Estimation of streamflow, base flow, and nitrate-nitrogen loads in Iowa using multiple linear regression models

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2005-01-01

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest. (JAWRA) (Copyright ?? 2005).

Understanding the Long-Term Spectral Variability of Cygnus X-1 from BATSE and ASM Observations

NASA Technical Reports Server (NTRS)

Zdziarski, Andrzej A.; Poutanen, Juri; Paciesas, William S.; Wen, Linqing; Six, N. Frank (Technical Monitor)

2002-01-01

We present a spectral analysis of observations of Cygnus X-1 by the RXTE/ASM (1.5-12 keV) and CGRO/BATSE (20-300 keV), including about 1200 days of simultaneous data. We find a number of correlations between intensities and hardnesses in different energy bands from 1.5 keV to 300 keV. In the hard (low) spectral state, there is a negative correlation between the ASM 1.5-12 keV flux and the hardness at any energy. In the soft (high) spectral state, the ASM flux is positively correlated with the ASM hardness (as previously reported) but uncorrelated with the BATSE hardness. In both spectral states, the BATSE hardness correlates with the flux above 100 keV, while it shows no correlation with the flux in the 20-100 keV range. At the same time, there is clear correlation between the BATSE fluxes below and above 100 keV. In the hard state, most of the variability can be explained by softening the overall spectrum with a pivot at approximately 50 keV. The observations show that there has to be another, independent variability pattern of lower amplitude where the spectral shape does not change when the luminosity changes. In the soft state, the variability is mostly caused by a variable hard (Comptonized) spectral component of a constant shape superimposed on a constant soft blackbody component. These variability patterns are in agreement with the dependence of the rms variability on the photon energy in the two states. We interpret the observed correlations in terms of theoretical Comptonization models. In the hard state, the variability appears to be driven mostly by changing flux in seed photons Comptonized in a hot thermal plasma cloud with an approximately constant power supply. In the soft state, the variability is consistent with flares of hybrid, thermal/nonthermal, plasma with variable power above a stable cold disk. Also, based on broadband pointed observations simultaneous with those of the ASM and BATSE, we find the intrinsic bolometric luminosity increases by a factor of approximately 3-4 from the hard state to the soft one, which supports models of the state transition based on a change of the accretion rate.

A waste characterisation procedure for ADM1 implementation based on degradation kinetics.

PubMed

Girault, R; Bridoux, G; Nauleau, F; Poullain, C; Buffet, J; Steyer, J-P; Sadowski, A G; Béline, F

2012-09-01

In this study, a procedure accounting for degradation kinetics was developed to split the total COD of a substrate into each input state variable required for Anaerobic Digestion Model n°1. The procedure is based on the combination of batch experimental degradation tests ("anaerobic respirometry") and numerical interpretation of the results obtained (optimisation of the ADM1 input state variable set). The effects of the main operating parameters, such as the substrate to inoculum ratio in batch experiments and the origin of the inoculum, were investigated. Combined with biochemical fractionation of the total COD of substrates, this method enabled determination of an ADM1-consistent input state variable set for each substrate with affordable identifiability. The substrate to inoculum ratio in the batch experiments and the origin of the inoculum influenced input state variables. However, based on results modelled for a CSTR fed with the substrate concerned, these effects were not significant. Indeed, if the optimal ranges of these operational parameters are respected, uncertainty in COD fractionation is mainly limited to temporal variability of the properties of the substrates. As the method is based on kinetics and is easy to implement for a wide range of substrates, it is a very promising way to numerically predict the effect of design parameters on the efficiency of an anaerobic CSTR. This method thus promotes the use of modelling for the design and optimisation of anaerobic processes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Latent variable method for automatic adaptation to background states in motor imagery BCI

NASA Astrophysics Data System (ADS)

Dagaev, Nikolay; Volkova, Ksenia; Ossadtchi, Alexei

2018-02-01

Objective. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. Approach. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model’s parameters, we suggest to use the expectation maximization algorithm. The proposed method is aimed at assessing characteristics of background states without any corresponding data labeling. In the context of asynchronous motor imagery paradigm, we applied this method to the real data from twelve able-bodied subjects with open/closed eyes serving as background states. Main results. We found that the latent variable method improved classification of target states compared to the baseline method (in seven of twelve subjects). In addition, we found that our method was also capable of background states recognition (in six of twelve subjects). Significance. Without any supervised information on background states, the latent variable method provides a way to improve classification in BCI by taking background states into account at the training stage and then by making decisions on target states weighted by posterior probabilities of background states at the prediction stage.

Computational Implementation of a Thermodynamically Based Work Potential Model For Progressive Microdamage and Transverse Cracking in Fiber-Reinforced Laminates

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Bednarcyk, Brett A.; Collier, Craig S.

2012-01-01

A continuum-level, dual internal state variable, thermodynamically based, work potential model, Schapery Theory, is used capture the effects of two matrix damage mechanisms in a fiber-reinforced laminated composite: microdamage and transverse cracking. Matrix microdamage accrues primarily in the form of shear microcracks between the fibers of the composite. Whereas, larger transverse matrix cracks typically span the thickness of a lamina and run parallel to the fibers. Schapery Theory uses the energy potential required to advance structural changes, associated with the damage mechanisms, to govern damage growth through a set of internal state variables. These state variables are used to quantify the stiffness degradation resulting from damage growth. The transverse and shear stiffness of the lamina are related to the internal state variables through a set of measurable damage functions. Additionally, the damage variables for a given strain state can be calculated from a set of evolution equations. These evolution equations and damage functions are implemented into the finite element method and used to govern the constitutive response of the material points in the model. Additionally, an axial failure criterion is included in the model. The response of a center-notched, buffer strip-stiffened panel subjected to uniaxial tension is investigated and results are compared to experiment.

I-States-as-Objects-Analysis (ISOA): Extensions of an Approach to Studying Short-Term Developmental Processes by Analyzing Typical Patterns

ERIC Educational Resources Information Center

Bergman, Lars R.; Nurmi, Jari-Erik; von Eye, Alexander A.

2012-01-01

I-states-as-objects-analysis (ISOA) is a person-oriented methodology for studying short-term developmental stability and change in patterns of variable values. ISOA is based on longitudinal data with the same set of variables measured at all measurement occasions. A key concept is the "i-state," defined as a person's pattern of variable…

Determination of continuous variable entanglement by purity measurements.

PubMed

Adesso, Gerardo; Serafini, Alessio; Illuminati, Fabrizio

2004-02-27

We classify the entanglement of two-mode Gaussian states according to their degree of total and partial mixedness. We derive exact bounds that determine maximally and minimally entangled states for fixed global and marginal purities. This characterization allows for an experimentally reliable estimate of continuous variable entanglement based on measurements of purity.

Variability of wildland fire emissions across the contiguous United States

Treesearch

YongQiang Liu

2004-01-01

This study analyzes spatial and temporal variability of emissions from wildland fires across the contiguous US. The emissions are estimates based on a recently constructed dataset of historical fire records collected by multiple US governlnental agencies. Both wildfire and prescribed fires have the highest emissions over the Pacific coastal states. Prescribed fire...

Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2003-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.

Continuous-variable quantum network coding for coherent states

NASA Astrophysics Data System (ADS)

Shang, Tao; Li, Ke; Liu, Jian-wei

2017-04-01

As far as the spectral characteristic of quantum information is concerned, the existing quantum network coding schemes can be looked on as the discrete-variable quantum network coding schemes. Considering the practical advantage of continuous variables, in this paper, we explore two feasible continuous-variable quantum network coding (CVQNC) schemes. Basic operations and CVQNC schemes are both provided. The first scheme is based on Gaussian cloning and ADD/SUB operators and can transmit two coherent states across with a fidelity of 1/2, while the second scheme utilizes continuous-variable quantum teleportation and can transmit two coherent states perfectly. By encoding classical information on quantum states, quantum network coding schemes can be utilized to transmit classical information. Scheme analysis shows that compared with the discrete-variable paradigms, the proposed CVQNC schemes provide better network throughput from the viewpoint of classical information transmission. By modulating the amplitude and phase quadratures of coherent states with classical characters, the first scheme and the second scheme can transmit 4{log _2}N and 2{log _2}N bits of information by a single network use, respectively.

Multivariate localization methods for ensemble Kalman filtering

NASA Astrophysics Data System (ADS)

Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

2015-12-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Inter-model Diversity of ENSO simulation and its relation to basic states

NASA Astrophysics Data System (ADS)

Kug, J. S.; Ham, Y. G.

2016-12-01

In this study, a new methodology is developed to improve the climate simulation of state-of-the-art coupledglobal climate models (GCMs), by a postprocessing based on the intermodel diversity. Based on the closeconnection between the interannual variability and climatological states, the distinctive relation between theintermodel diversity of the interannual variability and that of the basic state is found. Based on this relation,the simulated interannual variabilities can be improved, by correcting their climatological bias. To test thismethodology, the dominant intermodel difference in precipitation responses during El Niño-SouthernOscillation (ENSO) is investigated, and its relationship with climatological state. It is found that the dominantintermodel diversity of the ENSO precipitation in phase 5 of the Coupled Model Intercomparison Project(CMIP5) is associated with the zonal shift of the positive precipitation center during El Niño. This dominantintermodel difference is significantly correlated with the basic states. The models with wetter (dryer) climatologythan the climatology of the multimodel ensemble (MME) over the central Pacific tend to shift positiveENSO precipitation anomalies to the east (west). Based on the model's systematic errors in atmosphericENSO response and bias, the models with better climatological state tend to simulate more realistic atmosphericENSO responses.Therefore, the statistical method to correct the ENSO response mostly improves the ENSO response. Afterthe statistical correction, simulating quality of theMMEENSO precipitation is distinctively improved. Theseresults provide a possibility that the present methodology can be also applied to improving climate projectionand seasonal climate prediction.

Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2003-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satisfied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.

Electrochemical state and internal variables estimation using a reduced-order physics-based model of a lithium-ion cell and an extended Kalman filter

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

Stetzel, KD; Aldrich, LL; Trimboli, MS

2015-03-15

This paper addresses the problem of estimating the present value of electrochemical internal variables in a lithium-ion cell in real time, using readily available measurements of cell voltage, current, and temperature. The variables that can be estimated include any desired set of reaction flux and solid and electrolyte potentials and concentrations at any set of one-dimensional spatial locations, in addition to more standard quantities such as state of charge. The method uses an extended Kalman filter along with a one-dimensional physics-based reduced-order model of cell dynamics. Simulations show excellent and robust predictions having dependable error bounds for most internal variables.more » (C) 2014 Elsevier B.V. All rights reserved.« less

Implementation of continuous-variable quantum key distribution with composable and one-sided-device-independent security against coherent attacks.

PubMed

Gehring, Tobias; Händchen, Vitus; Duhme, Jörg; Furrer, Fabian; Franz, Torsten; Pacher, Christoph; Werner, Reinhard F; Schnabel, Roman

2015-10-30

Secret communication over public channels is one of the central pillars of a modern information society. Using quantum key distribution this is achieved without relying on the hardness of mathematical problems, which might be compromised by improved algorithms or by future quantum computers. State-of-the-art quantum key distribution requires composable security against coherent attacks for a finite number of distributed quantum states as well as robustness against implementation side channels. Here we present an implementation of continuous-variable quantum key distribution satisfying these requirements. Our implementation is based on the distribution of continuous-variable Einstein-Podolsky-Rosen entangled light. It is one-sided device independent, which means the security of the generated key is independent of any memoryfree attacks on the remote detector. Since continuous-variable encoding is compatible with conventional optical communication technology, our work is a step towards practical implementations of quantum key distribution with state-of-the-art security based solely on telecom components.

Implementation of continuous-variable quantum key distribution with composable and one-sided-device-independent security against coherent attacks

PubMed Central

Gehring, Tobias; Händchen, Vitus; Duhme, Jörg; Furrer, Fabian; Franz, Torsten; Pacher, Christoph; Werner, Reinhard F.; Schnabel, Roman

2015-01-01

Secret communication over public channels is one of the central pillars of a modern information society. Using quantum key distribution this is achieved without relying on the hardness of mathematical problems, which might be compromised by improved algorithms or by future quantum computers. State-of-the-art quantum key distribution requires composable security against coherent attacks for a finite number of distributed quantum states as well as robustness against implementation side channels. Here we present an implementation of continuous-variable quantum key distribution satisfying these requirements. Our implementation is based on the distribution of continuous-variable Einstein–Podolsky–Rosen entangled light. It is one-sided device independent, which means the security of the generated key is independent of any memoryfree attacks on the remote detector. Since continuous-variable encoding is compatible with conventional optical communication technology, our work is a step towards practical implementations of quantum key distribution with state-of-the-art security based solely on telecom components. PMID:26514280

A Proposal for Testing Local Realism Without Using Assumptions Related to Hidden Variable States

NASA Technical Reports Server (NTRS)

Ryff, Luiz Carlos

1996-01-01

A feasible experiment is discussed which allows us to prove a Bell's theorem for two particles without using an inequality. The experiment could be used to test local realism against quantum mechanics without the introduction of additional assumptions related to hidden variables states. Only assumptions based on direct experimental observation are needed.

Gate sequence for continuous variable one-way quantum computation

PubMed Central

Su, Xiaolong; Hao, Shuhong; Deng, Xiaowei; Ma, Lingyu; Wang, Meihong; Jia, Xiaojun; Xie, Changde; Peng, Kunchi

2013-01-01

Measurement-based one-way quantum computation using cluster states as resources provides an efficient model to perform computation and information processing of quantum codes. Arbitrary Gaussian quantum computation can be implemented sufficiently by long single-mode and two-mode gate sequences. However, continuous variable gate sequences have not been realized so far due to an absence of cluster states larger than four submodes. Here we present the first continuous variable gate sequence consisting of a single-mode squeezing gate and a two-mode controlled-phase gate based on a six-mode cluster state. The quantum property of this gate sequence is confirmed by the fidelities and the quantum entanglement of two output modes, which depend on both the squeezing and controlled-phase gates. The experiment demonstrates the feasibility of implementing Gaussian quantum computation by means of accessible gate sequences.

Mind wandering at the fingertips: automatic parsing of subjective states based on response time variability

PubMed Central

Bastian, Mikaël; Sackur, Jérôme

2013-01-01

Research from the last decade has successfully used two kinds of thought reports in order to assess whether the mind is wandering: random thought-probes and spontaneous reports. However, none of these two methods allows any assessment of the subjective state of the participant between two reports. In this paper, we present a step by step elaboration and testing of a continuous index, based on response time variability within Sustained Attention to Response Tasks (N = 106, for a total of 10 conditions). We first show that increased response time variability predicts mind wandering. We then compute a continuous index of response time variability throughout full experiments and show that the temporal position of a probe relative to the nearest local peak of the continuous index is predictive of mind wandering. This suggests that our index carries information about the subjective state of the subject even when he or she is not probed, and opens the way for on-line tracking of mind wandering. Finally we proceed a step further and infer the internal attentional states on the basis of the variability of response times. To this end we use the Hidden Markov Model framework, which allows us to estimate the durations of on-task and off-task episodes. PMID:24046753

Ontology and modeling patterns for state-based behavior representation

NASA Technical Reports Server (NTRS)

Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.;

Mechanistic materials modeling for nuclear fuel performance

DOE PAGES

Tonks, Michael R.; Andersson, David; Phillpot, Simon R.; ...

2017-03-15

Fuel performance codes are critical tools for the design, certification, and safety analysis of nuclear reactors. However, their ability to predict fuel behavior under abnormal conditions is severely limited by their considerable reliance on empirical materials models correlated to burn-up (a measure of the number of fission events that have occurred, but not a unique measure of the history of the material). In this paper, we propose a different paradigm for fuel performance codes to employ mechanistic materials models that are based on the current state of the evolving microstructure rather than burn-up. In this approach, a series of statemore » variables are stored at material points and define the current state of the microstructure. The evolution of these state variables is defined by mechanistic models that are functions of fuel conditions and other state variables. The material properties of the fuel and cladding are determined from microstructure/property relationships that are functions of the state variables and the current fuel conditions. Multiscale modeling and simulation is being used in conjunction with experimental data to inform the development of these models. Finally, this mechanistic, microstructure-based approach has the potential to provide a more predictive fuel performance capability, but will require a team of researchers to complete the required development and to validate the approach.« less

A special protection scheme utilizing trajectory sensitivity analysis in power transmission

NASA Astrophysics Data System (ADS)

Suriyamongkol, Dan

In recent years, new measurement techniques have provided opportunities to improve the North American Power System observability, control and protection. This dissertation discusses the formulation and design of a special protection scheme based on a novel utilization of trajectory sensitivity techniques with inputs consisting of system state variables and parameters. Trajectory sensitivity analysis (TSA) has been used in previous publications as a method for power system security and stability assessment, and the mathematical formulation of TSA lends itself well to some of the time domain power system simulation techniques. Existing special protection schemes often have limited sets of goals and control actions. The proposed scheme aims to maintain stability while using as many control actions as possible. The approach here will use the TSA in a novel way by using the sensitivities of system state variables with respect to state parameter variations to determine the state parameter controls required to achieve the desired state variable movements. The initial application will operate based on the assumption that the modeled power system has full system observability, and practical considerations will be discussed.

Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2006-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters (e.g., the projection approach to constrained filtering).

Analysis of watershed topography effects on summer precipitation variability in the southwestern United States

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, Dagbegnon C.; Singh, Vijay P.; Frauenfeld, Oliver W.

2014-04-01

With climate change, precipitation variability is projected to increase. The present study investigates the potential interactions between watershed characteristics and precipitation variability. The watershed is considered as a functional unit that may impact seasonal precipitation. The study uses historical precipitation data from 370 meteorological stations over the last five decades, and digital elevation data from regional watersheds in the southwestern United States. This domain is part of the North American Monsoon region, and the summer period (June-July-August, JJA) was considered. Based on an initial analysis for 1895-2011, the JJA precipitation accounts, on average, for 22-43% of the total annual precipitation, with higher percentages in the arid part of the region. The unique contribution of this research is that entropy theory is used to address precipitation variability in time and space. An entropy-based disorder index was computed for each station's precipitation record. The JJA total precipitation and number of precipitation events were considered in the analysis. The precipitation variability potentially induced by watershed topography was investigated using spatial regionalization combining principal component and cluster analysis. It was found that the disorder in precipitation total and number of events tended to be higher in arid regions. The spatial pattern showed that the entropy-based variability in precipitation amount and number of events gradually increased from east to west in the southwestern United States. Regarding the watershed topography influence on summer precipitation patterns, hilly relief has a stabilizing effect on seasonal precipitation variability in time and space. The results show the necessity to include watershed topography in global and regional climate model parameterizations.

Hierarchical Synthesis of Coastal Ecosystem Health Indicators at Karimunjawa National Marine Park

NASA Astrophysics Data System (ADS)

Danu Prasetya, Johan; Ambariyanto; Supriharyono; Purwanti, Frida

2018-02-01

The coastal ecosystem of Karimunjawa National Marine Park (KNMP) is facing various pressures, including from human activity. Monitoring the health condition of coastal ecosystems periodically is needed as an evaluation of the ecosystem condition. Systematic and consistent indicators are needed in monitoring of coastal ecosystem health. This paper presents hierarchical synthesis of coastal ecosystem health indicators using Analytic Hierarchy Process (AHP) method. Hierarchical synthesis is obtained from process of weighting by paired comparison based on expert judgments. The variables of coastal ecosystem health indicators in this synthesis consist of 3 level of variable, i.e. main variable, sub-variable and operational variable. As a result of assessment, coastal ecosystem health indicators consist of 3 main variables, i.e. State of Ecosystem, Pressure and Management. Main variables State of Ecosystem and Management obtain the same value i.e. 0.400, while Pressure value was 0.200. Each main variable consist of several sub-variable, i.e. coral reef, reef fish, mangrove and seagrass for State of Ecosystem; fisheries and marine tourism activity for Pressure; planning and regulation, institutional and also infrastructure and financing for Management. The highest value of sub-variable of main variable State of Ecosystem, Pressure and Management were coral reef (0.186); marine tourism pressure (0.133) and institutional (0.171), respectively. The highest value of operational variable of main variable State of Ecosystem, Pressure and Management were percent of coral cover (0.058), marine tourism pressure (0.133) and presence of zonation plan, regulation also socialization of monitoring program (0.53), respectively. Potential pressure from marine tourism activity is the variable that most affect the health of the ecosystem. The results of this research suggest that there is a need to develop stronger conservation strategies to facing with pressures from marine tourism activities.

Continuous variable quantum key distribution with modulated entangled states.

PubMed

Madsen, Lars S; Usenko, Vladyslav C; Lassen, Mikael; Filip, Radim; Andersen, Ulrik L

2012-01-01

Quantum key distribution enables two remote parties to grow a shared key, which they can use for unconditionally secure communication over a certain distance. The maximal distance depends on the loss and the excess noise of the connecting quantum channel. Several quantum key distribution schemes based on coherent states and continuous variable measurements are resilient to high loss in the channel, but are strongly affected by small amounts of channel excess noise. Here we propose and experimentally address a continuous variable quantum key distribution protocol that uses modulated fragile entangled states of light to greatly enhance the robustness to channel noise. We experimentally demonstrate that the resulting quantum key distribution protocol can tolerate more noise than the benchmark set by the ideal continuous variable coherent state protocol. Our scheme represents a very promising avenue for extending the distance for which secure communication is possible.

State variable modeling of the integrated engine and aircraft dynamics

NASA Astrophysics Data System (ADS)

Rotaru, Constantin; Sprinţu, Iuliana

2014-12-01

This study explores the dynamic characteristics of the combined aircraft-engine system, based on the general theory of the state variables for linear and nonlinear systems, with details leading first to the separate formulation of the longitudinal and the lateral directional state variable models, followed by the merging of the aircraft and engine models into a single state variable model. The linearized equations were expressed in a matrix form and the engine dynamics was included in terms of variation of thrust following a deflection of the throttle. The linear model of the shaft dynamics for a two-spool jet engine was derived by extending the one-spool model. The results include the discussion of the thrust effect upon the aircraft response when the thrust force associated with the engine has a sizable moment arm with respect to the aircraft center of gravity for creating a compensating moment.

Variability and Limits of US State Laws Regulating Workplace Wellness Programs.

PubMed

Pomeranz, Jennifer L; Garcia, Andrea M; Vesprey, Randy; Davey, Adam

2016-06-01

We examined variability in state laws related to workplace wellness programs for public and private employers. We conducted legal research using LexisNexis and Westlaw to create a master list of US state laws that existed in 2014 dedicated to workplace wellness programs. The master list was then divided into laws focusing on public employers and private employers. We created 2 codebooks to describe the variables used to examine the laws. Coders used LawAtlas(SM) Workbench to code the laws related to workplace wellness programs. Thirty-two states and the District of Columbia had laws related to workplace wellness programs in 2014. Sixteen states and the District of Columbia had laws dedicated to public employers, and 16 states had laws dedicated to private employers. Nine states and the District of Columbia had laws that did not specify employer type. State laws varied greatly in their methods of encouraging or shaping wellness program requirements. Few states have comprehensive requirements or incentives to support evidence-based workplace wellness programs.

General constraints on sampling wildlife on FIA plots

USGS Publications Warehouse

Bailey, L.L.; Sauer, J.R.; Nichols, J.D.; Geissler, P.H.; McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H.; Cieszewski, Chris J.

2005-01-01

This paper reviews the constraints to sampling wildlife populations at FIA points. Wildlife sampling programs must have well-defined goals and provide information adequate to meet those goals. Investigators should choose a State variable based on information needs and the spatial sampling scale. We discuss estimation-based methods for three State variables: species richness, abundance, and patch occupancy. All methods incorporate two essential sources of variation: detectability estimation and spatial variation. FIA sampling imposes specific space and time criteria that may need to be adjusted to meet local wildlife objectives.

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

PubMed

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate). Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

State Budgetary Assumptions. State Fiscal Brief No. 36.

ERIC Educational Resources Information Center

Boyd, Donald J.; Davis, Elizabeth I.

When states prepare their budgets, they usually base revenue and expenditure projections upon forecasts of national and state economic and demographic trends. This brief presents findings of a Center for the Study of the States survey that asked state budget offices what they were assuming for many key variables. The survey obtained 41 state…

Exploratory reconstructability analysis of accident TBI data

NASA Astrophysics Data System (ADS)

Zwick, Martin; Carney, Nancy; Nettleton, Rosemary

2018-02-01

This paper describes the use of reconstructability analysis to perform a secondary study of traumatic brain injury data from automobile accidents. Neutral searches were done and their results displayed with a hypergraph. Directed searches, using both variable-based and state-based models, were applied to predict performance on two cognitive tests and one neurological test. Very simple state-based models gave large uncertainty reductions for all three DVs and sizeable improvements in percent correct for the two cognitive test DVs which were equally sampled. Conditional probability distributions for these models are easily visualized with simple decision trees. Confounding variables and counter-intuitive findings are also reported.

An audience research study to disseminate evidence about comprehensive state mental health parity legislation to US State policymakers: protocol.

PubMed

Purtle, Jonathan; Lê-Scherban, Félice; Shattuck, Paul; Proctor, Enola K; Brownson, Ross C

2017-06-26

A large proportion of the US population has limited access to mental health treatments because insurance providers limit the utilization of mental health services in ways that are more restrictive than for physical health services. Comprehensive state mental health parity legislation (C-SMHPL) is an evidence-based policy intervention that enhances mental health insurance coverage and improves access to care. Implementation of C-SMHPL, however, is limited. State policymakers have the exclusive authority to implement C-SMHPL, but sparse guidance exists to inform the design of strategies to disseminate evidence about C-SMHPL, and more broadly, evidence-based treatments and mental illness, to this audience. The aims of this exploratory audience research study are to (1) characterize US State policymakers' knowledge and attitudes about C-SMHPL and identify individual- and state-level attributes associated with support for C-SMHPL; and (2) integrate quantitative and qualitative data to develop a conceptual framework to disseminate evidence about C-SMHPL, evidence-based treatments, and mental illness to US State policymakers. The study uses a multi-level (policymaker, state), mixed method (QUAN→qual) approach and is guided by Kingdon's Multiple Streams Framework, adapted to incorporate constructs from Aarons' Model of Evidence-Based Implementation in Public Sectors. A multi-modal survey (telephone, post-mail, e-mail) of 600 US State policymakers (500 legislative, 100 administrative) will be conducted and responses will be linked to state-level variables. The survey will span domains such as support for C-SMHPL, knowledge and attitudes about C-SMHPL and evidence-based treatments, mental illness stigma, and research dissemination preferences. State-level variables will measure factors associated with C-SMHPL implementation, such as economic climate and political environment. Multi-level regression will determine the relative strength of individual- and state-level variables on policymaker support for C-SMHPL. Informed by survey results, semi-structured interviews will be conducted with approximately 50 US State policymakers to elaborate upon quantitative findings. Then, using a systematic process, quantitative and qualitative data will be integrated and a US State policymaker-focused C-SMHPL dissemination framework will be developed. Study results will provide the foundation for hypothesis-driven, experimental studies testing the effects of different dissemination strategies on state policymakers' support for, and implementation of, evidence-based mental health policy interventions.

The Impact of ENSO on Extratropical Low Frequency Noise in Seasonal Forecasts

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Suarez, Max J.; Chang, Yehui; Branstator, Grant

2000-01-01

This study examines the uncertainty in forecasts of the January-February-March (JFM) mean extratropical circulation, and how that uncertainty is modulated by the El Nino/Southern Oscillation (ENSO). The analysis is based on ensembles of hindcasts made with an Atmospheric General Circulation Model (AGCM) forced with sea surface temperatures observed during; the 1983 El Nino and 1989 La Nina events. The AGCM produces pronounced interannual differences in the magnitude of the extratropical seasonal mean noise (intra-ensemble variability). The North Pacific, in particular, shows extensive regions where the 1989 seasonal mean noise kinetic energy (SKE), which is dominated by a "PNA-like" spatial structure, is more than twice that of the 1983 forecasts. The larger SKE in 1989 is associated with a larger than normal barotropic conversion of kinetic energy from the mean Pacific jet to the seasonal mean noise. The generation of SKE due to sub-monthly transients also shows substantial interannual differences, though these are much smaller than the differences in the mean flow conversions. An analysis of the Generation of monthly mean noise kinetic energy (NIKE) and its variability suggests that the seasonal mean noise is predominantly a statistical residue of variability resulting from dynamical processes operating on monthly and shorter times scales. A stochastically-forced barotropic model (linearized about the AGCM's 1983 and 1989 base states) is used to further assess the role of the basic state, submonthly transients, and tropical forcing, in modulating the uncertainties in the seasonal AGCM forecasts. When forced globally with spatially-white noise, the linear model generates much larger variance for the 1989 base state, consistent with the AGCM results. The extratropical variability for the 1989 base state is dominanted by a single eigenmode, and is strongly coupled with forcing over tropical western Pacific and the Indian Ocean, again consistent with the AGCM results. Linear calculations that include forcing from the AGCM variance of the tropical forcing and submonthly transients show a small impact on the variability over the Pacific/North American region compared with that of the base state differences.

CLIMATIC DATA ON ESTIMATED EFFECTIVE CHIMNEY HEIGHTS IN THE UNITED STATES

EPA Science Inventory

Plume rise calculations are based on the equations of Briggs (1975) for use with variable vertical profiles of temperature and wind speed. Results are presented for small and large chimneys, based on five years of twice-daily rawinsondes throughout the contiguous United States. I...

Vietnamese Americans' Attitudes toward Seeking Mental Health Services: Relation to Cultural Variables

ERIC Educational Resources Information Center

Nguyen, Quang Charles X.; Anderson, Louis P.

2005-01-01

This study examined the relation between culturally based variables and attitudes toward seeking mental health services among a community sample of Vietnamese Americans (N = 148) with at least 8 years' residence in the United States (U.S.). Variables included Stigma, Traditional Beliefs about Mental Illness, Help-Seeking Preferences, Problem…

Remote sensing of rangeland biodiversity

USDA-ARS?s Scientific Manuscript database

Rangelands are managed based on state and transition models for an ecological site. Transitions to alternative ecological states are indicative of degrading rangelands. Three key variables may be remotely sensed to detect transitions between alternative states: amount of bare soil, presence of inva...

Online Estimation of Model Parameters of Lithium-Ion Battery Using the Cubature Kalman Filter

NASA Astrophysics Data System (ADS)

Tian, Yong; Yan, Rusheng; Tian, Jindong; Zhou, Shijie; Hu, Chao

2017-11-01

Online estimation of state variables, including state-of-charge (SOC), state-of-energy (SOE) and state-of-health (SOH) is greatly crucial for the operation safety of lithium-ion battery. In order to improve estimation accuracy of these state variables, a precise battery model needs to be established. As the lithium-ion battery is a nonlinear time-varying system, the model parameters significantly vary with many factors, such as ambient temperature, discharge rate and depth of discharge, etc. This paper presents an online estimation method of model parameters for lithium-ion battery based on the cubature Kalman filter. The commonly used first-order resistor-capacitor equivalent circuit model is selected as the battery model, based on which the model parameters are estimated online. Experimental results show that the presented method can accurately track the parameters variation at different scenarios.

A viscoplastic model with application to LiF-22 percent CaF2 hypereutectic salt

NASA Technical Reports Server (NTRS)

Freed, A. D.; Walker, K. P.

1990-01-01

A viscoplastic model for class M (metal-like behavior) materials is presented. One novel feature is its use of internal variables to change the stress exponent of creep (where n is approximately = 5) to that of natural creep (where n = 3), in accordance with experimental observations. Another feature is the introduction of a coupling in the evolution equations of the kinematic and isotropic internal variables, making thermal recovery of the kinematic variable implicit. These features enable the viscoplastic model to reduce to that of steady-state creep in closed form. In addition, the hardening parameters associated with the two internal state variables (one scalar-valued, the other tensor-valued) are considered to be functions of state, instead of being taken as constant-valued. This feature enables each internal variable to represent a much wider spectrum of internal states for the material. The model is applied to a LiF-22 percent CaF2 hypereutectic salt, which is being considered as a thermal energy storage material for space-based solar dynamic power systems.

Anisotropic constitutive modeling for nickel base single crystal superalloys using a crystallographic approach

NASA Technical Reports Server (NTRS)

Stouffer, D. C.; Sheh, M. Y.

1988-01-01

A micromechanical model based on crystallographic slip theory was formulated for nickel-base single crystal superalloys. The current equations include both drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments have been conducted to evaluate the effect of back stress in single crystals. The results showed that (1) the back stress is orientation dependent; and (2) the back stress state variable in the inelastic flow equation is necessary for predicting anelastic behavior of the material. The model also demonstrated improved fatigue predictive capability. Model predictions and experimental data are presented for single crystal superalloy Rene N4 at 982 C.

Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

NASA Astrophysics Data System (ADS)

Chou, Chien-Ming; Wang, Ru-Yih

2004-04-01

This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

Continuous-Variable Measurement-Device-Independent Multipartite Quantum Communication Using Coherent States

NASA Astrophysics Data System (ADS)

Zhou, Jian; Guo, Ying

2017-02-01

A continuous-variable measurement-device-independent (CV-MDI) multipartite quantum communication protocol is designed to realize multipartite communication based on the GHZ state analysis using Gaussian coherent states. It can remove detector side attack as the multi-mode measurement is blindly done in a suitable Black Box. The entanglement-based CV-MDI multipartite communication scheme and the equivalent prepare-and-measurement scheme are proposed to analyze the security and guide experiment, respectively. The general eavesdropping and coherent attack are considered for the security analysis. Subsequently, all the attacks are ascribed to coherent attack against imperfect links. The asymptotic key rate of the asymmetric configuration is also derived with the numeric simulations illustrating the performance of the proposed protocol.

Remote sensing using MIMO systems

DOEpatents

Bikhazi, Nicolas; Young, William F; Nguyen, Hung D

2015-04-28

A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.

Variability of tornado occurrence over the continental United States since 1950

NASA Astrophysics Data System (ADS)

Guo, Li; Wang, Kaicun; Bluestein, Howard B.

2016-06-01

The United States experiences the most tornadoes of any country in the world. Given the catastrophic impact of tornadoes, concern has arisen regarding the variation in climatology of U.S. tornadoes under the changing climate. A recent study claimed that the temporal variability of tornado occurrence over the continental U.S. has increased since the 1970s. However, that study ignored the highly regionalized climatology of U.S. tornadoes. To address this issue, we examined the long-term trend of tornado temporal variability in each continental U.S. state. Based on the 64 year tornado records (1950-2013), we found that the trends in tornado temporal variability varied across the U.S., with only one third of the continental area or three out of 10 contiguous states (mostly from the Great Plains and Southeast, but where the frequency of occurrence of tornadoes is greater) displaying a significantly increasing trend. The other two-thirds area, where 60% of the U.S. tornadoes were reported (but the frequency of occurrence of tornadoes is less), however, showed a decreasing or a near-zero trend in tornado temporal variability. Furthermore, unlike the temporal variability alone, the combined spatial-temporal variability of U.S. tornado occurrence has remained nearly constant since 1950. Such detailed information on the climatological variability of U.S. tornadoes refines the claim of previous study and can be helpful for local mitigation efforts toward future tornado risks.

Modelling multiple cycles of static and dynamic recrystallisation using a fully implicit isotropic material model based on dislocation density

NASA Astrophysics Data System (ADS)

Jansen van Rensburg, Gerhardus J.; Kok, Schalk; Wilke, Daniel N.

2018-03-01

This paper presents the development and numerical implementation of a state variable based thermomechanical material model, intended for use within a fully implicit finite element formulation. Plastic hardening, thermal recovery and multiple cycles of recrystallisation can be tracked for single peak as well as multiple peak recrystallisation response. The numerical implementation of the state variable model extends on a J2 isotropic hypo-elastoplastic modelling framework. The complete numerical implementation is presented as an Abaqus UMAT and linked subroutines. Implementation is discussed with detailed explanation of the derivation and use of various sensitivities, internal state variable management and multiple recrystallisation cycle contributions. A flow chart explaining the proposed numerical implementation is provided as well as verification on the convergence of the material subroutine. The material model is characterised using two high temperature data sets for cobalt and copper. The results of finite element analyses using the material parameter values characterised on the copper data set are also presented.

State Variability in Supply of Office-based Primary Care Providers: United States, 2012

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

[The functional state classification and evaluation of the stability level in mental loads based on the factor structure of heart rate variability parameters].

PubMed

Mashin, V A; Mashina, M N

2004-12-01

In the paper, outcomes of the researches devoted to factor analysis of heart rate variability parameters and definition of the most informative parameters for diagnostics of functional states and an evaluation of level of stability to mental loads, are presented. The factor structure of parameters, which unclude integral level of heart rate variability (1), balance between activity of vagus and brain cortical-limbic systems (2), integrated level of cardiovascular system functioning (3), is substantiated. Factor analysis outcomes have been used for construction of functional state classification, for their differential diagnostics, and for development and check of algorithm for evaluation of the stability level in mental loads.

State variable theories based on Hart's formulation

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

Korhonen, M.A.; Hannula, S.P.; Li, C.Y.

In this paper a review of the development of a state variable theory for nonelastic deformation is given. The physical and phenomenological basis of the theory and the constitutive equations describing macroplastic, microplastic, anelastic and grain boundary sliding enhanced deformation are presented. The experimental and analytical evaluation of different parameters in the constitutive equations are described in detail followed by a review of the extensive experimental work on different materials. The technological aspects of the state variable approach are highlighted by examples of the simulative and predictive capabilities of the theory. Finally, a discussion of general capabilities, limitations and futuremore » developments of the theory and particularly the possible extensions to cover an even wider range of deformation or deformation-related phenomena is presented.« less

Multi-Particle Interferometry Based on Double Entangled States

NASA Technical Reports Server (NTRS)

Pittman, Todd B.; Shih, Y. H.; Strekalov, D. V.; Sergienko, A. V.; Rubin, M. H.

1996-01-01

A method for producing a 4-photon entangled state based on the use of two independent pair sources is discussed. Of particular interest is that each of the pair sources produces a two-photon state which is simultaneously entangled in both polarization and space-time variables. Performing certain measurements which exploit this double entanglement provides an opportunity for verifying the recent demonstration of nonlocality by Greenberger, Horne, and Zeilinger.

Criteria for genuine N -partite continuous-variable entanglement and Einstein-Podolsky-Rosen steering

NASA Astrophysics Data System (ADS)

Teh, R. Y.; Reid, M. D.

2014-12-01

Following previous work, we distinguish between genuine N -partite entanglement and full N -partite inseparability. Accordingly, we derive criteria to detect genuine multipartite entanglement using continuous-variable (position and momentum) measurements. Our criteria are similar but different to those based on the van Loock-Furusawa inequalities, which detect full N -partite inseparability. We explain how the criteria can be used to detect the genuine N -partite entanglement of continuous variable states generated from squeezed and vacuum state inputs, including the continuous-variable Greenberger-Horne-Zeilinger state, with explicit predictions for up to N =9 . This makes our work accessible to experiment. For N =3 , we also present criteria for tripartite Einstein-Podolsky-Rosen (EPR) steering. These criteria provide a means to demonstrate a genuine three-party EPR paradox, in which any single party is steerable by the remaining two parties.

Environmental variability, historical contingency, and the structure of regional fish and macroinvertebrate faunas in Ouachita Mountain stream systems

Treesearch

Lance R. Williams; Christopher M. Taylor; Melvin L. Warren; J. Alan Clingenpeel

2003-01-01

In 1990-1992, the United States Forest Service sampled six hydrologically variable streams paired in three different drainage basins in the Ouachita Mountains, Arkansas, U.S.A. Fishes, macroinvertebrates, and stream environmental variables were quantified for each stream. We used these data to examine the relationship between regional faunas (based on taxonomy and...

Interannual variability of ammonia concentrations over the United States: sources and implications

NASA Astrophysics Data System (ADS)

Schiferl, Luke D.; Heald, Colette L.; Van Damme, Martin; Clarisse, Lieven; Clerbaux, Cathy; Coheur, Pierre-François; Nowak, John B.; Neuman, J. Andrew; Herndon, Scott C.; Roscioli, Joseph R.; Eilerman, Scott J.

2016-09-01

The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008-2012). We find that the model generally underrepresents the ammonia concentration near large source regions (by 26 % at surface sites) and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. This work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

Anonymous voting for multi-dimensional CV quantum system

NASA Astrophysics Data System (ADS)

Rong-Hua, Shi; Yi, Xiao; Jin-Jing, Shi; Ying, Guo; Moon-Ho, Lee

2016-06-01

We investigate the design of anonymous voting protocols, CV-based binary-valued ballot and CV-based multi-valued ballot with continuous variables (CV) in a multi-dimensional quantum cryptosystem to ensure the security of voting procedure and data privacy. The quantum entangled states are employed in the continuous variable quantum system to carry the voting information and assist information transmission, which takes the advantage of the GHZ-like states in terms of improving the utilization of quantum states by decreasing the number of required quantum states. It provides a potential approach to achieve the efficient quantum anonymous voting with high transmission security, especially in large-scale votes. Project supported by the National Natural Science Foundation of China (Grant Nos. 61272495, 61379153, and 61401519), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130162110012), and the MEST-NRF of Korea (Grant No. 2012-002521).

Stator and Rotor Flux Based Deadbeat Direct Torque Control of Induction Machines

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.; Lorenz, Robert D.

2001-01-01

A new, deadbeat type of direct torque control is proposed, analyzed, and experimentally verified in this paper. The control is based on stator and rotor flux as state variables. This choice of state variables allows a graphical representation which is transparent and insightful. The graphical solution shows the effects of realistic considerations such as voltage and current limits. A position and speed sensorless implementation of the control, based on the self-sensing signal injection technique, is also demonstrated experimentally for low speed operation. The paper first develops the new, deadbeat DTC methodology and graphical representation of the new algorithm. It then evaluates feasibility via simulation and experimentally demonstrates performance of the new method with a laboratory prototype including the sensorless methods.

Stator and Rotor Flux Based Deadbeat Direct Torque Control of Induction Machines

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.; Lorenz, Robert D.

2003-01-01

A new, deadbeat type of direct torque control is proposed, analyzed and experimentally verified in this paper. The control is based on stator and rotor flux as state variables. This choice of state variables allows a graphical representation which is transparent and insightful. The graphical solution shows the effects of realistic considerations such as voltage and current limits. A position and speed sensorless implementation of the control, based on the self-sensing signal injection technique, is also demonstrated experimentally for low speed operation. The paper first develops the new, deadbeat DTC methodology and graphical representation of the new algorithm. It then evaluates feasibility via simulation and experimentally demonstrates performance of the new method with a laboratory prototype including the sensorless methods.

Stator and Rotor Flux Based Deadbeat Direct Torque Control of Induction Machines. Revision 1

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.; Lorenz, Robert D.

2002-01-01

A new, deadbeat type of direct torque control is proposed, analyzed, and experimentally verified in this paper. The control is based on stator and rotor flux as state variables. This choice of state variables allows a graphical representation which is transparent and insightful. The graphical solution shows the effects of realistic considerations such as voltage and current limits. A position and speed sensorless implementation of the control, based on the self-sensing signal injection technique, is also demonstrated experimentally for low speed operation. The paper first develops the new, deadbeat DTC methodology and graphical representation of the new algorithm. It then evaluates feasibility via simulation and experimentally demonstrates performance of the new method with a laboratory prototype including the sensorless methods.

Microprocessor based implementation of attitude and shape control of large space structures

NASA Technical Reports Server (NTRS)

Reddy, A. S. S. R.

1984-01-01

The feasibility of off the shelf eight bit and 16 bit microprocessors to implement linear state variable feedback control laws and assessing the real time response to spacecraft dynamics is studied. The complexity of the dynamic model is described along with the appropriate software. An experimental setup of a beam, microprocessor system for implementing the control laws and the needed generalized software to implement any state variable feedback control system is included.

The risk-adjusted vision beyond casemix (DRG) funding in Australia. International lessons in high complexity and capitation.

PubMed

Antioch, Kathryn M; Walsh, Michael K

2004-06-01

Hospitals throughout the world using funding based on diagnosis-related groups (DRG) have incurred substantial budgetary deficits, despite high efficiency. We identify the limitations of DRG funding that lack risk (severity) adjustment for State-wide referral services. Methods to risk adjust DRGs are instructive. The average price in casemix funding in the Australian State of Victoria is policy based, not benchmarked. Average cost weights are too low for high-complexity DRGs relating to State-wide referral services such as heart and lung transplantation and trauma. Risk-adjusted specified grants (RASG) are required for five high-complexity respiratory, cardiology and stroke DRGs incurring annual deficits of $3.6 million due to high casemix complexity and government under-funding despite high efficiency. Five stepwise linear regressions for each DRG excluded non-significant variables and assessed heteroskedasticity and multicollinearlity. Cost per patient was the dependent variable. Significant independent variables were age, length-of-stay outliers, number of disease types, diagnoses, procedures and emergency status. Diagnosis and procedure severity markers were identified. The methodology and the work of the State-wide Risk Adjustment Working Group can facilitate risk adjustment of DRGs State-wide and for Treasury negotiations for expenditure growth. The Alfred Hospital previously negotiated RASG of $14 million over 5 years for three trauma and chronic DRGs. Some chronic diseases require risk-adjusted capitation funding models for Australian Health Maintenance Organizations as an alternative to casemix funding. The use of Diagnostic Cost Groups can facilitate State and Federal government reform via new population-based risk adjusted funding models that measure health need.

An approach to online network monitoring using clustered patterns

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

Kim, Jinoh; Sim, Alex; Suh, Sang C.

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

An approach to online network monitoring using clustered patterns

DOE PAGES

Kim, Jinoh; Sim, Alex; Suh, Sang C.; ...

2017-03-13

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

Gapped two-body Hamiltonian for continuous-variable quantum computation.

PubMed

Aolita, Leandro; Roncaglia, Augusto J; Ferraro, Alessandro; Acín, Antonio

2011-03-04

We introduce a family of Hamiltonian systems for measurement-based quantum computation with continuous variables. The Hamiltonians (i) are quadratic, and therefore two body, (ii) are of short range, (iii) are frustration-free, and (iv) possess a constant energy gap proportional to the squared inverse of the squeezing. Their ground states are the celebrated Gaussian graph states, which are universal resources for quantum computation in the limit of infinite squeezing. These Hamiltonians constitute the basic ingredient for the adiabatic preparation of graph states and thus open new venues for the physical realization of continuous-variable quantum computing beyond the standard optical approaches. We characterize the correlations in these systems at thermal equilibrium. In particular, we prove that the correlations across any multipartition are contained exactly in its boundary, automatically yielding a correlation area law.

Predictions of Poisson's ratio in cross-ply laminates containing matrix cracks and delaminations

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Allen, David H.; Nottorf, Eric W.

1989-01-01

A damage-dependent constitutive model for laminated composites has been developed for the combined damage modes of matrix cracks and delaminations. The model is based on the concept of continuum damage mechanics and uses second-order tensor valued internal state variables to represent each mode of damage. The internal state variables are defined as the local volume average of the relative crack face displacements. Since the local volume for delaminations is specified at the laminate level, the constitutive model takes the form of laminate analysis equations modified by the internal state variables. Model implementation is demonstrated for the laminate engineering modulus E(x) and Poisson's ratio nu(xy) of quasi-isotropic and cross-ply laminates. The model predictions are in close agreement to experimental results obtained for graphite/epoxy laminates.

Morals or markets? Regulating assisted reproductive technologies as morality or economic policies in the states.

PubMed

Heidt-Forsythe, Erin

2017-01-01

The availability of assisted reproductive technologies (ARTs) in the medical marketplace complicates our understanding of reproductive public policy in the United States. Political debates over ARTs often are based on fundamental moral principles of life, reproduction, and kinship, similar to other reproductive policies in the United States. However, ARTs are an important moneymaking private enterprise for the U.S. biotechnology industry. This project investigates how the U.S. states regulate these unique and challenging technologies as either moral policies or economic policies. This study employs ordinary least squares (OLS) regression to estimate the significance of morality and economic policy variables on ART policies at the state level, noting associations between state-level political, economic, and gender variables on restrictive and permissive state-level ART policies. Economic variables (reflecting the biotechnology industry) and advocacy for access to ART on behalf of infertility patients increase the chances of states passing policies that enable consumer use of ARTs. Additionally, individual ART policies are distinct from one another in the ways that morality variables increase the chances of ART regulations. Surprisingly, the role of religious adherence among state residents varied in positive and negative relationships with individual policy passage. In general, these results support the hypothesis that ART laws are associated with economic as well as moral concerns of the states-ARTs lie at the intersection of issues of life and reproduction and of scientific innovation and health. What is most striking about these results is that they do not follow patterns seen in the legislation of abortion, contraception, and sexuality in general-those reproductive policies that are considered "morality policy." Similarly, economic variables are not consistently significant in the expected direction.

Contextual mediation of perceptions in hauntings and poltergeist-like experiences.

