler, Ralf

2013-12-01

Stochastic processes driven by stationary fractional Gaussian noise, that is, fractional Brownian motion and fractional Langevin-equation motion, are usually considered to be ergodic in the sense that, after an algebraic relaxation, time and ensemble averages of physical observables coincide. Recently it was demonstrated that fractional Brownian motion and fractional Langevin-equation motion under external confinement are transiently nonergodic-time and ensemble averages behave differently-from the moment when the particle starts to sense the confinement. Here we show that these processes also exhibit transient aging, that is, physical observables such as the time-averaged mean-squared displacement depend on the time lag between the initiation of the system at time t=0 and the start of the measurement at the aging time t(a). In particular, it turns out that for fractional Langevin-equation motion the aging dependence on t(a) is different between the cases of free and confined motion. We obtain explicit analytical expressions for the aged moments of the particle position as well as the time-averaged mean-squared displacement and present a numerical analysis of this transient aging phenomenon.

Neuro-fuzzy decoding of sensory information from ensembles of simultaneously recorded dorsal root ganglion neurons for functional electrical stimulation applications

NASA Astrophysics Data System (ADS)

Rigosa, J.; Weber, D. J.; Prochazka, A.; Stein, R. B.; Micera, S.

2011-08-01

Functional electrical stimulation (FES) is used to improve motor function after injury to the central nervous system. Some FES systems use artificial sensors to switch between finite control states. To optimize FES control of the complex behavior of the musculo-skeletal system in activities of daily life, it is highly desirable to implement feedback control. In theory, sensory neural signals could provide the required control signals. Recent studies have demonstrated the feasibility of deriving limb-state estimates from the firing rates of primary afferent neurons recorded in dorsal root ganglia (DRG). These studies used multiple linear regression (MLR) methods to generate estimates of limb position and velocity based on a weighted sum of firing rates in an ensemble of simultaneously recorded DRG neurons. The aim of this study was to test whether the use of a neuro-fuzzy (NF) algorithm (the generalized dynamic fuzzy neural networks (GD-FNN)) could improve the performance, robustness and ability to generalize from training to test sets compared to the MLR technique. NF and MLR decoding methods were applied to ensemble DRG recordings obtained during passive and active limb movements in anesthetized and freely moving cats. The GD-FNN model provided more accurate estimates of limb state and generalized better to novel movement patterns. Future efforts will focus on implementing these neural recording and decoding methods in real time to provide closed-loop control of FES using the information extracted from sensory neurons.

A Maximum-Likelihood Approach to Force-Field Calibration.

PubMed

Zaborowski, Bartłomiej; Jagieła, Dawid; Czaplewski, Cezary; Hałabis, Anna; Lewandowska, Agnieszka; Żmudzińska, Wioletta; Ołdziej, Stanisław; Karczyńska, Agnieszka; Omieczynski, Christian; Wirecki, Tomasz; Liwo, Adam

2015-09-28

A new approach to the calibration of the force fields is proposed, in which the force-field parameters are obtained by maximum-likelihood fitting of the calculated conformational ensembles to the experimental ensembles of training system(s). The maximum-likelihood function is composed of logarithms of the Boltzmann probabilities of the experimental conformations, calculated with the current energy function. Because the theoretical distribution is given in the form of the simulated conformations only, the contributions from all of the simulated conformations, with Gaussian weights in the distances from a given experimental conformation, are added to give the contribution to the target function from this conformation. In contrast to earlier methods for force-field calibration, the approach does not suffer from the arbitrariness of dividing the decoy set into native-like and non-native structures; however, if such a division is made instead of using Gaussian weights, application of the maximum-likelihood method results in the well-known energy-gap maximization. The computational procedure consists of cycles of decoy generation and maximum-likelihood-function optimization, which are iterated until convergence is reached. The method was tested with Gaussian distributions and then applied to the physics-based coarse-grained UNRES force field for proteins. The NMR structures of the tryptophan cage, a small α-helical protein, determined at three temperatures (T = 280, 305, and 313 K) by Hałabis et al. ( J. Phys. Chem. B 2012 , 116 , 6898 - 6907 ), were used. Multiplexed replica-exchange molecular dynamics was used to generate the decoys. The iterative procedure exhibited steady convergence. Three variants of optimization were tried: optimization of the energy-term weights alone and use of the experimental ensemble of the folded protein only at T = 280 K (run 1); optimization of the energy-term weights and use of experimental ensembles at all three temperatures (run 2); and optimization of the energy-term weights and the coefficients of the torsional and multibody energy terms and use of experimental ensembles at all three temperatures (run 3). The force fields were subsequently tested with a set of 14 α-helical and two α + β proteins. Optimization run 1 resulted in better agreement with the experimental ensemble at T = 280 K compared with optimization run 2 and in comparable performance on the test set but poorer agreement of the calculated folding temperature with the experimental folding temperature. Optimization run 3 resulted in the best fit of the calculated ensembles to the experimental ones for the tryptophan cage but in much poorer performance on the training set, suggesting that use of a small α-helical protein for extensive force-field calibration resulted in overfitting of the data for this protein at the expense of transferability. The optimized force field resulting from run 2 was found to fold 13 of the 14 tested α-helical proteins and one small α + β protein with the correct topologies; the average structures of 10 of them were predicted with accuracies of about 5 Å C(α) root-mean-square deviation or better. Test simulations with an additional set of 12 α-helical proteins demonstrated that this force field performed better on α-helical proteins than the previous parametrizations of UNRES. The proposed approach is applicable to any problem of maximum-likelihood parameter estimation when the contributions to the maximum-likelihood function cannot be evaluated at the experimental points and the dimension of the configurational space is too high to construct histograms of the experimental distributions.

Geometrical Solutions of Some Quadratic Equations with Non-Real Roots

ERIC Educational Resources Information Center

Pathak, H. K.; Grewal, A. S.

2002-01-01

This note gives geometrical/graphical methods of finding solutions of the quadratic equation ax[squared] + bx + c = 0, a [not equal to] 0, with non-real roots. Three different cases which give rise to non-real roots of the quadratic equation have been discussed. In case I a geometrical construction and its proof for finding the solutions of the…

Dynamics of Fractal Cluster Gels with Embedded Active Colloids

NASA Astrophysics Data System (ADS)

Szakasits, Megan E.; Zhang, Wenxuan; Solomon, Michael J.

2017-08-01

We find that embedded active colloids increase the ensemble-averaged mean squared displacement of particles in otherwise passively fluctuating fractal cluster gels. The enhancement in dynamics occurs by a mechanism in which the active colloids contribute to the average dynamics both directly through their own active motion and indirectly through their excitation of neighboring passive colloids in the fractal network. Fractal cluster gels are synthesized by addition of magnesium chloride to an initially stable suspension of 1.0 μ m polystyrene colloids in which a dilute concentration of platinum coated Janus colloids has been dispersed. The Janus colloids are thereby incorporated into the fractal network. We measure the ensemble-averaged mean squared displacement of all colloids in the gel before and after the addition of hydrogen peroxide, a fuel that drives diffusiophoretic motion of the Janus particles. The gel mean squared displacement increases by up to a factor of 3 for an active to passive particle ratio of 1 ∶20 and inputted active energy—defined based on the hydrogen peroxide's effect on colloid swim speed and run length—that is up to 9.5 times thermal energy, on a per particle basis. We model the enhancement in gel particle dynamics as the sum of a direct contribution from the displacement of the Janus particles themselves and an indirect contribution from the strain field that the active colloids induce in the surrounding passive particles.

Validation of Core Temperature Estimation Algorithm

DTIC Science & Technology

2016-01-29

plot of observed versus estimated core temperature with the line of identity (dashed) and the least squares regression line (solid) and line equation...estimated PSI with the line of identity (dashed) and the least squares regression line (solid) and line equation in the top left corner. (b) Bland...for comparison. The root mean squared error (RMSE) was also computed, as given by Equation 2.

Convex lattice polygons of fixed area with perimeter-dependent weights.

PubMed

Rajesh, R; Dhar, Deepak

2005-01-01

We study fully convex polygons with a given area, and variable perimeter length on square and hexagonal lattices. We attach a weight tm to a convex polygon of perimeter m and show that the sum of weights of all polygons with a fixed area s varies as s(-theta(conv))eK(t)square root(s) for large s and t less than a critical threshold tc, where K(t) is a t-dependent constant, and theta(conv) is a critical exponent which does not change with t. Using heuristic arguments, we find that theta(conv) is 1/4 for the square lattice, but -1/4 for the hexagonal lattice. The reason for this unexpected nonuniversality of theta(conv) is traced to existence of sharp corners in the asymptotic shape of these polygons.

High resolution statistical downscaling of the EUROSIP seasonal prediction. Application for southeastern Romania

NASA Astrophysics Data System (ADS)

Busuioc, Aristita; Dumitrescu, Alexandru; Dumitrache, Rodica; Iriza, Amalia

2017-04-01

Seasonal climate forecasts in Europe are currently issued at the European Centre for Medium-Range Weather Forecasts (ECMWF) in the form of multi-model ensemble predictions available within the "EUROSIP" system. Different statistical techniques to calibrate, downscale and combine the EUROSIP direct model output are used to optimize the quality of the final probabilistic forecasts. In this study, a statistical downscaling model (SDM) based on canonical correlation analysis (CCA) is used to downscale the EUROSIP seasonal forecast at a spatial resolution of 1km x 1km over the Movila farm placed in southeastern Romania. This application is achieved in the framework of the H2020 MOSES project (http://www.moses-project.eu). The combination between monthly standardized values of three climate variables (maximum/minimum temperatures-Tmax/Tmin, total precipitation-Prec) is used as predictand while combinations of various large-scale predictors are tested in terms of their availability as outputs in the seasonal EUROSIP probabilistic forecasting (sea level pressure, temperature at 850 hPa and geopotential height at 500 hPa). The predictors are taken from the ECMWF system considering 15 members of the ensemble, for which the hindcasts since 1991 until present are available. The model was calibrated over the period 1991-2014 and predictions for summers 2015 and 2016 were achieved. The calibration was made for the ensemble average as well as for each ensemble member. The model was developed for each lead time: one month anticipation for June, two months anticipation for July and three months anticipation for August. The main conclusions from these preliminary results are: best predictions (in terms of the anomaly sign) for Tmax (July-2 months anticipation, August-3 months anticipation) for both years (2015, 2016); for Tmin - good predictions only for August (3 months anticipation ) for both years; for precipitation, good predictions for July (2 months anticipation) in 2015 and August (3 months anticipation) in 2016; failed prediction for June (1-month anticipation) for all parameters. To see if the results obtained for 2015 and 2016 summers are in agreement with the general ECMWF model performance in forecast of the three predictors used in the CCA SDM calibration, the mean bias and root mean square errors (RMSE) calculated over the entire period in each grid point, for each ensemble member and ensemble average were computed. The obtained results are confirmed, showing highest ECMWF performance in forecasting of the three predictors for 3 months anticipation (August) and lowest performance for one month anticipation (June). The added value of the CCA SDM in forecasting local Tmax/Tmin and total precipitation was compared to the ECMWF performance using nearest grid point method. Comparisons were performed for the 1991-2014 period, taking into account the forecast made in May for July. An important improvement was found for the CCA SDM predictions in terms of the RMSE value (computed against observations) for Tmax/Tmin and less for precipitation. The tests are in progress for the other summer months (June, July).

Light-Regulated Gravitropism in Seedling Roots of Maize 1

PubMed Central

Feldman, Lewis J.; Briggs, Winslow R.

1987-01-01

Red light-induced changes in the gravitropism of roots of Zea mays variety Merit is a very low fluence response with a threshold of 10−9 moles per square meter and is not reversible by far red light. Blue light also affects root gravitropism but the sensitivity of roots to blue is 50 to 100 times less than to an equal fluence of red. In Z. mays Merit we conclude that phytochrome is the sole pigment associated with light-induced changes in root gravitropism. PMID:11539030

Method of measuring cross-flow vortices by use of an array of hot-film sensors

NASA Technical Reports Server (NTRS)

Agarwal, Aval K. (Inventor); Maddalon, Dal V. (Inventor); Mangalam, Siva M. (Inventor)

1993-01-01

The invention is a method for measuring the wavelength of cross-flow vortices of air flow having streamlines of flow traveling across a swept airfoil. The method comprises providing a plurality of hot-film sensors. Each hot-film sensor provides a signal which can be processed, and each hot-film sensor is spaced in a straight-line array such that the distance between successive hot-film sensors is less than the wavelength of the cross-flow vortices being measured. The method further comprises determining the direction of travel of the streamlines across the airfoil and positioning the straight-line array of hot film sensors perpendicular to the direction of travel of the streamlines, such that each sensor has a spanwise location. The method further comprises processing the signals provided by the sensors to provide root-mean-square values for each signal, plotting each root-mean-square value as a function of its spanwise location, and determining the wavelength of the cross-flow vortices by noting the distance between two maxima or two minima of root-mean-square values.

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association

PubMed Central

Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-01-01

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets’ state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems. PMID:29113085

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association.

PubMed

Liu, Yu; Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-11-05

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets' state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems.

Association of auricular pressing and heart rate variability in pre-exam anxiety students.

PubMed

Wu, Wocao; Chen, Junqi; Zhen, Erchuan; Huang, Huanlin; Zhang, Pei; Wang, Jiao; Ou, Yingyi; Huang, Yong

2013-03-25

A total of 30 students scoring between 12 and 20 on the Test Anxiety Scale who had been exhibiting an anxious state > 24 hours, and 30 normal control students were recruited. Indices of heart rate variability were recorded using an Actiheart electrocardiogram recorder at 10 minutes before auricular pressing, in the first half of stimulation and in the second half of stimulation. The results revealed that the standard deviation of all normal to normal intervals and the root mean square of standard deviation of normal to normal intervals were significantly increased after stimulation. The heart rate variability triangular index, very-low-frequency power, low-frequency power, and the ratio of low-frequency to high-frequency power were increased to different degrees after stimulation. Compared with normal controls, the root mean square of standard deviation of normal to normal intervals was significantly increased in anxious students following auricular pressing. These results indicated that auricular pressing can elevate heart rate variability, especially the root mean square of standard deviation of normal to normal intervals in students with pre-exam anxiety.

Association of auricular pressing and heart rate variability in pre-exam anxiety students

PubMed Central

Wu, Wocao; Chen, Junqi; Zhen, Erchuan; Huang, Huanlin; Zhang, Pei; Wang, Jiao; Ou, Yingyi; Huang, Yong

2013-01-01

A total of 30 students scoring between 12 and 20 on the Test Anxiety Scale who had been exhibiting an anxious state > 24 hours, and 30 normal control students were recruited. Indices of heart rate variability were recorded using an Actiheart electrocardiogram recorder at 10 minutes before auricular pressing, in the first half of stimulation and in the second half of stimulation. The results revealed that the standard deviation of all normal to normal intervals and the root mean square of standard deviation of normal to normal intervals were significantly increased after stimulation. The heart rate variability triangular index, very-low-frequency power, low-frequency power, and the ratio of low-frequency to high-frequency power were increased to different degrees after stimulation. Compared with normal controls, the root mean square of standard deviation of normal to normal intervals was significantly increased in anxious students following auricular pressing. These results indicated that auricular pressing can elevate heart rate variability, especially the root mean square of standard deviation of normal to normal intervals in students with pre-exam anxiety. PMID:25206734

Determining particle size and water content by near-infrared spectroscopy in the granulation of naproxen sodium.

PubMed

Bär, David; Debus, Heiko; Brzenczek, Sina; Fischer, Wolfgang; Imming, Peter

2018-03-20

Near-infrared spectroscopy is frequently used by the pharmaceutical industry to monitor and optimize several production processes. In combination with chemometrics, a mathematical-statistical technique, the following advantages of near-infrared spectroscopy can be applied: It is a fast, non-destructive, non-invasive, and economical analytical method. One of the most advanced and popular chemometric technique is the partial least square algorithm with its best applicability in routine and its results. The required reference analytic enables the analysis of various parameters of interest, for example, moisture content, particle size, and many others. Parameters like the correlation coefficient, root mean square error of prediction, root mean square error of calibration, and root mean square error of validation have been used for evaluating the applicability and robustness of these analytical methods developed. This study deals with investigating a Naproxen Sodium granulation process using near-infrared spectroscopy and the development of water content and particle-size methods. For the water content method, one should consider a maximum water content of about 21% in the granulation process, which must be confirmed by the loss on drying. Further influences to be considered are the constantly changing product temperature, rising to about 54 °C, the creation of hydrated states of Naproxen Sodium when using a maximum of about 21% water content, and the large quantity of about 87% Naproxen Sodium in the formulation. It was considered to use a combination of these influences in developing the near-infrared spectroscopy method for the water content of Naproxen Sodium granules. The "Root Mean Square Error" was 0.25% for calibration dataset and 0.30% for the validation dataset, which was obtained after different stages of optimization by multiplicative scatter correction and the first derivative. Using laser diffraction, the granules have been analyzed for particle sizes and obtaining the summary sieve sizes of >63 μm and >100 μm. The following influences should be considered for application in routine production: constant changes in water content up to 21% and a product temperature up to 54 °C. The different stages of optimization result in a "Root Mean Square Error" of 2.54% for the calibration data set and 3.53% for the validation set by using the Kubelka-Munk conversion and first derivative for the near-infrared spectroscopy method for a particle size >63 μm. For the near-infrared spectroscopy method using a particle size >100 μm, the "Root Mean Square Error" was 3.47% for the calibration data set and 4.51% for the validation set, while using the same pre-treatments. - The robustness and suitability of this methodology has already been demonstrated by its recent successful implementation in a routine granulate production process. Copyright © 2018 Elsevier B.V. All rights reserved.

Thermodynamics of a time-dependent and dissipative oval billiard: A heat transfer and billiard approach.

PubMed

Leonel, Edson D; Galia, Marcus Vinícius Camillo; Barreiro, Luiz Antonio; Oliveira, Diego F M

2016-12-01

We study some statistical properties for the behavior of the average squared velocity-hence the temperature-for an ensemble of classical particles moving in a billiard whose boundary is time dependent. We assume the collisions of the particles with the boundary of the billiard are inelastic, leading the average squared velocity to reach a steady-state dynamics for large enough time. The description of the stationary state is made by using two different approaches: (i) heat transfer motivated by the Fourier law and (ii) billiard dynamics using either numerical simulations and theoretical description.

Vapor-liquid equilibrium and critical asymmetry of square well and short square well chain fluids.

PubMed

Li, Liyan; Sun, Fangfang; Chen, Zhitong; Wang, Long; Cai, Jun

2014-08-07

The critical behavior of square well fluids with variable interaction ranges and of short square well chain fluids have been investigated by grand canonical ensemble Monte Carlo simulations. The critical temperatures and densities were estimated by a finite-size scaling analysis with the help of histogram reweighting technique. The vapor-liquid coexistence curve in the near-critical region was determined using hyper-parallel tempering Monte Carlo simulations. The simulation results for coexistence diameters show that the contribution of |t|(1-α) to the coexistence diameter dominates the singular behavior in all systems investigated. The contribution of |t|(2β) to the coexistence diameter is larger for the system with a smaller interaction range λ. While for short square well chain fluids, longer the chain length, larger the contribution of |t|(2β). The molecular configuration greatly influences the critical asymmetry: a short soft chain fluid shows weaker critical asymmetry than a stiff chain fluid with same chain length.

Soil moisture retrieval by active/passive microwave remote sensing data

NASA Astrophysics Data System (ADS)

Wu, Shengli; Yang, Lijuan

2012-09-01

This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.

Storage and computationally efficient permutations of factorized covariance and square-root information arrays

NASA Technical Reports Server (NTRS)

Muellerschoen, R. J.

1988-01-01

A unified method to permute vector stored Upper triangular Diagonal factorized covariance and vector stored upper triangular Square Root Information arrays is presented. The method involves cyclic permutation of the rows and columns of the arrays and retriangularization with fast (slow) Givens rotations (reflections). Minimal computation is performed, and a one dimensional scratch array is required. To make the method efficient for large arrays on a virtual memory machine, computations are arranged so as to avoid expensive paging faults. This method is potentially important for processing large volumes of radio metric data in the Deep Space Network.

Thermal Noise Limit in Frequency Stabilization of Lasers with Rigid Cavities

NASA Technical Reports Server (NTRS)

Numata, Kenji; Kemery, Amy; Camp, Jordan

2004-01-01

We evaluated thermal noise (Brownian motion) in a rigid reference cavity used for frequency stabilization of lasers, based on the mechanical loss of cavity materials and the numerical analysis of the mirror-spacer mechanics with t.he direct application of the fluctuation dissipation theorem. This noise sets a fundamental limit for the frequency stability achieved with a rigid frequency- reference cavity of order 1 Hz/square root Hz(0.01 Hz/square root Hz) at 10 mHz (100 Hz) at room temperature. This level coincides with the world-highest level stabilization results.

Longitudinal double-spin asymmetry and cross section for inclusive jet production in polarized proton collisions at square root of s = 200 GeV.

PubMed

Abelev, B I; Aggarwal, M M; Ahammed, Z; Amonett, J; Anderson, B D; Anderson, M; Arkhipkin, D; Averichev, G S; Bai, Y; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Bekele, S; Belaga, V V; Bellingeri-Laurikainen, A; Bellwied, R; Benedosso, F; Bhardwaj, S; Bhasin, A; Bhati, A K; Bichsel, H; Bielcik, J; Bielcikova, J; Bland, L C; Blyth, S-L; Bonner, B E; Botje, M; Bouchet, J; Brandin, A V; Bravar, A; Burton, T P; Bystersky, M; Cadman, R V; Cai, X Z; Caines, H; Sánchez, M Calderón de la Barca; Castillo, J; Catu, O; Cebra, D; Chajecki, Z; Chaloupka, P; Chattopadhyay, S; Chen, H F; Chen, J H; Cheng, J; Cherney, M; Chikanian, A; Christie, W; Coffin, J P; Cormier, T M; Cosentino, M R; Cramer, J G; Crawford, H J; Das, D; Das, S; Dash, S; Daugherity, M; de Moura, M M; Dedovich, T G; Dephillips, M; Derevschikov, A A; Didenko, L; Dietel, T; Djawotho, P; Dogra, S M; Dong, W J; Dong, X; Draper, J E; Du, F; Dunin, V B; Dunlop, J C; Mazumdar, M R Dutta; Eckardt, V; Edwards, W R; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Estienne, M; Fachini, P; Fatemi, R; Fedorisin, J; Filip, P; Finch, E; Fine, V; Fisyak, Y; Fu, J; Gagliardi, C A; Gaillard, L; Ganti, M S; Ghazikhanian, V; Ghosh, P; Gonzalez, J E; Gorbunov, Y G; Gos, H; Grebenyuk, O; Grosnick, D; Guertin, S M; Guimaraes, K S F F; Gupta, N; Gutierrez, T D; Haag, B; Hallman, T J; Hamed, A; Harris, J W; He, W; Heinz, M; Henry, T W; Hepplemann, S; Hippolyte, B; Hirsch, A; Hjort, E; Hoffman, A M; Hoffmann, G W; Horner, M J; Huang, H Z; Huang, S L; Hughes, E W; Humanic, T J; Igo, G; Jacobs, P; Jacobs, W W; Jakl, P; Jia, F; Jiang, H; Jones, P G; Judd, E G; Kabana, S; Kang, K; Kapitan, J; Kaplan, M; Keane, D; Kechechyan, A; Khodyrev, V Yu; Kim, B C; Kiryluk, J; Kisiel, A; Kislov, E M; Klein, S R; Kocoloski, A; Koetke, D D; Kollegger, T; Kopytine, M; Kotchenda, L; Kouchpil, V; Kowalik, K L; Kramer, M; Kravtsov, P; Kravtsov, V I; Krueger, K; Kuhn, C; Kulikov, A I; Kumar, A; Kuznetsov, A A; Lamont, M A C; Landgraf, J M; Lange, S; LaPointe, S; Laue, F; Lauret, J; Lebedev, A; Lednicky, R; Lee, C-H; Lehocka, S; LeVine, M J; Li, C; Li, Q; Li, Y; Lin, G; Lin, X; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, H; Liu, J; Liu, L; Liu, Z; Ljubicic, T; Llope, W J; Long, H; Longacre, R S; Love, W A; Lu, Y; Ludlam, T; Lynn, D; Ma, G L; Ma, J G; Ma, Y G; Magestro, D; Mahapatra, D P; Majka, R; Mangotra, L K; Manweiler, R; Margetis, S; Markert, C; Martin, L; Matis, H S; Matulenko, Yu A; McClain, C J; McShane, T S; Melnick, Yu; Meschanin, A; Millane, J; Miller, M L; Minaev, N G; Mioduszewski, S; Mironov, C; Mischke, A; Mishra, D K; Mitchell, J; Mohanty, B; Molnar, L; Moore, C F; Morozov, D A; Munhoz, M G; Nandi, B K; Nattrass, C; Nayak, T K; Nelson, J M; Netrakanti, P K; Nogach, L V; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Pachr, M; Pal, S K; Panebratsev, Y; Panitkin, S Y; Pavlinov, A I; Pawlak, T; Peitzmann, T; Perevoztchikov, V; Perkins, C; Peryt, W; Phatak, S C; Picha, R; Planinic, M; Pluta, J; Poljak, N; Porile, N; Porter, J; Poskanzer, A M; Potekhin, M; Potrebenikova, E; Potukuchi, B V K S; Prindle, D; Pruneau, C; Putschke, J; Rakness, G; Raniwala, R; Raniwala, S; Ray, R L; Razin, S V; Reinnarth, J; Relyea, D; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevskiy, O V; Romero, J L; Rose, A; Roy, C; Ruan, L; Russcher, M J; Sahoo, R; Sakuma, T; Salur, S; Sandweiss, J; Sarsour, M; Sazhin, P S; Schambach, J; Scharenberg, R P; Schmitz, N; Seger, J; Selyuzhenkov, I; Seyboth, P; Shabetai, A; Shahaliev, E; Shao, M; Sharma, M; Shen, W Q; Shimanskiy, S S; Sichtermann, E P; Simon, F; Singaraju, R N; Smirnov, N; Snellings, R; Sood, G; Sorensen, P; Sowinski, J; Speltz, J; Spinka, H M; Srivastava, B; Stadnik, A; Stanislaus, T D S; Stock, R; Stolpovsky, A; Strikhanov, M; Stringfellow, B; Suaide, A A P; Sugarbaker, E; Sumbera, M; Sun, Z; Surrow, B; Swanger, M; Symons, T J M; Szanto de Toledo, A; Tai, A; Takahashi, J; Tang, A H; Tarnowsky, T; Thein, D; Thomas, J H; Timmins, A R; Timoshenko, S; Tokarev, M; Trainor, T A; Trentalange, S; Tribble, R E; Tsai, O D; Ulery, J; Ullrich, T; Underwood, D G; Buren, G Van; van der Kolk, N; van Leeuwen, M; Molen, A M Vander; Varma, R; Vasilevski, I M; Vasiliev, A N; Vernet, R; Vigdor, S E; Viyogi, Y P; Vokal, S; Voloshin, S A; Waggoner, W T; Wang, F; Wang, G; Wang, J S; Wang, X L; Wang, Y; Watson, J W; Webb, J C; Westfall, G D; Wetzler, A; Whitten, C; Wieman, H; Wissink, S W; Witt, R; Wood, J; Wu, J; Xu, N; Xu, Q H; Xu, Z; Yepes, P; Yoo, I-K; Yurevich, V I; Zhan, W; Zhang, H; Zhang, W M; Zhang, Y; Zhang, Z P; Zhao, Y; Zhong, C; Zoulkarneev, R; Zoulkarneeva, Y; Zubarev, A N; Zuo, J X

2006-12-22

We report a measurement of the longitudinal double-spin asymmetry A(LL) and the differential cross section for inclusive midrapidity jet production in polarized proton collisions at square root of s = 200 GeV. The cross section data cover transverse momenta 5 < pT < 50 GeV/c and agree with next-to-leading order perturbative QCD evaluations. The A(LL) data cover 5 < pT < 17 GeV/c and disfavor at 98% C.L. maximal positive gluon polarization in the polarized nucleon.

Narrowing of the balance function with centrality in Au+Au collisions at the square root of SNN = 130 GeV.

PubMed

Adams, J; Adler, C; Ahammed, Z; Allgower, C; Amonett, J; Anderson, B D; Anderson, M; Averichev, G S; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Bekele, S; Belaga, V V; Bellwied, R; Berger, J; Bichsel, H; Billmeier, A; Bland, L C; Blyth, C O; Bonner, B E; Boucham, A; Brandin, A; Bravar, A; Cadman, R V; Caines, H; Calderónde la Barca Sánchez, M; Cardenas, A; Carroll, J; Castillo, J; Castro, M; Cebra, D; Chaloupka, P; Chattopadhyay, S; Chen, Y; Chernenko, S P; Cherney, M; Chikanian, A; Choi, B; Christie, W; Coffin, J P; Cormier, T M; Corral, M M; Cramer, J G; Crawford, H J; Derevschikov, A A; Didenko, L; Dietel, T; Draper, J E; Dunin, V B; Dunlop, J C; Eckardt, V; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Fachini, P; Faine, V; Faivre, J; Fatemi, R; Filimonov, K; Finch, E; Fisyak, Y; Flierl, D; Foley, K J; Fu, J; Gagliardi, C A; Gagunashvili, N; Gans, J; Gaudichet, L; Germain, M; Geurts, F; Ghazikhanian, V; Grachov, O; Grigoriev, V; Guedon, M; Guertin, S M; Gushin, E; Hallman, T J; Hardtke, D; Harris, J W; Heinz, M; Henry, T W; Heppelmann, S; Herston, T; Hippolyte, B; Hirsch, A; Hjort, E; Hoffmann, G W; Horsley, M; Huang, H Z; Humanic, T J; Igo, G; Ishihara, A; Ivanshin, Yu I; Jacobs, P; Jacobs, W W; Janik, M; Johnson, I; Jones, P G; Judd, E G; Kaneta, M; Kaplan, M; Keane, D; Kiryluk, J; Kisiel, A; Klay, J; Klein, S R; Klyachko, A; Kollegger, T; Konstantinov, A S; Kopytine, M; Kotchenda, L; Kovalenko, A D; Kramer, M; Kravtsov, P; Krueger, K; Kuhn, C; Kulikov, A I; Kunde, G J; Kunz, C L; Kutuev, R Kh; Kuznetsov, A A; Lamont, M A C; Landgraf, J M; Lange, S; Lansdell, C P; Lasiuk, B; Laue, F; Lauret, J; Lebedev, A; Lednický, R; Leontiev, V M; LeVine, M J; Li, Q; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, L; Liu, Z; Liu, Q J; Ljubicic, T; Llope, W J; Long, H; Longacre, R S; Lopez-Noriega, M; Love, W A; Ludlam, T; Lynn, D; Ma, J; Magestro, D; Majka, R; Margetis, S; Markert, C; Martin, L; Marx, J; Matis, H S; Matulenko, Yu A; McShane, T S; Meissner, F; Melnick, Yu; Meschanin, A; Messer, M; Miller, M L; Milosevich, Z; Minaev, N G; Mitchell, J; Moore, C F; Morozov, V; de Moura, M M; Munhoz, M G; Nelson, J M; Nevski, P; Nikitin, V A; Nogach, L V; Norman, B; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Paic, G; Pandey, S U; Panebratsev, Y; Panitkin, S Y; Pavlinov, A I; Pawlak, T; Perevoztchikov, V; Peryt, W; Petrov, V A; Planinic, M; Pluta, J; Porile, N; Porter, J; Poskanzer, A M; Potrebenikova, E; Prindle, D; Pruneau, C; Putschke, J; Rai, G; Rakness, G; Ravel, O; Ray, R L; Razin, S V; Reichhold, D; Reid, J G; Renault, G; Retiere, F; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevski, O V; Romero, J L; Rose, A; Roy, C; Rykov, V; Sakrejda, I; Salur, S; Sandweiss, J; Savin, I; Schambach, J; Scharenberg, R P; Schmitz, N; Schroeder, L S; Schüttauf, A; Schweda, K; Seger, J; Seliverstov, D; Seyboth, P; Shahaliev, E; Shestermanov, K E; Shimanskii, S S; Simon, F; Skoro, G; Smirnov, N; Snellings, R; Sorensen, P; Sowinski, J; Spinka, H M; Srivastava, B; Stephenson, E J; Stock, R; Stolpovsky, A; Strikhanov, M; Stringfellow, B; Struck, C; Suaide, A A P; Sugarbaker, E; Suire, C; Sumbera, M; Surrow, B; Symons, T J M; de Toledo, A Szanto; Szarwas, P; Tai, A; Takahashi, J; Tang, A H; Thein, D; Thomas, J H; Thompson, M; Tikhomirov, V; Tokarev, M; Tonjes, M B; Trainor, T A; Trentalange, S; Tribble, R E; Trofimov, V; Tsai, O; Ullrich, T; Underwood, D G; Van Buren, G; Vander Molen, A M; Vasilevski, I M; Vasiliev, A N; Vigdor, S E; Voloshin, S A; Wang, F; Ward, H; Watson, J W; Wells, R; Westfall, G D; Whitten, C; Wieman, H; Willson, R; Wissink, S W; Witt, R; Wood, J; Xu, N; Xu, Z; Yakutin, A E; Yamamoto, E; Yang, J; Yepes, P; Yurevich, V I; Zanevski, Y V; Zborovský, I; Zhang, H; Zhang, W M; Zoulkarneev, R; Zubarev, A N

2003-05-02

The balance function is a new observable based on the principle that charge is locally conserved when particles are pair produced. Balance functions have been measured for charged particle pairs and identified charged pion pairs in Au+Au collisions at the square root of SNN = 130 GeV at the Relativistic Heavy Ion Collider using STAR. Balance functions for peripheral collisions have widths consistent with model predictions based on a superposition of nucleon-nucleon scattering. Widths in central collisions are smaller, consistent with trends predicted by models incorporating late hadronization.

Tough cryogenic alloys from the Fe-Mn and Fe-Mn-Cr systems

NASA Technical Reports Server (NTRS)

Schanfein, M. J.; Zackay, V. F.; Morris, J. W., Jr.

1974-01-01

By adjusting composition, metastable gamma (austenite) and epsilon (hexagonal) martensite may be retained in Fe-Mn and Fe-Mn-Cr alloys and used to impact toughness through the TRIP mechanism. The resulting alloys have excellent toughness at cryogenic temperatures. The best alloys obtained to date are: Fe-20Mn, with sigma (sub y) = 79ksi and K sub IC = 275ksi square root of (in) at 77 K, and Fc-16Mn-8Cr, with sigma sub y = 85ksi and K sub IC = 72ksi square root of (in) at 77 K.

Search for the Higgs boson using neural networks in events with missing energy and b-quark jets in pp collisions at square root(s) = 1.96 TeV.

PubMed

Aaltonen, T; Adelman, J; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'Orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; d'Errico, M; Di Canto, A; di Giovanni, G P; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, T; Dube, S; Ebina, K; Elagin, A; Erbacher, R; Errede, D; Errede, S; Ershaidat, N; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Group, R C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Hughes, R E; Hurwitz, M; Husemann, U; Hussein, M; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leone, S; Lewis, J D; Lin, C-J; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Lovas, L; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Mastrandrea, P; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Mesropian, C; Miao, T; Mietlicki, D; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramanov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Potamianos, K; Poukhov, O; Prokoshin, F; Pronko, A; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Rutherford, B; Saarikko, H; Safonov, A; Sakumoto, W K; Santi, L; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Simonenko, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Suh, J S; Sukhanov, A; Suslov, I; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wolfe, H; Wright, T; Wu, X; Würthwein, F; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zhang, X; Zheng, Y; Zucchelli, S

2010-04-09

We report on a search for the standard model Higgs boson produced in association with a W or Z boson in pp collisions at square root(s)=1.96 TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb(-1). We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a b hadron. We find good agreement between data and background predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110 GeV/c(2) to 150 GeV/c(2). For a mass of 115 GeV/c(2) the observed (expected) limit is 6.9 (5.6) times the standard model prediction.

Search for the production of scalar bottom quarks in pp collisions at square root(s) = 1.96 TeV.