PubMed

Lange, R; Houran, J; Harte, T M; Havens, R A

1996-06-01

The content of perceived apparitions, e.g., bereavement hallucinations, cannot be explained entirely in terms of electromagnetically induced neurochemical processes. It was shown that contextual variables influential in hallucinatory and hypnotic states also structured reported haunting experiences. As predicted, high congruency was found between the experiential content and the nature of the contextual variables. Further, the number of contextual variables involved in an experience was related to the type of experience and the state or arousal preceding the experience. Based on these findings we argue that a more complete explanation of haunting experiences should take into account both electromagnetically induced neurochemical processes and factors related to contextual mediation.

Pharmacokinetic Variability of Drugs Used for Prophylactic Treatment of Migraine.

PubMed

Tfelt-Hansen, Peer; Ågesen, Frederik Nybye; Pavbro, Agniezka; Tfelt-Hansen, Jacob

2017-05-01

In this review, we evaluate the variability in the pharmacokinetics of 11 drugs with established prophylactic effects in migraine to facilitate 'personalized medicine' with these drugs. PubMed was searched for 'single-dose' and 'steady-state' pharmacokinetic studies of these 11 drugs. The maximum plasma concentration was reported in 248 single-dose and 115 steady-state pharmacokinetic studies, and the area under the plasma concentration-time curve was reported in 299 single-dose studies and 112 steady-state pharmacokinetic studies. For each study, the coefficient of variation was calculated for maximum plasma concentration and area under the plasma concentration-time curve, and we divided the drug variability into two categories; high variability, coefficient of variation >40%, or low or moderate variability, coefficient of variation <40%. Based on the area under the plasma concentration-time curve in steady-state studies, the following drugs have high pharmacokinetic variability: propranolol in 92% (33/36), metoprolol in 85% (33/39), and amitriptyline in 60% (3/5) of studies. The following drugs have low or moderate variability: atenolol in 100% (2/2), valproate in 100% (15/15), topiramate in 88% (7/8), and naproxen and candesartan in 100% (2/2) of studies. For drugs with low or moderate pharmacokinetic variability, treatment can start without initial titration of doses, whereas titration is used to possibly enhance tolerability of topiramate and amitriptyline. The very high pharmacokinetic variability of metoprolol and propranolol can result in very high plasma concentrations in a small minority of patients, and those drugs should therefore be titrated up from a low initial dose, depending mainly on the occurrence of adverse events.

Linear canonical transformations of coherent and squeezed states in the Wigner phase space. II - Quantitative analysis

NASA Technical Reports Server (NTRS)

Han, D.; Kim, Y. S.; Noz, Marilyn E.

1989-01-01

It is possible to calculate expectation values and transition probabilities from the Wigner phase-space distribution function. Based on the canonical transformation properties of the Wigner function, an algorithm is developed for calculating these quantities in quantum optics for coherent and squeezed states. It is shown that the expectation value of a dynamical variable can be written in terms of its vacuum expectation value of the canonically transformed variable. Parallel-axis theorems are established for the photon number and its variant. It is also shown that the transition probability between two squeezed states can be reduced to that of the transition from one squeezed state to vacuum.

A Model to Couple Flow, Thermal and Reactive Chemical Transport, and Geo-mechanics in Variably Saturated Media

NASA Astrophysics Data System (ADS)

Yeh, G. T.; Tsai, C. H.

2015-12-01

This paper presents the development of a THMC (thermal-hydrology-mechanics-chemistry) process model in variably saturated media. The governing equations for variably saturated flow and reactive chemical transport are obtained based on the mass conservation principle of species transport supplemented with Darcy's law, constraint of species concentration, equation of states, and constitutive law of K-S-P (Conductivity-Degree of Saturation-Capillary Pressure). The thermal transport equation is obtained based on the conservation of energy. The geo-mechanic displacement is obtained based on the assumption of equilibrium. Conventionally, these equations have been implicitly coupled via the calculations of secondary variables based on primary variables. The mechanisms of coupling have not been obvious. In this paper, governing equations are explicitly coupled for all primary variables. The coupling is accomplished via the storage coefficients, transporting velocities, and conduction-dispersion-diffusion coefficient tensor; one set each for every primary variable. With this new system of equations, the coupling mechanisms become clear. Physical interpretations of every term in the coupled equations will be discussed. Examples will be employed to demonstrate the intuition and superiority of these explicit coupling approaches. Keywords: Variably Saturated Flow, Thermal Transport, Geo-mechanics, Reactive Transport.

Continuous variable quantum cryptography: beating the 3 dB loss limit.

PubMed

Silberhorn, Ch; Ralph, T C; Lütkenhaus, N; Leuchs, G

2002-10-14

We demonstrate that secure quantum key distribution systems based on continuous variable implementations can operate beyond the apparent 3 dB loss limit that is implied by the beam splitting attack. The loss limit was established for standard minimum uncertainty states such as coherent states. We show that, by an appropriate postselection mechanism, we can enter a region where Eve's knowledge on Alice's key falls behind the information shared between Alice and Bob, even in the presence of substantial losses.

Simple proof of the quantum benchmark fidelity for continuous-variable quantum devices

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

Namiki, Ryo

2011-04-15

An experimental success criterion for continuous-variable quantum teleportation and memory is to surpass the limit of the average fidelity achieved by classical measure-and-prepare schemes with respect to a Gaussian-distributed set of coherent states. We present an alternative proof of the classical limit based on the familiar notions of state-channel duality and partial transposition. The present method enables us to produce a quantum-domain criterion associated with a given set of measured fidelities.

De Finetti representation theorem for infinite-dimensional quantum systems and applications to quantum cryptography.

PubMed

Renner, R; Cirac, J I

2009-03-20

We show that the quantum de Finetti theorem holds for states on infinite-dimensional systems, provided they satisfy certain experimentally verifiable conditions. This result can be applied to prove the security of quantum key distribution based on weak coherent states or other continuous variable states against general attacks.

Heart Rate Variability and Drawing Impairment in Hypoxemic COPD

ERIC Educational Resources Information Center

Incalzi, Raffaele Antonelli; Corsonello, Andrea; Trojano, Luigi; Pedone, Claudio; Acanfora, Domenico; Spada, Aldo; D'Addio, Gianni; Maestri, Roberto; Rengo, Franco; Rengo, Giuseppe

2009-01-01

We studied 54 patients with hypoxemic chronic obstructive pulmonary disease (COPD). The Mini Mental State Examination and the Mental Deterioration Battery were used for neuropsychological assessment. Heart rate variability (HRV) was assessed based on 24-h Holter ECG recording. Mann-Whitney test was used to compare HRV parameters of patients…

State funding for local public health: observations from six case studies.

PubMed

Potter, Margaret A; Fitzpatrick, Tiffany

2007-01-01

The purpose of this study is to describe state funding of local public health within the context of state public health system types. These types are based on administrative relationships, legal structures, and relative proportion of state funding in local public health budgets. We selected six states representing various types and geographic regions. A case study for each state summarized available information and was validated by state public health officials. An analysis of the case studies reveals that the variability of state public health systems--even within a given type--is matched by variability in approaches to funding local public health. Nevertheless, some meaningful associations appear. For example, higher proportions of state funding occur along with higher levels of state oversight and the existence of local service mandates in state law. These associations suggest topics for future research on public health financing in relation to local accountability, local input to state priority-setting, mandated local services, and the absence of state funds for public health services in some local jurisdictions.

Remote creation of hybrid entanglement between particle-like and wave-like optical qubits

NASA Astrophysics Data System (ADS)

Morin, Olivier; Huang, Kun; Liu, Jianli; Le Jeannic, Hanna; Fabre, Claude; Laurat, Julien

2014-07-01

The wave-particle duality of light has led to two different encodings for optical quantum information processing. Several approaches have emerged based either on particle-like discrete-variable states (that is, finite-dimensional quantum systems) or on wave-like continuous-variable states (that is, infinite-dimensional systems). Here, we demonstrate the generation of entanglement between optical qubits of these different types, located at distant places and connected by a lossy channel. Such hybrid entanglement, which is a key resource for a variety of recently proposed schemes, including quantum cryptography and computing, enables information to be converted from one Hilbert space to the other via teleportation and therefore the connection of remote quantum processors based upon different encodings. Beyond its fundamental significance for the exploration of entanglement and its possible instantiations, our optical circuit holds promise for implementations of heterogeneous network, where discrete- and continuous-variable operations and techniques can be efficiently combined.

Teleportation-based continuous variable quantum cryptography

NASA Astrophysics Data System (ADS)

Luiz, F. S.; Rigolin, Gustavo

2017-03-01

We present a continuous variable (CV) quantum key distribution (QKD) scheme based on the CV quantum teleportation of coherent states that yields a raw secret key made up of discrete variables for both Alice and Bob. This protocol preserves the efficient detection schemes of current CV technology (no single-photon detection techniques) and, at the same time, has efficient error correction and privacy amplification schemes due to the binary modulation of the key. We show that for a certain type of incoherent attack, it is secure for almost any value of the transmittance of the optical line used by Alice to share entangled two-mode squeezed states with Bob (no 3 dB or 50% loss limitation characteristic of beam splitting attacks). The present CVQKD protocol works deterministically (no postselection needed) with efficient direct reconciliation techniques (no reverse reconciliation) in order to generate a secure key and beyond the 50% loss case at the incoherent attack level.

Early prediction of extreme stratospheric polar vortex states based on causal precursors

NASA Astrophysics Data System (ADS)

Kretschmer, Marlene; Runge, Jakob; Coumou, Dim

2017-08-01

Variability in the stratospheric polar vortex (SPV) can influence the tropospheric circulation and thereby winter weather. Early predictions of extreme SPV states are thus important to improve forecasts of winter weather including cold spells. However, dynamical models are usually restricted in lead time because they poorly capture low-frequency processes. Empirical models often suffer from overfitting problems as the relevant physical processes and time lags are often not well understood. Here we introduce a novel empirical prediction method by uniting a response-guided community detection scheme with a causal discovery algorithm. This way, we objectively identify causal precursors of the SPV at subseasonal lead times and find them to be in good agreement with known physical drivers. A linear regression prediction model based on the causal precursors can explain most SPV variability (r2 = 0.58), and our scheme correctly predicts 58% (46%) of extremely weak SPV states for lead times of 1-15 (16-30) days with false-alarm rates of only approximately 5%. Our method can be applied to any variable relevant for (sub)seasonal weather forecasts and could thus help improving long-lead predictions.

Sequential Modular Position and Momentum Measurements of a Trapped Ion Mechanical Oscillator

NASA Astrophysics Data System (ADS)

Flühmann, C.; Negnevitsky, V.; Marinelli, M.; Home, J. P.

2018-04-01

The noncommutativity of position and momentum observables is a hallmark feature of quantum physics. However, this incompatibility does not extend to observables that are periodic in these base variables. Such modular-variable observables have been suggested as tools for fault-tolerant quantum computing and enhanced quantum sensing. Here, we implement sequential measurements of modular variables in the oscillatory motion of a single trapped ion, using state-dependent displacements and a heralded nondestructive readout. We investigate the commutative nature of modular variable observables by demonstrating no-signaling in time between successive measurements, using a variety of input states. Employing a different periodicity, we observe signaling in time. This also requires wave-packet overlap, resulting in quantum interference that we enhance using squeezed input states. The sequential measurements allow us to extract two-time correlators for modular variables, which we use to violate a Leggett-Garg inequality. Signaling in time and Leggett-Garg inequalities serve as efficient quantum witnesses, which we probe here with a mechanical oscillator, a system that has a natural crossover from the quantum to the classical regime.

Use of an urban intensity index to assess urban effects on streams in three contrasting environmental settings

USGS Publications Warehouse

Tate, C.M.; Cuffney, T.F.; McMahon, G.; Giddings, E.M.P.; Coles, J.F.; Zappia, H.

2005-01-01

To assess the effects of urbanization on assemblages (fish, invertebrate, and algal), physical habitat, and water chemistry, we investigated the relations among varying intensities of basin urbanization and stream ecology in three metropolitan areas: the humid northeastern United States around Boston, Massachusetts; the humid southeastern United States around Birmingham, Alabama; and the semiarid western United States around Salt Lake City, Utah. A consistent process was used to develop a multimetric urban intensity index (UII) based on locally important variables (land-use/land-cover, infrastructure, and socioeconomic variables) in each study area and a common urban intensity index (CUII) based on a subset of five variables common to all study areas. The UII was used to characterize 30 basins along an urban gradient in each metropolitan area. Study basins were located within a single ecoregion in each of the metropolitan areas. The UII, ecoregions, and site characteristics provided a method for limiting the variability of natural landscape characteristics while assessing the magnitude of urban effects. Conditions in Salt Lake City (semiarid climate and water diversions) and Birmingham (topography) required nesting sites within the same basin. The UII and CUII facilitated comparisons of aquatic assemblages response to urbanization across different environmental settings. ?? 2005 by the American Fisheries Society.

A crystallographic model for the tensile and fatigue response for Rene N4 at 982 C

NASA Technical Reports Server (NTRS)

Sheh, M. Y.; Stouffer, D. C.

1990-01-01

An anisotropic constitutive model based on crystallographic slip theory was formulated for nickel-base single-crystal superalloys. The current equations include both drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments have been conducted to evaluate the existence of back stress in single crystals. The results showed that the back stress effect of reverse inelastic flow on the unloading stress is orientation-dependent, and a back stress state variable in the inelastic flow equation is necessary for predicting inelastic behavior. Model correlations and predictions of experimental data are presented for the single crystal superalloy Rene N4 at 982 C.

Understanding the Long-Term Spectral Variability of Cygnus X-1 with Burst and Transient Source Experiment and All-Sky Monitor Observations

NASA Technical Reports Server (NTRS)

Zdziarski, Andrzej A.; Poutanen, Juri; Paciesas, William S.; Wen, Lin-Qing

2002-01-01

We present a comprehensive analysis of all observations of Cyg X-1 by the Compton Gamma Ray Observatory Burst and Transient Source Experiment (BATSE; 20-300 keV) and by the Rossi X-Ray Timing Explorer all-sky monitor (ASM; 1.5-12 keV) until 2002 June, including approximately 1200 days of simultaneous data. We find a number of correlations between fluxes and hardnesses in different energy bands. In the hard (low) spectral state, there is a negative correlation between the ASM 1.5-12 keV flux and the hardness at any energy. In the soft (high) spectral state, the ASM flux is positively correlated with the ASM hardness but uncorrelated with the BATSE hardness. In both spectral states, the BATSE hardness correlates with the flux above 100 keV, while it shows no correlation with the 20-100 keV flux. At the same time, there is clear correlation between the BATSE fluxes below and above 100 keV. In the hard state, most of the variability can be explained by softening the overall spectrum with a pivot at approximately 50 keV. There is also another, independent variability pattern of lower amplitude where the spectral shape does not change when the luminosity changes. In the soft state, the variability is mostly caused by a variable hard (Comptonized) spectral component of a constant shape superposed on a constant soft blackbody component. These variability patterns are in agreement with the dependencies of the rms variability on the photon energy in the two states. We also study in detail recent soft states from late 2000 until 2002. The last of them has lasted thus far for more than 200 days. Their spectra are generally harder in the 1.5-5 keV band and similar or softer in the 3-12 keV band than the spectra of the 1996 soft state, whereas the rms variability is stronger in all the ASM bands. On the other hand, the 1994 soft state transition observed by BATSE appears very similar to the 1996 one. We interpret the variability patterns in terms of theoretical Comptonization models. In the hard state, the variability appears to be driven mostly by changing flux in seed photons Comptonized in a hot thermal plasma cloud with an approximately constant power supply. In the soft state, the variability is consistent with flares of hybrid, thermal/nonthermal, plasma with variable power above a stable cold disk. The spectral and timing differences between the 1996 and 2000-2002 soft states are explained by a decrease of the color disk temperature. Also, on the basis of broadband pointed observations simultaneous with those of the ASM and BATSE, we find the intrinsic bolometric luminosity increases by a factor of approximately 3-4 from the hard state to the soft one, which supports models of the state transition based on a change of the accretion rate.

Brain entropy and human intelligence: A resting-state fMRI study

PubMed Central

Calderone, Daniel; Morales, Leah J.

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

Brain entropy and human intelligence: A resting-state fMRI study.

PubMed

Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

Entanglement enhancement through multirail noise reduction for continuous-variable measurement-based quantum-information processing

NASA Astrophysics Data System (ADS)

Su, Yung-Chao; Wu, Shin-Tza

2017-09-01

We study theoretically the teleportation of a controlled-phase (cz) gate through measurement-based quantum-information processing for continuous-variable systems. We examine the degree of entanglement in the output modes of the teleported cz-gate for two classes of resource states: the canonical cluster states that are constructed via direct implementations of two-mode squeezing operations and the linear-optical version of cluster states which are built from linear-optical networks of beam splitters and phase shifters. In order to reduce the excess noise arising from finite-squeezed resource states, teleportation through resource states with different multirail designs will be considered and the enhancement of entanglement in the teleported cz gates will be analyzed. For multirail cluster with an arbitrary number of rails, we obtain analytical expressions for the entanglement in the output modes and analyze in detail the results for both classes of resource states. At the same time, we also show that for uniformly squeezed clusters the multirail noise reduction can be optimized when the excess noise is allocated uniformly to the rails. To facilitate the analysis, we develop a trick with manipulations of quadrature operators that can reveal rather efficiently the measurement sequence and corrective operations needed for the measurement-based gate teleportation, which will also be explained in detail.

Is There a Hole in the Bucket? Understanding SCHIP Retention. Assessing the New Federalism: An Urban Institute Program To Assess Changing Social Policies. Occasional Paper.

ERIC Educational Resources Information Center

Hill, Ian; Lutzky, Amy Westpfahl

This study examined states efforts to retain children in their State Childrens Health Insurance Program (SCHIP). Data were obtained during spring and summer of 2000 through telephone interviews with state program officials from eight states selected based on a variety of demographic and programmatic variables; the states were Alabama, California,…

Rivers and Floodplains as Key Components of Global Terrestrial Water Storage Variability

NASA Astrophysics Data System (ADS)

Getirana, Augusto; Kumar, Sujay; Girotto, Manuela; Rodell, Matthew

2017-10-01

This study quantifies the contribution of rivers and floodplains to terrestrial water storage (TWS) variability. We use state-of-the-art models to simulate land surface processes and river dynamics and to separate TWS into its main components. Based on a proposed impact index, we show that surface water storage (SWS) contributes 8% of TWS variability globally, but that contribution differs widely among climate zones. Changes in SWS are a principal component of TWS variability in the tropics, where major rivers flow over arid regions and at high latitudes. SWS accounts for 22-27% of TWS variability in both the Amazon and Nile Basins. Changes in SWS are negligible in the Western U.S., Northern Africa, Middle East, and central Asia. Based on comparisons with Gravity Recovery and Climate Experiment-based TWS, we conclude that accounting for SWS improves simulated TWS in most of South America, Africa, and Southern Asia, confirming that SWS is a key component of TWS variability.

[A meta-analysis of the variables related to depression in Korean patients with a stroke].

PubMed

Park, Eun Young; Shin, In Soo; Kim, Jung Hee

2012-08-01

The purpose of this study was to use meta-analysis to evaluate the variables related to depression in patients who have had a stroke. The materials of this study were based on 16 variables obtained from 26 recent studies over a span of 10 years which were selected from doctoral dissertations, master's thesis and published articles. Related variables were categorized into sixteen variables and six variable groups which included general characteristics of the patients, disease characteristics, psychological state, physical function, basic needs, and social variables. Also, the classification of six defensive and three risk variables group was based on the negative or positive effect of depression. The quality of life (ES=-.79) and acceptance of disability (ES=-.64) were highly correlated with depression in terms of defensive variables. For risk variables, anxiety (ES=.66), stress (ES=.53) showed high correlation effect size among the risk variables. These findings showed that defensive and risk variables were related to depression among stroke patients. Psychological interventions and improvement in physical functions should be effective in decreasing depression among stroke patients.

A STATE-VARIABLE APPROACH FOR PREDICTING THE TIME REQUIRED FOR 50% RECRYSTALLIZATION

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

M. STOUT; ET AL

2000-08-01

It is important to be able to model the recrystallization kinetics in aluminum alloys during hot deformation. The industrial relevant process of hot rolling is an example of where the knowledge of whether or not a material recrystallizes is critical to making a product with the correct properties. Classically, the equations that describe the kinetics of recrystallization predict the time to 50% recrystallization. These equations are largely empirical; they are based on the free energy for recrystallization, a Zener-Holloman parameter, and have several adjustable exponents to fit the equation to engineering data. We have modified this form of classical theorymore » replacing the Zener-Hollomon parameter with a deformation energy increment, a free energy available to drive recrystallization. The advantage of this formulation is that the deformation energy increment is calculated based on the previously determined temperature and strain-rate sensitivity of the constitutive response. We modeled the constitutive response of the AA5182 aluminum using a state variable approach, the value of the state variable is a function of the temperature and strain-rate history of deformation. Thus, the recrystallization kinetics is a function of only the state variable and free energy for recrystallization. There are no adjustable exponents as in classical theory. Using this approach combined with engineering recrystallization data we have been able to predict the kinetics of recrystallization in AA5182 as a function of deformation strain rate and temperature.« less

Using state variables to model the response of tumour cells to radiation and heat: a novel multi-hit-repair approach.

PubMed

Scheidegger, Stephan; Fuchs, Hans U; Zaugg, Kathrin; Bodis, Stephan; Füchslin, Rudolf M

2013-01-01

In order to overcome the limitations of the linear-quadratic model and include synergistic effects of heat and radiation, a novel radiobiological model is proposed. The model is based on a chain of cell populations which are characterized by the number of radiation induced damages (hits). Cells can shift downward along the chain by collecting hits and upward by a repair process. The repair process is governed by a repair probability which depends upon state variables used for a simplistic description of the impact of heat and radiation upon repair proteins. Based on the parameters used, populations up to 4-5 hits are relevant for the calculation of the survival. The model describes intuitively the mathematical behaviour of apoptotic and nonapoptotic cell death. Linear-quadratic-linear behaviour of the logarithmic cell survival, fractionation, and (with one exception) the dose rate dependencies are described correctly. The model covers the time gap dependence of the synergistic cell killing due to combined application of heat and radiation, but further validation of the proposed approach based on experimental data is needed. However, the model offers a work bench for testing different biological concepts of damage induction, repair, and statistical approaches for calculating the variables of state.

Characterizing Individual Differences in Functional Connectivity Using Dual-Regression and Seed-Based Approaches

PubMed Central

Smith, David V.; Utevsky, Amanda V.; Bland, Amy R.; Clement, Nathan; Clithero, John A.; Harsch, Anne E. W.; Carter, R. McKell; Huettel, Scott A.

2014-01-01

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent components analysis (ICA). We estimated voxelwise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust—yet frequently ignored—neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. PMID:24662574

A global perspective on Glacial- to Interglacial variability change

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2017-04-01

Changes in climate variability are more important for society than changes in the mean state alone. While we will be facing a large-scale shift of the mean climate in the future, its implications for climate variability are not well constrained. Here we quantify changes in temperature variability as climate shifted from the Last Glacial cold to the Holocene warm period. Greenland ice core oxygen isotope records provide evidence of this climatic shift, and are used as reference datasets in many palaeoclimate studies worldwide. A striking feature in these records is pronounced millennial variability in the Glacial, and a distinct reduction in variance in the Holocene. We present quantitative estimates of the change in variability on 500- to 1500-year timescales based on a global compilation of high-resolution proxy records for temperature which span both the Glacial and the Holocene. The estimates are derived based on power spectral analysis, and corrected using estimates of the proxy signal-to-noise ratios. We show that, on a global scale, variability at the Glacial maximum is five times higher than during the Holocene, with a possible range of 3-10 times. The spatial pattern of the variability change is latitude-dependent. While the tropics show no changes in variability, mid-latitude changes are higher. A slight overall reduction in variability in the centennial to millennial range is found in Antarctica. The variability decrease in the Greenland ice core oxygen isotope records is larger than in any other proxy dataset. These results therefore contradict the view of a globally quiescent Holocene following the instable Glacial, and imply that, in terms of centennial to millennial temperature variability, the two states may be more similar than previously thought.

The status of states' policies to support evidence-based practices in children's mental health.

PubMed

Cooper, Janice L; Aratani, Yumiko

2009-12-01

This study examined the efforts of states' mental health authorities to promote the use of evidence-based practices through policy. Data were drawn from three components of a national study, including a survey of state children's mental health directors (N=53), which was developed using a three-step process that involved stakeholders. Data from the directors' survey revealed that over 90% of states are implementing strategies to support the use of evidence-based practices. The scope of these efforts varies, with 36% reporting statewide reach. Further, states' strategies for implementing evidence-based practices are often not accompanied by comparable efforts to enhance information systems, even though enhancing such systems can bolster opportunities for successful implementation. Variability in the adoption of evidence-based practices, poor attention to information systems, and inconsistent fiscal policies threaten states' efforts to improve the quality of children's mental health services.

Quantum key distribution using continuous-variable non-Gaussian states

NASA Astrophysics Data System (ADS)

Borelli, L. F. M.; Aguiar, L. S.; Roversi, J. A.; Vidiella-Barranco, A.

2016-02-01

In this work, we present a quantum key distribution protocol using continuous-variable non-Gaussian states, homodyne detection and post-selection. The employed signal states are the photon added then subtracted coherent states (PASCS) in which one photon is added and subsequently one photon is subtracted from the field. We analyze the performance of our protocol, compared with a coherent state-based protocol, for two different attacks that could be carried out by the eavesdropper (Eve). We calculate the secret key rate transmission in a lossy line for a superior channel (beam-splitter) attack, and we show that we may increase the secret key generation rate by using the non-Gaussian PASCS rather than coherent states. We also consider the simultaneous quadrature measurement (intercept-resend) attack, and we show that the efficiency of Eve's attack is substantially reduced if PASCS are used as signal states.

Pattern of state coal taxation. [Review

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

Gulley, D.A.

1981-01-01

This paper reviews the recent history of state coal taxation and reports an empirically-based effort at defining the key determinants of state and local coal taxation. A pattern emerges but the analysis is complicated by the empirical and conceptual difficulties typical of such studies. Perhaps as important a result as the detection of a pattern is the recognition that many seemingly important variables do not appear to have consistently influenced tax levels. For policy makers and for industry, it appears that the present concern over a coal-states cartel is excessive. One can speculate that draconian tax adjustments on the basismore » of a crude-indicator-like reserve base will ultimately transfer less wealth than would skillful preemption of rent. It is also noteworthy that the sign of the tax effort variable is positive, indicating that coal tax rates are consistent with other tax efforts, not a substitute for them. Accepting impacts and general tax effort variables as the best explanations of interstate variations in tax effort is a somewhat different matter than determining what any given state's tax rate ought to be; such a question lies beyond the scope of this paper. This tax-determinant study can not define the right level of coal taxation, but it can suggest that no trend is yet evident toward entrepreneurial tax rates. 20 references, 4 figures.« less

Predicting In-State Workforce Retention After Graduate Medical Education Training.

PubMed

Koehler, Tracy J; Goodfellow, Jaclyn; Davis, Alan T; Spybrook, Jessaca; vanSchagen, John E; Schuh, Lori

2017-02-01

There is a paucity of literature when it comes to identifying predictors of in-state retention of graduate medical education (GME) graduates, such as the demographic and educational characteristics of these physicians. The purpose was to use demographic and educational predictors to identify graduates from a single Michigan GME sponsoring institution, who are also likely to practice medicine in Michigan post-GME training. We included all residents and fellows who graduated between 2000 and 2014 from 1 of 18 GME programs at a Michigan-based sponsoring institution. Predictor variables identified by logistic regression with cross-validation were used to create a scoring tool to determine the likelihood of a GME graduate to practice medicine in the same state post-GME training. A 6-variable model, which included 714 observations, was identified. The predictor variables were birth state, program type (primary care versus non-primary care), undergraduate degree location, medical school location, state in which GME training was completed, and marital status. The positive likelihood ratio (+LR) for the scoring tool was 5.31, while the negative likelihood ratio (-LR) was 0.46, with an accuracy of 74%. The +LR indicates that the scoring tool was useful in predicting whether graduates who trained in a Michigan-based GME sponsoring institution were likely to practice medicine in Michigan following training. Other institutions could use these techniques to identify key information that could help pinpoint matriculating residents/fellows likely to practice medicine within the state in which they completed their training.

Effectiveness of Blog Response Strategies to Minimize Crisis Effects

ERIC Educational Resources Information Center

Tomsic, Louis P.

2010-01-01

This study examined the effects of four post-crisis responses on five different variables using a blog tool. The four post-crisis responses are information only, compensation, apology, and sympathy. The five dependent variables are reputation, anger (negative emotion), negative word-of-mouth, account acceptance and state of the publics based on…

Estimation of Hidden State Variables of the Intracranial System Using Constrained Nonlinear Kalman Filters

PubMed Central

Nenov, Valeriy; Bergsneider, Marvin; Glenn, Thomas C.; Vespa, Paul; Martin, Neil

2007-01-01

Impeded by the rigid skull, assessment of physiological variables of the intracranial system is difficult. A hidden state estimation approach is used in the present work to facilitate the estimation of unobserved variables from available clinical measurements including intracranial pressure (ICP) and cerebral blood flow velocity (CBFV). The estimation algorithm is based on a modified nonlinear intracranial mathematical model, whose parameters are first identified in an offline stage using a nonlinear optimization paradigm. Following the offline stage, an online filtering process is performed using a nonlinear Kalman filter (KF)-like state estimator that is equipped with a new way of deriving the Kalman gain satisfying the physiological constraints on the state variables. The proposed method is then validated by comparing different state estimation methods and input/output (I/O) configurations using simulated data. It is also applied to a set of CBFV, ICP and arterial blood pressure (ABP) signal segments from brain injury patients. The results indicated that the proposed constrained nonlinear KF achieved the best performance among the evaluated state estimators and that the state estimator combined with the I/O configuration that has ICP as the measured output can potentially be used to estimate CBFV continuously. Finally, the state estimator combined with the I/O configuration that has both ICP and CBFV as outputs can potentially estimate the lumped cerebral arterial radii, which are not measurable in a typical clinical environment. PMID:17281533

Developing the formula for state subsidies for health care in Finland.

PubMed

Häkkinen, Unto; Järvelin, Jutta

2004-01-01

The aim was to generate a research-based proposal for a new subsidy formula for municipal healthcare services in Finland. Small-area data on potential need variables, supply of and access to services, and age-, sex- and case-mix-standardised service utilisation per capita were used. Utilisation was regressed in order to identify need variables and the cost weights for the selected need variables were subsequently derived using various multilevel models and structural equation methods. The variables selected for the subsidy formula were as follows: age- and sex-standardised mortality (age under 65 years) and income for outpatient primary health services; age- and sex-standardised mortality (all ages) and index of overcrowded housing for elderly care and long-term inpatient care; index of disability pensions for those aged 15-55 years and migration for specialised non-psychiatric care; and index of living alone and income for psychiatric care. Decisions on the amount of state subsidies can be divided into three stages, of which the first two are mainly political and the third is based on the results of this study.

Adaptable state based control system

NASA Technical Reports Server (NTRS)

Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)

2004-01-01

An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.

Quantitative effects of composting state variables on C/N ratio through GA-aided multivariate analysis.

PubMed

Sun, Wei; Huang, Guo H; Zeng, Guangming; Qin, Xiaosheng; Yu, Hui

2011-03-01

It is widely known that variation of the C/N ratio is dependent on many state variables during composting processes. This study attempted to develop a genetic algorithm aided stepwise cluster analysis (GASCA) method to describe the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting. The experimental data from six bench-scale composting reactors were used to demonstrate the applicability of GASCA. Within the GASCA framework, GA searched optimal sets of both specified state variables and SCA's internal parameters; SCA established statistical nonlinear relationships between state variables and the C/N ratio; to avoid unnecessary and time-consuming calculation, a proxy table was introduced to save around 70% computational efforts. The obtained GASCA cluster trees had smaller sizes and higher prediction accuracy than the conventional SCA trees. Based on the optimal GASCA tree, the effects of the GA-selected state variables on the C/N ratio were ranged in a descending order as: NH₄+-N concentration>Moisture content>Ash Content>Mean Temperature>Mesophilic bacteria biomass. Such a rank implied that the variation of ammonium nitrogen concentration, the associated temperature and the moisture conditions, the total loss of both organic matters and available mineral constituents, and the mesophilic bacteria activity, were critical factors affecting the C/N ratio during the investigated food waste composting. This first application of GASCA to composting modelling indicated that more direct search algorithms could be coupled with SCA or other multivariate analysis methods to analyze complicated relationships during composting and many other environmental processes. Copyright © 2010 Elsevier B.V. All rights reserved.

Recent changes in county-level corn yield variability in the United States from observations and crop models

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

Leng, Guoyong

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less

Relative roles of weather variables and change in human population in malaria: comparison over different states of India.

PubMed

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria.

Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India

PubMed Central

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Background Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. Method We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. Results For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. Conclusion The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. PMID:24971510

a System Dynamics Approach for Looking at the Human and Environmental Interactions of Community-Based Irrigation Systems in New Mexico

NASA Astrophysics Data System (ADS)

Ochoa, C. G.; Tidwell, V. C.

2012-12-01

In the arid southwestern United States community water management systems have adapted to cope with climate variability and with socio-cultural and economic changes that have occurred since the establishment of these systems more than 300 years ago. In New Mexico, the community-based irrigation systems were established by Spanish settlers and have endured climate variability in the form of low levels of precipitation and have prevailed over important socio-political changes including the transfer of territory between Spain and Mexico, and between Mexico and the United States. Because of their inherent nature of integrating land and water use with society involvement these community-based systems have multiple and complex economic, ecological, and cultural interactions. Current urban population growth and more variable climate conditions are adding pressure to the survival of these systems. We are conducting a multi-disciplinary research project that focuses on characterizing these intrinsically complex human and natural interactions in three community-based irrigation systems in northern New Mexico. We are using a system dynamics approach to integrate different hydrological, ecological, socio-cultural and economic aspects of these three irrigation systems. Coupled with intensive field data collection, we are building a system dynamics model that will enable us to simulate important linkages and interactions between environmental and human elements occurring in each of these water management systems. We will test different climate variability and population growth scenarios and the expectation is that we will be able to identify critical tipping points of these systems. Results from this model can be used to inform policy recommendations relevant to the environment and to urban and agricultural land use planning in the arid southwestern United States.

Modified hyperbolic sine model for titanium dioxide-based memristive thin films

NASA Astrophysics Data System (ADS)

Abu Bakar, Raudah; Syahirah Kamarozaman, Nur; Fazlida Hanim Abdullah, Wan; Herman, Sukreen Hana

2018-03-01

Since the emergence of memristor as the newest fundamental circuit elements, studies on memristor modeling have been evolved. To date, the developed models were based on the linear model, linear ionic drift model using different window functions, tunnelling barrier model and hyperbolic-sine function based model. Although using hyperbolic-sine function model could predict the memristor electrical properties, the model was not well fitted to the experimental data. In order to improve the performance of the hyperbolic-sine function model, the state variable equation was modified. On the one hand, the addition of window function cannot provide an improved fitting. By multiplying the Yakopcic’s state variable model to Chang’s model on the other hand resulted in the closer agreement with the TiO2 thin film experimental data. The percentage error was approximately 2.15%.

Anisotropic constitutive modeling for nickel-base single crystal superalloys. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Sheh, Michael Y.

1988-01-01

An anisotropic constitutive model was developed based on crystallographic slip theory for nickel base single crystal superalloys. The constitutive equations developed utilizes drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments were conducted to evaluate the existence of back stress in single crystal superalloy Rene N4 at 982 C. The results suggest that: (1) the back stress is orientation dependent; and (2) the back stress state variable is required for the current model to predict material anelastic recovery behavior. The model was evaluated for its predictive capability on single crystal material behavior including orientation dependent stress-strain response, tension/compression asymmetry, strain rate sensitivity, anelastic recovery behavior, cyclic hardening and softening, stress relaxation, creep and associated crystal lattice rotation. Limitation and future development needs are discussed.

Adjustment of prior constraints for an improved crop monitoring with the Earth Observation Land Data Assimilation System (EO-LDAS)

NASA Astrophysics Data System (ADS)

Truckenbrodt, Sina C.; Gómez-Dans, José; Stelmaszczuk-Górska, Martyna A.; Chernetskiy, Maxim; Schmullius, Christiane C.

2017-04-01

Throughout the past decades various satellite sensors have been launched that record reflectance in the optical domain and facilitate comprehensive monitoring of the vegetation-covered land surface from space. The interaction of photons with the canopy, leaves and soil that determines the spectrum of reflected sunlight can be simulated with radiative transfer models (RTMs). The inversion of RTMs permits the derivation of state variables such as leaf area index (LAI) and leaf chlorophyll content from top-of-canopy reflectance. Space-borne data are, however, insufficient for an unambiguous derivation of state variables and additional constraints are required to resolve this ill-posed problem. Data assimilation techniques permit the conflation of various information with due allowance for associated uncertainties. The Earth Observation Land Data Assimilation System (EO-LDAS) integrates RTMs into a dynamic process model that describes the temporal evolution of state variables. In addition, prior information is included to further constrain the inversion and enhance the state variable derivation. In previous studies on EO-LDAS, prior information was represented by temporally constant values for all investigated state variables, while information about their phenological evolution was neglected. Here, we examine to what extent the implementation of prior information reflecting the phenological variability improves the performance of EO-LDAS with respect to the monitoring of crops on the agricultural Gebesee test site (Central Germany). Various routines for the generation of prior information are tested. This involves the usage of data on state variables that was acquired in previous years as well as the application of phenological models. The performance of EO-LDAS with the newly implemented prior information is tested based on medium resolution satellite imagery (e.g., RapidEye REIS, Sentinel-2 MSI, Landsat-7 ETM+ and Landsat-8 OLI). The predicted state variables are validated against in situ data from the Gebesee test site that were acquired with a weekly to fortnightly resolution throughout the growing seasons of 2010, 2013, 2014 and 2016. Furthermore, the results are compared with the outcome of using constant values as prior information. In this presentation, the EO-LDAS scheme and results obtained from different prior information are presented.

Effects of phase vector and history extension on prediction power of adaptive-network based fuzzy inference system (ANFIS) model for a real scale anaerobic wastewater treatment plant operating under unsteady state.

PubMed

Perendeci, Altinay; Arslan, Sever; Tanyolaç, Abdurrahman; Celebi, Serdar S

2009-10-01

A conceptual neural fuzzy model based on adaptive-network based fuzzy inference system, ANFIS, was proposed using available input on-line and off-line operational variables for a sugar factory anaerobic wastewater treatment plant operating under unsteady state to estimate the effluent chemical oxygen demand, COD. The predictive power of the developed model was improved as a new approach by adding the phase vector and the recent values of COD up to 5-10 days, longer than overall retention time of wastewater in the system. History of last 10 days for COD effluent with two-valued phase vector in the input variable matrix including all parameters had more predictive power. History of 7 days with two-valued phase vector in the matrix comprised of only on-line variables yielded fairly well estimations. The developed ANFIS model with phase vector and history extension has been able to adequately represent the behavior of the treatment system.

Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2005-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

Highway Safety Information System guidebook for the Maine state data files. Volume 2 : single variable tabulations

DOT National Transportation Integrated Search

2012-10-01

The United States and European Union (EU) share many of the same transportation research issues, challenges, and goals. They also share a belief that cooperative vehicle (also termed connected vehicle) systems, based on vehicle-to-vehicle and vehicle...

Variability of attention processes in ADHD: observations from the classroom.

PubMed

Rapport, Mark D; Kofler, Michael J; Alderson, R Matt; Timko, Thomas M; Dupaul, George J

2009-05-01

Classroom- and laboratory-based efforts to study the attentional problems of children with ADHD are incongruent in elucidating attentional deficits; however, none have explored within- or between-minute variability in the classroom attentional processing in children with ADHD. High and low attention groups of ADHD children defined via cluster analysis, and 36 typically developing children, were observed while completing academic assignments in their general education classrooms. All children oscillated between attentive and inattentive states; however, children in both ADHD groups switched states more frequently and remained attentive for shorter durations relative to typically developing children. Overall differences in attention and optimal ability to maintain attention among the groups are consistent with laboratory studies of increased ADHD-related interindividual and intergroup variability but inconsistent with laboratory results of increased intra-individual variability and attention decrements over time.

Quantum simulation of quantum field theory using continuous variables

DOE PAGES

Marshall, Kevin; Pooser, Raphael C.; Siopsis, George; ...

2015-12-14

Much progress has been made in the field of quantum computing using continuous variables over the last couple of years. This includes the generation of extremely large entangled cluster states (10,000 modes, in fact) as well as a fault tolerant architecture. This has lead to the point that continuous-variable quantum computing can indeed be thought of as a viable alternative for universal quantum computing. With that in mind, we present a new algorithm for continuous-variable quantum computers which gives an exponential speedup over the best known classical methods. Specifically, this relates to efficiently calculating the scattering amplitudes in scalar bosonicmore » quantum field theory, a problem that is known to be hard using a classical computer. Thus, we give an experimental implementation based on cluster states that is feasible with today's technology.« less

Quantum simulation of quantum field theory using continuous variables

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

Marshall, Kevin; Pooser, Raphael C.; Siopsis, George

Much progress has been made in the field of quantum computing using continuous variables over the last couple of years. This includes the generation of extremely large entangled cluster states (10,000 modes, in fact) as well as a fault tolerant architecture. This has lead to the point that continuous-variable quantum computing can indeed be thought of as a viable alternative for universal quantum computing. With that in mind, we present a new algorithm for continuous-variable quantum computers which gives an exponential speedup over the best known classical methods. Specifically, this relates to efficiently calculating the scattering amplitudes in scalar bosonicmore » quantum field theory, a problem that is known to be hard using a classical computer. Thus, we give an experimental implementation based on cluster states that is feasible with today's technology.« less

Optimized tomography of continuous variable systems using excitation counting

NASA Astrophysics Data System (ADS)

Shen, Chao; Heeres, Reinier W.; Reinhold, Philip; Jiang, Luyao; Liu, Yi-Kai; Schoelkopf, Robert J.; Jiang, Liang

2016-11-01

We propose a systematic procedure to optimize quantum state tomography protocols for continuous variable systems based on excitation counting preceded by a displacement operation. Compared with conventional tomography based on Husimi or Wigner function measurement, the excitation counting approach can significantly reduce the number of measurement settings. We investigate both informational completeness and robustness, and provide a bound of reconstruction error involving the condition number of the sensing map. We also identify the measurement settings that optimize this error bound, and demonstrate that the improved reconstruction robustness can lead to an order-of-magnitude reduction of estimation error with given resources. This optimization procedure is general and can incorporate prior information of the unknown state to further simplify the protocol.

Electronic Thermometer Readings

NASA Technical Reports Server (NTRS)

2001-01-01

NASA Stennis' adaptive predictive algorithm for electronic thermometers uses sample readings during the initial rise in temperature and applies an algorithm that accurately and rapidly predicts the steady state temperature. The final steady state temperature of an object can be calculated based on the second-order logarithm of the temperature signals acquired by the sensor and predetermined variables from the sensor characteristics. These variables are calculated during tests of the sensor. Once the variables are determined, relatively little data acquisition and data processing time by the algorithm is required to provide a near-accurate approximation of the final temperature. This reduces the delay in the steady state response time of a temperature sensor. This advanced algorithm can be implemented in existing software or hardware with an erasable programmable read-only memory (EPROM). The capability for easy integration eliminates the expense of developing a whole new system that offers the benefits provided by NASA Stennis' technology.

The role of state anxiety in children's memories for pain.

PubMed

Noel, Melanie; Chambers, Christine T; McGrath, Patrick J; Klein, Raymond M; Stewart, Sherry H

2012-06-01

To investigate the impact of experimentally manipulated state anxiety and the influence of anxiety-related variables on children's memories for pain. A total of 110 children (60 boys) between the ages of 8 and 12 years were randomly assigned to complete a state anxiety induction task or a control task. Following experimental manipulation, children completed a laboratory pain task, pain ratings, and questionnaire measures of anxiety-related variables. 2 weeks later, children provided pain ratings based on their memories of the pain task. The experimental manipulation effectively induced state anxiety; however, pain memories did not differ between groups. Irrespective of group assignment, children with higher state anxiety had more negative pain memories. State anxiety uniquely predicted children's pain memories over and above other well established factors. Anxiety sensitivity and trait anxiety were significant predictors of recalled pain-related fear. These data highlight the importance of anxiety in the development of children's memories for pain.

Quantifying non-Markovianity of continuous-variable Gaussian dynamical maps

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

Vasile, Ruggero; Maniscalco, Sabrina; Paris, Matteo G. A.

2011-11-15

We introduce a non-Markovianity measure for continuous-variable open quantum systems based on the idea put forward in H.-P. Breuer et al.[Phys. Rev. Lett. 103, 210401 (2009);], that is, by quantifying the flow of information from the environment back to the open system. Instead of the trace distance we use here the fidelity to assess distinguishability of quantum states. We employ our measure to evaluate non-Markovianity of two paradigmatic Gaussian channels: the purely damping channel and the quantum Brownian motion channel with Ohmic environment. We consider different classes of Gaussian states and look for pairs of states maximizing the backflow ofmore » information. For coherent states we find simple analytical solutions, whereas for squeezed states we provide both exact numerical and approximate analytical solutions in the weak coupling limit.« less

Thermodynamic neutral density: A new physically-based, energy-constrained, materially conserved neutral density variable for quantifying mixing and tracking water masses in the ocean

NASA Astrophysics Data System (ADS)

Tailleux, R.

2016-02-01

A new materially-conserved quasi-neutral density variable has been constructed, called thermodynamic neutral density. It is composed of two parts. The first part is the Lorenz reference density entering Lorenz theory of available potential energy, which can be interpreted as the potential density of a fluid parcel referenced to the pressure it would have in Lorenz reference state of minimum potential energy. The second part is an empirical correction for pressure, which can be suitably chosen to make thermodynamic neutral density a very good approximation of Jackett and McDougall (1997) neutral density over most of the ocean water masses for which the latter is defined. Thermodynamic neutral density possesses many advantages over the empirically constructed Jackett and McDougall (1997) neutral density: 1) it is physically-based; 2) it is easily computed using fast and efficient methods for arbitrary states of the ocean, not just the present state, using the recently developed methodology by Saenz et al. (2015); 3) it is exactly neutral in a state of rest, and approximately neutral in the present ocean; 4) it is exactly materially conserved (it is a function of salinity and potential temperature only) and not plagued by unphysical nonmaterial effects, so can be used unambiguously to define and diagnose diapycnal and isopycnal mixing; 5) it is based on available potential energy, and therefore is the most suitable variable to discuss the energy cost of adiabatic stirring; 6) it is the variable that should be used to define the isopycnal and diapycnal directions in rotated diffusion tensor, as it can be shown that using the directions defined by the local neutral tangent plane as currently done causes spurious destruction of water masses. References: J. A. Saenz, R. Tailleux, E.D. Butler, G.O. Hughes, and K.I.C. Oliver, 2015: Estimating Lorenz's reference state in an ocean with a nonlinear equation of state for seawater. J. Phys. Oceanogr., 45, 1242—1257

Newtonian nudging for a Richards equation-based distributed hydrological model

NASA Astrophysics Data System (ADS)

Paniconi, Claudio; Marrocu, Marino; Putti, Mario; Verbunt, Mark

The objective of data assimilation is to provide physically consistent estimates of spatially distributed environmental variables. In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimilation scheme. Nudging is shown to be successful in improving the hydrological simulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitivity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexible, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be readily extended to any of these features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation techniques in a Richards equation-based hydrological model.

Trend analysis of precipitation in Jharkhand State, India. Investigating precipitation variability in Jharkhand State

NASA Astrophysics Data System (ADS)

Chandniha, Surendra Kumar; Meshram, Sarita Gajbhiye; Adamowski, Jan Franklin; Meshram, Chandrashekhar

2017-10-01

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901-2011) from 18 meteorological stations. Autocorrelation and Mann-Kendall/modified Mann-Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt-Mann-Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901-2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901-1949, which was reversed during the subsequent period (1950-2011).

Classification of the European Union member states according to the relative level of sustainable development.

PubMed

Anna, Bluszcz

Nowadays methods of measurement and assessment of the level of sustained development at the international, national and regional level are a current research problem, which requires multi-dimensional analysis. The relative assessment of the sustainability level of the European Union member states and the comparative analysis of the position of Poland relative to other countries was the aim of the conducted studies in the article. EU member states were treated as objects in the multi-dimensional space. Dimensions of space were specified by ten diagnostic variables describing the sustainability level of UE countries in three dimensions, i.e., social, economic and environmental. Because the compiled statistical data were expressed in different units of measure, taxonomic methods were used for building an aggregated measure to assess the level of sustainable development of EU member states, which through normalisation of variables enabled the comparative analysis between countries. Methodology of studies consisted of eight stages, which included, among others: defining data matrices, calculating the variability coefficient for all variables, which variability coefficient was under 10 %, division of variables into stimulants and destimulants, selection of the method of variable normalisation, developing matrices of normalised data, selection of the formula and calculating the aggregated indicator of the relative level of sustainable development of the EU countries, calculating partial development indicators for three studies dimensions: social, economic and environmental and the classification of the EU countries according to the relative level of sustainable development. Statistical date were collected based on the Polish Central Statistical Office publication.