PubMed

Aaltonen, T; Adelman, J; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'Orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; d'Errico, M; Di Canto, A; di Giovanni, G P; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, T; Dube, S; Ebina, K; Elagin, A; Erbacher, R; Errede, D; Errede, S; Ershaidat, N; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Group, R C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Hughes, R E; Hurwitz, M; Husemann, U; Hussein, M; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leone, S; Lewis, J D; Lin, C-J; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Lovas, L; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Mastrandrea, P; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Mesropian, C; Miao, T; Mietlicki, D; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramanov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Potamianos, K; Poukhov, O; Prokoshin, F; Pronko, A; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Rutherford, B; Saarikko, H; Safonov, A; Sakumoto, W K; Santi, L; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Simonenko, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Suh, J S; Sukhanov, A; Suslov, I; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wolfe, H; Wright, T; Wu, X; Würthwein, F; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zhang, X; Zheng, Y; Zucchelli, S

2010-08-20

We report on a search for direct scalar bottom quark (sbottom) pair production in pp collisions at square root(s) = 1.96 TeV, in events with large missing transverse energy and two jets of hadrons in the final state, where at least one of the jets is required to be identified as originating from a b quark. The study uses a collider detector at Fermilab Run II data sample corresponding to 2.65 fb(-1) of integrated luminosity. The data are in agreement with the standard model. In an R-parity conserving minimal supersymmetric scenario, and assuming that the sbottom decays exclusively into a bottom quark and a neutralino, 95% confidence-level upper limits on the sbottom pair production cross section of 0.1 pb are obtained. For neutralino masses below 70 GeV/c2, sbottom masses up to 230 GeV/c2 are excluded at 95% confidence level.

Rapid Detection of Volatile Oil in Mentha haplocalyx by Near-Infrared Spectroscopy and Chemometrics.

PubMed

Yan, Hui; Guo, Cheng; Shao, Yang; Ouyang, Zhen

2017-01-01

Near-infrared spectroscopy combined with partial least squares regression (PLSR) and support vector machine (SVM) was applied for the rapid determination of chemical component of volatile oil content in Mentha haplocalyx . The effects of data pre-processing methods on the accuracy of the PLSR calibration models were investigated. The performance of the final model was evaluated according to the correlation coefficient ( R ) and root mean square error of prediction (RMSEP). For PLSR model, the best preprocessing method combination was first-order derivative, standard normal variate transformation (SNV), and mean centering, which had of 0.8805, of 0.8719, RMSEC of 0.091, and RMSEP of 0.097, respectively. The wave number variables linking to volatile oil are from 5500 to 4000 cm-1 by analyzing the loading weights and variable importance in projection (VIP) scores. For SVM model, six LVs (less than seven LVs in PLSR model) were adopted in model, and the result was better than PLSR model. The and were 0.9232 and 0.9202, respectively, with RMSEC and RMSEP of 0.084 and 0.082, respectively, which indicated that the predicted values were accurate and reliable. This work demonstrated that near infrared reflectance spectroscopy with chemometrics could be used to rapidly detect the main content volatile oil in M. haplocalyx . The quality of medicine directly links to clinical efficacy, thus, it is important to control the quality of Mentha haplocalyx . Near-infrared spectroscopy combined with partial least squares regression (PLSR) and support vector machine (SVM) was applied for the rapid determination of chemical component of volatile oil content in Mentha haplocalyx . For SVM model, 6 LVs (less than 7 LVs in PLSR model) were adopted in model, and the result was better than PLSR model. It demonstrated that near infrared reflectance spectroscopy with chemometrics could be used to rapidly detect the main content volatile oil in Mentha haplocalyx . Abbreviations used: 1 st der: First-order derivative; 2 nd der: Second-order derivative; LOO: Leave-one-out; LVs: Latent variables; MC: Mean centering, NIR: Near-infrared; NIRS: Near infrared spectroscopy; PCR: Principal component regression, PLSR: Partial least squares regression; RBF: Radial basis function; RMSEC: Root mean square error of cross validation, RMSEC: Root mean square error of calibration; RMSEP: Root mean square error of prediction; SNV: Standard normal variate transformation; SVM: Support vector machine; VIP: Variable Importance in projection.

Kepler Mission: A Search for Terrestrial Planets

NASA Technical Reports Server (NTRS)

Koch, D.; Borucki, W.; Jenkens, J.; Dunham, E.; DeVincenzi, Donald (Technical Monitor)

2001-01-01

The Kepler Mission is a search for terrestrial planets by monitoring a large ensemble of stars for the periodic transits of planets. The mission consists of a 95-cm aperture photometer with 105 square deg field of view that monitors 100,000 dwarf stars for four years. The mission is unique in its ability to detect Earth-size planets in the habitable zone of other stars in the extended solar neighborhood. An Earth-size transit of a solar-like star causes a change in brightness of about 100 ppm. Laboratory testing has demonstrated that a total system noise level of 20 ppm is readily achievable on the timescale of transits. Earth-like transits have been created and reliably measured in an end-to-end system test that has all known sources of noise including, spacecraft jitter. To detect Earth-size planets, the photometer must be spaceborne; this also eliminates the day-night and seasonal cycle interruptions of ground-based observing. The photometer will stare at a single field of stars for four years, with an option to continue for two more years. This allows for detection of four transits of planets in Mars-like orbits and detection of planets even smaller than Earth especially for short period orbits, since the signal to noise improves as the square root of the number of transits observed. In addition to detection of planets, Kepler data are also useful for understanding the activity cycles and rotation rates of the stars observed. For the 3,000 stars brighter than mv= 11.4 p-mode oscillations are measured. The mission has been selected as one of three candidates for NASA's next Discovery mission.

Best of both worlds: combining pharma data and state of the art modeling technology to improve in Silico pKa prediction.

PubMed

Fraczkiewicz, Robert; Lobell, Mario; Göller, Andreas H; Krenz, Ursula; Schoenneis, Rolf; Clark, Robert D; Hillisch, Alexander

2015-02-23

In a unique collaboration between a software company and a pharmaceutical company, we were able to develop a new in silico pKa prediction tool with outstanding prediction quality. An existing pKa prediction method from Simulations Plus based on artificial neural network ensembles (ANNE), microstates analysis, and literature data was retrained with a large homogeneous data set of drug-like molecules from Bayer. The new model was thus built with curated sets of ∼14,000 literature pKa values (∼11,000 compounds, representing literature chemical space) and ∼19,500 pKa values experimentally determined at Bayer Pharma (∼16,000 compounds, representing industry chemical space). Model validation was performed with several test sets consisting of a total of ∼31,000 new pKa values measured at Bayer. For the largest and most difficult test set with >16,000 pKa values that were not used for training, the original model achieved a mean absolute error (MAE) of 0.72, root-mean-square error (RMSE) of 0.94, and squared correlation coefficient (R(2)) of 0.87. The new model achieves significantly improved prediction statistics, with MAE = 0.50, RMSE = 0.67, and R(2) = 0.93. It is commercially available as part of the Simulations Plus ADMET Predictor release 7.0. Good predictions are only of value when delivered effectively to those who can use them. The new pKa prediction model has been integrated into Pipeline Pilot and the PharmacophorInformatics (PIx) platform used by scientists at Bayer Pharma. Different output formats allow customized application by medicinal chemists, physical chemists, and computational chemists.

Evaluating uncertainties in multi-layer soil moisture estimation with support vector machines and ensemble Kalman filtering

NASA Astrophysics Data System (ADS)

Liu, Di; Mishra, Ashok K.; Yu, Zhongbo

2016-07-01

This paper examines the combination of support vector machines (SVM) and the dual ensemble Kalman filter (EnKF) technique to estimate root zone soil moisture at different soil layers up to 100 cm depth. Multiple experiments are conducted in a data rich environment to construct and validate the SVM model and to explore the effectiveness and robustness of the EnKF technique. It was observed that the performance of SVM relies more on the initial length of training set than other factors (e.g., cost function, regularization parameter, and kernel parameters). The dual EnKF technique proved to be efficient to improve SVM with observed data either at each time step or at a flexible time steps. The EnKF technique can reach its maximum efficiency when the updating ensemble size approaches a certain threshold. It was observed that the SVM model performance for the multi-layer soil moisture estimation can be influenced by the rainfall magnitude (e.g., dry and wet spells).

Sound diffraction at wall impedance discontinuities in a circular cylinder, investigated using Wiener-Hopf technique

NASA Technical Reports Server (NTRS)

Cho, Y. C.

1983-01-01

Rigorous solutions are presented for sound diffraction in a circular cylinder with axial discontinuities of the wall admittance (or impedance). Analytical expressions are derived for the reflection and the transmission coefficients for duct modes. The results are discussed quantitatively in the limits of small admittance shifts (delta) and of low frequencies (ka). One of the results is the low frequency behavior of the reflection coefficient R(o) sub 00 of the fundamental mode. For the mode of a hardwall duct reflected from the junction with a softwall duct, (R(o) sub oo yields - (1-square root of (ka) square root of (2/i delta)); this result is in contrast to the frequency dependence of the reflection from the open end of a hardwall duct, for which R(o) sub oo yields - 1-(ka) squared/2 .

Nondestructive quantification of the soluble-solids content and the available acidity of apples by Fourier-transform near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Ying, Yibin; Liu, Yande; Tao, Yang

2005-09-01

This research evaluated the feasibility of using Fourier-transform near-infrared (FT-NIR) spectroscopy to quantify the soluble-solids content (SSC) and the available acidity (VA) in intact apples. Partial least-squares calibration models, obtained from several preprocessing techniques (smoothing, derivative, etc.) in several wave-number ranges were compared. The best models were obtained with the high coefficient determination (r) 0.940 for the SSC and a moderate r of 0.801 for the VA, root-mean-square errors of prediction of 0.272% and 0.053%, and root-mean-square errors of calibration of 0.261% and 0.046%, respectively. The results indicate that the FT-NIR spectroscopy yields good predictions of the SSC and also showed the feasibility of using it to predict the VA of apples.

Effect of root planing on surface topography: an in-vivo randomized experimental trial.

PubMed

Rosales-Leal, J I; Flores, A B; Contreras, T; Bravo, M; Cabrerizo-Vílchez, M A; Mesa, F

2015-04-01

The root surface topography exerts a major influence on clinical attachment and bacterial recolonization after root planing. In-vitro topographic studies have yielded variable results, and clinical studies are necessary to compare root surface topography after planing with current ultrasonic devices and with traditional manual instrumentation. The aim of this study was to compare the topography of untreated single-rooted teeth planed in vivo with a curette, a piezoelectric ultrasonic (PU) scraper or a vertically oscillating ultrasonic (VOU) scraper. In a randomized experimental trial of 19 patients, 44 single-rooted teeth were randomly assigned to one of four groups for: no treatment; manual root planing with a curette; root planing with a PU scraper; or root planing with a VOU scraper. Post-treatment, the teeth were extracted and their topography was analyzed in 124 observations with white-light confocal microscopy, measuring the roughness parameters arithmetic average height, root-mean-square roughness, maximum height of peaks, maximum depth of valleys, absolute height, skewness and kurtosis. The roughness values arithmetic average height and root-mean-square roughness were similar after each treatment and lower than after no treatment ( p < 0.05). Absolute height was lower in the VOU group than in the untreated ( p = 0.0026) and PU (p = 0.045) groups. Surface morphology was similar after the three treatments and was less irregular than in the untreated group. Values for the remaining roughness parameters were similar among all treatment groups ( p > 0.05). Both ultrasonic devices reduce the roughness, producing a similar topography to that observed after manual instrumentation with a curette, to which they appear to represent a valid alternative. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Red Wine Age Estimation by the Alteration of Its Color Parameters: Fourier Transform Infrared Spectroscopy as a Tool to Monitor Wine Maturation Time

PubMed Central

Basalekou, M.; Pappas, C.; Kotseridis, Y.; Tarantilis, P. A.; Kontaxakis, E.

2017-01-01

Color, phenolic content, and chemical age values of red wines made from Cretan grape varieties (Kotsifali, Mandilari) were evaluated over nine months of maturation in different containers for two vintages. The wines differed greatly on their anthocyanin profiles. Mid-IR spectra were also recorded with the use of a Fourier Transform Infrared Spectrophotometer in ZnSe disk mode. Analysis of Variance was used to explore the parameter's dependency on time. Determination models were developed for the chemical age indexes using Partial Least Squares (PLS) (TQ Analyst software) considering the spectral region 1830–1500 cm−1. The correlation coefficients (r) for chemical age index i were 0.86 for Kotsifali (Root Mean Square Error of Calibration (RMSEC) = 0.067, Root Mean Square Error of Prediction (RMSEP) = 0,115, and Root Mean Square Error of Validation (RMSECV) = 0.164) and 0.90 for Mandilari (RMSEC = 0.050, RMSEP = 0.040, and RMSECV = 0.089). For chemical age index ii the correlation coefficients (r) were 0.86 and 0.97 for Kotsifali (RMSEC 0.044, RMSEP = 0.087, and RMSECV = 0.214) and Mandilari (RMSEC = 0.024, RMSEP = 0.033, and RMSECV = 0.078), respectively. The proposed method is simpler, less time consuming, and more economical and does not require chemical reagents. PMID:29225994

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

Quick method (FT-NIR) for the determination of oil and major fatty acids content in whole achenes of milk thistle (Silybum marianum (L.) Gaertn.).

PubMed

Koláčková, Pavla; Růžičková, Gabriela; Gregor, Tomáš; Šišperová, Eliška

2015-08-30

Calibration models for the Fourier transform-near infrared (FT-NIR) instrument were developed for quick and non-destructive determination of oil and fatty acids in whole achenes of milk thistle. Samples with a range of oil and fatty acid levels were collected and their transmittance spectra were obtained by the FT-NIR instrument. Based on these spectra and data gained by the means of the reference method - Soxhlet extraction and gas chromatography (GC) - calibration models were created by means of partial least square (PLS) regression analysis. Precision and accuracy of the calibration models was verified via the cross-validation of validation samples whose spectra were not part of the calibration model and also according to the root mean square error of prediction (RMSEP), root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV) and the validation coefficient of determination (R(2) ). R(2) for whole seeds were 0.96, 0.96, 0.83 and 0.67 and the RMSEP values were 0.76, 1.68, 1.24, 0.54 for oil, linoleic (C18:2), oleic (C18:1) and palmitic (C16:0) acids, respectively. The calibration models are appropriate for the non-destructive determination of oil and fatty acids levels in whole seeds of milk thistle. © 2014 Society of Chemical Industry.

Parameterizing the binding properties of dissolved organic matter with default values skews the prediction of copper solution speciation and ecotoxicity in soil.

PubMed

Djae, Tanalou; Bravin, Matthieu N; Garnier, Cédric; Doelsch, Emmanuel

2017-04-01

Parameterizing speciation models by setting the percentage of dissolved organic matter (DOM) that is reactive (% r-DOM) toward metal cations at a single 65% default value is very common in predictive ecotoxicology. The authors tested this practice by comparing the free copper activity (pCu 2+  = -log 10 [Cu 2+ ]) measured in 55 soil sample solutions with pCu 2+ predicted with the Windermere humic aqueous model (WHAM) parameterized by default. Predictions of Cu toxicity to soil organisms based on measured or predicted pCu 2+ were also compared. Default WHAM parameterization substantially skewed the prediction of measured pCu 2+ by up to 2.7 pCu 2+ units (root mean square residual = 0.75-1.3) and subsequently the prediction of Cu toxicity for microbial functions, invertebrates, and plants by up to 36%, 45%, and 59% (root mean square residuals ≤9 %, 11%, and 17%), respectively. Reparametrizing WHAM by optimizing the 2 DOM binding properties (i.e., % r-DOM and the Cu complexation constant) within a physically realistic value range much improved the prediction of measured pCu 2+ (root mean square residual = 0.14-0.25). Accordingly, this WHAM parameterization successfully predicted Cu toxicity for microbial functions, invertebrates, and plants (root mean square residual ≤3.4%, 4.4%, and 5.8%, respectively). Thus, it is essential to account for the real heterogeneity in DOM binding properties for relatively accurate prediction of Cu speciation in soil solution and Cu toxic effects on soil organisms. Environ Toxicol Chem 2017;36:898-905. © 2016 SETAC. © 2016 SETAC.

Analysis of S-box in Image Encryption Using Root Mean Square Error Method

NASA Astrophysics Data System (ADS)

Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

2012-07-01

The use of substitution boxes (S-boxes) in encryption applications has proven to be an effective nonlinear component in creating confusion and randomness. The S-box is evolving and many variants appear in literature, which include advanced encryption standard (AES) S-box, affine power affine (APA) S-box, Skipjack S-box, Gray S-box, Lui J S-box, residue prime number S-box, Xyi S-box, and S8 S-box. These S-boxes have algebraic and statistical properties which distinguish them from each other in terms of encryption strength. In some circumstances, the parameters from algebraic and statistical analysis yield results which do not provide clear evidence in distinguishing an S-box for an application to a particular set of data. In image encryption applications, the use of S-boxes needs special care because the visual analysis and perception of a viewer can sometimes identify artifacts embedded in the image. In addition to existing algebraic and statistical analysis already used for image encryption applications, we propose an application of root mean square error technique, which further elaborates the results and enables the analyst to vividly distinguish between the performances of various S-boxes. While the use of the root mean square error analysis in statistics has proven to be effective in determining the difference in original data and the processed data, its use in image encryption has shown promising results in estimating the strength of the encryption method. In this paper, we show the application of the root mean square error analysis to S-box image encryption. The parameters from this analysis are used in determining the strength of S-boxes

Minimum error discrimination between similarity-transformed quantum states

NASA Astrophysics Data System (ADS)

Jafarizadeh, M. A.; Sufiani, R.; Mazhari Khiavi, Y.

2011-07-01

Using the well-known necessary and sufficient conditions for minimum error discrimination (MED), we extract an equivalent form for the MED conditions. In fact, by replacing the inequalities corresponding to the MED conditions with an equivalent but more suitable and convenient identity, the problem of mixed state discrimination with optimal success probability is solved. Moreover, we show that the mentioned optimality conditions can be viewed as a Helstrom family of ensembles under some circumstances. Using the given identity, MED between N similarity transformed equiprobable quantum states is investigated. In the case that the unitary operators are generating a set of irreducible representation, the optimal set of measurements and corresponding maximum success probability of discrimination can be determined precisely. In particular, it is shown that for equiprobable pure states, the optimal measurement strategy is the square-root measurement (SRM), whereas for the mixed states, SRM is not optimal. In the case that the unitary operators are reducible, there is no closed-form formula in the general case, but the procedure can be applied in each case in accordance to that case. Finally, we give the maximum success probability of optimal discrimination for some important examples of mixed quantum states, such as generalized Bloch sphere m-qubit states, spin-j states, particular nonsymmetric qudit states, etc.

Daily Reservoir Inflow Forecasting using Deep Learning with Downscaled Multi-General Circulation Models (GCMs) Platform

NASA Astrophysics Data System (ADS)

Li, D.; Fang, N. Z.

2017-12-01

Dallas-Fort Worth Metroplex (DFW) has a population of over 7 million depending on many water supply reservoirs. The reservoir inflow plays a vital role in water supply decision making process and long-term strategic planning for the region. This paper demonstrates a method of utilizing deep learning algorithms and multi-general circulation model (GCM) platform to forecast reservoir inflow for three reservoirs within the DFW: Eagle Mountain Lake, Lake Benbrook and Lake Arlington. Ensemble empirical mode decomposition was firstly employed to extract the features, which were then represented by the deep belief networks (DBNs). The first 75 years of the historical data (1940 -2015) were used to train the model, while the last 2 years of the data (2016-2017) were used for the model validation. The weights of each DBN gained from the training process were then applied to establish a neural network (NN) that was able to forecast reservoir inflow. Feature predictors used for the forecasting model were generated from weather forecast results of the downscaled multi-GCM platform for the North Texas region. By comparing root mean square error (RMSE) and mean bias error (MBE) with the observed data, the authors found that the deep learning with downscaled multi-GCM platform is an effective approach in the reservoir inflow forecasting.

A Method for Snow Reanalysis: The Sierra Nevada (USA) Example

NASA Technical Reports Server (NTRS)

Girotto, Manuela; Margulis, Steven; Cortes, Gonzalo; Durand, Michael

2017-01-01

This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.

Evaluation of precipitation forecasts from 3D-Var and hybrid GSI-based system during Indian summer monsoon 2015

NASA Astrophysics Data System (ADS)

Singh, Sanjeev Kumar; Prasad, V. S.

2018-02-01

This paper presents a systematic investigation of medium-range rainfall forecasts from two versions of the National Centre for Medium Range Weather Forecasting (NCMRWF)-Global Forecast System based on three-dimensional variational (3D-Var) and hybrid analysis system namely, NGFS and HNGFS, respectively, during Indian summer monsoon (June-September) 2015. The NGFS uses gridpoint statistical interpolation (GSI) 3D-Var data assimilation system, whereas HNGFS uses hybrid 3D ensemble-variational scheme. The analysis includes the evaluation of rainfall fields and comparisons of rainfall using statistical score such as mean precipitation, bias, correlation coefficient, root mean square error and forecast improvement factor. In addition to these, categorical scores like Peirce skill score and bias score are also computed to describe particular aspects of forecasts performance. The comparison results of mean precipitation reveal that both the versions of model produced similar large-scale feature of Indian summer monsoon rainfall for day-1 through day-5 forecasts. The inclusion of fully flow-dependent background error covariance significantly improved the wet biases in HNGFS over the Indian Ocean. The forecast improvement factor and Peirce skill score in the HNGFS have also found better than NGFS for day-1 through day-5 forecasts.

Assimilation of Terrestrial Water Storage from GRACE in a Snow-Dominated Basin

NASA Technical Reports Server (NTRS)

Forman, Barton A.; Reichle, R. H.; Rodell, M.

2011-01-01

Terrestrial water storage (TWS) information derived from Gravity Recovery and Climate Experiment (GRACE) measurements is assimilated into a land surface model over the Mackenzie River basin located in northwest Canada. Assimilation is conducted using an ensemble Kalman smoother (EnKS). Model estimates with and without assimilation are compared against independent observational data sets of snow water equivalent (SWE) and runoff. For SWE, modest improvements in mean difference (MD) and root mean squared difference (RMSD) are achieved as a result of the assimilation. No significant differences in temporal correlations of SWE resulted. Runoff statistics of MD remain relatively unchanged while RMSD statistics, in general, are improved in most of the sub-basins. Temporal correlations are degraded within the most upstream sub-basin, but are, in general, improved at the downstream locations, which are more representative of an integrated basin response. GRACE assimilation using an EnKS offers improvements in hydrologic state/flux estimation, though comparisons with observed runoff would be enhanced by the use of river routing and lake storage routines within the prognostic land surface model. Further, GRACE hydrology products would benefit from the inclusion of better constrained models of post-glacial rebound, which significantly affects GRACE estimates of interannual hydrologic variability in the Mackenzie River basin.

Asymptotic coincidence of the statistics for degenerate and non-degenerate correlated real Wishart ensembles

NASA Astrophysics Data System (ADS)

Wirtz, Tim; Kieburg, Mario; Guhr, Thomas

2017-06-01

The correlated Wishart model provides the standard benchmark when analyzing time series of any kind. Unfortunately, the real case, which is the most relevant one in applications, poses serious challenges for analytical calculations. Often these challenges are due to square root singularities which cannot be handled using common random matrix techniques. We present a new way to tackle this issue. Using supersymmetry, we carry out an anlaytical study which we support by numerical simulations. For large but finite matrix dimensions, we show that statistical properties of the fully correlated real Wishart model generically approach those of a correlated real Wishart model with doubled matrix dimensions and doubly degenerate empirical eigenvalues. This holds for the local and global spectral statistics. With Monte Carlo simulations we show that this is even approximately true for small matrix dimensions. We explicitly investigate the k-point correlation function as well as the distribution of the largest eigenvalue for which we find a surprisingly compact formula in the doubly degenerate case. Moreover we show that on the local scale the k-point correlation function exhibits the sine and the Airy kernel in the bulk and at the soft edges, respectively. We also address the positions and the fluctuations of the possible outliers in the data.

Free Energy Landscape - Settlements of Key Residues.

NASA Astrophysics Data System (ADS)

Aroutiounian, Svetlana

2007-03-01

FEL perspective in studies of protein folding transitions reflects notion that since there are ˜10^N conformations to scan in search of lowest free energy state, random search is beyond biological timescale. Protein folding must follow certain fel pathways and folding kinetics of evolutionary selected proteins dominates kinetic traps. Good model for functional robustness of natural proteins - coarse-grained model protein is not very accurate but affords bringing simulations closer to biological realm; Go-like potential secures the fel funnel shape; biochemical contacts signify the funnel bottleneck. Boltzmann-weighted ensemble of protein conformations and histogram method are used to obtain from MC sampling of protein conformational space the approximate probability distribution. The fel is F(rmsd) = -1/βLn[Hist(rmsd)], β=kBT and rmsd is root-mean-square-deviation from native conformation. The sperm whale myoglobin has rich dynamic behavior, is small and large - on computational scale, has a symmetry in architecture and unusual sextet of residue pairs. Main idea: there is a mathematical relation between protein fel and a key residues set providing stability to folding transition. Is the set evolutionary conserved also for functional reasons? Hypothesis: primary sequence determines the key residues positions conserved as stabilizers and the fel is the battlefield for the folding stability. Preliminary results: primary sequence - not the architecture, is the rule settler, indeed.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

2018-01-01

Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-07-02

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2.« less

Minimum error discrimination between similarity-transformed quantum states

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

Jafarizadeh, M. A.; Institute for Studies in Theoretical Physics and Mathematics, Tehran 19395-1795; Research Institute for Fundamental Sciences, Tabriz 51664

2011-07-15

Using the well-known necessary and sufficient conditions for minimum error discrimination (MED), we extract an equivalent form for the MED conditions. In fact, by replacing the inequalities corresponding to the MED conditions with an equivalent but more suitable and convenient identity, the problem of mixed state discrimination with optimal success probability is solved. Moreover, we show that the mentioned optimality conditions can be viewed as a Helstrom family of ensembles under some circumstances. Using the given identity, MED between N similarity transformed equiprobable quantum states is investigated. In the case that the unitary operators are generating a set of irreduciblemore » representation, the optimal set of measurements and corresponding maximum success probability of discrimination can be determined precisely. In particular, it is shown that for equiprobable pure states, the optimal measurement strategy is the square-root measurement (SRM), whereas for the mixed states, SRM is not optimal. In the case that the unitary operators are reducible, there is no closed-form formula in the general case, but the procedure can be applied in each case in accordance to that case. Finally, we give the maximum success probability of optimal discrimination for some important examples of mixed quantum states, such as generalized Bloch sphere m-qubit states, spin-j states, particular nonsymmetric qudit states, etc.« less

Analysis of EMG patterns of control subjects and subjects with ACL deficiency during an unanticipated walking cut task.

PubMed

Houck, Jeff R; Wilding, Gregory E; Gupta, Resmi; De Haven, Kenneth E; Maloney, Mike

2007-04-01

The purpose of this study was to describe the muscle activation patterns of the vastus lateralis (VL), medial hamstrings (MH) and lateral hamstrings (LH) associated with subjects that were anterior cruciate ligament (ACL) deficient and controls. A total of 54 subjects participated in this study including 25 ACL deficient subjects subdivided into copers (n=9) and non-copers (n=16) using clinical criteria. Muscle activation patterns were recorded at 1000 Hz during an unanticipated side step cut task. The root mean square processed data (time constant 11 ms) were ensemble averaged from 20% of stance before heel strike to toe off. Using the first five harmonics of the Fourier Coefficients as features, muscle activation patterns were divided using a cluster analysis algorithm. A majority (76-93%) of control subjects used three muscle activation patterns for each muscle. The coper group preferentially used a particular VL and MH activation pattern >2 times more frequently than controls. The non-coper group also preferentially used a MH activation pattern >2 times more frequently than controls and utilized a unique MH and LH activation pattern, distinct from the copers and controls. Specific muscle activation patterns distinguish subsets of subjects that are healthy and injured, suggesting possible patterns of muscle activation that contribute to coping status.

Vegetation root zone storage and rooting depth, derived from local calibration of a global hydrological model

NASA Astrophysics Data System (ADS)

van der Ent, R.; Van Beek, R.; Sutanudjaja, E.; Wang-Erlandsson, L.; Hessels, T.; Bastiaanssen, W.; Bierkens, M. F.

2017-12-01

The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. Root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.

Vegetation root zone storage and rooting depth, derived from local calibration of a global hydrological model

NASA Astrophysics Data System (ADS)

van der Ent, Ruud; van Beek, Rens; Sutanudjaja, Edwin; Wang-Erlandsson, Lan; Hessels, Tim; Bastiaanssen, Wim; Bierkens, Marc

2017-04-01

The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. For root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.

Improving Marine Corps Assignment of SDAP Levels

DTIC Science & Technology

2013-03-01

Nettles , Colonel, USMC, M&RA (MPO). 15 Information Paper SDAP. 17 for a job or being able to fill the position at all, in addition to the potential to...Total 7850672.93 60132 130.557323 Root MSE = 6.2241... Root MSE = .26638 Adj R-squared = 0.0097 Residual 4577.29534 64507 .070958118

On Nth roots of positive operators

NASA Technical Reports Server (NTRS)

Brown, D. R.; Omalley, M. J.

1978-01-01

A bounded operator A on a Hilbert space H was positive. These operators were symmetric, and as such constitute a natural generalization of nonnegative real diagonal matrices. The following result is thus both well known and not surprising: A positive operator has a unique positive square root (under operator composition).

A Comparison of Normal and Elliptical Estimation Methods in Structural Equation Models.

ERIC Educational Resources Information Center

Schumacker, Randall E.; Cheevatanarak, Suchittra

Monte Carlo simulation compared chi-square statistics, parameter estimates, and root mean square error of approximation values using normal and elliptical estimation methods. Three research conditions were imposed on the simulated data: sample size, population contamination percent, and kurtosis. A Bentler-Weeks structural model established the…

An Examination of Statistical Power in Multigroup Dynamic Structural Equation Models

ERIC Educational Resources Information Center

Prindle, John J.; McArdle, John J.

2012-01-01

This study used statistical simulation to calculate differential statistical power in dynamic structural equation models with groups (as in McArdle & Prindle, 2008). Patterns of between-group differences were simulated to provide insight into how model parameters influence power approximations. Chi-square and root mean square error of…

Quality aspects of ex vivo root canal treatments done by undergraduate dental students using four different endodontic treatment systems.

PubMed

Jungnickel, Luise; Kruse, Casper; Vaeth, Michael; Kirkevang, Lise-Lotte

2018-04-01

To evaluate factors associated with treatment quality of ex vivo root canal treatments performed by undergraduate dental students using different endodontic treatment systems. Four students performed root canal treatment on 80 extracted human teeth using four endodontic treatment systems in designated treatment order following a Latin square design. Lateral seal and length of root canal fillings was radiographically assessed; for lateral seal, a graded visual scale was used. Treatment time was measured separately for access preparation, biomechanical root canal preparation, obturation and for the total procedure. Mishaps were registered. An ANOVA mirroring the Latin square design was performed. Use of machine-driven nickel-titanium systems resulted in overall better quality scores for lateral seal than use of the manual stainless-steel system. Among systems with machine-driven files, scores did not significantly differ. Use of machine-driven instruments resulted in shorter treatment time than manual instrumentation. Machine-driven systems with few files achieved shorter treatment times. With increasing number of treatments, root canal-filling quality increased, treatment time decreased; a learning curve was plotted. No root canal shaping file separated. The use of endodontic treatment systems with machine-driven files led to higher quality lateral seal compared to the manual system. The three contemporary machine-driven systems delivered comparable results regarding quality of root canal fillings; they were safe to use and provided a more efficient workflow than the manual technique. Increasing experience had a positive impact on the quality of root canal fillings while treatment time decreased.

Simulating the Generalized Gibbs Ensemble (GGE): A Hilbert space Monte Carlo approach

NASA Astrophysics Data System (ADS)

Alba, Vincenzo

By combining classical Monte Carlo and Bethe ansatz techniques we devise a numerical method to construct the Truncated Generalized Gibbs Ensemble (TGGE) for the spin-1/2 isotropic Heisenberg (XXX) chain. The key idea is to sample the Hilbert space of the model with the appropriate GGE probability measure. The method can be extended to other integrable systems, such as the Lieb-Liniger model. We benchmark the approach focusing on GGE expectation values of several local observables. As finite-size effects decay exponentially with system size, moderately large chains are sufficient to extract thermodynamic quantities. The Monte Carlo results are in agreement with both the Thermodynamic Bethe Ansatz (TBA) and the Quantum Transfer Matrix approach (QTM). Remarkably, it is possible to extract in a simple way the steady-state Bethe-Gaudin-Takahashi (BGT) roots distributions, which encode complete information about the GGE expectation values in the thermodynamic limit. Finally, it is straightforward to simulate extensions of the GGE, in which, besides the local integral of motion (local charges), one includes arbitrary functions of the BGT roots. As an example, we include in the GGE the first non-trivial quasi-local integral of motion.

Non-universal tracer diffusion in crowded media of non-inert obstacles.

PubMed

Ghosh, Surya K; Cherstvy, Andrey G; Metzler, Ralf

2015-01-21

We study the diffusion of a tracer particle, which moves in continuum space between a lattice of excluded volume, immobile non-inert obstacles. In particular, we analyse how the strength of the tracer-obstacle interactions and the volume occupancy of the crowders alter the diffusive motion of the tracer. From the details of partitioning of the tracer diffusion modes between trapping states when bound to obstacles and bulk diffusion, we examine the degree of localisation of the tracer in the lattice of crowders. We study the properties of the tracer diffusion in terms of the ensemble and time averaged mean squared displacements, the trapping time distributions, the amplitude variation of the time averaged mean squared displacements, and the non-Gaussianity parameter of the diffusing tracer. We conclude that tracer-obstacle adsorption and binding triggers a transient anomalous diffusion. From a very narrow spread of recorded individual time averaged trajectories we exclude continuous type random walk processes as the underlying physical model of the tracer diffusion in our system. For moderate tracer-crowder attraction the motion is found to be fully ergodic, while at stronger attraction strength a transient disparity between ensemble and time averaged mean squared displacements occurs. We also put our results into perspective with findings from experimental single-particle tracking and simulations of the diffusion of tagged tracers in dense crowded suspensions. Our results have implications for the diffusion, transport, and spreading of chemical components in highly crowded environments inside living cells and other structured liquids.

On the use of the noncentral chi-square density function for the distribution of helicopter spectral estimates

NASA Technical Reports Server (NTRS)

Garber, Donald P.

1993-01-01

A probability density function for the variability of ensemble averaged spectral estimates from helicopter acoustic signals in Gaussian background noise was evaluated. Numerical methods for calculating the density function and for determining confidence limits were explored. Density functions were predicted for both synthesized and experimental data and compared with observed spectral estimate variability.

Microcanonical ensemble simulation method applied to discrete potential fluids

NASA Astrophysics Data System (ADS)

Sastre, Francisco; Benavides, Ana Laura; Torres-Arenas, José; Gil-Villegas, Alejandro

2015-09-01

In this work we extend the applicability of the microcanonical ensemble simulation method, originally proposed to study the Ising model [A. Hüller and M. Pleimling, Int. J. Mod. Phys. C 13, 947 (2002), 10.1142/S0129183102003693], to the case of simple fluids. An algorithm is developed by measuring the transition rates probabilities between macroscopic states, that has as advantage with respect to conventional Monte Carlo NVT (MC-NVT) simulations that a continuous range of temperatures are covered in a single run. For a given density, this new algorithm provides the inverse temperature, that can be parametrized as a function of the internal energy, and the isochoric heat capacity is then evaluated through a numerical derivative. As an illustrative example we consider a fluid composed of particles interacting via a square-well (SW) pair potential of variable range. Equilibrium internal energies and isochoric heat capacities are obtained with very high accuracy compared with data obtained from MC-NVT simulations. These results are important in the context of the application of the Hüller-Pleimling method to discrete-potential systems, that are based on a generalization of the SW and square-shoulder fluids properties.

Improved estimation of anomalous diffusion exponents in single-particle tracking experiments

NASA Astrophysics Data System (ADS)

Kepten, Eldad; Bronshtein, Irena; Garini, Yuval

2013-05-01

The mean square displacement is a central tool in the analysis of single-particle tracking experiments, shedding light on various biophysical phenomena. Frequently, parameters are extracted by performing time averages on single-particle trajectories followed by ensemble averaging. This procedure, however, suffers from two systematic errors when applied to particles that perform anomalous diffusion. The first is significant at short-time lags and is induced by measurement errors. The second arises from the natural heterogeneity in biophysical systems. We show how to estimate and correct these two errors and improve the estimation of the anomalous parameters for the whole particle distribution. As a consequence, we manage to characterize ensembles of heterogeneous particles even for rather short and noisy measurements where regular time-averaged mean square displacement analysis fails. We apply this method to both simulations and in vivo measurements of telomere diffusion in 3T3 mouse embryonic fibroblast cells. The motion of telomeres is found to be subdiffusive with an average exponent constant in time. Individual telomere exponents are normally distributed around the average exponent. The proposed methodology has the potential to improve experimental accuracy while maintaining lower experimental costs and complexity.

Application of square-root filtering for spacecraft attitude control

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Schmidt, S. F.; Goka, T.

1978-01-01

Suitable digital algorithms are developed and tested for providing on-board precision attitude estimation and pointing control for potential use in the Landsat-D spacecraft. These algorithms provide pointing accuracy of better than 0.01 deg. To obtain necessary precision with efficient software, a six state-variable square-root Kalman filter combines two star tracker measurements to update attitude estimates obtained from processing three gyro outputs. The validity of the estimation and control algorithms are established, and the sensitivity of their performance to various error sources and software parameters are investigated by detailed digital simulation. Spacecraft computer memory, cycle time, and accuracy requirements are estimated.

J/Psi production in pp collisions at square root = 200 GeV at the BNL relativistic heavy ion collider.

PubMed

Cooper, Fred; Liu, Ming X; Nayak, Gouranga C

2004-10-22

We study J/psi production in pp collisions at BNL Relativistic Heavy Ion Collider (RHIC) within the PHENIX detector acceptance range using the color singlet and color octet mechanism which are based on perturbative QCD and nonrelativistic QCD. Here we show that the color octet mechanism reproduces the RHIC data for J/psi production in pp collisions with respect to the p(T) distribution, the rapidity distribution, and the total cross section at square root = 200 GeV. The color singlet mechanism leads to a relatively small contribution to the total cross section when compared to the octet contribution.

Advanced optical system for scanning-spot photorefractive keratectomy (PRK)

NASA Astrophysics Data System (ADS)

Mrochen, Michael; Wullner, Christian; Semchishen, Vladimir A.; Seiler, Theo

1999-06-01

Purpose: The goal of this presentation is to discuss the use of the Light Shaping Beam Homogenizer in an optical system for scanning-spot PRK. Methods: The basic principle of the LSBH is the transformation of any incident intensity distribution by light scattering on an irregular microlens structure z = f(x,y). The relief of this microlens structure is determined by a defined statistical function, i.e. it is defined by the mean root-squared tilt σ of the surface relief. Therefore, the beam evolution after the LSBH and in the focal plane of an imaging lens was measured for various root-squared tilts. Beside this, an optical setup for scanning-spot PRK was assembled according to the theoretical and experimental results. Results: The divergence, homogeneity and the Gaussian radius of the intensity distribution in the treatment plane of the scanning-spot PRK laser system is mainly characterized by dependent on root-mean-square tilt σ of the LSBH, as it will be explained by the theoretical description of the LSBH. Conclusions: The LSBH represents a simple, low cost beam homogenizer with low energy losses, for scanning-spot excimer laser systems.

Month-to-month and year-to-year reproducibility of high frequency QRS ECG signals

NASA Technical Reports Server (NTRS)

Batdorf, Niles J.; Feiveson, Alan H.; Schlegel, Todd T.

2004-01-01

High frequency electrocardiography analyzing the entire QRS complex in the frequency range of 150 to 250 Hz may prove useful in the detection of coronary artery disease, yet the long-term stability of these waveforms has not been fully characterized. Therefore, we prospectively investigated the reproducibility of the root mean squared voltage, kurtosis, and the presence versus absence of reduced amplitude zones in signal averaged 12-lead high frequency QRS recordings acquired in the supine position one month apart in 16 subjects and one year apart in 27 subjects. Reproducibility of root mean squared voltage and kurtosis was excellent over these time intervals in the limb leads, and acceptable in the precordial leads using both the V-lead and CR-lead derivations. The relative error of root mean squared voltage was 12% month-to-month and 16% year-to-year in the serial recordings when averaged over all 12 leads. Reduced amplitude zones were also reproducible up to a rate of 87% and 81%, respectively, for the month-to-month and year-to-year recordings. We conclude that 12-lead high frequency QRS electrocardiograms are sufficiently reproducible for clinical use.

[Gaussian process regression and its application in near-infrared spectroscopy analysis].

PubMed

Feng, Ai-Ming; Fang, Li-Min; Lin, Min

2011-06-01

Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.

System and Method for Determining Rate of Rotation Using Brushless DC Motor

NASA Technical Reports Server (NTRS)

Howard, David E. (Inventor); Smith, Dennis A. (Inventor)

2000-01-01

A system and method are provided for measuring rate of rotation. A brushless DC motor is rotated and produces a back electromagnetic force (emf) on each winding thereof. Each winding's back-emf is squared. The squared outputs associated with each winding are combined, with the square root being taken of such combination, to produce a DC output proportional only to the rate of rotation of the motor's shaft.

Deposition of aerially applied BT in an oak forest and its prediction with the FSCBG model

USGS Publications Warehouse

Anderson, Dean E.; Miller, David R.; Wang, Yansen; Yendol, William G.; Mierzejewski, Karl; McManus, Michael L.

1992-01-01

Data are provided from 17 single-swath aerial spray trials that were conducted over a fully leafed, 16-m tall, mixed oak forest. The distribution of cross-swath spray deposits was sampled at the top of the canopy and below the canopy. Micrometeorological conditions were measured above and within the canopy during the spray trials. The USDA Forest Service FSCBG (Forest Service-Cramer-Barry-Grim) model was run to predict the target sampler catch for each trial using forest stand, airplane-application-equipment configuration, and micrometeorological conditions as inputs. Observations showed an average cross-swath deposition of 100 IU cm−2 with large run-to-run variability in deposition patterns, magnitudes, and drift. Eleven percent of the spray material that reached the top of the canopy penetrated through the tree canopy to the forest floor.The FSCBG predictions of the ensemble-averaged deposition were within 17% of the measured deposition at the canopy top and within 8% on the ground beneath the canopy. Run-to-run deposit predictions by FSCBG were considerably less variable than the measured deposits. Individual run predictions were much less accurate than the ensemble-averaged predictions as demonstrated by an average root-mean-square-error (rmse) of 27.9 IU CM−2 at the top of the canopy. Comparisons of the differences between predicted and observed deposits indicated that the model accuracy was sensitive to atmospheric stability conditions. In neutral and stable conditions, a regular pattern of error was indicated by overprediction of the canopy-top deposit at distances from 0 to 20 m downwind from the flight line and underprediction of the deposit both farther downwind than 20 m and upwind of the flight line. In unstable conditions the model generally underpredicted the deposit downwind from the flight line, but showed no regular pattern of error.

Dynamical Downscaling of Seasonal Climate Prediction over Nordeste Brazil with ECHAM3 and NCEP's Regional Spectral Models at IRI.

NASA Astrophysics Data System (ADS)

Nobre, Paulo; Moura, Antonio D.; Sun, Liqiang

2001-12-01

This study presents an evaluation of a seasonal climate forecast done with the International Research Institute for Climate Prediction (IRI) dynamical forecast system (regional model nested into a general circulation model) over northern South America for January-April 1999, encompassing the rainy season over Brazil's Nordeste. The one-way nesting is one in two tiers: first the NCEP's Regional Spectral Model (RSM) runs with an 80-km grid mesh forced by the ECHAM3 atmospheric general circulation model (AGCM) outputs; then the RSM runs with a finer grid mesh (20 km) forced by the forecasts generated by the RSM-80. An ensemble of three realizations is done. Lower boundary conditions over the oceans for both ECHAM and RSM model runs are sea surface temperature forecasts over the tropical oceans. Soil moisture is initialized by ECHAM's inputs. The rainfall forecasts generated by the regional model are compared with those of the AGCM and observations. It is shown that the regional model at 80-km resolution improves upon the AGCM rainfall forecast, reducing both seasonal bias and root-mean-square error. On the other hand, the RSM-20 forecasts presented larger errors, with spatial patterns that resemble those of local topography. The better forecast of the position and width of the intertropical convergence zone (ITCZ) over the tropical Atlantic by the RSM-80 model is one of the principal reasons for better-forecast scores of the RSM-80 relative to the AGCM. The regional model improved the spatial as well as the temporal details of rainfall distribution, and also presenting the minimum spread among the ensemble members. The statistics of synoptic-scale weather variability on seasonal timescales were best forecast with the regional 80-km model over the Nordeste. The possibility of forecasting the frequency distribution of dry and wet spells within the rainy season is encouraging.

Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

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

Mirocha, Jeff D.; Simpson, Matthew D.; Fast, Jerome D.

Simulations of two periods featuring three consecutive low level jet (LLJ) events in the US Upper Great Plains during the autumn of 2011 were conducted to explore the impacts of various setup configurations and physical process models on simulated flow parameters within the lowest 200 m above the surface, using the Weather Research and Forecasting (WRF) model. Sensitivities of simulated flow parameters to the horizontal and vertical grid spacing, planetary boundary layer (PBL) and land surface model (LSM) physics options, were assessed. Data from a Light Detection and Ranging (lidar) system, deployed to the Weather Forecast Improvement Project (WFIP; Finleymore » et al. 2013) were used to evaluate the accuracy of simulated wind speed and direction at 80 m above the surface, as well as their vertical distributions between 120 and 40 m, covering the typical span of contemporary tall wind turbines. All of the simulations qualitatively captured the overall diurnal cycle of wind speed and stratification, producing LLJs during each overnight period, however large discrepancies occurred at certain times for each simulation in relation to the observations. 54-member ensembles encompassing changes of the above discussed configuration parameters displayed a wide range of simulated vertical distributions of wind speed and direction, and potential temperature, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error (RMSE) statistics show that different ensemble members performed better and worse in various simulated parameters at different times, with no clearly superior configuration . Simulations using a PBL parameterization designed specifically for the stable conditions investigated herein provided superior overall simulations of wind speed at 80 m, demonstrating the efficacy of targeting improvements of physical process models in areas of known deficiencies. However, the considerable magnitudes of the RMSE values of even the best performing simulations indicate ample opportunities for further improvements.« less

Validation of Seasonal Forecast of Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Das, Sukanta Kumar; Deb, Sanjib Kumar; Kishtawal, C. M.; Pal, Pradip Kumar

2015-06-01

The experimental seasonal forecast of Indian summer monsoon (ISM) rainfall during June through September using Community Atmosphere Model (CAM) version 3 has been carried out at the Space Applications Centre Ahmedabad since 2009. The forecasts, based on a number of ensemble members (ten minimum) of CAM, are generated in several phases and updated on regular basis. On completion of 5 years of experimental seasonal forecasts in operational mode, it is required that the overall validation or correctness of the forecast system is quantified and that the scope is assessed for further improvements of the forecast over time, if any. The ensemble model climatology generated by a set of 20 identical CAM simulations is considered as the model control simulation. The performance of the forecast has been evaluated by assuming the control simulation as the model reference. The forecast improvement factor shows positive improvements, with higher values for the recent forecasted years as compared to the control experiment over the Indian landmass. The Taylor diagram representation of the Pearson correlation coefficient (PCC), standard deviation and centered root mean square difference has been used to demonstrate the best PCC, in the order of 0.74-0.79, recorded for the seasonal forecast made during 2013. Further, the bias score of different phases of experiment revealed the fact that the ISM rainfall forecast is affected by overestimation in predicting the low rain-rate (less than 7 mm/day), but by underestimation in the medium and high rain-rate (higher than 11 mm/day). Overall, the analysis shows significant improvement of the ISM forecast over the last 5 years, viz. 2009-2013, due to several important modifications that have been implemented in the forecast system. The validation exercise has also pointed out a number of shortcomings in the forecast system; these will be addressed in the upcoming years of experiments to improve the quality of the ISM prediction.

Evaluating Air-Quality Models: Review and Outlook.

NASA Astrophysics Data System (ADS)

Weil, J. C.; Sykes, R. I.; Venkatram, A.

1992-10-01

Over the past decade, much attention has been devoted to the evaluation of air-quality models with emphasis on model performance in predicting the high concentrations that are important in air-quality regulations. This paper stems from our belief that this practice needs to be expanded to 1) evaluate model physics and 2) deal with the large natural or stochastic variability in concentration. The variability is represented by the root-mean- square fluctuating concentration (c about the mean concentration (C) over an ensemble-a given set of meteorological, source, etc. conditions. Most air-quality models used in applications predict C, whereas observations are individual realizations drawn from an ensemble. For cC large residuals exist between predicted and observed concentrations, which confuse model evaluations.This paper addresses ways of evaluating model physics in light of the large c the focus is on elevated point-source models. Evaluation of model physics requires the separation of the mean model error-the difference between the predicted and observed C-from the natural variability. A residual analysis is shown to be an elective way of doing this. Several examples demonstrate the usefulness of residuals as well as correlation analyses and laboratory data in judging model physics.In general, c models and predictions of the probability distribution of the fluctuating concentration (c), (c, are in the developmental stage, with laboratory data playing an important role. Laboratory data from point-source plumes in a convection tank show that (c approximates a self-similar distribution along the plume center plane, a useful result in a residual analysis. At pmsent,there is one model-ARAP-that predicts C, c, and (c for point-source plumes. This model is more computationally demanding than other dispersion models (for C only) and must be demonstrated as a practical tool. However, it predicts an important quantity for applications- the uncertainty in the very high and infrequent concentrations. The uncertainty is large and is needed in evaluating operational performance and in predicting the attainment of air-quality standards.

Input Forces Estimation for Nonlinear Systems by Applying a Square-Root Cubature Kalman Filter.

PubMed

Song, Xuegang; Zhang, Yuexin; Liang, Dakai

2017-10-10

This work presents a novel inverse algorithm to estimate time-varying input forces in nonlinear beam systems. With the system parameters determined, the input forces can be estimated in real-time from dynamic responses, which can be used for structural health monitoring. In the process of input forces estimation, the Runge-Kutta fourth-order algorithm was employed to discretize the state equations; a square-root cubature Kalman filter (SRCKF) was employed to suppress white noise; the residual innovation sequences, a priori state estimate, gain matrix, and innovation covariance generated by SRCKF were employed to estimate the magnitude and location of input forces by using a nonlinear estimator. The nonlinear estimator was based on the least squares method. Numerical simulations of a large deflection beam and an experiment of a linear beam constrained by a nonlinear spring were employed. The results demonstrated accuracy of the nonlinear algorithm.

Quantitative determination of additive Chlorantraniliprole in Abamectin preparation: Investigation of bootstrapping soft shrinkage approach by mid-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Yan, Hong; Song, Xiangzhong; Tian, Kuangda; Chen, Yilin; Xiong, Yanmei; Min, Shungeng

2018-02-01

A novel method, mid-infrared (MIR) spectroscopy, which enables the determination of Chlorantraniliprole in Abamectin within minutes, is proposed. We further evaluate the prediction ability of four wavelength selection methods, including bootstrapping soft shrinkage approach (BOSS), Monte Carlo uninformative variable elimination (MCUVE), genetic algorithm partial least squares (GA-PLS) and competitive adaptive reweighted sampling (CARS) respectively. The results showed that BOSS method obtained the lowest root mean squared error of cross validation (RMSECV) (0.0245) and root mean squared error of prediction (RMSEP) (0.0271), as well as the highest coefficient of determination of cross-validation (Qcv2) (0.9998) and the coefficient of determination of test set (Q2test) (0.9989), which demonstrated that the mid infrared spectroscopy can be used to detect Chlorantraniliprole in Abamectin conveniently. Meanwhile, a suitable wavelength selection method (BOSS) is essential to conducting a component spectral analysis.

Nondestructive quantification of the soluble-solids content and the available acidity of apples by Fourier-transform near-infrared spectroscopy

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

Ying Yibin; Liu Yande; Tao Yang

2005-09-01

This research evaluated the feasibility of using Fourier-transform near-infrared (FT-NIR) spectroscopy to quantify the soluble-solids content (SSC) and the available acidity (VA) in intact apples. Partial least-squares calibration models, obtained from several preprocessing techniques (smoothing, derivative, etc.) in several wave-number ranges were compared. The best models were obtained with the high coefficient determination (r{sup 2}) 0.940 for the SSC and a moderate r{sup 2} of 0.801 for the VA, root-mean-square errors of prediction of 0.272% and 0.053%, and root-mean-square errors of calibration of 0.261% and 0.046%, respectively. The results indicate that the FT-NIR spectroscopy yields good predictions of the SSCmore » and also showed the feasibility of using it to predict the VA of apples.« less

An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 2: The added value from climate forecast models

DOE PAGES

Yuan, Xing

2016-06-22

This is the second paper of a two-part series on introducing an experimental seasonal hydrological forecasting system over the Yellow River basin in northern China. While the natural hydrological predictability in terms of initial hydrological conditions (ICs) is investigated in a companion paper, the added value from eight North American Multimodel Ensemble (NMME) climate forecast models with a grand ensemble of 99 members is assessed in this paper, with an implicit consideration of human-induced uncertainty in the hydrological models through a post-processing procedure. The forecast skill in terms of anomaly correlation (AC) for 2 m air temperature and precipitation does not necessarily decrease overmore » leads but is dependent on the target month due to a strong seasonality for the climate over the Yellow River basin. As there is more diversity in the model performance for the temperature forecasts than the precipitation forecasts, the grand NMME ensemble mean forecast has consistently higher skill than the best single model up to 6 months for the temperature but up to 2 months for the precipitation. The NMME climate predictions are downscaled to drive the variable infiltration capacity (VIC) land surface hydrological model and a global routing model regionalized over the Yellow River basin to produce forecasts of soil moisture, runoff and streamflow. And the NMME/VIC forecasts are compared with the Ensemble Streamflow Prediction method (ESP/VIC) through 6-month hindcast experiments for each calendar month during 1982–2010. As verified by the VIC offline simulations, the NMME/VIC is comparable to the ESP/VIC for the soil moisture forecasts, and the former has higher skill than the latter only for the forecasts at long leads and for those initialized in the rainy season. The forecast skill for runoff is lower for both forecast approaches, but the added value from NMME/VIC is more obvious, with an increase of the average AC by 0.08–0.2. To compare with the observed streamflow, both the hindcasts from NMME/VIC and ESP/VIC are post-processed through a linear regression model fitted by using VIC offline-simulated streamflow. The post-processed NMME/VIC reduces the root mean squared error (RMSE) from the post-processed ESP/VIC by 5–15 %. And the reduction occurs mostly during the transition from wet to dry seasons. As a result, with the consideration of the uncertainty in the hydrological models, the added value from climate forecast models is decreased especially at short leads, suggesting the necessity of improving the large-scale hydrological models in human-intervened river basins.« less

A Comparison Between Heliosat-2 and Artificial Neural Network Methods for Global Horizontal Irradiance Retrievals over Desert Environments

NASA Astrophysics Data System (ADS)

Ghedira, H.; Eissa, Y.

2012-12-01

Global horizontal irradiance (GHI) retrievals at the surface of any given location could be used for preliminary solar resource assessments. More accurately, the direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) are also required to estimate the global tilt irradiance, mainly used for fixed flat plate collectors. Two different satellite-based models for solar irradiance retrievals have been applied over the desert environment of the United Arab Emirates (UAE). Both models employ channels of the SEVIRI instrument, onboard the geostationary satellite Meteosat Second Generation, as their main inputs. The satellite images used in this study have a temporal resolution of 15-min and a spatial resolution of 3-km. The objective of this study is to compare between the GHI retrieved using the Heliosat-2 method and an artificial neural network (ANN) ensemble method over the UAE. The high-resolution visible channel of SEVIRI is used in the Heliosat-2 method to derive the cloud index. The cloud index is then used to compute the cloud transmission, while the cloud-free GHI is computed from the Linke turbidity factor. The product of the cloud transmission and the cloud-free GHI denotes the estimated GHI. A constant underestimation is observed in the estimated GHI over the dataset available in the UAE. Therefore, the cloud-free DHI equation in the model was recalibrated to fix the bias. After recalibration, results over the UAE show a root mean square error (RMSE) value of 10.1% and a mean bias error (MBE) of -0.5%. As for the ANN approach, six thermal channels of SEVIRI were used to estimate the DHI and the total optical depth of the atmosphere (δ). An ensemble approach is employed to obtain a better generalizability of the results, as opposed to using one single weak network. The DNI is then computed from the estimated δ using the Beer-Bouguer-Lambert law. The GHI is computed from the DNI and DHI estimates. The RMSE for the estimated GHI obtained over an independent dataset over the UAE is 7.2% and the MBE is +1.9%. The results obtained by the two methods have shown that both the recalibrated Heliosat-2 and the ANN ensemble methods estimate the GHI at a 15-min resolution with high accuracy. The advantage of the ANN ensemble approach is that it derives the GHI from accurate DNI and DHI estimates. The DNI and DHI estimates are valuable when computing the global tilt irradiance. Also, accurate DNI estimates are beneficial for preliminary site selection for concentrating solar powered plants.

An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 2: The added value from climate forecast models

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

Yuan, Xing

This is the second paper of a two-part series on introducing an experimental seasonal hydrological forecasting system over the Yellow River basin in northern China. While the natural hydrological predictability in terms of initial hydrological conditions (ICs) is investigated in a companion paper, the added value from eight North American Multimodel Ensemble (NMME) climate forecast models with a grand ensemble of 99 members is assessed in this paper, with an implicit consideration of human-induced uncertainty in the hydrological models through a post-processing procedure. The forecast skill in terms of anomaly correlation (AC) for 2 m air temperature and precipitation does not necessarily decrease overmore » leads but is dependent on the target month due to a strong seasonality for the climate over the Yellow River basin. As there is more diversity in the model performance for the temperature forecasts than the precipitation forecasts, the grand NMME ensemble mean forecast has consistently higher skill than the best single model up to 6 months for the temperature but up to 2 months for the precipitation. The NMME climate predictions are downscaled to drive the variable infiltration capacity (VIC) land surface hydrological model and a global routing model regionalized over the Yellow River basin to produce forecasts of soil moisture, runoff and streamflow. And the NMME/VIC forecasts are compared with the Ensemble Streamflow Prediction method (ESP/VIC) through 6-month hindcast experiments for each calendar month during 1982–2010. As verified by the VIC offline simulations, the NMME/VIC is comparable to the ESP/VIC for the soil moisture forecasts, and the former has higher skill than the latter only for the forecasts at long leads and for those initialized in the rainy season. The forecast skill for runoff is lower for both forecast approaches, but the added value from NMME/VIC is more obvious, with an increase of the average AC by 0.08–0.2. To compare with the observed streamflow, both the hindcasts from NMME/VIC and ESP/VIC are post-processed through a linear regression model fitted by using VIC offline-simulated streamflow. The post-processed NMME/VIC reduces the root mean squared error (RMSE) from the post-processed ESP/VIC by 5–15 %. And the reduction occurs mostly during the transition from wet to dry seasons. As a result, with the consideration of the uncertainty in the hydrological models, the added value from climate forecast models is decreased especially at short leads, suggesting the necessity of improving the large-scale hydrological models in human-intervened river basins.« less

Search for the Higgs boson in events with missing transverse energy and b quark jets produced in pp collisions at square root(s)=1.96 TeV.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; De Lorenzo, G; Dell'Orso, M; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Forrester, S; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Giagu, S; Giakoumopolou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Hamilton, A; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; Iyutin, B; James, E; Jayatilaka, B; Jeans, D; Jeon, E J; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Rott, C; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Salamanna, G; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyrla, A; Shalhout, S Z; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sun, H; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S

2008-05-30

We search for the standard model Higgs boson produced in association with an electroweak vector boson in events with no identified charged leptons, large imbalance in transverse momentum, and two jets where at least one contains a secondary vertex consistent with the decay of b hadrons. We use approximately 1 fb(-1) integrated luminosity of pp collisions at square root(s)=1.96 TeV recorded by the Collider Detector at Fermilab II experiment at the Tevatron. We find 268 (16) single (double) b-tagged candidate events, where 248+/-43 (14.4+/-2.7) are expected from standard model background processes. We observe no significant excess over the expected background and thus set 95% confidence level upper limits on the Higgs boson production cross section for several Higgs boson masses ranging from 110 to 140 GeV/c(2). For a mass of 115 GeV/c(2), the observed (expected) limit is 20.4 (14.2) times the standard model prediction.

Combat Traction II, Phase II. Volume I, Narrative

DTIC Science & Technology

1974-10-01

by S. M. Warren, M. K. Wahi, R. L. Amberg, H. H. Straub, and N. S. Attri of the Boeing Commercial Airplanc Company under combined NASA, USAF, and F,.A...inverted; they can be squared, or their square roots can be taken. Such manipulations are proper and are usually performed to create a more convenient

Effect of microstructure and notch root radius on fracture toughness of an aluminum metal matrix composite

NASA Technical Reports Server (NTRS)

Manoharan, M.; Lewandowski, J. J.

1989-01-01

Recent results on the effects of matrix aging condition (matrix temper) and notch root radius on the measured fracture toughness of a SiC particulate reinforced aluminum alloy are reviewed. Stress intensity factors at catastrophic fracture were obtained for both underaged and overaged composites reveal. The linear relation found between apparent fracture toughness and the square root of the notch root radius implies a linear dependence of the crack opening displacement on the notch root radius. The results suggest a strain controlled fracture process, and indicate that there are differences in the fracture micromechanisms of the two aging conditions.

Is the Sudlow site I of human serum albumin more generous to adopt prospective anti-cancer bioorganic compound than that of bovine: A combined spectroscopic and docking simulation approach.

PubMed

Joshi, Ritika; Jadhao, Manojkumar; Kumar, Himank; Ghosh, Sujit Kumar

2017-12-01

A comparative biophysical study on the individual conformational adaptation embraced by two homologous serum albumins (SA) (bovine and human) towards a potential anticancer bioorganic compound 2-(6-chlorobenzo[d] thiazol-2-yl)-1H-benzo[de] isoquinoline-1,3(2H)- dione (CBIQD) is apparent from the discrimination in binding behavior and the ensuing consequences accomplished by combined in vitro optical spectroscopy, in silico molecular docking and molecular dynamics (MD) simulation. The Sudlow site I of HSA although anion receptive, harbors neutral CBIQD in Sudlow site I (subdomain IIA, close to Trp) of HSA, while in BSA its prefers to snugly fit into Sudlow site II (subdomain IIIA, close to Tyr). Based on discernable diminution of HSA mean fluorescence lifetime as a function of biluminophore concentration, facile occurrence of fluorescence resonance energy transfer (FRET) is substantiated as the probable quenching mechanism accompanied by structural deformations in the protein ensemble. CBIQD establishes itself within HSA close to Trp214, and consequently reduces the micropolarity of the cybotactic environment that is predominantly constituted by hydrophobic amino acid residues. The stronger association of CBIQD with HSA encourages an allosteric modulation leading to slight deformation in its secondary structure whereas for BSA the association is comparatively weaker. Sudlow site I of HSA is capable to embrace a favorable conformation like malleable gold to provide room for incoming CBIQD, whereas for BSA it behaves more like rigid cast-iron which does not admit any change thus forcing CBIQD to occupy an altogether different binding location i.e. the Sudlow site II. The anticancer CBIQD is found to be stable within the HSA scaffold as vindicated by root mean square deviation (RMSD) and root mean square fluctuation (RMSF) obtained by MD simulation. A competitively inhibited esterase-like activity of HSA upon CBIQD binding to Lys199 and Arg257 residues, plausibly envisions that similar naphthalimide based prodrugs, bearing ester functionality, can be particularly activated by Sudlow site I of HSA. The consolidated spectroscopic research described herein may encourage design of naphthalimide based pro-drugs for effective in vivo biodistribution using HSA-based drug delivery systems. Copyright © 2017 Elsevier Inc. All rights reserved.

Representational analysis of extended disorder in atomistic ensembles derived from total scattering data

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

Neilson, James R.; McQueen, Tyrel M.

With the increased availability of high-intensity time-of-flight neutron and synchrotron X-ray scattering sources that can access wide ranges of momentum transfer, the pair distribution function method has become a standard analysis technique for studying disorder of local coordination spheres and at intermediate atomic separations. In some cases, rational modeling of the total scattering data (Bragg and diffuse) becomes intractable with least-squares approaches, necessitating reverse Monte Carlo simulations using large atomistic ensembles. However, the extraction of meaningful information from the resulting atomistic ensembles is challenging, especially at intermediate length scales. Representational analysis is used here to describe the displacements of atomsmore » in reverse Monte Carlo ensembles from an ideal crystallographic structure in an approach analogous to tight-binding methods. Rewriting the displacements in terms of a local basis that is descriptive of the ideal crystallographic symmetry provides a robust approach to characterizing medium-range order (and disorder) and symmetry breaking in complex and disordered crystalline materials. Lastly, this method enables the extraction of statistically relevant displacement modes (orientation, amplitude and distribution) of the crystalline disorder and provides directly meaningful information in a locally symmetry-adapted basis set that is most descriptive of the crystal chemistry and physics.« less

Representational analysis of extended disorder in atomistic ensembles derived from total scattering data

DOE PAGES

Neilson, James R.; McQueen, Tyrel M.

2015-09-20

With the increased availability of high-intensity time-of-flight neutron and synchrotron X-ray scattering sources that can access wide ranges of momentum transfer, the pair distribution function method has become a standard analysis technique for studying disorder of local coordination spheres and at intermediate atomic separations. In some cases, rational modeling of the total scattering data (Bragg and diffuse) becomes intractable with least-squares approaches, necessitating reverse Monte Carlo simulations using large atomistic ensembles. However, the extraction of meaningful information from the resulting atomistic ensembles is challenging, especially at intermediate length scales. Representational analysis is used here to describe the displacements of atomsmore » in reverse Monte Carlo ensembles from an ideal crystallographic structure in an approach analogous to tight-binding methods. Rewriting the displacements in terms of a local basis that is descriptive of the ideal crystallographic symmetry provides a robust approach to characterizing medium-range order (and disorder) and symmetry breaking in complex and disordered crystalline materials. Lastly, this method enables the extraction of statistically relevant displacement modes (orientation, amplitude and distribution) of the crystalline disorder and provides directly meaningful information in a locally symmetry-adapted basis set that is most descriptive of the crystal chemistry and physics.« less

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis.

PubMed

Lee, Byeong-Ju; Kim, Hye-Youn; Lim, Sa Rang; Huang, Linfang; Choi, Hyung-Kyoon

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis

PubMed Central

Lim, Sa Rang; Huang, Linfang

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values. PMID:29049369

Direct and simultaneous quantification of tannin mean degree of polymerization and percentage of galloylation in grape seeds using diffuse reflectance fourier transform-infrared spectroscopy.

PubMed

Pappas, Christos; Kyraleou, Maria; Voskidi, Eleni; Kotseridis, Yorgos; Taranilis, Petros A; Kallithraka, Stamatina

2015-02-01

The direct and simultaneous quantitative determination of the mean degree of polymerization (mDP) and the degree of galloylation (%G) in grape seeds were quantified using diffuse reflectance infrared Fourier transform spectroscopy and partial least squares (PLS). The results were compared with those obtained using the conventional analysis employing phloroglucinolysis as pretreatment followed by high performance liquid chromatography-UV and mass spectrometry detection. Infrared spectra were recorded in solid state samples after freeze drying. The 2nd derivative of the 1832 to 1416 and 918 to 739 cm(-1) spectral regions for the quantification of mDP, the 2nd derivative of the 1813 to 607 cm(-1) spectral region for the degree of %G determination and PLS regression were used. The determination coefficients (R(2) ) of mDP and %G were 0.99 and 0.98, respectively. The corresponding values of the root-mean-square error of calibration were found 0.506 and 0.692, the root-mean-square error of cross validation 0.811 and 0.921, and the root-mean-square error of prediction 0.612 and 0.801. The proposed method in comparison with the conventional method is simpler, less time consuming, more economical, and requires reduced quantities of chemical reagents and fewer sample pretreatment steps. It could be a starting point for the design of more specific models according to the requirements of the wineries. © 2015 Institute of Food Technologists®

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

Determination of the vapor-liquid transition of square-well particles using a novel generalized-canonical-ensemble-based method

NASA Astrophysics Data System (ADS)

Zhao, Liang; Xu, Shun; Tu, Yu-Song; Zhou, Xin

2017-06-01

Not Available Project supported by the National Natural Science Foundation for Outstanding Young Scholars, China (Grant No. 11422542), the National Natural Science Foundation of China (Grant Nos. 11605151 and 11675138), and the Shanghai Supercomputer Center of China and Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase).

The comparison of automated clustering algorithms for resampling representative conformer ensembles with RMSD matrix.

PubMed

Kim, Hyoungrae; Jang, Cheongyun; Yadav, Dharmendra K; Kim, Mi-Hyun

2017-03-23

The accuracy of any 3D-QSAR, Pharmacophore and 3D-similarity based chemometric target fishing models are highly dependent on a reasonable sample of active conformations. Since a number of diverse conformational sampling algorithm exist, which exhaustively generate enough conformers, however model building methods relies on explicit number of common conformers. In this work, we have attempted to make clustering algorithms, which could find reasonable number of representative conformer ensembles automatically with asymmetric dissimilarity matrix generated from openeye tool kit. RMSD was the important descriptor (variable) of each column of the N × N matrix considered as N variables describing the relationship (network) between the conformer (in a row) and the other N conformers. This approach used to evaluate the performance of the well-known clustering algorithms by comparison in terms of generating representative conformer ensembles and test them over different matrix transformation functions considering the stability. In the network, the representative conformer group could be resampled for four kinds of algorithms with implicit parameters. The directed dissimilarity matrix becomes the only input to the clustering algorithms. Dunn index, Davies-Bouldin index, Eta-squared values and omega-squared values were used to evaluate the clustering algorithms with respect to the compactness and the explanatory power. The evaluation includes the reduction (abstraction) rate of the data, correlation between the sizes of the population and the samples, the computational complexity and the memory usage as well. Every algorithm could find representative conformers automatically without any user intervention, and they reduced the data to 14-19% of the original values within 1.13 s per sample at the most. The clustering methods are simple and practical as they are fast and do not ask for any explicit parameters. RCDTC presented the maximum Dunn and omega-squared values of the four algorithms in addition to consistent reduction rate between the population size and the sample size. The performance of the clustering algorithms was consistent over different transformation functions. Moreover, the clustering method can also be applied to molecular dynamics sampling simulation results.

Seeking for the rational basis of the median model: the optimal combination of multi-model ensemble results

NASA Astrophysics Data System (ADS)

Riccio, A.; Giunta, G.; Galmarini, S.

2007-04-01

In this paper we present an approach for the statistical analysis of multi-model ensemble results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides. We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach called "median model", originally introduced in Galmarini et al. (2004a, b). This approach also provides a way to systematically reduce (and quantify) model uncertainties, thus supporting the decision-making process and/or regulatory-purpose activities in a very effective manner.

Seeking for the rational basis of the Median Model: the optimal combination of multi-model ensemble results

NASA Astrophysics Data System (ADS)

Riccio, A.; Giunta, G.; Galmarini, S.

2007-12-01

In this paper we present an approach for the statistical analysis of multi-model ensemble results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides. We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach called "median model", originally introduced in Galmarini et al. (2004a, b). This approach also provides a way to systematically reduce (and quantify) model uncertainties, thus supporting the decision-making process and/or regulatory-purpose activities in a very effective manner.