Universal Quantum Computing with Measurement-Induced Continuous-Variable Gate Sequence in a Loop-Based Architecture.

PubMed

Takeda, Shuntaro; Furusawa, Akira

2017-09-22

We propose a scalable scheme for optical quantum computing using measurement-induced continuous-variable quantum gates in a loop-based architecture. Here, time-bin-encoded quantum information in a single spatial mode is deterministically processed in a nested loop by an electrically programmable gate sequence. This architecture can process any input state and an arbitrary number of modes with almost minimum resources, and offers a universal gate set for both qubits and continuous variables. Furthermore, quantum computing can be performed fault tolerantly by a known scheme for encoding a qubit in an infinite-dimensional Hilbert space of a single light mode.

Universal Quantum Computing with Measurement-Induced Continuous-Variable Gate Sequence in a Loop-Based Architecture

NASA Astrophysics Data System (ADS)

Takeda, Shuntaro; Furusawa, Akira

2017-09-01

We propose a scalable scheme for optical quantum computing using measurement-induced continuous-variable quantum gates in a loop-based architecture. Here, time-bin-encoded quantum information in a single spatial mode is deterministically processed in a nested loop by an electrically programmable gate sequence. This architecture can process any input state and an arbitrary number of modes with almost minimum resources, and offers a universal gate set for both qubits and continuous variables. Furthermore, quantum computing can be performed fault tolerantly by a known scheme for encoding a qubit in an infinite-dimensional Hilbert space of a single light mode.

Quantifying Landscape Spatial Pattern: What Is the State of the Art?

Treesearch

Eric J. Gustafson

1998-01-01

Landscape ecology is based on the premise that there are strong links between ecological pattern and ecological function and process. Ecological systems are spatially heterogeneous, exhibiting consid-erable complexity and variability in time and space. This variability is typically represented by categorical maps or by a collection of samples taken at specific spatial...

Special Education Directors' Views of Community-Based Vocational Instruction

ERIC Educational Resources Information Center

Pickens, Julie L.; Dymond, Stacy K.

2014-01-01

The purpose of this study was to investigate the views of special education directors toward community-based vocational instruction (CBVI). Participants included a non-proportional random sample of 47 directors from one state who completed an online or paper-based survey. Independent variables were directors' years of experience, geographic…

Development of design guidelines for proper selection of graded aggregate base in Maryland state highways : [research summary].

DOT National Transportation Integrated Search

2015-01-01

Millions of tons of graded aggregate base (GAB) materials are used in construction of : highway base layers in Maryland due to their satisfactory mechanical properties. The : fines content of a GAB material is highly variable and is often related to ...

Application of recurrence quantification analysis to automatically estimate infant sleep states using a single channel of respiratory data.

PubMed

Terrill, Philip I; Wilson, Stephen J; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

2012-08-01

Previous work has identified that non-linear variables calculated from respiratory data vary between sleep states, and that variables derived from the non-linear analytical tool recurrence quantification analysis (RQA) are accurate infant sleep state discriminators. This study aims to apply these discriminators to automatically classify 30 s epochs of infant sleep as REM, non-REM and wake. Polysomnograms were obtained from 25 healthy infants at 2 weeks, 3, 6 and 12 months of age, and manually sleep staged as wake, REM and non-REM. Inter-breath interval data were extracted from the respiratory inductive plethysmograph, and RQA applied to calculate radius, determinism and laminarity. Time-series statistic and spectral analysis variables were also calculated. A nested cross-validation method was used to identify the optimal feature subset, and to train and evaluate a linear discriminant analysis-based classifier. The RQA features radius and laminarity and were reliably selected. Mean agreement was 79.7, 84.9, 84.0 and 79.2 % at 2 weeks, 3, 6 and 12 months, and the classifier performed better than a comparison classifier not including RQA variables. The performance of this sleep-staging tool compares favourably with inter-human agreement rates, and improves upon previous systems using only respiratory data. Applications include diagnostic screening and population-based sleep research.

Smooth brome (Bromus inermis Leyss) response to concrete grinding residue application

USDA-ARS?s Scientific Manuscript database

Concrete grinding residue (CGR) is a slurry byproduct created by concrete pavement maintenance operations. The application of CGR to roadside soils is not consistently regulated by state agencies across the United States. Much of this variability in regulation may be due to the lack of science-base...

ESTIMATED EFFECTIVE CHIMNEY HEIGHTS BASED ON RAWINSONDE OBSERVATIONS AT SELECTED SITES IN THE UNITED STATES

EPA Science Inventory

The plume rise equations of Briggs (1975) for variable vertical profiles of temperature and wind speed are described and applied for hypothetical small and very large chimneys at five NWS rawinsonde stations across the United States. From other available data additional informati...

Prediction of Psilocybin Response in Healthy Volunteers

PubMed Central

Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X.

2012-01-01

Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin. PMID:22363492

Prediction of psilocybin response in healthy volunteers.

PubMed

Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X

2012-01-01

Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin.

A new adaptive estimation method of spacecraft thermal mathematical model with an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Akita, T.; Takaki, R.; Shima, E.

2012-04-01

An adaptive estimation method of spacecraft thermal mathematical model is presented. The method is based on the ensemble Kalman filter, which can effectively handle the nonlinearities contained in the thermal model. The state space equations of the thermal mathematical model is derived, where both temperature and uncertain thermal characteristic parameters are considered as the state variables. In the method, the thermal characteristic parameters are automatically estimated as the outputs of the filtered state variables, whereas, in the usual thermal model correlation, they are manually identified by experienced engineers using trial-and-error approach. A numerical experiment of a simple small satellite is provided to verify the effectiveness of the presented method.

Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

PubMed

Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

2018-05-30

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Dataset of timberland variables used to assess forest conditions in two Southeastern United States' fuelsheds

DOE PAGES

Parish, Esther S.; Dale, Virginia H.; Tobin, Emma; ...

2017-05-27

The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017). This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (FIA) data from multiple state inventories were aggregated and used to extract ten annual timberland variables for trend analysis in two case study bioenergy fuelshed areas. This dataset is made publically available to enable critical or extended analyses of changes in forest conditions, either for the fuelshed areas supplying the ports of Savannah, Georgia and Chesapeake, Virginia,more » or for other southeastern US forested areas contributing biomass to the export wood pellet industry.« less

Dataset of timberland variables used to assess forest conditions in two Southeastern United States' fuelsheds

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

Parish, Esther S.; Dale, Virginia H.; Tobin, Emma

The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017). This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (FIA) data from multiple state inventories were aggregated and used to extract ten annual timberland variables for trend analysis in two case study bioenergy fuelshed areas. This dataset is made publically available to enable critical or extended analyses of changes in forest conditions, either for the fuelshed areas supplying the ports of Savannah, Georgia and Chesapeake, Virginia,more » or for other southeastern US forested areas contributing biomass to the export wood pellet industry.« less

Predicting Power Outages Using Multi-Model Ensemble Forecasts

NASA Astrophysics Data System (ADS)

Cerrai, D.; Anagnostou, E. N.; Yang, J.; Astitha, M.

2017-12-01

Power outages affect every year millions of people in the United States, affecting the economy and conditioning the everyday life. An Outage Prediction Model (OPM) has been developed at the University of Connecticut for helping utilities to quickly restore outages and to limit their adverse consequences on the population. The OPM, operational since 2015, combines several non-parametric machine learning (ML) models that use historical weather storm simulations and high-resolution weather forecasts, satellite remote sensing data, and infrastructure and land cover data to predict the number and spatial distribution of power outages. A new methodology, developed for improving the outage model performances by combining weather- and soil-related variables using three different weather models (WRF 3.7, WRF 3.8 and RAMS/ICLAMS), will be presented in this study. First, we will present a performance evaluation of each model variable, by comparing historical weather analyses with station data or reanalysis over the entire storm data set. Hence, each variable of the new outage model version is extracted from the best performing weather model for that variable, and sensitivity tests are performed for investigating the most efficient variable combination for outage prediction purposes. Despite that the final variables combination is extracted from different weather models, this ensemble based on multi-weather forcing and multi-statistical model power outage prediction outperforms the currently operational OPM version that is based on a single weather forcing variable (WRF 3.7), because each model component is the closest to the actual atmospheric state.

Recurrence-plot-based measures of complexity and their application to heart-rate-variability data.

PubMed

Marwan, Norbert; Wessel, Niels; Meyerfeldt, Udo; Schirdewan, Alexander; Kurths, Jürgen

2002-08-01

The knowledge of transitions between regular, laminar or chaotic behaviors is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods that, however, require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart-rate-variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e., chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our measures to the heart-rate-variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.

Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches.

PubMed

Smith, David V; Utevsky, Amanda V; Bland, Amy R; Clement, Nathan; Clithero, John A; Harsch, Anne E W; McKell Carter, R; Huettel, Scott A

2014-07-15

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust-yet frequently ignored-neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Reality of delusion: migrant perception of levels of living and opportunity in Venezuela, 1961-1971.

PubMed

Eastwood, D A

1983-07-01

To facilitate comparison of how well migrant perceptions may have accorded with reality and of the effects of that migration between 1961-71 may have had on relative regional development in Venezuela, a composite index based on state census data must be constructed by which the country's overall levels of living and social well being can be examined. The index constructed was loosely based on a range of variables suggested by Knox, but with the specific selected variables restricted by those data available in the Venezuelan censuses and other institutional reports. 20 variables were selected. Using these variables, a composite index of levels of living and social well being was constructed. The resultant index (S scores) for each state in 1971 appear in a table and a figure. These S scores demonstrated the relatively higher levels of living in the northern core area around Caracas, with S scores of over 200 in the Federal District and Miranda State. Ripple effects from the northern core also produced high scores in Aragua and Caraboba states. Secondary centers of relative prosperity were Zulia in the west and Bolivar in the east. The traditional Andean population centers in Tachira and Merida also scored positively. In contrast low S scores were found in a central belt of rural states. Lowest scores of all were in the states of Apure and Barinas, isolated on the southern margins of the central belt. Overall, the 1971 S scores decreased as distance from Caracas increased and clearly illustrated Venezuela's acute core/periphery imbalance. Despite the very substantial migration throughout the 1961-71 period, with only minor exceptions, the level of living pattern was essentially static, as a comparison of 1961 and 1971 reveals. Only the states of Bolivar (because of Guayanese industrial growth) and Nueva Esparata (because of its designation as a free port) showed significant 1961-71 improvement in state rankings; only Cojedes and Falcon (for unknown reasons) had significant decline. S scores clearly remained higher in the less rural states. In general, the majority of migration was toward those states with the higher S scores, and the high S scores correlated strongly and positively with net 1961-71 migration. The broad migrant perception of where potentially better overall conditions were likely to be found appeared to be largely accurate. When this overall picture was reduced to specific variables, the reality of migrant perception became less clear. Migrants tended to move not only to where wages were higher but also to where unemployment was higher.

Optimal control in microgrid using multi-agent reinforcement learning.

PubMed

Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin

2012-11-01

This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Impact damage resistance of composite fuselage structure, part 1

NASA Technical Reports Server (NTRS)

Dost, E. F.; Avery, W. B.; Ilcewicz, L. B.; Grande, D. H.; Coxon, B. R.

1992-01-01

The impact damage resistance of laminated composite transport aircraft fuselage structures was studied experimentally. A statistically based designed experiment was used to examine numerous material, laminate, structural, and extrinsic (e.g., impactor type) variables. The relative importance and quantitative measure of the effect of each variable and variable interactions on responses including impactor dynamic response, visibility, and internal damage state were determined. The study utilized 32 three-stiffener panels, each with a unique combination of material type, material forms, and structural geometry. Two manufacturing techniques, tow placement and tape lamination, were used to build panels representative of potential fuselage crown, keel, and lower side-panel designs. Various combinations of impactor variables representing various foreign-object-impact threats to the aircraft were examined. Impacts performed at different structural locations within each panel (e.g., skin midbay, stiffener attaching flange, etc.) were considered separate parallel experiments. The relationship between input variables, measured damage states, and structural response to this damage are presented including recommendations for materials and impact test methods for fuselage structure.

A Hierarchical Modulation Coherent Communication Scheme for Simultaneous Four-State Continuous-Variable Quantum Key Distribution and Classical Communication

NASA Astrophysics Data System (ADS)

Yang, Can; Ma, Cheng; Hu, Linxi; He, Guangqiang

2018-06-01

We present a hierarchical modulation coherent communication protocol, which simultaneously achieves classical optical communication and continuous-variable quantum key distribution. Our hierarchical modulation scheme consists of a quadrature phase-shifting keying modulation for classical communication and a four-state discrete modulation for continuous-variable quantum key distribution. The simulation results based on practical parameters show that it is feasible to transmit both quantum information and classical information on a single carrier. We obtained a secure key rate of 10^{-3} bits/pulse to 10^{-1} bits/pulse within 40 kilometers, and in the meantime the maximum bit error rate for classical information is about 10^{-7}. Because continuous-variable quantum key distribution protocol is compatible with standard telecommunication technology, we think our hierarchical modulation scheme can be used to upgrade the digital communication systems to extend system function in the future.

Kalman filters for assimilating near-surface observations in the Richards equation - Part 2: A dual filter approach for simultaneous retrieval of states and parameters

NASA Astrophysics Data System (ADS)

Medina, H.; Romano, N.; Chirico, G. B.

2012-12-01

We present a dual Kalman Filter (KF) approach for retrieving states and parameters controlling soil water dynamics in a homogenous soil column by using near-surface state observations. The dual Kalman filter couples a standard KF algorithm for retrieving the states and an unscented KF algorithm for retrieving the parameters. We examine the performance of the dual Kalman Filter applied to two alternative state-space formulations of the Richards equation, respectively differentiated by the type of variable employed for representing the states: either the soil water content (θ) or the soil matric pressure head (h). We use a synthetic time-series series of true states and noise corrupted observations and a synthetic time-series of meteorological forcing. The performance analyses account for the effect of the input parameters, the observation depth and the assimilation frequency as well as the relationship between the retrieved states and the assimilated variables. We show that the identifiability of the parameters is strongly conditioned by several factors, such as the initial guess of the unknown parameters, the wet or dry range of the retrieved states, the boundary conditions, as well as the form (h-based or θ-based) of the state-space formulation. State identifiability is instead efficient even with a relatively coarse time-resolution of the assimilated observation. The accuracy of the retrieved states exhibits limited sensitivity to the observation depth and the assimilation frequency.

Study on the variable cycle engine modeling techniques based on the component method

NASA Astrophysics Data System (ADS)

Zhang, Lihua; Xue, Hui; Bao, Yuhai; Li, Jijun; Yan, Lan

2016-01-01

Based on the structure platform of the gas turbine engine, the components of variable cycle engine were simulated by using the component method. The mathematical model of nonlinear equations correspondeing to each component of the gas turbine engine was established. Based on Matlab programming, the nonlinear equations were solved by using Newton-Raphson steady-state algorithm, and the performance of the components for engine was calculated. The numerical simulation results showed that the model bulit can describe the basic performance of the gas turbine engine, which verified the validity of the model.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

DOE PAGES

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.; ...

2017-01-01

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution.

PubMed

Cai, Hong; Long, Christopher M; DeRose, Christopher T; Boynton, Nicholas; Urayama, Junji; Camacho, Ryan; Pomerene, Andrew; Starbuck, Andrew L; Trotter, Douglas C; Davids, Paul S; Lentine, Anthony L

2017-05-29

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

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

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Automatic classifier based on heart rate variability to identify fallers among hypertensive subjects.

PubMed

Melillo, Paolo; Jovic, Alan; De Luca, Nicola; Pecchia, Leandro

2015-08-01

Accidental falls are a major problem of later life. Different technologies to predict falls have been investigated, but with limited success, mainly because of low specificity due to a high false positive rate. This Letter presents an automatic classifier based on heart rate variability (HRV) analysis with the goal to identify fallers automatically. HRV was used in this study as it is considered a good estimator of autonomic nervous system (ANS) states, which are responsible, among other things, for human balance control. Nominal 24 h electrocardiogram recordings from 168 cardiac patients (age 72 ± 8 years, 60 female), of which 47 were fallers, were investigated. Linear and nonlinear HRV properties were analysed in 30 min excerpts. Different data mining approaches were adopted and their performances were compared with a subject-based receiver operating characteristic analysis. The best performance was achieved by a hybrid algorithm, RUSBoost, integrated with feature selection method based on principal component analysis, which achieved satisfactory specificity and accuracy (80 and 72%, respectively), but low sensitivity (51%). These results suggested that ANS states causing falls could be reliably detected, but also that not all the falls were due to ANS states.

Five-wave-packet quantum error correction based on continuous-variable cluster entanglement

PubMed Central

Hao, Shuhong; Su, Xiaolong; Tian, Caixing; Xie, Changde; Peng, Kunchi

2015-01-01

Quantum error correction protects the quantum state against noise and decoherence in quantum communication and quantum computation, which enables one to perform fault-torrent quantum information processing. We experimentally demonstrate a quantum error correction scheme with a five-wave-packet code against a single stochastic error, the original theoretical model of which was firstly proposed by S. L. Braunstein and T. A. Walker. Five submodes of a continuous variable cluster entangled state of light are used for five encoding channels. Especially, in our encoding scheme the information of the input state is only distributed on three of the five channels and thus any error appearing in the remained two channels never affects the output state, i.e. the output quantum state is immune from the error in the two channels. The stochastic error on a single channel is corrected for both vacuum and squeezed input states and the achieved fidelities of the output states are beyond the corresponding classical limit. PMID:26498395

Analytical study of bound states in graphene nanoribbons and carbon nanotubes: The variable phase method and the relativistic Levinson theorem

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

Miserev, D. S., E-mail: d.miserev@student.unsw.edu.au, E-mail: erazorheader@gmail.com

2016-06-15

The problem of localized states in 1D systems with a relativistic spectrum, namely, graphene stripes and carbon nanotubes, is studied analytically. The bound state as a superposition of two chiral states is completely described by their relative phase, which is the foundation of the variable phase method (VPM) developed herein. Based on our VPM, we formulate and prove the relativistic Levinson theorem. The problem of bound states can be reduced to the analysis of closed trajectories of some vector field. Remarkably, the Levinson theorem appears as the Poincaré index theorem for these closed trajectories. The VPM equation is also reducedmore » to the nonrelativistic and semiclassical limits. The limit of a small momentum p{sub y} of transverse quantization is applicable to an arbitrary integrable potential. In this case, a single confined mode is predicted.« less

Variable-rate optical communication through the turbulent atmosphere. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Levitt, B. K.

1971-01-01

It was demonstrated that the data transmitter can extract real time, channel state information by processing the field received when a pilot tone is sent from the data receiver to the data transmitter. Based on these channel measurements, optimal variable rate techniques were derived and significant improvements in system perforamnce were obtained, particularly at low bit error rates.

Finite element implementation of state variable-based viscoplasticity models

NASA Technical Reports Server (NTRS)

Iskovitz, I.; Chang, T. Y. P.; Saleeb, A. F.

1991-01-01

The implementation of state variable-based viscoplasticity models is made in a general purpose finite element code for structural applications of metals deformed at elevated temperatures. Two constitutive models, Walker's and Robinson's models, are studied in conjunction with two implicit integration methods: the trapezoidal rule with Newton-Raphson iterations and an asymptotic integration algorithm. A comparison is made between the two integration methods, and the latter method appears to be computationally more appealing in terms of numerical accuracy and CPU time. However, in order to make the asymptotic algorithm robust, it is necessary to include a self adaptive scheme with subincremental step control and error checking of the Jacobian matrix at the integration points. Three examples are given to illustrate the numerical aspects of the integration methods tested.

A Monte Carlo Analysis of the Thrust Imbalance for the RSRMV Booster During Both the Ignition Transient and Steady State Operation

NASA Technical Reports Server (NTRS)

Foster, Winfred A., Jr.; Crowder, Winston; Steadman, Todd E.

2014-01-01

This paper presents the results of statistical analyses performed to predict the thrust imbalance between two solid rocket motor boosters to be used on the Space Launch System (SLS) vehicle. Two legacy internal ballistics codes developed for the Space Shuttle program were coupled with a Monte Carlo analysis code to determine a thrust imbalance envelope for the SLS vehicle based on the performance of 1000 motor pairs. Thirty three variables which could impact the performance of the motors during the ignition transient and thirty eight variables which could impact the performance of the motors during steady state operation of the motor were identified and treated as statistical variables for the analyses. The effects of motor to motor variation as well as variations between motors of a single pair were included in the analyses. The statistical variations of the variables were defined based on data provided by NASA's Marshall Space Flight Center for the upgraded five segment booster and from the Space Shuttle booster when appropriate. The results obtained for the statistical envelope are compared with the design specification thrust imbalance limits for the SLS launch vehicle

A Monte Carlo Analysis of the Thrust Imbalance for the Space Launch System Booster During Both the Ignition Transient and Steady State Operation

NASA Technical Reports Server (NTRS)

Foster, Winfred A., Jr.; Crowder, Winston; Steadman, Todd E.

2014-01-01

This paper presents the results of statistical analyses performed to predict the thrust imbalance between two solid rocket motor boosters to be used on the Space Launch System (SLS) vehicle. Two legacy internal ballistics codes developed for the Space Shuttle program were coupled with a Monte Carlo analysis code to determine a thrust imbalance envelope for the SLS vehicle based on the performance of 1000 motor pairs. Thirty three variables which could impact the performance of the motors during the ignition transient and thirty eight variables which could impact the performance of the motors during steady state operation of the motor were identified and treated as statistical variables for the analyses. The effects of motor to motor variation as well as variations between motors of a single pair were included in the analyses. The statistical variations of the variables were defined based on data provided by NASA's Marshall Space Flight Center for the upgraded five segment booster and from the Space Shuttle booster when appropriate. The results obtained for the statistical envelope are compared with the design specification thrust imbalance limits for the SLS launch vehicle.

Variable-Resistivity Material For Memory Circuits

NASA Technical Reports Server (NTRS)

Nagasubramanian, Ganesan; Distefano, Salvador; Moacanin, Jovan

1989-01-01

Nonvolatile memory elements packed densely. Electrically-erasable, programmable, read-only memory matrices made with newly-synthesized organic material of variable electrical resistivity. Material, polypyrrole doped with tetracyanoquinhydrone (TCNQ), changes reversibly between insulating or higher-resistivity state and conducting or low-resistivity state. Thin film of conductive polymer separates layer of row conductors from layer of column conductors. Resistivity of film at each intersection and, therefore, resistance of memory element defined by row and column, increased or decreased by application of suitable switching voltage. Matrix circuits made with this material useful for experiments in associative electronic memories based on models of neural networks.

Performance-Based Compensation: Focus on Special Education Teachers. inForum

ERIC Educational Resources Information Center

Burdette, Paula

2011-01-01

The purpose of this document is to describe states' work in the area of performance-based compensation with a focus on special educators, including how teacher evaluation informs compensation decisions, support given to local education agencies (LEAs), variables used to make compensation decisions and how performance-based compensation is funded.…

Characterizing Uncertainty and Variability in PBPK Models: State of the Science and Needs for Research and Implementation

EPA Science Inventory

Mode-of-action based risk and safety assessments can rely upon tissue dosimetry estimates in animals and humans obtained from physiologically-based pharmacokinetic (PBPK) modeling. However, risk assessment also increasingly requires characterization of uncertainty and variabilit...

Economic factors influencing land use changes in the South-Central United States

Treesearch

Ralph J. Alig; Fred C. White; Brian C. Murray

1988-01-01

Econometric models of land use change were estimated for two physiographic regions in the South-Central United States. Results are consistent-with the economic hierarchy of land use, with population and personal income being significant explanatory variables. Findings regarding the importance of relative agricultural and forestry market-based incomes in influencing...

Teaching, Academic Achievement, and Attitudes toward Mathematics in the United States and Nigeria

ERIC Educational Resources Information Center

Perry, S. Marshall; Catapano, Michael; Ramon, Olosunde Gbolagade

2016-01-01

This paper explores the relationships among attitudes toward mathematics, teaching, and academic achievement in mathematics. Based on the contextual and social nature of academic self-concept, two complementary studies are discussed. The first study from the northeastern United States examined the relationships among these variables in 84 high…

Centrifugal compressor fault diagnosis based on qualitative simulation and thermal parameters

NASA Astrophysics Data System (ADS)

Lu, Yunsong; Wang, Fuli; Jia, Mingxing; Qi, Yuanchen

2016-12-01

This paper concerns fault diagnosis of centrifugal compressor based on thermal parameters. An improved qualitative simulation (QSIM) based fault diagnosis method is proposed to diagnose the faults of centrifugal compressor in a gas-steam combined-cycle power plant (CCPP). The qualitative models under normal and two faulty conditions have been built through the analysis of the principle of centrifugal compressor. To solve the problem of qualitative description of the observations of system variables, a qualitative trend extraction algorithm is applied to extract the trends of the observations. For qualitative states matching, a sliding window based matching strategy which consists of variables operating ranges constraints and qualitative constraints is proposed. The matching results are used to determine which QSIM model is more consistent with the running state of system. The correct diagnosis of two typical faults: seal leakage and valve stuck in the centrifugal compressor has validated the targeted performance of the proposed method, showing the advantages of fault roots containing in thermal parameters.

Manticore and CS mode : parallelizable encryption with joint cipher-state authentication.

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

Torgerson, Mark Dolan; Draelos, Timothy John; Schroeppel, Richard Crabtree

2004-10-01

We describe a new mode of encryption with inexpensive authentication, which uses information from the internal state of the cipher to provide the authentication. Our algorithms have a number of benefits: (1) the encryption has properties similar to CBC mode, yet the encipherment and authentication can be parallelized and/or pipelined, (2) the authentication overhead is minimal, and (3) the authentication process remains resistant against some IV reuse. We offer a Manticore class of authenticated encryption algorithms based on cryptographic hash functions, which support variable block sizes up to twice the hash output length and variable key lengths. A proof ofmore » security is presented for the MTC4 and Pepper algorithms. We then generalize the construction to create the Cipher-State (CS) mode of encryption that uses the internal state of any round-based block cipher as an authenticator. We provide hardware and software performance estimates for all of our constructions and give a concrete example of the CS mode of encryption that uses AES as the encryption primitive and adds a small speed overhead (10-15%) compared to AES alone.« less

Continuous operation of four-state continuous-variable quantum key distribution system

NASA Astrophysics Data System (ADS)

Matsubara, Takuto; Ono, Motoharu; Oguri, Yusuke; Ichikawa, Tsubasa; Hirano, Takuya; Kasai, Kenta; Matsumoto, Ryutaroh; Tsurumaru, Toyohiro

2016-10-01

We report on the development of continuous-variable quantum key distribution (CV-QKD) system that are based on discrete quadrature amplitude modulation (QAM) and homodyne detection of coherent states of light. We use a pulsed light source whose wavelength is 1550 nm and repetition rate is 10 MHz. The CV-QKD system can continuously generate secret key which is secure against entangling cloner attack. Key generation rate is 50 kbps when the quantum channel is a 10 km optical fiber. The CV-QKD system we have developed utilizes the four-state and post-selection protocol [T. Hirano, et al., Phys. Rev. A 68, 042331 (2003).]; Alice randomly sends one of four states {|+/-α⟩,|+/-𝑖α⟩}, and Bob randomly performs x- or p- measurement by homodyne detection. A commercially available balanced receiver is used to realize shot-noise-limited pulsed homodyne detection. GPU cards are used to accelerate the software-based post-processing. We use a non-binary LDPC code for error correction (reverse reconciliation) and the Toeplitz matrix multiplication for privacy amplification.

Flatness-based control in successive loops for stabilization of heart's electrical activity

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Melkikh, Alexey

2016-12-01

The article proposes a new flatness-based control method implemented in successive loops which allows for stabilization of the heart's electrical activity. Heart's pacemaking function is modeled as a set of coupled oscillators which potentially can exhibit chaotic behavior. It is shown that this model satisfies differential flatness properties. Next, the control and stabilization of this model is performed with the use of flatness-based control implemented in cascading loops. By applying a per-row decomposition of the state-space model of the coupled oscillators a set of nonlinear differential equations is obtained. Differential flatness properties are shown to hold for the subsystems associated with the each one of the aforementioned differential equations and next a local flatness-based controller is designed for each subsystem. For the i-th subsystem, state variable xi is chosen to be the flat output and state variable xi+1 is taken to be a virtual control input. Then the value of the virtual control input which eliminates the output tracking error for the i-th subsystem becomes reference setpoint for the i + 1-th subsystem. In this manner the control of the entire state-space model is performed by successive flatness-based control loops. By arriving at the n-th row of the state-space model one computes the control input that can be actually exerted on the aforementioned biosystem. This real control input of the coupled oscillators' system, contains recursively all virtual control inputs associated with the previous n - 1 rows of the state-space model. This control approach achieves asymptotically the elimination of the chaotic oscillation effects and the stabilization of the heart's pulsation rhythm. The stability of the proposed control scheme is proven with the use of Lyapunov analysis.

Spinning Spacecraft Attitude Estimation Using Markley Variables: Filter Implementation And Results

NASA Technical Reports Server (NTRS)

Sedlak, Joseph E.

2005-01-01

Attitude estimation is often more difficult for spinning spacecraft than for three-axis stabilized platforms due to the need to follow rapidly-varying state vector elements and the lack of three-axis rate measurements from gyros. The estimation problem simplifies when torques are negligible and nutation has damped out, but the general case requires a sequential filter with dynamics propagation. This paper describes the implementation and test results for an extended Kalman filter for spinning spacecraft attitude and rate estimation based on a novel set of variables suggested in a paper by Markley [AAS93-3301 (referred to hereafter as Markley variables). Markley has demonstrated that the new set of variables provides a superior parameterization for numerical integration of the attitude dynamics for spinning or momentum-biased spacecraft. The advantage is that the Markley variables have fewer rapidly-varying elements than other representations such as the attitude quaternion and rate vector. A filter based on these variables was expected to show improved performance due to the more accurate numerical state propagation. However, for a variety of test cases, it has been found that the new filter, as currently implemented, does not perform significantly better than a quaternion-based filter that was developed and tested in parallel. This paper reviews the mathematical background for a filter based on Markley variables. It also describes some features of the implementation and presents test results. The test cases are based on a mission using magnetometer and Sun sensor data and gyro measurements on two axes normal to the spin axis. The orbit and attitude scenarios and spacecraft parameters are modeled after one of the THEMIS (Time History of Events and Macroscale Interactions during Substorms) probes. Several tests are presented that demonstrate the filter accuracy and convergence properties. The tests include torque-free motion with various nutation angles, large constant-torque attitude slews, sensor misalignments, large initial attitude and rate errors, and cases with low data frequency. It is found that the convergence is rapid, the radius of convergence is large, and the results are reasonably accurate even in the presence of unmodeled perturbations.

Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India.

PubMed

Kumar, Rajesh; Dash, Chinmaya; Rani, Khushbu

2017-09-01

Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover ( p  < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.

Unemployment and mortality among Finnish men, 1981-5.

PubMed Central

Martikainen, P T

1990-01-01

OBJECTIVE--To ascertain whether, after controlling for several relevant background variables simultaneously, unemployment is related to mortality and to assess whether this relation is causal or whether unhealthy people are more likely to become unemployed. DESIGN--Prospective study of mortality in Finland during 1981-5 based on 1980 census data on 30-54 year old wage earner men and with particular attention to unemployment in the year before the census. SETTING--Research project at the University of Helsinki. SUBJECTS--All wage earner men in Finland aged 30-54 at the 1980 census. MAIN OUTCOME MEASURES--Causes of death during 1981-5 and duration of unemployment in the year before the census. Background variables controlled for were age, socioeconomic state, marital state, and health. The data were analysed by log linear regression models. RESULTS--During the study period 1981-5, which covered almost 2.7 million person years, there were 9810 deaths. After controlling for all background variables relative total mortality among unemployed versus employed men was 1.93 (95% confidence interval 1.82 to 2.05). The excess mortality was highest in accidental and violent causes of death (relative mortality 2.51; 95% confidence interval 2.28 to 2.76). For circulatory diseases the relative death rate was 1.54 (95% confidence interval 1.40 to 1.70), but among neoplasms only lung cancer was associated with excess mortality. Selection for unemployment based on age, socioeconomic state, and marital state was evident but no such selection was detected based on health. Effects of unemployment on mortality were more pronounced with increasing duration of unemployment. CONCLUSIONS--The relative excess mortality of unemployed men in Finland cannot fully be explained by demographic, social, and health variables preceding unemployment. Unemployment therefore seems to have an independent causal effect on male mortality. Further studies are needed to elucidate the mechanisms between unemployment and mortality. PMID:2282395

Variability in interhospital trauma data coding and scoring: A challenge to the accuracy of aggregated trauma registries.

PubMed

Arabian, Sandra S; Marcus, Michael; Captain, Kevin; Pomphrey, Michelle; Breeze, Janis; Wolfe, Jennefer; Bugaev, Nikolay; Rabinovici, Reuven

2015-09-01

Analyses of data aggregated in state and national trauma registries provide the platform for clinical, research, development, and quality improvement efforts in trauma systems. However, the interhospital variability and accuracy in data abstraction and coding have not yet been directly evaluated. This multi-institutional, Web-based, anonymous study examines interhospital variability and accuracy in data coding and scoring by registrars. Eighty-two American College of Surgeons (ACS)/state-verified Level I and II trauma centers were invited to determine different data elements including diagnostic, procedure, and Abbreviated Injury Scale (AIS) coding as well as selected National Trauma Data Bank definitions for the same fictitious case. Variability and accuracy in data entries were assessed by the maximal percent agreement among the registrars for the tested data elements, and 95% confidence intervals were computed to compare this level of agreement to the ideal value of 100%. Variability and accuracy in all elements were compared (χ testing) based on Trauma Quality Improvement Program (TQIP) membership, level of trauma center, ACS verification, and registrar's certifications. Fifty registrars (61%) completed the survey. The overall accuracy for all tested elements was 64%. Variability was noted in all examined parameters except for the place of occurrence code in all groups and the lower extremity AIS code in Level II trauma centers and in the Certified Specialist in Trauma Registry- and Certified Abbreviated Injury Scale Specialist-certified registrar groups. No differences in variability were noted when groups were compared based on TQIP membership, level of center, ACS verification, and registrar's certifications, except for prehospital Glasgow Coma Scale (GCS), where TQIP respondents agreed more than non-TQIP centers (p = 0.004). There is variability and inaccuracy in interhospital data coding and scoring of injury information. This finding casts doubt on the validity of registry data used in all aspects of trauma care and injury surveillance.

Casemix funding for acute hospital inpatient services in Australia.

PubMed

Duckett, S J

1998-10-19

Casemix funding was introduced first in Victoria in 1993-94, and since then most States have moved towards either casemix funding or using casemix to inform the budget setting process. The five States implementing casemix have adopted some common funding elements: all use AN-DRG-3; all have introduced capping, msot commonly at the hospital level; and all ensure accuracy of diagnosis and procedure coding through coding audits. Two funding models have been developed. The fixed and variable model involves a fixed grant for hospital overhead costs and a payment for each patient treated, covering only variable costs. The integrated model provides an integrated payment to hospitals for each patient treated, covering both the fixed and variable costs. There are different weight setting processes and base prices between the States, which result in marked differences in the price paid for the same type of case treated in similar hospitals. Learning across State boundaries should be encouraged, with knowledge of what is effective and what is ineffective in casemix funding arrangements being used to develop Australian best practice in this area.

Uncertainty relation for the discrete Fourier transform.

PubMed

Massar, Serge; Spindel, Philippe

2008-05-16

We derive an uncertainty relation for two unitary operators which obey a commutation relation of the form UV=e(i phi) VU. Its most important application is to constrain how much a quantum state can be localized simultaneously in two mutually unbiased bases related by a discrete fourier transform. It provides an uncertainty relation which smoothly interpolates between the well-known cases of the Pauli operators in two dimensions and the continuous variables position and momentum. This work also provides an uncertainty relation for modular variables, and could find applications in signal processing. In the finite dimensional case the minimum uncertainty states, discrete analogues of coherent and squeezed states, are minimum energy solutions of Harper's equation, a discrete version of the harmonic oscillator equation.

RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

PubMed

Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

2015-09-03

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

Internal state variable plasticity-damage modeling of AISI 4140 steel including microstructure-property relations: temperature and strain rate effects

NASA Astrophysics Data System (ADS)

Nacif el Alaoui, Reda

Mechanical structure-property relations have been quantified for AISI 4140 steel. under different strain rates and temperatures. The structure-property relations were used. to calibrate a microstructure-based internal state variable plasticity-damage model for. monotonic tension, compression and torsion plasticity, as well as damage evolution. Strong stress state and temperature dependences were observed for the AISI 4140 steel. Tension tests on three different notched Bridgman specimens were undertaken to study. the damage-triaxiality dependence for model validation purposes. Fracture surface. analysis was performed using Scanning Electron Microscopy (SEM) to quantify the void. nucleation and void sizes in the different specimens. The stress-strain behavior exhibited. a fairly large applied stress state (tension, compression dependence, and torsion), a. moderate temperature dependence, and a relatively small strain rate dependence.

Newtonian Nudging For A Richards Equation-based Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

Paniconi, C.; Marrocu, M.; Putti, M.; Verbunt, M.

In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimila- tion scheme. Nudging is shown to be successful in improving the hydrological sim- ulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitiv- ity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexi- ble, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be read- ily extended to any features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation techniques in a Richards equation-based hydrological model.

Building state capacity in Russia: A case study of energy sector reform, 1992--1998

NASA Astrophysics Data System (ADS)

Kim, Younkyoo

This study seeks an explanation for the neglect of state building in Russia. The major hypothesis is that dependence on external rent leads to the weakness of the state. Three intervening variables---transaction costs, bargaining power of the state, and discount rates---are posited to explain variance on the dependent variable, the weakness of the state. Based on the exploration of three dimensions of energy sector reform, the dissertation argues that in the short run resource rents may be the only reliable and adequate source of finance for the Russian government. The division of resource rents among the many claimants (state vs. business, state vs. society, Moscow vs. regions, and Russia vs. foreign companies), it submits, will pose a stringent test of the viability of democratic governance in Russia. The dissertation concludes that some evidence indicates that Russia has in fact met the characteristics of the rentier state. The greater reliance on a large resource sector for revenue has led to high transaction costs of tax collection, weak bargaining power of the state, and high discount rates of government officials in Russia.

Empirical Assessment of Spatial Prediction Methods for Location Cost Adjustment Factors

PubMed Central

Migliaccio, Giovanni C.; Guindani, Michele; D'Incognito, Maria; Zhang, Linlin

2014-01-01

In the feasibility stage, the correct prediction of construction costs ensures that budget requirements are met from the start of a project's lifecycle. A very common approach for performing quick-order-of-magnitude estimates is based on using Location Cost Adjustment Factors (LCAFs) that compute historically based costs by project location. Nowadays, numerous LCAF datasets are commercially available in North America, but, obviously, they do not include all locations. Hence, LCAFs for un-sampled locations need to be inferred through spatial interpolation or prediction methods. Currently, practitioners tend to select the value for a location using only one variable, namely the nearest linear-distance between two sites. However, construction costs could be affected by socio-economic variables as suggested by macroeconomic theories. Using a commonly used set of LCAFs, the City Cost Indexes (CCI) by RSMeans, and the socio-economic variables included in the ESRI Community Sourcebook, this article provides several contributions to the body of knowledge. First, the accuracy of various spatial prediction methods in estimating LCAF values for un-sampled locations was evaluated and assessed in respect to spatial interpolation methods. Two Regression-based prediction models were selected, a Global Regression Analysis and a Geographically-weighted regression analysis (GWR). Once these models were compared against interpolation methods, the results showed that GWR is the most appropriate way to model CCI as a function of multiple covariates. The outcome of GWR, for each covariate, was studied for all the 48 states in the contiguous US. As a direct consequence of spatial non-stationarity, it was possible to discuss the influence of each single covariate differently from state to state. In addition, the article includes a first attempt to determine if the observed variability in cost index values could be, at least partially explained by independent socio-economic variables. PMID:25018582

Simulated lumped-parameter system reduced-order adaptive control studies

NASA Technical Reports Server (NTRS)

Johnson, C. R., Jr.; Lawrence, D. A.; Taylor, T.; Malakooti, M. V.

1981-01-01

Two methods of interpreting the misbehavior of reduced order adaptive controllers are discussed. The first method is based on system input-output description and the second is based on state variable description. The implementation of the single input, single output, autoregressive, moving average system is considered.

Quantum annealing with parametrically driven nonlinear oscillators

NASA Astrophysics Data System (ADS)

Puri, Shruti

While progress has been made towards building Ising machines to solve hard combinatorial optimization problems, quantum speedups have so far been elusive. Furthermore, protecting annealers against decoherence and achieving long-range connectivity remain important outstanding challenges. With the hope of overcoming these challenges, I introduce a new paradigm for quantum annealing that relies on continuous variable states. Unlike the more conventional approach based on two-level systems, in this approach, quantum information is encoded in two coherent states that are stabilized by parametrically driving a nonlinear resonator. I will show that a fully connected Ising problem can be mapped onto a network of such resonators, and outline an annealing protocol based on adiabatic quantum computing. During the protocol, the resonators in the network evolve from vacuum to coherent states representing the ground state configuration of the encoded problem. In short, the system evolves between two classical states following non-classical dynamics. As will be supported by numerical results, this new annealing paradigm leads to superior noise resilience. Finally, I will discuss a realistic circuit QED realization of an all-to-all connected network of parametrically driven nonlinear resonators. The continuous variable nature of the states in the large Hilbert space of the resonator provides new opportunities for exploring quantum phase transitions and non-stoquastic dynamics during the annealing schedule.

Physiological state characterization by clustering heart rate, heart rate variability and movement activity information.

PubMed

Bidargaddi, Niranjan; Sarela, Antti; Korhonen, Ilkka

2008-01-01

The objective is to identify whether it is possible to discriminate between normal and abnormal physiological state based on heart rate (HR), heart rate variability (HRV) and movement activity information in subjects with cardiovascular complications. HR, HRV and movement information were obtained from cardiac patients over a period of 6 weeks using an ambulatory activity and single lead ECG monitor. By applying k-means clustering on HR, HRV and movement information obtained from cardiac patients, we obtained 3 clusters in inactive state and one cluster in active state. Two clusters in inactive state characterized by - a) high HR and low HRV b) low HRV and low HR, could be inferred as pathological with abnormal autonomic function. Further, activity information was significant in differentiating between the normal cluster found in active and an abnormal cluster found in inactive states, both with low HRV. This indicates that the activity information must be taken into account while interpreting HR and HRV information.

Stability of uncertain impulsive complex-variable chaotic systems with time-varying delays.

PubMed

Zheng, Song

2015-09-01

In this paper, the robust exponential stabilization of uncertain impulsive complex-variable chaotic delayed systems is considered with parameters perturbation and delayed impulses. It is assumed that the considered complex-variable chaotic systems have bounded parametric uncertainties together with the state variables on the impulses related to the time-varying delays. Based on the theories of adaptive control and impulsive control, some less conservative and easily verified stability criteria are established for a class of complex-variable chaotic delayed systems with delayed impulses. Some numerical simulations are given to validate the effectiveness of the proposed criteria of impulsive stabilization for uncertain complex-variable chaotic delayed systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Influence of Strategy of Learning and Achievement Motivation of Learning Achievement Class VIII Students of State Junior High School in District Blitar

ERIC Educational Resources Information Center

Ayundawati, Dyah; Setyosari, Punaji; Susilo, Herawati; Sihkabuden

2016-01-01

This study aims for know influence of problem-based learning strategies and achievement motivation on learning achievement. The method used in this research is quantitative method. The instrument used in this study is two fold instruments to measure moderator variable (achievement motivation) and instruments to measure the dependent variable (the…

Effects of climatic variability and change on forest ecosystems: a comprehensive science synthesis for the U.S

Treesearch

James M. Vose; David L. Peterson; Toral Patel-Weynand

2012-01-01

This report is a scientific assessment of the current condition and likely future condition of forest resources in the United States relative to climatic variability and change. It serves as the U.S. Forest Service forest sector technical report for the National Climate Assessment and includes descriptions of key regional issues and examples of a risk-based framework...

Synchronization of chaotic systems involving fractional operators of Liouville-Caputo type with variable-order

NASA Astrophysics Data System (ADS)

Coronel-Escamilla, A.; Gómez-Aguilar, J. F.; Torres, L.; Escobar-Jiménez, R. F.; Valtierra-Rodríguez, M.

2017-12-01

In this paper, we propose a state-observer-based approach to synchronize variable-order fractional (VOF) chaotic systems. In particular, this work is focused on complete synchronization with a so-called unidirectional master-slave topology. The master is described by a dynamical system in state-space representation whereas the slave is described by a state observer. The slave is composed of a master copy and a correction term which in turn is constituted of an estimation error and an appropriate gain that assures the synchronization. The differential equations of the VOF chaotic system are described by the Liouville-Caputo and Atangana-Baleanu-Caputo derivatives. Numerical simulations involving the synchronization of Rössler oscillators, Chua's systems and multi-scrolls are studied. The simulations show that different chaotic behaviors can be obtained if different smooths functions defined in the interval (0 , 1 ] are used as the variable order of the fractional derivatives. Furthermore, simulations show that the VOF chaotic systems can be synchronized.

Tropical Ocean Surface Energy Balance Variability: Linking Weather to Climate Scales

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Clayson, Carol Anne

2013-01-01

Radiative and turbulent surface exchanges of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing the spatiotemporal variability of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. These fluxes are integral components to tropical ocean-atmosphere variability; they can drive ocean mixed layer variations and modify the atmospheric boundary layer properties including moist static stability, thereby influencing larger-scale tropical dynamics. Non-parametric cluster-based classification of atmospheric and ocean surface properties has shown an ability to identify coherent weather regimes, each typically associated with similar properties and processes. Using satellite-based observational radiative and turbulent energy flux products, this study investigates the relationship between these weather states and surface energy processes within the context of tropical climate variability. Investigations of surface energy variations accompanying intraseasonal and interannual tropical variability often use composite-based analyses of the mean quantities of interest. Here, a similar compositing technique is employed, but the focus is on the distribution of the heat and moisture fluxes within their weather regimes. Are the observed changes in surface energy components dominated by changes in the frequency of the weather regimes or through changes in the associated fluxes within those regimes? It is this question that the presented work intends to address. The distribution of the surface heat and moisture fluxes is evaluated for both normal and non-normal states. By examining both phases of the climatic oscillations, the symmetry of energy and water cycle responses are considered.

Control of variable speed variable pitch wind turbine based on a disturbance observer

NASA Astrophysics Data System (ADS)

Ren, Haijun; Lei, Xin

2017-11-01

In this paper, a novel sliding mode controller based on disturbance observer (DOB) to optimize the efficiency of variable speed variable pitch (VSVP) wind turbine is developed and analyzed. Due to the highly nonlinearity of the VSVP system, the model is linearly processed to obtain the state space model of the system. Then, a conventional sliding mode controller is designed and a DOB is added to estimate wind speed. The proposed control strategy can successfully deal with the random nature of wind speed, the nonlinearity of VSVP system, the uncertainty of parameters and external disturbance. Via adding the observer to the sliding mode controller, it can greatly reduce the chattering produced by the sliding mode switching gain. The simulation results show that the proposed control system has the effectiveness and robustness.

Wildlife management in southwestern Pinon-juniper woodlands

Treesearch

Jeffery C. Whitney

2008-01-01

Pinon-juniper woodlands in the southwestern United States (Arizona and New Mexico) represent approximately 54,000 square miles, equivalent to roughly 20% of the land base for the two states. Within this broad habitat type, there is a high degree of variability of vegetation in terms of species composition, their relative abundance, percent canopy cover, and typically...

The private forest-land owners of the United States

Treesearch

Thomas W. Birch; Douglas G. Lewis; H. Fred Kaiser

1982-01-01

A report on a 1978 survey of private forest-land owners, based on 11,076 questionnaires. About 7.8 million ownership units hold 333 million acres of privately owned forest land in the United States. Regional and subregional breakdowns are included for such important variables as form of ownership; owner's occupation, age, sex, race, residence, and education; size...

Constitutive relations describing creep deformation for multi-axial time-dependent stress states

NASA Astrophysics Data System (ADS)

McCartney, L. N.

1981-02-01

A THEORY of primary and secondary creep deformation in metals is presented, which is based upon the concept of tensor internal state variables and the principles of continuum mechanics and thermodynamics. The theory is able to account for both multi-axial and time-dependent stress and strain states. The wellknown concepts of elastic, anelastic and plastic strains follow naturally from the theory. Homogeneous stress states are considered in detail and a simplified theory is derived by linearizing with respect to the internal state variables. It is demonstrated that the model can be developed in such a way that multi-axial constant-stress creep data can be presented as a single relationship between an equivalent stress and an equivalent strain. It is shown how the theory may be used to describe the multi-axial deformation of metals which are subjected to constant stress states. The multi-axial strain response to a general cyclic stress state is calculated. For uni-axial stress states, square-wave loading and a thermal fatigue stress cycle are analysed.