Unsteady convection in tin in a Bridgman configuration

NASA Technical Reports Server (NTRS)

Knuteson, David J.; Fripp, Archibald L.; Woodell, Glenn A.; Debnam, William J., Jr.; Narayanan, Ranga

1991-01-01

When a quiescent fluid is heated sufficiently from below, steady convection will begin. Further heating will cause oscillatory and then turbulent flow. Theoretical results predict that the frequency of oscillation will depend on the square root of the Rayleigh number in the fluid. In the current work, liquid tin was heated from below for three aspect ratios, h/R = 3.4, 5.3, and 7.0. The experimental results are curve-fit for the square-root relation and also for a linear relation. The fit of the expression is evaluated using a correlation coefficient. An estimate for the first critical Rayleigh number (onset of steady convection) is obtained for both expressions. These values are compared to previous experimental results.

Probability of stress-corrosion fracture under random loading.

NASA Technical Reports Server (NTRS)

Yang, J.-N.

1972-01-01

A method is developed for predicting the probability of stress-corrosion fracture of structures under random loadings. The formulation is based on the cumulative damage hypothesis and the experimentally determined stress-corrosion characteristics. Under both stationary and nonstationary random loadings, the mean value and the variance of the cumulative damage are obtained. The probability of stress-corrosion fracture is then evaluated using the principle of maximum entropy. It is shown that, under stationary random loadings, the standard deviation of the cumulative damage increases in proportion to the square root of time, while the coefficient of variation (dispersion) decreases in inversed proportion to the square root of time. Numerical examples are worked out to illustrate the general results.

Multiplicity and pseudorapidity distributions of photons in Au+Au collisions at square root of (S(NN)) = 62.4 GeV.

PubMed

Adams, J; Aggarwal, M M; Ahammed, Z; Amonett, J; Anderson, B D; Arkhipkin, D; Averichev, G S; Badyal, S K; Bai, Y; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Bekele, S; Belaga, V V; Bellingeri-Laurikainen, A; Bellwied, R; Berger, J; Bezverkhny, B I; Bhardwaj, S; Bhasin, A; Bhati, A K; Bichsel, H; Bielcik, J; Bielcikova, J; Billmeier, A; Bland, L C; Blyth, C O; Blyth, S; Bonner, B E; Botje, M; Boucham, A; Bouchet, J; Brandin, A V; Bravar, A; Bystersky, M; Cadman, R V; Cai, X Z; Caines, H; de la Barca Sánchez, M Calderón; Castillo, J; Catu, O; Cebra, D; Chajecki, Z; Chaloupka, P; Chattopadhyay, S; Chen, H F; Chen, Y; Cheng, J; Cherney, M; Chikanian, A; Christie, W; Coffin, J P; Cormier, T M; Cosentino, M R; Cramer, J G; Crawford, H J; Das, D; Das, S; de Moura, M M; Dedovich, T G; Derevschikov, A A; Didenko, L; Dietel, T; Dogra, S M; Dong, W J; Dong, X; Draper, J E; Du, F; Dubey, A K; Dunin, V B; Dunlop, J C; Mazumdar, M R Dutta; Eckardt, V; Edwards, W R; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Estienne, M; Fachini, P; Faivre, J; Fatemi, R; Fedorisin, J; Filimonov, K; Filip, P; Finch, E; Fine, V; Fisyak, Y; Fornazier, K S F; Fu, J; Gagliardi, C A; Gaillard, L; Gans, J; Ganti, M S; Geurts, F; Ghazikhanian, V; Ghosh, P; Gonzalez, J E; Gos, H; Grachov, O; Grebenyuk, O; Grosnick, D; Guertin, S M; Guo, Y; Gupta, A; Gutierrez, T D; Hallman, T J; Hamed, A; Hardtke, D; Harris, J W; Heinz, M; Henry, T W; Hepplemann, S; Hippolyte, B; Hirsch, A; Hjort, E; Hoffmann, G W; Horner, M; Huang, H Z; Huang, S L; Hughes, E W; Humanic, T J; Igo, G; Ishihara, A; Jacobs, P; Jacobs, W W; Jedynak, M; Jiang, H; Jones, P G; Judd, E G; Kabana, S; Kang, K; Kaplan, M; Keane, D; Kechechyan, A; Khodyrev, V Yu; Kiryluk, J; Kisiel, A; Kislov, E M; Klay, J; Klein, S R; Koetke, D D; Kollegger, T; Kopytine, M; Kotchenda, L; Kowalik, K L; Kramer, M; Kravtsov, P; Kravtsov, V I; Krueger, K; Kuhn, C; Kulikov, A I; Kumar, A; Kutuev, R Kh; Kuznetsov, A A; Lamont, M A C; Landgraf, J M; Lange, S; Laue, F; Lauret, J; Lebedev, A; Lednicky, R; Lehocka, S; Levine, M J; Li, C; Li, Q; Li, Y; Lin, G; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, H; Liu, J; Liu, L; Liu, Q J; Liu, Z; Ljubicic, T; Llope, W J; Long, H; Longacre, R S; Lopez-Noriega, M; Love, W A; Lu, Y; Ludlam, T; Lynn, D; Ma, G L; Ma, J G; Ma, Y G; Magestro, D; Mahajan, S; Mahapatra, D P; Majka, R; Mangotra, L K; Manweiler, R; Margetis, S; Markert, C; Martin, L; Marx, J N; Matis, H S; Matulenko, Yu A; McClain, C J; McShane, T S; Meissner, F; Melnick, Yu; Meschanin, A; Miller, M L; Minaev, N G; Mironov, C; Mischke, A; Mishra, D K; Mitchell, J; Mohanty, B; Molnar, L; Moore, C F; Morozov, D A; Munhoz, M G; Nandi, B K; Nayak, S K; Nayak, T K; Nelson, J M; Netrakanti, P K; Nikitin, V A; Nogach, L V; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Pal, S K; Panebratsev, Y; Panitkin, S Y; Pavlinov, A I; Pawlak, T; Peitzmann, T; Perevoztchikov, V; Perkins, C; Peryt, W; Petrov, V A; Phatak, S C; Picha, R; Planinic, M; Pluta, J; Porile, N; Porter, J; Poskanzer, A M; Potekhin, M; Potrebenikova, E; Potukuchi, B V K S; Prindle, D; Pruneau, C; Putschke, J; Rakness, G; Raniwala, R; Raniwala, S; Ravel, O; Ray, R L; Razin, S V; Reichhold, D; Reid, J G; Reinnarth, J; Renault, G; Retiere, F; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevskiy, O V; Romero, J L; Rose, A; Roy, C; Ruan, L; Russcher, M J; Sahoo, R; Sakrejda, I; Salur, S; Sandweiss, J; Sarsour, M; Savin, I; Sazhin, P S; Schambach, J; Scharenberg, R P; Schmitz, N; Schweda, K; Seger, J; Seyboth, P; Shahaliev, E; Shao, M; Shao, W; Sharma, M; Shen, W Q; Shestermanov, K E; Shimanskiy, S S; Sichtermann, E; Simon, F; Singaraju, R N; Smirnov, N; Snellings, R; Sood, G; Sorensen, P; Sowinski, J; Speltz, J; Spinka, H M; Srivastava, B; Stadnik, A; Stanislaus, T D S; Stock, R; Stolpovsky, A; Strikhanov, M; Stringfellow, B; Suaide, A A P; Sugarbaker, E; Suire, C; Sumbera, M; Surrow, B; Swanger, M; Symons, T J M; de Toledo, A Szanto; Tai, A; Takahashi, J; Tang, A H; Tarnowsky, T; Thein, D; Thomas, J H; Timoshenko, S; Tokarev, M; Trainor, T A; Trentalange, S; Tribble, R E; Tsai, O D; Ulery, J; Ullrich, T; Underwood, D G; Buren, G Van; van Leeuwen, M; Molen, A M Vander; Varma, R; Vasilevski, I M; Vasiliev, A N; Vernet, R; Vigdor, S E; Viyogi, Y P; Vokal, S; Voloshin, S A; Waggoner, W T; Wang, F; Wang, G; Wang, G; Wang, X L; Wang, Y; Wang, Y; Wang, Z M; Ward, H; Watson, J W; Webb, J C; Westfall, G D; Wetzler, A; Whitten, C; Wieman, H; Wissink, S W; Witt, R; Wood, J; Wu, J; Xu, N; Xu, Z; Xu, Z Z; Yamamoto, E; Yepes, P; Yurevich, V I; Zborovsky, I; Zhang, H; Zhang, W M; Zhang, Y; Zhang, Z P; Zoulkarneev, R; Zoulkarneeva, Y; Zubarev, A N

2005-08-05

We present the first measurement of pseudorapidity distribution of photons in the region 2.3 < or = eta < or = 3.7 for different centralities in Au+Au collisions at square root of (S(NN)) = 62.4 GeV. We find that the photon yield scales with the number of participating nucleons at all collision centralities studied. The pseudorapidity distribution of photons, dominated by pi0 decays, has been compared to those of charged pions, photons, and inclusive charged particles from heavy-ion and nucleon-nucleon collisions at various energies. The photon production has been shown to be consistent with the energy and centrality independent limiting fragmentation scenario.

Gram-Schmidt algorithms for covariance propagation

NASA Technical Reports Server (NTRS)

Thornton, C. L.; Bierman, G. J.

1977-01-01

This paper addresses the time propagation of triangular covariance factors. Attention is focused on the square-root free factorization, P = UD(transpose of U), where U is unit upper triangular and D is diagonal. An efficient and reliable algorithm for U-D propagation is derived which employs Gram-Schmidt orthogonalization. Partitioning the state vector to distinguish bias and coloured process noise parameters increase mapping efficiency. Cost comparisons of the U-D, Schmidt square-root covariance and conventional covariance propagation methods are made using weighted arithmetic operation counts. The U-D time update is shown to be less costly than the Schmidt method; and, except in unusual circumstances, it is within 20% of the cost of conventional propagation.

Gram-Schmidt algorithms for covariance propagation

NASA Technical Reports Server (NTRS)

Thornton, C. L.; Bierman, G. J.

1975-01-01

This paper addresses the time propagation of triangular covariance factors. Attention is focused on the square-root free factorization, P = UDU/T/, where U is unit upper triangular and D is diagonal. An efficient and reliable algorithm for U-D propagation is derived which employs Gram-Schmidt orthogonalization. Partitioning the state vector to distinguish bias and colored process noise parameters increases mapping efficiency. Cost comparisons of the U-D, Schmidt square-root covariance and conventional covariance propagation methods are made using weighted arithmetic operation counts. The U-D time update is shown to be less costly than the Schmidt method; and, except in unusual circumstances, it is within 20% of the cost of conventional propagation.

Design and resolution analysis of parabolic mirror spectrometer

NASA Astrophysics Data System (ADS)

Wu, Su; Wang, Guodong; Xia, Guo; Sun, Yanchao; Hu, Mingyong

2017-10-01

In order to further eliminate aberration and improve resolution, the paper employs parabolic mirror as the collimating mirror and the focusing mirror to design "Z" configuration and "U" configuration optical structure of parabolic spectrometer with the F number 2.5 and the spectral range varying from 250 nm to 850 nm. We conduct experiments on ZEMAX to simulate and optimize the initial parameters of two structures with the root-mean-square (RMS) radius of spots along Y axis as the optimization goal. Through analyzing the spot diagram and the root-mean-square (RMS) of Y axis, we can see that the "U" configuration spectrometers can achieve much better spectral resolution than the "Z" configuration.

Search for a standard model Higgs boson in WH --> lvbb in pp collisions at square root s = 1.96 TeV.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burke, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cordelli, M; Cortiana, G; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heijboer, A; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Hussein, M; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, H S; Lee, S W; Leone, S; Lewis, J D; Lin, C-S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lucchesi, D; Luci, C; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Würthwein, F; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zhang, X; Zheng, Y; Zucchelli, S

2009-09-04

We present a search for a standard model Higgs boson produced in association with a W boson using 2.7 fb(-1) of integrated luminosity of pp collision data taken at square root s = 1.96 TeV. Limits on the Higgs boson production rate are obtained for masses between 100 and 150 GeV/c(2). Through the use of multivariate techniques, the analysis achieves an observed (expected) 95% confidence level upper limit of 5.6 (4.8) times the theoretically expected production cross section for a standard model Higgs boson with a mass of 115 GeV/c(2).

Downdating a time-varying square root information filter

NASA Technical Reports Server (NTRS)

Muellerschoen, Ronald J.

1990-01-01

A new method to efficiently downdate an estimate and covariance generated by a discrete time Square Root Information Filter (SRIF) is presented. The method combines the QR factor downdating algorithm of Gill and the decentralized SRIF algorithm of Bierman. Efficient removal of either measurements or a priori information is possible without loss of numerical integrity. Moreover, the method includes features for detecting potential numerical degradation. Performance on a 300 parameter system with 5800 data points shows that the method can be used in real time and hence is a promising tool for interactive data analysis. Additionally, updating a time-varying SRIF filter with either additional measurements or a priori information proceeds analogously.

Alignment of Ge nanoislands on Si(111) by Ga-induced substrate self-patterning.

PubMed

Schmidt, Th; Flege, J I; Gangopadhyay, S; Clausen, T; Locatelli, A; Heun, S; Falta, J

2007-02-09

A novel mechanism is described which enables the selective formation of three-dimensional Ge islands. Submonolayer adsorption of Ga on Si(111) at high temperature leads to a self-organized two-dimensional pattern formation by separation of the 7 x 7 substrate and Ga/Si(111)-(square root[3] x square root[3])-R30 degrees domains. The latter evolve at step edges and domain boundaries of the initial substrate reconstruction. Subsequent Ge deposition results in the growth of 3D islands which are aligned at the boundaries between bare and Ga-covered domains. This result is explained in terms of preferential nucleation conditions due to a modulation of the surface chemical potential.

Measurement of inclusive jet cross sections in Z/gamma*(-->e+e-) + jets production in pp[over ] collisions at square root s = 1.96 TeV.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; De Lorenzo, G; Dell'orso, M; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Forrester, S; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Gerberich, H; Gerdes, D; Giagu, S; Giakoumopolou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Hamilton, A; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; Iyutin, B; James, E; Jayatilaka, B; Jeans, D; Jeon, E J; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Salamanna, G; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyria, A; Shalhout, S Z; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sun, H; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S

2008-03-14

Inclusive jet cross sections in Z/gamma* events, with Z/gamma* decaying into an electron-positron pair, are measured as a function of jet transverse momentum and jet multiplicity in pp[over ] collisions at square root s = 1.96 TeV with the upgraded Collider Detector at Fermilab in run II, based on an integrated luminosity of 1.7 fb(-1). The measurements cover the rapidity region |y(jet)|<2.1 and the transverse momentum range p(T)(jet)>30 GeV/c. Next-to-leading order perturbative QCD predictions are in good agreement with the measured cross sections.

Measurement of the Lambda b0 lifetime in Lambda b0-->J/psi Lambda 0 in pp collisions at square root s=1.96 TeV.

PubMed

Abulencia, A; Adelman, J; Affolder, T; Akimoto, T; Albrow, M G; Ambrose, D; Amerio, S; Amidei, D; Anastassov, A; Anikeev, K; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Arguin, J-F; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Bedeschi, F; Behari, S; Belforte, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Budroni, S; Burkett, K; Busetto, G; Bussey, P; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carrillo, S; Carlsmith, D; Carosi, R; Carron, S; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, I; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciljak, M; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Coca, M; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Cyr, D; DaRonco, S; D'Auria, S; Davies, T; D'Onofrio, M; Dagenhart, D; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; Dell'Orso, M; Delli Paoli, F; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; DiTuro, P; Dörr, C; Donati, S; Donega, M; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, I; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Foland, A; Forrester, S; Foster, G W; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garcia, J E; Garberson, F; Garfinkel, A F; Gay, C; Gerberich, H; Gerdes, D; Giagu, S; Giannetti, P; Gibson, A; Gibson, K; Gimmell, J L; Ginsburg, C; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Goldstein, J; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Griffiths, M; Grinstein, S; Grosso-Pilcher, C; Group, R C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Hamilton, A; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Holloway, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ishizawa, Y; Ivanov, A; Iyutin, B; James, E; Jang, D; Jayatilaka, B; Jeans, D; Jensen, H; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Karchin, P E; Kato, Y; Kemp, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kovalev, A; Kraan, A C; Kraus, J; Kravchenko, I; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kusakabe, Y; Kwang, S; Laasanen, A T; Labarga, L; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Lindgren, M; Lipeles, E; Liss, T M; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Loverre, P; Lu, R-S; Lucchesi, D; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Manca, G; Margaroli, F; Marginean, R; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Maruyama, T; Mastrandrea, P; Masubuchi, T; Matsunaga, H; Mattson, M E; Mazini, R; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyamoto, A; Moed, S; Moggi, N; Mohr, B; Moore, R; Morello, M; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Nachtman, J; Nagano, A; Naganoma, J; Nahn, S; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nigmanov, T; Nodulman, L; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Pagliarone, C; Palencia, E; Papadimitriou, V; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prokoshin, F; Pronko, A; Proudfoot, J; Ptochos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ranjan, N; Rappoccio, S; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Sabik, S; Safonov, A; Sakumoto, W K; Salamanna, G; Saltó, O; Saltzberg, D; Sánchez, C; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savard, P; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyrla, A; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Sjolin, J; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; Spreitzer, T; Squillacioti, P; Stanitzki, M; Staveris-Polykalas, A; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sun, H; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Takikawa, K; Tanaka, M; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Tesarek, R J; Thom, J; Thompson, A S; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tsuchiya, R; Tsuno, S; Turini, N; Ukegawa, F; Unverhau, T; Uozumi, S; Usynin, D; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Veramendi, G; Veszpremi, V; Vidal, R; Vila, I; Vilar, R; Vine, T; Vollrath, I; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner, J; Wagner, W; Wallny, R; Wang, S M; Warburton, A; Waschke, S; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zhou, J; Zucchelli, S

2007-03-23

We report a measurement of the Lambda b0 lifetime in the exclusive decay Lambda b0-->J/psi Lambda 0 in pp collisions at square root s=1.96 TeV using an integrated luminosity of 1.0 fb-1 of data collected by the CDF II detector at the Fermilab Tevatron. Using fully reconstructed decays, we measure tau(Lambda b0)=1.593(-0.078)(+0.083)(stat)+/-0.033(syst) ps. This is the single most precise measurement of tau(Lambda b0) and is 3.2sigma higher than the current world average.

Particle multiplicities in lead-lead collisions at the CERN large hadron collider from nonlinear evolution with running coupling corrections.

PubMed

Albacete, Javier L

2007-12-31

We present predictions for the pseudorapidity density of charged particles produced in central Pb-Pb collisions at the LHC. Particle production in such collisions is calculated in the framework of k(t) factorization. The nuclear unintegrated gluon distributions at LHC energies are determined from numerical solutions of the Balitsky-Kovchegov equation including recently calculated running coupling corrections. The initial conditions for the evolution are fixed by fitting Relativistic Heavy Ion Collider data at collision energies square root[sNN]=130 and 200 GeV per nucleon. We obtain dNch(Pb-Pb)/deta(square root[sNN]=5.5 TeV)/eta=0 approximately 1290-1480.

CABS-flex: server for fast simulation of protein structure fluctuations

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2013-01-01

The CABS-flex server (http://biocomp.chem.uw.edu.pl/CABSflex) implements CABS-model–based protocol for the fast simulations of near-native dynamics of globular proteins. In this application, the CABS model was shown to be a computationally efficient alternative to all-atom molecular dynamics—a classical simulation approach. The simulation method has been validated on a large set of molecular dynamics simulation data. Using a single input (user-provided file in PDB format), the CABS-flex server outputs an ensemble of protein models (in all-atom PDB format) reflecting the flexibility of the input structure, together with the accompanying analysis (residue mean-square-fluctuation profile and others). The ensemble of predicted models can be used in structure-based studies of protein functions and interactions. PMID:23658222

CABS-flex: Server for fast simulation of protein structure fluctuations.

PubMed

Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2013-07-01

The CABS-flex server (http://biocomp.chem.uw.edu.pl/CABSflex) implements CABS-model-based protocol for the fast simulations of near-native dynamics of globular proteins. In this application, the CABS model was shown to be a computationally efficient alternative to all-atom molecular dynamics--a classical simulation approach. The simulation method has been validated on a large set of molecular dynamics simulation data. Using a single input (user-provided file in PDB format), the CABS-flex server outputs an ensemble of protein models (in all-atom PDB format) reflecting the flexibility of the input structure, together with the accompanying analysis (residue mean-square-fluctuation profile and others). The ensemble of predicted models can be used in structure-based studies of protein functions and interactions.

The solution of transcendental equations

NASA Technical Reports Server (NTRS)

Agrawal, K. M.; Outlaw, R.

1973-01-01

Some of the existing methods to globally approximate the roots of transcendental equations namely, Graeffe's method, are studied. Summation of the reciprocated roots, Whittaker-Bernoulli method, and the extension of Bernoulli's method via Koenig's theorem are presented. The Aitken's delta squared process is used to accelerate the convergence. Finally, the suitability of these methods is discussed in various cases.

An investigation of empennage buffeting

NASA Technical Reports Server (NTRS)

Lan, C. E.; Lee, I. G.

1986-01-01

Progress in the investigation of empennage buffeting in reviewed. In summary, the following tasks were accomplished: relevant literatures was reviewed; equations for calculating structural response were formulated; root-mean-square values of root bending moment for a 65-degree rigid delta wing were calculated and compared with data; and a water-tunnel test program for an F-18 model was completed.

Nanostructured complex oxides as a route towards thermal behavior in artificial spin ice systems

NASA Astrophysics Data System (ADS)

Chopdekar, R. V.; Li, B.; Wynn, T. A.; Lee, M. S.; Jia, Y.; Liu, Z. Q.; Biegalski, M. D.; Retterer, S. T.; Young, A. T.; Scholl, A.; Takamura, Y.

2017-07-01

We have used soft x-ray photoemission electron microscopy to image the magnetization of single-domain L a0.7S r0.3Mn O3 nanoislands arranged in geometrically frustrated configurations such as square ice and kagome ice geometries. Upon thermal randomization, ensembles of nanoislands with strong interisland magnetic coupling relax towards low-energy configurations. Statistical analysis shows that the likelihood of ensembles falling into low-energy configurations depends strongly on the annealing temperature. Annealing to just below the Curie temperature of the ferromagnetic film (TC=338 K ) allows for a much greater probability of achieving low-energy configurations as compared to annealing above the Curie temperature. At this thermally active temperature of 325 K, the ensemble of ferromagnetic nanoislands explore their energy landscape over time and eventually transition to lower energy states as compared to the frozen-in configurations obtained upon cooling from above the Curie temperature. Thus, this materials system allows for a facile method to systematically study thermal evolution of artificial spin ice arrays of nanoislands at temperatures modestly above room temperature.

Barlow, Peter (1776-1862)

NASA Astrophysics Data System (ADS)

Murdin, P.

2000-11-01

Nautical engineer, born in Norwich, Norfolk, England, professor of mathematics in the Royal Military Academy, Woolwich, where he worked on the strength of ships' timbers, tidal engineering and ships' magnetism. His best known publication is New Mathematical Tables, giving the factors, squares, cubes, square and cube roots, reciprocals and hyperbolic logarithms of all numbers from 1 to 10 000, tog...

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

Wu, Qishi; Berry, M. L..; Grieme, M.

We propose a localization-based radiation source detection (RSD) algorithm using the Ratio of Squared Distance (ROSD) method. Compared with the triangulation-based method, the advantages of this ROSD method are multi-fold: i) source location estimates based on four detectors improve their accuracy, ii) ROSD provides closed-form source location estimates and thus eliminates the imaginary-roots issue, and iii) ROSD produces a unique source location estimate as opposed to two real roots (if any) in triangulation, and obviates the need to identify real phantom roots during clustering.

Gas-liquid coexistence for the boson square-well fluid and the (4)He binodal anomaly.

PubMed

Fantoni, Riccardo

2014-08-01

The binodal of a boson square-well fluid is determined as a function of the particle mass through a quantum Gibbs ensemble Monte Carlo algorithm devised by R. Fantoni and S. Moroni [J. Chem. Phys. (to be published)]. In the infinite mass limit we recover the classical result. As the particle mass decreases, the gas-liquid critical point moves at lower temperatures. We explicitly study the case of a quantum delocalization de Boer parameter close to the one of (4)He. For comparison, we also determine the gas-liquid coexistence curve of (4)He for which we are able to observe the binodal anomaly below the λ-transition temperature.

The contribution of transient counterion imbalances to DNA bending fluctuations.

PubMed

Manning, Gerald S

2006-05-01

A two-sided model for DNA is employed to analyze fluctuations of the spatial distribution of condensed counterions and the effect of these fluctuations on transient bending. We analyze two classes of fluctuations. In the first, the number of condensed counterions on one side of the DNA remains at its average value, while on the other side, counterions are lost to bulk solution or gained from it. The second class of fluctuations is characterized by movement of some counterions from one side of the DNA to the other. The root-mean-square fluctuation for each class is calculated from counterion condensation theory. The amplitude of the root-mean-square fluctuation depends on the ionic strength as well as the length of the segment considered and is of the order 5-10%. Both classes of fluctuation result in transient bends toward the side of greater counterion density. The bending amplitudes are approximately 15% of the total root-mean-square bends associated with the persistence length of DNA. We are thus led to suggest that asymmetric fluctuations of counterion density contribute modestly but significantly toward the aggregate of thermalized solvent fluctuations that cause bending deformations of DNA free in solution. The calculations support the idea that counterions may exert some modulating influence on the fine structure of DNA.

On the local structure of spacetime in ghost-free bimetric theory and massive gravity

NASA Astrophysics Data System (ADS)

Hassan, S. F.; Kocic, Mikica

2018-05-01

The ghost-free bimetric theory describes interactions of gravity with another spin-2 field in terms of two Lorentzian metrics. However, if the two metrics do not admit compatible notions of space and time, the formulation of the initial value problem becomes problematic. Furthermore, the interaction potential is given in terms of the square root of a matrix which is in general nonunique and possibly nonreal. In this paper we show that both these issues are evaded by requiring reality and general covariance of the equations. First we prove that the reality of the square root matrix leads to a classification of the allowed metrics in terms of the intersections of their null cones. Then, the requirement of general covariance further restricts the allowed metrics to geometries that admit compatible notions of space and time. It also selects a unique definition of the square root matrix. The restrictions are compatible with the equations of motion. These results ensure that the ghost-free bimetric theory can be defined unambiguously and that the two metrics always admit compatible 3+1 decompositions, at least locally. In particular, these considerations rule out certain solutions of massive gravity with locally Closed Causal Curves, which have been used to argue that the theory is acausal.

Negligible fractionation of Kr and Xe isotopes by molecular diffusion in water

NASA Astrophysics Data System (ADS)

Tyroller, Lina; Brennwald, Matthias S.; Busemann, Henner; Maden, Colin; Baur, Heinrich; Kipfer, Rolf

2018-06-01

Molecular diffusion is a key transport process for noble gases in water. Such diffusive transport is often thought to cause a mass-dependent fractionation of noble gas isotopes that is inversely proportional to the square root of the ratio of their atomic mass, referred to as the square root relation. Previous studies, challenged the commonly held assumption that the square root relation adequately describes the behaviour of noble gas isotopes diffusing through water. However, the effect of diffusion on noble gas isotopes has only been determined experimentally for He, Ne and Ar to date, whereas the extent of fractionation of Kr and Xe has not been measured. In the present study the fractionation of Kr and Xe isotopes diffusing through water immobilised by adding agar was quantified through measuring the respective isotope ratio after diffusing through the immobilised water. No fractionation of Kr and Xe isotopes was observed, even using high-precision noble gas analytics. These results complement our current understanding on isotopic fractionation of noble gases diffusing through water. Therefore this complete data set builds a robust basis to describe molecular diffusion of noble gases in water in a physical sound manner which is fundamental to assess the physical aspects of gas dynamics in aquatic systems.

Stability analysis of the Peregrine solution via squared eigenfunctions

NASA Astrophysics Data System (ADS)

Schober, C. M.; Strawn, M.

2017-10-01

A preliminary numerical investigation involving ensembles of perturbed initial data for the Peregrine soliton (the lowest order rational solution of the nonlinear Schrödinger equation) indicates that it is unstable [16]. In this paper we analytically investigate the linear stability of the Peregrine soliton, appealing to the fact that the Peregrine solution can be viewed as the singular limit of a single mode spatially periodic breathers (SPB). The "squared eigenfunction" connection between the Zakharov-Shabat (Z-S) system and the linearized NLS equation is employed in the stability analysis. Specifically, we determine the eigenfunctions of the Z-S system associated with the Peregrine soliton and construct a family of solutions of the associated linearized NLS (about the Peregrine) in terms of quadratic products of components of the eigenfunctions (i.e., the squared eigenfunction). We find there exist solutions of the linearization that grow exponentially in time, thus showing the Peregrine soliton is linearly unstable.

Rovibrational spectra of ammonia. I. Unprecedented accuracy of a potential energy surface used with nonadiabatic corrections.

PubMed

Huang, Xinchuan; Schwenke, David W; Lee, Timothy J

2011-01-28

In this work, we build upon our previous work on the theoretical spectroscopy of ammonia, NH(3). Compared to our 2008 study, we include more physics in our rovibrational calculations and more experimental data in the refinement procedure, and these enable us to produce a potential energy surface (PES) of unprecedented accuracy. We call this the HSL-2 PES. The additional physics we include is a second-order correction for the breakdown of the Born-Oppenheimer approximation, and we find it to be critical for improved results. By including experimental data for higher rotational levels in the refinement procedure, we were able to greatly reduce our systematic errors for the rotational dependence of our predictions. These additions together lead to a significantly improved total angular momentum (J) dependence in our computed rovibrational energies. The root-mean-square error between our predictions using the HSL-2 PES and the reliable energy levels from the HITRAN database for J = 0-6 and J = 7∕8 for (14)NH(3) is only 0.015 cm(-1) and 0.020∕0.023 cm(-1), respectively. The root-mean-square errors for the characteristic inversion splittings are approximately 1∕3 smaller than those for energy levels. The root-mean-square error for the 6002 J = 0-8 transition energies is 0.020 cm(-1). Overall, for J = 0-8, the spectroscopic data computed with HSL-2 is roughly an order of magnitude more accurate relative to our previous best ammonia PES (denoted HSL-1). These impressive numbers are eclipsed only by the root-mean-square error between our predictions for purely rotational transition energies of (15)NH(3) and the highly accurate Cologne database (CDMS): 0.00034 cm(-1) (10 MHz), in other words, 2 orders of magnitude smaller. In addition, we identify a deficiency in the (15)NH(3) energy levels determined from a model of the experimental data.

The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration.

PubMed

Farina, Dario; Leclerc, Frédéric; Arendt-Nielsen, Lars; Buttelli, Olivier; Madeleine, Pascal

2008-02-01

The aim of the study was to confirm the hypothesis that the longer a contraction is sustained, the larger are the changes in the spatial distribution of muscle activity. For this purpose, surface electromyographic (EMG) signals were recorded with a 13 x 5 grid of electrodes from the upper trapezius muscle of 11 healthy male subjects during static contractions with shoulders 90 degrees abducted until endurance. The entropy (degree of uniformity) and center of gravity of the EMG root mean square map were computed to assess spatial inhomogeneity in muscle activation and changes over time in EMG amplitude spatial distribution. At the endurance time, entropy decreased (mean+/-SD, percent change 2.0+/-1.6%; P<0.0001) and the center of gravity moved in the cranial direction (shift 11.2+/-6.1mm; P<0.0001) with respect to the beginning of the contraction. The shift in the center of gravity was positively correlated with endurance time (R(2)=0.46, P<0.05), thus subjects with larger shift in the activity map showed longer endurance time. The percent variation in average (over the grid) root mean square was positively correlated with the shift in the center of gravity (R(2)=0.51, P<0.05). Moreover, the shift in the center of gravity was negatively correlated to both initial and final (at the endurance) entropy (R(2)=0.54 and R(2)=0.56, respectively; P<0.01 in both cases), indicating that subjects with less uniform root mean square maps had larger shift of the center of gravity over time. The spatial changes in root mean square EMG were likely due to spatially-dependent changes in motor unit activation during the sustained contraction. It was concluded that the changes in spatial muscle activity distribution play a role in the ability to maintain a static contraction.

Development and evaluation of a soft wearable weight support device for reducing muscle fatigue on shoulder

PubMed Central

Cho, Kyu-Jin

2017-01-01

Compensating the weight of human limbs is important in reducing muscle fatigue experienced by manual laborers. In this study, a compact and lightweight soft wearable weight support device was developed and evaluated. The device supports gravitational force on the shoulder at any arm posture, although there are some limitations in its assistive performance. The device actuator consists of a cam-rod structure, a tendon-driven mechanism, and a rubber band. The desired assistive torque is translated to the shoulder joint along a tendon routing structure. Device performance was evaluated by measuring muscle activation in with-assist and without-assist conditions. Muscle activation on the deltoid was measured by surface electromyography. An experimental protocol consisting of a series of exercises was executed with six healthy subjects. The subjects raised and lowered their arm from 0 to 100 degrees for 30 times under eight conditions, which were combined with-assist and without-assist conditions, and holding the horizontal angle of the arm at 0, 30, 60, or 90 degrees against the sagittal plane. Surface electromyography data were pre-processed and analyzed using a root mean square method. When muscle fatigue occurs, the root mean square of the surface electromyography increases nonlinearly. This was calculated using the standard deviation of the root mean square. Three of six subjects showed decreased variation of the root mean square between the exercises in the with-assist condition. One subject’s result was significantly reduced (by about 57.6%) in the with-assist condition. In contrast, two subjects did not show significant difference between measurements taken in the with-assist and without-assist conditions. One subject was dropped from the experiment because the device did not fit the subject’s body. In conclusion, the effectiveness of the soft wearable weight support device in supporting shoulder movements was verified through the decreased variation of muscle activation. PMID:28291825

Development and evaluation of a soft wearable weight support device for reducing muscle fatigue on shoulder.

PubMed

Park, Daegeun; Cho, Kyu-Jin

2017-01-01

Compensating the weight of human limbs is important in reducing muscle fatigue experienced by manual laborers. In this study, a compact and lightweight soft wearable weight support device was developed and evaluated. The device supports gravitational force on the shoulder at any arm posture, although there are some limitations in its assistive performance. The device actuator consists of a cam-rod structure, a tendon-driven mechanism, and a rubber band. The desired assistive torque is translated to the shoulder joint along a tendon routing structure. Device performance was evaluated by measuring muscle activation in with-assist and without-assist conditions. Muscle activation on the deltoid was measured by surface electromyography. An experimental protocol consisting of a series of exercises was executed with six healthy subjects. The subjects raised and lowered their arm from 0 to 100 degrees for 30 times under eight conditions, which were combined with-assist and without-assist conditions, and holding the horizontal angle of the arm at 0, 30, 60, or 90 degrees against the sagittal plane. Surface electromyography data were pre-processed and analyzed using a root mean square method. When muscle fatigue occurs, the root mean square of the surface electromyography increases nonlinearly. This was calculated using the standard deviation of the root mean square. Three of six subjects showed decreased variation of the root mean square between the exercises in the with-assist condition. One subject's result was significantly reduced (by about 57.6%) in the with-assist condition. In contrast, two subjects did not show significant difference between measurements taken in the with-assist and without-assist conditions. One subject was dropped from the experiment because the device did not fit the subject's body. In conclusion, the effectiveness of the soft wearable weight support device in supporting shoulder movements was verified through the decreased variation of muscle activation.

Temperature sensitivity of soil microbial activity modeled by the square root equation as a unifying model to differentiate between direct temperature effects and microbial community adaptation.

PubMed

Bååth, Erland

2018-07-01

Numerous models have been used to express the temperature sensitivity of microbial growth and activity in soil making it difficult to compare results from different habitats. Q10 still is one of the most common ways to express temperature relationships. However, Q10 is not constant with temperature and will differ depending on the temperature interval used for the calculation. The use of the square root (Ratkowsky) relationship between microbial activity (A) and temperature below optimum temperature, √A = a × (T-T min ), is proposed as a simple and adequate model that allow for one descriptor, T min (a theoretical minimum temperature for growth and activity), to estimate correct Q10-values over the entire in situ temperature interval. The square root model can adequately describe both microbial growth and respiration, allowing for an easy determination of T min . Q10 for any temperature interval can then be calculated by Q10 = [(T + 10 - T min )/(T-T min )] 2 , where T is the lowest temperature in the Q10 comparison. T min also describes the temperature adaptation of the microbial community. An envelope of T min covering most natural soil habitats varying between -15°C (cold habitats like Antarctica/Arctic) to 0°C (tropical habitats like rain forests and deserts) is suggested, with an 0.3°C increase in T min per 1°C increase in mean annual temperature. It is shown that the main difference between common temperature relationships used in global models is differences in the assumed temperature adaptation of the soil microbial community. The use of the square root equation will allow for one descriptor, T min , determining the temperature response of soil microorganisms, and at the same time allow for comparing temperature sensitivity of microbial activity between habitats, including future projections. © 2018 John Wiley & Sons Ltd.

Finding the Root Causes of Statistical Inconsistency in Community Earth System Model Output

NASA Astrophysics Data System (ADS)

Milroy, D.; Hammerling, D.; Baker, A. H.

2017-12-01

Baker et al (2015) developed the Community Earth System Model Ensemble Consistency Test (CESM-ECT) to provide a metric for software quality assurance by determining statistical consistency between an ensemble of CESM outputs and new test runs. The test has proved useful for detecting statistical difference caused by compiler bugs and errors in physical modules. However, detection is only the necessary first step in finding the causes of statistical difference. The CESM is a vastly complex model comprised of millions of lines of code which is developed and maintained by a large community of software engineers and scientists. Any root cause analysis is correspondingly challenging. We propose a new capability for CESM-ECT: identifying the sections of code that cause statistical distinguishability. The first step is to discover CESM variables that cause CESM-ECT to classify new runs as statistically distinct, which we achieve via Randomized Logistic Regression. Next we use a tool developed to identify CESM components that define or compute the variables found in the first step. Finally, we employ the application Kernel GENerator (KGEN) created in Kim et al (2016) to detect fine-grained floating point differences. We demonstrate an example of the procedure and advance a plan to automate this process in our future work.

Computed tomography assessment of the efficiency of different techniques for removal of root canal filling material.

PubMed

Dall'Agnol, Cristina; Hartmann, Mateus Silveira Martins; Barletta, Fernando Branco

2008-01-01

This study evaluated the efficiency of different techniques for removal of filling material from root canals, using computed tomography (CT). Sixty mesial roots from extracted human mandibular molars were used. Root canals were filled and, after 6 months, the teeth were randomly assigned to 3 groups, according to the root-filling removal technique: Group A - hand instrumentation with K-type files; Group B - reciprocating instrumentation with engine-driven K-type files; and Group C rotary instrumentation with engine-driven ProTaper system. CT scans were used to assess the volume of filling material inside the root canals before and after the removal procedure. In both moments, the area of filling material was outlined by an experienced radiologist and the volume of filling material was automatically calculated by the CT software program. Based on the volume of initial and residual filling material of each specimen, the percentage of filling material removed from the root canals by the different techniques was calculated. Data were analyzed statistically by ANOVA and chi-square test for linear trend (?=0.05). No statistically significant difference (p=0.36) was found among the groups regarding the percent means of removed filling material. The analysis of the association between the percentage of filling material removal (high or low) and the proposed techniques by chi-square test showed statistically significant difference (p=0.015), as most cases in group B (reciprocating technique) presented less than 50% of filling material removed (low percent removal). In conclusion, none of the techniques evaluated in this study was effective in providing complete removal of filling material from the root canals.

Rapid Isolation and Detection for RNA Biomarkers for TBI Diagnostics

DTIC Science & Technology

2015-10-01

V., Grape and wine sensory attributes correlate with pattern- based discrimination of Cabernet Sauvignon wines by a peptidic sensor array, Tetrahedron... wine samples. Partial Least Squares Regression (PLSR) was used for the correlation of wine sensory attributes to the peptide-based receptor...responses. Data analysis was done using the software XLSTAT Addinsoft, NewYork) and R.Absorbance values due to wine without the sensing ensembles were

Ensemble Methods

NASA Astrophysics Data System (ADS)

Re, Matteo; Valentini, Giorgio

2012-03-01

Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been proposed to explain the characteristics and the successful application of ensembles to different application domains. For instance, Allwein, Schapire, and Singer interpreted the improved generalization capabilities of ensembles of learning machines in the framework of large margin classifiers [4,177], Kleinberg in the context of stochastic discrimination theory [112], and Breiman and Friedman in the light of the bias-variance analysis borrowed from classical statistics [21,70]. Empirical studies showed that both in classification and regression problems, ensembles improve on single learning machines, and moreover large experimental studies compared the effectiveness of different ensemble methods on benchmark data sets [10,11,49,188]. The interest in this research area is motivated also by the availability of very fast computers and networks of workstations at a relatively low cost that allow the implementation and the experimentation of complex ensemble methods using off-the-shelf computer platforms. However, as explained in Section 26.2 there are deeper reasons to use ensembles of learning machines, motivated by the intrinsic characteristics of the ensemble methods. The main aim of this chapter is to introduce ensemble methods and to provide an overview and a bibliography of the main areas of research, without pretending to be exhaustive or to explain the detailed characteristics of each ensemble method. The paper is organized as follows. In the next section, the main theoretical and practical reasons for combining multiple learners are introduced. Section 26.3 depicts the main taxonomies on ensemble methods proposed in the literature. In Section 26.4 and 26.5, we present an overview of the main supervised ensemble methods reported in the literature, adopting a simple taxonomy, originally proposed in Ref. [201]. Applications of ensemble methods are only marginally considered, but a specific section on some relevant applications of ensemble methods in astronomy and astrophysics has been added (Section 26.6). The conclusion (Section 26.7) ends this paper and lists some issues not covered in this work.

Cost-sensitive AdaBoost algorithm for ordinal regression based on extreme learning machine.

PubMed

Riccardi, Annalisa; Fernández-Navarro, Francisco; Carloni, Sante

2014-10-01

In this paper, the well known stagewise additive modeling using a multiclass exponential (SAMME) boosting algorithm is extended to address problems where there exists a natural order in the targets using a cost-sensitive approach. The proposed ensemble model uses an extreme learning machine (ELM) model as a base classifier (with the Gaussian kernel and the additional regularization parameter). The closed form of the derived weighted least squares problem is provided, and it is employed to estimate analytically the parameters connecting the hidden layer to the output layer at each iteration of the boosting algorithm. Compared to the state-of-the-art boosting algorithms, in particular those using ELM as base classifier, the suggested technique does not require the generation of a new training dataset at each iteration. The adoption of the weighted least squares formulation of the problem has been presented as an unbiased and alternative approach to the already existing ELM boosting techniques. Moreover, the addition of a cost model for weighting the patterns, according to the order of the targets, enables the classifier to tackle ordinal regression problems further. The proposed method has been validated by an experimental study by comparing it with already existing ensemble methods and ELM techniques for ordinal regression, showing competitive results.

Post-processing through linear regression

NASA Astrophysics Data System (ADS)

van Schaeybroeck, B.; Vannitsem, S.

2011-03-01

Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

Diffuse-flow conceptualization and simulation of the Edwards aquifer, San Antonio region, Texas

USGS Publications Warehouse

Lindgren, R.J.

2006-01-01

A numerical ground-water-flow model (hereinafter, the conduit-flow Edwards aquifer model) of the karstic Edwards aquifer in south-central Texas was developed for a previous study on the basis of a conceptualization emphasizing conduit development and conduit flow, and included simulating conduits as one-cell-wide, continuously connected features. Uncertainties regarding the degree to which conduits pervade the Edwards aquifer and influence ground-water flow, as well as other uncertainties inherent in simulating conduits, raised the question of whether a model based on the conduit-flow conceptualization was the optimum model for the Edwards aquifer. Accordingly, a model with an alternative hydraulic conductivity distribution without conduits was developed in a study conducted during 2004-05 by the U.S. Geological Survey, in cooperation with the San Antonio Water System. The hydraulic conductivity distribution for the modified Edwards aquifer model (hereinafter, the diffuse-flow Edwards aquifer model), based primarily on a conceptualization in which flow in the aquifer predominantly is through a network of numerous small fractures and openings, includes 38 zones, with hydraulic conductivities ranging from 3 to 50,000 feet per day. Revision of model input data for the diffuse-flow Edwards aquifer model was limited to changes in the simulated hydraulic conductivity distribution. The root-mean-square error for 144 target wells for the calibrated steady-state simulation for the diffuse-flow Edwards aquifer model is 20.9 feet. This error represents about 3 percent of the total head difference across the model area. The simulated springflows for Comal and San Marcos Springs for the calibrated steady-state simulation were within 2.4 and 15 percent of the median springflows for the two springs, respectively. The transient calibration period for the diffuse-flow Edwards aquifer model was 1947-2000, with 648 monthly stress periods, the same as for the conduit-flow Edwards aquifer model. The root-mean-square error for a period of drought (May-November 1956) for the calibrated transient simulation for 171 target wells is 33.4 feet, which represents about 5 percent of the total head difference across the model area. The root-mean-square error for a period of above-normal rainfall (November 1974-July 1975) for the calibrated transient simulation for 169 target wells is 25.8 feet, which represents about 4 percent of the total head difference across the model area. The root-mean-square error ranged from 6.3 to 30.4 feet in 12 target wells with long-term water-level measurements for varying periods during 1947-2000 for the calibrated transient simulation for the diffuse-flow Edwards aquifer model, and these errors represent 5.0 to 31.3 percent of the range in water-level fluctuations of each of those wells. The root-mean-square errors for the five major springs in the San Antonio segment of the aquifer for the calibrated transient simulation, as a percentage of the range of discharge fluctuations measured at the springs, varied from 7.2 percent for San Marcos Springs and 8.1 percent for Comal Springs to 28.8 percent for Leona Springs. The root-mean-square errors for hydraulic heads for the conduit-flow Edwards aquifer model are 27, 76, and 30 percent greater than those for the diffuse-flow Edwards aquifer model for the steady-state, drought, and above-normal rainfall synoptic time periods, respectively. The goodness-of-fit between measured and simulated springflows is similar for Comal, San Marcos, and Leona Springs for the diffuse-flow Edwards aquifer model and the conduit-flow Edwards aquifer model. The root-mean-square errors for Comal and Leona Springs were 15.6 and 21.3 percent less, respectively, whereas the root-mean-square error for San Marcos Springs was 3.3 percent greater for the diffuse-flow Edwards aquifer model compared to the conduit-flow Edwards aquifer model. The root-mean-square errors for San Antonio and San Pedro Springs were appreciably greater, 80.2 and 51.0 percent, respectively, for the diffuse-flow Edwards aquifer model. The simulated water budgets for the diffuse-flow Edwards aquifer model are similar to those for the conduit-flow Edwards aquifer model. Differences in percentage of total sources or discharges for a budget component are 2.0 percent or less for all budget components for the steady-state and transient simulations. The largest difference in terms of the magnitude of water budget components for the transient simulation for 1956 was a decrease of about 10,730 acre-feet per year (about 2 per-cent) in springflow for the diffuse-flow Edwards aquifer model compared to the conduit-flow Edwards aquifer model. This decrease in springflow (a water budget discharge) was largely offset by the decreased net loss of water from storage (a water budget source) of about 10,500 acre-feet per year.

Design and comparative performance analysis of different chirping profiles of tanh apodized fiber Bragg grating and comparison with the dispersion compensation fiber for long-haul transmission system

NASA Astrophysics Data System (ADS)

Dar, Aasif Bashir; Jha, Rakesh Kumar

2017-03-01

Various dispersion compensation units are presented and evaluated in this paper. These dispersion compensation units include dispersion compensation fiber (DCF), DCF merged with fiber Bragg grating (FBG) (joint technique), and linear, square root, and cube root chirped tanh apodized FBG. For the performance evaluation 10 Gb/s NRZ transmission system over 100-km-long single-mode fiber is used. The three chirped FBGs are optimized individually to yield pulse width reduction percentage (PWRP) of 86.66, 79.96, 62.42% for linear, square root, and cube root, respectively. The DCF and Joint technique both provide a remarkable PWRP of 94.45 and 96.96%, respectively. The performance of optimized linear chirped tanh apodized FBG and DCF is compared for long-haul transmission system on the basis of quality factor of received signal. For both the systems maximum transmission distance is calculated such that quality factor is ≥ 6 at the receiver and result shows that performance of FBG is comparable to that of DCF with advantages of very low cost, small size and reduced nonlinear effects.

Synchronous front-face fluorescence spectroscopy for authentication of the adulteration of edible vegetable oil with refined used frying oil.

PubMed

Tan, Jin; Li, Rong; Jiang, Zi-Tao; Tang, Shu-Hua; Wang, Ying; Shi, Meng; Xiao, Yi-Qian; Jia, Bin; Lu, Tian-Xiang; Wang, Hao

2017-02-15

Synchronous front-face fluorescence spectroscopy has been developed for the discrimination of used frying oil (UFO) from edible vegetable oil (EVO), the estimation of the using time of UFO, and the determination of the adulteration of EVO with UFO. Both the heating time of laboratory prepared UFO and the adulteration of EVO with UFO could be determined by partial least squares regression (PLSR). To simulate the EVO adulteration with UFO, for each kind of oil, fifty adulterated samples at the adulterant amounts range of 1-50% were prepared. PLSR was then adopted to build the model and both full (leave-one-out) cross-validation and external validation were performed to evaluate the predictive ability. Under the optimum condition, the plots of observed versus predicted values exhibited high linearity (R(2)>0.96). The root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) were both lower than 3%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Feasibility of using near infrared spectroscopy to detect and quantify an adulterant in high quality sandalwood oil.

PubMed

Kuriakose, Saji; Joe, I Hubert

2013-11-01

Determination of the authenticity of essential oils has become more significant, in recent years, following some illegal adulteration and contamination scandals. The present investigative study focuses on the application of near infrared spectroscopy to detect sample authenticity and quantify economic adulteration of sandalwood oils. Several data pre-treatments are investigated for calibration and prediction using partial least square regression (PLSR). The quantitative data analysis is done using a new spectral approach - full spectrum or sequential spectrum. The optimum number of PLS components is obtained according to the lowest root mean square error of calibration (RMSEC=0.00009% v/v). The lowest root mean square error of prediction (RMSEP=0.00016% v/v) in the test set and the highest coefficient of determination (R(2)=0.99989) are used as the evaluation tools for the best model. A nonlinear method, locally weighted regression (LWR), is added to extract nonlinear information and to compare with the linear PLSR model. Copyright © 2013 Elsevier B.V. All rights reserved.

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Slojkowski, Steven; Lowe, Jonathan; Woodburn, James

2015-01-01

Since launch, the FDF has performed daily OD for LRO using the Goddard Trajectory Determination System (GTDS). GTDS is a batch least-squares (BLS) estimator. The tracking data arc for OD is 36 hours. Current operational OD uses 200 x 200 lunar gravity, solid lunar tides, solar radiation pressure (SRP) using a spherical spacecraft area model, and point mass gravity for the Earth, Sun, and Jupiter. LRO tracking data consists of range and range-rate measurements from: Universal Space Network (USN) stations in Sweden, Germany, Australia, and Hawaii. A NASA antenna at White Sands, New Mexico (WS1S). NASA Deep Space Network (DSN) stations. DSN data was sparse and not included in this study. Tracking is predominantly (50) from WS1S. The OD accuracy requirements are: Definitive ephemeris accuracy of 500 meters total position root-mean-squared (RMS) and18 meters radial RMS. Predicted orbit accuracy less than 800 meters root sum squared (RSS) over an 84-hour prediction span.

Application of Rapid Visco Analyser (RVA) viscograms and chemometrics for maize hardness characterisation.

PubMed

Guelpa, Anina; Bevilacqua, Marta; Marini, Federico; O'Kennedy, Kim; Geladi, Paul; Manley, Marena

2015-04-15

It has been established in this study that the Rapid Visco Analyser (RVA) can describe maize hardness, irrespective of the RVA profile, when used in association with appropriate multivariate data analysis techniques. Therefore, the RVA can complement or replace current and/or conventional methods as a hardness descriptor. Hardness modelling based on RVA viscograms was carried out using seven conventional hardness methods (hectoliter mass (HLM), hundred kernel mass (HKM), particle size index (PSI), percentage vitreous endosperm (%VE), protein content, percentage chop (%chop) and near infrared (NIR) spectroscopy) as references and three different RVA profiles (hard, soft and standard) as predictors. An approach using locally weighted partial least squares (LW-PLS) was followed to build the regression models. The resulted prediction errors (root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP)) for the quantification of hardness values were always lower or in the same order of the laboratory error of the reference method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Feasibility of using near infrared spectroscopy to detect and quantify an adulterant in high quality sandalwood oil

NASA Astrophysics Data System (ADS)

Kuriakose, Saji; Joe, I. Hubert

2013-11-01

Determination of the authenticity of essential oils has become more significant, in recent years, following some illegal adulteration and contamination scandals. The present investigative study focuses on the application of near infrared spectroscopy to detect sample authenticity and quantify economic adulteration of sandalwood oils. Several data pre-treatments are investigated for calibration and prediction using partial least square regression (PLSR). The quantitative data analysis is done using a new spectral approach - full spectrum or sequential spectrum. The optimum number of PLS components is obtained according to the lowest root mean square error of calibration (RMSEC = 0.00009% v/v). The lowest root mean square error of prediction (RMSEP = 0.00016% v/v) in the test set and the highest coefficient of determination (R2 = 0.99989) are used as the evaluation tools for the best model. A nonlinear method, locally weighted regression (LWR), is added to extract nonlinear information and to compare with the linear PLSR model.

Real-time core body temperature estimation from heart rate for first responders wearing different levels of personal protective equipment.

PubMed

Buller, Mark J; Tharion, William J; Duhamel, Cynthia M; Yokota, Miyo

2015-01-01

First responders often wear personal protective equipment (PPE) for protection from on-the-job hazards. While PPE ensembles offer individuals protection, they limit one's ability to thermoregulate, and can place the wearer in danger of heat exhaustion and higher cardiac stress. Automatically monitoring thermal-work strain is one means to manage these risks, but measuring core body temperature (Tc) has proved problematic. An algorithm that estimates Tc from sequential measures of heart rate (HR) was compared to the observed Tc from 27 US soldiers participating in three different chemical/biological training events (45-90 min duration) while wearing PPE. Hotter participants (higher Tc) averaged (HRs) of 140 bpm and reached Tc around 39 °C. Overall the algorithm had a small bias (0.02 °C) and root mean square error (0.21 °C). Limits of agreement (LoA ± 0.48 °C) were similar to comparisons of Tc measured by oesophageal and rectal probes. The algorithm shows promise for use in real-time monitoring of encapsulated first responders. An algorithm to estimate core temperature (Tc) from non-invasive measures of HR was validated. Three independent studies (n = 27) compared the estimated Tc to the observed Tc in humans participating in chemical/ biological hazard training. The algorithm’s bias and variance to observed data were similar to that found from comparisons of oesophageal and rectal measurements.

Development of an analytical model for estimating global terrestrial carbon assimilation using a rate-limitation framework

NASA Astrophysics Data System (ADS)

Donohue, Randall; Yang, Yuting; McVicar, Tim; Roderick, Michael

2016-04-01

A fundamental question in climate and ecosystem science is "how does climate regulate the land surface carbon budget?" To better answer that question, here we develop an analytical model for estimating mean annual terrestrial gross primary productivity (GPP), which is the largest carbon flux over land, based on a rate-limitation framework. Actual GPP (climatological mean from 1982 to 2010) is calculated as a function of the balance between two GPP potentials defined by the climate (i.e., precipitation and solar radiation) and a third parameter that encodes other environmental variables and modifies the GPP-climate relationship. The developed model was tested at three spatial scales using different GPP sources, i.e., (1) observed GPP from 94 flux-sites, (2) modelled GPP (using the model-tree-ensemble approach) at 48654 (0.5 degree) grid-cells and (3) at 32 large catchments across the globe. Results show that the proposed model could account for the spatial GPP patterns, with a root-mean-square error of 0.70, 0.65 and 0.3 g C m-2 d-1 and R2 of 0.79, 0.92 and 0.97 for the flux-site, grid-cell and catchment scales, respectively. This analytical GPP model shares a similar form with the Budyko hydroclimatological model, which opens the possibility of a general analytical framework to analyze the linked carbon-water-energy cycles.

Evaluating MTCLIM for incident daily solar radiation and humidity in diverse meteorological and topographical environments in the main Hawaiian Islands

NASA Astrophysics Data System (ADS)

Giambelluca, T. W.; Needham, H.; Longman, R. J.

2017-12-01

Continuous and high resolution climatologies are important inputs in determining future scenarios for land processes. In Hawaíi, a lack of continuous meteorological data has been a problem for both ecological and hydrological research of land-surface processes at daily time scales. For downward shortwave radiation (SWdown) and relative humidity (RH) climate variables, the number of surface stations which record daily values are limited and tend to be situated at city airports or in convenient locations leaving large sections of the islands underrepresented. The aim of this study is to evaluate the rationale behind using the mountain microclimate simulator MTCLIM to obtain a gridded observation based ensemble of SWdown and RH data at a daily increment for the period of 1990-2014 for the main Hawaiian Islands. Preliminary results, testing model output with observed data, show mean bias errors (%MBE) of 1.15 W/m2 for SWdown and -0.8% for RH. Mean absolute errors (%MAE) of 32.83 W/m2 SWdown and 14.96% RH, with root mean square errors (%RMSE) of 40.17 W/m2 SWdown and 11.75% RH. Further optimization of the model and additional methods to reduce errors are being investigated to improve the model's functionality with Hawaíi's extreme climate gradients.

An application of hybrid downscaling model to forecast summer precipitation at stations in China

NASA Astrophysics Data System (ADS)

Liu, Ying; Fan, Ke

2014-06-01

A pattern prediction hybrid downscaling method was applied to predict summer (June-July-August) precipitation at China 160 stations. The predicted precipitation from the downscaling scheme is available one month before. Four predictors were chosen to establish the hybrid downscaling scheme. The 500-hPa geopotential height (GH5) and 850-hPa specific humidity (q85) were from the skillful predicted output of three DEMETER (Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction) general circulation models (GCMs). The 700-hPa geopotential height (GH7) and sea level pressure (SLP) were from reanalysis datasets. The hybrid downscaling scheme (HD-4P) has better prediction skill than a conventional statistical downscaling model (SD-2P) which contains two predictors derived from the output of GCMs, although two downscaling schemes were performed to improve the seasonal prediction of summer rainfall in comparison with the original output of the DEMETER GCMs. In particular, HD-4P downscaling predictions showed lower root mean square errors than those based on the SD-2P model. Furthermore, the HD-4P downscaling model reproduced the China summer precipitation anomaly centers more accurately than the scenario of the SD-2P model in 1998. A hybrid downscaling prediction should be effective to improve the prediction skill of summer rainfall at stations in China.

Sweat loss prediction using a multi-model approach

NASA Astrophysics Data System (ADS)

Xu, Xiaojiang; Santee, William R.

2011-07-01

A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.

Removing Shape-Preserving Transformations in Square-Root Elastic (SRE) Framework for Shape Analysis of Curves

PubMed Central

Joshi, Shantanu H.; Klassen, Eric; Srivastava, Anuj; Jermyn, Ian

2011-01-01

This paper illustrates and extends an efficient framework, called the square-root-elastic (SRE) framework, for studying shapes of closed curves, that was first introduced in [2]. This framework combines the strengths of two important ideas - elastic shape metric and path-straightening methods - for finding geodesics in shape spaces of curves. The elastic metric allows for optimal matching of features between curves while path-straightening ensures that the algorithm results in geodesic paths. This paper extends this framework by removing two important shape preserving transformations: rotations and re-parameterizations, by forming quotient spaces and constructing geodesics on these quotient spaces. These ideas are demonstrated using experiments involving 2D and 3D curves. PMID:21738385

Force and Directional Force Modulation Effects on Accuracy and Variability in Low-Level Pinch Force Tracking.

PubMed

Park, Sangsoo; Spirduso, Waneen; Eakin, Tim; Abraham, Lawrence

2018-01-01

The authors investigated how varying the required low-level forces and the direction of force change affect accuracy and variability of force production in a cyclic isometric pinch force tracking task. Eighteen healthy right-handed adult volunteers performed the tracking task over 3 different force ranges. Root mean square error and coefficient of variation were higher at lower force levels and during minimum reversals compared with maximum reversals. Overall, the thumb showed greater root mean square error and coefficient of variation scores than did the index finger during maximum reversals, but not during minimum reversals. The observed impaired performance during minimum reversals might originate from history-dependent mechanisms of force production and highly coupled 2-digit performance.

Constraining f(T) teleparallel gravity by big bang nucleosynthesis: f(T) cosmology and BBN.

PubMed

Capozziello, S; Lambiase, G; Saridakis, E N

2017-01-01

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f ( T ) gravity. The three most studied viable f ( T ) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f ( T ) models can successfully satisfy the BBN constraints.

Research relative to the development of a cryogenic microwave cavity gradiometer for orbital use

NASA Technical Reports Server (NTRS)

Grossi, M. D.

1985-01-01

Technical approaches to increase the sensitivity of a non-cryogenic gradiometer toward the goal of 0.001 EU/square root of Hz, with solutions that have the potential of achieving an even more ambitious threshold, such as 0.0001 EU/square root of Hz are discussed. This goal can be achieved with a gradiometer design in which the proof masses are each suspended from two small arms, the torsion of which is directly related to the displacement of the sensing element. A negative-spring action, aimed at reducing the resonance frequency, is provided in this design by means of an external electrostatic field. This configuration of the instrument is also suitable for use in a tensorial arrangement.

Suppression of hadrons with large transverse momentum in central Au+Au collisions at root square[s(NN)] = 130 GeV.

PubMed

Adcox, K; Adler, S S; Ajitanand, N N; Akiba, Y; Alexander, J; Aphecetche, L; Arai, Y; Aronson, S H; Averbeck, R; Awes, T C; Barish, K N; Barnes, P D; Barrette, J; Bassalleck, B; Bathe, S; Baublis, V; Bazilevsky, A; Belikov, S; Bellaiche, F G; Belyaev, S T; Bennett, M J; Berdnikov, Y; Botelho, S; Brooks, M L; Brown, D S; Bruner, N; Bucher, D; Buesching, H; Bumazhnov, V; Bunce, G; Burward-Hoy, J; Butsyk, S; Carey, T A; Chand, P; Chang, J; Chang, W C; Chavez, L L; Chernichenko, S; Chi, C Y; Chiba, J; Chiu, M; Choudhury, R K; Christ, T; Chujo, T; Chung, M S; Chung, P; Cianciolo, V; Cole, B A; D'Enterria, D G; David, G; Delagrange, H; Denisov, A; Deshpande, A; Desmond, E J; Dietzsch, O; Dinesh, B V; Drees, A; Durum, A; Dutta, D; Ebisu, K; Efremenko, Y V; El Chenawi, K; En'yo, H; Esumi, S; Ewell, L; Ferdousi, T; Fields, D E; Fokin, S L; Fraenkel, Z; Franz, A; Frawley, A D; Fung, S-Y; Garpman, S; Ghosh, T K; Glenn, A; Godoi, A L; Goto, Y; Greene, S V; Grosse Perdekamp, M; Gupta, S K; Guryn, W; Gustafsson, H-A; Haggerty, J S; Hamagaki, H; Hansen, A G; Hara, H; Hartouni, E P; Hayano, R; Hayashi, N; He, X; Hemmick, T K; Heuser, J M; Hibino, M; Hill, J C; Ho, D S; Homma, K; Hong, B; Hoover, A; Ichihara, T; Imai, K; Ippolitov, M S; Ishihara, M; Jacak, B V; Jang, W Y; Jia, J; Johnson, B M; Johnson, S C; Joo, K S; Kametani, S; Kang, J H; Kann, M; Kapoor, S S; Kelly, S; Khachaturov, B; Khanzadeev, A; Kikuchi, J; Kim, D J; Kim, H J; Kim, S Y; Kim, Y G; Kinnison, W W; Kistenev, E; Kiyomichi, A; Klein-Boesing, C; Klinksiek, S; Kochenda, L; Kochetkov, V; Koehler, D; Kohama, T; Kotchetkov, D; Kozlov, A; Kroon, P J; Kurita, K; Kweon, M J; Kwon, Y; Kyle, G S; Lacey, R; Lajoie, J G; Lauret, J; Lebedev, A; Lee, D M; Leitch, M J; Li, X H; Li, Z; Lim, D J; Liu, M X; Liu, X; Liu, Z; Maguire, C F; Mahon, J; Makdisi, Y I; Manko, V I; Mao, Y; Mark, S K; Markacs, S; Martinez, G; Marx, M D; Masaike, A; Matathias, F; Matsumoto, T; McGaughey, P L; Melnikov, E; Merschmeyer, M; Messer, F; Messer, M; Miake, Y; Miller, T E; Milov, A; Mioduszewski, S; Mischke, R E; Mishra, G C; Mitchell, J T; Mohanty, A K; Morrison, D P; Moss, J M; Mühlbacher, F; Muniruzzaman, M; Murata, J; Nagamiya, S; Nagasaka, Y; Nagle, J L; Nakada, Y; Nandi, B K; Newby, J; Nikkinen, L; Nilsson, P; Nishimura, S; Nyanin, A S; Nystrand, J; O'Brien, E; Ogilvie, C A; Ohnishi, H; Ojha, I D; Ono, M; Onuchin, V; Oskarsson, A; Osterman, L; Otterlund, I; Oyama, K; Paffrath, L; Palounek, A P T; Pantuev, V S; Papavassiliou, V; Pate, S F; Peitzmann, T; Petridis, A N; Pinkenburg, C; Pisani, R P; Pitukhin, P; Plasil, F; Pollack, M; Pope, K; Purschke, M L; Ravinovich, I; Read, K F; Reygers, K; Riabov, V; Riabov, Y; Rosati, M; Rose, A A; Ryu, S S; Saito, N; Sakaguchi, A; Sakaguchi, T; Sako, H; Sakuma, T; Samsonov, V; Sangster, T C; Santo, R; Sato, H D; Sato, S; Sawada, S; Schlei, B R; Schutz, Y; Semenov, V; Seto, R; Shea, T K; Shein, I; Shibata, T-A; Shigaki, K; Shiina, T; Shin, Y H; Sibiriak, I G; Silvermyr, D; Sim, K S; Simon-Gillo, J; Singh, C P; Singh, V; Sivertz, M; Soldatov, A; Soltz, R A; Sorensen, S; Stankus, P W; Starinsky, N; Steinberg, P; Stenlund, E; Ster, A; Stoll, S P; Sugioka, M; Sugitate, T; Sullivan, J P; Sumi, Y; Sun, Z; Suzuki, M; Takagui, E M; Taketani, A; Tamai, M; Tanaka, K H; Tanaka, Y; Taniguchi, E; Tannenbaum, M J; Thomas, J; Thomas, J H; Thomas, T L; Tian, W; Tojo, J; Torii, H; Towell, R S; Tserruya, I; Tsuruoka, H; Tsvetkov, A A; Tuli, S K; Tydesjö, H; Tyurin, N; Ushiroda, T; van Hecke, H W; Velissaris, C; Velkovska, J; Velkovsky, M; Vinogradov, A A; Volkov, M A; Vorobyov, A; Vznuzdaev, E; Wang, H; Watanabe, Y; White, S N; Witzig, C; Wohn, F K; Woody, C L; Xie, W; Yagi, K; Yokkaichi, S; Young, G R; Yushmanov, I E; Zajc, W A; Zhang, Z; Zhou, S

2002-01-14

Transverse momentum spectra for charged hadrons and for neutral pions in the range 1 GeV/c

Direct measurement of the W Boson width in ppover collisions at square roots = 1.96 TeV.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; González, B Alvarez; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Almenar, C Cuenca; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; De Lorenzo, G; Dell'orso, M; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Giovanni, G P Di; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Forrester, S; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Gerberich, H; Gerdes, D; Giagu, S; Giakoumopolou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; da Costa, J Guimaraes; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Hamilton, A; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; Iyutin, B; James, E; Jayatilaka, B; Jeans, D; Jeon, E J; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M; Fernandez, P Movilla; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Griso, S Pagan; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Salamanna, G; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyria, A; Shalhout, S Z; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; Spreitzer, T; Squillacioti, P; Stanitzki, M; Denis, R St; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sun, H; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S

2008-02-22

A direct measurement of the total decay width of the W boson Gamma(W) is presented using 350 pb(-1) of data from pp[over ] collisions at square root s = 1.96 TeV collected with the CDF II detector at the Fermilab Tevatron. The width is determined by normalizing predicted signal and background distributions to 230 185 W candidates decaying to enu and micronu in the transverse-mass region 50

Occupation probabilities and fluctuations in the asymmetric simple inclusion process

NASA Astrophysics Data System (ADS)

Reuveni, Shlomi; Hirschberg, Ori; Eliazar, Iddo; Yechiali, Uri

2014-04-01

The asymmetric simple inclusion process (ASIP), a lattice-gas model of unidirectional transport and aggregation, was recently proposed as an "inclusion" counterpart of the asymmetric simple exclusion process. In this paper we present an exact closed-form expression for the probability that a given number of particles occupies a given set of consecutive lattice sites. Our results are expressed in terms of the entries of Catalan's trapezoids—number arrays which generalize Catalan's numbers and Catalan's triangle. We further prove that the ASIP is asymptotically governed by the following: (i) an inverse square-root law of occupation, (ii) a square-root law of fluctuation, and (iii) a Rayleigh law for the distribution of interexit times. The universality of these results is discussed.

Search for pair production of scalar bottom quarks in pp collisions at square root of s = 1.96 TeV.