A stochastic global identification framework for aerospace structures operating under varying flight states

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotis; Nardari, Raphael; Li, Yu-Hung; Chang, Fu-Kuo

2018-01-01

In this work, a novel data-based stochastic "global" identification framework is introduced for aerospace structures operating under varying flight states and uncertainty. In this context, the term "global" refers to the identification of a model that is capable of representing the structure under any admissible flight state based on data recorded from a sample of these states. The proposed framework is based on stochastic time-series models for representing the structural dynamics and aeroelastic response under multiple flight states, with each state characterized by several variables, such as the airspeed, angle of attack, altitude and temperature, forming a flight state vector. The method's cornerstone lies in the new class of Vector-dependent Functionally Pooled (VFP) models which allow the explicit analytical inclusion of the flight state vector into the model parameters and, hence, system dynamics. This is achieved via the use of functional data pooling techniques for optimally treating - as a single entity - the data records corresponding to the various flight states. In this proof-of-concept study the flight state vector is defined by two variables, namely the airspeed and angle of attack of the vehicle. The experimental evaluation and assessment is based on a prototype bio-inspired self-sensing composite wing that is subjected to a series of wind tunnel experiments under multiple flight states. Distributed micro-sensors in the form of stretchable sensor networks are embedded in the composite layup of the wing in order to provide the sensing capabilities. Experimental data collected from piezoelectric sensors are employed for the identification of a stochastic global VFP model via appropriate parameter estimation and model structure selection methods. The estimated VFP model parameters constitute two-dimensional functions of the flight state vector defined by the airspeed and angle of attack. The identified model is able to successfully represent the wing's aeroelastic response under the admissible flight states via a minimum number of estimated parameters compared to standard identification approaches. The obtained results demonstrate the high accuracy and effectiveness of the proposed global identification framework, thus constituting a first step towards the next generation of "fly-by-feel" aerospace vehicles with state awareness capabilities.

Investigating Einstein-Podolsky-Rosen steering of continuous-variable bipartite states by non-Gaussian pseudospin measurements

NASA Astrophysics Data System (ADS)

Xiang, Yu; Xu, Buqing; Mišta, Ladislav; Tufarelli, Tommaso; He, Qiongyi; Adesso, Gerardo

2017-10-01

Einstein-Podolsky-Rosen (EPR) steering is an asymmetric form of correlations which is intermediate between quantum entanglement and Bell nonlocality, and can be exploited as a resource for quantum communication with one untrusted party. In particular, steering of continuous-variable Gaussian states has been extensively studied theoretically and experimentally, as a fundamental manifestation of the EPR paradox. While most of these studies focused on quadrature measurements for steering detection, two recent works revealed that there exist Gaussian states which are only steerable by suitable non-Gaussian measurements. In this paper we perform a systematic investigation of EPR steering of bipartite Gaussian states by pseudospin measurements, complementing and extending previous findings. We first derive the density-matrix elements of two-mode squeezed thermal Gaussian states in the Fock basis, which may be of independent interest. We then use such a representation to investigate steering of these states as detected by a simple nonlinear criterion, based on second moments of the correlation matrix constructed from pseudospin operators. This analysis reveals previously unexplored regimes where non-Gaussian measurements are shown to be more effective than Gaussian ones to witness steering of Gaussian states in the presence of local noise. We further consider an alternative set of pseudospin observables, whose expectation value can be expressed more compactly in terms of Wigner functions for all two-mode Gaussian states. However, according to the adopted criterion, these observables are found to be always less sensitive than conventional Gaussian observables for steering detection. Finally, we investigate continuous-variable Werner states, which are non-Gaussian mixtures of Gaussian states, and find that pseudospin measurements are always more effective than Gaussian ones to reveal their steerability. Our results provide useful insights on the role of non-Gaussian measurements in characterizing quantum correlations of Gaussian and non-Gaussian states of continuous-variable quantum systems.

Light valve based on nonimaging optics with potential application in cold climate greenhouses

NASA Astrophysics Data System (ADS)

Valerio, Angel A.; Mossman, Michele A.; Whitehead, Lorne A.

2014-09-01

We have evaluated a new concept for a variable light valve and thermal insulation system based on nonimaging optics. The system incorporates compound parabolic concentrators and can readily be switched between an open highly light transmissive state and a closed highly thermally insulating state. This variable light valve makes the transition between high thermal insulation and efficient light transmittance practical and may be useful in plant growth environments to provide both adequate sunlight illumination and thermal insulation as needed. We have measured light transmittance values exceeding 80% for the light valve design and achieved thermal insulation values substantially exceeding those of traditional energy efficient windows. The light valve system presented in this paper represents a potential solution for greenhouse food production in locations where greenhouses are not feasible economically due to high heating cost.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Flux-Based Deadbeat Control of Induction-Motor Torque

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.; Lorenz, Robert D.

2003-01-01

An improved method and prior methods of deadbeat direct torque control involve the use of pulse-width modulation (PWM) of applied voltages. The prior methods are based on the use of stator flux and stator current as state variables, leading to mathematical solutions of control equations in forms that do not lend themselves to clear visualization of solution spaces. In contrast, the use of rotor and stator fluxes as the state variables in the present improved method lends itself to graphical representations that aid in understanding possible solutions under various operating conditions. In addition, the present improved method incorporates the superposition of high-frequency carrier signals for use in a motor-self-sensing technique for estimating the rotor shaft angle at any speed (including low or even zero speed) without need for additional shaft-angle-measuring sensors.

Study of the Algorithm of Backtracking Decoupling and Adaptive Extended Kalman Filter Based on the Quaternion Expanded to the State Variable for Underwater Glider Navigation

PubMed Central

Huang, Haoqian; Chen, Xiyuan; Zhou, Zhikai; Xu, Yuan; Lv, Caiping

2014-01-01

High accuracy attitude and position determination is very important for underwater gliders. The cross-coupling among three attitude angles (heading angle, pitch angle and roll angle) becomes more serious when pitch or roll motion occurs. This cross-coupling makes attitude angles inaccurate or even erroneous. Therefore, the high accuracy attitude and position determination becomes a difficult problem for a practical underwater glider. To solve this problem, this paper proposes backing decoupling and adaptive extended Kalman filter (EKF) based on the quaternion expanded to the state variable (BD-AEKF). The backtracking decoupling can eliminate effectively the cross-coupling among the three attitudes when pitch or roll motion occurs. After decoupling, the adaptive extended Kalman filter (AEKF) based on quaternion expanded to the state variable further smoothes the filtering output to improve the accuracy and stability of attitude and position determination. In order to evaluate the performance of the proposed BD-AEKF method, the pitch and roll motion are simulated and the proposed method performance is analyzed and compared with the traditional method. Simulation results demonstrate the proposed BD-AEKF performs better. Furthermore, for further verification, a new underwater navigation system is designed, and the three-axis non-magnetic turn table experiments and the vehicle experiments are done. The results show that the proposed BD-AEKF is effective in eliminating cross-coupling and reducing the errors compared with the conventional method. PMID:25479331

Study of the algorithm of backtracking decoupling and adaptive extended Kalman filter based on the quaternion expanded to the state variable for underwater glider navigation.

PubMed

Huang, Haoqian; Chen, Xiyuan; Zhou, Zhikai; Xu, Yuan; Lv, Caiping

2014-12-03

High accuracy attitude and position determination is very important for underwater gliders. The cross-coupling among three attitude angles (heading angle, pitch angle and roll angle) becomes more serious when pitch or roll motion occurs. This cross-coupling makes attitude angles inaccurate or even erroneous. Therefore, the high accuracy attitude and position determination becomes a difficult problem for a practical underwater glider. To solve this problem, this paper proposes backing decoupling and adaptive extended Kalman filter (EKF) based on the quaternion expanded to the state variable (BD-AEKF). The backtracking decoupling can eliminate effectively the cross-coupling among the three attitudes when pitch or roll motion occurs. After decoupling, the adaptive extended Kalman filter (AEKF) based on quaternion expanded to the state variable further smoothes the filtering output to improve the accuracy and stability of attitude and position determination. In order to evaluate the performance of the proposed BD-AEKF method, the pitch and roll motion are simulated and the proposed method performance is analyzed and compared with the traditional method. Simulation results demonstrate the proposed BD-AEKF performs better. Furthermore, for further verification, a new underwater navigation system is designed, and the three-axis non-magnetic turn table experiments and the vehicle experiments are done. The results show that the proposed BD-AEKF is effective in eliminating cross-coupling and reducing the errors compared with the conventional method.

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

A new scheme of general hybrid projective complete dislocated synchronization

NASA Astrophysics Data System (ADS)

Chu, Yan-dong; Chang, Ying-Xiang; An, Xin-lei; Yu, Jian-Ning; Zhang, Jian-Gang

2011-03-01

Based on the Lyapunov stability theorem, a new type of chaos synchronization, general hybrid projective complete dislocated synchronization (GHPCDS), is proposed under the framework of drive-response systems. The difference between the GHPCDS and complete synchronization is that every state variable of drive system does not equal the corresponding state variable, but equal other ones of response system while evolving in time. The GHPCDS includes complete dislocated synchronization, dislocated anti-synchronization and projective dislocated synchronization as its special item. As examples, the Lorenz chaotic system, Rössler chaotic system, hyperchaotic Chen system and hyperchaotic Lü system are discussed. Numerical simulations are given to show the effectiveness of these methods.

Estimate of Shock-Hugoniot Adiabat of Liquids from Hydrodynamics

NASA Astrophysics Data System (ADS)

Bouton, E.; Vidal, P.

2007-12-01

Shock states are generally obtained from shock velocity (D) and material velocity (u) measurements. In this paper, we propose a hydrodynamical method for estimating the (D-u) relation of Nitromethane from easily measured properties of the initial state. The method is based upon the differentiation of the Rankine-Hugoniot jump relations with the initial temperature considered as a variable and under the constraint of a unique nondimensional shock-Hugoniot. We then obtain an ordinary differential equation for the shock velocity D in the variable u. Upon integration, this method predicts the shock Hugoniot of liquid Nitromethane with a 5% accuracy for initial temperatures ranging from 250 K to 360 K.

Gaussian-modulated coherent-state measurement-device-independent quantum key distribution

NASA Astrophysics Data System (ADS)

Ma, Xiang-Chun; Sun, Shi-Hai; Jiang, Mu-Sheng; Gui, Ming; Liang, Lin-Mei

2014-04-01

Measurement-device-independent quantum key distribution (MDI-QKD), leaving the detection procedure to the third partner and thus being immune to all detector side-channel attacks, is very promising for the construction of high-security quantum information networks. We propose a scheme to implement MDI-QKD, but with continuous variables instead of discrete ones, i.e., with the source of Gaussian-modulated coherent states, based on the principle of continuous-variable entanglement swapping. This protocol not only can be implemented with current telecom components but also has high key rates compared to its discrete counterpart; thus it will be highly compatible with quantum networks.

A canonical state-space representation for SISO systems using multipoint Jordan CFE. [Continued-Fraction Expansion

NASA Technical Reports Server (NTRS)

Hwang, Chyi; Guo, Tong-Yi; Shieh, Leang-San

1991-01-01

A canonical state-space realization based on the multipoint Jordan continued-fraction expansion (CFE) is presented for single-input-single-output (SISO) systems. The similarity transformation matrix which relates the new canonical form to the phase-variable canonical form is also derived. The presented canonical state-space representation is particularly attractive for the application of SISO system theory in which a reduced-dimensional time-domain model is necessary.

State-space modeling of population sizes and trends in Nihoa Finch and Millerbird

USGS Publications Warehouse

Gorresen, P. Marcos; Brinck, Kevin W.; Camp, Richard J.; Farmer, Chris; Plentovich, Sheldon M.; Banko, Paul C.

2016-01-01

Both of the 2 passerines endemic to Nihoa Island, Hawai‘i, USA—the Nihoa Millerbird (Acrocephalus familiaris kingi) and Nihoa Finch (Telespiza ultima)—are listed as endangered by federal and state agencies. Their abundances have been estimated by irregularly implemented fixed-width strip-transect sampling from 1967 to 2012, from which area-based extrapolation of the raw counts produced highly variable abundance estimates for both species. To evaluate an alternative survey method and improve abundance estimates, we conducted variable-distance point-transect sampling between 2010 and 2014. We compared our results to those obtained from strip-transect samples. In addition, we applied state-space models to derive improved estimates of population size and trends from the legacy time series of strip-transect counts. Both species were fairly evenly distributed across Nihoa and occurred in all or nearly all available habitat. Population trends for Nihoa Millerbird were inconclusive because of high within-year variance. Trends for Nihoa Finch were positive, particularly since the early 1990s. Distance-based analysis of point-transect counts produced mean estimates of abundance similar to those from strip-transects but was generally more precise. However, both survey methods produced biologically unrealistic variability between years. State-space modeling of the long-term time series of abundances obtained from strip-transect counts effectively reduced uncertainty in both within- and between-year estimates of population size, and allowed short-term changes in abundance trajectories to be smoothed into a long-term trend.

Modeling eutrophic lakes: From mass balance laws to ordinary differential equations

NASA Astrophysics Data System (ADS)

Marasco, Addolorata; Ferrara, Luciano; Romano, Antonio

Starting from integral balance laws, a model based on nonlinear ordinary differential equations (ODEs) describing the evolution of Phosphorus cycle in a lake is proposed. After showing that the usual homogeneous model is not compatible with the mixture theory, we prove that an ODEs model still holds but for the mean values of the state variables provided that the nonhomogeneous involved fields satisfy suitable conditions. In this model the trophic state of a lake is described by the mean densities of Phosphorus in water and sediments, and phytoplankton biomass. All the quantities appearing in the model can be experimentally evaluated. To propose restoration programs, the evolution of these state variables toward stable steady state conditions is analyzed. Moreover, the local stability analysis is performed with respect to all the model parameters. Some numerical simulations and a real application to lake Varese conclude the paper.

Structured decision making as a conceptual framework to identify thresholds for conservation and management

USGS Publications Warehouse

Martin, J.; Runge, M.C.; Nichols, J.D.; Lubow, B.C.; Kendall, W.L.

2009-01-01

Thresholds and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds may have led to confusion in attempts to apply the concept of thresholds to conservation decisions. Here, we advocate a framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of the decision process that are inherently subjective (management objectives, potential management actions) from those that are more objective (system models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included in the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision thresholds are determined by the above-listed components of a structured decision process. These components may themselves vary over time, inducing variation in the decision thresholds inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structured decision processes that include all three kinds of thresholds. ?? 2009 by the Ecological Society of America.

Entropy as a collective variable

NASA Astrophysics Data System (ADS)

Parrinello, Michele

Sampling complex free energy surfaces that exhibit long lived metastable states separated by kinetic bottlenecks is one of the most pressing issues in the atomistic simulations of matter. Not surprisingly many solutions to this problem have been suggested. Many of them are based on the identification of appropriate collective variables that span the manifold of the slow varying modes of the system. While much effort has been put in devising and even constructing on the fly appropriate collective variables there is still a cogent need of introducing simple, generic, physically transparent, and yet effective collective variables. Motivated by the physical observation that in many case transitions between one metastable state and another result from a trade off between enthalpy and entropy we introduce appropriate collective variables that are able to represent in a simple way these two physical properties. We use these variables in the context of the recently introduced variationally enhanced sampling and apply it them with success to the simulation of crystallization from the liquid and to conformational transitions in protein. Department of Chemistry and Applied Biosciences, ETH Zurich, and Facolta' di Informatica, Istituto di Scienze Computazionali, Universita' della Svizzera Italiana, Via G. Buffi 13, 6900 Lugano, Switzerland.

Heart-Rate Variability-More than Heart Beats?

PubMed

Ernst, Gernot

2017-01-01

Heart-rate variability (HRV) is frequently introduced as mirroring imbalances within the autonomous nerve system. Many investigations are based on the paradigm that increased sympathetic tone is associated with decreased parasympathetic tone and vice versa . But HRV is probably more than an indicator for probable disturbances in the autonomous system. Some perturbations trigger not reciprocal, but parallel changes of vagal and sympathetic nerve activity. HRV has also been considered as a surrogate parameter of the complex interaction between brain and cardiovascular system. Systems biology is an inter-disciplinary field of study focusing on complex interactions within biological systems like the cardiovascular system, with the help of computational models and time series analysis, beyond others. Time series are considered surrogates of the particular system, reflecting robustness or fragility. Increased variability is usually seen as associated with a good health condition, whereas lowered variability might signify pathological changes. This might explain why lower HRV parameters were related to decreased life expectancy in several studies. Newer integrating theories have been proposed. According to them, HRV reflects as much the state of the heart as the state of the brain. The polyvagal theory suggests that the physiological state dictates the range of behavior and psychological experience. Stressful events perpetuate the rhythms of autonomic states, and subsequently, behaviors. Reduced variability will according to this theory not only be a surrogate but represent a fundamental homeostasis mechanism in a pathological state. The neurovisceral integration model proposes that cardiac vagal tone, described in HRV beyond others as HF-index, can mirror the functional balance of the neural networks implicated in emotion-cognition interactions. Both recent models represent a more holistic approach to understanding the significance of HRV.

Origin of the OFF state variability in ReRAM cells

NASA Astrophysics Data System (ADS)

Salaoru, Iulia; Khiat, Ali; Li, Qingjiang; Berdan, Radu; Papavassiliou, Christos; Prodromakis, Themistoklis

2014-04-01

This work exploits the switching dynamics of nanoscale resistive random access memory (ReRAM) cells with particular emphasis on the origin of the observed variability when cells are consecutively cycled/programmed at distinct memory states. It is demonstrated that this variance is a common feature of all ReRAM elements and is ascribed to the formation and rupture of conductive filaments that expand across the active core, independently of the material employed as the active switching core, the causal physical switching mechanism, the switching mode (bipolar/unipolar) or even the unit cells' dimensions. Our hypothesis is supported through both experimental and theoretical studies on TiO2 and In2O3 : SnO2 (ITO) based ReRAM cells programmed at three distinct resistive states. Our prototypes employed TiO2 or ITO active cores over 5 × 5 µm2 and 100 × 100 µm2 cell areas, with all tested devices demonstrating both unipolar and bipolar switching modalities. In the case of TiO2-based cells, the underlying switching mechanism is based on the non-uniform displacement of ionic species that foster the formation of conductive filaments. On the other hand, the resistive switching observed in the ITO-based devices is considered to be due to a phase change mechanism. The selected experimental parameters allowed us to demonstrate that the observed programming variance is a common feature of all ReRAM devices, proving that its origin is dependent upon randomly oriented local disorders within the active core that have a substantial impact on the overall state variance, particularly for high-resistive states.

European Scientific Notes. Volume 37, Number 1.

DTIC Science & Technology

1983-01-31

instantoneous sea-state condition can be tions vary widely in their realism , with computed from a special data base coded some producing dynamic color pictures...between the variables of accuracy, approach channels, the alignment of practicality, realism , and expense. jetties, and the establishment of Because the...tidal current variables The system certainly seems to be valid, have been played into some of the and the smooth dynamics, realism , and simulator runs

Analyzing Variability in Ebola-Related Controls Applied to Returned Travelers in the United States

PubMed Central

Siedner, Mark J.; Stoto, Michael A.

2015-01-01

Public health authorities have adopted entry screening and subsequent restrictions on travelers from Ebola-affected West African countries as a strategy to prevent importation of Ebola virus disease (EVD) cases. We analyzed international, federal, and state policies—principally based on the policy documents themselves and media reports—to evaluate policy variability. We employed means-ends fit analysis to elucidate policy objectives. We found substantial variation in the specific approaches favored by WHO, CDC, and various American states. Several US states impose compulsory quarantine on a broader range of travelers or require more extensive monitoring than recommended by CDC or WHO. Observed differences likely partially resulted from different actors having different policy goals—particularly the federal government having to balance foreign policy objectives less salient to states. Further, some state-level variation appears to be motivated by short-term political goals. We propose recommendations to improve future policies, which include the following: (1) actors should explicitly clarify their objectives, (2) legal authority should be modernized and clarified, and (3) the federal government should consider preempting state approaches that imperil its goals. PMID:26348222

A variable capacitance based modeling and power capability predicting method for ultracapacitor

NASA Astrophysics Data System (ADS)

Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

2018-01-01

Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

Electrical characterizations of MIS structures based on variable-gap n(p)-HgCdTe grown by MBE on Si(0 1 3) substrates

NASA Astrophysics Data System (ADS)

Voitsekhovskii, A. V.; Nesmelov, S. N.; Dzyadukh, S. M.; Varavin, V. S.; Dvoretskii, S. A.; Mikhailov, N. N.; Yakushev, M. V.; Sidorov, G. Yu.

2017-12-01

Metal-insulator-semiconductor (MIS) structures based on n(p)-Hg1-xCdxTe (x = 0.22-0.40) with near-surface variable-gap layers were grown by the molecular-beam epitaxy (MBE) technique on the Si (0 1 3) substrates. Electrical properties of MIS structures were investigated experimentally at various temperatures (9-77 K) and directions of voltage sweep. The ;narrow swing; technique was used to determine the spectra of fast surface states with the exception of hysteresis effects. It is established that the density of fast surface states at the MCT/Al2O3 interface at a minimum does not exceed 3 × 1010 eV-1 × cm-2. For MIS structures based on n-MCT/Si(0 1 3), the differential resistance of the space-charge region in strong inversion mode in the temperature range 50-90 K is limited by the Shockley-Read-Hall generation in the space-charge region.

Gaussian-based techniques for quantum propagation from the time-dependent variational principle: Formulation in terms of trajectories of coupled classical and quantum variables

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

Shalashilin, Dmitrii V.; Burghardt, Irene

2008-08-28

In this article, two coherent-state based methods of quantum propagation, namely, coupled coherent states (CCS) and Gaussian-based multiconfiguration time-dependent Hartree (G-MCTDH), are put on the same formal footing, using a derivation from a variational principle in Lagrangian form. By this approach, oscillations of the classical-like Gaussian parameters and oscillations of the quantum amplitudes are formally treated in an identical fashion. We also suggest a new approach denoted here as coupled coherent states trajectories (CCST), which completes the family of Gaussian-based methods. Using the same formalism for all related techniques allows their systematization and a straightforward comparison of their mathematical structuremore » and cost.« less

Evidence for a Time-Invariant Phase Variable in Human Ankle Control

PubMed Central

Gregg, Robert D.; Rouse, Elliott J.; Hargrove, Levi J.; Sensinger, Jonathon W.

2014-01-01

Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-dependent feedback to accommodate perturbations. Two popular theories have been proposed for the underlying embodiment of phase in the human pattern generator: a time-dependent internal representation or a time-invariant feedback representation (i.e., reflex mechanisms). In either case the neuromuscular system must update or represent the phase of locomotor patterns based on the system state, which can include measurements of hundreds of variables. However, a much simpler representation of phase has emerged in recent designs for legged robots, which control joint patterns as functions of a single monotonic mechanical variable, termed a phase variable. We propose that human joint patterns may similarly depend on a physical phase variable, specifically the heel-to-toe movement of the Center of Pressure under the foot. We found that when the ankle is unexpectedly rotated to a position it would have encountered later in the step, the Center of Pressure also shifts forward to the corresponding later position, and the remaining portion of the gait pattern ensues. This phase shift suggests that the progression of the stance ankle is controlled by a biomechanical phase variable, motivating future investigations of phase variables in human locomotor control. PMID:24558485

Empirical analyses of plant-climate relationships for the western United States

Treesearch

Gerald E. Rehfeldt; Nicholas L. Crookston; Marcus V. Warwell; Jeffrey S. Evans

2006-01-01

The Random Forests multiple-regression tree was used to model climate profiles of 25 biotic communities of the western United States and nine of their constituent species. Analyses of the communities were based on a gridded sample of ca. 140,000 points, while those for the species used presence-absence data from ca. 120,000 locations. Independent variables included 35...

Leadership among Secondary School Agricultural Science Teachers and Their Job Performance in Akwa Ibom State, Nigeria

ERIC Educational Resources Information Center

Ben, Camilus Bassey

2012-01-01

The main purpose of this study is to investigate leadership among secondary school Agricultural Science teachers and their job performance in Akwa Ibom State. To achieve the aim of this study, three research hypotheses were generated to direct the study. Literature was reviewed based on the variables derived from the postulated hypotheses. Survey…

A Quantitative Examination of the Influence of Non-Instructional Variables on Meeting State Accountability Standards

ERIC Educational Resources Information Center

Newman, Lisa D.

2017-01-01

Since the 1990's, schools across the United States have been held accountable for increased student learning. Increased use of growth-based accountability models and a lack of clarity on what each model measures have resulted in a need for additional research focused on the real-world implications for teacher agency and school accountability. The…

A Four-State Comparison of Expenditures and Income Sources of Financial Aid Recipients in Public Colleges and Universities.

ERIC Educational Resources Information Center

Stampen, Jacob O.; Fenske, Robert H.

The way public college students finance college was studied, based on student resource and expenditure surveys from four states: Arizona, California, New York, and Wisconsin. Comparisons were made of demographic and academic variables, as well as expenditure patterns of students receiving different kinds of aid. The following four aid recipient…

An Application of Durkheim's Theory of Suicide to Prison Suicide Rates in the United States

ERIC Educational Resources Information Center

Tartaro, Christine; Lester, David

2005-01-01

E. Durkheim (1897) suggested that the societal rate of suicide might be explained by societal factors, such as marriage, divorce, and birth rates. The current study examined male prison suicide rates and suicide rates for men in the total population in the United States and found that variables based on Durkheim's theory of suicide explained…

Brazil soybean yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.

Connections between Narrow Line Seyfert 1 Galaxies and Stellar Black Hole Candidates

NASA Astrophysics Data System (ADS)

Negoro, H.

Connections between narrow line Seyfert 1 galaxies (NLS1s) and black hole candidates are described. It has been pointed out that X-ray properties of NLS1s are simlar to those of stellar black hole candidates (BHCs). It is, however, not clear that NLS1s are corresponding to what `state' in the BHCs. Recently, rapid spectral variations during X-ray flares in a few NLS1s have been discovered using ASCA data. The properties of the spectral variations are very similar to those seen in stellar black hole candidates in the hard state. Such temporal variability accompanying the spectral change has not been recognized in black hole candidates in other states. These and recent theoretical progress based on a time variability model of the BHCs in the hard state imply that the advection plays an important role in the accretion process not only in the BHCs in the hard state, but also in NLS1s.

Toward a Unified View of Black-Hole High-Energy States

NASA Technical Reports Server (NTRS)

Nowak, Michael A.

1995-01-01

We present here a review of high-energy (greater than 1 keV) observations of seven black-hole candidates, six of which have estimated masses. In this review we focus on two parameters of interest: the ratio of 'nonthermal' to total luminosity as a function of the total luminosity divided by the Eddington luminosity, and the root-mean-square (rms) variability as a function of the nonthermal-to-total luminosity ratio. Below approx. 10% Eddington luminosity, the sources tend to be strictly nonthermal (the so called 'off' and 'low' states). Above this luminosity the sources become mostly thermal (the 'high' state). with the nonthermal component increasing with luminosity (the 'very high' and 'flare' states). There are important exceptions to this behavior, however, and no steady - as opposed to transient - source has been observed over a wide range of parameter space. In addition, the rms variability is positively correlated with the ratio of nonthermal to total luminosity, although there may be a minimum level of variability associated with 'thermal' states. We discuss these results in light of theoretical models and find that currently no single model describes the full range of black-hole high-energy behavior. In fact, the observations are exactly opposite from what one expects based upon simple notions of accretion disk instabilities.

Experimental investigation of terahertz quantum cascade laser with variable barrier heights

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

Jiang, Aiting; Vijayraghavan, Karun; Belkin, Mikhail A., E-mail: mbelkin@ece.utexas.edu

2014-04-28

We report an experimental study of terahertz quantum cascade lasers with variable barrier heights based on the Al{sub x}Ga{sub 1–x}As/GaAs material system. Two new designs are developed based on semiclassical ensemble Monte Carlo simulations using state-of-the-art Al{sub 0.15}Ga{sub 0.85}As/GaAs three-quantum-well resonant phonon depopulation active region design as a reference. The new designs achieved maximum lasing temperatures of 188 K and 172 K, as compared to the maximum lasing temperature of 191 K for the reference structure. These results demonstrate that terahertz quantum cascade laser designs with variable barrier heights provide a viable alternative to the traditional active region designs with fixed barrier composition.more » Additional design space offered by using variable barriers may lead to future improvements in the terahertz quantum cascade laser performance.« less

Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

PubMed Central

Liu, Yan; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established. PMID:24191134

Safety early warning research for highway construction based on case-based reasoning and variable fuzzy sets.

PubMed

Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

A Neuron-Based Screening Platform for Optimizing Genetically-Encoded Calcium Indicators

PubMed Central

Schreiter, Eric R.; Hasseman, Jeremy P.; Tsegaye, Getahun; Fosque, Benjamin F.; Behnam, Reza; Shields, Brenda C.; Ramirez, Melissa; Kimmel, Bruce E.; Kerr, Rex A.; Jayaraman, Vivek; Looger, Loren L.; Svoboda, Karel; Kim, Douglas S.

2013-01-01

Fluorescent protein-based sensors for detecting neuronal activity have been developed largely based on non-neuronal screening systems. However, the dynamics of neuronal state variables (e.g., voltage, calcium, etc.) are typically very rapid compared to those of non-excitable cells. We developed an electrical stimulation and fluorescence imaging platform based on dissociated rat primary neuronal cultures. We describe its use in testing genetically-encoded calcium indicators (GECIs). Efficient neuronal GECI expression was achieved using lentiviruses containing a neuronal-selective gene promoter. Action potentials (APs) and thus neuronal calcium levels were quantitatively controlled by electrical field stimulation, and fluorescence images were recorded. Images were segmented to extract fluorescence signals corresponding to individual GECI-expressing neurons, which improved sensitivity over full-field measurements. We demonstrate the superiority of screening GECIs in neurons compared with solution measurements. Neuronal screening was useful for efficient identification of variants with both improved response kinetics and high signal amplitudes. This platform can be used to screen many types of sensors with cellular resolution under realistic conditions where neuronal state variables are in relevant ranges with respect to timing and amplitude. PMID:24155972

A System-Oriented Approach for the Optimal Control of Process Chains under Stochastic Influences

NASA Astrophysics Data System (ADS)

Senn, Melanie; Schäfer, Julian; Pollak, Jürgen; Link, Norbert

2011-09-01

Process chains in manufacturing consist of multiple connected processes in terms of dynamic systems. The properties of a product passing through such a process chain are influenced by the transformation of each single process. There exist various methods for the control of individual processes, such as classical state controllers from cybernetics or function mapping approaches realized by statistical learning. These controllers ensure that a desired state is obtained at process end despite of variations in the input and disturbances. The interactions between the single processes are thereby neglected, but play an important role in the optimization of the entire process chain. We divide the overall optimization into two phases: (1) the solution of the optimization problem by Dynamic Programming to find the optimal control variable values for each process for any encountered end state of its predecessor and (2) the application of the optimal control variables at runtime for the detected initial process state. The optimization problem is solved by selecting adequate control variables for each process in the chain backwards based on predefined quality requirements for the final product. For the demonstration of the proposed concept, we have chosen a process chain from sheet metal manufacturing with simplified transformation functions.

Candidate soil indicators for monitoring the progress of constructed wetlands toward a natural state: a statistical approach

USGS Publications Warehouse

Stapanian, Martin A.; Adams, Jean V.; Fennessy, M. Siobhan; Mack, John; Micacchion, Mick

2013-01-01

A persistent question among ecologists and environmental managers is whether constructed wetlands are structurally or functionally equivalent to naturally occurring wetlands. We examined 19 variables collected from 10 constructed and nine natural emergent wetlands in Ohio, USA. Our primary objective was to identify candidate indicators of wetland class (natural or constructed), based on measurements of soil properties and an index of vegetation integrity, that can be used to track the progress of constructed wetlands toward a natural state. The method of nearest shrunken centroids was used to find a subset of variables that would serve as the best classifiers of wetland class, and error rate was calculated using a five-fold cross-validation procedure. The shrunken differences of percent total organic carbon (% TOC) and percent dry weight of the soil exhibited the greatest distances from the overall centroid. Classification based on these two variables yielded a misclassification rate of 11% based on cross-validation. Our results indicate that % TOC and percent dry weight can be used as candidate indicators of the status of emergent, constructed wetlands in Ohio and for assessing the performance of mitigation. The method of nearest shrunken centroids has excellent potential for further applications in ecology.

Variable-amplitude oscillatory shear response of amorphous materials.

PubMed

Perchikov, Nathan; Bouchbinder, Eran

2014-06-01

Variable-amplitude oscillatory shear tests are emerging as powerful tools to investigate and quantify the nonlinear rheology of amorphous solids, complex fluids, and biological materials. Quite a few recent experimental and atomistic simulation studies demonstrated that at low shear amplitudes, an amorphous solid settles into an amplitude- and initial-conditions-dependent dissipative limit cycle, in which back-and-forth localized particle rearrangements periodically bring the system to the same state. At sufficiently large shear amplitudes, the amorphous system loses memory of the initial conditions, exhibits chaotic particle motions accompanied by diffusive behavior, and settles into a stochastic steady state. The two regimes are separated by a transition amplitude, possibly characterized by some critical-like features. Here we argue that these observations support some of the physical assumptions embodied in the nonequilibrium thermodynamic, internal-variables based, shear-transformation-zone model of amorphous viscoplasticity; most notably that "flow defects" in amorphous solids are characterized by internal states between which they can make transitions, and that structural evolution is driven by dissipation associated with plastic deformation. We present a rather extensive theoretical analysis of the thermodynamic shear-transformation-zone model for a variable-amplitude oscillatory shear protocol, highlighting its success in accounting for various experimental and simulational observations, as well as its limitations. Our results offer a continuum-level theoretical framework for interpreting the variable-amplitude oscillatory shear response of amorphous solids and may promote additional developments.

Multiscale equation-free algorithms for molecular dynamics

NASA Astrophysics Data System (ADS)

Abi Mansour, Andrew

Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.

The NOWESP research data base

NASA Astrophysics Data System (ADS)

Radach, G.; Gekeler, J.; Becker, G.; Bot, P.; Castaing, P.; Colijn, F.; Damm, P.; Danielssen, D.; Føyn, L.; Gamble, J.; Laane, R.; Mommaerts, J. P.; Nehring, D.; Pegler, K.; van Raaphorst, W.; Wilson, J.

1996-09-01

In the NOWESP project historical data from the Northwest European Shelf were compiled and evaluated to estimate the variability and trends in water movements, concentrations of dissolved and particulate constituents, and fluxes of the relevant substances across the shelf. As an integral part of the project, the NOWESP Research Data Base was created as a research tool to provide the data and data products needed for the analyses within the project. The tasks of the NOWESP Research Data Base group were the acquisition of the relevant data sets, with the intensive support of all partners, organization of the data sets in the NOWESP Research Data Base, merging of the specific data sets for the ten main state variables used in NOWESP, and the provision of data products for analysis within NOWESP. The data compiled during NOWESP represent a unique data set for the Northwest European Shelf. The data set is sufficiently comprehensive to allow the definition of long time series at about 14 sites in eight areas. It further enables the derivation of mean annual cycles of horizontal distributions of nine main state variables. NOWESP thus has provided valuable data sets for estimating budgets and fluxes across the shelf and, in addition, important data sets for the forcing and validation of ecological shelf sea models. An overview of the NOWESP data set is given. The organization of the data base is described in some detail, and examples of the products obtained for NOWESP are displayed.

A comparison of two software architectural styles for space-based control systems

NASA Technical Reports Server (NTRS)

Dvorak, D.

2003-01-01

In the hardware/software design of control systems it is almost an article of faith to decompose a system into loosely coupled subsystems, with state variables encapsulated inside device and subsystem objects.

Unsupervised Calculation of Free Energy Barriers in Large Crystalline Systems

NASA Astrophysics Data System (ADS)

Swinburne, Thomas D.; Marinica, Mihai-Cosmin

2018-03-01

The calculation of free energy differences for thermally activated mechanisms in the solid state are routinely hindered by the inability to define a set of collective variable functions that accurately describe the mechanism under study. Even when possible, the requirement of descriptors for each mechanism under study prevents implementation of free energy calculations in the growing range of automated material simulation schemes. We provide a solution, deriving a path-based, exact expression for free energy differences in the solid state which does not require a converged reaction pathway, collective variable functions, Gram matrix evaluations, or probability flux-based estimators. The generality and efficiency of our method is demonstrated on a complex transformation of C 15 interstitial defects in iron and double kink nucleation on a screw dislocation in tungsten, the latter system consisting of more than 120 000 atoms. Both cases exhibit significant anharmonicity under experimentally relevant temperatures.

Phenomenological model for transient deformation based on state variables

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

Jackson, M S; Cho, C W; Alexopoulos, P

The state variable theory of Hart, while providing a unified description of plasticity-dominated deformation, exhibits deficiencies when it is applied to transient deformation phenomena at stresses below yield. It appears that the description of stored anelastic strain is oversimplified. Consideration of a simple physical picture based on continuum dislocation pileups suggests that the neglect of weak barriers to dislocation motion is the source of these inadequacies. An appropriately modified description incorporating such barriers then allows the construction of a macroscopic model including transient effects. Although the flow relations for the microplastic element required in the new theory are not known,more » tentative assignments may be made for such functions. The model then exhibits qualitatively correct behavior when tensile, loading-unloading, reverse loading, and load relaxation tests are simulated. Experimental procedures are described for determining the unknown parameters and functions in the new model.« less

A comparison of two above-ground biomass estimation techniques integrating satellite-based remotely sensed data and ground data for tropical and semiarid forests in Puerto Rico

NASA Astrophysics Data System (ADS)

Iiames, J. S.; Riegel, J.; Lunetta, R.

2013-12-01

Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA) program. The U.S. Environmental Protection Agency (EPA) estimated above-ground forest biomass implementing methodology first posited by the Woods Hole Research Center developed for conterminous United States (National Biomass and Carbon Dataset [NBCD2000]). For EPA's effort, spatial predictor layers for above-ground biomass estimation included derived products from the U.S. Geologic Survey (USGS) National Land Cover Dataset 2001 (NLCD) (landcover and canopy density), the USGS Gap Analysis Program (forest type classification), the USGS National Elevation Dataset, and the NASA Shuttle Radar Topography Mission (tree heights). In contrast, the U.S. Forest Service (USFS) biomass product integrated FIA ground-based data with a suite of geospatial predictor variables including: (1) the Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; (2) NLCD land cover proportions; (3) topographic variables; (4) monthly and annual climate parameters; and (5) other ancillary variables. Correlations between both data sets were made at variable watershed scales to test level of agreement. Notice: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S EPA funded and conducted the research described in this paper. Although this work was reviewed by the EPA and has been approved for publication, it may not necessarily reflect official Agency policy. Mention of any trade names or commercial products does not constitute endorsement or recommendation for use.

Estimation of sum-to-one constrained parameters with non-Gaussian extensions of ensemble-based Kalman filters: application to a 1D ocean biogeochemical model

NASA Astrophysics Data System (ADS)

Simon, E.; Bertino, L.; Samuelsen, A.

2011-12-01

Combined state-parameter estimation in ocean biogeochemical models with ensemble-based Kalman filters is a challenging task due to the non-linearity of the models, the constraints of positiveness that apply to the variables and parameters, and the non-Gaussian distribution of the variables in which they result. Furthermore, these models are sensitive to numerous parameters that are poorly known. Previous works [1] demonstrated that the Gaussian anamorphosis extensions of ensemble-based Kalman filters were relevant tools to perform combined state-parameter estimation in such non-Gaussian framework. In this study, we focus on the estimation of the grazing preferences parameters of zooplankton species. These parameters are introduced to model the diet of zooplankton species among phytoplankton species and detritus. They are positive values and their sum is equal to one. Because the sum-to-one constraint cannot be handled by ensemble-based Kalman filters, a reformulation of the parameterization is proposed. We investigate two types of changes of variables for the estimation of sum-to-one constrained parameters. The first one is based on Gelman [2] and leads to the estimation of normal distributed parameters. The second one is based on the representation of the unit sphere in spherical coordinates and leads to the estimation of parameters with bounded distributions (triangular or uniform). These formulations are illustrated and discussed in the framework of twin experiments realized in the 1D coupled model GOTM-NORWECOM with Gaussian anamorphosis extensions of the deterministic ensemble Kalman filter (DEnKF). [1] Simon E., Bertino L. : Gaussian anamorphosis extension of the DEnKF for combined state and parameter estimation : application to a 1D ocean ecosystem model. Journal of Marine Systems, 2011. doi :10.1016/j.jmarsys.2011.07.007 [2] Gelman A. : Method of Moments Using Monte Carlo Simulation. Journal of Computational and Graphical Statistics, 4, 1, 36-54, 1995.

Multistate λ-local-elevation umbrella-sampling (MS-λ-LEUS): method and application to the complexation of cations by crown ethers.

PubMed

Bieler, Noah S; Tschopp, Jan P; Hünenberger, Philippe H

2015-06-09

An extension of the λ-local-elevation umbrella-sampling (λ-LEUS) scheme [ Bieler et al. J. Chem. Theory Comput. 2014 , 10 , 3006 ] is proposed to handle the multistate (MS) situation, i.e. the calculation of the relative free energies of multiple physical states based on a single simulation. The key element of the MS-λ-LEUS approach is to use a single coupling variable Λ controlling successive pairwise mutations between the states of interest in a cyclic fashion. The Λ variable is propagated dynamically as an extended-system variable, using a coordinate transformation with plateaus and a memory-based biasing potential as in λ-LEUS. Compared to other available MS schemes (one-step perturbation, enveloping distribution sampling and conventional λ-dynamics) the proposed method presents a number of important advantages, namely: (i) the physical states are visited explicitly and over finite time periods; (ii) the extent of unphysical space required to ensure transitions is kept minimal and, in particular, one-dimensional; (iii) the setup protocol solely requires the topologies of the physical states; and (iv) the method only requires limited modifications in a simulation code capable of handling two-state mutations. As an initial application, the absolute binding free energies of five alkali cations to three crown ethers in three different solvents are calculated. The results are found to reproduce qualitatively the main experimental trends and, in particular, the experimental selectivity of 18C6 for K(+) in water and methanol, which is interpreted in terms of opposing trends along the cation series between the solvation free energy of the cation and the direct electrostatic interactions within the complex.

Ecological site-based assessments of wind and water erosion: informing accelerated soil erosion management in rangelands

USGS Publications Warehouse

Webb, Nicholas P.; Herrick, Jeffrey E.; Duniway, Michael C.

2014-01-01

Accelerated soil erosion occurs when anthropogenic processes modify soil, vegetation or climatic conditions causing erosion rates at a location to exceed their natural variability. Identifying where and when accelerated erosion occurs is a critical first step toward its effective management. Here we explore how erosion assessments structured in the context of ecological sites (a land classification based on soils, landscape setting and ecological potential) and their vegetation states (plant assemblages that may change due to management) can inform systems for reducing accelerated soil erosion in rangelands. We evaluated aeolian horizontal sediment flux and fluvial sediment erosion rates for five ecological sites in southern New Mexico, USA, using monitoring data and rangeland-specific wind and water erosion models. Across the ecological sites, plots in shrub-encroached and shrub-dominated vegetation states were consistently susceptible to aeolian sediment flux and fluvial sediment erosion. Both processes were found to be highly variable for grassland and grass-succulent states across the ecological sites at the plot scale (0.25 Ha). We identify vegetation thresholds that define cover levels below which rapid (exponential) increases in aeolian sediment flux and fluvial sediment erosion occur across the ecological sites and vegetation states. Aeolian sediment flux and fluvial erosion in the study area can be effectively controlled when bare ground cover is 100 cm in length is less than ~35%. Land use and management activities that alter cover levels such that they cross thresholds, and/or drive vegetation state changes, may increase the susceptibility of areas to erosion. Land use impacts that are constrained within the range of natural variability should not result in accelerated soil erosion. Evaluating land condition against the erosion thresholds identified here will enable identification of areas susceptible to accelerated soil erosion and the development of practical management solutions.

Fall risk factors analysis based on sample entropy of plantar kinematic signal during stance phase.

PubMed

Shengyun Liang; Huiyu Jia; Zilong Li; Huiqi Li; Xing Gao; Zuchang Ma; Yingnan Ma; Guoru Zhao

2016-08-01

Falls are a multi-causal phenomenon with a complex interaction. The aim of our research is to study the effect of multiple variables for potential risk of falls and construct an elderly fall risk assessment model based on demographics data and gait characteristics. A total of 101 subjects, whom belong to Malianwa Street, aged above 50 years old and participated in questionnaire survey. Participants were classified into three groups (high, medium and low risk group) according to the score of elderly fall risk assessment scale. In addition, the data of ground reaction force (GRF) and ground reaction moment (GRM) was record when they performed walking at comfortable state. The demographic variables, sample entropy of GRF and GRM, and impulse difference of bilateral foot were considered as potential explanatory variables of risk assessment model. Firstly, we investigated whether different groups could present difference in every variable. Statistical differences were found for the following variables: age (p=2.28e-05); impulse difference (p=0.02036); sample entropy of GRF in vertical direction (p=0.0144); sample entropy of GRM in anterior-posterior direction (p=0.0387). Finally, the multiple regression analysis results indicated that age, impulse difference and sample entropy of resultant GRM could identify individuals who had different levels of fall risk. Therefore, those results could potentially be useful in the fall risk assessment and monitor the state of physical function in elderly population.

What Makes a Difference during the Last Two Years of High School: An Overview of Studies Based on High School and Beyond Data.

ERIC Educational Resources Information Center

Marsh, Herbert W.

Variables that influence growth and change in educational outcomes in the last 2 years of high school were studied using data from the High School and Beyond (HSB) study. The HSB study provided a database of thousands of variables for about 30 students from each of 1,000 randomly selected high schools in the United States in their sophomore and…

Diagnosis of delay-deadline failures in real time discrete event models.

PubMed

Biswas, Santosh; Sarkar, Dipankar; Bhowal, Prodip; Mukhopadhyay, Siddhartha

2007-10-01

In this paper a method for fault detection and diagnosis (FDD) of real time systems has been developed. A modeling framework termed as real time discrete event system (RTDES) model is presented and a mechanism for FDD of the same has been developed. The use of RTDES framework for FDD is an extension of the works reported in the discrete event system (DES) literature, which are based on finite state machines (FSM). FDD of RTDES models are suited for real time systems because of their capability of representing timing faults leading to failures in terms of erroneous delays and deadlines, which FSM-based ones cannot address. The concept of measurement restriction of variables is introduced for RTDES and the consequent equivalence of states and indistinguishability of transitions have been characterized. Faults are modeled in terms of an unmeasurable condition variable in the state map. Diagnosability is defined and the procedure of constructing a diagnoser is provided. A checkable property of the diagnoser is shown to be a necessary and sufficient condition for diagnosability. The methodology is illustrated with an example of a hydraulic cylinder.

Continuous-variable entanglement distillation of non-Gaussian mixed states

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

Dong Ruifang; Lassen, Mikael; Department of Physics, Technical University of Denmark, Building 309, DK-2800 Lyngby

2010-07-15

Many different quantum-information communication protocols such as teleportation, dense coding, and entanglement-based quantum key distribution are based on the faithful transmission of entanglement between distant location in an optical network. The distribution of entanglement in such a network is, however, hampered by loss and noise that is inherent in all practical quantum channels. Thus, to enable faithful transmission one must resort to the protocol of entanglement distillation. In this paper we present a detailed theoretical analysis and an experimental realization of continuous variable entanglement distillation in a channel that is inflicted by different kinds of non-Gaussian noise. The continuous variablemore » entangled states are generated by exploiting the third order nonlinearity in optical fibers, and the states are sent through a free-space laboratory channel in which the losses are altered to simulate a free-space atmospheric channel with varying losses. We use linear optical components, homodyne measurements, and classical communication to distill the entanglement, and we find that by using this method the entanglement can be probabilistically increased for some specific non-Gaussian noise channels.« less

Lithium-ion battery state of function estimation based on fuzzy logic algorithm with associated variables

NASA Astrophysics Data System (ADS)

Gan, L.; Yang, F.; Shi, Y. F.; He, H. L.

2017-11-01

Many occasions related to batteries demand to know how much continuous and instantaneous power can batteries provide such as the rapidly developing electric vehicles. As the large-scale applications of lithium-ion batteries, lithium-ion batteries are used to be our research object. Many experiments are designed to get the lithium-ion battery parameters to ensure the relevance and reliability of the estimation. To evaluate the continuous and instantaneous load capability of a battery called state-of-function (SOF), this paper proposes a fuzzy logic algorithm based on battery state-of-charge(SOC), state-of-health(SOH) and C-rate parameters. Simulation and experimental results indicate that the proposed approach is suitable for battery SOF estimation.