PubMed

Abazov, V M; Abbott, B; Abolins, M; Acharya, B S; Adams, M; Adams, T; Agelou, M; Ahn, S H; Ahsan, M; Alexeev, G D; Alkhazov, G; Alton, A; Alverson, G; Alves, G A; Anastasoaie, M; Andeen, T; Anderson, S; Andrieu, B; Anzelc, M S; Arnoud, Y; Arov, M; Askew, A; Asman, B; Jesus, A C S Assis; Atramentov, O; Autermann, C; Avila, C; Ay, C; Badaud, F; Baden, A; Bagby, L; Baldin, B; Bandurin, D V; Banerjee, P; Banerjee, S; Barberis, E; Bargassa, P; Baringer, P; Barnes, C; Barreto, J; Bartlett, J F; Bassler, U; Bauer, D; Bean, A; Begalli, M; Begel, M; Belanger-Champagne, C; Bellantoni, L; Bellavance, A; Benitez, J A; Beri, S B; Bernardi, G; Bernhard, R; Berntzon, L; Bertram, I; Besançon, M; Beuselinck, R; Bezzubov, V A; Bhat, P C; Bhatnagar, V; Binder, M; Biscarat, C; Black, K M; Blackler, I; Blazey, G; Blekman, F; Blessing, S; Bloch, D; Bloom, K; Blumenschein, U; Boehnlein, A; Boeriu, O; Bolton, T A; Borissov, G; Bos, K; Bose, T; Brandt, A; Brock, R; Brooijmans, G; Bross, A; Brown, D; Buchanan, N J; Buchholz, D; Buehler, M; Buescher, V; Burdin, S; Burke, S; Burnett, T H; Busato, E; Buszello, C P; Butler, J M; Calfayan, P; Calvet, S; Cammin, J; Caron, S; Carvalho, W; Casey, B C K; Cason, N M; Castilla-Valdez, H; Chakraborty, D; Chan, K M; Chandra, A; Charles, F; Cheu, E; Chevallier, F; Cho, D K; Choi, S; Choudhary, B; Christofek, L; Claes, D; Clément, B; Clément, C; Coadou, Y; Cooke, M; Cooper, W E; Coppage, D; Corcoran, M; Cousinou, M-C; Cox, B; Crépé-Renaudin, S; Cutts, D; Cwiok, M; da Motta, H; Das, A; Das, M; Davies, B; Davies, G; Davis, G A; De, K; de Jong, P; de Jong, S J; De La Cruz-Burelo, E; De Oliveira Martins, C; Degenhardt, J D; Déliot, F; Demarteau, M; Demina, R; Demine, P; Denisov, D; Denisov, S P; Desai, S; Diehl, H T; Diesburg, M; Doidge, M; Dominguez, A; Dong, H; Dudko, L V; Duflot, L; Dugad, S R; Duggan, D; Duperrin, A; Dyer, J; Dyshkant, A; Eads, M; Edmunds, D; Edwards, T; Ellison, J; Elmsheuser, J; Elvira, V D; Eno, S; Ermolov, P; Evans, H; Evdokimov, A; Evdokimov, V N; Fatakia, S N; Feligioni, L; Ferapontov, A V; Ferbel, T; Fiedler, F; Filthaut, F; Fisher, W; Fisk, H E; Fleck, I; Ford, M; Fortner, M; Fox, H; Fu, S; Fuess, S; Gadfort, T; Galea, C F; Gallas, E; Galyaev, E; Garcia, C; Garcia-Bellido, A; Gardner, J; Gavrilov, V; Gay, A; Gay, P; Gelé, D; Gelhaus, R; Gerber, C E; Gershtein, Y; Gillberg, D; Ginther, G; Gollub, N; Gómez, B; Goussiou, A; Grannis, P D; Greenlee, H; Greenwood, Z D; Gregores, E M; Grenier, G; Gris, Ph; Grivaz, J-F; Grünendahl, S; Grünewald, M W; Guo, F; Guo, J; Gutierrez, G; Gutierrez, P; Haas, A; Hadley, N J; Haefner, P; Hagopian, S; Haley, J; Hall, I; Hall, R E; Han, L; Hanagaki, K; Harder, K; Harel, A; Harrington, R; Hauptman, J M; Hauser, R; Hays, J; Hebbeker, T; Hedin, D; Hegeman, J G; Heinmiller, J M; Heinson, A P; Heintz, U; Hensel, C; Herner, K; Hesketh, G; Hildreth, M D; Hirosky, R; Hobbs, J D; Hoeneisen, B; Hoeth, H; Hohlfeld, M; Hong, S J; Hooper, R; Houben, P; Hu, Y; Hubacek, Z; Hynek, V; Iashvili, I; Illingworth, R; Ito, A S; Jabeen, S; Jaffré, M; Jain, S; Jakobs, K; Jarvis, C; Jenkins, A; Jesik, R; Johns, K; Johnson, C; Johnson, M; Jonckheere, A; Jonsson, P; Juste, A; Käfer, D; Kahn, S; Kajfasz, E; Kalinin, A M; Kalk, J M; Kalk, J R; Kappler, S; Karmanov, D; Kasper, J; Kasper, P; Katsanos, I; Kau, D; Kaur, R; Kehoe, R; Kermiche, S; Khalatyan, N; Khanov, A; Kharchilava, A; Kharzheev, Y M; Khatidze, D; Kim, H; Kim, T J; Kirby, M H; Klima, B; Kohli, J M; Konrath, J-P; Kopal, M; Korablev, V M; Kotcher, J; Kothari, B; Koubarovsky, A; Kozelov, A V; Kozminski, J; Krop, D; Kryemadhi, A; Kuhl, T; Kumar, A; Kunori, S; Kupco, A; Kurca, T; Kvita, J; Lammers, S; Landsberg, G; Lazoflores, J; Le Bihan, A-C; Lebrun, P; Lee, W M; Leflat, A; Lehner, F; Lesne, V; Leveque, J; Lewis, P; Li, J; Li, Q Z; Lima, J G R; Lincoln, D; Linnemann, J; Lipaev, V V; Lipton, R; Liu, Z; Lobo, L; Lobodenko, A; Lokajicek, M; Lounis, A; Love, P; Lubatti, H J; Lynker, M; Lyon, A L; Maciel, A K A; Madaras, R J; Mättig, P; Magass, C; Magerkurth, A; Magnan, A-M; Makovec, N; Mal, P K; Malbouisson, H B; Malik, S; Malyshev, V L; Mao, H S; Maravin, Y; Martens, M; McCarthy, R; Meder, D; Melnitchouk, A; Mendes, A; Mendoza, L; Merkin, M; Merritt, K W; Meyer, A; Meyer, J; Michaut, M; Miettinen, H; Millet, T; Mitrevski, J; Molina, J; Mondal, N K; Monk, J; Moore, R W; Moulik, T; Muanza, G S; Mulders, M; Mulhearn, M; Mundim, L; Mutaf, Y D; Nagy, E; Naimuddin, M; Narain, M; Naumann, N A; Neal, H A; Negret, J P; Neustroev, P; Noeding, C; Nomerotski, A; Novaes, S F; Nunnemann, T; O'Dell, V; O'Neil, D C; Obrant, G; Oguri, V; Oliveira, N; Oshima, N; Otec, R; Y Garzón, G J Otero; Owen, M; Padley, P; Parashar, N; Park, S-J; Park, S K; Parsons, J; Partridge, R; Parua, N; Patwa, A; Pawloski, G; Perea, P M; Perez, E; Peters, K; Pétroff, P; Petteni, M; Piegaia, R; Piper, J; Pleier, M-A; Podesta-Lerma, P L M; Podstavkov, V M; Pogorelov, Y; Pol, M-E; Pompos, A; Pope, B G; Popov, A V; Potter, C; Prado da Silva, W L; Prosper, H B; Protopopescu, S; Qian, J; Quadt, A; Quinn, B; Rangel, M S; Rani, K J; Ranjan, K; Ratoff, P N; Renkel, P; Reucroft, S; Rijssenbeek, M; Ripp-Baudot, I; Rizatdinova, F; Robinson, S; Rodrigues, R F; Royon, C; Rubinov, P; Ruchti, R; Rud, V I; Sajot, G; Sánchez-Hernández, A; Sanders, M P; Santoro, A; Savage, G; Sawyer, L; Scanlon, T; Schaile, D; Schamberger, R D; Scheglov, Y; Schellman, H; Schieferdecker, P; Schmitt, C; Schwanenberger, C; Schwartzman, A; Schwienhorst, R; Sekaric, J; Sengupta, S; Severini, H; Shabalina, E; Shamim, M; Shary, V; Shchukin, A A; Shephard, W D; Shivpuri, R K; Shpakov, D; Siccardi, V; Sidwell, R A; Simak, V; Sirotenko, V; Skubic, P; Slattery, P; Smith, R P; Snow, G R; Snow, J; Snyder, S; Söldner-Rembold, S; Song, X; Sonnenschein, L; Sopczak, A; Sosebee, M; Soustruznik, K; Souza, M; Spurlock, B; Stark, J; Steele, J; Stolin, V; Stone, A; Stoyanova, D A; Strandberg, J; Strandberg, S; Strang, M A; Strauss, M; Ströhmer, R; Strom, D; Strovink, M; Stutte, L; Sumowidagdo, S; Sznajder, A; Talby, M; Tamburello, P; Taylor, W; Telford, P; Temple, J; Tiller, B; Titov, M; Tokmenin, V V; Tomoto, M; Toole, T; Torchiani, I; Towers, S; Trefzger, T; Trincaz-Duvoid, S; Tsybychev, D; Tuchming, B; Tully, C; Turcot, A S; Tuts, P M; Unalan, R; Uvarov, L; Uvarov, S; Uzunyan, S; Vachon, B; van den Berg, P J; Van Kooten, R; van Leeuwen, W M; Varelas, N; Varnes, E W; Vartapetian, A; Vasilyev, I A; Vaupel, M; Verdier, P; Vertogradov, L S; Verzocchi, M; Villeneuve-Seguier, F; Vint, P; Vlimant, J-R; Von Toerne, E; Voutilainen, M; Vreeswijk, M; Wahl, H D; Wang, L; Wang, M H L S; Warchol, J; Watts, G; Wayne, M; Weber, M; Weerts, H; Wermes, N; Wetstein, M; White, A; Wicke, D; Wilson, G W; Wimpenny, S J; Wobisch, M; Womersley, J; Wood, D R; Wyatt, T R; Xie, Y; Xuan, N; Yacoob, S; Yamada, R; Yan, M; Yasuda, T; Yatsunenko, Y A; Yip, K; Yoo, H D; Youn, S W; Yu, C; Yu, J; Yurkewicz, A; Zatserklyaniy, A; Zeitnitz, C; Zhang, D; Zhao, T; Zhou, B; Zhu, J; Zielinski, M; Zieminska, D; Zieminski, A; Zutshi, V; Zverev, E G

2006-10-27

A search for direct production of scalar bottom quarks (b) is performed with 310 pb(-1) of data collected by the D0 experiment in pp collisions at square root s = 1.96 TeV at the Fermilab Tevatron Collider. The topology analyzed consists of two b jets and an imbalance in transverse momentum due to undetected neutralinos (chi(1)0), with chi(1)0 assumed to be the lightest supersymmetric particle. We find the data consistent with standard model expectations, and set a 95% C.L. exclusion domain in the (m(b), m(chi(1)0)) mass plane, improving significantly upon the results from run I of the Tevatron.

Thermodynamic stability of nanosized multicomponent bubbles/droplets: the square gradient theory and the capillary approach.

PubMed

Wilhelmsen, Øivind; Bedeaux, Dick; Kjelstrup, Signe; Reguera, David

2014-01-14

Formation of nanosized droplets/bubbles from a metastable bulk phase is connected to many unresolved scientific questions. We analyze the properties and stability of multicomponent droplets and bubbles in the canonical ensemble, and compare with single-component systems. The bubbles/droplets are described on the mesoscopic level by square gradient theory. Furthermore, we compare the results to a capillary model which gives a macroscopic description. Remarkably, the solutions of the square gradient model, representing bubbles and droplets, are accurately reproduced by the capillary model except in the vicinity of the spinodals. The solutions of the square gradient model form closed loops, which shows the inherent symmetry and connected nature of bubbles and droplets. A thermodynamic stability analysis is carried out, where the second variation of the square gradient description is compared to the eigenvalues of the Hessian matrix in the capillary description. The analysis shows that it is impossible to stabilize arbitrarily small bubbles or droplets in closed systems and gives insight into metastable regions close to the minimum bubble/droplet radii. Despite the large difference in complexity, the square gradient and the capillary model predict the same finite threshold sizes and very similar stability limits for bubbles and droplets, both for single-component and two-component systems.

Thermodynamic stability of nanosized multicomponent bubbles/droplets: The square gradient theory and the capillary approach

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

Wilhelmsen, Øivind, E-mail: oivind.wilhelmsen@ntnu.no; Bedeaux, Dick; Kjelstrup, Signe

Formation of nanosized droplets/bubbles from a metastable bulk phase is connected to many unresolved scientific questions. We analyze the properties and stability of multicomponent droplets and bubbles in the canonical ensemble, and compare with single-component systems. The bubbles/droplets are described on the mesoscopic level by square gradient theory. Furthermore, we compare the results to a capillary model which gives a macroscopic description. Remarkably, the solutions of the square gradient model, representing bubbles and droplets, are accurately reproduced by the capillary model except in the vicinity of the spinodals. The solutions of the square gradient model form closed loops, which showsmore » the inherent symmetry and connected nature of bubbles and droplets. A thermodynamic stability analysis is carried out, where the second variation of the square gradient description is compared to the eigenvalues of the Hessian matrix in the capillary description. The analysis shows that it is impossible to stabilize arbitrarily small bubbles or droplets in closed systems and gives insight into metastable regions close to the minimum bubble/droplet radii. Despite the large difference in complexity, the square gradient and the capillary model predict the same finite threshold sizes and very similar stability limits for bubbles and droplets, both for single-component and two-component systems.« less

Root water uptake and lateral interactions among root systems in a temperate forest

NASA Astrophysics Data System (ADS)

Agee, E.; He, L.; Bisht, G.; Gough, C. M.; Couvreur, V.; Matheny, A. M.; Bohrer, G.; Ivanov, V. Y.

2016-12-01

A growing body of research has highlighted the importance of root architecture and hydraulic properties to the maintenance of the transpiration stream under water limitation and drought. Detailed studies of single plant systems have shown the ability of root systems to adjust zones of uptake due to the redistribution of local water potential gradients, thereby delaying the onset of stress under drying conditions. An open question is how lateral interactions and competition among neighboring plants impact individual and community resilience to water stress. While computational complexity has previously hindered the implementation of microscopic root system structure and function in larger scale hydrological models, newer hybrid approaches allow for the resolution of these properties at the plot scale. Using a modified version of the PFLOTRAN model, which represents the 3-D physics of variably saturated soil, we model root water uptake in a one-hectare temperate forest plot under natural and synthetic forcings. Two characteristic hydraulic architectures, tap roots and laterally sprawling roots, are implemented in an ensemble of simulations. Variations of root architecture, their hydraulic properties, and degree of system interactions produce variable local response to water limitation and provide insights on individual and community response to changing meteorological conditions. Results demonstrate the ability of interacting systems to shift areas of active uptake based on local gradients, allowing individuals to meet water demands despite competition from their peers. These results further illustrate how inter- and intra-species variations in root properties may influence not only individual response to water stress, but also help quantify the margins of resilience for forest ecosystems under changing climate.

Maths Resource.

ERIC Educational Resources Information Center

Tapson, Frank

1985-01-01

Flow diagrams developing cube roots and formulas for the square, sphere, cube, circle and sector, oblong, and cylinder are presented. Some comments on their use, along with calculators, are included. (MNS)

Slow Crack Growth and Fracture Toughness of Sapphire for the International Space Station Fluids and Combustion Facility

NASA Technical Reports Server (NTRS)

Salem, Jonathan A.

2006-01-01

The fracture toughness, inert flexural strength, and slow crack growth parameters of the r- and a-planes of sapphire grown by the Heat Exchange Method were measured to qualify sapphire for structural use in the International Space Station. The fracture toughness in dry nitrogen, K(sub Ipb), was 2.31 +/- 0.12 MPa(square root of)m and 2.47 +/- 0.15 MPa(squre root of)m for the a- and r-planes, respectively. Fracture toughness measured in water via the operational procedure in ASTM C1421 was significantly lower, K(sub Ivb) = 1.95+/- 0.03 MPa(square root of)m, 1.94 +/- 0.07 and 1.77 +/- 0.13 MPa(square root of)m for the a- , m- and r-planes, respectively. The mean inert flexural strength in dry nitrogen was 1085 +/- 127 MPa for the r-plane and 1255 +/- 547 MPa for the a-plane. The power law slow crack growth exponent for testing in water was n = 21 +/- 4 for the r-plane and n (greater than or equal to) 31 for the a-plane. The power law slow crack growth coefficient was A = 2.81 x 10(exp -14) m/s x (MPa(squre root of)m)/n for the r-plane and A (approx. equals)2.06 x 10(exp -15) m/s x (MPa(square root of)m)/n for the a-plane. The r- and a-planes of sapphire are relatively susceptible to stress corrosion induced slow crack growth in water. However, failure occurs by competing modes of slow crack growth at long failure times and twinning for short failure time and inert environments. Slow crack growth testing needs to be performed at low failure stress levels and long failure times so that twinning does not affect the results. Some difficulty was encountered in measuring the slow crack growth parameters for the a-plane due to a short finish (i.e., insufficient material removal for elimination of the damage generated in the early grinding stages). A consistent preparation method that increases the Weibull modulus of sapphire test specimens and components is needed. This would impart higher component reliability, even if higher Weibull modulus is gained at the sacrifice of absolute strength of the component. The current specification frequently used for the preparation of sapphire test specimens and components (e.g., a "60/40" scratch-dig finish) is inadequate to avoid a short finish.

Multi-analyte quantification in bioprocesses by Fourier-transform-infrared spectroscopy by partial least squares regression and multivariate curve resolution.

PubMed

Koch, Cosima; Posch, Andreas E; Goicoechea, Héctor C; Herwig, Christoph; Lendl, Bernhard

2014-01-07

This paper presents the quantification of Penicillin V and phenoxyacetic acid, a precursor, inline during Pencillium chrysogenum fermentations by FTIR spectroscopy and partial least squares (PLS) regression and multivariate curve resolution - alternating least squares (MCR-ALS). First, the applicability of an attenuated total reflection FTIR fiber optic probe was assessed offline by measuring standards of the analytes of interest and investigating matrix effects of the fermentation broth. Then measurements were performed inline during four fed-batch fermentations with online HPLC for the determination of Penicillin V and phenoxyacetic acid as reference analysis. PLS and MCR-ALS models were built using these data and validated by comparison of single analyte spectra with the selectivity ratio of the PLS models and the extracted spectral traces of the MCR-ALS models, respectively. The achieved root mean square errors of cross-validation for the PLS regressions were 0.22 g L(-1) for Penicillin V and 0.32 g L(-1) for phenoxyacetic acid and the root mean square errors of prediction for MCR-ALS were 0.23 g L(-1) for Penicillin V and 0.15 g L(-1) for phenoxyacetic acid. A general work-flow for building and assessing chemometric regression models for the quantification of multiple analytes in bioprocesses by FTIR spectroscopy is given. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Verification of Ensemble Forecasts for the New York City Operations Support Tool

NASA Astrophysics Data System (ADS)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

National Dam Safety Program. West Millpond Dam (NY 01060), Mohawk River Basin, City of Gloversville, Fulton County, New York. Phase I Inspection Report,

DTIC Science & Technology

1981-09-02

numerous and constantly changing internal and external con- ditions, and is evolutionary in nature. It would be incorrect to assume that the present...to seepage and piping ( internal erosion) problems if a tree blows over and pulls out its roots or if a tree dies and its roots rot. The roots of...for the actual size of the drainage area (same for 10 square miles or less) were inputted to the program as percentages of the index PKF in

The Normals to a Parabola and the Real Roots of a Cubic

ERIC Educational Resources Information Center

Bains, Majinder S.; Thoo, J. B.

2007-01-01

The geometric problem of finding the number of normals to the parabola y = x[squared] through a given point is equivalent to the algebraic problem of finding the number of distinct real roots of a cubic equation. Apollonius solved the former problem, and Cardano gave a solution to the latter. The two problems are bridged by Neil's (semi-cubical)…

Can small hydrophobic gold nanoparticles inhibit β2-microglobulin fibrillation?

NASA Astrophysics Data System (ADS)

Brancolini, Giorgia; Toroz, Dimitrios; Corni, Stefano

2014-06-01

Inorganic nanoparticles stabilized by a shell of organic ligands can enhance or suppress the natural propensity of proteins to form fibrils. Functionalization facilitates targeted delivery of the nanoparticles to various cell types, bioimaging, drug delivery and other therapeutic and diagnostic applications. In this study, we provide a computational model of the effect of a prototypical thiol-protected gold nanoparticle, Au25L18- (L = S(CH2)2Ph) on the β2-microglobulin natural fibrillation propensity. To reveal the molecular basis of the protein-nanoparticle association process, we performed various simulations at multiple levels (Classical Molecular Dynamics and Brownian Dynamics) that cover multiple length- and timescales. The results provide a model of the ensemble of structures constituting the protein-gold nanoparticle complexes, and insights into the driving forces for the binding of β2-microglobulin to hydrophobic small size gold nanoparticles. We have found that the small nanoparticles can bind the protein to form persistent complexes. This binding of nanoparticles is able to block the active sites of domains from binding to another protein, thus leading to potential inhibition of the fibrillation activity. A comparison with the binding patches identified for the interaction of the protein with a known inhibitor of fibrillation, supports our conclusion.Inorganic nanoparticles stabilized by a shell of organic ligands can enhance or suppress the natural propensity of proteins to form fibrils. Functionalization facilitates targeted delivery of the nanoparticles to various cell types, bioimaging, drug delivery and other therapeutic and diagnostic applications. In this study, we provide a computational model of the effect of a prototypical thiol-protected gold nanoparticle, Au25L18- (L = S(CH2)2Ph) on the β2-microglobulin natural fibrillation propensity. To reveal the molecular basis of the protein-nanoparticle association process, we performed various simulations at multiple levels (Classical Molecular Dynamics and Brownian Dynamics) that cover multiple length- and timescales. The results provide a model of the ensemble of structures constituting the protein-gold nanoparticle complexes, and insights into the driving forces for the binding of β2-microglobulin to hydrophobic small size gold nanoparticles. We have found that the small nanoparticles can bind the protein to form persistent complexes. This binding of nanoparticles is able to block the active sites of domains from binding to another protein, thus leading to potential inhibition of the fibrillation activity. A comparison with the binding patches identified for the interaction of the protein with a known inhibitor of fibrillation, supports our conclusion. Electronic supplementary information (ESI) available: Details on the molecular dynamics simulation results. Table S1 reports results of the MD trajectories with a single NP at different initial velocities (d1, d2, d3, and d4) (three-dimensional structures and contact residues). Table S2 reports results of the MD trajectories with a couple of NPs at different initial velocities (initial orientations, three-dimensional structures, contact residues and root-mean-square deviations). Table S3 reports root-mean-square fluctuations and divergence of the protein structure with respect to the NMR model. Table S4 describes the average energy of the final complexes. See DOI: 10.1039/c4nr01514b

Nanosatellite constellation deployment using on-board magnetic torquer interaction with space plasma

NASA Astrophysics Data System (ADS)

Park, Ji Hyun; Matsuzawa, Shinji; Inamori, Takaya; Jeung, In-Seuck

2018-04-01

One of the advantages that drive nanosatellite development is the potential of multi-point observation through constellation operation. However, constellation deployment of nanosatellites has been a challenge, as thruster operations for orbit maneuver were limited due to mass, volume, and power. Recently, a de-orbiting mechanism using magnetic torquer interaction with space plasma has been introduced, so-called plasma drag. As no additional hardware nor propellant is required, plasma drag has the potential in being used as constellation deployment method. In this research, a novel constellation deployment method using plasma drag is proposed. Orbit decay rate of the satellites in a constellation is controlled using plasma drag in order to achieve a desired phase angle and phase angle rate. A simplified 1D problem is formulated for an elementary analysis of the constellation deployment time. Numerical simulations are further performed for analytical analysis assessment and sensitivity analysis. Analytical analysis and numerical simulation results both agree that the constellation deployment time is proportional to the inverse square root of magnetic moment, the square root of desired phase angle and the square root of satellite mass. CubeSats ranging from 1 to 3 U (1-3 kg nanosatellites) are examined in order to investigate the feasibility of plasma drag constellation on nanosatellite systems. The feasibility analysis results show that plasma drag constellation is feasible on CubeSats, which open up the possibility of CubeSat constellation missions.

Comparison of Logistic Regression and Artificial Neural Network in Low Back Pain Prediction: Second National Health Survey

PubMed Central

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

Background: The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Methods: Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. Results: The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Conclusions: Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant. PMID:23113198

Comparison of logistic regression and artificial neural network in low back pain prediction: second national health survey.

PubMed

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant.

[Establishment of the Mathematical Model for PMI Estimation Using FTIR Spectroscopy and Data Mining Method].

PubMed

Wang, L; Qin, X C; Lin, H C; Deng, K F; Luo, Y W; Sun, Q R; Du, Q X; Wang, Z Y; Tuo, Y; Sun, J H

2018-02-01

To analyse the relationship between Fourier transform infrared （FTIR） spectrum of rat's spleen tissue and postmortem interval （PMI） for PMI estimation using FTIR spectroscopy combined with data mining method. Rats were sacrificed by cervical dislocation, and the cadavers were placed at 20 ℃. The FTIR spectrum data of rats' spleen tissues were taken and measured at different time points. After pretreatment, the data was analysed by data mining method. The absorption peak intensity of rat's spleen tissue spectrum changed with the PMI, while the absorption peak position was unchanged. The results of principal component analysis （PCA） showed that the cumulative contribution rate of the first three principal components was 96%. There was an obvious clustering tendency for the spectrum sample at each time point. The methods of partial least squares discriminant analysis （PLS-DA） and support vector machine classification （SVMC） effectively divided the spectrum samples with different PMI into four categories （0-24 h, 48-72 h, 96-120 h and 144-168 h）. The determination coefficient （ R ²） of the PMI estimation model established by PLS regression analysis was 0.96, and the root mean square error of calibration （RMSEC） and root mean square error of cross validation （RMSECV） were 9.90 h and 11.39 h respectively. In prediction set, the R ² was 0.97, and the root mean square error of prediction （RMSEP） was 10.49 h. The FTIR spectrum of the rat's spleen tissue can be effectively analyzed qualitatively and quantitatively by the combination of FTIR spectroscopy and data mining method, and the classification and PLS regression models can be established for PMI estimation. Copyright© by the Editorial Department of Journal of Forensic Medicine.

Four new topological indices based on the molecular path code.

PubMed

Balaban, Alexandru T; Beteringhe, Adrian; Constantinescu, Titus; Filip, Petru A; Ivanciuc, Ovidiu

2007-01-01

The sequence of all paths pi of lengths i = 1 to the maximum possible length in a hydrogen-depleted molecular graph (which sequence is also called the molecular path code) contains significant information on the molecular topology, and as such it is a reasonable choice to be selected as the basis of topological indices (TIs). Four new (or five partly new) TIs with progressively improved performance (judged by correctly reflecting branching, centricity, and cyclicity of graphs, ordering of alkanes, and low degeneracy) have been explored. (i) By summing the squares of all numbers in the sequence one obtains Sigmaipi(2), and by dividing this sum by one plus the cyclomatic number, a Quadratic TI is obtained: Q = Sigmaipi(2)/(mu+1). (ii) On summing the Square roots of all numbers in the sequence one obtains Sigmaipi(1/2), and by dividing this sum by one plus the cyclomatic number, the TI denoted by S is obtained: S = Sigmaipi(1/2)/(mu+1). (iii) On dividing terms in this sum by the corresponding topological distances, one obtains the Distance-reduced index D = Sigmai{pi(1/2)/[i(mu+1)]}. Two similar formulas define the next two indices, the first one with no square roots: (iv) distance-Attenuated index: A = Sigmai{pi/[i(mu + 1)]}; and (v) the last TI with two square roots: Path-count index: P = Sigmai{pi(1/2)/[i(1/2)(mu + 1)]}. These five TIs are compared for their degeneracy, ordering of alkanes, and performance in QSPR (for all alkanes with 3-12 carbon atoms and for all possible chemical cyclic or acyclic graphs with 4-6 carbon atoms) in correlations with six physical properties and one chemical property.

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2013-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography. These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC. Distribution Statement A: Approved for Public Release; distribution is unlimited

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S. P.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2012-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography (METOC). These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC.

Barley root hair growth and morphology in soil, sand, and water solution media and relationship with nickel toxicity.

PubMed

Lin, Yanqing; Allen, Herbert E; Di Toro, Dominic M

2016-08-01

Barley, Hordeum vulgare (Doyce), was grown in the 3 media of soil, hydroponic sand solution (sand), and hydroponic water solution (water) culture at the same environmental conditions for 4 d. Barley roots were scanned, and root morphology was analyzed. Plants grown in the 3 media had different root morphology and nickel (Ni) toxicity response. Root elongations and total root lengths followed the sequence soil > sand > water. Plants grown in water culture were more sensitive to Ni toxicity and had greater root hair length than those from soil and sand cultures, which increased root surface area. The unit root surface area as root surface area per centimeter of length of root followed the sequence water > sand > soil and was found to be related with root elongation. Including the unit root surface area, the difference in root elongation and 50% effective concentration were diminished, and percentage of root elongations can be improved with a root mean square error approximately 10% for plants grown in different media. Because the unit root surface area of plants in sand culture is closer to that in soil culture, the sand culture method, not water culture, is recommended for toxicity parameter estimation. Environ Toxicol Chem 2016;35:2125-2133. © 2016 SETAC. © 2016 SETAC.

Evaluation of bond strength of various epoxy resin based sealers in oval shaped root canals.

PubMed

Cakici, Fatih; Cakici, Elif Bahar; Ceyhanli, Kadir Tolga; Celik, Ersan; Kucukekenci, Funda Fundaoglu; Gunseren, Arif Onur

2016-09-30

The aim of this study was to evaluate the bond strength of AH plus, Acroseal, and Adseal to the root canal dentin. A total of 36 single-rooted, mandibular premolar teeth were used. Root canal shaping procedures were performed with ProTaper rotary instruments (Dentsply Maillefer) up to size F4. The prepared samples were then randomly assembled into 3 groups (n = 12). For each group, an ultrasonic tip (size 15, 0.02 taper) which was also coated with an epoxy resin based sealer and placed 2 mm shorter than the working length. The sealer was then activated for 10 s. A push-out test was used to measure the bond strength between the root canal dentine and the sealer. Kruskal-Wallis test to evaluate the push-out bond strength of epoxy based sealer (P = 0.05). The failure mode data were statistically analyzed using Pearson's chi square test (P = 0.05). Kruskal-Wallis test indicated that there were no statistically significant difference among the push out bond strength values of 3 mm (p = 0.123) and 6 mm (P = 0.057) for groups, there was statistically significant difference push out bond strength value of 9 mm (P = 0.032). Pearson's chi square test showed statistically significant differences for the failure types among the groups. Various epoxy resin based sealers activated ultrasonically showed similar bond strength in oval shaped root canals. Apical sections for all groups have higher push out bond strength values than middle and coronal sections.

Forward neutral pion production in p + p and d + Au collisions at square root sNN=200 GeV.

PubMed

Adams, J; Aggarwal, M M; Ahammed, Z; Amonett, J; Anderson, B D; Arkhipkin, D; Averichev, G S; Badyal, S K; Bai, Y; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Bekele, S; Belaga, V V; Bellingeri-Laurikainen, A; Bellwied, R; Berger, J; Bezverkhny, B I; Bharadwaj, S; Bhasin, A; Bhati, A K; Bhatia, V S; Bichsel, H; Bielcik, J; Bielcikova, J; Billmeier, A; Bland, L C; Blyth, C O; Blyth, S-L; Bonner, B E; Botje, M; Boucham, A; Bouchet, J; Brandin, A V; Bravar, A; Bystersky, M; Cadman, R V; Cai, X Z; Caines, H; Sánchez, M Calderón de la Barca; Catu, O; Cebra, D; Chajecki, Z; Chaloupka, P; Chattopadhyay, S; Chen, H F; Chen, J H; Chen, Y; Cheng, J; Cherney, M; Chikanian, A; Choi, H A; Christie, W; Coffin, J P; Cormier, T M; Cosentino, M R; Cramer, J G; Crawford, H J; Das, D; Das, S; Daugherity, M; de Moura, M M; Dedovich, T G; Dephillips, M; Derevschikov, A A; Didenko, L; Dietel, T; Dogra, S M; Dong, W J; Dong, X; Draper, J E; Du, F; Dubey, A K; Dunin, V B; Dunlop, J C; Mazumdar, M R Dutta; Eckardt, V; Edwards, W R; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Estienne, M; Fachini, P; Faivre, J; Fatemi, R; Fedorisin, J; Filimonov, K; Filip, P; Finch, E; Fine, V; Fisyak, Y; Fornazier, K S F; Fox, B D; Fu, J; Gagliardi, C A; Gaillard, L; Gans, J; Ganti, M S; Geurts, F; Ghazikhanian, V; Ghosh, P; Gonzalez, J E; Gorbunov, Y G; Gos, H; Grachov, O; Grebenyuk, O; Grosnick, D; Guertin, S M; Guo, Y; Gupta, A; Gupta, N; Gutierrez, T D; Hallman, T J; Hamed, A; Harris, J W; Heinz, M; Henry, T W; Hepplemann, S; Hippolyte, B; Hirsch, A; Hjort, E; Hoffmann, G W; Horner, M J; Huang, H Z; Huang, S L; Hughes, E W; Humanic, T J; Igo, G; Ishihara, A; Jacobs, P; Jacobs, W W; Jiang, H; Jones, P G; Judd, E G; Kabana, S; Kang, K; Kaplan, M; Keane, D; Kechechyan, A; Khodyrev, V Yu; Kim, B C; Kiryluk, J; Kisiel, A; Kislov, E M; Klein, S R; Koetke, D D; Kollegger, T; Kopytine, M; Kotchenda, L; Kowalik, K L; Kramer, M; Kravtsov, P; Kravtsov, V I; Krueger, K; Kuhn, C; Kulikov, A I; Kumar, A; Kutuev, R Kh; Kuznetsov, A A; Lamb, R; Lamont, M A C; Landgraf, J M; Lange, S; Laue, F; Lauret, J; Lebedev, A; Lednicky, R; Lee, C-H; Lehocka, S; Levine, M J; Li, C; Li, Q; Li, Y; Lin, G; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, H; Liu, J; Liu, L; Liu, Q J; Liu, Z; Ljubicic, T; Llope, W J; Long, H; Longacre, R S; Lopez-Noriega, M; Love, W A; Lu, Y; Ludlam, T; Lynn, D; Ma, G L; Ma, J G; Ma, Y G; Magestro, D; Mahajan, S; Mahapatra, D P; Majka, R; Mangotra, L K; Manweiler, R; Margetis, S; Markert, C; Martin, L; Marx, J N; Matis, H S; Matulenko, Yu A; McClain, C J; McShane, T S; Melnick, Yu; Meschanin, A; Miller, M L; Minaev, N G; Mironov, C; Mischke, A; Mishra, D K; Mitchell, J; Mioduszewski, S; Mohanty, B; Molnar, L; Moore, C F; Morozov, D A; Munhoz, M G; Nandi, B K; Nayak, S K; Nayak, T K; Nelson, J M; Netrakanti, P K; Nikitin, V A; Nogach, L V; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Pal, S K; Panebratsev, Y; Panitkin, S Y; Pavlinov, A I; Pawlak, T; Peitzmann, T; Perevoztchikov, V; Perkins, C; Peryt, W; Petrov, V A; Phatak, S C; Picha, R; Planinic, M; Pluta, J; Porile, N; Porter, J; Poskanzer, A M; Potekhin, M; Potrebenikova, E; Potukuchi, B V K S; Prindle, D; Pruneau, C; Putschke, J; Rakness, G; Raniwala, R; Raniwala, S; Ravel, O; Ray, R L; Razin, S V; Reichhold, D; Reid, J G; Reinnarth, J; Renault, G; Retiere, F; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevskiy, O V; Romero, J L; Rose, A; Roy, C; Ruan, L; Russcher, M J; Sahoo, R; Sakrejda, I; Salur, S; Sandweiss, J; Sarsour, M; Savin, I; Sazhin, P S; Schambach, J; Scharenberg, R P; Schmitz, N; Schweda, K; Seger, J; Selyuzhenkov, I; Seyboth, P; Shabetai, A; Shahaliev, E; Shao, M; Shao, W; Sharma, M; Shen, W Q; Shestermanov, K E; Shimanskiy, S S; Sichtermann, E; Simon, F; Singaraju, R N; Smirnov, N; Snellings, R; Sood, G; Sorensen, P; Sowinski, J; Speltz, J; Spinka, H M; Srivastava, B; Stadnik, A; Stanislaus, T D S; Stock, R; Stolpovsky, A; Strikhanov, M; Stringfellow, B; Suaide, A A P; Sugarbaker, E; Sumbera, M; Surrow, B; Swanger, M; Symons, T J M; de Toledo, A Szanto; Tai, A; Takahashi, J; Tang, A H; Tarnowsky, T; Thein, D; Thomas, J H; Timmins, A R; Timoshenko, S; Tokarev, M; Trainor, T A; Trentalange, S; Tribble, R E; Tsai, O D; Ulery, J; Ullrich, T; Underwood, D G; Buren, G Van; van der Kolk, N; van Leeuwen, M; Molen, A M Vander; Varma, R; Vasilevski, I M; Vasiliev, A N; Vernet, R; Vigdor, S E; Viyogi, Y P; Vokal, S; Voloshin, S A; Waggoner, W T; Wang, F; Wang, G; Wang, G; Wang, X L; Wang, Y; Wang, Y; Wang, Z M; Ward, H; Watson, J W; Webb, J C; Westfall, G D; Wetzler, A; Whitten, C; Wieman, H; Wissink, S W; Witt, R; Wood, J; Wu, J; Xu, N; Xu, Q H; Xu, Z; Xu, Z Z; Yepes, P; Yoo, I-K; Yurevich, V I; Zborovsky, I; Zhang, H; Zhang, W M; Zhang, Y; Zhang, Z P; Zhong, C; Zoulkarneev, R; Zoulkarneeva, Y; Zubarev, A N; Zuo, J X

2006-10-13

Measurements of the production of forward pi0 mesons from p + p and d + Au collisions at square root sNN=200 GeV are reported. The p + p yield generally agrees with next-to-leading order perturbative QCD calculations. The d + Au yield per binary collision is suppressed as eta increases, decreasing to approximately 30% of the p + p yield at eta =4.00, well below shadowing expectations. Exploratory measurements of azimuthal correlations of the forward pi0 with charged hadrons at eta approximately 0 show a recoil peak in p + p that is suppressed in d + Au at low pion energy. These observations are qualitatively consistent with a saturation picture of the low-x gluon structure of heavy nuclei.