Four-State Continuous-Variable Quantum Key Distribution with Photon Subtraction

NASA Astrophysics Data System (ADS)

Li, Fei; Wang, Yijun; Liao, Qin; Guo, Ying

2018-06-01

Four-state continuous-variable quantum key distribution (CVQKD) is one of the discretely modulated CVQKD which generates four nonorthogonal coherent states and exploits the sign of the measured quadrature of each state to encode information rather than uses the quadrature \\hat {x} or \\hat {p} itself. It has been proven that four-state CVQKD is more suitable than Gaussian modulated CVQKD in terms of transmission distance. In this paper, we propose an improved four-state CVQKD using an non-Gaussian operation, photon subtraction. A suitable photon-subtraction operation can be exploited to improve the maximal transmission of CVQKD in point-to-point quantum communication since it provides a method to enhance the performance of entanglement-based (EB) CVQKD. Photon subtraction not only can lengthen the maximal transmission distance by increasing the signal-to-noise rate but also can be easily implemented with existing technologies. Security analysis shows that the proposed scheme can lengthen the maximum transmission distance. Furthermore, by taking finite-size effect into account we obtain a tighter bound of the secure distance, which is more practical than that obtained in the asymptotic limit.

New insight on intergenerational attachment from a relationship-based analysis.

PubMed

Bailey, Heidi N; Tarabulsy, George M; Moran, Greg; Pederson, David R; Bento, Sandi

2017-05-01

Research on attachment transmission has focused on variable-centered analyses, where hypotheses are tested by examining linear associations between variables. The purpose of this study was to apply a relationship-centered approach to data analysis, where adult states of mind, maternal sensitivity, and infant attachment were conceived as being three components of a single, intergenerational relationship. These variables were assessed in 90 adolescent and 99 adult mother-infant dyads when infants were 12 months old. Initial variable-centered analyses replicated the frequently observed associations between these three core attachment variables. Relationship-based, latent class analyses then revealed that the most common pattern among young mother dyads featured maternal unresolved trauma, insensitive interactive behavior, and disorganized infant attachment (61%), whereas the most prevalent adult mother dyad relationship pattern involved maternal autonomy, sensitive maternal behavior, and secure infant attachment (59%). Three less prevalent relationship patterns were also observed. Moderation analyses revealed that the adolescent-adult mother distinction differentiated between secure and disorganized intergenerational relationship patterns, whereas experience of traumatic events distinguished between disorganized and avoidant patterns. Finally, socioeconomic status distinguished between avoidant and secure patterns. Results emphasize the value of a relationship-based approach, adding an angle of understanding to the study of attachment transmission.

A hybrid model for traffic flow and crowd dynamics with random individual properties.

PubMed

Schleper, Veronika

2015-04-01

Based on an established mathematical model for the behavior of large crowds, a new model is derived that is able to take into account the statistical variation of individual maximum walking speeds. The same model is shown to be valid also in traffic flow situations, where for instance the statistical variation of preferred maximum speeds can be considered. The model involves explicit bounds on the state variables, such that a special Riemann solver is derived that is proved to respect the state constraints. Some care is devoted to a valid construction of random initial data, necessary for the use of the new model. The article also includes a numerical method that is shown to respect the bounds on the state variables and illustrative numerical examples, explaining the properties of the new model in comparison with established models.

Continuous-Variable Instantaneous Quantum Computing is Hard to Sample.

PubMed

Douce, T; Markham, D; Kashefi, E; Diamanti, E; Coudreau, T; Milman, P; van Loock, P; Ferrini, G

2017-02-17

Instantaneous quantum computing is a subuniversal quantum complexity class, whose circuits have proven to be hard to simulate classically in the discrete-variable realm. We extend this proof to the continuous-variable (CV) domain by using squeezed states and homodyne detection, and by exploring the properties of postselected circuits. In order to treat postselection in CVs, we consider finitely resolved homodyne detectors, corresponding to a realistic scheme based on discrete probability distributions of the measurement outcomes. The unavoidable errors stemming from the use of finitely squeezed states are suppressed through a qubit-into-oscillator Gottesman-Kitaev-Preskill encoding of quantum information, which was previously shown to enable fault-tolerant CV quantum computation. Finally, we show that, in order to render postselected computational classes in CVs meaningful, a logarithmic scaling of the squeezing parameter with the circuit size is necessary, translating into a polynomial scaling of the input energy.

Estimate of shock-Hugoniot adiabat of liquids from hydrodyamics

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

Bouton, E.; Vidal, P.

2007-12-12

Shock states are generally obtained from shock velocity (D) and material velocity (u) measurements. In this paper, we propose a hydrodynamical method for estimating the (D-u) relation of Nitromethane from easily measured properties of the initial state. The method is based upon the differentiation of the Rankine-Hugoniot jump relations with the initial temperature considered as a variable and under the constraint of a unique nondimensional shock-Hugoniot. We then obtain an ordinary differential equation for the shock velocity D in the variable u. Upon integration, this method predicts the shock Hugoniot of liquid Nitromethane with a 5% accuracy for initial temperaturesmore » ranging from 250 K to 360 K.« less

Continuous variable quantum key distribution with a real local oscillator using simultaneous pilot signals.

PubMed

Kleis, Sebastian; Rueckmann, Max; Schaeffer, Christian G

2017-04-15

In this Letter, we propose a novel implementation of continuous variable quantum key distribution that operates with a real local oscillator placed at the receiver site. In addition, pulsing of the continuous wave laser sources is not required, leading to an extraordinary practical and secure setup. It is suitable for arbitrary schemes based on modulated coherent states and heterodyne detection. The shown results include transmission experiments, as well as an excess noise analysis applying a discrete 8-state phase modulation. Achievable key rates under collective attacks are estimated. The results demonstrate the high potential of the approach to achieve high secret key rates at relatively low effort and cost.

Linear Extended State Observer-Based Motion Synchronization Control for Hybrid Actuation System of More Electric Aircraft.

PubMed

Wang, Xingjian; Liao, Rui; Shi, Cun; Wang, Shaoping

2017-10-25

Moving towards the more electric aircraft (MEA), a hybrid actuator configuration provides an opportunity to introduce electromechanical actuator (EMA) into primary flight control. In the hybrid actuation system (HAS), an electro-hydraulic servo actuator (EHSA) and an EMA operate on the same control surface. In order to solve force fighting problem in HAS, this paper proposes a novel linear extended state observer (LESO)-based motion synchronization control method. To cope with the problem of unavailability of the state signals required by the motion synchronization controller, LESO is designed for EHSA and EMA to observe the state variables. Based on the observed states of LESO, motion synchronization controllers could enable EHSA and EMA to simultaneously track the desired motion trajectories. Additionally, nonlinearities, uncertainties and unknown disturbances as well as the coupling term between EHSA and EMA can be estimated and compensated by using the extended state of the proposed LESO. Finally, comparative simulation results indicate that the proposed LESO-based motion synchronization controller could reduce significant force fighting between EHSA and EMA.

Linear Extended State Observer-Based Motion Synchronization Control for Hybrid Actuation System of More Electric Aircraft

PubMed Central

Liao, Rui; Shi, Cun; Wang, Shaoping

2017-01-01

Moving towards the more electric aircraft (MEA), a hybrid actuator configuration provides an opportunity to introduce electromechanical actuator (EMA) into primary flight control. In the hybrid actuation system (HAS), an electro-hydraulic servo actuator (EHSA) and an EMA operate on the same control surface. In order to solve force fighting problem in HAS, this paper proposes a novel linear extended state observer (LESO)-based motion synchronization control method. To cope with the problem of unavailability of the state signals required by the motion synchronization controller, LESO is designed for EHSA and EMA to observe the state variables. Based on the observed states of LESO, motion synchronization controllers could enable EHSA and EMA to simultaneously track the desired motion trajectories. Additionally, nonlinearities, uncertainties and unknown disturbances as well as the coupling term between EHSA and EMA can be estimated and compensated by using the extended state of the proposed LESO. Finally, comparative simulation results indicate that the proposed LESO-based motion synchronization controller could reduce significant force fighting between EHSA and EMA. PMID:29068392

The Use of Microcomputer Based Laboratories in Chemistry Secondary Education: Present State of the Art and Ideas for Research-Based Practice

ERIC Educational Resources Information Center

Tortosa, Montserrat

2012-01-01

In microcomputer based laboratories (MBL) and data loggers, one or more sensors are connected to an interphase and this to a computer. This equipment allows visualization in real time of the variables of an experiment and provides the possibility of measuring magnitudes which are difficult to measure with traditional equipment. Research shows that…

Hydrologic classification of rivers based on cluster analysis of dimensionless hydrologic signatures: Applications for environmental instream flows

NASA Astrophysics Data System (ADS)

Praskievicz, S. J.; Luo, C.

2017-12-01

Classification of rivers is useful for a variety of purposes, such as generating and testing hypotheses about watershed controls on hydrology, predicting hydrologic variables for ungaged rivers, and setting goals for river management. In this research, we present a bottom-up (based on machine learning) river classification designed to investigate the underlying physical processes governing rivers' hydrologic regimes. The classification was developed for the entire state of Alabama, based on 248 United States Geological Survey (USGS) stream gages that met criteria for length and completeness of records. Five dimensionless hydrologic signatures were derived for each gage: slope of the flow duration curve (indicator of flow variability), baseflow index (ratio of baseflow to average streamflow), rising limb density (number of rising limbs per unit time), runoff ratio (ratio of long-term average streamflow to long-term average precipitation), and streamflow elasticity (sensitivity of streamflow to precipitation). We used a Bayesian clustering algorithm to classify the gages, based on the five hydrologic signatures, into distinct hydrologic regimes. We then used classification and regression trees (CART) to predict each gaged river's membership in different hydrologic regimes based on climatic and watershed variables. Using existing geospatial data, we applied the CART analysis to classify ungaged streams in Alabama, with the National Hydrography Dataset Plus (NHDPlus) catchment (average area 3 km2) as the unit of classification. The results of the classification can be used for meeting management and conservation objectives in Alabama, such as developing statewide standards for environmental instream flows. Such hydrologic classification approaches are promising for contributing to process-based understanding of river systems.

Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil

NASA Astrophysics Data System (ADS)

de Carvalho, Luiz G.; de Carvalho Alves, Marcelo; de Oliveira, Marcelo S.; Vianello, Rubens L.; Sediyama, Gilberto C.; de Carvalho, Luis M. T.

2010-11-01

The objective of the present study was to assess for Minas Gerais the cokriging methodology, in order to characterize the spatial variability of Thornthwaite annual moisture index, annual rainfall, and average annual air temperature, based on geographical coordinates, altitude, latitude, and longitude. The climatic element data referred to 39 INMET climatic stations located in the state of Minas Gerais and in nearby areas and the covariables altitude, latitude, and longitude to the SRTM digital elevation model. Spatial dependence of data was observed through spherical cross semivariograms and cross covariance models. Box-Cox and log transformation were applied to the positive variables. In these situations, kriged predictions were back-transformed and returned to the same scale as the original data. Trend was removed using global polynomial interpolation. Universal simple cokriging best characterized the climate variables without tendentiousness and with high accuracy and precision when compared to simple cokriging. Considering the satisfactory implementation of universal simple cokriging for the monitoring of climatic elements, this methodology presents enormous potential for the characterization of climate change impact in Minas Gerais state.

Enhanced production of lovastatin by Omphalotus olearius (DC.) Singer in solid state fermentation.

PubMed

Atlı, Burcu; Yamaç, Mustafa; Yıldız, Zeki; Isikhuemnen, Omoanghe S

2015-01-01

Although lovastatin production has been reported for different microorganism species, there is limited information about lovastatin production by basidiomycetes. The optimization of culture parameters that enhances lovastatin production by Omphalotus olearius OBCC 2002 was investigated, using statistically based experimental designs under solid state fermentation. The Plackett Burman design was used in the first step to test the relative importance of the variables affecting production of lovastatin. Amount and particle size of barley were identified as efficient variables. In the latter step, the interactive effects of selected efficient variables were studied with a full factorial design. A maximum lovastatin yield of 139.47mg/g substrate was achieved by the fermentation of 5g of barley, 1-2mm particle diam., at 28°C. This study showed that O. olearius OBCC 2002 has a high capacity for lovastatin production which could be enhanced by using solid state fermentation with novel and cost-effective substrates, such as barley. Copyright © 2013 Revista Iberoamericana de Micología. Published by Elsevier Espana. All rights reserved.

Characterization of Nighttime Light Variability Over the Southeastern United States

NASA Technical Reports Server (NTRS)

Cole, Tony A.; Molthan, Andrew L.; Schultz, Lori A.

2016-01-01

City lights provide indications of human activity at night. Nighttime satellite imagery offers daily snapshots of this activity. With calibrated, science-quality imagery, long-term monitoring can also be achieved. The degree to which city lights fluctuate, however, is not well known. For the application of detecting power outages, this degree of variability is crucial for assessing reductions to city lights based on historical trends. Eight southeastern U.S. cities are analyzed to understand the relationship between emission variability and several population centers. A preliminary, example case power outage study is also discussed as a transition into future work.

Modification of LRFD resistance factors based on site variability : final report, November 2009.

DOT National Transportation Integrated Search

2009-11-01

Current practice by the Florida Department of Transportation (FDOT), Federal Highway Administration (FHWA), and American Association of State Highway Transportation Officials (AASHTO) for deep foundation design is to use a constant load and resistanc...

pH-Dependent spin state population and 19F NMR chemical shift via remote ligand protonation in an iron(ii) complex.

PubMed

Gaudette, Alexandra I; Thorarinsdottir, Agnes E; Harris, T David

2017-11-30

An Fe II complex that features a pH-dependent spin state population, by virtue of a variable ligand protonation state, is described. This behavior leads to a highly pH-dependent 19 F NMR chemical shift with a sensitivity of 13.9(5) ppm per pH unit at 37 °C, thereby demonstrating the potential utility of the complex as a 19 F chemical shift-based pH sensor.

Are Droughts in the United States Great Plains Predictable on Seasonal and Longer Time Scales?

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Suarez, M.; Pegion, P.; Kistler, M.; Einaudi, Franco (Technical Monitor)

2001-01-01

The United States Great Plains has experienced numerous episodes of unusually dry conditions lasting anywhere from months to several years, In this presentation, we will examine the predictability of such episodes and the physical mechanisms controlling the variability of the summer climate of the continental United States. The analysis is based on ensembles of multi-year simulations and seasonal hindcasts generated with the NASA Seasonal to-Interannual Prediction Project (NSIPP-1) General Circulation Model.

A performability solution method for degradable nonrepairable systems

NASA Technical Reports Server (NTRS)

Furchtgott, D. G.; Meyer, J. F.

1984-01-01

The present performability model-solving algorithm identifies performance with 'reward', representing the state behavior of a system S by a finite-state stochastic process and determining reward by means of reward rates that are associated with the states of the base model. A general method is obtained for determining the probability distribution function of the performance (reward) variable, and therefore the performability, of the corresponding system. This is done for bounded utilization periods, and the result is an integral expression which is either analytically or numerically solvable.

City plants as ecological indicator of environment quality in St. Petersburg

NASA Astrophysics Data System (ADS)

Sapunov, Valentin; Glazyrina, Tatyana

2017-04-01

Under increase of natural hazard activity and anthropogenic pressure the effective and cheep monitoring methods become necessary. Majority of modern methods of monitoring, such as space and air, needs significant foundation. The simplest monitoring method is biological indication, basing on essay of variability, sex ration and sexual dimorphism. Such a method does not need long time efforts and may be realized by short observation. Urban plants are natural indicators of ecological pressure. Check or their state may give us significant information on area pollution by use of principles of phenogenic indication. Genetic and phenotypic variability of different organism have general principles and constants. The per cent of abnormal organisms and coefficient of variability are stable for majority of species under favorable state and increase under unfavorable conditions. The basis for indication is both state of adult trees and morphological variability of pollen grains. The part of dried threes and threes infected by parasites-xylophagous is correlated with toxic pollution. Float asymmetry of lives is measure of mutagenic pollution. Abnormal form of three (dichotomy, curved) is criteria of teratogenic pollution. Importance of such an indication is increased by such incidents as Chernobyl, Fucusima and so on. Algorithm for analyze of such a data is considered. The map of ecological pressure of St. Petersburg is presented.

A Comparison of Two Above-Ground Biomass Estimation Techniques Integrating Satellite-Based Remotely Sensed Data and Ground Data for Tropical and Semiarid Forests in Puerto Rico

EPA Science Inventory

Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA)...

Career Guidance in India Based on O*NET and Cultural Variables

ERIC Educational Resources Information Center

Bhatnagar, Mohit

2018-01-01

The Occupational Information Network (O*NET) is the primary source of occupational information in the United States (US). In this study, I review O*NET's usage for career guidance in India and conceive a career intervention based on it. In an empirical evaluation adopting a posttest-only experimental design with post-graduate management students…

Estimation of the Aral Sea state predictability based on the open data sources and the unique field observations

NASA Astrophysics Data System (ADS)

Izhitskiy, Alexander; Ayzel, Georgy; Zavialov, Peter; Kurbaniyazov, Abilgazi

2016-04-01

The Aral Sea, formerly one of the four largest lakes in the world, has lost over 90% of its volume during the dramatical dessication mainly caused by the severe alteration of water budget of the basin. Shrinkage of the Aral Sea resulted in profound changes of the lake's ecosystem, that became a subject for a number of publications based on a wide range of methods such as field observations, remote sensing data analysis and numerical modeling. However, by the early 21th century, the number of field studies decreased significantly due to almost complete cessation of navigation and displacement of the Aral's shoreline far away from roads and other infrastructure. Thus, only a small amount of field data (salinity, temperature, etc.) for different regions of the lake is available for the last two decades. On the other hand, a set of the open data sources (sea level variability, atmospheric reanalysis) were developed for the region. The main idea of the presented study is to estimate the possibility of prediction of the Aral Sea state using coupled system of basic geoanalysis tools, numerical modeling of hydrological cycle (both for sea and land-surface interactions with atmosphere) and state-of-art machine learning techniques. Firstly, available in situ data, obtained in the Aral Sea by Shirshov Institute and other researchers, are concerned as the "base points of state" for each year within the studied period. Secondly, consistent patterns in the interannual variability of all other available parameters, taken from the open data sources and numerical modeling predictions, are founded out. As a result, such an approach allows predicting the future state of sea basing on the possible climatic scenario.

Shallow cumuli ensemble statistics for development of a stochastic parameterization

NASA Astrophysics Data System (ADS)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a Poisson distribution, and cloud properties sub-sampled from a generalized ensemble distribution. We study the role of the different cloud subtypes in a shallow convective ensemble and how the diverse cloud properties and cloud lifetimes affect the system macro-state. To what extent does the cloud-base mass flux distribution deviate from the simple Boltzmann distribution and how does it affect the results from the stochastic model? Is the memory, provided by the finite lifetime of individual clouds, of importance for the ensemble statistics? We also test for the minimal information given as an input to the stochastic model, able to reproduce the ensemble mean statistics and the variability in a convective ensemble. An important property of the resulting distribution of the sub-grid convective states is its scale-adaptivity - the smaller the grid-size, the broader the compound distribution of the sub-grid states.

Control of AUVs using differential flatness theory and the derivative-free nonlinear Kalman Filter

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Raffo, Guilerme

2015-12-01

The paper proposes nonlinear control and filtering for Autonomous Underwater Vessels (AUVs) based on differential flatness theory and on the use of the Derivative-free nonlinear Kalman Filter. First, it is shown that the 6-DOF dynamic model of the AUV is a differentially flat one. This enables its transformation into the linear canonical (Brunovsky) form and facilitates the design of a state feedback controller. A problem that has to be dealt with is the uncertainty about the parameters of the AUV's dynamic model, as well the external perturbations which affect its motion. To cope with this, it is proposed to use a disturbance observer which is based on the Derivative-free nonlinear Kalman Filter. The considered filtering method consists of the standard Kalman Filter recursion applied on the linearized model of the vessel and of an inverse transformation based on differential flatness theory, which enables to obtain estimates of the state variables of the initial nonlinear model of the vessel. The Kalman Filter-based disturbance observer performs simultaneous estimation of the non-measurable state variables of the AUV and of the perturbation terms that affect its dynamics. By estimating such disturbances, their compensation is also succeeded through suitable modification of the feedback control input. The efficiency of the proposed AUV control and estimation scheme is confirmed through simulation experiments.

Physically based modeling in catchment hydrology at 50: Survey and outlook

NASA Astrophysics Data System (ADS)

Paniconi, Claudio; Putti, Mario

2015-09-01

Integrated, process-based numerical models in hydrology are rapidly evolving, spurred by novel theories in mathematical physics, advances in computational methods, insights from laboratory and field experiments, and the need to better understand and predict the potential impacts of population, land use, and climate change on our water resources. At the catchment scale, these simulation models are commonly based on conservation principles for surface and subsurface water flow and solute transport (e.g., the Richards, shallow water, and advection-dispersion equations), and they require robust numerical techniques for their resolution. Traditional (and still open) challenges in developing reliable and efficient models are associated with heterogeneity and variability in parameters and state variables; nonlinearities and scale effects in process dynamics; and complex or poorly known boundary conditions and initial system states. As catchment modeling enters a highly interdisciplinary era, new challenges arise from the need to maintain physical and numerical consistency in the description of multiple processes that interact over a range of scales and across different compartments of an overall system. This paper first gives an historical overview (past 50 years) of some of the key developments in physically based hydrological modeling, emphasizing how the interplay between theory, experiments, and modeling has contributed to advancing the state of the art. The second part of the paper examines some outstanding problems in integrated catchment modeling from the perspective of recent developments in mathematical and computational science.

Drivers of Seasonal Variability in Marine Boundary Layer Aerosol Number Concentration Investigated Using a Steady State Approach

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

Mohrmann, Johannes; Wood, Robert; McGibbon, Jeremy

Marine boundary layer (MBL) aerosol particles affect the climate through their interaction with MBL clouds. Although both MBL clouds and aerosol particles have pronounced seasonal cycles, the factors controlling seasonal variability of MBL aerosol particle concentration are not well-constrained. In this paper an aerosol budget is constructed representing the effects of wet deposition, free-tropospheric entrainment, primary surface sources, and advection on the MBL accumulation mode aerosol number concentration (N a). These terms are further parameterized, and by assuming that on seasonal timescales N a is in steady state, the budget equation is rearranged to form a diagnostic equation for Nmore » a based on observable variables. Using data primarily collected in the subtropical northeast Pacific during the MAGIC campaign (Marine ARM (Atmospheric Radiation Measurement) GPCI (GCSS Pacific Cross-section Intercomparison) Investigation of Clouds), estimates of both mean summer and winter N a concentrations are made using the simplified steady-state model and seasonal mean observed variables, and are found to match well with the observed N a. To attribute the modeled difference between summer and winter aerosol concentrations to individual observed variables (e.g. precipitation rate, free-tropospheric aerosol number concentration), a local sensitivity analysis is combined with the seasonal difference in observed variables. This analysis shows that despite wintertime precipitation frequency being lower than summer, the higher winter precipitation rate accounted for approximately 60% of the modeled seasonal difference in N a, which emphasizes the importance of marine stratocumulus precipitation in determining MBL aerosol concentrations on longer time scales.« less

Drivers of Seasonal Variability in Marine Boundary Layer Aerosol Number Concentration Investigated Using a Steady State Approach

DOE PAGES

Mohrmann, Johannes; Wood, Robert; McGibbon, Jeremy; ...

2018-01-21

Marine boundary layer (MBL) aerosol particles affect the climate through their interaction with MBL clouds. Although both MBL clouds and aerosol particles have pronounced seasonal cycles, the factors controlling seasonal variability of MBL aerosol particle concentration are not well-constrained. In this paper an aerosol budget is constructed representing the effects of wet deposition, free-tropospheric entrainment, primary surface sources, and advection on the MBL accumulation mode aerosol number concentration (N a). These terms are further parameterized, and by assuming that on seasonal timescales N a is in steady state, the budget equation is rearranged to form a diagnostic equation for Nmore » a based on observable variables. Using data primarily collected in the subtropical northeast Pacific during the MAGIC campaign (Marine ARM (Atmospheric Radiation Measurement) GPCI (GCSS Pacific Cross-section Intercomparison) Investigation of Clouds), estimates of both mean summer and winter N a concentrations are made using the simplified steady-state model and seasonal mean observed variables, and are found to match well with the observed N a. To attribute the modeled difference between summer and winter aerosol concentrations to individual observed variables (e.g. precipitation rate, free-tropospheric aerosol number concentration), a local sensitivity analysis is combined with the seasonal difference in observed variables. This analysis shows that despite wintertime precipitation frequency being lower than summer, the higher winter precipitation rate accounted for approximately 60% of the modeled seasonal difference in N a, which emphasizes the importance of marine stratocumulus precipitation in determining MBL aerosol concentrations on longer time scales.« less

Drivers of Seasonal Variability in Marine Boundary Layer Aerosol Number Concentration Investigated Using a Steady State Approach

NASA Astrophysics Data System (ADS)

Mohrmann, Johannes; Wood, Robert; McGibbon, Jeremy; Eastman, Ryan; Luke, Edward

2018-01-01

Marine boundary layer (MBL) aerosol particles affect the climate through their interaction with MBL clouds. Although both MBL clouds and aerosol particles have pronounced seasonal cycles, the factors controlling seasonal variability of MBL aerosol particle concentration are not well constrained. In this paper an aerosol budget is constructed representing the effects of wet deposition, free-tropospheric entrainment, primary surface sources, and advection on the MBL accumulation mode aerosol number concentration (Na). These terms are then parameterized, and by assuming that on seasonal time scales Na is in steady state, the budget equation is rearranged to form a diagnostic equation for Na based on observable variables. Using data primarily collected in the subtropical northeast Pacific during the MAGIC campaign (Marine ARM (Atmospheric Radiation Measurement) GPCI (GCSS Pacific Cross-Section Intercomparison) Investigation of Clouds), estimates of both mean summer and winter Na concentrations are made using the simplified steady state model and seasonal mean observed variables. These are found to match well with the observed Na. To attribute the modeled difference between summer and winter aerosol concentrations to individual observed variables (e.g., precipitation rate and free-tropospheric aerosol number concentration), a local sensitivity analysis is combined with the seasonal difference in observed variables. This analysis shows that despite wintertime precipitation frequency being lower than summer, the higher winter precipitation rate accounted for approximately 60% of the modeled seasonal difference in Na, which emphasizes the importance of marine stratocumulus precipitation in determining MBL aerosol concentrations on longer time scales.

Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA).

PubMed

Muckley, Matthew J; Noll, Douglas C; Fessler, Jeffrey A

2015-02-01

Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms.

Fast Parallel MR Image Reconstruction via B1-based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA)

PubMed Central

Noll, Douglas C.; Fessler, Jeffrey A.

2014-01-01

Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms. PMID:25330484

[Ecological security early-warning in Zhoushan Islands based on variable weight model].

PubMed

Zhou, Bin; Zhong, Lin-sheng; Chen, Tian; Zhou, Rui

2015-06-01

Ecological security early warning, as an important content of ecological security research, is of indicating significance in maintaining regional ecological security. Based on driving force, pressure, state, impact and response (D-P-S-I-R) framework model, this paper took Zhoushan Islands in Zhejiang Province as an example to construct the ecological security early warning index system, test degrees of ecological security early warning of Zhoushan Islands from 2000 to 2012 by using the method of variable weight model, and forecast ecological security state of 2013-2018 by Markov prediction method. The results showed that the variable weight model could meet the study needs of ecological security early warning of Zhoushan Islands. There was a fluctuant rising ecological security early warning index from 0.286 to 0.484 in Zhoushan Islands between year 2000 and 2012, in which the security grade turned from "serious alert" into " medium alert" and the indicator light turned from "orange" to "yellow". The degree of ecological security warning was "medium alert" with the light of "yellow" for Zhoushan Islands from 2013 to 2018. These findings could provide a reference for ecological security maintenance of Zhoushan Islands.

Quantum anonymous voting with unweighted continuous-variable graph states

NASA Astrophysics Data System (ADS)

Guo, Ying; Feng, Yanyan; Zeng, Guihua

2016-08-01

Motivated by the revealing topological structures of continuous-variable graph state (CVGS), we investigate the design of quantum voting scheme, which has serious advantages over the conventional ones in terms of efficiency and graphicness. Three phases are included, i.e., the preparing phase, the voting phase and the counting phase, together with three parties, i.e., the voters, the tallyman and the ballot agency. Two major voting operations are performed on the yielded CVGS in the voting process, namely the local rotation transformation and the displacement operation. The voting information is carried by the CVGS established before hand, whose persistent entanglement is deployed to keep the privacy of votes and the anonymity of legal voters. For practical applications, two CVGS-based quantum ballots, i.e., comparative ballot and anonymous survey, are specially designed, followed by the extended ballot schemes for the binary-valued and multi-valued ballots under some constraints for the voting design. Security is ensured by entanglement of the CVGS, the voting operations and the laws of quantum mechanics. The proposed schemes can be implemented using the standard off-the-shelf components when compared to discrete-variable quantum voting schemes attributing to the characteristics of the CV-based quantum cryptography.

Socioeconomic determinants of fertility: selected Mexican regions, 1976-1977.

PubMed

Pick, J B; Butler, E W; Pavgi, S

1988-01-01

Cumulative fertility is analyzed for 4 regions of Mexico, based on World Fertility Survey data of 1976-77; the state of Baja California, the Northwest region, the State of Jalisco, and the Northeast region. Based on stepwise regression methodology, the study compares results for 12 subsamples of married respondents, 3 age categories by 4 regions. The dependent variables are children ever born and children ever born in the last 5 years. Migration, urban, educational, and occupational variables are included as independent variables. Regression results reveal level of education is the major, and negative, influence on fertility. Other results include specific negative effects for prior occupation, size of place of residence, and childhood place of residence. Fertility effects appear different for migration origin and destination regions, but more similar for younger ages. Effects of migration on fertility are small. Mean fertility as measured by children ever born was 4.34 for the 1976-77 World Fertility Survey samples versus 3.69 for the Mexican census of 1980. Fertility varied somewhat by region with the highest and lowest values in Jalisco and the Northeast, respectively. Expected age-related changes in fertility were noted.

Associations between Depressive State and Impaired Higher-Level Functional Capacity in the Elderly with Long-Term Care Requirements.

PubMed

Ogata, Soshiro; Hayashi, Chisato; Sugiura, Keiko; Hayakawa, Kazuo

2015-01-01

Depressive state has been reported to be significantly associated with higher-level functional capacity among community-dwelling elderly. However, few studies have investigated the associations among people with long-term care requirements. We aimed to investigate the associations between depressive state and higher-level functional capacity and obtain marginal odds ratios using propensity score analyses in people with long-term care requirements. We conducted a cross-sectional study based on participants aged ≥ 65 years (n = 545) who were community dwelling and used outpatient care services for long-term preventive care. We measured higher-level functional capacity, depressive state, and possible confounders. Then, we estimated the marginal odds ratios (i.e., the change in odds of impaired higher-level functional capacity if all versus no participants were exposed to depressive state) by logistic models using generalized linear models with the inverse probability of treatment weighting (IPTW) for propensity score and design-based standard errors. Depressive state was used as the exposure variable and higher-level functional capacity as the outcome variable. The all absolute standardized differences after the IPTW using the propensity scores were < 10% which indicated negligible differences in the mean or prevalence of the covariates between non-depressive state and depressive state. The marginal odds ratios were estimated by the logistic models with IPTW using the propensity scores. The marginal odds ratios were 2.17 (95%CI: 1.13-4.19) for men and 2.57 (95%CI: 1.26-5.26) for women. Prevention of depressive state may contribute to not only depressive state but also higher-level functional capacity.

A generator for unique quantum random numbers based on vacuum states

NASA Astrophysics Data System (ADS)

Gabriel, Christian; Wittmann, Christoffer; Sych, Denis; Dong, Ruifang; Mauerer, Wolfgang; Andersen, Ulrik L.; Marquardt, Christoph; Leuchs, Gerd

2010-10-01

Random numbers are a valuable component in diverse applications that range from simulations over gambling to cryptography. The quest for true randomness in these applications has engendered a large variety of different proposals for producing random numbers based on the foundational unpredictability of quantum mechanics. However, most approaches do not consider that a potential adversary could have knowledge about the generated numbers, so the numbers are not verifiably random and unique. Here we present a simple experimental setup based on homodyne measurements that uses the purity of a continuous-variable quantum vacuum state to generate unique random numbers. We use the intrinsic randomness in measuring the quadratures of a mode in the lowest energy vacuum state, which cannot be correlated to any other state. The simplicity of our source, combined with its verifiably unique randomness, are important attributes for achieving high-reliability, high-speed and low-cost quantum random number generators.

Flatness-based control and Kalman filtering for a continuous-time macroeconomic model

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Ghosh, T.; Busawon, K.; Binns, R.

2017-11-01

The article proposes flatness-based control for a nonlinear macro-economic model of the UK economy. The differential flatness properties of the model are proven. This enables to introduce a transformation (diffeomorphism) of the system's state variables and to express the state-space description of the model in the linear canonical (Brunowsky) form in which both the feedback control and the state estimation problem can be solved. For the linearized equivalent model of the macroeconomic system, stabilizing feedback control can be achieved using pole placement methods. Moreover, to implement stabilizing feedback control of the system by measuring only a subset of its state vector elements the Derivative-free nonlinear Kalman Filter is used. This consists of the Kalman Filter recursion applied on the linearized equivalent model of the financial system and of an inverse transformation that is based again on differential flatness theory. The asymptotic stability properties of the control scheme are confirmed.

Photoswitchable carbohydrate-based fluorosurfactants as tuneable ice recrystallization inhibitors.

PubMed

Adam, Madeleine K; Hu, Yingxue; Poisson, Jessica S; Pottage, Matthew J; Ben, Robert N; Wilkinson, Brendan L

2017-02-01

Cryopreservation is an important technique employed for the storage and preservation of biological tissues and cells. The limited effectiveness and significant toxicity of conventionally-used cryoprotectants, such as DMSO, have prompted efforts toward the rational design of less toxic alternatives, including carbohydrate-based surfactants. In this paper, we report the modular synthesis and ice recrystallization inhibition (IRI) activity of a library of variably substituted, carbohydrate-based fluorosurfactants. Carbohydrate-based fluorosurfactants possessed a variable mono- or disaccharide head group appended to a hydrophobic fluoroalkyl-substituted azobenzene tail group. Light-addressable fluorosurfactants displayed weak-to-moderate IRI activity that could be tuned through selection of carbohydrate head group, position of the trifluoroalkyl group on the azobenzene ring, and isomeric state of the azobenzene tail fragment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Superconducting fault current-limiter with variable shunt impedance

DOEpatents

Llambes, Juan Carlos H; Xiong, Xuming

2013-11-19

A superconducting fault current-limiter is provided, including a superconducting element configured to resistively or inductively limit a fault current, and one or more variable-impedance shunts electrically coupled in parallel with the superconducting element. The variable-impedance shunt(s) is configured to present a first impedance during a superconducting state of the superconducting element and a second impedance during a normal resistive state of the superconducting element. The superconducting element transitions from the superconducting state to the normal resistive state responsive to the fault current, and responsive thereto, the variable-impedance shunt(s) transitions from the first to the second impedance. The second impedance of the variable-impedance shunt(s) is a lower impedance than the first impedance, which facilitates current flow through the variable-impedance shunt(s) during a recovery transition of the superconducting element from the normal resistive state to the superconducting state, and thus, facilitates recovery of the superconducting element under load.

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

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

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi

2014-04-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m -2 yr -1 and total NPP in the range of 318–490more » Tg C yr -1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m -2 yr -1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m -2 yr -1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.« less

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

ASCS online fault detection and isolation based on an improved MPCA

NASA Astrophysics Data System (ADS)

Peng, Jianxin; Liu, Haiou; Hu, Yuhui; Xi, Junqiang; Chen, Huiyan

2014-09-01

Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling ( T 2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T 2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

Investigation of the inputs for the MEPDG for rigid pavements.

DOT National Transportation Integrated Search

2013-03-01

There are great advantages in the design of infrastructure if design procedures are used that are based : on mechanisms and variables that determine the performance of the element in service. The American : Association of State Highway and Transporta...

Extended state observer-based motion synchronisation control for hybrid actuation system of large civil aircraft

NASA Astrophysics Data System (ADS)

Wang, Xingjian; Shi, Cun; Wang, Shaoping

2017-07-01

Hybrid actuation system with dissimilar redundant actuators, which is composed of a hydraulic actuator (HA) and an electro-hydrostatic actuator (EHA), has been applied on modern civil aircraft to improve the reliability. However, the force fighting problem arises due to different dynamic performances between HA and EHA. This paper proposes an extended state observer (ESO)-based motion synchronisation control method. To cope with the problem of unavailability of the state signals, the well-designed ESO is utilised to observe the HA and EHA state variables which are unmeasured. In particular, the extended state of ESO can estimate the lumped effect of the unknown external disturbances acting on the control surface, the nonlinear dynamics, uncertainties, and the coupling term between HA and EHA. Based on the observed states of ESO, motion synchronisation controllers are presented to make HA and EHA to simultaneously track the desired motion trajectories, which are generated by a trajectory generator. Additionally, the unknown disturbances and the coupling terms can be compensated by using the extended state of the proposed ESO. Finally, comparative simulation results indicate that the proposed ESO-based motion synchronisation controller can achieve great force fighting reduction between HA and EHA.

Identification of the protein folding transition state from molecular dynamics trajectories

NASA Astrophysics Data System (ADS)

Muff, S.; Caflisch, A.

2009-03-01

The rate of protein folding is governed by the transition state so that a detailed characterization of its structure is essential for understanding the folding process. In vitro experiments have provided a coarse-grained description of the folding transition state ensemble (TSE) of small proteins. Atomistic details could be obtained by molecular dynamics (MD) simulations but it is not straightforward to extract the TSE directly from the MD trajectories, even for small peptides. Here, the structures in the TSE are isolated by the cut-based free-energy profile (cFEP) using the network whose nodes and links are configurations sampled by MD and direct transitions among them, respectively. The cFEP is a barrier-preserving projection that does not require arbitrarily chosen progress variables. First, a simple two-dimensional free-energy surface is used to illustrate the successful determination of the TSE by the cFEP approach and to explain the difficulty in defining boundary conditions of the Markov state model for an entropically stabilized free-energy minimum. The cFEP is then used to extract the TSE of a β-sheet peptide with a complex free-energy surface containing multiple basins and an entropic region. In contrast, Markov state models with boundary conditions defined by projected variables and conventional histogram-based free-energy profiles are not able to identify the TSE of the β-sheet peptide.

How Does Variability in Aragonite Saturation Proxies Impact Our Estimates of the Intensity and Duration of Exposure to Aragonite Corrosive Conditions in a Coastal Upwelling System?

NASA Astrophysics Data System (ADS)

Abell, J. T.; Jacobsen, J.; Bjorkstedt, E.

2016-02-01

Determining aragonite saturation state (Ω) in seawater requires measurement of two parameters of the carbonate system: most commonly dissolved inorganic carbon (DIC) and total alkalinity (TA). The routine measurement of DIC and TA is not always possible on frequently repeated hydrographic lines or at moored-time series that collect hydrographic data at short time intervals. In such cases a proxy can be developed that relates the saturation state as derived from one time or infrequent DIC and TA measurements (Ωmeas) to more frequently measured parameters such as dissolved oxygen (DO) and temperature (Temp). These proxies are generally based on best-fit parameterizations that utilize references values of DO and Temp and adjust linear coefficients until the error between the proxy-derived saturation state (Ωproxy) and Ωmeas is minimized. Proxies have been used to infer Ω from moored hydrographic sensors and gliders which routinely collect DO and Temp data but do not include carbonate parameter measurements. Proxies can also calculate Ω in regional oceanographic models which do not explicitly include carbonate parameters. Here we examine the variability and accuracy of Ωproxy along a near-shore hydrographic line and a moored-time series stations at Trinidad Head, CA. The saturation state is determined using proxies from different coastal regions of the California Current Large Marine Ecosystem and from different years of sampling along the hydrographic line. We then calculate the variability and error associated with the use of different proxy coefficients, the sensitivity to reference values and the inclusion of additional variables. We demonstrate how this variability affects estimates of the intensity and duration of exposure to aragonite corrosive conditions on the near-shore shelf and in the water column.

A comparison of recharge rates in aquifers of the United States based on groundwater-age data

USGS Publications Warehouse

McMahon, P.B.; Plummer, Niel; Böhlke, J.K.; Shapiro, S.D.; Hinkle, S.R.

2011-01-01

An overview is presented of existing groundwater-age data and their implications for assessing rates and timescales of recharge in selected unconfined aquifer systems of the United States. Apparent age distributions in aquifers determined from chlorofluorocarbon, sulfur hexafluoride, tritium/helium-3, and radiocarbon measurements from 565 wells in 45 networks were used to calculate groundwater recharge rates. Timescales of recharge were defined by 1,873 distributed tritium measurements and 102 radiocarbon measurements from 27 well networks. Recharge rates ranged from < 10 to 1,200 mm/yr in selected aquifers on the basis of measured vertical age distributions and assuming exponential age gradients. On a regional basis, recharge rates based on tracers of young groundwater exhibited a significant inverse correlation with mean annual air temperature and a significant positive correlation with mean annual precipitation. Comparison of recharge derived from groundwater ages with recharge derived from stream base-flow evaluation showed similar overall patterns but substantial local differences. Results from this compilation demonstrate that age-based recharge estimates can provide useful insights into spatial and temporal variability in recharge at a national scale and factors controlling that variability. Local age-based recharge estimates provide empirical data and process information that are needed for testing and improving more spatially complete model-based methods.

Path-integral methods for analyzing the effects of fluctuations in stochastic hybrid neural networks.

PubMed

Bressloff, Paul C

2015-01-01

We consider applications of path-integral methods to the analysis of a stochastic hybrid model representing a network of synaptically coupled spiking neuronal populations. The state of each local population is described in terms of two stochastic variables, a continuous synaptic variable and a discrete activity variable. The synaptic variables evolve according to piecewise-deterministic dynamics describing, at the population level, synapses driven by spiking activity. The dynamical equations for the synaptic currents are only valid between jumps in spiking activity, and the latter are described by a jump Markov process whose transition rates depend on the synaptic variables. We assume a separation of time scales between fast spiking dynamics with time constant [Formula: see text] and slower synaptic dynamics with time constant τ. This naturally introduces a small positive parameter [Formula: see text], which can be used to develop various asymptotic expansions of the corresponding path-integral representation of the stochastic dynamics. First, we derive a variational principle for maximum-likelihood paths of escape from a metastable state (large deviations in the small noise limit [Formula: see text]). We then show how the path integral provides an efficient method for obtaining a diffusion approximation of the hybrid system for small ϵ. The resulting Langevin equation can be used to analyze the effects of fluctuations within the basin of attraction of a metastable state, that is, ignoring the effects of large deviations. We illustrate this by using the Langevin approximation to analyze the effects of intrinsic noise on pattern formation in a spatially structured hybrid network. In particular, we show how noise enlarges the parameter regime over which patterns occur, in an analogous fashion to PDEs. Finally, we carry out a [Formula: see text]-loop expansion of the path integral, and use this to derive corrections to voltage-based mean-field equations, analogous to the modified activity-based equations generated from a neural master equation.

How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables.

PubMed

Brooks, Mollie E; Mugabo, Marianne; Rodgers, Gwendolen M; Benton, Timothy G; Ozgul, Arpat

2016-03-01

Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g. individual size) are commonly used in demographic analyses to represent the effect of past environments on demographic rates. We quantified how well the size of individuals captures the effects of a population's past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; that is, different measures of body size (e.g. length, volume, mass, fat stores) will be better or worse proxies for various life-history processes. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

On-chip continuous-variable quantum entanglement

NASA Astrophysics Data System (ADS)

Masada, Genta; Furusawa, Akira

2016-09-01

Entanglement is an essential feature of quantum theory and the core of the majority of quantum information science and technologies. Quantum computing is one of the most important fruits of quantum entanglement and requires not only a bipartite entangled state but also more complicated multipartite entanglement. In previous experimental works to demonstrate various entanglement-based quantum information processing, light has been extensively used. Experiments utilizing such a complicated state need highly complex optical circuits to propagate optical beams and a high level of spatial interference between different light beams to generate quantum entanglement or to efficiently perform balanced homodyne measurement. Current experiments have been performed in conventional free-space optics with large numbers of optical components and a relatively large-sized optical setup. Therefore, they are limited in stability and scalability. Integrated photonics offer new tools and additional capabilities for manipulating light in quantum information technology. Owing to integrated waveguide circuits, it is possible to stabilize and miniaturize complex optical circuits and achieve high interference of light beams. The integrated circuits have been firstly developed for discrete-variable systems and then applied to continuous-variable systems. In this article, we review the currently developed scheme for generation and verification of continuous-variable quantum entanglement such as Einstein-Podolsky-Rosen beams using a photonic chip where waveguide circuits are integrated. This includes balanced homodyne measurement of a squeezed state of light. As a simple example, we also review an experiment for generating discrete-variable quantum entanglement using integrated waveguide circuits.

On the use of internal state variables in thermoviscoplastic constitutive equations

NASA Technical Reports Server (NTRS)

Allen, D. H.; Beek, J. M.

1985-01-01

The general theory of internal state variables are reviewed to apply it to inelastic metals in use in high temperature environments. In this process, certain constraints and clarifications will be made regarding internal state variables. It is shown that the Helmholtz free energy can be utilized to construct constitutive equations which are appropriate for metallic superalloys. Internal state variables are shown to represent locally averaged measures of dislocation arrangement, dislocation density, and intergranular fracture. The internal state variable model is demonstrated to be a suitable framework for comparison of several currently proposed models for metals and can therefore be used to exhibit history dependence, nonlinearity, and rate as well as temperature sensitivity.

A Tightly Coupled Non-Equilibrium Magneto-Hydrodynamic Model for Inductively Coupled RF Plasmas

DTIC Science & Technology

2016-02-29

development a tightly coupled magneto-hydrodynamic model for Inductively Coupled Radio- Frequency (RF) Plasmas. Non Local Thermodynamic Equilibrium (NLTE...for Inductively Coupled Radio-Frequency (RF) Plasmas. Non Local Thermodynamic Equilibrium (NLTE) effects are described based on a hybrid State-to-State... thermodynamic variable. This choice allows one to hide the non-linearity of the gas (total) thermal conductivity κ and can partially alle- 2 viate numerical

Information Leakage Analysis by Abstract Interpretation

NASA Astrophysics Data System (ADS)

Zanioli, Matteo; Cortesi, Agostino

Protecting the confidentiality of information stored in a computer system or transmitted over a public network is a relevant problem in computer security. The approach of information flow analysis involves performing a static analysis of the program with the aim of proving that there will not be leaks of sensitive information. In this paper we propose a new domain that combines variable dependency analysis, based on propositional formulas, and variables' value analysis, based on polyhedra. The resulting analysis is strictly more accurate than the state of the art abstract interpretation based analyses for information leakage detection. Its modular construction allows to deal with the tradeoff between efficiency and accuracy by tuning the granularity of the abstraction and the complexity of the abstract operators.

Testing quantum contextuality of continuous-variable states

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

McKeown, Gerard; Paternostro, Mauro; Paris, Matteo G. A.

2011-06-15

We investigate the violation of noncontextuality by a class of continuous-variable states, including variations of entangled coherent states and a two-mode continuous superposition of coherent states. We generalize the Kochen-Specker (KS) inequality discussed by Cabello [A. Cabello, Phys. Rev. Lett. 101, 210401 (2008)] by using effective bidimensional observables implemented through physical operations acting on continuous-variable states, in a way similar to an approach to the falsification of Bell-Clauser-Horne-Shimony-Holt inequalities put forward recently. We test for state-independent violation of KS inequalities under variable degrees of state entanglement and mixedness. We then demonstrate theoretically the violation of a KS inequality for anymore » two-mode state by using pseudospin observables and a generalized quasiprobability function.« less

Use of the quasi-geostrophic dynamical framework to reconstruct the 3-D ocean state in a high-resolution realistic simulation of North Atlantic.

NASA Astrophysics Data System (ADS)

Fresnay, Simon; Ponte, Aurélien

2017-04-01

The quasi-geostrophic (QG) framework has been, is and will be still for years to come a cornerstone method linking observations with estimates of the ocean circulation and state. We have used here the QG framework to reconstruct dynamical variables of the 3-D ocean in a state-of-the-art high-resolution (1/60 deg, 300 vertical levels) numerical simulation of the North Atlantic (NATL60). The work was carried out in 3 boxes of the simulation: Gulf Stream, Azores and Reykjaness Ridge. In a first part, general diagnostics describing the eddying dynamics have been performed and show that the QG scaling verifies in general, at depths distant from mixed layer and bathymetric gradients. Correlations with surface observables variables (e.g. temperature, sea level) were computed and estimates of quasi-geostrophic potential vorticity (QGPV) were reconstructed by the means of regression laws. It is shown that that reconstruction of QGPV exhibits valuable skill for a restricted scale range, mainly using sea level as the variable of regression. Additional discussion is given, based on the flow balanced with QGPV. This work is part of the DIMUP project, aiming to improve our ability to operationnaly estimate the ocean state.

Application of State Analysis and Goal-based Operations to a MER Mission Scenario

NASA Technical Reports Server (NTRS)

Morris, John Richard; Ingham, Michel D.; Mishkin, Andrew H.; Rasmussen, Robert D.; Starbird, Thomas W.

2006-01-01

State Analysis is a model-based systems engineering methodology employing a rigorous discovery process which articulates operations concepts and operability needs as an integrated part of system design. The process produces requirements on system and software design in the form of explicit models which describe the system behavior in terms of state variables and the relationships among them. By applying State Analysis to an actual MER flight mission scenario, this study addresses the specific real world challenges of complex space operations and explores technologies that can be brought to bear on future missions. The paper first describes the tools currently used on a daily basis for MER operations planning and provides an in-depth description of the planning process, in the context of a Martian day's worth of rover engineering activities, resource modeling, flight rules, science observations, and more. It then describes how State Analysis allows for the specification of a corresponding goal-based sequence that accomplishes the same objectives, with several important additional benefits.

A stochastic hybrid systems based framework for modeling dependent failure processes

PubMed Central

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods. PMID:28231313

A stochastic hybrid systems based framework for modeling dependent failure processes.

PubMed

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods.

[Determinants of dental services utilization by adults: a population-based study in Florianópolis, Santa Catarina State, Brazil].

PubMed

Miranda, Camila Dal-Bó Coradini; Peres, Marco Aurélio

2013-11-01

This study aimed to estimate the prevalence of dental services utilization by adults and to identify associated socioeconomic, demographic, behavioral, and self-awareness factors. A cross-sectional population-based study was conducted with adults living in the urban area of Florianópolis, Santa Catarina State, Brazil, in 2009. Associations were tested between use of dental services and predisposing, enabling, and needs-based variables. Multivariate analysis was conducted using Poisson regression with estimates of prevalence ratios and was stratified by place of last dental appointment. Prevalence of dental services utilization was 66% (95%CI: 62.9-70.7). Dental visits were 20% more frequent among women and 72% more frequent among individuals with more schooling (the latter in both public and private dental services). Individuals with private dental plans used dental services 13% more than those without. Schooling was the most important variable in predicting utilization. The study's results show the importance of monitoring associated factors in order to promote more equitable use of dental services.

Estimating 1970-99 average annual groundwater recharge in Wisconsin using streamflow data

USGS Publications Warehouse

Gebert, Warren A.; Walker, John F.; Kennedy, James L.

2011-01-01

Average annual recharge in Wisconsin for the period 1970-99 was estimated using streamflow data from U.S. Geological Survey continuous-record streamflow-gaging stations and partial-record sites. Partial-record sites have discharge measurements collected during low-flow conditions. The average annual base flow of a stream divided by the drainage area is a good approximation of the recharge rate; therefore, once average annual base flow is determined recharge can be calculated. Estimates of recharge for nearly 72 percent of the surface area of the State are provided. The results illustrate substantial spatial variability of recharge across the State, ranging from less than 1 inch to more than 12 inches per year. The average basin size for partial-record sites (50 square miles) was less than the average basin size for the gaging stations (305 square miles). Including results for smaller basins reveals a spatial variability that otherwise would be smoothed out using only estimates for larger basins. An error analysis indicates that the techniques used provide base flow estimates with standard errors ranging from 5.4 to 14 percent.

Saturation-state sensitivity of marine bivalve larvae to ocean acidification

NASA Astrophysics Data System (ADS)

Waldbusser, George G.; Hales, Burke; Langdon, Chris J.; Haley, Brian A.; Schrader, Paul; Brunner, Elizabeth L.; Gray, Matthew W.; Miller, Cale A.; Gimenez, Iria

2015-03-01

Ocean acidification results in co-varying inorganic carbon system variables. Of these, an explicit focus on pH and organismal acid-base regulation has failed to distinguish the mechanism of failure in highly sensitive bivalve larvae. With unique chemical manipulations of seawater we show definitively that larval shell development and growth are dependent on seawater saturation state, and not on carbon dioxide partial pressure or pH. Although other physiological processes are affected by pH, mineral saturation state thresholds will be crossed decades to centuries ahead of pH thresholds owing to nonlinear changes in the carbonate system variables as carbon dioxide is added. Our findings were repeatable for two species of bivalve larvae could resolve discrepancies in experimental results, are consistent with a previous model of ocean acidification impacts due to rapid calcification in bivalve larvae, and suggest a fundamental ocean acidification bottleneck at early life-history for some marine keystone species.

Tobacco cessation among users of telephone and web-based interventions--four states, 2011-2012.

PubMed

Puckett, Mary; Neri, Antonio; Thompson, Trevor; Underwood, J Michael; Momin, Behnoosh; Kahende, Jennifer; Zhang, Lei; Stewart, Sherri L

2015-01-02

Smoking caused an average of 480,000 deaths per year in the United States from 2005 to 2009, and three in 10 cancer deaths in the United States are tobacco related. Tobacco cessation is a high public health priority, and all states offer some form of tobacco cessation service. Quitlines provide telephone-based counseling services and are an effective intervention for tobacco cessation. In addition to telephone services, 96% of all U.S. quitlines offer Web-based cessation services. Evidence is limited on the number of tobacco users who use more than one type of service, and studies report mixed results on whether combined telephone and Web-based counseling improves long-term cessation compared with telephone alone. CDC conducted a survey of users of telephone and Web-based cessation services in four states to determine the cessation success of users of these interventions. After adjusting for multiple variables, persons who used both telephone and Web-based services were more likely to report abstinence from smoking for 30 days at follow up (odds ratio = 1.3) compared with telephone-only users and with Web-only users (odds ratio = 1.5). These findings suggest that states might consider offering both types of cessation services to increase cessation success.

Application of Consider Covariance to the Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Lundberg, John B.

1996-01-01

The extended Kalman filter (EKF) is the basis for many applications of filtering theory to real-time problems where estimates of the state of a dynamical system are to be computed based upon some set of observations. The form of the EKF may vary somewhat from one application to another, but the fundamental principles are typically unchanged among these various applications. As is the case in many filtering applications, models of the dynamical system (differential equations describing the state variables) and models of the relationship between the observations and the state variables are created. These models typically employ a set of constants whose values are established my means of theory or experimental procedure. Since the estimates of the state are formed assuming that the models are perfect, any modeling errors will affect the accuracy of the computed estimates. Note that the modeling errors may be errors of commission (errors in terms included in the model) or omission (errors in terms excluded from the model). Consequently, it becomes imperative when evaluating the performance of real-time filters to evaluate the effect of modeling errors on the estimates of the state.

The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study.

PubMed

Ross, James L; Andersen, Peter F

2018-04-17

The Kalman filter is an efficient data assimilation tool to refine an estimate of a state variable using measured data and the variable's correlations in space and/or time. The ensemble Kalman filter (EnKF) (Evensen 2004, 2009) is a Kalman filter variant that employs Monte Carlo analysis to define the correlations that help to refine the updated state. While use of EnKF in hydrology is somewhat limited, it has been successfully applied in other fields of engineering (e.g., oil reservoir modeling, weather forecasting). Here, EnKF is used to refine a simulated groundwater tetrachloroethylene (TCE) plume that underlies the Tooele Army Depot-North (TEAD-N) in Utah, based on observations of TCE in the aquifer. The resulting EnKF-based assimilated plume is simulated forward in time to predict future plume migration. The correlations that underpin EnKF updating implicitly contain information about how the plume developed over time under the influence of complex site hydrology and variable source history, as they are predicated on multiple realizations of a well-calibrated numerical groundwater flow and transport model. The EnKF methodology is compared to an ordinary kriging-based assimilation method with respect to the accurate representation of plume concentrations in order to determine the relative efficacy of EnKF for water quality data assimilation. © 2018, National Ground Water Association.

Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation

DTIC Science & Technology

2012-09-01

interpreting the state vector as the health indicator and a threshold is used on this variable in order to compute EOL (end-of-life) and RUL. Here, we...End-of-life ( EOL ) would match the true spread and would not change from one experiment to another. This is, however, in practice impossible to achieve

An Ensemble Successive Project Algorithm for Liquor Detection Using Near Infrared Sensor.

PubMed

Qu, Fangfang; Ren, Dong; Wang, Jihua; Zhang, Zhong; Lu, Na; Meng, Lei

2016-01-11

Spectral analysis technique based on near infrared (NIR) sensor is a powerful tool for complex information processing and high precision recognition, and it has been widely applied to quality analysis and online inspection of agricultural products. This paper proposes a new method to address the instability of small sample sizes in the successive projections algorithm (SPA) as well as the lack of association between selected variables and the analyte. The proposed method is an evaluated bootstrap ensemble SPA method (EBSPA) based on a variable evaluation index (EI) for variable selection, and is applied to the quantitative prediction of alcohol concentrations in liquor using NIR sensor. In the experiment, the proposed EBSPA with three kinds of modeling methods are established to test their performance. In addition, the proposed EBSPA combined with partial least square is compared with other state-of-the-art variable selection methods. The results show that the proposed method can solve the defects of SPA and it has the best generalization performance and stability. Furthermore, the physical meaning of the selected variables from the near infrared sensor data is clear, which can effectively reduce the variables and improve their prediction accuracy.

Bounds on internal state variables in viscoplasticity

NASA Technical Reports Server (NTRS)

Freed, Alan D.

1993-01-01

A typical viscoplastic model will introduce up to three types of internal state variables in order to properly describe transient material behavior; they are as follows: the back stress, the yield stress, and the drag strength. Different models employ different combinations of these internal variables--their selection and description of evolution being largely dependent on application and material selection. Under steady-state conditions, the internal variables cease to evolve and therefore become related to the external variables (stress and temperature) through simple functional relationships. A physically motivated hypothesis is presented that links the kinetic equation of viscoplasticity with that of creep under steady-state conditions. From this hypothesis one determines how the internal variables relate to one another at steady state, but most importantly, one obtains bounds on the magnitudes of stress and back stress, and on the yield stress and drag strength.

Use of streamflow data to estimate base flowground-water recharge for Wisconsin

USGS Publications Warehouse

Gebert, W.A.; Radloff, M.J.; Considine, E.J.; Kennedy, J.L.

2007-01-01

The average annual base flow/recharge was determined for streamflow-gaging stations throughout Wisconsin by base-flow separation. A map of the State was prepared that shows the average annual base flow for the period 1970-99 for watersheds at 118 gaging stations. Trend analysis was performed on 22 of the 118 streamflow-gaging stations that had long-term records, unregulated flow, and provided aerial coverage of the State. The analysis found that a statistically significant increasing trend was occurring for watersheds where the primary land use was agriculture. Most gaging stations where the land cover was forest had no significant trend. A method to estimate the average annual base flow at ungaged sites was developed by multiple-regression analysis using basin characteristics. The equation with the lowest standard error of estimate, 9.5%, has drainage area, soil infiltration and base flow factor as independent variables. To determine the average annual base flow for smaller watersheds, estimates were made at low-flow partial-record stations in 3 of the 12 major river basins in Wisconsin. Regression equations were developed for each of the three major river basins using basin characteristics. Drainage area, soil infiltration, basin storage and base-flow factor were the independent variables in the regression equations with the lowest standard error of estimate. The standard error of estimate ranged from 17% to 52% for the three river basins. ?? 2007 American Water Resources Association.

Multiswitching combination synchronisation of non-identical fractional-order chaotic systems

NASA Astrophysics Data System (ADS)

Bhat, Muzaffar Ahmad; Khan, Ayub

2018-06-01

In this paper, multiswitching combination synchronisation (MSCS) scheme has been investigated in a class of three non-identical fractional-order chaotic systems. The fractional-order Lorenz and Chen systems are taken as the drive systems. The combination of multidrive systems is then synchronised with the fractional-order Lü chaotic system. In MSCS, the state variables of the two drive systems synchronise with different state variables of the response system, simultaneously. Based on the stability of fractional-order chaotic systems, the MSCS of three fractional-order non-identical systems has been investigated. For the synchronisation of three non-identical fractional-order chaotic systems, suitable controllers have been designed. Theoretical analysis and numerical results are presented to demonstrate the validity and feasibility of the applied method.

Crowd-Sourced Radio Science at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Fry, C. D.; McTernan, J. K.; Suggs, R. M.; Rawlins, L.; Krause, L. H.; Gallagher, D. L.; Adams, M. L.

2018-01-01

August 21, 2017 provided a unique opportunity to investigate the effects of the total solar eclipse on high frequency (HF) radio propagation and ionospheric variability. In Marshall Space Flight Center's partnership with the US Space and Rocket Center (USSRC) and Austin Peay State University (APSU), we engaged citizen scientists and students in an investigation of the effects of an eclipse on the mid-latitude ionosphere. Activities included fieldwork and station-based data collection of HF Amateur Radio frequency bands and VLF radio waves before, during, and after the eclipse to build a continuous record of changing propagation conditions as the moon's shadow marched across the United States. Post-eclipse radio propagation analysis provided insights into ionospheric variability due to the eclipse.

A risk-based statistical investigation of the quantification of polymorphic purity of a pharmaceutical candidate by solid-state 19F NMR.

PubMed

Barry, Samantha J; Pham, Tran N; Borman, Phil J; Edwards, Andrew J; Watson, Simon A

2012-01-27

The DMAIC (Define, Measure, Analyse, Improve and Control) framework and associated statistical tools have been applied to both identify and reduce variability observed in a quantitative (19)F solid-state NMR (SSNMR) analytical method. The method had been developed to quantify levels of an additional polymorph (Form 3) in batches of an active pharmaceutical ingredient (API), where Form 1 is the predominant polymorph. In order to validate analyses of the polymorphic form, a single batch of API was used as a standard each time the method was used. The level of Form 3 in this standard was observed to gradually increase over time, the effect not being immediately apparent due to method variability. In order to determine the cause of this unexpected increase and to reduce method variability, a risk-based statistical investigation was performed to identify potential factors which could be responsible for these effects. Factors identified by the risk assessment were investigated using a series of designed experiments to gain a greater understanding of the method. The increase of the level of Form 3 in the standard was primarily found to correlate with the number of repeat analyses, an effect not previously reported in SSNMR literature. Differences in data processing (phasing and linewidth) were found to be responsible for the variability in the method. After implementing corrective actions the variability was reduced such that the level of Form 3 was within an acceptable range of ±1% ww(-1) in fresh samples of API. Copyright © 2011. Published by Elsevier B.V.

Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning.

PubMed

Kesler, Shelli R; Rao, Arvind; Blayney, Douglas W; Oakley-Girvan, Ingrid A; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34-65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy ( p < 0.0001). The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables ( p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.

Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning

PubMed Central

Kesler, Shelli R.; Rao, Arvind; Blayney, Douglas W.; Oakley-Girvan, Ingrid A.; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34–65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy (p < 0.0001). The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables (p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment. PMID:29187817

Variables that Correlate with Faculty Use of Research-Based Instructional Strategies

NASA Astrophysics Data System (ADS)

Henderson, Charles; Dancy, Melissa H.; Niewiadomska-Bugaj, Magdalena

2010-10-01

During the Fall of 2008 a web survey, designed to collect information about pedagogical knowledge and practices, was completed by a representative sample of 722 physics faculty across the United States (a 50.3% response rate). This paper examines how 20 predictor variables correlate with faculty knowledge about and use of research-based instructional strategies (RBIS). Profiles were developed for each of four faculty levels of knowledge about and use of RBIS. Logistic regression analysis was used to identify a subset of the variables that could predict group membership. Five significant predictor variables were identified. High levels of knowledge and use of RBIS were associated with the following characteristics: attendee of the physics and astronomy new faculty workshop, attendee of at least one talk or workshop related to teaching in the last two years, satisfaction with meeting instructional goals, regular reader of one or more journals related to teaching, and being female. High research productivity and large class sizes were not found to be barriers to use of at least some RBIS.

Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2017-10-01

We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space. Copyright © 2017 Elsevier B.V. All rights reserved.

New and Improved GLDAS and NLDAS Data Sets and Data Services at HDISC/NASA

NASA Technical Reports Server (NTRS)

Rui, Hualan; Beaudoing, Hiroko Kato; Mocko, David M.; Rodell, Matthew; Teng, William L.; Vollmer. Bruce

2010-01-01

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. Generating global fields of these variables, however, is still a challenge. The goal of a land data assimilation system (LDAS)is to ingest satellite-and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast.

Segmenting hospitals for improved management strategy.

PubMed

Malhotra, N K

1989-09-01

The author presents a conceptual framework for the a priori and clustering-based approaches to segmentation and evaluates them in the context of segmenting institutional health care markets. An empirical study is reported in which the hospital market is segmented on three state-of-being variables. The segmentation approach also takes into account important organizational decision-making variables. The sophisticated Thurstone Case V procedure is employed. Several marketing implications for hospitals, other health care organizations, hospital suppliers, and donor publics are identified.

A study of renal blood flow regulation using the discrete wavelet transform

NASA Astrophysics Data System (ADS)

Pavlov, Alexey N.; Pavlova, Olga N.; Mosekilde, Erik; Sosnovtseva, Olga V.

2010-02-01

In this paper we provide a way to distinguish features of renal blood flow autoregulation mechanisms in normotensive and hypertensive rats based on the discrete wavelet transform. Using the variability of the wavelet coefficients we show distinctions that occur between the normal and pathological states. A reduction of this variability in hypertension is observed on the microscopic level of the blood flow in efferent arteriole of single nephrons. This reduction is probably associated with higher flexibility of healthy cardiovascular system.

A 24 km fiber-based discretely signaled continuous variable quantum key distribution system.

PubMed

Dinh Xuan, Quyen; Zhang, Zheshen; Voss, Paul L

2009-12-21

We report a continuous variable key distribution system that achieves a final secure key rate of 3.45 kilobits/s over a distance of 24.2 km of optical fiber. The protocol uses discrete signaling and post-selection to improve reconciliation speed and quantifies security by means of quantum state tomography. Polarization multiplexing and a frequency translation scheme permit transmission of a continuous wave local oscillator and suppression of noise from guided acoustic wave Brillouin scattering by more than 27 dB.

Security of continuous-variable quantum key distribution against general attacks.

PubMed

Leverrier, Anthony; García-Patrón, Raúl; Renner, Renato; Cerf, Nicolas J

2013-01-18

We prove the security of Gaussian continuous-variable quantum key distribution with coherent states against arbitrary attacks in the finite-size regime. In contrast to previously known proofs of principle (based on the de Finetti theorem), our result is applicable in the practically relevant finite-size regime. This is achieved using a novel proof approach, which exploits phase-space symmetries of the protocols as well as the postselection technique introduced by Christandl, Koenig, and Renner [Phys. Rev. Lett. 102, 020504 (2009)].

Heart-Rate Variability—More than Heart Beats?

PubMed Central

Ernst, Gernot

2017-01-01

Heart-rate variability (HRV) is frequently introduced as mirroring imbalances within the autonomous nerve system. Many investigations are based on the paradigm that increased sympathetic tone is associated with decreased parasympathetic tone and vice versa. But HRV is probably more than an indicator for probable disturbances in the autonomous system. Some perturbations trigger not reciprocal, but parallel changes of vagal and sympathetic nerve activity. HRV has also been considered as a surrogate parameter of the complex interaction between brain and cardiovascular system. Systems biology is an inter-disciplinary field of study focusing on complex interactions within biological systems like the cardiovascular system, with the help of computational models and time series analysis, beyond others. Time series are considered surrogates of the particular system, reflecting robustness or fragility. Increased variability is usually seen as associated with a good health condition, whereas lowered variability might signify pathological changes. This might explain why lower HRV parameters were related to decreased life expectancy in several studies. Newer integrating theories have been proposed. According to them, HRV reflects as much the state of the heart as the state of the brain. The polyvagal theory suggests that the physiological state dictates the range of behavior and psychological experience. Stressful events perpetuate the rhythms of autonomic states, and subsequently, behaviors. Reduced variability will according to this theory not only be a surrogate but represent a fundamental homeostasis mechanism in a pathological state. The neurovisceral integration model proposes that cardiac vagal tone, described in HRV beyond others as HF-index, can mirror the functional balance of the neural networks implicated in emotion–cognition interactions. Both recent models represent a more holistic approach to understanding the significance of HRV. PMID:28955705

VARIABILITY AND CHARACTER ASSOCIATION IN ROSE COLOURED LEADWORT (PLUMBAGO ROSEA Linn.)

PubMed Central

Kurian, Alice; Anitha, C.A.; Nybe, E.V.

2001-01-01

Forty five plumbago rosea accessions collected from different parts of Kerala state were evaluated for variability in morphological and yield related characters and plumbagin content. Highly significant variation was evident for all the characters studied except leaf size indicating wide variability in the accessions. Accessions PR 25 and PR 31 appear to be promising with respect to root yield and high plumbagin content. Character association revelated significant and positive correlation of all the characters except leaf size with yield. Hence, selection of high yielding types could easily be done based on visual characters expressing more vegetative growth but with reduced leaf size. PMID:22557037

Quantifying human disturbance in watersheds: Variable selection and performance of a GIS-based disturbance index for predicting the biological condition of perennial streams

USGS Publications Warehouse

Falcone, James A.; Carlisle, Daren M.; Weber, Lisa C.

2010-01-01

Characterizing the relative severity of human disturbance in watersheds is often part of stream assessments and is frequently done with the aid of Geographic Information System (GIS)-derived data. However, the choice of variables and how they are used to quantify disturbance are often subjective. In this study, we developed a number of disturbance indices by testing sets of variables, scoring methods, and weightings of 33 potential disturbance factors derived from readily available GIS data. The indices were calibrated using 770 watersheds located in the western United States for which the severity of disturbance had previously been classified from detailed local data by the United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP). The indices were calibrated by determining which variable or variable combinations and aggregation method best differentiated between least- and most-disturbed sites. Indices composed of several variables performed better than any individual variable, and best results came from a threshold method of scoring using six uncorrelated variables: housing unit density, road density, pesticide application, dam storage, land cover along a mainstem buffer, and distance to nearest canal/pipeline. The final index was validated with 192 withheld watersheds and correctly classified about two-thirds (68%) of least- and most-disturbed sites. These results provide information about the potential for using a disturbance index as a screening tool for a priori ranking of watersheds at a regional/national scale, and which landscape variables and methods of combination may be most helpful in doing so.

On the primary variable switching technique for simulating unsaturated-saturated flows

NASA Astrophysics Data System (ADS)

Diersch, H.-J. G.; Perrochet, P.

Primary variable switching appears as a promising numerical technique for variably saturated flows. While the standard pressure-based form of the Richards equation can suffer from poor mass balance accuracy, the mixed form with its improved conservative properties can possess convergence difficulties for dry initial conditions. On the other hand, variable switching can overcome most of the stated numerical problems. The paper deals with variable switching for finite elements in two and three dimensions. The technique is incorporated in both an adaptive error-controlled predictor-corrector one-step Newton (PCOSN) iteration strategy and a target-based full Newton (TBFN) iteration scheme. Both schemes provide different behaviors with respect to accuracy and solution effort. Additionally, a simplified upstream weighting technique is used. Compared with conventional approaches the primary variable switching technique represents a fast and robust strategy for unsaturated problems with dry initial conditions. The impact of the primary variable switching technique is studied over a wide range of mostly 2D and partly difficult-to-solve problems (infiltration, drainage, perched water table, capillary barrier), where comparable results are available. It is shown that the TBFN iteration is an effective but error-prone procedure. TBFN sacrifices temporal accuracy in favor of accelerated convergence if aggressive time step sizes are chosen.

A Time Integration Algorithm Based on the State Transition Matrix for Structures with Time Varying and Nonlinear Properties

NASA Technical Reports Server (NTRS)

Bartels, Robert E.

2003-01-01

A variable order method of integrating the structural dynamics equations that is based on the state transition matrix has been developed. The method has been evaluated for linear time variant and nonlinear systems of equations. When the time variation of the system can be modeled exactly by a polynomial it produces nearly exact solutions for a wide range of time step sizes. Solutions of a model nonlinear dynamic response exhibiting chaotic behavior have been computed. Accuracy of the method has been demonstrated by comparison with solutions obtained by established methods.

Dynamic rupture modeling with laboratory-derived constitutive relations

USGS Publications Warehouse

Okubo, P.G.

1989-01-01

A laboratory-derived state variable friction constitutive relation is used in the numerical simulation of the dynamic growth of an in-plane or mode II shear crack. According to this formulation, originally presented by J.H. Dieterich, frictional resistance varies with the logarithm of the slip rate and with the logarithm of the frictional state variable as identified by A.L. Ruina. Under conditions of steady sliding, the state variable is proportional to (slip rate)-1. Following suddenly introduced increases in slip rate, the rate and state dependencies combine to produce behavior which resembles slip weakening. When rupture nucleation is artificially forced at fixed rupture velocity, rupture models calculated with the state variable friction in a uniformly distributed initial stress field closely resemble earlier rupture models calculated with a slip weakening fault constitutive relation. Model calculations suggest that dynamic rupture following a state variable friction relation is similar to that following a simpler fault slip weakening law. However, when modeling the full cycle of fault motions, rate-dependent frictional responses included in the state variable formulation are important at low slip rates associated with rupture nucleation. -from Author

Documentation for the State Variables Package for the Groundwater-Management Process of MODFLOW-2005 (GWM-2005)

USGS Publications Warehouse

Ahlfeld, David P.; Barlow, Paul M.; Baker, Kristine M.

2011-01-01

Many groundwater-management problems are concerned with the control of one or more variables that reflect the state of a groundwater-flow system or a coupled groundwater/surface-water system. These system state variables include the distribution of heads within an aquifer, streamflow rates within a hydraulically connected stream, and flow rates into or out of aquifer storage. This report documents the new State Variables Package for the Groundwater-Management Process of MODFLOW-2005 (GWM-2005). The new package provides a means to explicitly represent heads, streamflows, and changes in aquifer storage as state variables in a GWM-2005 simulation. The availability of these state variables makes it possible to include system state in the objective function and enhances existing capabilities for constructing constraint sets for a groundwater-management formulation. The new package can be used to address groundwater-management problems such as the determination of withdrawal strategies that meet water-supply demands while simultaneously maximizing heads or streamflows, or minimizing changes in aquifer storage. Four sample problems are provided to demonstrate use of the new package for typical groundwater-management applications.

An entropy-variables-based formulation of residual distribution schemes for non-equilibrium flows

NASA Astrophysics Data System (ADS)

Garicano-Mena, Jesús; Lani, Andrea; Degrez, Gérard

2018-06-01

In this paper we present an extension of Residual Distribution techniques for the simulation of compressible flows in non-equilibrium conditions. The latter are modeled by means of a state-of-the-art multi-species and two-temperature model. An entropy-based variable transformation that symmetrizes the projected advective Jacobian for such a thermophysical model is introduced. Moreover, the transformed advection Jacobian matrix presents a block diagonal structure, with mass-species and electronic-vibrational energy being completely decoupled from the momentum and total energy sub-system. The advantageous structure of the transformed advective Jacobian can be exploited by contour-integration-based Residual Distribution techniques: established schemes that operate on dense matrices can be substituted by the same scheme operating on the momentum-energy subsystem matrix and repeated application of scalar scheme to the mass-species and electronic-vibrational energy terms. Finally, the performance gain of the symmetrizing-variables formulation is quantified on a selection of representative testcases, ranging from subsonic to hypersonic, in inviscid or viscous conditions.

Variable Selection for Regression Models of Percentile Flows

NASA Astrophysics Data System (ADS)

Fouad, G.

2017-12-01

Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high degree of multicollinearity, possibly illustrating the co-evolution of climatic and physiographic conditions. Given the ineffectiveness of many variables used here, future work should develop new variables that target specific processes associated with percentile flows.

Double Photoionization of excited Lithium and Beryllium

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

Yip, Frank L.; McCurdy, C. William; Rescigno, Thomas N.

2010-05-20

We present total, energy-sharing and triple differential cross sections for one-photon, double ionization of lithium and beryllium starting from aligned, excited P states. We employ a recently developed hybrid atomic orbital/ numerical grid method based on the finite-element discrete-variable representation and exterior complex scaling. Comparisons with calculated results for the ground-state atoms, as well as analogous results for ground-state and excited helium, serve to highlight important selection rules and show some interesting effects that relate to differences between inter- and intra-shell electron correlation.

Addressing Air, Land & Water Nitrogen Issues under Changing Climate Trends & Variability

EPA Science Inventory

The climate of western U.S. dairy producing states is anticipated to change significantly over the next 50 to 75 years. A multimedia modeling system based upon the “nitrogen cascade” concept has been configured to address three aspects of sustainability (environmenta...

An algorithm for analytical solution of basic problems featuring elastostatic bodies with cavities and surface flaws

NASA Astrophysics Data System (ADS)

Penkov, V. B.; Levina, L. V.; Novikova, O. S.; Shulmin, A. S.

2018-03-01

Herein we propose a methodology for structuring a full parametric analytical solution to problems featuring elastostatic media based on state-of-the-art computing facilities that support computerized algebra. The methodology includes: direct and reverse application of P-Theorem; methods of accounting for physical properties of media; accounting for variable geometrical parameters of bodies, parameters of boundary states, independent parameters of volume forces, and remote stress factors. An efficient tool to address the task is the sustainable method of boundary states originally designed for the purposes of computerized algebra and based on the isomorphism of Hilbertian spaces of internal states and boundary states of bodies. We performed full parametric solutions of basic problems featuring a ball with a nonconcentric spherical cavity, a ball with a near-surface flaw, and an unlimited medium with two spherical cavities.

Continuity-based model interfacing for plant-wide simulation: a general approach.

PubMed

Volcke, Eveline I P; van Loosdrecht, Mark C M; Vanrolleghem, Peter A

2006-08-01

In plant-wide simulation studies of wastewater treatment facilities, often existing models from different origin need to be coupled. However, as these submodels are likely to contain different state variables, their coupling is not straightforward. The continuity-based interfacing method (CBIM) provides a general framework to construct model interfaces for models of wastewater systems, taking into account conservation principles. In this contribution, the CBIM approach is applied to study the effect of sludge digestion reject water treatment with a SHARON-Anammox process on a plant-wide scale. Separate models were available for the SHARON process and for the Anammox process. The Benchmark simulation model no. 2 (BSM2) is used to simulate the behaviour of the complete WWTP including sludge digestion. The CBIM approach is followed to develop three different model interfaces. At the same time, the generally applicable CBIM approach was further refined and particular issues when coupling models in which pH is considered as a state variable, are pointed out.

Brazil wheat yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate wheat yields for the wheat growing states of Rio Grande do Sul, Parana, and Santa Catarina in Brazil. The meteorological data of these three states were pooled and the years 1972 to 1979 were used to develop the model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature.

Linear Modeling and Evaluation of Controls on Flow Response in Western Post-Fire Watersheds

NASA Astrophysics Data System (ADS)

Saxe, S.; Hogue, T. S.; Hay, L.

2015-12-01

This research investigates the impact of wildfires on watershed flow regimes throughout the western United States, specifically focusing on evaluation of fire events within specified subregions and determination of the impact of climate and geophysical variables in post-fire flow response. Fire events were collected through federal and state-level databases and streamflow data were collected from U.S. Geological Survey stream gages. 263 watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. For each watershed, percent changes in runoff ratio (RO), annual seven day low-flows (7Q2) and annual seven day high-flows (7Q10) were calculated from pre- to post-fire. Numerous independent variables were identified for each watershed and fire event, including topographic, land cover, climate, burn severity, and soils data. The national watersheds were divided into five regions through K-clustering and a lasso linear regression model, applying the Leave-One-Out calibration method, was calculated for each region. Nash-Sutcliffe Efficiency (NSE) was used to determine the accuracy of the resulting models. The regions encompassing the United States along and west of the Rocky Mountains, excluding the coastal watersheds, produced the most accurate linear models. The Pacific coast region models produced poor and inconsistent results, indicating that the regions need to be further subdivided. Presently, RO and HF response variables appear to be more easily modeled than LF. Results of linear regression modeling showed varying importance of watershed and fire event variables, with conflicting correlation between land cover types and soil types by region. The addition of further independent variables and constriction of current variables based on correlation indicators is ongoing and should allow for more accurate linear regression modeling.

Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013

USGS Publications Warehouse

Driscoll, Jessica; Hay, Lauren E.; Bock, Andrew R.

2017-01-01

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.

Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking

DTIC Science & Technology

2015-07-01

corresponding cost function to be J(u) = ( xd − x)TQx ( xd − x) + uTRu, (20) where Qx ∈ RKnx×Knx is positive semi-definite, R and u are as in (3), xd is a...sequence of desired states, xd = ( xd ,k+1, . . . , xd ,k+K), x is a sequence of predicted states, x = (xk+1, . . . ,xk+K), and K is the given prediction...vact,k−1+b, ωact,k−1+b), based ωk θk vk xd ,i−1 xd ,i xd ,i+1 xk yk Figure 5: Definition of the robot velocities, vk and ωk, and three pose variables

A Dynamic Bayesian Network model for long-term simulation of clinical complications in type 1 diabetes.

PubMed

Marini, Simone; Trifoglio, Emanuele; Barbarini, Nicola; Sambo, Francesco; Di Camillo, Barbara; Malovini, Alberto; Manfrini, Marco; Cobelli, Claudio; Bellazzi, Riccardo

2015-10-01

The increasing prevalence of diabetes and its related complications is raising the need for effective methods to predict patient evolution and for stratifying cohorts in terms of risk of developing diabetes-related complications. In this paper, we present a novel approach to the simulation of a type 1 diabetes population, based on Dynamic Bayesian Networks, which combines literature knowledge with data mining of a rich longitudinal cohort of type 1 diabetes patients, the DCCT/EDIC study. In particular, in our approach we simulate the patient health state and complications through discretized variables. Two types of models are presented, one entirely learned from the data and the other partially driven by literature derived knowledge. The whole cohort is simulated for fifteen years, and the simulation error (i.e. for each variable, the percentage of patients predicted in the wrong state) is calculated every year on independent test data. For each variable, the population predicted in the wrong state is below 10% on both models over time. Furthermore, the distributions of real vs. simulated patients greatly overlap. Thus, the proposed models are viable tools to support decision making in type 1 diabetes. Copyright © 2015 Elsevier Inc. All rights reserved.

Learning in Noise: Dynamic Decision-Making in a Variable Environment

PubMed Central

Gureckis, Todd M.; Love, Bradley C.

2009-01-01

In engineering systems, noise is a curse, obscuring important signals and increasing the uncertainty associated with measurement. However, the negative effects of noise and uncertainty are not universal. In this paper, we examine how people learn sequential control strategies given different sources and amounts of feedback variability. In particular, we consider people’s behavior in a task where short- and long-term rewards are placed in conflict (i.e., the best option in the short-term is worst in the long-term). Consistent with a model based on reinforcement learning principles (Gureckis & Love, in press), we find that learners differentially weight information predictive of the current task state. In particular, when cues that signal state are noisy and uncertain, we find that participants’ ability to identify an optimal strategy is strongly impaired relative to equivalent amounts of uncertainty that obscure the rewards/valuations of those states. In other situations, we find that noise and uncertainty in reward signals may paradoxically improve performance by encouraging exploration. Our results demonstrate how experimentally-manipulated task variability can be used to test predictions about the mechanisms that learners engage in dynamic decision making tasks. PMID:20161328

Sleep variability and cardiac autonomic modulation in adolescents – Penn State Child Cohort (PSCC) study

PubMed Central

Rodríguez-Colón, Sol M.; He, Fan; Bixler, Edward O.; Fernandez-Mendoza, Julio; Vgontzas, Alexandros N.; Calhoun, Susan; Zheng, Zhi-Jie; Liao, Duanping

2015-01-01

Objective To investigate the effects of objectively measured habitual sleep patterns on cardiac autonomic modulation (CAM) in a population-based sample of adolescents. Methods We used data from 421 adolescents who completed the follow-up examination in the Penn State Children Cohort study. CAM was assessed by heart rate (HR) variability (HRV) analysis of beat-to-beat normal R-R intervals from a 39-h electrocardiogram, on a 30-min basis. The HRV indices included frequency domain (HF, LF, and LF/HF ratio), and time domain (SDNN, RMSSD, and heart rate or HR) variables. Actigraphy was used for seven consecutive nights to estimate nightly sleep duration and time in bed. The seven-night mean (SD) of sleep duration and sleep efficiency were used to represent sleep duration, duration variability, sleep efficiency, and efficiency variability, respectively. HF and LF were log-transformed for statistical analysis. Linear mixed-effect models were used to analyze the association between sleep patterns and CAM. Results After adjusting for major confounders, increased sleep duration variability and efficiency variability were significantly associated with lower HRV and higher HR during the 39-h, as well as separated by daytime and nighttime. For instance, a 1-h increase in sleep duration variability is associated with −0.14(0.04), −0.12(0.06), and −0.16(0.05) ms2 decrease in total, daytime, and nighttime HF, respectively. No associations were found between sleep duration, or sleep efficiency and HRV. Conclusion Higher habitual sleep duration variability and efficiency variability are associated with lower HRV and higher HR, suggesting that an irregular sleep pattern has an adverse impact on CAM, even in healthy adolescents. PMID:25555635

Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan.

PubMed

Nomi, Jason S; Bolt, Taylor S; Ezie, C E Chiemeka; Uddin, Lucina Q; Heller, Aaron S

2017-05-31

Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study used resting-state fMRI data from a large sample of male and female human participants covering a wide age range (6-85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 s). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation. SIGNIFICANCE STATEMENT Although brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan. Copyright © 2017 the authors 0270-6474/17/375539-10$15.00/0.

State dynamics of a double sandbar system

NASA Astrophysics Data System (ADS)

Price, T. D.; Ruessink, B. G.

2011-04-01

A 9.3-year dataset of low-tide time-exposure images from Surfers Paradise, Northern Gold Coast, Australia was used to characterise the state dynamics of a double sandbar system. The morphology of the nearshore sandbars was described by means of the sequential bar state classification scheme of Wright and Short [1984. Morphodynamic variability of surf zones and beaches: a synthesis. Marine Geology 56, 93-118]. Besides the two end members (the dissipative (D) and the reflective (R) states) and the four intermediate states (longshore bar and trough (LBT), rhythmic bar and beach (RBB), transverse bar and rip (TBR) and low tide terrace (LTT)), we identified two additional intermediate bar states. The erosive transverse bar and rip (eTBR) state related to the dominant oblique angle of wave incidence at the study site and the rhythmic low tide terrace (rLTT) related to the multiple bar setting. Using the alongshore barline variability and alongshore trough continuity as morphological indicators enabled the objective classification of the inner and outer bar states from the images. The outer bar was mostly in the TBR state and generally advanced sequentially through the states LBT-RBB-TBR-eTBR-LBT, with occasional transitions to the D state. Wave events led to abrupt state transitions of the outer bar, but, in contrast to expectations, did not necessarily correspond to upstate transitions. Instead, upstate (downstate) transitions coincided with angles of wave incidence θ larger (smaller) than 30°. The upstate TBR-eTBR-LBT sequence during high-angle events highlights the role of alongshore currents in bar straightening. The outer bar was found to govern the state of the inner bar to a large extent. Two types of inner bar behaviour were distinguished, based on the outer bar state. For intermediate outer bar states, the alongshore variability of the dominant inner rLTT state (52% in time) mainly related to that of the outer bar, implying some sort of morphological coupling. For dissipative outer bar states, however, the more upstate inner bar frequently separated from the shoreline and persistently developed rip channels as TBR became the most frequent state (60% in time).

Sensitivity Analysis of Weather Variables on Offsite Consequence Analysis Tools in South Korea and the United States.

PubMed

Kim, Min-Uk; Moon, Kyong Whan; Sohn, Jong-Ryeul; Byeon, Sang-Hoon

2018-05-18

We studied sensitive weather variables for consequence analysis, in the case of chemical leaks on the user side of offsite consequence analysis (OCA) tools. We used OCA tools Korea Offsite Risk Assessment (KORA) and Areal Location of Hazardous Atmospheres (ALOHA) in South Korea and the United States, respectively. The chemicals used for this analysis were 28% ammonia (NH₃), 35% hydrogen chloride (HCl), 50% hydrofluoric acid (HF), and 69% nitric acid (HNO₃). The accident scenarios were based on leakage accidents in storage tanks. The weather variables were air temperature, wind speed, humidity, and atmospheric stability. Sensitivity analysis was performed using the Statistical Package for the Social Sciences (SPSS) program for dummy regression analysis. Sensitivity analysis showed that impact distance was not sensitive to humidity. Impact distance was most sensitive to atmospheric stability, and was also more sensitive to air temperature than wind speed, according to both the KORA and ALOHA tools. Moreover, the weather variables were more sensitive in rural conditions than in urban conditions, with the ALOHA tool being more influenced by weather variables than the KORA tool. Therefore, if using the ALOHA tool instead of the KORA tool in rural conditions, users should be careful not to cause any differences in impact distance due to input errors of weather variables, with the most sensitive one being atmospheric stability.

An approximate Riemann solver for thermal and chemical nonequilibrium flows

NASA Technical Reports Server (NTRS)

Prabhu, Ramadas K.

1994-01-01

Among the many methods available for the determination of inviscid fluxes across a surface of discontinuity, the flux-difference-splitting technique that employs Roe-averaged variables has been used extensively by the CFD community because of its simplicity and its ability to capture shocks exactly. This method, originally developed for perfect gas flows, has since been extended to equilibrium as well as nonequilibrium flows. Determination of the Roe-averaged variables for the case of a perfect gas flow is a simple task; however, for thermal and chemical nonequilibrium flows, some of the variables are not uniquely defined. Methods available in the literature to determine these variables seem to lack sound bases. The present paper describes a simple, yet accurate, method to determine all the variables for nonequilibrium flows in the Roe-average state. The basis for this method is the requirement that the Roe-averaged variables form a consistent set of thermodynamic variables. The present method satisfies the requirement that the square of the speed of sound be positive.

Ecosystem functioning is enveloped by hydrometeorological variability.

PubMed

Pappas, Christoforos; Mahecha, Miguel D; Frank, David C; Babst, Flurin; Koutsoyiannis, Demetris

2017-09-01

Terrestrial ecosystem processes, and the associated vegetation carbon dynamics, respond differently to hydrometeorological variability across timescales, and so does our scientific understanding of the underlying mechanisms. Long-term variability of the terrestrial carbon cycle is not yet well constrained and the resulting climate-biosphere feedbacks are highly uncertain. Here we present a comprehensive overview of hydrometeorological and ecosystem variability from hourly to decadal timescales integrating multiple in situ and remote-sensing datasets characterizing extra-tropical forest sites. We find that ecosystem variability at all sites is confined within a hydrometeorological envelope across sites and timescales. Furthermore, ecosystem variability demonstrates long-term persistence, highlighting ecological memory and slow ecosystem recovery rates after disturbances. However, simulation results with state-of-the-art process-based models do not reflect this long-term persistent behaviour in ecosystem functioning. Accordingly, we develop a cross-time-scale stochastic framework that captures hydrometeorological and ecosystem variability. Our analysis offers a perspective for terrestrial ecosystem modelling and paves the way for new model-data integration opportunities in Earth system sciences.

Solar Irradiance Variability is Caused by the Magnetic Activity on the Solar Surface.

PubMed

Yeo, Kok Leng; Solanki, Sami K; Norris, Charlotte M; Beeck, Benjamin; Unruh, Yvonne C; Krivova, Natalie A

2017-09-01

The variation in the radiative output of the Sun, described in terms of solar irradiance, is important to climatology. A common assumption is that solar irradiance variability is driven by its surface magnetism. Verifying this assumption has, however, been hampered by the fact that models of solar irradiance variability based on solar surface magnetism have to be calibrated to observed variability. Making use of realistic three-dimensional magnetohydrodynamic simulations of the solar atmosphere and state-of-the-art solar magnetograms from the Solar Dynamics Observatory, we present a model of total solar irradiance (TSI) that does not require any such calibration. In doing so, the modeled irradiance variability is entirely independent of the observational record. (The absolute level is calibrated to the TSI record from the Total Irradiance Monitor.) The model replicates 95% of the observed variability between April 2010 and July 2016, leaving little scope for alternative drivers of solar irradiance variability at least over the time scales examined (days to years).

Towards Improved Forecasts of Atmospheric and Oceanic Circulations over the Complex Terrain of the Eastern Mediterranean

NASA Technical Reports Server (NTRS)

Chronis, Themis; Case, Jonathan L.; Papadopoulos, Anastasios; Anagnostou, Emmanouil N.; Mecikalski, John R.; Haines, Stephanie L.

2008-01-01

Forecasting atmospheric and oceanic circulations accurately over the Eastern Mediterranean has proved to be an exceptional challenge. The existence of fine-scale topographic variability (land/sea coverage) and seasonal dynamics variations can create strong spatial gradients in temperature, wind and other state variables, which numerical models may have difficulty capturing. The Hellenic Center for Marine Research (HCMR) is one of the main operational centers for wave forecasting in the eastern Mediterranean. Currently, HCMR's operational numerical weather/ocean prediction model is based on the coupled Eta/Princeton Ocean Model (POM). Since 1999, HCMR has also operated the POSEIDON floating buoys as a means of state-of-the-art, real-time observations of several oceanic and surface atmospheric variables. This study attempts a first assessment at improving both atmospheric and oceanic prediction by initializing a regional Numerical Weather Prediction (NWP) model with high-resolution sea surface temperatures (SST) from remotely sensed platforms in order to capture the small-scale characteristics.

[Association between social deprivation and causes of mortality among elderly residents in the city of Recife, Pernambuco State, Brazil].

PubMed

Silva, Vanessa de Lima; Leal, Márcia Carréra Campos; Marino, Jacira Guiro; Marques, Ana Paula de Oliveira

2008-05-01

This paper aims to analyze mortality among elderly residents in the city of Recife, Pernambuco State, Brazil, and its association with social deprivation (hardship) in the year 2000. An ecological study was performed, and 94 neighborhoods and 5 social strata were analyzed. The independent variable consisted of a composite social deprivation indicator, obtained for each neighborhood and calculated through a scoring technique based on census variables: water supply, sewage, illiteracy, and head-of-household's years of schooling and income. The dependent variables were: mortality rate in individuals > 60 years of age and cause-specific mortality rates. The association was calculated by means of the Pearson correlation coefficient, linear regression, and mortality odds between social deprivation strata formed by grouping of neighborhoods according to the indicator's quintiles. The data show a statistically significant positive correlation between social deprivation and mortality in the elderly from pneumonia, protein-energy malnutrition, tuberculosis, diarrhea/gastroenteritis, and traffic accidents, and a negative correlation with deaths from bronchopulmonary and breast cancers.

Reduced Lung Cancer Mortality With Lower Atmospheric Pressure.

PubMed

Merrill, Ray M; Frutos, Aaron

2018-01-01

Research has shown that higher altitude is associated with lower risk of lung cancer and improved survival among patients. The current study assessed the influence of county-level atmospheric pressure (a measure reflecting both altitude and temperature) on age-adjusted lung cancer mortality rates in the contiguous United States, with 2 forms of spatial regression. Ordinary least squares regression and geographically weighted regression models were used to evaluate the impact of climate and other selected variables on lung cancer mortality, based on 2974 counties. Atmospheric pressure was significantly positively associated with lung cancer mortality, after controlling for sunlight, precipitation, PM2.5 (µg/m 3 ), current smoker, and other selected variables. Positive county-level β coefficient estimates ( P < .05) for atmospheric pressure were observed throughout the United States, higher in the eastern half of the country. The spatial regression models showed that atmospheric pressure is positively associated with age-adjusted lung cancer mortality rates, after controlling for other selected variables.

Correlates of engaging in survival sex among homeless youth and young adults.

PubMed

Walls, N Eugene; Bell, Stephanie

2011-09-01

Using a sample of 1,625 homeless youth and young adults aged 10 to 25 from 28 different states in the United States, this study examines the correlates of having engaged in survival sex. Findings suggest that differences exist based on demographic variables (gender, age, race, and sexual orientation), lifetime drug use (inhalants, Valium™, crack cocaine, alcohol, Coricidin™, and morphine), recent drug use (alcohol, ecstasy, heroin, and methamphetamine), mental health variables (suicide attempts, familial history of substance use, and having been in substance abuse treatment), and health variables (sharing needles and having been tested for HIV). In addition to replicating previous findings, this study's findings suggest that African American youth; gay, lesbian, or bisexual youth; and youth who had been tested for HIV were significantly more likely to have engaged in survival sex than White, heterosexual youth, and youth who had not been tested for HIV, respectively. Implications for interventions with youth and suggestions for future research are discussed.

Mechanisms Controlling Global Mean Sea Surface Temperature Determined From a State Estimate

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Piecuch, C. G.