Particle-type dependence of azimuthal anisotropy and nuclear modification of particle production in Au+Au collisions at square root of sNN=200 GeV.

PubMed

Adams, J; Adler, C; Aggarwal, M M; Ahammed, Z; Amonett, J; Anderson, B D; Anderson, M; Arkhipkin, D; Averichev, G S; Badyal, S K; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Bekele, S; Belaga, V V; Bellwied, R; Berger, J; Bezverkhny, B I; Bhardwaj, S; Bhaskar, P; Bhati, A K; Bichsel, H; Billmeier, A; Bland, L C; Blyth, C O; Bonner, B E; Botje, M; Boucham, A; Brandin, A; Bravar, A; Cadman, R V; Cai, X Z; Caines, H; Calderón de la Barca Sánchez, M; Carroll, J; Castillo, J; Castro, M; Cebra, D; Chaloupka, P; Chattopadhyay, S; Chen, H F; Chen, Y; Chernenko, S P; Cherney, M; Chikanian, A; Choi, B; Christie, W; Coffin, J P; Cormier, T M; Cramer, J G; Crawford, H J; Das, D; Das, S; Derevschikov, A A; Didenko, L; Dietel, T; Dong, W J; Dong, X; Draper, J E; Du, F; Dubey, A K; Dunin, V B; Dunlop, J C; Dutta Majumdar, M R; Eckardt, V; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Estienne, M; Fachini, P; Faine, V; Faivre, J; Fatemi, R; Filimonov, K; Filip, P; Finch, E; Fisyak, Y; Flierl, D; Foley, K J; Fu, J; Gagliardi, C A; Gagunashvili, N; Gans, J; Ganti, M S; Gaudichet, L; Germain, M; Geurts, F; Ghazikhanian, V; Ghosh, P; Gonzalez, J E; Grachov, O; Grigoriev, V; Gronstal, S; Grosnick, D; Guedon, M; Guertin, S M; Gupta, A; Gushin, E; Gutierrez, T D; Hallman, T J; Hardtke, D; Harris, J W; Heinz, M; Henry, T W; Heppelmann, S; Herston, T; Hippolyte, B; Hirsch, A; Hjort, E; Hoffmann, G W; Horsley, M; Huang, H Z; Huang, S L; Humanic, T J; Igo, G; Ishihara, A; Jacobs, P; Jacobs, W W; Janik, M; Jiang, H; Johnson, I; Jones, P G; Judd, E G; Kabana, S; Kaneta, M; Kaplan, M; Keane, D; Khodyrev, V Yu; Kiryluk, J; Kisiel, A; Klay, J; Klein, S R; Klyachko, A; Koetke, D D; Kollegger, T; Kopytine, M; Kotchenda, L; Kovalenko, A D; Kramer, M; Kravtsov, P; Kravtsov, V I; Krueger, K; Kuhn, C; Kulikov, A I; Kumar, A; Kunde, G J; Kunz, C L; Kutuev, R Kh; Kuznetsov, A A; Lamont, M A C; Landgraf, J M; Lange, S; Lansdell, C P; Lasiuk, B; Laue, F; Lauret, J; Lebedev, A; Lednický, R; LeVine, M J; Li, C; Li, Q; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, L; Liu, Z; Liu, Q J; Ljubicic, T; Llope, W J; Long, H; Longacre, R S; Lopez-Noriega, M; Love, W A; Ludlam, T; Lynn, D; Ma, J; Ma, Y G; Magestro, D; Mahajan, S; Mangotra, L K; Mahapatra, D P; Majka, R; Manweiler, R; Margetis, S; Markert, C; Martin, L; Marx, J; Matis, H S; Matulenko, Yu A; McShane, T S; Meissner, F; Melnick, Yu; Meschanin, A; Messer, M; Miller, M L; Milosevich, Z; Minaev, N G; Mironov, C; Mishra, D; Mitchell, J; Mohanty, B; Molnar, L; Moore, C F; Mora-Corral, M J; Morozov, D A; Morozov, V; de Moura, M M; Munhoz, M G; Nandi, B K; Nayak, S K; Nayak, T K; Nelson, J M; Nevski, P; Nikitin, V A; Nogach, L V; Norman, B; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Paic, G; Pandey, S U; Pal, S K; Panebratsev, Y; Panitkin, S Y; Pavlinov, A I; Pawlak, T; Perevoztchikov, V; Perkins, C; Peryt, W; Petrov, V A; Phatak, S C; Picha, R; Planinic, M; Pluta, J; Porile, N; Porter, J; Poskanzer, A M; Potekhin, M; Potrebenikova, E; Potukuchi, B V K S; Prindle, D; Pruneau, C; Putschke, J; Rai, G; Rakness, G; Raniwala, R; Raniwala, S; Ravel, O; Ray, R L; Razin, S V; Reichhold, D; Reid, J G; Renault, G; Retiere, F; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevski, O V; Romero, J L; Rose, A; Roy, C; Ruan, L J; Sahoo, R; Sakrejda, I; Salur, S; Sandweiss, J; Savin, I; Schambach, J; Scharenberg, R P; Schmitz, N; Schroeder, L S; Schweda, K; Seger, J; Seliverstov, D; Seyboth, P; Shahaliev, E; Shao, M; Sharma, M; Shestermanov, K E; Shimanskii, S S; Singaraju, R N; Simon, F; Skoro, G; Smirnov, N; Snellings, R; Sood, G; Sorensen, P; Sowinski, J; Spinka, H M; Srivastava, B; Stanislaus, S; Stock, R; Stolpovsky, A; Strikhanov, M; Stringfellow, B; Struck, C; Suaide, A A P; Sugarbaker, E; Suire, C; Sumbera, M; Surrow, B; Symons, T J M; de Toledo, A Szanto; Szarwas, P; Tai, A; Takahashi, J; Tang, A H; Thein, D; Thomas, J H; Tikhomirov, V; Tokarev, M; Tonjes, M B; Trainor, T A; Trentalange, S; Tribble, R E; Trivedi, M D; Trofimov, V; Tsai, O; Ullrich, T; Underwood, D G; Van Buren, G; VanderMolen, A M; Vasiliev, A N; Vasiliev, M; Vigdor, S E; Viyogi, Y P; Voloshin, S A; Waggoner, W; Wang, F; Wang, G; Wang, X L; Wang, Z M; Ward, H; Watson, J W; Wells, R; Westfall, G D; Whitten, C; Wieman, H; Willson, R; Wissink, S W; Witt, R; Wood, J; Wu, J; Xu, N; Xu, Z; Xu, Z Z; Yamamoto, E; Yepes, P; Yurevich, V I; Zanevski, Y V; Zborovský, I; Zhang, H; Zhang, W M; Zhang, Z P; Zołnierczuk, P A; Zoulkarneev, R; Zoulkarneeva, J; Zubarev, A N

2004-02-06

We present STAR measurements of the azimuthal anisotropy parameter v(2) and the binary-collision scaled centrality ratio R(CP) for kaons and lambdas (Lambda+Lambda) at midrapidity in Au+Au collisions at square root of s(NN)=200 GeV. In combination, the v(2) and R(CP) particle-type dependencies contradict expectations from partonic energy loss followed by standard fragmentation in vacuum. We establish p(T) approximately 5 GeV/c as the value where the centrality dependent baryon enhancement ends. The K(0)(S) and Lambda+Lambda v(2) values are consistent with expectations of constituent-quark-number scaling from models of hadron formation by parton coalescence or recombination.

Systemic inflammatory markers and sources of social support among older adults in the Memory Research Unit cohort.

PubMed

McHugh Power, Joanna; Carney, Sile; Hannigan, Caoimhe; Brennan, Sabina; Wolfe, Hannah; Lynch, Marina; Kee, Frank; Lawlor, Brian

2016-11-01

Potential associations between systemic inflammation and social support received by a sample of 120 older adults were examined here. Inflammatory markers, cognitive function, social support and psychosocial wellbeing were evaluated. A structural equation modelling approach was used to analyse the data. The model was a good fit [Formula: see text], p < 0.001; comparative fit index = 0.973; Tucker-Lewis Index = 0.962; root mean square error of approximation = 0.021; standardised root mean-square residual = 0.074). Chemokine levels were associated with increased age ( β = 0.276), receipt of less social support from friends ( β = -0.256) and body mass index ( β = -0.256). Results are discussed in relation to social signal transduction theory.

System size and energy dependence of jet-induced hadron pair correlation shapes in Cu+Cu and Au+Au collisions at square root sNN=200 and 62.4 GeV.

PubMed

Adare, A; Adler, S S; Afanasiev, S; Aidala, C; Ajitanand, N N; Akiba, Y; Al-Bataineh, H; Alexander, J; Al-Jamel, A; Aoki, K; Aphecetche, L; Armendariz, R; Aronson, S H; Asai, J; Atomssa, E T; Averbeck, R; Awes, T C; Azmoun, B; Babintsev, V; Baksay, G; Baksay, L; Baldisseri, A; Barish, K N; Barnes, P D; Bassalleck, B; Bathe, S; Batsouli, S; Baublis, V; Bauer, F; Bazilevsky, A; Belikov, S; Bennett, R; Berdnikov, Y; Bickley, A A; Bjorndal, M T; Boissevain, J G; Borel, H; Boyle, K; Brooks, M L; Brown, D S; Bruner, N; Bucher, D; Buesching, H; Bumazhnov, V; Bunce, G; Burward-Hoy, J M; Butsyk, S; Camard, X; Campbell, S; Chai, J-S; Chand, P; Chang, B S; Chang, W C; Charvet, J-L; Chernichenko, S; Chiba, J; Chi, C Y; Chiu, M; Choi, I J; Choudhury, R K; Chujo, T; Chung, P; Churyn, A; Cianciolo, V; Cleven, C R; Cobigo, Y; Cole, B A; Comets, M P; Constantin, P; Csanád, M; Csörgo, T; Cussonneau, J P; Dahms, T; Das, K; David, G; Deák, F; Deaton, M B; Dehmelt, K; Delagrange, H; Denisov, A; d'Enterria, D; Deshpande, A; Desmond, E J; Devismes, A; Dietzsch, O; Dion, A; Donadelli, M; Drachenberg, J L; Drapier, O; Drees, A; Dubey, A K; Durum, A; Dutta, D; Dzhordzhadze, V; Efremenko, Y V; Egdemir, J; Ellinghaus, F; Emam, W S; Enokizono, A; En'yo, H; Espagnon, B; Esumi, S; Eyser, K O; Fields, D E; Finck, C; Finger, M; Finger, M; Fleuret, F; Fokin, S L; Forestier, B; Fox, B D; Fraenkel, Z; Frantz, J E; Franz, A; Frawley, A D; Fujiwara, K; Fukao, Y; Fung, S-Y; Fusayasu, T; Gadrat, S; Garishvili, I; Gastineau, F; Germain, M; Glenn, A; Gong, H; Gonin, M; Gosset, J; Goto, Y; Granier de Cassagnac, R; Grau, N; Greene, S V; Grosse Perdekamp, M; Gunji, T; Gustafsson, H-A; Hachiya, T; Hadj Henni, A; Haegemann, C; Haggerty, J S; Hagiwara, M N; Hamagaki, H; Han, R; Hansen, A G; Harada, H; Hartouni, E P; Haruna, K; Harvey, M; Haslum, E; Hasuko, K; Hayano, R; Heffner, M; Hemmick, T K; Hester, T; Heuser, J M; He, X; Hidas, P; Hiejima, H; Hill, J C; Hobbs, R; Hohlmann, M; Holmes, M; Holzmann, W; Homma, K; Hong, B; Hoover, A; Horaguchi, T; Hornback, D; Hur, M G; Ichihara, T; Ikonnikov, V V; Imai, K; Inaba, M; Inoue, Y; Inuzuka, M; Isenhower, D; Isenhower, L; Ishihara, M; Isobe, T; Issah, M; Isupov, A; Jacak, B V; Jia, J; Jin, J; Jinnouchi, O; Johnson, B M; Johnson, S C; Joo, K S; Jouan, D; Kajihara, F; Kametani, S; Kamihara, N; Kamin, J; Kaneta, M; Kang, J H; Kanou, H; Katou, K; Kawabata, T; Kawagishi, T; Kawall, D; Kazantsev, A V; Kelly, S; Khachaturov, B; Khanzadeev, A; Kikuchi, J; Kim, D H; Kim, D J; Kim, E; Kim, G-B; Kim, H J; Kim, Y-S; Kinney, E; Kiss, A; Kistenev, E; Kiyomichi, A; Klay, J; Klein-Boesing, C; Kobayashi, H; Kochenda, L; Kochetkov, V; Kohara, R; Komkov, B; Konno, M; Kotchetkov, D; Kozlov, A; Král, A; Kravitz, A; Kroon, P J; Kubart, J; Kuberg, C H; Kunde, G J; Kurihara, N; Kurita, K; Kweon, M J; Kwon, Y; Kyle, G S; Lacey, R; Lai, Y-S; Lajoie, J G; Lebedev, A; Le Bornec, Y; Leckey, S; Lee, D M; Lee, M K; Lee, T; Leitch, M J; Leite, M A L; Lenzi, B; Lim, H; Liska, T; Litvinenko, A; Liu, M X; Li, X; Li, X H; Love, B; Lynch, D; Maguire, C F; Makdisi, Y I; Malakhov, A; Malik, M D; Manko, V I; Mao, Y; Martinez, G; Masek, L; Masui, H; Matathias, F; Matsumoto, T; McCain, M C; McCumber, M; McGaughey, P L; Miake, Y; Mikes, P; Miki, K; Miller, T E; Milov, A; Mioduszewski, S; Mishra, G C; Mishra, M; Mitchell, J T; Mitrovski, M; Mohanty, A K; Morreale, A; Morrison, D P; Moss, J M; Moukhanova, T V; Mukhopadhyay, D; Muniruzzaman, M; Murata, J; Nagamiya, S; Nagata, Y; Nagle, J L; Naglis, M; Nakagawa, I; Nakamiya, Y; Nakamura, T; Nakano, K; Newby, J; Nguyen, M; Norman, B E; Nyanin, A S; Nystrand, J; O'Brien, E; Oda, S X; Ogilvie, C A; Ohnishi, H; Ojha, I D; Okada, H; Okada, K; Oka, M; Omiwade, O O; Oskarsson, A; Otterlund, I; Ouchida, M; Oyama, K; Ozawa, K; Pak, R; Pal, D; Palounek, A P T; Pantuev, V; Papavassiliou, V; Park, J; Park, W J; Pate, S F; Pei, H; Penev, V; Peng, J-C; Pereira, H; Peresedov, V; Peressounko, D Yu; Pierson, A; Pinkenburg, C; Pisani, R P; Purschke, M L; Purwar, A K; Qualls, J M; Qu, H; Rak, J; Rakotozafindrabe, A; Ravinovich, I; Read, K F; Rembeczki, S; Reuter, M; Reygers, K; Riabov, V; Riabov, Y; Roche, G; Romana, A; Rosati, M; Rosendahl, S S E; Rosnet, P; Rukoyatkin, P; Rykov, V L; Ryu, S S; Sahlmueller, B; Saito, N; Sakaguchi, T; Sakai, S; Sakata, H; Samsonov, V; Sanfratello, L; Santo, R; Sato, H D; Sato, S; Sawada, S; Schutz, Y; Seele, J; Seidl, R; Semenov, V; Seto, R; Sharma, D; Shea, T K; Shein, I; Shevel, A; Shibata, T-A; Shigaki, K; Shimomura, M; Shohjoh, T; Shoji, K; Sickles, A; Silva, C L; Silvermyr, D; Silvestre, C; Sim, K S; Singh, C P; Singh, V; Skutnik, S; Slunecka, M; Smith, W C; Soldatov, A; Soltz, R A; Sondheim, W E; Sorensen, S P; Sourikova, I V; Staley, F; Stankus, P W; Stenlund, E; Stepanov, M; Ster, A; Stoll, S P; Sugitate, T; Suire, C; Sullivan, J P; Sziklai, J; Tabaru, T; Takagi, S; Takagui, E M; Taketani, A; Tanaka, K H; Tanaka, Y; Tanida, K; Tannenbaum, M J; Taranenko, A; Tarján, P; Thomas, T L; Togawa, M; Toia, A; Tojo, J; Tomásek, L; Torii, H; Towell, R S; Tram, V-N; Tserruya, I; Tsuchimoto, Y; Tuli, S K; Tydesjö, H; Tyurin, N; Uam, T J; Vale, C; Valle, H; vanHecke, H W; Velkovska, J; Velkovsky, M; Vertesi, R; Veszprémi, V; Vinogradov, A A; Virius, M; Volkov, M A; Vrba, V; Vznuzdaev, E; Wagner, M; Walker, D; Wang, X R; Watanabe, Y; Wessels, J; White, S N; Willis, N; Winter, D; Wohn, F K; Woody, C L; Wysocki, M; Xie, W; Yamaguchi, Y L; Yanovich, A; Yasin, Z; Ying, J; Yokkaichi, S; Young, G R; Younus, I; Yushmanov, I E; Zajc, W A; Zaudtke, O; Zhang, C; Zhou, S; Zimányi, J; Zolin, L; Zong, X

2007-06-08

We present azimuthal angle correlations of intermediate transverse momentum (1-4 GeV/c) hadrons from dijets in Cu+Cu and Au+Au collisions at square root sNN=62.4 and 200 GeV. The away-side dijet induced azimuthal correlation is broadened, non-Gaussian, and peaked away from Delta phi=pi in central and semicentral collisions in all the systems. The broadening and peak location are found to depend upon the number of participants in the collision, but not on the collision energy or beam nuclei. These results are consistent with sound or shock wave models, but pose challenges to Cherenkov gluon radiation models.

Stress corrosion cracking susceptibility of 18 Ni maraging steel

NASA Technical Reports Server (NTRS)

Humphries, T. S.; Nelson, E. E.

1974-01-01

The stress corrosion cracking (SCC) resistance of 18Ni maraging steel (grades 200, 250, 300, and 350) was determined in 3.5 percent salt (NaCl) solution, synthetic sea water, high humidity, and outside MSFC atmosphere. All grades of the maraging steel were found to be susceptible to SCC in varying degrees according to their strengths, with the lowest strength steel (grade 200) being the least susceptible and the highest strength steel (grade 350), the most susceptible to SCC. The SCC resistance of 250 grade maraging steel was also evaluated in salt and salt-chromate solutions using fracture mechanics techniques. The threshold value, K sub SCC, was found to be approximately 44 MN/sq m square root m, (40 ksi square root in.) or 40 percent of the K sub Q value.

Search for pair production of scalar top quarks in R-parity violating decay modes in pp collisions at square root of s=1.8 TeV.

PubMed

Acosta, D; Affolder, T; Akimoto, H; Albrow, M G; Ambrose, D; Amidei, D; Anikeev, K; Antos, J; Apollinari, G; Arisawa, T; Artikov, A; Asakawa, T; Ashmanskas, W; Azfar, F; Azzi-Bacchetta, P; Bacchetta, N; Bachacou, H; Badgett, W; Bailey, S; de Barbaro, P; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Barone, M; Bauer, G; Bedeschi, F; Behari, S; Belforte, S; Bell, W H; Bellettini, G; Bellinger, J; Benjamin, D; Bensinger, J; Beretvas, A; Berryhill, J; Bhatti, A; Binkley, M; Bisello, D; Bishai, M; Blair, R E; Blocker, C; Bloom, K; Blumenfeld, B; Blusk, S R; Bocci, A; Bodek, A; Bolla, G; Bolshov, A; Bonushkin, Y; Bortoletto, D; Boudreau, J; Brandl, A; Bromberg, C; Brozovic, M; Brubaker, E; Bruner, N; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Byrum, K L; Cabrera, S; Calafiura, P; Campbell, M; Carithers, W; Carlson, J; Carlsmith, D; Caskey, W; Castro, A; Cauz, D; Cerri, A; Cerrito, L; Chan, A W; Chang, P S; Chang, P T; Chapman, J; Chen, C; Chen, Y C; Cheng, M-T; Chertok, M; Chiarelli, G; Chirikov-Zorin, I; Chlachidze, G; Chlebana, F; Christofek, L; Chu, M L; Chung, J Y; Chung, W-H; Chung, Y S; Ciobanu, C I; Clark, A G; Coca, M; Colijn, A P; Connolly, A; Convery, M; Conway, J; Cordelli, M; Cranshaw, J; Culbertson, R; Dagenhart, D; D'Auria, S; De Cecco, S; DeJongh, F; Dell'Agnello, S; Dell'Orso, M; Demers, S; Demortier, L; Deninno, M; De Pedis, D; Derwent, P F; Devlin, T; Dionisi, C; Dittmann, J R; Dominguez, A; Donati, S; D'Onofrio, M; Dorigo, T; Eddy, N; Einsweiler, K; Engels, E; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fan, Q; Farrington, S; Feild, R G; Fernandez, J P; Ferretti, C; Field, R D; Fiori, I; Flaugher, B; Flores-Castillo, L R; Foster, G W; Franklin, M; Freeman, J; Friedman, J; Fukui, Y; Furic, I; Galeotti, S; Gallas, A; Gallinaro, M; Gao, T; Garcia-Sciveres, M; Garfinkel, A F; Gatti, P; Gay, C; Gerdes, D W; Gerstein, E; Giagu, S; Giannetti, P; Giolo, K; Giordani, M; Giromini, P; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Goldstein, J; Gomez, G; Goncharov, M; Gorelov, I; Goshaw, A T; Gotra, Y; Goulianos, K; Green, C; Gresele, A; Grim, G; Grosso-Pilcher, C; Guenther, M; Guillian, G; Guimaraes da Costa, J; Haas, R M; Haber, C; Hahn, S R; Halkiadakis, E; Hall, C; Handa, T; Handler, R; Happacher, F; Hara, K; Hardman, A D; Harris, R M; Hartmann, F; Hatakeyama, K; Hauser, J; Heinrich, J; Heiss, A; Hennecke, M; Herndon, M; Hill, C; Hocker, A; Hoffman, K D; Hollebeek, R; Holloway, L; Hou, S; Huffman, B T; Hughes, R; Huston, J; Huth, J; Ikeda, H; Issever, C; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; Iwai, J; Iwata, Y; Iyutin, B; James, E; Jones, M; Joshi, U; Kambara, H; Kamon, T; Kaneko, T; Kang, J; Karagoz Unel, M; Karr, K; Kartal, S; Kasha, H; Kato, Y; Keaffaber, T A; Kelley, K; Kelly, M; Kennedy, R D; Kephart, R; Khazins, D; Kikuchi, T; Kilminster, B; Kim, B J; Kim, D H; Kim, H S; Kim, M J; Kim, S B; Kim, S H; Kim, T H; Kim, Y K; Kirby, M; Kirk, M; Kirsch, L; Klimenko, S; Koehn, P; Kondo, K; Konigsberg, J; Korn, A; Korytov, A; Kotelnikov, K; Kovacs, E; Kroll, J; Kruse, M; Krutelyov, V; Kuhlmann, S E; Kurino, K; Kuwabara, T; Kuznetsova, N; Laasanen, A T; Lai, N; Lami, S; Lammel, S; Lancaster, J; Lannon, K; Lancaster, M; Lander, R; Lath, A; Latino, G; LeCompte, T; Le, Y; Lee, J; Lee, S W; Leonardo, N; Leone, S; Lewis, J D; Li, K; Lin, C S; Lindgren, M; Liss, T M; Liu, J B; Liu, T; Liu, Y C; Litvintsev, D O; Lobban, O; Lockyer, N S; Loginov, A; Loken, J; Loreti, M; Lucchesi, D; Lukens, P; Lusin, S; Lyons, L; Lys, J; Madrak, R; Maeshima, K; Maksimovic, P; Malferrari, L; Mangano, M; Manca, G; Mariotti, M; Martignon, G; Martin, M; Martin, A; Martin, V; Martínez, M; Matthews, J A J; Mazzanti, P; McFarland, K S; McIntyre, P; Menguzzato, M; Menzione, A; Merkel, P; Mesropian, C; Meyer, A; Miao, T; Miller, R; Miller, J S; Minato, H; Miscetti, S; Mishina, M; Mitselmakher, G; Miyazaki, Y; Moggi, N; Moore, E; Moore, R; Morita, Y; Moulik, T; Mulhearn, M; Mukherjee, A; Muller, T; Munar, A; Murat, P; Murgia, S; Nachtman, J; Nagaslaev, V; Nahn, S; Nakada, H; Nakano, I; Napora, R; Niell, F; Nelson, C; Nelson, T; Neu, C; Neubauer, M S; Neuberger, D; Newman-Holmes, C; Ngan, C-Y P; Nigmanov, T; Niu, H; Nodulman, L; Nomerotski, A; Oh, S H; Oh, Y D; Ohmoto, T; Ohsugi, T; Oishi, R; Okusawa, T; Olsen, J; Orejudos, W; Pagliarone, C; Palmonari, F; Paoletti, R; Papadimitriou, V; Partos, D; Patrick, J; Pauletta, G; Paulini, M; Pauly, T; Paus, C; Pellett, D; Penzo, A; Pescara, L; Phillips, T J; Piacentino, G; Piedra, J; Pitts, K T; Pompos, A; Pondrom, L; Pope, G; Pratt, T; Prokoshin, F; Proudfoot, J; Ptohos, F; Pukhov, O; Punzi, G; Rademacker, J; Rakitine, A; Ratnikov, F; Ray, H; Reher, D; Reichold, A; Renton, P; Rescigno, M; Ribon, A; Riegler, W; Rimondi, F; Ristori, L; Riveline, M; Robertson, W J; Rodrigo, T; Rolli, S; Rosenson, L; Roser, R; Rossin, R; Rott, C; Roy, A; Ruiz, A; Ryan, D; Safonov, A; St Denis, R; Sakumoto, W K; Saltzberg, D; Sanchez, C; Sansoni, A; Santi, L; Sarkar, S; Sato, H; Savard, P; Savoy-Navarro, A; Schlabach, P; Schmidt, E E; Schmidt, M P; Schmitt, M; Scodellaro, L; Scott, A; Scribano, A; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Semeria, F; Shah, T; Shapiro, M D; Shepard, P F; Shibayama, T; Shimojima, M; Shochet, M; Sidoti, A; Siegrist, J; Sill, A; Sinervo, P; Singh, P; Slaughter, A J; Sliwa, K; Snider, F D; Snihur, R; Solodsky, A; Spalding, J; Speer, T; Spezziga, M; Sphicas, P; Spinella, F; Spiropulu, M; Spiegel, L; Steele, J; Stefanini, A; Strologas, J; Strumia, F; Stuart, D; Sukhanov, A; Sumorok, K; Suzuki, T; Takano, T; Takashima, R; Takikawa, K; Tamburello, P; Tanaka, M; Tannenbaum, B; Tecchio, M; Tesarek, R J; Teng, P K; Terashi, K; Tether, S; Thom, J; Thompson, A S; Thomson, E; Thurman-Keup, R; Tipton, P; Tkaczyk, S; Toback, D; Tollefson, K; Tonelli, D; Tonnesmann, M; Toyoda, H; Trischuk, W; De Troconiz, J F; Tseng, J; Tsybychev, D; Turini, N; Ukegawa, F; Unverhau, T; Vaiciulis, T; Valls, J; Varganov, A; Vataga, E; Vejcik, S; Velev, G; Veramendi, G; Vidal, R; Vila, I; Vilar, R; Volobouev, I; von der Mey, M; Vucinic, D; Wagner, R G; Wagner, R L; Wagner, W; Wallace, N B; Wan, Z; Wang, C; Wang, M J; Wang, S M; Ward, B; Waschke, S; Watanabe, T; Waters, D; Watts, T; Weber, M; Wenzel, H; Wester, W C; Whitehouse, B; Wicklund, A B; Wicklund, E; Wilkes, T; Williams, H H; Wilson, P; Winer, B L; Winn, D; Wolbers, S; Wolinski, D; Wolinski, J; Wolinski, S; Wolter, M; Worm, S; Wu, X; Würthwein, F; Wyss, J; Yang, U K; Yao, W; Yeh, G P; Yeh, P; Yi, K; Yoh, J; Yosef, C; Yoshida, T; Yu, I; Yu, S; Yu, Z; Yun, J C; Zanello, L; Zanetti, A; Zetti, F; Zucchelli, S

2004-02-06

We present the results of a search for pair production of scalar top quarks (t(1)) in an R-parity violating supersymmetry scenario in 106 pb(-1) of pp collisions at square root of s=1.8 TeV collected by the Collider Detector at Fermilab. In this mode each t(1) decays into a tau lepton and a b quark. We search for events with two tau's, one decaying leptonically (e or mu) and one decaying hadronically, and two jets. No candidate events pass our final selection criteria. We set a 95% confidence level lower limit on the t(1) mass at 122 GeV/c(2) for Br(t(1)-->tau b)=1.

Ensemble predictive model for more accurate soil organic carbon spectroscopic estimation

NASA Astrophysics Data System (ADS)

Vašát, Radim; Kodešová, Radka; Borůvka, Luboš

2017-07-01

A myriad of signal pre-processing strategies and multivariate calibration techniques has been explored in attempt to improve the spectroscopic prediction of soil organic carbon (SOC) over the last few decades. Therefore, to come up with a novel, more powerful, and accurate predictive approach to beat the rank becomes a challenging task. However, there may be a way, so that combine several individual predictions into a single final one (according to ensemble learning theory). As this approach performs best when combining in nature different predictive algorithms that are calibrated with structurally different predictor variables, we tested predictors of two different kinds: 1) reflectance values (or transforms) at each wavelength and 2) absorption feature parameters. Consequently we applied four different calibration techniques, two per each type of predictors: a) partial least squares regression and support vector machines for type 1, and b) multiple linear regression and random forest for type 2. The weights to be assigned to individual predictions within the ensemble model (constructed as a weighted average) were determined by an automated procedure that ensured the best solution among all possible was selected. The approach was tested at soil samples taken from surface horizon of four sites differing in the prevailing soil units. By employing the ensemble predictive model the prediction accuracy of SOC improved at all four sites. The coefficient of determination in cross-validation (R2cv) increased from 0.849, 0.611, 0.811 and 0.644 (the best individual predictions) to 0.864, 0.650, 0.824 and 0.698 for Site 1, 2, 3 and 4, respectively. Generally, the ensemble model affected the final prediction so that the maximal deviations of predicted vs. observed values of the individual predictions were reduced, and thus the correlation cloud became thinner as desired.

Quality assessment of gasoline using comprehensive two-dimensional gas chromatography combined with unfolded partial least squares: A reliable approach for the detection of gasoline adulteration.

PubMed

Parastar, Hadi; Mostafapour, Sara; Azimi, Gholamhasan

2016-01-01

Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make calibration samples. Appropriate statistical parameters of regression coefficient of 0.996-0.998, root-mean square error of prediction of 0.005-0.010 and relative error of prediction of 1.54-3.82% for the calibration set show the reliability of the developed method. In addition, the developed method is externally validated with three samples in validation set (with a relative error of prediction below 10.0%). Finally, to test the applicability of the proposed strategy for the analysis of real samples, five real gasoline samples collected from gas stations are used for this purpose and the gasoline proportions were in range of 70-85%. Also, the relative standard deviations were below 8.5% for different samples in the prediction set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A novel life cycle arising from leaf segments in plants regenerated from horseradish hairy roots.

PubMed

Mano, Y; Matsuhashi, M

1995-03-01

Horseradish (Armoracia rusticana) hairy root clones were established from hairy roots which were transformed with the Ri plasmid in Agrobacterium rhizogenes 15834. The transformed plants, which were regenerated from hairy root clones, had thicker roots with extensive lateral branches and thicker stems, and grew faster compared with non-transformed horseradish plants. Small sections of leaves of the transformed plants generated adventitious roots in phytohormone-free G (modified Gamborg's) medium. Root proliferation was followed by adventitious shoot formation and plant regeneration. Approximately twenty plants were regenerated per square centimeter of leaf. The transformed plants were easily transferable from sterile conditions to soil. When leaf segments of the transformed plants were cultured in a liquid fertilizer under non-sterile conditions, adventitious roots were generated at the cut ends of the leaves. Adventitious shoots were generated at the boundary between the leaf and the adventitious roots and developed into complete plants. This novel life cycle arising from leaf segments is a unique property of the transformed plants derived from hairy root clones.

Analysis of the Relationship between the "n"th Root Which Is a Whole Number and the "n" Consecutive Odd Numbers

ERIC Educational Resources Information Center

Kwenge, Erasmus; Mwewa, Peter; Mulenga, H. M.

2015-01-01

The study was undertaken to establish the relationship between the roots of the perfect numbers and the "n" consecutive odd numbers. Odd numbers were arranged in such a way that their sums were either equal to the perfect square number or equal to a cube. The findings on the patterns and relationships of the numbers showed that there was…

Sample allocation balancing overall representativeness and stratum precision.

PubMed

Diaz-Quijano, Fredi Alexander

2018-05-07

In large-scale surveys, it is often necessary to distribute a preset sample size among a number of strata. Researchers must make a decision between prioritizing overall representativeness or precision of stratum estimates. Hence, I evaluated different sample allocation strategies based on stratum size. The strategies evaluated herein included allocation proportional to stratum population; equal sample for all strata; and proportional to the natural logarithm, cubic root, and square root of the stratum population. This study considered the fact that, from a preset sample size, the dispersion index of stratum sampling fractions is correlated with the population estimator error and the dispersion index of stratum-specific sampling errors would measure the inequality in precision distribution. Identification of a balanced and efficient strategy was based on comparing those both dispersion indices. Balance and efficiency of the strategies changed depending on overall sample size. As the sample to be distributed increased, the most efficient allocation strategies were equal sample for each stratum; proportional to the logarithm, to the cubic root, to square root; and that proportional to the stratum population, respectively. Depending on sample size, each of the strategies evaluated could be considered in optimizing the sample to keep both overall representativeness and stratum-specific precision. Copyright © 2018 Elsevier Inc. All rights reserved.

Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

NASA Technical Reports Server (NTRS)

Reichle, R. H.

2010-01-01

Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

Electron acceleration by an obliquely propagating electromagnetic wave in the regime of validity of the Fokker-Planck-Kolmogorov approach

NASA Technical Reports Server (NTRS)

Hizanidis, Kyriakos; Vlahos, L.; Polymilis, C.

1989-01-01

The relativistic motion of an ensemble of electrons in an intense monochromatic electromagnetic wave propagating obliquely in a uniform external magnetic field is studied. The problem is formulated from the viewpoint of Hamiltonian theory and the Fokker-Planck-Kolmogorov approach analyzed by Hizanidis (1989), leading to a one-dimensional diffusive acceleration along paths of constant zeroth-order generalized Hamiltonian. For values of the wave amplitude and the propagating angle inside the analytically predicted stochastic region, the numerical results suggest that the diffusion probes proceeds in stages. In the first stage, the electrons are accelerated to relatively high energies by sampling the first few overlapping resonances one by one. During that stage, the ensemble-average square deviation of the variable involved scales quadratically with time. During the second stage, they scale linearly with time. For much longer times, deviation from linear scaling slowly sets in.

Decorrelation correction for nanoparticle tracking analysis of dilute polydisperse suspensions in bulk flow

NASA Astrophysics Data System (ADS)

Hartman, John; Kirby, Brian

2017-03-01

Nanoparticle tracking analysis, a multiprobe single particle tracking technique, is a widely used method to quickly determine the concentration and size distribution of colloidal particle suspensions. Many popular tools remove non-Brownian components of particle motion by subtracting the ensemble-average displacement at each time step, which is termed dedrifting. Though critical for accurate size measurements, dedrifting is shown here to introduce significant biasing error and can fundamentally limit the dynamic range of particle size that can be measured for dilute heterogeneous suspensions such as biological extracellular vesicles. We report a more accurate estimate of particle mean-square displacement, which we call decorrelation analysis, that accounts for correlations between individual and ensemble particle motion, which are spuriously introduced by dedrifting. Particle tracking simulation and experimental results show that this approach more accurately determines particle diameters for low-concentration polydisperse suspensions when compared with standard dedrifting techniques.

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

Quantifying non-ergodic dynamics of force-free granular gases.

PubMed

Bodrova, Anna; Chechkin, Aleksei V; Cherstvy, Andrey G; Metzler, Ralf

2015-09-14

Brownian motion is ergodic in the Boltzmann-Khinchin sense that long time averages of physical observables such as the mean squared displacement provide the same information as the corresponding ensemble average, even at out-of-equilibrium conditions. This property is the fundamental prerequisite for single particle tracking and its analysis in simple liquids. We study analytically and by event-driven molecular dynamics simulations the dynamics of force-free cooling granular gases and reveal a violation of ergodicity in this Boltzmann-Khinchin sense as well as distinct ageing of the system. Such granular gases comprise materials such as dilute gases of stones, sand, various types of powders, or large molecules, and their mixtures are ubiquitous in Nature and technology, in particular in Space. We treat-depending on the physical-chemical properties of the inter-particle interaction upon their pair collisions-both a constant and a velocity-dependent (viscoelastic) restitution coefficient ε. Moreover we compare the granular gas dynamics with an effective single particle stochastic model based on an underdamped Langevin equation with time dependent diffusivity. We find that both models share the same behaviour of the ensemble mean squared displacement (MSD) and the velocity correlations in the limit of weak dissipation. Qualitatively, the reported non-ergodic behaviour is generic for granular gases with any realistic dependence of ε on the impact velocity of particles.

An inverse method to estimate emission rates based on nonlinear least-squares-based ensemble four-dimensional variational data assimilation with local air concentration measurements.

PubMed

Geng, Xiaobing; Xie, Zhenghui; Zhang, Lijun; Xu, Mei; Jia, Binghao

2018-03-01

An inverse source estimation method is proposed to reconstruct emission rates using local air concentration sampling data. It involves the nonlinear least squares-based ensemble four-dimensional variational data assimilation (NLS-4DVar) algorithm and a transfer coefficient matrix (TCM) created using FLEXPART, a Lagrangian atmospheric dispersion model. The method was tested by twin experiments and experiments with actual Cs-137 concentrations measured around the Fukushima Daiichi Nuclear Power Plant (FDNPP). Emission rates can be reconstructed sequentially with the progression of a nuclear accident, which is important in the response to a nuclear emergency. With pseudo observations generated continuously, most of the emission rates were estimated accurately, except under conditions when the wind blew off land toward the sea and at extremely slow wind speeds near the FDNPP. Because of the long duration of accidents and variability in meteorological fields, monitoring networks composed of land stations only in a local area are unable to provide enough information to support an emergency response. The errors in the estimation compared to the real observations from the FDNPP nuclear accident stemmed from a shortage of observations, lack of data control, and an inadequate atmospheric dispersion model without improvement and appropriate meteorological data. The proposed method should be developed further to meet the requirements of a nuclear emergency response. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Langevin equation with fluctuating diffusivity: A two-state model

NASA Astrophysics Data System (ADS)

Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

2016-07-01

Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool.

In vitro study of the variable square pulse Er:YAG laser cutting efficacy for apicectomy.

PubMed

Grgurević, Josko; Grgurević, Lovro; Miletić, Ivana; Karlović, Zoran; Krmek, Silvana Jukić; Anić, Ivica

2005-06-01

Variable square pulse (VSP) Er:YAG laser should be quicker than older Er:YAG lasers. The objectives were: (1) comparison of VSP laser and mechanical handpiece efficacy for apicectomy and (2) determination of optimal pulse width/energy/frequency combination. Sixty extracted, single-rooted mature human teeth with round apical parts were instrumented, root filled, cleaned, and divided into four groups. Apical 2 mm of each root were apicectomized with mechanical handpiece and Er:YAG laser with three different settings (LaserA = 200 mJ/300 microseconds/ 8 Hz; LaserB = 200 mJ/100 microseconds/8 Hz; LaserC = 380 mJ/100 microseconds/20 Hz). Timing results were statistically compared. LaserC was the most efficient setting. Differences between groups were significant except between LaserC-Mechanical and LaserA-LaserC (P < 0.05). VSP Er:YAG laser used for apicectomy is slower by a factor of 7-31 than mechanical handpiece, but treatment outcome is acceptable. Optimal settings for apicectomy with VSP laser are 380 mJ/100 microseconds/20 Hz. Copyright 2005 Wiley-Liss, Inc.

Validation of the Family Inpatient Communication Survey.

PubMed

Torke, Alexia M; Monahan, Patrick; Callahan, Christopher M; Helft, Paul R; Sachs, Greg A; Wocial, Lucia D; Slaven, James E; Montz, Kianna; Inger, Lev; Burke, Emily S

2017-01-01

Although many family members who make surrogate decisions report problems with communication, there is no validated instrument to accurately measure surrogate/clinician communication for older adults in the acute hospital setting. The objective of this study was to validate a survey of surrogate-rated communication quality in the hospital that would be useful to clinicians, researchers, and health systems. After expert review and cognitive interviewing (n = 10 surrogates), we enrolled 350 surrogates (250 development sample and 100 validation sample) of hospitalized adults aged 65 years and older from three hospitals in one metropolitan area. The communication survey and a measure of decision quality were administered within hospital days 3 and 10. Mental health and satisfaction measures were administered six to eight weeks later. Factor analysis showed support for both one-factor (Total Communication) and two-factor models (Information and Emotional Support). Item reduction led to a final 30-item scale. For the validation sample, internal reliability (Cronbach's alpha) was 0.96 (total), 0.94 (Information), and 0.90 (Emotional Support). Confirmatory factor analysis fit statistics were adequate (one-factor model, comparative fit index = 0.981, root mean square error of approximation = 0.62, weighted root mean square residual = 1.011; two-factor model comparative fit index = 0.984, root mean square error of approximation = 0.055, weighted root mean square residual = 0.930). Total score and subscales showed significant associations with the Decision Conflict Scale (Pearson correlation -0.43, P < 0.001 for total score). Emotional Support was associated with improved mental health outcomes at six to eight weeks, such as anxiety (-0.19 P < 0.001), and Information was associated with satisfaction with the hospital stay (0.49, P < 0.001). The survey shows high reliability and validity in measuring communication experiences for hospital surrogates. The scale has promise for measurement of communication quality and is predictive of important outcomes, such as surrogate satisfaction and well-being. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Spectral combination of spherical gravitational curvature boundary-value problems

NASA Astrophysics Data System (ADS)

PitoÅák, Martin; Eshagh, Mehdi; Šprlák, Michal; Tenzer, Robert; Novák, Pavel

2018-04-01

Four solutions of the spherical gravitational curvature boundary-value problems can be exploited for the determination of the Earth's gravitational potential. In this article we discuss the combination of simulated satellite gravitational curvatures, i.e., components of the third-order gravitational tensor, by merging these solutions using the spectral combination method. For this purpose, integral estimators of biased- and unbiased-types are derived. In numerical studies, we investigate the performance of the developed mathematical models for the gravitational field modelling in the area of Central Europe based on simulated satellite measurements. Firstly, we verify the correctness of the integral estimators for the spectral downward continuation by a closed-loop test. Estimated errors of the combined solution are about eight orders smaller than those from the individual solutions. Secondly, we perform a numerical experiment by considering the Gaussian noise with the standard deviation of 6.5× 10-17 m-1s-2 in the input data at the satellite altitude of 250 km above the mean Earth sphere. This value of standard deviation is equivalent to a signal-to-noise ratio of 10. Superior results with respect to the global geopotential model TIM-r5 are obtained by the spectral downward continuation of the vertical-vertical-vertical component with the standard deviation of 2.104 m2s-2, but the root mean square error is the largest and reaches 9.734 m2s-2. Using the spectral combination of all gravitational curvatures the root mean square error is more than 400 times smaller but the standard deviation reaches 17.234 m2s-2. The combination of more components decreases the root mean square error of the corresponding solutions while the standard deviations of the combined solutions do not improve as compared to the solution from the vertical-vertical-vertical component. The presented method represents a weight mean in the spectral domain that minimizes the root mean square error of the combined solutions and improves standard deviation of the solution based only on the least accurate components.

Design of Glucagon-Like Peptide-1 Receptor Agonist for Diabetes Mellitus from Traditional Chinese Medicine

PubMed Central

Tang, Hsin-Chieh; Chen, Calvin Yu-Chian

2014-01-01

Glucagon-like peptide-1 (GLP-1) is a promising target for diabetes mellitus (DM) therapy and reduces the occurrence of diabetes due to obesity. However, GLP-1 will be hydrolyzed soon by the enzyme dipeptidyl peptidase-4 (DPP-4). We tried to design small molecular drugs for GLP-1 receptor agonist from the world's largest traditional Chinese medicine (TCM) Database@Taiwan. According to docking results of virtual screening, we selected 2 TCM compounds, wenyujinoside and 28-deglucosylchikusetsusaponin IV, for further molecular dynamics (MD) simulation. GLP-1 was assigned as the control compound. Based on the results of root mean square deviation (RMSD), solvent accessible surface (SAS), mean square deviation (MSD), Gyrate, total energy, root mean square fluctuation (RMSF), matrices of smallest distance of residues, database of secondary structure assignment (DSSP), cluster analysis, and distance of H-bond, we concluded that all the 3 compounds could bind and activate GLP-1 receptor by computational simulation. Wenyujinoside and 28-deglucosylchikusetsusaponin IV were the TCM compounds that could be GLP-1 receptor agonists. PMID:24891870

Design of glucagon-like Peptide-1 receptor agonist for diabetes mellitus from traditional chinese medicine.

PubMed

Tang, Hsin-Chieh; Chen, Calvin Yu-Chian

2014-01-01

Glucagon-like peptide-1 (GLP-1) is a promising target for diabetes mellitus (DM) therapy and reduces the occurrence of diabetes due to obesity. However, GLP-1 will be hydrolyzed soon by the enzyme dipeptidyl peptidase-4 (DPP-4). We tried to design small molecular drugs for GLP-1 receptor agonist from the world's largest traditional Chinese medicine (TCM) Database@Taiwan. According to docking results of virtual screening, we selected 2 TCM compounds, wenyujinoside and 28-deglucosylchikusetsusaponin IV, for further molecular dynamics (MD) simulation. GLP-1 was assigned as the control compound. Based on the results of root mean square deviation (RMSD), solvent accessible surface (SAS), mean square deviation (MSD), Gyrate, total energy, root mean square fluctuation (RMSF), matrices of smallest distance of residues, database of secondary structure assignment (DSSP), cluster analysis, and distance of H-bond, we concluded that all the 3 compounds could bind and activate GLP-1 receptor by computational simulation. Wenyujinoside and 28-deglucosylchikusetsusaponin IV were the TCM compounds that could be GLP-1 receptor agonists.

[Study on predicting sugar content and valid acidity of apples by near infrared diffuse reflectance technique].

PubMed

Liu, Yan-de; Ying, Yi-bin; Fu, Xia-ping

2005-11-01

The nondestructive method for quantifying sugar content (SC) and available acid (VA) of intact apples using diffuse near infrared reflectance and optical fiber sensing techniques were explored in the present research. The standard sample sets and prediction models were established by partial least squares analysis (PLS). A total of 120 Shandong Fuji apples were tested in the wave number of 12,500 - 4000 cm(-1) using Fourier transform near infrared spectroscopy. The results of the research indicated that the nondestructive quantification of SC and VA, gave a high correlation coefficient 0.970 and 0.906, a low root mean square error of prediction (RMSEP) 0.272 and 0.056 2, a low root mean square error of calibration (RMSEC) 0.261 and 0.0677, and a small difference between RMSEP and RMSEC 0.011 a nd 0.0115. It was suggested that the diffuse nearinfrared reflectance technique be feasible for nondestructive determination of apple sugar content in the wave number range of 10,341 - 5461 cm(-1) and for available acid in the wave number range of 10,341 - 3818 cm(-1).

Analysis of Lard in Lipstick Formulation Using FTIR Spectroscopy and Multivariate Calibration: A Comparison of Three Extraction Methods.

PubMed

Waskitho, Dri; Lukitaningsih, Endang; Sudjadi; Rohman, Abdul

2016-01-01

Analysis of lard extracted from lipstick formulation containing castor oil has been performed using FTIR spectroscopic method combined with multivariate calibration. Three different extraction methods were compared, namely saponification method followed by liquid/liquid extraction with hexane/dichlorometane/ethanol/water, saponification method followed by liquid/liquid extraction with dichloromethane/ethanol/water, and Bligh & Dyer method using chloroform/methanol/water as extracting solvent. Qualitative and quantitative analysis of lard were performed using principle component (PCA) and partial least square (PLS) analysis, respectively. The results showed that, in all samples prepared by the three extraction methods, PCA was capable of identifying lard at wavelength region of 1200-800 cm -1 with the best result was obtained by Bligh & Dyer method. Furthermore, PLS analysis at the same wavelength region used for qualification showed that Bligh and Dyer was the most suitable extraction method with the highest determination coefficient (R 2 ) and the lowest root mean square error of calibration (RMSEC) as well as root mean square error of prediction (RMSEP) values.

Detection of Butter Adulteration with Lard by Employing (1)H-NMR Spectroscopy and Multivariate Data Analysis.

PubMed

Fadzillah, Nurrulhidayah Ahmad; Man, Yaakob bin Che; Rohman, Abdul; Rosman, Arieff Salleh; Ismail, Amin; Mustafa, Shuhaimi; Khatib, Alfi

2015-01-01

The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance ((1)H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all proton bearing compounds, and consequently all relevant sample classes. Since the spectra obtained were too complex to be analyzed visually by the naked eyes, the classification of spectra was carried out.The multivariate calibration of partial least square (PLS) regression was used for modelling the relationship between actual value of lard and predicted value. The model yielded a highest regression coefficient (R(2)) of 0.998 and the lowest root mean square error calibration (RMSEC) of 0.0091% and root mean square error prediction (RMSEP) of 0.0090, respectively. Cross validation testing evaluates the predictive power of the model. PLS model was shown as good models as the intercept of R(2)Y and Q(2)Y were 0.0853 and -0.309, respectively.

Assessing climate change over the Marche Region (central Italy) from 1961 to 2100: projected changes in mean temperature and future heat waves characterization (with a statistical evaluation of RCMs local performance)

NASA Astrophysics Data System (ADS)

Sangelantoni, Lorenzo; Coluccelli, Alessandro; Russo, Aniello

2014-05-01

Marche region (central Italy, facing the Adriatic Sea) climate dynamics are connected to the Mediterranean basin, identified as one of the most sensitive areas to ongoing climate change. Taken into account difficulties to carry out an overarching assessment over the heterogeneous Mediterranean climate-change issues frame, we opted toward a consistent regional bordered study. Projected changes in mean seasonal temperature, with an introductory multi-statistical model performance evaluation and a future heat waves intensity and duration characterization, are here presented. Multi-model projections over Marche Region, on daily mean, minimum and maximum temperature, have been extracted from the outputs of a set of 7 Regional Climate Models (RCMs) over Europe run by several research Institutes participating to the EU ENSEMBLE project. These climate simulations from 1961 to 2100 refer to the boundary conditions of the IPCC A1B emission scenario, and have a horizontal resolution of 25km × 25km. Furthermore, two RCMs outputs from Med-CORDEX project, with a higher horizontal resolution (12km x 12km) and boundary conditions provided by the new Representative Concentration Pathway (RCP) 4.5 and 8.5, are considered. Observed daily mean, minimum and maximum temperature over Marche region domain have been extracted from E-OBS gridded data set (Version 9.0) referring to the period 1970-2004. This twofold work firstly provides a concise statistical summary of how well employed RCMs reproduce observed (1970-2004) mean temperature over Marche region in term of correlation, root-mean-square difference, and ratio of their variances, graphically displayed on a 2D-Taylor diagram. This multi-statistical model performance evaluation easily allows: - to compare the agreement with observation of the 9 individual RCMs - to compare RCMs with different horizontal resolution (12 km and 25 km) - to evaluate the improvement provided by the RCMs ensemble. Results indicate that the 9 RCMs ensemble provides the statistically best reproduction of the observed interannual mean temperature distribution. Secondly, we assessed projected seasonal ensemble average change in mean temperature referring to the ending 21st century obtained by comparison between 2071-2100 and 1961-1990 time slice modeled mean value over Marche region. Results emphasize summer as the season most affected by projected temperature increase (+4.5°C / +5.0°C), followed by spring season temperature increase (+3.5°C / +4.0°C). Finally, considering that some of the most severe health hazards arise from multi-day heat-waves, associated with both hot day-time and warm night-time temperatures, we assessed modeled trend (1961-2100) of the heat waves intensity and duration: intensity through the temporal evolution of the summer (J J A months) maximum and minimum temperature 90th percentile, heat waves length by temporal evolution of two detected threshold-based indices (annual maximum number of consecutive days characterized by Tmin >= 24°C and annual maximum number of consecutive days characterized by Tmax > = 32°C). Same analysis for both coastal and mountainous areas has been conducted. Future research plans aim to involve ensemble RCMs simulation, processed with bias correction methods, in forcing climate change impacts models, to provide a detailed regional heat waves impacts scenario, mainly over agriculture and health sectors.

Non-stationary least-squares complex decomposition for microseismic noise attenuation

NASA Astrophysics Data System (ADS)

Chen, Yangkang

2018-06-01

Microseismic data processing and imaging are crucial for subsurface real-time monitoring during hydraulic fracturing process. Unlike the active-source seismic events or large-scale earthquake events, the microseismic event is usually of very small magnitude, which makes its detection challenging. The biggest trouble of microseismic data is the low signal-to-noise ratio issue. Because of the small energy difference between effective microseismic signal and ambient noise, the effective signals are usually buried in strong random noise. I propose a useful microseismic denoising algorithm that is based on decomposing a microseismic trace into an ensemble of components using least-squares inversion. Based on the predictive property of useful microseismic event along the time direction, the random noise can be filtered out via least-squares fitting of multiple damping exponential components. The method is flexible and almost automated since the only parameter needed to be defined is a decomposition number. I use some synthetic and real data examples to demonstrate the potential of the algorithm in processing complicated microseismic data sets.

On some labelings of triangular snake and central graph of triangular snake graph

NASA Astrophysics Data System (ADS)

Agasthi, P.; Parvathi, N.

2018-04-01

A Triangular snake Tn is obtained from a path u 1 u 2 … u n by joining ui and u i+1 to a new vertex wi for 1≤i≤n‑1. A Central graph of Triangular snake C(T n ) is obtained by subdividing each edge of Tn exactly once and joining all the non adjacent vertices of Tn . In this paper the ways to construct square sum, square difference, Root Mean square, strongly Multiplicative, Even Mean and Odd Mean labeling for Triangular Snake and Central graph of Triangular Snake graphs are reported.

Online measurement of urea concentration in spent dialysate during hemodialysis.

PubMed

Olesberg, Jonathon T; Arnold, Mark A; Flanigan, Michael J

2004-01-01

We describe online optical measurements of urea in the effluent dialysate line during regular hemodialysis treatment of several patients. Monitoring urea removal can provide valuable information about dialysis efficiency. Spectral measurements were performed with a Fourier-transform infrared spectrometer equipped with a flow-through cell. Spectra were recorded across the 5000-4000 cm(-1) (2.0-2.5 microm) wavelength range at 1-min intervals. Savitzky-Golay filtering was used to remove baseline variations attributable to the temperature dependence of the water absorption spectrum. Urea concentrations were extracted from the filtered spectra by use of partial least-squares regression and the net analyte signal of urea. Urea concentrations predicted by partial least-squares regression matched concentrations obtained from standard chemical assays with a root mean square error of 0.30 mmol/L (0.84 mg/dL urea nitrogen) over an observed concentration range of 0-11 mmol/L. The root mean square error obtained with the net analyte signal of urea was 0.43 mmol/L with a calibration based only on a set of pure-component spectra. The error decreased to 0.23 mmol/L when a slope and offset correction were used. Urea concentrations can be continuously monitored during hemodialysis by near-infrared spectroscopy. Calibrations based on the net analyte signal of urea are particularly appealing because they do not require a training step, as do statistical multivariate calibration procedures such as partial least-squares regression.

Ensemble prediction of air quality using the WRF/CMAQ model system for health effect studies in China

NASA Astrophysics Data System (ADS)

Hu, Jianlin; Li, Xun; Huang, Lin; Ying, Qi; Zhang, Qiang; Zhao, Bin; Wang, Shuxiao; Zhang, Hongliang

2017-11-01

Accurate exposure estimates are required for health effect analyses of severe air pollution in China. Chemical transport models (CTMs) are widely used to provide spatial distribution, chemical composition, particle size fractions, and source origins of air pollutants. The accuracy of air quality predictions in China is greatly affected by the uncertainties of emission inventories. The Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the Weather Research and Forecasting (WRF) model were used in this study to simulate air pollutants in China in 2013. Four simulations were conducted with four different anthropogenic emission inventories, including the Multi-resolution Emission Inventory for China (MEIC), the Emission Inventory for China by School of Environment at Tsinghua University (SOE), the Emissions Database for Global Atmospheric Research (EDGAR), and the Regional Emission inventory in Asia version 2 (REAS2). Model performance of each simulation was evaluated against available observation data from 422 sites in 60 cities across China. Model predictions of O3 and PM2.5 generally meet the model performance criteria, but performance differences exist in different regions, for different pollutants, and among inventories. Ensemble predictions were calculated by linearly combining the results from different inventories to minimize the sum of the squared errors between the ensemble results and the observations in all cities. The ensemble concentrations show improved agreement with observations in most cities. The mean fractional bias (MFB) and mean fractional errors (MFEs) of the ensemble annual PM2.5 in the 60 cities are -0.11 and 0.24, respectively, which are better than the MFB (-0.25 to -0.16) and MFE (0.26-0.31) of individual simulations. The ensemble annual daily maximum 1 h O3 (O3-1h) concentrations are also improved, with mean normalized bias (MNB) of 0.03 and mean normalized errors (MNE) of 0.14, compared to MNB of 0.06-0.19 and MNE of 0.16-0.22 of the individual predictions. The ensemble predictions agree better with observations with daily, monthly, and annual averaging times in all regions of China for both PM2.5 and O3-1h. The study demonstrates that ensemble predictions from combining predictions from individual emission inventories can improve the accuracy of predicted temporal and spatial distributions of air pollutants. This study is the first ensemble model study in China using multiple emission inventories, and the results are publicly available for future health effect studies.

Near-infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Parching Process of Traditional Chinese Medicine Based on Two Kinds of Chemical Indicators.

PubMed

Li, Kaiyue; Wang, Weiying; Liu, Yanping; Jiang, Su; Huang, Guo; Ye, Liming

2017-01-01

The active ingredients and thus pharmacological efficacy of traditional Chinese medicine (TCM) at different degrees of parching process vary greatly. Near-infrared spectroscopy (NIR) was used to develop a new method for rapid online analysis of TCM parching process, using two kinds of chemical indicators (5-(hydroxymethyl) furfural [5-HMF] content and 420 nm absorbance) as reference values which were obviously observed and changed in most TCM parching process. Three representative TCMs, Areca ( Areca catechu L.), Malt ( Hordeum Vulgare L.), and Hawthorn ( Crataegus pinnatifida Bge.), were used in this study. With partial least squares regression, calibration models of NIR were generated based on two kinds of reference values, i.e. 5-HMF contents measured by high-performance liquid chromatography (HPLC) and 420 nm absorbance measured by ultraviolet-visible spectroscopy (UV/Vis), respectively. In the optimized models for 5-HMF, the root mean square errors of prediction (RMSEP) for Areca, Malt, and Hawthorn was 0.0192, 0.0301, and 0.2600 and correlation coefficients ( R cal ) were 99.86%, 99.88%, and 99.88%, respectively. Moreover, in the optimized models using 420 nm absorbance as reference values, the RMSEP for Areca, Malt, and Hawthorn was 0.0229, 0.0096, and 0.0409 and R cal were 99.69%, 99.81%, and 99.62%, respectively. NIR models with 5-HMF content and 420 nm absorbance as reference values can rapidly and effectively identify three kinds of TCM in different parching processes. This method has great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online analysis and quality control in TCM industrial manufacturing process. Near-infrared spectroscopy.(NIR) was used to develop a new method for online analysis of traditional Chinese medicine.(TCM) parching processCalibration and validation models of Areca, Malt, and Hawthorn were generated by partial least squares regression using 5.(hydroxymethyl) furfural contents and 420.nm absorbance as reference values, respectively, which were main indicator components during parching process of most TCMThe established NIR models of three TCMs had low root mean square errors of prediction and high correlation coefficientsThe NIR method has great promise for use in TCM industrial manufacturing processes for rapid online analysis and quality control. Abbreviations used: NIR: Near-infrared Spectroscopy; TCM: Traditional Chinese medicine; Areca: Areca catechu L.; Hawthorn: Crataegus pinnatifida Bge.; Malt: Hordeum vulgare L.; 5-HMF: 5-(hydroxymethyl) furfural; PLS: Partial least squares; D: Dimension faction; SLS: Straight line subtraction, MSC: Multiplicative scatter correction; VN: Vector normalization; RMSECV: Root mean square errors of cross-validation; RMSEP: Root mean square errors of validation; R cal : Correlation coefficients; RPD: Residual predictive deviation; PAT: Process analytical technology; FDA: Food and Drug Administration; ICH: International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use.

The influence of spectral nudging on typhoon formation in regional climate models

NASA Astrophysics Data System (ADS)

Feser, Frauke; Barcikowska, Monika

2012-03-01

Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden-Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model, with results slightly closer to reanalysis data for the spectral nudged simulations. On the basis of this regional climate model hindcast study of a single typhoon season, spectral nudging seems to be favourable since it has mostly positive effects on typhoon formation, location and general circulation patterns in the generation areas of TCs.

Assimilation of IASI partial tropospheric columns with an Ensemble Kalman Filter over Europe

NASA Astrophysics Data System (ADS)

Coman, A.; Foret, G.; Beekmann, M.; Eremenko, M.; Dufour, G.; Gaubert, B.; Ung, A.; Schmechtig, C.; Flaud, J.-M.; Bergametti, G.

2011-09-01

Partial lower tropospheric ozone columns provided by the IASI (Infrared Atmospheric Sounding Interferometer) instrument have been assimilated into a chemistry-transport model at continental scale (CHIMERE) using an Ensemble Kalman Filter (EnKF). Analyses are made for the month of July 2007 over the European domain. Launched in 2006, aboard the MetOp-A satellite, IASI shows high sensitivity for ozone in the free troposphere and low sensitivity at the ground; therefore it is important to evaluate if assimilation of these observations can improve free tropospheric ozone, and possibly surface ozone. The analyses are validated against independent ozone observations from sondes, MOZAIC1 aircraft and ground based stations (AIRBASE - the European Air quality dataBase) and compared with respect to the free run of CHIMERE. These comparisons show a decrease in error of 6 parts-per-billion (ppb) in the free troposphere over the Frankfurt area, and also a reduction of the root mean square error (respectively bias) at the surface of 19% (33%) for more than 90% of existing ground stations. This provides evidence of the potential of data assimilation of tropospheric IASI columns to better describe the tropospheric ozone distribution, including surface ozone, despite the lower sensitivity. The changes in concentration resulting from the observational constraints were quantified and several geophysical explanations for the findings of this study were drawn. The corrections were most pronounced over Italy and the Mediterranean region, on the average we noted an average reduction of 8-9 ppb in the free troposphere with respect to the free run, and still a reduction of 5.5 ppb at ground, likely due to a longer residence time of air masses in this part associated to the general circulation pattern (i.e. dominant western circulation) and to persistent anticyclonic conditions over the Mediterranean basin. This is an important geophysical result, since the ozone burden is large over this area, with impact on the radiative balance and air quality. 1 Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by in-service AIrbus airCraft ( http://mozaic.aero.obs-mip.fr/web/)

Estimation of snow emissivity via assimilation of multi-frequency passive microwave data into an ensemble-based data assimilation system

NASA Astrophysics Data System (ADS)

Farhadi, L.; Bateni, S. M.; Auligne, T.; Navari, M.

2017-12-01

Snow emissivity is a key parameter for the estimation of snow surface temperature, which is needed as an initial value in climate models and determination of the outgoing long-wave radiation. Moreover, snow emissivity is required for retrieval of atmospheric parameters (e.g., temperature and humidity profiles) from satellite measurements and satellite data assimilations in numerical weather prediction systems. Microwave emission models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Existing microwave emission models introduce significant uncertainties in their snow emissivity estimates. This is mainly due to shortcomings of the dense media theory for snow medium at high frequencies, and erroneous forcing variables. The well-known limitations of passive microwave data such as coarse spatial resolution, saturation in deep snowpack, and signal loss in wet snow are the major drawbacks of passive microwave retrieval algorithms for estimation of snow emissivity. A full exploitation of the information contained in the remote sensing data can be achieved by merging them with snow emission models within a data assimilation framework. Such an optimal merging can overcome the specific limitations of models and remote sensing data. An Ensemble Batch Smoother (EnBS) data assimilation framework was developed in this study to combine the synthetically generated passive microwave brightness temperatures at 1.4-, 18.7-, 36.5-, and 89-GHz frequencies with the MEMLS microwave emission model to reduce the uncertainty of the snow emissivity estimates. We have used the EnBS algorithm in the context of observing system simulation experiment (or synthetic experiment) at the local scale observation site (LSOS) of the NASA CLPX field campaign. Our findings showed that the developed methodology significantly improves the estimates of the snow emissivity. The simultaneous assimilation of passive microwave brightness temperatures at all frequencies (i.e., 1.4-, 18.7-, 36.5-, and 89-GHz) reduce the root-mean-square-error (RMSE) of snow emissivity at 1.4-, 18.7-, 36.5-, and 89-GHz (H-pol.) by 80%, 42%, 52%, 40%, respectively compared to the corresponding snow emissivity estimates from the open-loop model.

Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.

NASA Astrophysics Data System (ADS)

Nair, A. S.; Indu, J.

2017-12-01

Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb assimilation. The results indicate an improvement in Tb simulations based on the multi polarization difference index approach with a correlation of 0.81 (figure 1b (e)) and bias of < 5 K with respect to the SMOS Tb.

Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

NASA Astrophysics Data System (ADS)

Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

2016-02-01

The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

Light scattering from laser induced pit ensembles on high power laser optics

DOE PAGES

Feigenbaum, Eyal; Elhadj, Selim; Matthews, Manyalibo J.

2015-01-01

Far-field light scattering characteristics from randomly arranged shallow Gaussian-like shaped laser induced pits, found on optics exposed to high energy laser pulses, is studied. Closed-form expressions for the far-field intensity distribution and scattered power are derived for individual pits and validated using numerical calculations of both Fourier optics and FDTD solutions to Maxwell’s equations. It is found that the scattered power is proportional to the square of the pit width and approximately also to the square of the pit depth, with the proportionality factor scaling with pit depth. As a result, the power scattered from shallow pitted optics is expectedmore » to be substantially lower than assuming complete scattering from the total visible footprint of the pits.« less

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

PubMed

Ramírez, J; Górriz, J M; Ortiz, A; Martínez-Murcia, F J; Segovia, F; Salas-Gonzalez, D; Castillo-Barnes, D; Illán, I A; Puntonet, C G

2018-05-15

Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have suggested that people with MCI tend to progress to AD at a rate of about 10-15% per year. However, the ability of clinicians and machine learning systems to predict AD based on MRI biomarkers at an early stage is still a challenging problem that can have a great impact in improving treatments. The proposed system, developed by the SiPBA-UGR team for this challenge, is based on feature standardization, ANOVA feature selection, partial least squares feature dimension reduction and an ensemble of One vs. Rest random forest classifiers. With the aim of improving its performance when discriminating healthy controls (HC) from MCI, a second binary classification level was introduced that reconsiders the HC and MCI predictions of the first level. The system was trained and evaluated on an ADNI datasets that consist of T1-weighted MRI morphological measurements from HC, stable MCI, converter MCI and AD subjects. The proposed system yields a 56.25% classification score on the test subset which consists of 160 real subjects. The classifier yielded the best performance when compared to: (i) One vs. One (OvO), One vs. Rest (OvR) and error correcting output codes (ECOC) as strategies for reducing the multiclass classification task to multiple binary classification problems, (ii) support vector machines, gradient boosting classifier and random forest as base binary classifiers, and (iii) bagging ensemble learning. A robust method has been proposed for the international challenge on MCI prediction based on MRI data. The system yielded the second best performance during the competition with an accuracy rate of 56.25% when evaluated on the real subjects of the test set. Copyright © 2017 Elsevier B.V. All rights reserved.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

NASA Astrophysics Data System (ADS)

Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

2015-09-01

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images. Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

PubMed Central

Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

2015-01-01

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. Methods We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 seconds. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.04375 mAs, were investigated. Both the analytical FDK algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. Results With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images. Conclusions Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode. PMID:26352168

Time and materials needed to survey, inject systemic fungicides, and install root-graft barriers for Dutch elm disease management

Treesearch

William N., Jr. Cannon; Jack H. Barger; Charles J. Kostichka; Charles J. Kostichka

1986-01-01

Dutch elm disease control practice in 15 communities showed a wide range of time and material required to apply control methods. The median time used for each method was: sanitation survey, 9.8 hours per square mile; symptom survey, 96 hours per thousand elms; systemic fungicide injection, 1.4 hours per elm; and root-graft barrier installation, 2.2 hours per barrier (5...

Derivation of formulas for root-mean-square errors in location, orientation, and shape in triangulation solution of an elongated object in space

NASA Technical Reports Server (NTRS)

Long, S. A. T.

1974-01-01

Formulas are derived for the root-mean-square (rms) displacement, slope, and curvature errors in an azimuth-elevation image trace of an elongated object in space, as functions of the number and spacing of the input data points and the rms elevation error in the individual input data points from a single observation station. Also, formulas are derived for the total rms displacement, slope, and curvature error vectors in the triangulation solution of an elongated object in space due to the rms displacement, slope, and curvature errors, respectively, in the azimuth-elevation image traces from different observation stations. The total rms displacement, slope, and curvature error vectors provide useful measure numbers for determining the relative merits of two or more different triangulation procedures applicable to elongated objects in space.

Rapidity dependence of antiproton-to-proton ratios in Au+Au collisions at square root of (sNN) = 130 GeV.

PubMed

Bearden, I G; Beavis, D; Besliu, C; Blyakhman, Y; Brzychczyk, J; Budick, B; Bøggild, H; Chasman, C; Christensen, C H; Christiansen, P; Cibor, J; Debbe, R; Gaardhøje, J J; Grotowski, K; Hagel, K; Hansen, O; Holm, A; Holme, A K; Ito, H; Jakobsen, E; Jipa, A; Jørdre, J I; Jundt, F; Jørgensen, C E; Keutgen, T; Kim, E J; Kozik, T; Larsen, T M; Lee, J H; Lee, Y K; Løvhøiden, G L; Majka, Z; Makeev, A; McBreen, B; Murray, M; Natowitz, J; Nielsen, B S; Olchanski, K; Olness, J; Ouerdane, D; Planeta, R; Rami, F; Röhrich, D; Samset, B H; Sanders, S J; Sheetz, R A; Sosin, Z; Staszel, P; Thorsteinsen, T F; Tveter, T S; Videbaek, F; Wada, R; Wieloch, A; Zgura, I S

2001-09-10

Measurements, with the BRAHMS detector, of the antiproton-to-proton ratio at midrapidities and forward rapidities, are presented for Au+Au reactions at square root of [s(NN)] = 130 GeV, and for three different collision centralities. For collisions in the 0%-40% centrality range, we find N(&pmacr;)/N(p) = 0.64+/-0.04((stat))+/-0.06((syst)) at y approximately 0, 0.66+/-0.03+/-0.06 at y approximately 0.7, and 0.41+/-0.04+/-0.06 at y approximately 2. The ratios are found to be nearly independent of collision centrality and transverse momentum. The antiproton and proton rapidity densities vary differently with rapidity, and indicate a significant degree of collision transparency, although a net-baryon free midrapidity plateau (Bjorken limit) is not yet reached.