2018-04-01

Global mean sea surface temperature (T¯) is a variable of primary interest in studies of climate variability and change. The temporal evolution of T¯ can be influenced by surface heat fluxes (F¯) and by diffusion (D¯) and advection (A¯) processes internal to the ocean, but quantifying the contribution of these different factors from data alone is prone to substantial uncertainties. Here we derive a closed T¯ budget for the period 1993-2015 based on a global ocean state estimate, which is an exact solution of a general circulation model constrained to most extant ocean observations through advanced optimization methods. The estimated average temperature of the top (10-m thick) level in the model, taken to represent T¯, shows relatively small variability at most time scales compared to F¯, D¯, or A¯, reflecting the tendency for largely balancing effects from all the latter terms. The seasonal cycle in T¯ is mostly determined by small imbalances between F¯ and D¯, with negligible contributions from A¯. While D¯ seems to simply damp F¯ at the annual period, a different dynamical role for D¯ at semiannual period is suggested by it being larger than F¯. At periods longer than annual, A¯ contributes importantly to T¯ variability, pointing to the direct influence of the variable ocean circulation on T¯ and mean surface climate.

Improved Uncertainty Quantification in Groundwater Flux Estimation Using GRACE

NASA Astrophysics Data System (ADS)

Reager, J. T., II; Rao, P.; Famiglietti, J. S.; Turmon, M.

2015-12-01

Groundwater change is difficult to monitor over large scales. One of the most successful approaches is in the remote sensing of time-variable gravity using NASA Gravity Recovery and Climate Experiment (GRACE) mission data, and successful case studies have created the opportunity to move towards a global groundwater monitoring framework for the world's largest aquifers. To achieve these estimates, several approximations are applied, including those in GRACE processing corrections, the formulation of the formal GRACE errors, destriping and signal recovery, and the numerical model estimation of snow water, surface water and soil moisture storage states used to isolate a groundwater component. A major weakness in these approaches is inconsistency: different studies have used different sources of primary and ancillary data, and may achieve different results based on alternative choices in these approximations. In this study, we present two cases of groundwater change estimation in California and the Colorado River basin, selected for their good data availability and varied climates. We achieve a robust numerical estimate of post-processing uncertainties resulting from land-surface model structural shortcomings and model resolution errors. Groundwater variations should demonstrate less variability than the overlying soil moisture state does, as groundwater has a longer memory of past events due to buffering by infiltration and drainage rate limits. We apply a model ensemble approach in a Bayesian framework constrained by the assumption of decreasing signal variability with depth in the soil column. We also discuss time variable errors vs. time constant errors, across-scale errors v. across-model errors, and error spectral content (across scales and across model). More robust uncertainty quantification for GRACE-based groundwater estimates would take all of these issues into account, allowing for more fair use in management applications and for better integration of GRACE-based measurements with observations from other sources.

Carbon fluxes in tropical forest ecosystems: the value of Eddy-covariance data for individual-based dynamic forest gap models

NASA Astrophysics Data System (ADS)

Roedig, Edna; Cuntz, Matthias; Huth, Andreas

2015-04-01

The effects of climatic inter-annual fluctuations and human activities on the global carbon cycle are uncertain and currently a major issue in global vegetation models. Individual-based forest gap models, on the other hand, model vegetation structure and dynamics on a small spatial (<100 ha) and large temporal scale (>1000 years). They are well-established tools to reproduce successions of highly-diverse forest ecosystems and investigate disturbances as logging or fire events. However, the parameterizations of the relationships between short-term climate variability and forest model processes are often uncertain in these models (e.g. daily variable temperature and gross primary production (GPP)) and cannot be constrained from forest inventories. We addressed this uncertainty and linked high-resolution Eddy-covariance (EC) data with an individual-based forest gap model. The forest model FORMIND was applied to three diverse tropical forest sites in the Amazonian rainforest. Species diversity was categorized into three plant functional types. The parametrizations for the steady-state of biomass and forest structure were calibrated and validated with different forest inventories. The parameterizations of relationships between short-term climate variability and forest model processes were evaluated with EC-data on a daily time step. The validations of the steady-state showed that the forest model could reproduce biomass and forest structures from forest inventories. The daily estimations of carbon fluxes showed that the forest model reproduces GPP as observed by the EC-method. Daily fluctuations of GPP were clearly reflected as a response to daily climate variability. Ecosystem respiration remains a challenge on a daily time step due to a simplified soil respiration approach. In the long-term, however, the dynamic forest model is expected to estimate carbon budgets for highly-diverse tropical forests where EC-measurements are rare.

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location.

EO based Agro-ecosystem approach for climate change adaptation in enhancing the crop production efficiency in the Indo-gangetic plains of India

NASA Astrophysics Data System (ADS)

Pandey, Suraj

This study develops a spatial mapping of agro-ecological zones based on earth observation model using MODIS regional dataset as a tool to guide key areas of cropping system and targeting to climate change strategies. This tool applies to the Indo-gangetic Plains of north India to target the domains of bio-physical characteristics and socio-economics with respect to changing climate in the region. It derive on secondary data for spatially-explicit variables at the state/district level, which serve as indicators of climate variability based on sustainable livelihood approach, natural, social and human. The study details the methodology used and generates the spatial climate risk maps for composite indicators of livelihood and vulnerability index in the region.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

NASA Astrophysics Data System (ADS)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

Characterizing uncertainty and variability in physiologically based pharmacokinetic models: state of the science and needs for research and implementation.

PubMed

Barton, Hugh A; Chiu, Weihsueh A; Setzer, R Woodrow; Andersen, Melvin E; Bailer, A John; Bois, Frédéric Y; Dewoskin, Robert S; Hays, Sean; Johanson, Gunnar; Jones, Nancy; Loizou, George; Macphail, Robert C; Portier, Christopher J; Spendiff, Martin; Tan, Yu-Mei

2007-10-01

Physiologically based pharmacokinetic (PBPK) models are used in mode-of-action based risk and safety assessments to estimate internal dosimetry in animals and humans. When used in risk assessment, these models can provide a basis for extrapolating between species, doses, and exposure routes or for justifying nondefault values for uncertainty factors. Characterization of uncertainty and variability is increasingly recognized as important for risk assessment; this represents a continuing challenge for both PBPK modelers and users. Current practices show significant progress in specifying deterministic biological models and nondeterministic (often statistical) models, estimating parameters using diverse data sets from multiple sources, using them to make predictions, and characterizing uncertainty and variability of model parameters and predictions. The International Workshop on Uncertainty and Variability in PBPK Models, held 31 Oct-2 Nov 2006, identified the state-of-the-science, needed changes in practice and implementation, and research priorities. For the short term, these include (1) multidisciplinary teams to integrate deterministic and nondeterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through improved documentation of model structure(s), parameter values, sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include (1) theoretical and practical methodological improvements for nondeterministic/statistical modeling; (2) better methods for evaluating alternative model structures; (3) peer-reviewed databases of parameters and covariates, and their distributions; (4) expanded coverage of PBPK models across chemicals with different properties; and (5) training and reference materials, such as cases studies, bibliographies/glossaries, model repositories, and enhanced software. The multidisciplinary dialogue initiated by this Workshop will foster the collaboration, research, data collection, and training necessary to make characterizing uncertainty and variability a standard practice in PBPK modeling and risk assessment.

Task planning with uncertainty for robotic systems. Thesis

NASA Technical Reports Server (NTRS)

Cao, Tiehua

1993-01-01

In a practical robotic system, it is important to represent and plan sequences of operations and to be able to choose an efficient sequence from them for a specific task. During the generation and execution of task plans, different kinds of uncertainty may occur and erroneous states need to be handled to ensure the efficiency and reliability of the system. An approach to task representation, planning, and error recovery for robotic systems is demonstrated. Our approach to task planning is based on an AND/OR net representation, which is then mapped to a Petri net representation of all feasible geometric states and associated feasibility criteria for net transitions. Task decomposition of robotic assembly plans based on this representation is performed on the Petri net for robotic assembly tasks, and the inheritance of properties of liveness, safeness, and reversibility at all levels of decomposition are explored. This approach provides a framework for robust execution of tasks through the properties of traceability and viability. Uncertainty in robotic systems are modeled by local fuzzy variables, fuzzy marking variables, and global fuzzy variables which are incorporated in fuzzy Petri nets. Analysis of properties and reasoning about uncertainty are investigated using fuzzy reasoning structures built into the net. Two applications of fuzzy Petri nets, robot task sequence planning and sensor-based error recovery, are explored. In the first application, the search space for feasible and complete task sequences with correct precedence relationships is reduced via the use of global fuzzy variables in reasoning about subgoals. In the second application, sensory verification operations are modeled by mutually exclusive transitions to reason about local and global fuzzy variables on-line and automatically select a retry or an alternative error recovery sequence when errors occur. Task sequencing and task execution with error recovery capability for one and multiple soft components in robotic systems are investigated.

Low-Dimensional Statistics of Anatomical Variability via Compact Representation of Image Deformations.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2016-10-01

Using image-based descriptors to investigate clinical hypotheses and therapeutic implications is challenging due to the notorious "curse of dimensionality" coupled with a small sample size. In this paper, we present a low-dimensional analysis of anatomical shape variability in the space of diffeomorphisms and demonstrate its benefits for clinical studies. To combat the high dimensionality of the deformation descriptors, we develop a probabilistic model of principal geodesic analysis in a bandlimited low-dimensional space that still captures the underlying variability of image data. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than models based on the high-dimensional state-of-the-art approaches such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA).

A liquid lens switching-based motionless variable fiber-optic delay line

NASA Astrophysics Data System (ADS)

Khwaja, Tariq Shamim; Reza, Syed Azer; Sheikh, Mumtaz

2018-05-01

We present a Variable Fiber-Optic Delay Line (VFODL) module capable of imparting long variable delays by switching an input optical/RF signal between Single Mode Fiber (SMF) patch cords of different lengths through a pair of Electronically Controlled Tunable Lenses (ECTLs) resulting in a polarization-independent operation. Depending on intended application, the lengths of the SMFs can be chosen accordingly to achieve the desired VFODL operation dynamic range. If so desired, the state of the input signal polarization can be preserved with the use of commercially available polarization-independent ECTLs along with polarization-maintaining SMFs (PM-SMFs), resulting in an output polarization that is identical to the input. An ECTL-based design also improves power consumption and repeatability. The delay switching mechanism is electronically-controlled, involves no bulk moving parts, and can be fully-automated. The VFODL module is compact due to the use of small optical components and SMFs that can be packaged compactly.

Variability in visual working memory ability limits the efficiency of perceptual decision making.

PubMed

Ester, Edward F; Ho, Tiffany C; Brown, Scott D; Serences, John T

2014-04-02

The ability to make rapid and accurate decisions based on limited sensory information is a critical component of visual cognition. Available evidence suggests that simple perceptual discriminations are based on the accumulation and integration of sensory evidence over time. However, the memory system(s) mediating this accumulation are unclear. One candidate system is working memory (WM), which enables the temporary maintenance of information in a readily accessible state. Here, we show that individual variability in WM capacity is strongly correlated with the speed of evidence accumulation in speeded two-alternative forced choice tasks. This relationship generalized across different decision-making tasks, and could not be easily explained by variability in general arousal or vigilance. Moreover, we show that performing a difficult discrimination task while maintaining a concurrent memory load has a deleterious effect on the latter, suggesting that WM storage and decision making are directly linked.

Hydrologic-energy balance constraints on the Holocene lake-level history of lake Titicaca, South America

NASA Astrophysics Data System (ADS)

Rowe, H. D.; Dunbar, R. B.

2004-09-01

A basin-scale hydrologic-energy balance model that integrates modern climatological, hydrological, and hypsographic observations was developed for the modern Lake Titicaca watershed (northern Altiplano, South America) and operated under variable conditions to understand controls on post-glacial changes in lake level. The model simulates changes in five environmental variables (air temperature, cloud fraction, precipitation, relative humidity, and land surface albedo). Relatively small changes in three meteorological variables (mean annual precipitation, temperature, and/or cloud fraction) explain the large mid-Holocene lake-level decrease (˜85 m) inferred from seismic reflection profiling and supported by sediment-based paleoproxies from lake sediments. Climatic controls that shape the present-day Altiplano and the sediment-based record of Holocene lake-level change are combined to interpret model-derived lake-level simulations in terms of changes in the mean state of ENSO and its impact on moisture transport to the Altiplano.

Representativeness-based sampling network design for the State of Alaska

Treesearch

Forrest M. Hoffman; Jitendra Kumar; Richard T. Mills; William W. Hargrove

2013-01-01

Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection,...

META II Complex Systems Design and Analysis (CODA)

DTIC Science & Technology

2011-08-01

37  3.8.7  Variables, Parameters and Constraints ............................................................. 37  3.8.8  Objective...18  Figure 7: Inputs, States, Outputs and Parameters of System Requirements Specifications ......... 19...Design Rule Based on Device Parameter ....................................................... 57  Figure 35: AEE Device Design Rules (excerpt

The importance of environmental variability and management control error to optimal harvest policies

USGS Publications Warehouse

Hunter, C.M.; Runge, M.C.

2004-01-01

State-dependent strategies (SDSs) are the most general form of harvest policy because they allow the harvest rate to depend, without constraint, on the state of the system. State-dependent strategies that provide an optimal harvest rate for any system state can be calculated, and stochasticity can be appropriately accommodated in this optimization. Stochasticity poses 2 challenges to harvest policies: (1) the population will never be at the equilibrium state; and (2) stochasticity induces uncertainty about future states. We investigated the effects of 2 types of stochasticity, environmental variability and management control error, on SDS harvest policies for a white-tailed deer (Odocoileus virginianus) model, and contrasted these with a harvest policy based on maximum sustainable yield (MSY). Increasing stochasticity resulted in more conservative SDSs; that is, higher population densities were required to support the same harvest rate, but these effects were generally small. As stochastic effects increased, SDSs performed much better than MSY. Both deterministic and stochastic SDSs maintained maximum mean annual harvest yield (AHY) and optimal equilibrium population size (Neq) in a stochastic environment, whereas an MSY policy could not. We suggest 3 rules of thumb for harvest management of long-lived vertebrates in stochastic systems: (1) an SDS is advantageous over an MSY policy, (2) using an SDS rather than an MSY is more important than whether a deterministic or stochastic SDS is used, and (3) for SDSs, rankings of the variability in management outcomes (e.g., harvest yield) resulting from parameter stochasticity can be predicted by rankings of the deterministic elasticities.

A comparative study of job satisfaction among nurses, psychologists/psychotherapists and social workers working in Quebec mental health teams.

PubMed

Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie

2017-01-01

This study identified multiple socio-professional and team effectiveness variables, based on the Input-Mediator-Output-Input (IMOI) model, and tested their associations with job satisfaction for three categories of mental health professionals (nurses, psychologists/psychotherapists, and social workers). Job satisfaction was assessed with the Job Satisfaction Survey. Independent variables were classified into four categories: 1) Socio-professional Characteristics; 2) Team Attributes; 3) Team Processes; and 4) Team Emergent States. Variables were entered successively, by category, into a hierarchical regression model. Team Processes contributed the greatest number of variables to job satisfaction among all professional groups, including team support which was the only significant variable common to all three types of professionals. Greater involvement in the decision-making process, and lower levels of team conflict (Team Processes) were associated with job satisfaction among nurses and social workers. Lower seniority on team (Socio-professional Characteristics), and team collaboration (Team Processes) were associated with job satisfaction among nurses, as was belief in the advantages of interdisciplinary collaboration (Team Emergent States) among psychologists. Knowledge sharing (Team Processes) and affective commitment to the team (Team Emergent States) were associated with job satisfaction among social workers. Results suggest the need for mental health decision-makers and team managers to offer adequate support to mental health professionals, to involve nurses and social workers in the decision-making process, and implement procedures and mechanisms favourable to the prevention or resolution of team conflict with a view toward increasing job satisfaction among mental health professionals.

Security of Continuous-Variable Quantum Key Distribution via a Gaussian de Finetti Reduction

NASA Astrophysics Data System (ADS)

Leverrier, Anthony

2017-05-01

Establishing the security of continuous-variable quantum key distribution against general attacks in a realistic finite-size regime is an outstanding open problem in the field of theoretical quantum cryptography if we restrict our attention to protocols that rely on the exchange of coherent states. Indeed, techniques based on the uncertainty principle are not known to work for such protocols, and the usual tools based on de Finetti reductions only provide security for unrealistically large block lengths. We address this problem here by considering a new type of Gaussian de Finetti reduction, that exploits the invariance of some continuous-variable protocols under the action of the unitary group U (n ) (instead of the symmetric group Sn as in usual de Finetti theorems), and by introducing generalized S U (2 ,2 ) coherent states. Crucially, combined with an energy test, this allows us to truncate the Hilbert space globally instead as at the single-mode level as in previous approaches that failed to provide security in realistic conditions. Our reduction shows that it is sufficient to prove the security of these protocols against Gaussian collective attacks in order to obtain security against general attacks, thereby confirming rigorously the widely held belief that Gaussian attacks are indeed optimal against such protocols.

Security of Continuous-Variable Quantum Key Distribution via a Gaussian de Finetti Reduction.

PubMed

Leverrier, Anthony

2017-05-19

Establishing the security of continuous-variable quantum key distribution against general attacks in a realistic finite-size regime is an outstanding open problem in the field of theoretical quantum cryptography if we restrict our attention to protocols that rely on the exchange of coherent states. Indeed, techniques based on the uncertainty principle are not known to work for such protocols, and the usual tools based on de Finetti reductions only provide security for unrealistically large block lengths. We address this problem here by considering a new type of Gaussian de Finetti reduction, that exploits the invariance of some continuous-variable protocols under the action of the unitary group U(n) (instead of the symmetric group S_{n} as in usual de Finetti theorems), and by introducing generalized SU(2,2) coherent states. Crucially, combined with an energy test, this allows us to truncate the Hilbert space globally instead as at the single-mode level as in previous approaches that failed to provide security in realistic conditions. Our reduction shows that it is sufficient to prove the security of these protocols against Gaussian collective attacks in order to obtain security against general attacks, thereby confirming rigorously the widely held belief that Gaussian attacks are indeed optimal against such protocols.

Mind-Reading and Behavior-Reading against Agents with and without Anthropomorphic Features in a Competitive Situation

PubMed Central

Terada, Kazunori; Yamada, Seiji

2017-01-01

Humans use two distinct cognitive strategies separately to understand and predict other humans' behavior. One is mind-reading, in which an internal state such as an intention or an emotional state is assumed to be a source of a variety of behaviors. The other is behavior-reading, in which an actor's behavior is modeled based on stimulus-response associations without assuming internal states behind the behavior. We hypothesize that anthropomorphic features are key for an observer switching between these two cognitive strategies in a competitive situation. We provide support for this hypothesis through two studies using four agents with different appearances. We show that only a human agent was thought to possess both the ability to generate a variety of behaviors and internal mental states, such as minds and emotions (Study 1). We also show that humans used mixed (opposing) strategies against a human agent and exploitative strategies against the agents with mechanical appearances when they played a repeated zero-sum game (Study 2). Our findings show that humans understand that human behavior is varied; that humans have internal states, such as minds and emotions; that the behavior of machines is governed by a limited number of fixed rules; and that machines do not possess internal mental states. Our findings also suggest that the function of mind-reading is to trigger a strategy for use against agents with variable behavior and that humans exploit others who lack behavioral variability based on behavior-reading in a competitive situation. PMID:28736536

Investigation on the Nonlinear Control System of High-Pressure Common Rail (HPCR) System in a Diesel Engine

NASA Astrophysics Data System (ADS)

Cai, Le; Mao, Xiaobing; Ma, Zhexuan

2018-02-01

This study first constructed the nonlinear mathematical model of the high-pressure common rail (HPCR) system in the diesel engine. Then, the nonlinear state transformation was performed using the flow’s calculation and the standard state space equation was acquired. Based on sliding-mode variable structure control (SMVSC) theory, a sliding-mode controller for nonlinear systems was designed for achieving the control of common rail pressure and the diesel engine’s rotational speed. Finally, on the simulation platform of MATLAB, the designed nonlinear HPCR system was simulated. The simulation results demonstrate that sliding-mode variable structure control algorithm shows favorable control performances and overcome the shortcomings of traditional PID control in overshoot, parameter adjustment, system precision, adjustment time and ascending time.

Modeling of vegetation canopy reflectance: Status, issues and recommended future strategy

NASA Technical Reports Server (NTRS)

Goel, N. S. (Editor)

1982-01-01

Various technical issues related to mapping of vegetative type, condition and stage of maturity, utilizing remotely sensed spectral data are reviewed. The existing knowledge base of models, especially of radiative properties of the vegetation canopy and atmosphere, is reviewed to establish the state of the art for addressing the problem of vegetation mapping. Activities to advance the state of the art are recommended. They include working on canopy reflectance and atmospheric scattering models, and field measurements of canopy reflectance as well as of canopy components. Leaf area index (LAI) and solar radiation interception (SRI) are identified as the two most important vegetation variables requiring further investigation. It is recommended that activities related to sensing them or understanding their relationships with measurable variables, should be encouraged and supported.

Challenges and Emerging Concepts in the Development of Adaptive, Computer-based Tutoring Systems for Team Training

DTIC Science & Technology

2011-11-01

based perception of each team member‟s behavior and physiology with the goal of predicting unobserved variables (e.g., cognitive state). Along with...sensing technologies are showing promise as enablers of computer-based perception of each team member‟s behavior and physiology with the goal...an essential element of team performance. The perception that other team members may be unable to perform their tasks is detrimental to trust and

Modelling Pseudocalanus elongatus stage-structured population dynamics embedded in a water column ecosystem model for the northern North Sea

NASA Astrophysics Data System (ADS)

Moll, Andreas; Stegert, Christoph

2007-01-01

This paper outlines an approach to couple a structured zooplankton population model with state variables for eggs, nauplii, two copepodites stages and adults adapted to Pseudocalanus elongatus into the complex marine ecosystem model ECOHAM2 with 13 state variables resolving the carbon and nitrogen cycle. Different temperature and food scenarios derived from laboratory culture studies were examined to improve the process parameterisation for copepod stage dependent development processes. To study annual cycles under realistic weather and hydrographic conditions, the coupled ecosystem-zooplankton model is applied to a water column in the northern North Sea. The main ecosystem state variables were validated against observed monthly mean values. Then vertical profiles of selected state variables were compared to the physical forcing to study differences between zooplankton as one biomass state variable or partitioned into five population state variables. Simulated generation times are more affected by temperature than food conditions except during the spring phytoplankton bloom. Up to six generations within the annual cycle can be discerned in the simulation.

The decadal state of the terrestrial carbon cycle: Global retrievals of terrestrial carbon allocation, pools, and residence times

PubMed Central

Bloom, A. Anthony; Exbrayat, Jean-François; van der Velde, Ivar R.; Feng, Liang; Williams, Mathew

2016-01-01

The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85–88%) in contrast to higher latitudes (73–82%), where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42–0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64–0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types. PMID:26787856

Proof-of-principle experimental realization of a qubit-like qudit-based quantum key distribution scheme

NASA Astrophysics Data System (ADS)

Wang, Shuang; Yin, Zhen-Qiang; Chau, H. F.; Chen, Wei; Wang, Chao; Guo, Guang-Can; Han, Zheng-Fu

2018-04-01

In comparison to qubit-based protocols, qudit-based quantum key distribution ones generally allow two cooperative parties to share unconditionally secure keys under a higher channel noise. However, it is very hard to prepare and measure the required quantum states in qudit-based protocols in general. One exception is the recently proposed highly error tolerant qudit-based protocol known as the Chau15 (Chau 2015 Phys. Rev. A 92 062324). Remarkably, the state preparation and measurement in this protocol can be done relatively easily since the required states are phase encoded almost like the diagonal basis states of a qubit. Here we report the first proof-of-principle demonstration of the Chau15 protocol. One highlight of our experiment is that its post-processing is based on practical one-way manner, while the original proposal in Chau (2015 Phys. Rev. A 92 062324) relies on complicated two-way post-processing, which is a great challenge in experiment. In addition, by manipulating time-bin qudit and measurement with a variable delay interferometer, our realization is extensible to qudit with high-dimensionality and confirms the experimental feasibility of the Chau15 protocol.

Quantum-Enhanced Sensing Based on Time Reversal of Nonlinear Dynamics.

PubMed

Linnemann, D; Strobel, H; Muessel, W; Schulz, J; Lewis-Swan, R J; Kheruntsyan, K V; Oberthaler, M K

2016-07-01

We experimentally demonstrate a nonlinear detection scheme exploiting time-reversal dynamics that disentangles continuous variable entangled states for feasible readout. Spin-exchange dynamics of Bose-Einstein condensates is used as the nonlinear mechanism which not only generates entangled states but can also be time reversed by controlled phase imprinting. For demonstration of a quantum-enhanced measurement we construct an active atom SU(1,1) interferometer, where entangled state preparation and nonlinear readout both consist of parametric amplification. This scheme is capable of exhausting the quantum resource by detecting solely mean atom numbers. Controlled nonlinear transformations widen the spectrum of useful entangled states for applied quantum technologies.

Correlation Between Fracture Network Properties and Stress Variability in Geological Media

NASA Astrophysics Data System (ADS)

Lei, Qinghua; Gao, Ke

2018-05-01

We quantitatively investigate the stress variability in fractured geological media under tectonic stresses. The fracture systems studied include synthetic fracture networks following power law length scaling and natural fracture patterns based on outcrop mapping. The stress field is derived from a finite-discrete element model, and its variability is analyzed using a set of mathematical formulations that honor the tensorial nature of stress data. We show that local stress perturbation, quantified by the Euclidean distance of a local stress tensor to the mean stress tensor, has a positive, linear correlation with local fracture intensity, defined as the total fracture length per unit area within a local sampling window. We also evaluate the stress dispersion of the entire stress field using the effective variance, that is, a scalar-valued measure of the overall stress variability. The results show that a well-connected fracture system under a critically stressed state exhibits strong local and global stress variabilities.

Linear and nonlinear measures of fetal heart rate patterns evaluated on very short fetal magnetocardiograms.

PubMed

Moraes, Eder Rezende; Murta, Luiz Otavio; Baffa, Oswaldo; Wakai, Ronald T; Comani, Silvia

2012-10-01

We analyzed the effectiveness of linear short- and long-term variability time domain parameters, an index of sympatho-vagal balance (SDNN/RMSSD) and entropy in differentiating fetal heart rate patterns (fHRPs) on the fetal heart rate (fHR) series of 5, 3 and 2 min duration reconstructed from 46 fetal magnetocardiograms. Gestational age (GA) varied from 21 to 38 weeks. FHRPs were classified based on the fHR standard deviation. In sleep states, we observed that vagal influence increased with GA, and entropy significantly increased (decreased) with GA (SDNN/RMSSD), demonstrating that a prevalence of vagal activity with autonomous nervous system maturation may be associated with increased sleep state complexity. In active wakefulness, we observed a significant negative (positive) correlation of short-term (long-term) variability parameters with SDNN/RMSSD. ANOVA statistics demonstrated that long-term irregularity and standard deviation of normal-to-normal beat intervals (SDNN) best differentiated among fHRPs. Our results confirm that short- and long-term variability parameters are useful to differentiate between quiet and active states, and that entropy improves the characterization of sleep states. All measures differentiated fHRPs more effectively on very short HR series, as a result of the fMCG high temporal resolution and of the intrinsic timescales of the events that originate the different fHRPs.

A statistical-based approach for acoustic tomography of the atmosphere.

PubMed

Kolouri, Soheil; Azimi-Sadjadi, Mahmood R; Ziemann, Astrid

2014-01-01

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a statistical-based acoustic travel-time tomography algorithm based on dual state-parameter unscented Kalman filter (UKF) which is capable of reconstructing and tracking, in time, temperature, and wind velocity fields (state variables) as well as the dynamic model parameters within a specified investigation area. An adaptive 3-D spatial-temporal autoregressive model is used to capture the state evolution in the UKF. The observations used in the dual state-parameter UKF process consist of the acoustic time of arrivals measured for every pair of transmitter/receiver nodes deployed in the investigation area. The proposed method is then applied to the data set collected at the Meteorological Observatory Lindenberg, Germany, as part of the STINHO experiment, and the reconstruction results are presented.

An application of Durkheim's theory of suicide to prison suicide rates in the United States.

PubMed

Tartaro, Christine; Lester, David

2005-06-01

E. Durkheim (1897) suggested that the societal rate of suicide might be explained by societal factors, such as marriage, divorce, and birth rates. The current study examined male prison suicide rates and suicide rates for men in the total population in the United States and found that variables based on Durkheim's theory of suicide explained prison suicide rates better than suicide rates for total population. Possible reasons for these findings are discussed.

Universal Barenco quantum gates via a tunable noncollinear interaction

NASA Astrophysics Data System (ADS)

Shi, Xiao-Feng

2018-03-01

The Barenco gate (B ) is a type of two-qubit quantum gate based on which alone universal quantum computation can be achieved. Each B is characterized by three angles (α , θ , and ϕ ), though it works in a two-qubit Hilbert space. Here we design B via a noncollinear interaction V | r1r2>< r1r3|+H .c . , where | ri> is a state that can be excited from a qubit state and V is adjustable. We present two protocols for B . The first (second) protocol consists of two (six) pulses and one (two) wait period(s), where the former causes rotations between qubit states and excited states, and the latter induces gate transformation via the noncollinear interaction. In the first protocol, the variable ϕ can be tuned by varying the phases of external controls, and the other two variables α and θ , tunable via adjustment of the wait duration, have a linear dependence on each other. Meanwhile, the first protocol can give rise to cnot and controlled-y gates. In the second protocol, α ,θ , and ϕ can be varied by changing the interaction amplitudes and wait durations, and the latter two are dependent on α nonlinearly. Both protocols can also lead to another universal gate when {α ,ϕ }={1 /4 ,1 /2 }π with appropriate parameters. Implementation of these universal gates is analyzed based on the van der Waals interaction of neutral Rydberg atoms.

Assessing the adequacy of water storage infrastructure capacity under hydroclimatic variability and water demands in the United States

NASA Astrophysics Data System (ADS)

Ho, M. W.; Devineni, N.; Cook, E. R.; Lall, U.

2017-12-01

As populations and associated economic activity in the US evolve, regional demands for water likewise change. For regions dependent on surface water, dams and reservoirs are critical to storing and managing releases of water and regulating the temporal and spatial availability of water in order to meet these demands. Storage capacities typically range from seasonal storage in the east to multi-annual and decadal-scale storage in the drier west. However, most dams in the US were designed with limited knowledge regarding the range, frequency, and persistence of hydroclimatic extremes. Demands for water supplied by these dams have likewise changed. Furthermore, many dams in the US are now reaching or have already exceeded their economic design life. The converging issues of aging dams, improved knowledge of hydroclimatic variability, and evolving demands for dam services result in a pressing need to evaluate existing reservoir capacities with respect to contemporary water demands, long term hydroclimatic variability, and service reliability into the future. Such an effort is possible given the recent development of two datasets that respectively address hydroclimatic variability in the conterminous United States over the past 555 years and human water demand related water stress over the same region. The first data set is a paleoclimate reconstruction of streamflow variability across the CONUS region based on a tree-ring informed reconstruction of the Palmer Drought Severity Index. This streamflow reconstruction suggested that wet spells with shorter drier spells were a key feature of 20th century streamflow compared with the preceding 450 years. The second data set in an annual cumulative drought index that is a measure of water balance based on water supplied through precipitation and water demands based on evaporative demands, agricultural, urban, and industrial demands. This index identified urban and regional hotspots that were particularly dependent on water transfers and vulnerable to persistent drought risk. These data sets are used in conjunction with the national inventory of dams to assess the current capacity of dams to meet water demands considering variability in streamflow over the past 555 years. A case study in the North-East US is presented.

The Soft State of Cygnus X-1 Observed with NuSTAR: A Variable Corona and a Stable Inner Disk

NASA Technical Reports Server (NTRS)

Walton, D. J.; Tomsick, J. A.; Madsen, K. K.; Grinberg, V.; Barret, D.; Boggs, S. E.; Christensen, F. E.; Clavel, M.; Craig, W. W.; Fabian, A. C.;

The Soft State of Cygnus X-1 Observed with NuSTAR: A Variable Corona and a Stable Inner Disk

NASA Astrophysics Data System (ADS)

Walton, D. J.; Tomsick, J. A.; Madsen, K. K.; Grinberg, V.; Barret, D.; Boggs, S. E.; Christensen, F. E.; Clavel, M.; Craig, W. W.; Fabian, A. C.; Fuerst, F.; Hailey, C. J.; Harrison, F. A.; Miller, J. M.; Parker, M. L.; Rahoui, F.; Stern, D.; Tao, L.; Wilms, J.; Zhang, W.

2016-07-01

We present a multi-epoch hard X-ray analysis of Cygnus X-1 in its soft state based on four observations with the Nuclear Spectroscopic Telescope Array (NuSTAR). Despite the basic similarity of the observed spectra, there is clear spectral variability between epochs. To investigate this variability, we construct a model incorporating both the standard disk-corona continuum and relativistic reflection from the accretion disk, based on prior work on Cygnus X-1, and apply this model to each epoch independently. We find excellent consistency for the black hole spin and the iron abundance of the accretion disk, which are expected to remain constant on observational timescales. In particular, we confirm that Cygnus X-1 hosts a rapidly rotating black hole, 0.93≲ {a}* ≲ 0.96, in broad agreement with the majority of prior studies of the relativistic disk reflection and constraints on the spin obtained through studies of the thermal accretion disk continuum. Our work also confirms the apparent misalignment between the inner disk and the orbital plane of the binary system reported previously, finding the magnitude of this warp to be ˜10°-15°. This level of misalignment does not significantly change (and may even improve) the agreement between our reflection results and the thermal continuum results regarding the black hole spin. The spectral variability observed by NuSTAR is dominated by the primary continuum, implying variability in the temperature of the scattering electron plasma. Finally, we consistently observe absorption from ionized iron at ˜6.7 keV, which varies in strength as a function of orbital phase in a manner consistent with the absorbing material being an ionized phase of the focused stellar wind from the supergiant companion star.

Multivariate dynamic Tobit models with lagged observed dependent variables: An effectiveness analysis of highway safety laws.

PubMed

Dong, Chunjiao; Xie, Kun; Zeng, Jin; Li, Xia

2018-04-01

Highway safety laws aim to influence driver behaviors so as to reduce the frequency and severity of crashes, and their outcomes. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT models to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as the explanatory variables and socio-demographic and traffic factors are used as the control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher speeding fines, older licensing age, and stronger graduated licensing provisions. Injury and PDO crashes would be significantly reduced with stricter laws prohibiting the use of hand-held communication devices and higher fines for drunk driving. Copyright © 2018 Elsevier Ltd. All rights reserved.

Towards equation of state of dark energy from quasar monitoring: Reverberation strategy

NASA Astrophysics Data System (ADS)

Czerny, B.; Hryniewicz, K.; Maity, I.; Schwarzenberg-Czerny, A.; Życki, P. T.; Bilicki, M.

2013-08-01

Context. High-redshift quasars can be used to constrain the equation of state of dark energy. They can serve as a complementary tool to supernovae Type Ia, especially at z > 1. Aims: The method is based on the determination of the size of the broad line region (BLR) from the emission line delay, the determination of the absolute monochromatic luminosity either from the observed statistical relation or from a model of the formation of the BLR, and the determination of the observed monochromatic flux from photometry. This allows the luminosity distance to a quasar to be obtained, independently from its redshift. The accuracy of the measurements is, however, a key issue. Methods: We modeled the expected accuracy of the measurements by creating artificial quasar monochromatic lightcurves and responses from the BLR under various assumptions about the variability of a quasar, BLR extension, distribution of the measurements in time, accuracy of the measurements, and the intrinsic line variability. Results: We show that the five-year monitoring of a single quasar based on the Mg II line should give an accuracy of 0.06-0.32 mag in the distance modulus which will allow new constraints to be put on the expansion rate of the Universe at high redshifts. Successful monitoring of higher redshift quasars based on C IV lines requires proper selection of the objects to avoid sources with much higher levels of the intrinsic variability of C IV compared to Mg II.

Imperfect physician assistant and physical therapist admissions processes in the United States

PubMed Central

2014-01-01

We compared and contrasted physician assistant and physical therapy profession admissions processes based on the similar number of accredited programs in the United States and the co-existence of many programs in the same school of health professions, because both professions conduct similar centralized application procedures administered by the same organization. Many studies are critical of the fallibility and inadequate scientific rigor of the high-stakes nature of health professions admissions decisions, yet typical admission processes remain very similar. Cognitive variables, most notably undergraduate grade point averages, have been shown to be the best predictors of academic achievement in the health professions. The variability of non-cognitive attributes assessed and the methods used to measure them have come under increasing scrutiny in the literature. The variance in health professions students’ performance in the classroom and on certifying examinations remains unexplained, and cognitive considerations vary considerably between and among programs that describe them. One uncertainty resulting from this review is whether or not desired candidate attributes highly sought after by individual programs are more student-centered or graduate-centered. Based on the findings from the literature, we suggest that student success in the classroom versus the clinic is based on a different set of variables. Given the range of positions and general lack of reliability and validity in studies of non-cognitive admissions attributes, we think that health professions admissions processes remain imperfect works in progress. PMID:24810020

Hybrid Methods in Quantum Information

NASA Astrophysics Data System (ADS)

Marshall, Kevin

Today, the potential power of quantum information processing comes as no surprise to physicist or science-fiction writer alike. However, the grand promises of this field remain unrealized, despite significant strides forward, due to the inherent difficulties of manipulating quantum systems. Simply put, it turns out that it is incredibly difficult to interact, in a controllable way, with the quantum realm when we seem to live our day to day lives in a classical world. In an effort to solve this challenge, people are exploring a variety of different physical platforms, each with their strengths and weaknesses, in hopes of developing new experimental methods that one day might allow us to control a quantum system. One path forward rests in combining different quantum systems in novel ways to exploit the benefits of different systems while circumventing their respective weaknesses. In particular, quantum systems come in two different flavours: either discrete-variable systems or continuous-variable ones. The field of hybrid quantum information seeks to combine these systems, in clever ways, to help overcome the challenges blocking the path between what is theoretically possible and what is achievable in a laboratory. In this thesis we explore four topics in the context of hybrid methods in quantum information, in an effort to contribute to the resolution of existing challenges and to stimulate new avenues of research. First, we explore the manipulation of a continuous-variable quantum system consisting of phonons in a linear chain of trapped ions where we use the discretized internal levels to mediate interactions. Using our proposed interaction we are able to implement, for example, the acoustic equivalent of a beam splitter with modest experimental resources. Next we propose an experimentally feasible implementation of the cubic phase gate, a primitive non-Gaussian gate required for universal continuous-variable quantum computation, based off sequential photon subtraction. We then discuss the notion of embedding a finite dimensional state into a continuous-variable system, and propose a method of performing quantum computations on encrypted continuous-variable states. This protocol allows for a client, of limited quantum ability, to outsource a computation while hiding their information. Next, we discuss the possibility of performing universal quantum computation on discrete-variable logical states encoded in mixed continuous-variable quantum states. Finally, we present an account of open problems related to our results, and possible future avenues of research.

Polynomial expansions of single-mode motions around equilibrium points in the circular restricted three-body problem

NASA Astrophysics Data System (ADS)

Lei, Hanlun; Xu, Bo; Circi, Christian

2018-05-01

In this work, the single-mode motions around the collinear and triangular libration points in the circular restricted three-body problem are studied. To describe these motions, we adopt an invariant manifold approach, which states that a suitable pair of independent variables are taken as modal coordinates and the remaining state variables are expressed as polynomial series of them. Based on the invariant manifold approach, the general procedure on constructing polynomial expansions up to a certain order is outlined. Taking the Earth-Moon system as the example dynamical model, we construct the polynomial expansions up to the tenth order for the single-mode motions around collinear libration points, and up to order eight and six for the planar and vertical-periodic motions around triangular libration point, respectively. The application of the polynomial expansions constructed lies in that they can be used to determine the initial states for the single-mode motions around equilibrium points. To check the validity, the accuracy of initial states determined by the polynomial expansions is evaluated.

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Longitudinal Mercury Monitoring Within the Japanese and Korean Communities (United States): Implications for Exposure Determination and Public Health Protection

EPA Science Inventory

Background: Estimates of exposure to toxicants are predominantly obtained from single timepoint data. Fishconsumption guidance based on these data may be incomplete as recommendations are unlikely to consider impact from factors such as intraindividual variability, seasonal dif...

Residential expansion as a continental threat to U.S. coastal ecosystems

Treesearch

J.G. Bartlett; D.M. Mageean; R.J. O' Connor

2000-01-01

Spatially extensive analysis of satellite, climate, and census data reveals human-environment interactions of regional or continental concern in the United States. A grid-based principal components analysis of Bureau of Census variables revealed two independent demographic phenomena, a-settlement reflecting traditional human settlement patterns and p-settlement...

A Model-Based Approach to Inventory Stratification

Treesearch

Ronald E. McRoberts

2006-01-01

Forest inventory programs report estimates of forest variables for areas of interest ranging in size from municipalities to counties to States and Provinces. Classified satellite imagery has been shown to be an effective source of ancillary data that, when used with stratified estimation techniques, contributes to increased precision with little corresponding increase...

The Evaluation and Research of Multi-Project Programs: Program Component Analysis.

ERIC Educational Resources Information Center

Baker, Eva L.

1977-01-01

It is difficult to base evaluations on concepts irrelevant to state policy making. Evaluation of a multiproject program requires both time and differentiation of method. Data from the California Early Childhood Program illustrate process variables for program component analysis, and research questions for intraprogram comparison. (CP)

Ecophysiological parameters for Pacific Northwest trees.

Treesearch

Amy E. Hessl; Cristina Milesi; Michael A. White; David L. Peterson; Robert E. Keane

2004-01-01

We developed a species- and location-specific database of published ecophysiological variables typically used as input parameters for biogeochemical models of coniferous and deciduous forested ecosystems in the Western United States. Parameters are based on the requirements of Biome-BGC, a widely used biogeochemical model that was originally parameterized for the...

Application of Probabilistic Methods for the Determination of an Economically Robust HSCT Configuration

NASA Technical Reports Server (NTRS)

Mavris, Dimitri N.; Bandte, Oliver; Schrage, Daniel P.

1996-01-01

This paper outlines an approach for the determination of economically viable robust design solutions using the High Speed Civil Transport (HSCT) as a case study. Furthermore, the paper states the advantages of a probability based aircraft design over the traditional point design approach. It also proposes a new methodology called Robust Design Simulation (RDS) which treats customer satisfaction as the ultimate design objective. RDS is based on a probabilistic approach to aerospace systems design, which views the chosen objective as a distribution function introduced by so called noise or uncertainty variables. Since the designer has no control over these variables, a variability distribution is defined for each one of them. The cumulative effect of all these distributions causes the overall variability of the objective function. For cases where the selected objective function depends heavily on these noise variables, it may be desirable to obtain a design solution that minimizes this dependence. The paper outlines a step by step approach on how to achieve such a solution for the HSCT case study and introduces an evaluation criterion which guarantees the highest customer satisfaction. This customer satisfaction is expressed by the probability of achieving objective function values less than a desired target value.

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.

Stochastic inference with spiking neurons in the high-conductance state

NASA Astrophysics Data System (ADS)

Petrovici, Mihai A.; Bill, Johannes; Bytschok, Ilja; Schemmel, Johannes; Meier, Karlheinz

2016-10-01

The highly variable dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference but stand in apparent contrast to the deterministic response of neurons measured in vitro. Based on a propagation of the membrane autocorrelation across spike bursts, we provide an analytical derivation of the neural activation function that holds for a large parameter space, including the high-conductance state. On this basis, we show how an ensemble of leaky integrate-and-fire neurons with conductance-based synapses embedded in a spiking environment can attain the correct firing statistics for sampling from a well-defined target distribution. For recurrent networks, we examine convergence toward stationarity in computer simulations and demonstrate sample-based Bayesian inference in a mixed graphical model. This points to a new computational role of high-conductance states and establishes a rigorous link between deterministic neuron models and functional stochastic dynamics on the network level.

A Numerical Scheme for Ordinary Differential Equations Having Time Varying and Nonlinear Coefficients Based on the State Transition Matrix

NASA Technical Reports Server (NTRS)

Bartels, Robert E.

2002-01-01

A variable order method of integrating initial value ordinary differential equations that is based on the state transition matrix has been developed. The method has been evaluated for linear time variant and nonlinear systems of equations. While it is more complex than most other methods, it produces exact solutions at arbitrary time step size when the time variation of the system can be modeled exactly by a polynomial. Solutions to several nonlinear problems exhibiting chaotic behavior have been computed. Accuracy of the method has been demonstrated by comparison with an exact solution and with solutions obtained by established methods.

Lidar Applications in Atmospheric Dynamics: Measurements of Wind, Moisture and Boundary Layer Evolution

NASA Technical Reports Server (NTRS)

Demoz, Belay; Whiteman, David; Gentry, Bruce; Schwemmer, Geary; Evans, Keith; DiGirolamo, Paolo; Comer, Joseph

2005-01-01

A large array of state-of-the-art ground-based and airborne remote and in-situ sensors were deployed during the International H2O Project (THOP), a field experiment that took place over the Southern Great Plains (SGP) of the United States from 13 May to 30 June 2002. These instruments provided extensive measurements of water vapor mixing ratio in order to better understand the influence of its variability on convection and on the skill of quantitative precipitation prediction (Weckwerth et all, 2004). Among the instrument deployed were ground based lidars from NASA/GSFC that included the Scanning Raman Lidar (SRL), the Goddard Laboratory for Observing Winds (GLOW), and the Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE). A brief description of the three lidars is given below. This study presents ground-based measurements of wind, boundary layer structure and water vapor mixing ratio measurements observed by three co-located lidars during MOP at the MOP ground profiling site in the Oklahoma Panhandle (hereafter referred as Homestead). This presentation will focus on the evolution and variability of moisture and wind in the boundary layer when frontal and/or convergence boundaries (e.g. bores, dry lines, thunderstorm outflows etc) were observed.

The application of thermally induced multistable composites to morphing aircraft structures

NASA Astrophysics Data System (ADS)

Mattioni, Filippo; Weaver, Paul M.; Potter, Kevin D.; Friswell, Michael I.

2008-03-01

One approach to morphing aircraft is to use bistable or multistable structures that have two or more stable equilibrium configurations to define a discrete set of shapes for the morphing structure. Moving between these stable states may be achieved using an actuation system or by aerodynamic loads. This paper considers three concepts for morphing aircraft based on multistable structures, namely a variable sweep wing, bistable blended winglets and a variable camber trailing edge. The philosophy behind these concepts is outlined, and simulated and experimental results are given.

Application of remote sensing to state and regional problems

NASA Technical Reports Server (NTRS)

Miller, W. F. (Principal Investigator); Quattrochi, D. A.; Carter, B. D.; Higgs, G. K.; Solomon, J. L.; Wax, C. L.

1979-01-01

The author has identified the following significant results. The Lowndes County data base is essentially complete with 18 primary variables and 16 proximity variables encoded into the geo-information system. The single purpose, decision tree classifier is now operational. Signatures for the thematic extraction of strip mines from LANDSAT Digital data were obtained by employing both supervised and nonsupervised procedures. Dry, blowing sand areas of beach were also identified from the LANDSAT data. The primary procedure was the analysis of analog data on the I2S signal slicer.

Post Detection Target State Estimation Using Heuristic Information Processing - A Preliminary Investigation

DTIC Science & Technology

1977-09-01

Interpolation algorithm allows this to be done when the transition boundaries are defined close together and parallel to one another. In this case the...in the variable kernel esti- -mates.) In [2] a goodness-of-fit criterion for a set of sam- One question of great interest to us in this study pies...an estimate /(x) is For the unimodal case the ab.olute minimum okV .based on the variables ocurs at k .= 100, ce 5. At this point we have j Mean

Unconditional optimality of Gaussian attacks against continuous-variable quantum key distribution.

PubMed

García-Patrón, Raúl; Cerf, Nicolas J

2006-11-10

A fully general approach to the security analysis of continuous-variable quantum key distribution (CV-QKD) is presented. Provided that the quantum channel is estimated via the covariance matrix of the quadratures, Gaussian attacks are shown to be optimal against all collective eavesdropping strategies. The proof is made strikingly simple by combining a physical model of measurement, an entanglement-based description of CV-QKD, and a recent powerful result on the extremality of Gaussian states [M. M. Wolf, Phys. Rev. Lett. 96, 080502 (2006)10.1103/PhysRevLett.96.080502].

Continuous-variable quantum key distribution protocols over noisy channels.

PubMed

García-Patrón, Raúl; Cerf, Nicolas J

2009-04-03

A continuous-variable quantum key distribution protocol based on squeezed states and heterodyne detection is introduced and shown to attain higher secret key rates over a noisy line than any other one-way Gaussian protocol. This increased resistance to channel noise can be understood as resulting from purposely adding noise to the signal that is converted into the secret key. This notion of noise-enhanced tolerance to noise also provides a better physical insight into the poorly understood discrepancies between the previously defined families of Gaussian protocols.

Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective

NASA Astrophysics Data System (ADS)

Wen, Shaobo; An, Haizhong; Chen, Zhihua; Liu, Xueyong

2017-08-01

In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government's policy mix.

The discriminatory value of cardiorespiratory interactions in distinguishing awake from anaesthetised states: a randomised observational study.

PubMed

Kenwright, D A; Bernjak, A; Draegni, T; Dzeroski, S; Entwistle, M; Horvat, M; Kvandal, P; Landsverk, S A; McClintock, P V E; Musizza, B; Petrovčič, J; Raeder, J; Sheppard, L W; Smith, A F; Stankovski, T; Stefanovska, A

2015-12-01

Depth of anaesthesia monitors usually analyse cerebral function with or without other physiological signals; non-invasive monitoring of the measured cardiorespiratory signals alone would offer a simple, practical alternative. We aimed to investigate whether such signals, analysed with novel, non-linear dynamic methods, would distinguish between the awake and anaesthetised states. We recorded ECG, respiration, skin temperature, pulse and skin conductivity before and during general anaesthesia in 27 subjects in good cardiovascular health, randomly allocated to receive propofol or sevoflurane. Mean values, variability and dynamic interactions were determined. Respiratory rate (p = 0.0002), skin conductivity (p = 0.03) and skin temperature (p = 0.00006) changed with sevoflurane, and skin temperature (p = 0.0005) with propofol. Pulse transit time increased by 17% with sevoflurane (p = 0.02) and 11% with propofol (p = 0.007). Sevoflurane reduced the wavelet energy of heart (p = 0.0004) and respiratory (p = 0.02) rate variability at all frequencies, whereas propofol decreased only the heart rate variability below 0.021 Hz (p < 0.05). The phase coherence was reduced by both agents at frequencies below 0.145 Hz (p < 0.05), whereas the cardiorespiratory synchronisation time was increased (p < 0.05). A classification analysis based on an optimal set of discriminatory parameters distinguished with 95% success between the awake and anaesthetised states. We suggest that these results can contribute to the design of new monitors of anaesthetic depth based on cardiovascular signals alone. © 2015 The Authors. Anaesthesia published by John Wiley & Sons Ltd on behalf of Association of Anaesthetists of Great Britain and Ireland.

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Extracting Plant Phenology Metrics in a Great Basin Watershed: Methods and Considerations for Quantifying Phenophases in a Cold Desert.

PubMed

Snyder, Keirith A; Wehan, Bryce L; Filippa, Gianluca; Huntington, Justin L; Stringham, Tamzen K; Snyder, Devon K

2016-11-18

Plant phenology is recognized as important for ecological dynamics. There has been a recent advent of phenology and camera networks worldwide. The established PhenoCam Network has sites in the United States, including the western states. However, there is a paucity of published research from semi-arid regions. In this study, we demonstrate the utility of camera-based repeat digital imagery and use of R statistical phenopix package to quantify plant phenology and phenophases in four plant communities in the semi-arid cold desert region of the Great Basin. We developed an automated variable snow/night filter for removing ephemeral snow events, which allowed fitting of phenophases with a double logistic algorithm. We were able to detect low amplitude seasonal variation in pinyon and juniper canopies and sagebrush steppe, and characterize wet and mesic meadows in area-averaged analyses. We used individual pixel-based spatial analyses to separate sagebrush shrub canopy pixels from interspace by determining differences in phenophases of sagebrush relative to interspace. The ability to monitor plant phenology with camera-based images fills spatial and temporal gaps in remotely sensed data and field based surveys, allowing species level relationships between environmental variables and phenology to be developed on a fine time scale thus providing powerful new tools for land management.

Evaluation of two momentum control variable schemes and their impact on the variational assimilation of radarwind data: Case study of a squall line

NASA Astrophysics Data System (ADS)

Li, Xin; Zeng, Mingjian; Wang, Yuan; Wang, Wenlan; Wu, Haiying; Mei, Haixia

2016-10-01

Different choices of control variables in variational assimilation can bring about different influences on the analyzed atmospheric state. Based on the WRF model's three-dimensional variational assimilation system, this study compares the behavior of two momentum control variable options—streamfunction velocity potential ( ψ-χ) and horizontal wind components ( U-V)—in radar wind data assimilation for a squall line case that occurred in Jiangsu Province on 24 August 2014. The wind increment from the single observation test shows that the ψ-χ control variable scheme produces negative increments in the neighborhood around the observation point because streamfunction and velocity potential preserve integrals of velocity. On the contrary, the U-V control variable scheme objectively reflects the information of the observation itself. Furthermore, radial velocity data from 17 Doppler radars in eastern China are assimilated. As compared to the impact of conventional observation, the assimilation of radar radial velocity based on the U-V control variable scheme significantly improves the mesoscale dynamic field in the initial condition. The enhanced low-level jet stream, water vapor convergence and low-level wind shear result in better squall line forecasting. However, the ψ-χ control variable scheme generates a discontinuous wind field and unrealistic convergence/divergence in the analyzed field, which lead to a degraded precipitation forecast.

Bulk-friction modeling of afterslip and the modified Omori law

USGS Publications Warehouse

Wennerberg, Leif; Sharp, Robert V.

1997-01-01

Afterslip data from the Superstition Hills fault in southern California, a creep event on the same fault, the modified Omori law, and cumulative moments from aftershocks of the 1957 Aleutian Islands earthquake all indicate that the original formulation by Dieterich (1981) [Constitutive properties of faults with simulated gouge. AGU, Geophys. Monogr. 24, 103–120] for friction evolution is more appropriate for systems far from instability than the commonly used approximation developed by Ruina (1983) [Slip instability and state variable friction laws. J. Geophys. Res. 88, 10359–10370] to study instability. The mathematical framework we use to test the friction models is a one-dimensional, massless spring-slider under the simplifying assumption, proposed by Scholz (1990) [The Mechanics of Earthquakes and Faulting. Cambridge University Press] and used by Marone et al. (1991) [On the mechanics of earthquake afterslip. J. Geophys. Res., 96: 8441–8452], that the state variable takes on its velocity-dependent steady-state value throughout motion in response to a step in stress. This assumption removes explicit state-variable dependence from the model, obviating the need to consider state-variable evolution equations. Anti-derivatives of the modified Omori law fit our data very well and are very good approximate solutions to our model equations. A plausible friction model with Omori-law solutions used by Wesson (1988) [Dynamics of fault creep. J. Geophys. Res. 93, 8929–8951] to model fault creep and generalized by Rice (1983) [Constitutive relations for fault slip and earthquake instabilities. Pure Appl. Geophys. 121, 443–475] to a rate-and-state variable friction model yields exactly Omori's law with exponents greater than 1, but yields unstable solutions for Omori exponents less than 1. We estimate from the Dieterich formulation the dimensionless parameter a∗ which is equal to the product of the nominal coefficient of friction and the more commonly reported friction parameter a. We find that a∗ is typically positive, qualitatively consistent with laboratory observations, although our observations are considerably larger than laboratory values. However, we also find good model fits for a∗ < 0 when data correspond to Omori exponents less than 1. A modification of the stability analysis by Rice and Ruina (1983) [Stability of steady frictional slipping. J. Appl. Mech. 50, 343–349] indicates that a∗ < 0 is not a consequence of our assumption regarding state-variable evolution. A consistent interpretation of a∗ < 0 in terms of laboratory models appears to be that the data are from later portions of processes better characterized by two-state-variable friction models. a∗ < 0 is explained by assuming that our data cannot resolve the co-seismic evolution of a short-length-scale state variable to a velocity-weakening state; our parameterization leads to an apparent negative instantaneous viscosity. We estimate the largest critical slip distance associated with afterslip to be ∼1–10 cm, consistent with other estimates for near-surface materials. We assume that our observed large values for a∗ reflect the fact that our model ignores the geometrical complexities of three-dimensional stresses in fractured crustal materials around a fault zone with frictional stresses that vary on a fault surface. Our one-dimensional model parameters reflect spatially averaged, bulk, stress and frictional properties of a fault zone, where we clearly cannot specify the details of the averaging process. Our analysis of Omori's law suggests that bulk-frictional properties of a fault zone are well described by our simple laboratory-based models, but they would need to change during the seismic cycle for a mainshock instability to recur, unless a mainshock-aftershock sequence were characterized by a process similar to the arrested instabilities possible in two-state-variable systems.

Bulk-friction modeling of afterslip and the modified Omori law

NASA Astrophysics Data System (ADS)

Wennerberg, Leif; Sharp, Robert V.

1997-08-01

Afterslip data from the Superstition Hills fault in southern California, a creep event on the same fault, the modified Omori law, and cumulative moments from aftershocks of the 1957 Aleutian Islands earthquake all indicate that the original formulation by Dieterich (1981) [Constitutive properties of faults with simulated gouge. AGU, Geophys. Monogr. 24, 103-120] for friction evolution is more appropriate for systems far from instability than the commonly used approximation developed by Ruina (1983) [Slip instability and state variable friction laws. J. Geophys. Res. 88, 10359-10370] to study instability. The mathematical framework we use to test the friction models is a one-dimensional, massless spring-slider under the simplifying assumption, proposed by Scholz (1990) [The Mechanics of Earthquakes and Faulting. Cambridge University Press] and used by Marone et al. (1991) [On the mechanics of earthquake afterslip. J. Geophys. Res., 96: 8441-8452], that the state variable takes on its velocity-dependent steady-state value throughout motion in response to a step in stress. This assumption removes explicit state-variable dependence from the model, obviating the need to consider state-variable evolution equations. Anti-derivatives of the modified Omori law fit our data very well and are very good approximate solutions to our model equations. A plausible friction model with Omori-law solutions used by Wesson (1988) [Dynamics of fault creep. J. Geophys. Res. 93, 8929-8951] to model fault creep and generalized by Rice (1983) [Constitutive relations for fault slip and earthquake instabilities. Pure Appl. Geophys. 121, 443-475] to a rate-and-state variable friction model yields exactly Omori's law with exponents greater than 1, but yields unstable solutions for Omori exponents less than 1. We estimate from the Dieterich formulation the dimensionless parameter a∗ which is equal to the product of the nominal coefficient of friction and the more commonly reported friction parameter a. We find that a∗ is typically positive, qualitatively consistent with laboratory observations, although our observations are considerably larger than laboratory values. However, we also find good model fits for a∗ < 0 when data correspond to Omori exponents less than 1. A modification of the stability analysis by Rice and Ruina (1983) [Stability of steady frictional slipping. J. Appl. Mech. 50, 343-349] indicates that a∗ < 0 is not a consequence of our assumption regarding state-variable evolution. A consistent interpretation of a∗ < 0 in terms of laboratory models appears to be that the data are from later portions of processes better characterized by two-state-variable friction models. a∗ < 0 is explained by assuming that our data cannot resolve the co-seismic evolution of a short-length-scale state variable to a velocity-weakening state; our parameterization leads to an apparent negative instantaneous viscosity. We estimate the largest critical slip distance associated with afterslip to be ˜1-10 cm, consistent with other estimates for near-surface materials. We assume that our observed large values for a∗ reflect the fact that our model ignores the geometrical complexities of three-dimensional stresses in fractured crustal materials around a fault zone with frictional stresses that vary on a fault surface. Our one-dimensional model parameters reflect spatially averaged, bulk, stress and frictional properties of a fault zone, where we clearly cannot specify the details of the averaging process. Our analysis of Omori's law suggests that bulk-frictional properties of a fault zone are well described by our simple laboratory-based models, but they would need to change during the seismic cycle for a mainshock instability to recur, unless a mainshock-aftershock sequence were characterized by a process similar to the arrested instabilities possible in two-state-variable systems.

Sliding mode control for Mars entry based on extended state observer

NASA Astrophysics Data System (ADS)

Lu, Kunfeng; Xia, Yuanqing; Shen, Ganghui; Yu, Chunmei; Zhou, Liuyu; Zhang, Lijun

2017-11-01

This paper addresses high-precision Mars entry guidance and control approach via sliding mode control (SMC) and Extended State Observer (ESO). First, differential flatness (DF) approach is applied to the dynamic equations of the entry vehicle to represent the state variables more conveniently. Then, the presented SMC law can guarantee the property of finite-time convergence of tracking error, which requires no information on high uncertainties that are estimated by ESO, and the rigorous proof of tracking error convergence is given. Finally, Monte Carlo simulation results are presented to demonstrate the effectiveness of the suggested approach.

Mapping ecological states in a complex environment

NASA Astrophysics Data System (ADS)

Steele, C. M.; Bestelmeyer, B.; Burkett, L. M.; Ayers, E.; Romig, K.; Slaughter, A.

2013-12-01

The vegetation of northern Chihuahuan Desert rangelands is sparse, heterogeneous and for most of the year, consists of a large proportion of non-photosynthetic material. The soils in this area are spectrally bright and variable in their reflectance properties. Both factors provide challenges to the application of remote sensing for estimating canopy variables (e.g., leaf area index, biomass, percentage canopy cover, primary production). Additionally, with reference to current paradigms of rangeland health assessment, remotely-sensed estimates of canopy variables have limited practical use to the rangeland manager if they are not placed in the context of ecological site and ecological state. To address these challenges, we created a multifactor classification system based on the USDA-NRCS ecological site schema and associated state-and-transition models to map ecological states on desert rangelands in southern New Mexico. Applying this system using per-pixel image processing techniques and multispectral, remotely sensed imagery raised other challenges. Per-pixel image classification relies upon the spectral information in each pixel alone, there is no reference to the spatial context of the pixel and its relationship with its neighbors. Ecological state classes may have direct relevance to managers but the non-unique spectral properties of different ecological state classes in our study area means that per-pixel classification of multispectral data performs poorly in discriminating between different ecological states. We found that image interpreters who are familiar with the landscape and its associated ecological site descriptions perform better than per-pixel classification techniques in assigning ecological states. However, two important issues affect manual classification methods: subjectivity of interpretation and reproducibility of results. An alternative to per-pixel classification and manual interpretation is object-based image analysis. Object-based image analysis provides a platform for classification that more closely resembles human recognition of objects within a remotely sensed image. The analysis presented here compares multiple thematic maps created for test locations on the USDA-ARS Jornada Experimental Range ranch. Three study sites in different pastures, each 300 ha in size, were selected for comparison on the basis of their ecological site type (';Clayey', ';Sandy' and a combination of both) and the degree of complexity of vegetation cover. Thematic maps were produced for each study site using (i) manual interpretation of digital aerial photography (by five independent interpreters); (ii) object-oriented, decision-tree classification of fine and moderate spatial resolution imagery (Quickbird; Landsat Thematic Mapper) and (iii) ground survey. To identify areas of uncertainty, we compared agreement in location, areal extent and class assignation between 5 independently produced, manually-digitized ecological state maps and with the map created from ground survey. Location, areal extent and class assignation of the map produced by object-oriented classification was also assessed with reference to the ground survey map.

Delay compensation in integrated communication and control systems. I - Conceptual development and analysis

NASA Technical Reports Server (NTRS)

Luck, Rogelio; Ray, Asok

1990-01-01

A procedure for compensating for the effects of distributed network-induced delays in integrated communication and control systems (ICCS) is proposed. The problem of analyzing systems with time-varying and possibly stochastic delays could be circumvented by use of a deterministic observer which is designed to perform under certain restrictive but realistic assumptions. The proposed delay-compensation algorithm is based on a deterministic state estimator and a linear state-variable-feedback control law. The deterministic observer can be replaced by a stochastic observer without any structural modifications of the delay compensation algorithm. However, if a feedforward-feedback control law is chosen instead of the state-variable feedback control law, the observer must be modified as a conventional nondelayed system would be. Under these circumstances, the delay compensation algorithm would be accordingly changed. The separation principle of the classical Luenberger observer holds true for the proposed delay compensator. The algorithm is suitable for ICCS in advanced aircraft, spacecraft, manufacturing automation, and chemical process applications.

Estimation of Subjective Mental Work Load Level with Heart Rate Variability by Tolerance to Driver's Mental Load

NASA Astrophysics Data System (ADS)

Yokoi, Toshiyuki; Itoh, Michimasa; Oguri, Koji

Most of the traffic accidents have been caused by inappropriate driver's mental state. Therefore, driver monitoring is one of the most important challenges to prevent traffic accidents. Some studies for evaluating the driver's mental state while driving have been reported; however driver's mental state should be estimated in real-time in the future. This paper proposes a way to estimate quantitatively driver's mental workload using heart rate variability. It is assumed that the tolerance to driver's mental workload is different depending on the individual. Therefore, we classify people based on their individual tolerance to mental workload. Our estimation method is multiple linear regression analysis, and we compare it to NASA-TLX which is used as the evaluation method of subjective mental workload. As a result, the coefficient of correlation improved from 0.83 to 0.91, and the standard deviation of error also improved. Therefore, our proposed method demonstrated the possibility to estimate mental workload.

Big five personality and residential mobility: a state-level analysis of the USA.

PubMed

McCann, Stewart J H

2015-01-01

Relations of the state-aggregated Big Five personality scores of 619,397 residents to four 2005 state-level residential mobility criteria were examined with the 50 states as cases. Multiple regression controlling for five state demographic variables showed (a) higher state neuroticism was strongly associated with lower mobility, lower same-county mobility, and lower between-county mobility; (b) higher state extraversion was associated with lower mobility and lower same-county mobility, but only with neuroticism and/or conscientiousness controlled; and (c) conscientiousness was related to same-residence, same-county, and different-county mobility, but only without demographic variables controlled. Discussion is grounded in the dangers of cross-level speculation and the potential of a basic assumption of geographical psychology that an area's aggregate position on a dispositional variable is associated there with behavioral and psychological tendencies related to that variable.

Entanglement criterion for tripartite systems based on local sum uncertainty relations

NASA Astrophysics Data System (ADS)

Akbari-Kourbolagh, Y.; Azhdargalam, M.

2018-04-01

We propose a sufficient criterion for the entanglement of tripartite systems based on local sum uncertainty relations for arbitrarily chosen observables of subsystems. This criterion generalizes the tighter criterion for bipartite systems introduced by Zhang et al. [C.-J. Zhang, H. Nha, Y.-S. Zhang, and G.-C. Guo, Phys. Rev. A 81, 012324 (2010), 10.1103/PhysRevA.81.012324] and can be used for both discrete- and continuous-variable systems. It enables us to detect the entanglement of quantum states without having a complete knowledge of them. Its utility is illustrated by some examples of three-qubit, qutrit-qutrit-qubit, and three-mode Gaussian states. It is found that, in comparison with other criteria, this criterion is able to detect some three-qubit bound entangled states more efficiently.

Spatial EPR entanglement in atomic vapor quantum memory

NASA Astrophysics Data System (ADS)

Parniak, Michal; Dabrowski, Michal; Wasilewski, Wojciech

Spatially-structured quantum states of light are staring to play a key role in modern quantum science with the rapid development of single-photon sensitive cameras. In particular, spatial degree of freedom holds a promise to enhance continous-variable quantum memories. Here we present the first demonstration of spatial entanglement between an atomic spin-wave and a photon measured with an I-sCMOS camera. The system is realized in a warm atomic vapor quantum memory based on rubidium atoms immersed in inert buffer gas. In the experiment we create and characterize a 12-dimensional entangled state exhibiting quantum correlations between a photon and an atomic ensemble in position and momentum bases. This state allows us to demonstrate the Einstein-Podolsky-Rosen paradox in its original version, with an unprecedented delay time of 6 μs between generation of entanglement and detection of the atomic state.

Sliding mode control based on Kalman filter dynamic estimation of battery SOC

NASA Astrophysics Data System (ADS)

He, Dongmeia; Hou, Enguang; Qiao, Xin; Liu, Guangmin

2018-06-01

Lithium-ion battery charge state of the accurate and rapid estimation of battery management system is the key technology. In this paper, an exponentially reaching law sliding-mode variable structure control algorithm based on Kalman filter is proposed to estimate the state of charge of Li-ion battery for the dynamic nonlinear system. The RC equivalent circuit model is established, and the model equation with specific structure is given. The proposed Kalman filter sliding mode structure is used to estimate the state of charge of the battery in the battery model, and the jitter effect can be avoided and the estimation performance can be improved. The simulation results show that the proposed Kalman filter sliding mode control has good accuracy in estimating the state of charge of the battery compared with the ordinary Kalman filter, and the error range is within 3%.

Development of a Josephson vortex two-state system based on a confocal annular Josephson junction

NASA Astrophysics Data System (ADS)

Monaco, Roberto; Mygind, Jesper; Koshelets, Valery P.

2018-07-01

We report theoretical and experimental work on the development of a Josephson vortex two-state system based on a confocal annular Josephson tunnel junction (CAJTJ). The key ingredient of this geometrical configuration is a periodically variable width that generates a spatial vortex potential with bistable states. This intrinsic vortex potential can be tuned by an externally applied magnetic field and tilted by a bias current. The two-state system is accurately modeled by a one-dimensional sine-Gordon like equation by means of which one can numerically calculate both the magnetic field needed to set the vortex in a given state as well as the vortex-depinning currents. Experimental data taken at 4.2 {{K}} on high-quality Nb/Al-AlOx/Nb CAJTJs with an individual trapped fluxon advocate the presence of a robust and finely tunable double-well potential for which reliable manipulation of the vortex state has been classically demonstrated. The vortex is prepared in a given potential by means of an externally applied magnetic field, while the state readout is accomplished by measuring the vortex-depinning current in a small magnetic field. Our proof of principle experiment convincingly demonstrates that the proposed vortex two-state system based on CAJTJs is robust and workable.

HadCM3 Simulations of ENSO behaviour during the Mid-Pliocene Warm Period

NASA Astrophysics Data System (ADS)

Bonham, S. G.; Haywood, A. M.; Lunt, D. J.

2009-04-01

It has been suggested that a permanent El Niño state existed during the mid-Pliocene (ca. 3.3 - 3.0 Ma BP), with a west-to-east temperature gradient in the tropical Pacific considerably weaker than today. This is based upon a number of palaeoceanographic studies which have examined the development of the thermocline and SST gradient in the tropical Pacific over the last five million years. This state is now being referred to as El Padre in recognition of the fact that a mean state warming in EEP SSTs does not necessarily imply the presence of a permanent El Niño. Recent results from mid-Pliocene coupled ocean-atmosphere model simulations have shown clear ENSO variability whilst maintaining the warming in the EEP. This research expands on this study, using the UK Met Office GCM (HadCM3), to examine the behaviour and characteristics of ENSO in two mid-Pliocene simulations (with an open and closed Central American Seaway, CAS) compared with a control pre-industrial run, as well as produce a detailed profile of the mean state climates. The results shown include timescales of ENSO variability across four regions in the Pacific, as well as frequency, EOF and wavelet analysis. We have also looked at the interaction of ENSO with the annual cycle and the onset of ENSO events, and the interdecadal variability in the simulations. The initial timeseries produced have shown a greater variability of ENSO during the closed CAS mid-Pliocene simulation where the system oscillates between events much more frequently than seen in the pre-industrial run. The EOF and wavelet analyses quantify this behaviour, showing that the variability is approximately 15% higher over the central and eastern equatorial Pacific, with a period of oscillation of 2-5 years compared with 4-8 years for the pre-industrial simulation. These results will be compared with those obtained from the second mid-Pliocene simulation (open CAS).

Early predictors of occupational back reinjury: results from a prospective study of workers in Washington State.

PubMed

Keeney, Benjamin J; Turner, Judith A; Fulton-Kehoe, Deborah; Wickizer, Thomas M; Chan, Kwun Chuen Gary; Franklin, Gary M

2013-01-15

Prospective population-based cohort study. To identify early predictors of self-reported occupational back reinjury within 1 year after work-related back injury. Back injuries are the costliest and most prevalent disabling occupational injuries in the United States. A substantial proportion of workers with back injuries have reinjuries after returning to work, yet there are few studies of risk factors for occupational back reinjuries. We aimed to identify the incidence and early (in the claim) predictors of self-reported back reinjury by approximately 1 year after the index injury among Washington State workers with new work disability claims for back injuries. The Washington Workers' Compensation Disability Risk Identification Study Cohort provided a large, population-based sample with information on variables in 7 domains: sociodemographic, employment-related, pain and function, clinical status, health care, health behavior, and psychological. We conducted telephone interviews with workers 3 weeks and 1 year after submission of a time-loss claim for the injury. We first identified predictors (P < 0.10) of self-reported reinjury within 1 year in bivariate analyses. Those variables were then included in a multivariate logistic regression model predicting occupational back reinjury. A total of 290 (25.8%) of 1123 (70.0% response rate) workers who completed the 1-year follow-up interview and had returned to work reported having reinjured their back at work. Baseline variables significantly associated with reinjury (P < 0.05) in the multivariate model included male sex, constant whole-body vibration at work, previous similar injury, 4 or more previous claims of any type, possessing health insurance, and high fear-avoidance scores. Baseline obesity was associated with reduced odds of reinjury. No other employment-related or psychological variables were significant. One-fourth of the workers who received work disability compensation for a back injury self-reported reinjury after returning to work. Baseline variables in multiple domains predicted occupational back reinjury. Increased knowledge of early risk factors for reinjury may help to lead to interventions, such as efforts to reduce fear avoidance and graded activity to promote recovery, effective in lowering the risk of reinjury.

A critical assessment of in-flight particle state during plasma spraying of YSZ and its implications on coating properties and process reliability

NASA Astrophysics Data System (ADS)

Srinivasan, Vasudevan

Air plasma spray is inherently complex due to the deviation from equilibrium conditions, three dimensional nature, multitude of interrelated (controllable) parameters and (uncontrollable) variables involved, and stochastic variability at different stages. The resultant coatings are complex due to the layered high defect density microstructure. Despite the widespread use and commercial success for decades in earthmoving, automotive, aerospace and power generation industries, plasma spray has not been completely understood and prime reliance for critical applications such as thermal barrier coatings on gas turbines are yet to be accomplished. This dissertation is aimed at understanding the in-flight particle state of the plasma spray process towards designing coatings and achieving coating reliability with the aid of noncontact in-flight particle and spray stream sensors. Key issues such as the phenomena of optimum particle injection and the definition of spray stream using particle state are investigated. Few strategies to modify the microstructure and properties of Yttria Stabilized Zirconia coatings are examined systematically using the framework of process maps. An approach to design process window based on design relevant coating properties is presented. Options to control the process for enhanced reproducibility and reliability are examined and the resultant variability is evaluated systematically at the different stages in the process. The 3D variability due to the difference in plasma characteristics has been critically examined by investigating splats collected from the entire spray footprint.

Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Jadidoleslam, N.; Mantilla, R.

2017-12-01

The Iowa Flood Center has developed a regional high-resolution flood-forecasting model for the state of Iowa that decomposes the landscape into hillslopes of about 0.1 km2. For the model to benefit, through data assimilation, from SMAP observations of soil moisture (SM) at scales of approximately 100 km2, we are testing a framework to connect SMAP-scale observations to the small-scale SM variability calculated by our rainfall-runoff models. As a step in this direction, we performed data analyses of 15-min point SM observations using a network of about 30 TDR instruments spread throughout the state. We developed a stochastic point-scale SM model that captures 1) SM increases due to rainfall inputs, and 2) SM decay during dry periods. We use a power law model to describe soil moisture decay during dry periods, and a single parameter logistic curve to describe precipitation feedback on soil moisture. We find that the parameters of the models behave as time-independent random variables with stationary distributions. Using data-based simulation, we explore differences in the dynamical range of variability of hillslope and SMAP-scale domains. The simulations allow us to predict the runoff field and streamflow hydrographs for the state of Iowa during the three largest flooding periods (2008, 2014, and 2016). We also use the results to determine the reduction in forecast uncertainty from assimilation of unbiased SMAP-scale soil moisture observations.

The Role of Dysfunctional Myths in a Decision-Making Process under Bounded Rationality: A Complex Dynamical Systems Perspective.

PubMed

Stamovlasis, Dimitrios; Vaiopoulou, Julie

2017-07-01

The present study examines the factors influencing a decision-making process, with specific focus on the role of dysfunctional myths (DM). DM are thoughts or beliefs that are rather irrational, however influential to people's decisions. In this paper a decision-making process regarding the career choice of university students majoring in natural sciences and education (N=496) is examined by analyzing survey data taken via Career Decision Making Difficulties Questionnaire (CDDQ). The difficulty of making the choice and the certainty about one's decision were the state variables, while the independent variables were factors related to the lack of information or knowledge needed, which actually reflect a bounded rationality. Cusp catastrophe analysis, based on both least squares and maximum likelihood procedures, showed that the nonlinear models predicting the two state variables were superior to linear alternatives. Factors related to lack of knowledge about the steps involved in the process of career decision-making, lack of information about the various occupations, lack of information about self and lack of motivation acted as asymmetry, while dysfunctional myths acted as bifurcation factor for both state variables. The catastrophe model, grounded in empirical data, revealed a unique role for DM and a better interpretation within the context of complexity and the notion of bounded rationality. The analysis opens the nonlinear dynamical systems (NDS) perspective in studying decision-making processes. Theoretical and practical implications are discussed.

Inferring Spatio-temporal Variations in the Risk of Extreme Precipitation in the Western United States from Tree-ring Chronologies

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.

2017-12-01

This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.

Inferring Spatio-temporal Variations in the Risk of Extreme Precipitation in the Western United States from Tree-ring Chronologies

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.

2016-12-01

This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.

Structural Brain Connectivity Constrains within-a-Day Variability of Direct Functional Connectivity

PubMed Central

Park, Bumhee; Eo, Jinseok; Park, Hae-Jeong

2017-01-01

The idea that structural white matter connectivity constrains functional connectivity (interactions among brain regions) has widely been explored in studies of brain networks; studies have mostly focused on the “average” strength of functional connectivity. The question of how structural connectivity constrains the “variability” of functional connectivity remains unresolved. In this study, we investigated the variability of resting state functional connectivity that was acquired every 3 h within a single day from 12 participants (eight time sessions within a 24-h period, 165 scans per session). Three different types of functional connectivity (functional connectivity based on Pearson correlation, direct functional connectivity based on partial correlation, and the pseudo functional connectivity produced by their difference) were estimated from resting state functional magnetic resonance imaging data along with structural connectivity defined using fiber tractography of diffusion tensor imaging. Those types of functional connectivity were evaluated with regard to properties of structural connectivity (fiber streamline counts and lengths) and types of structural connectivity such as intra-/inter-hemispheric edges and topological edge types in the rich club organization. We observed that the structural connectivity constrained the variability of direct functional connectivity more than pseudo-functional connectivity and that the constraints depended strongly on structural connectivity types. The structural constraints were greater for intra-hemispheric and heterologous inter-hemispheric edges than homologous inter-hemispheric edges, and feeder and local edges than rich club edges in the rich club architecture. While each edge was highly variable, the multivariate patterns of edge involvement, especially the direct functional connectivity patterns among the rich club brain regions, showed low variability over time. This study suggests that structural connectivity not only constrains the strength of functional connectivity, but also the within-a-day variability of functional connectivity and connectivity patterns, particularly the direct functional connectivity among brain regions. PMID:28848416

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816

Dominant root locus in state estimator design for material flow processes: A case study of hot strip rolling.

PubMed

Fišer, Jaromír; Zítek, Pavel; Skopec, Pavel; Knobloch, Jan; Vyhlídal, Tomáš

2017-05-01

The purpose of the paper is to achieve a constrained estimation of process state variables using the anisochronic state observer tuned by the dominant root locus technique. The anisochronic state observer is based on the state-space time delay model of the process. Moreover the process model is identified not only as delayed but also as non-linear. This model is developed to describe a material flow process. The root locus technique combined with the magnitude optimum method is utilized to investigate the estimation process. Resulting dominant roots location serves as a measure of estimation process performance. The higher the dominant (natural) frequency in the leftmost position of the complex plane the more enhanced performance with good robustness is achieved. Also the model based observer control methodology for material flow processes is provided by means of the separation principle. For demonstration purposes, the computer-based anisochronic state observer is applied to the strip temperatures estimation in the hot strip finishing mill composed of seven stands. This application was the original motivation to the presented research. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Multiproxy reconstruction of tropical Pacific Holocene temperature gradients and water column structure

NASA Astrophysics Data System (ADS)

Arbuszewski, J. A.; Oppo, D.; Huang, K.; Dubois, N.; Galy, V.; Mohtadi, M.; Herbert, T.; Rosenthal, Y.; Linsley, B. K.

2012-12-01

The El Niño-Southern Oscillation (ENSO) is the most prominent mode of tropical Pacific climate variability and has the potential to significantly impact the climate of the Indo-Pacific region and globally1. In the past, the mean state of the Pacific Ocean has, at times, resembled El Niño or La Niña conditions2. Although the dynamical relationships responsible for these changes have been studied through paleoproxy reconstructions and climate modeling, many questions remain. Recent paleoproxy based studies of tropical Pacific hydrology and surface temperature variability have hypothesized that observed climatological changes over the Holocene are directly linked to ENSO and/or mean state variability, complementing studies that dynamically relate centennial scale ENSO variability to mean state changes3-8. These studies have suggested that mid Holocene ENSO variability was low and the mean state was more "La Niña" like3-6. In the late Holocene, paleoproxy data has been interpreted as indicating an increase in ENSO variability with a more moderate mean ocean state3-6. However, alternative explanations could exist. Here, we test the hypothesis that observed climatological changes in the eastern tropical Pacific are related to mean state or ENSO variability during the Holocene. We focus our study on two sets of cores from the equatorial Pacific, with one located in the Indo-Pacific Warm Pool (BJ803-119 GGC, 117MC, sedimentation rates ~29 cm/kyr) and the other just off the Galapagos in the heart of the Eastern Cold Tongue (KNR195-5 43 GGC, 42MC, sedimentation rates ~20cm/kyr). The western site lies in the region predicted by models to show the greatest variations in temperature and water column structure in response to mean state changes, while the eastern site lies in the area most prone to changes due to ENSO variability7. Together, these sites allow us the best chance to robustly reconstruct ENSO and mean state related changes. We use a multiproxy approach and consider records from organic (sterol abundances) and inorganic proxies (Mg/Ca and δ18O of 3 planktonic foraminiferal species, % G. bulloides) to reconstruct zonal tropical Pacific (sub)surface temperature and stratification gradients over the Holocene. A benefit of using this approach is that it enables us to combine the strengths of each individual proxy to derive more robust records. We will compare our records with published paleoproxy and model studies in the Pacific and Indo-Pacific regions. Armed with this information, we aim to better understand mean state changes in the tropical Pacific over the Holocene. 1 Ropelewski, C. F. & Halpert, M. S. Monthly Weather Review 115, 1606-1626 (1987). 2 Collins, M. et al. Nature Geoscience 3, doi: 10.1038/NGEO1868 (2010). 3 Koutavas, A., Lynch-Steiglitz, J., Marchitto, T. & Sachs, J. Science 297, 226-230 (2002). 4 Moy, C. M., Seltzer, G. O., Rodbell, D. T. & Anderson, D. M. Nature 420, 162-165 (2002). 5 Conroy, J. L., Overpeck, J. T., Cole, J. E., Shanahan, T. M. & Steinitz-Kannan, M. Quaternary Science Reviews 27, 1166-1180 (2008). 6 Makou, M. C., Eglinton, T. I., Oppo, D. W. & Hughen, K. A. Geology 38, 43-46 (2010). 7 Karnauskas, K., Smerdon, J., Seager, R. & Gonzalez-Rouco, J. Journal of Climate, doi: 10.1178/JCLI-D-1111-00421.00421 (2012 (in press)). 8 Clement, A., Seager, R. & Cane, M. Paleoceanography 14, 441-456 (2000).

Using XMM-Newton to study the energy-dependent variability of H 1743-322 during its 2014 outburst

NASA Astrophysics Data System (ADS)

Stiele, H.; Yu, W.

2016-08-01

Black hole transients evolve during bright outbursts, showing distinct changes in their spectral and variability properties. These changes are interpreted as evidence for changes in the accretion flow and in the X-ray-emitting regions. We obtained an anticipated XMM-Newton Target of Opportunity observation of H 1743-322 during its outburst in 2014 September. Based on data from eight outbursts observed in the last 10 yr, we expected to catch the start of the hard-to-soft state transition. The fact that neither the general shape of the observed power density spectrum nor the characteristic frequency shows an energy dependence implies that the source remained in the low-hard state at the time of our observation near outburst peak. The spectral properties agree with the source being in the low-hard state, and a Swift/XRT monitoring of the outburst revealed that H 1743-322 stayed in the low-hard state during the entire outburst (known as a `failed outburst'). Here we derive the averaged QPO waveform and obtain phase-resolved spectra. A comparison of the phase-resolved spectra with the phase-averaged energy spectrum reveals spectral pivoting. We compare variability on long and short time-scales using covariance spectra and find that the covariance ratio does not show an increase towards lower energies. In other binaries an increase has been found. There are two possible explanations: either the absence of additional disc variability on longer time-scales is related to the high inclination of H 1743-322 compared with other black hole X-ray binaries, or it is the reason why we observe H 1743-322 during a failed outburst. More data on failed outbursts and on high-inclination sources will be needed in order to investigate these two possibilities further.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS.

PubMed

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-01-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

NASA Astrophysics Data System (ADS)

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-10-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

Development of Cell Models as a Basis for Bioreactor Design for Genetically Modified Bacteria

DTIC Science & Technology

1986-10-30

of future behavior based on specifying the current state vector . Generally a total population greater than 10,000 is sufficient to allow treatment of...specifying the current state vector (essentially values for all variables in the model). Deterministic models become increasingly valid as the number of...host I A) and therein PARASItIS converts the host’s biomaterial or activities into its own + A and B are in physical contact. SYMBIOSIS (or perhaps Oi

Demonstration of coherent-state discrimination using a displacement-controlled photon-number-resolving detector.

PubMed

Wittmann, Christoffer; Andersen, Ulrik L; Takeoka, Masahiro; Sych, Denis; Leuchs, Gerd

2010-03-12

We experimentally demonstrate a new measurement scheme for the discrimination of two coherent states. The measurement scheme is based on a displacement operation followed by a photon-number-resolving detector, and we show that it outperforms the standard homodyne detector which we, in addition, prove to be optimal within all Gaussian operations including conditional dynamics. We also show that the non-Gaussian detector is superior to the homodyne detector in a continuous variable quantum key distribution scheme.

State Estimation Using Dependent Evidence Fusion: Application to Acoustic Resonance-Based Liquid Level Measurement.

PubMed

Xu, Xiaobin; Li, Zhenghui; Li, Guo; Zhou, Zhe

2017-04-21

Estimating the state of a dynamic system via noisy sensor measurement is a common problem in sensor methods and applications. Most state estimation methods assume that measurement noise and state perturbations can be modeled as random variables with known statistical properties. However in some practical applications, engineers can only get the range of noises, instead of the precise statistical distributions. Hence, in the framework of Dempster-Shafer (DS) evidence theory, a novel state estimatation method by fusing dependent evidence generated from state equation, observation equation and the actual observations of the system states considering bounded noises is presented. It can be iteratively implemented to provide state estimation values calculated from fusion results at every time step. Finally, the proposed method is applied to a low-frequency acoustic resonance level gauge to obtain high-accuracy measurement results.

A mathematical model for Vertical Attitude Takeoff and Landing (VATOL) aircraft simulation. Volume 2: Model equations and base aircraft data

NASA Technical Reports Server (NTRS)

Fortenbaugh, R. L.

1980-01-01

Equations incorporated in a VATOL six degree of freedom off-line digital simulation program and data for the Vought SF-121 VATOL aircraft concept which served as the baseline for the development of this program are presented. The equations and data are intended to facilitate the development of a piloted VATOL simulation. The equation presentation format is to state the equations which define a particular model segment. Listings of constants required to quantify the model segment, input variables required to exercise the model segment, and output variables required by other model segments are included. In several instances a series of input or output variables are followed by a section number in parentheses which identifies the model segment of origination or termination of those variables.

A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Zurita-Milla, R.; de Wit, A. J. W.; Brazile, J.; Singh, R.; Schaepman, M. E.

2007-05-01

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise. In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical-empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections. The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.

Spatial structure and scaling of macropores in hydrological process at small catchment scale

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter

2013-04-01

During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.

Automatic design of basin-specific drought indexes for highly regulated water systems

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea Francesco; Pulido-Velazquez, Manuel

2018-04-01

Socio-economic costs of drought are progressively increasing worldwide due to undergoing alterations of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, traditional drought indexes often fail at detecting critical events in highly regulated systems, where natural water availability is conditioned by the operation of water infrastructures such as dams, diversions, and pumping wells. Here, ad hoc index formulations are usually adopted based on empirical combinations of several, supposed-to-be significant, hydro-meteorological variables. These customized formulations, however, while effective in the design basin, can hardly be generalized and transferred to different contexts. In this study, we contribute FRIDA (FRamework for Index-based Drought Analysis), a novel framework for the automatic design of basin-customized drought indexes. In contrast to ad hoc empirical approaches, FRIDA is fully automated, generalizable, and portable across different basins. FRIDA builds an index representing a surrogate of the drought conditions of the basin, computed by combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm. We used the Wrapper for Quasi-Equally Informative Subset Selection (W-QEISS), which features a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The preferred variable subset is selected among the efficient solutions and used to formulate the final index according to alternative model structures. We apply FRIDA to the case study of the Jucar river basin (Spain), a drought-prone and highly regulated Mediterranean water resource system, where an advanced drought management plan relying on the formulation of an ad hoc state index is used for triggering drought management measures. The state index was constructed empirically with a trial-and-error process begun in the 1980s and finalized in 2007, guided by the experts from the Confederación Hidrográfica del Júcar (CHJ). Our results show that the automated variable selection outcomes align with CHJ's 25-year-long empirical refinement. In addition, the resultant FRIDA index outperforms the official State Index in terms of accuracy in reproducing the target variable and cardinality of the selected inputs set.

Coding completeness and quality of relative survival-related variables in the National Program of Cancer Registries Cancer Surveillance System, 1995-2008.

PubMed

Wilson, Reda J; O'Neil, M E; Ntekop, E; Zhang, Kevin; Ren, Y

2014-01-01

Calculating accurate estimates of cancer survival is important for various analyses of cancer patient care and prognosis. Current US survival rates are estimated based on data from the National Cancer Institute's (NCI's) Surveillance, Epidemiology, and End RESULTS (SEER) program, covering approximately 28 percent of the US population. The National Program of Cancer Registries (NPCR) covers about 96 percent of the US population. Using a population-based database with greater US population coverage to calculate survival rates at the national, state, and regional levels can further enhance the effective monitoring of cancer patient care and prognosis in the United States. The first step is to establish the coding completeness and coding quality of the NPCR data needed for calculating survival rates and conducting related validation analyses. Using data from the NPCR-Cancer Surveillance System (CSS) from 1995 through 2008, we assessed coding completeness and quality on 26 data elements that are needed to calculate cancer relative survival estimates and conduct related analyses. Data elements evaluated consisted of demographic, follow-up, prognostic, and cancer identification variables. Analyses were performed showing trends of these variables by diagnostic year, state of residence at diagnosis, and cancer site. Mean overall percent coding completeness by each NPCR central cancer registry averaged across all data elements and diagnosis years ranged from 92.3 percent to 100 percent. RESULTS showing the mean percent coding completeness for the relative survival-related variables in NPCR data are presented. All data elements but 1 have a mean coding completeness greater than 90 percent as was the mean completeness by data item group type. Statistically significant differences in coding completeness were found in the ICD revision number, cause of death, vital status, and date of last contact variables when comparing diagnosis years. The majority of data items had a coding quality greater than 90 percent, with exceptions found in cause of death, follow-up source, and the SEER Summary Stage 1977, and SEER Summary Stage 2000. Percent coding completeness and quality are very high for variables in the NPCR-CSS that are covariates to calculating relative survival. NPCR provides the opportunity to calculate relative survival that may be more generalizable to the US population.

G-autonomy of EEG recordings of psychotic patients undergoing the primitive expression form of dance therapy

NASA Astrophysics Data System (ADS)

Ventouras, E.-C.; Lardi, I.; Dimitriou, S.; Margariti, A.; Chondraki, P.; Kalatzis, I.; Economou, N.-T.; Tsekou, H.; Paparrigopoulos, T.; Ktonas, P. Y.

2015-09-01

Primitive expression (PE) is a form of dance therapy (DT) that involves an interaction of ethologically and socially based forms which are supplied for re-enactment. Brain connectivity has been measured in electroencephalographic (EEG) data of patients with schizophrenia undergoing PE DT, using the correlation coefficient and mutual information. These parameters do not measure the existence or absence of directionality in the connectivity. The present study investigates the use of the G-autonomy measure of EEG electrode voltages of the same group of schizophrenic patients. G-autonomy is a measure of the “autonomy” of a system. It indicates the degree by which prediction of the system's future evolution is enhanced by taking into account its own past states, in comparison to predictions based on past states of a set of external variables. In the present research, “own” past states refer to voltage values in the time series recorded at a specific electrode and “external” variables refer to the voltage values recorded at other electrodes. Indication is provided for an acute effect of early-stage PE DT expressed by the augmentation of G-autonomy in the delta rhythm and an acute effect of late- stage PE DT expressed by the reduction of G-autonomy in the theta and alpha rhythms.

Combination of process and vibration data for improved condition monitoring of industrial systems working under variable operating conditions

NASA Astrophysics Data System (ADS)

Ruiz-Cárcel, C.; Jaramillo, V. H.; Mba, D.; Ottewill, J. R.; Cao, Y.

2016-01-01

The detection and diagnosis of faults in industrial processes is a very active field of research due to the reduction in maintenance costs achieved by the implementation of process monitoring algorithms such as Principal Component Analysis, Partial Least Squares or more recently Canonical Variate Analysis (CVA). Typically the condition of rotating machinery is monitored separately using vibration analysis or other specific techniques. Conventional vibration-based condition monitoring techniques are based on the tracking of key features observed in the measured signal. Typically steady-state loading conditions are required to ensure consistency between measurements. In this paper, a technique based on merging process and vibration data is proposed with the objective of improving the detection of mechanical faults in industrial systems working under variable operating conditions. The capabilities of CVA for detection and diagnosis of faults were tested using experimental data acquired from a compressor test rig where different process faults were introduced. Results suggest that the combination of process and vibration data can effectively improve the detectability of mechanical faults in systems working under variable operating conditions.

Mean Field Analysis of Stochastic Neural Network Models with Synaptic Depression

NASA Astrophysics Data System (ADS)

Yasuhiko Igarashi,; Masafumi Oizumi,; Masato Okada,

2010-08-01

We investigated the effects of synaptic depression on the macroscopic behavior of stochastic neural networks. Dynamical mean field equations were derived for such networks by taking the average of two stochastic variables: a firing-state variable and a synaptic variable. In these equations, the average product of thesevariables is decoupled as the product of their averages because the two stochastic variables are independent. We proved the independence of these two stochastic variables assuming that the synaptic weight Jij is of the order of 1/N with respect to the number of neurons N. Using these equations, we derived macroscopic steady-state equations for a network with uniform connections and for a ring attractor network with Mexican hat type connectivity and investigated the stability of the steady-state solutions. An oscillatory uniform state was observed in the network with uniform connections owing to a Hopf instability. For the ring network, high-frequency perturbations were shown not to affect system stability. Two mechanisms destabilize the inhomogeneous steady state, leading to two oscillatory states. A Turing instability leads to a rotating bump state, while a Hopf instability leads to an oscillatory bump state, which was previously unreported. Various oscillatory states take place in a network with synaptic depression depending on the strength of the interneuron connections.

Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism

PubMed Central

Fleming, R.M.T.; Thiele, I.; Provan, G.; Nasheuer, H.P.

2010-01-01

The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in E. coli and compare favourably with in silico prediction by flux balance analysis. PMID:20230840

Fluctuation relation based continuum model for thermoviscoplasticity in metals

NASA Astrophysics Data System (ADS)

Roy Chowdhury, Shubhankar; Roy, Debasish; Reddy, J. N.; Srinivasa, Arun

2016-11-01

A continuum plasticity model for metals is presented from considerations of non-equilibrium thermodynamics. Of specific interest is the application of a fluctuation relation that subsumes the second law of thermodynamics en route to deriving the evolution equations for the internal state variables. The modelling itself is accomplished in a two-temperature framework that appears naturally by considering the thermodynamic system to be composed of two weakly interacting subsystems, viz. a kinetic vibrational subsystem corresponding to the atomic lattice vibrations and a configurational subsystem of the slower degrees of freedom describing the motion of defects in a plastically deforming metal. An apparently physical nature of the present model derives upon considering the dislocation density, which characterizes the configurational subsystem, as a state variable. Unlike the usual constitutive modelling aided by the second law of thermodynamics that merely provides a guideline to select the admissible (though possibly non-unique) processes, the present formalism strictly determines the process or the evolution equations for the thermodynamic states while including the effect of fluctuations. The continuum model accommodates finite deformation and describes plastic deformation in a yield-free setup. The theory here is essentially limited to face-centered cubic metals modelled with a single dislocation density as the internal variable. Limited numerical simulations are presented with validation against relevant experimental data.

Global Qualitative Flow-Path Modeling for Local State Determination in Simulation and Analysis

NASA Technical Reports Server (NTRS)

Malin, Jane T. (Inventor); Fleming, Land D. (Inventor)

1998-01-01

For qualitative modeling and analysis, a general qualitative abstraction of power transmission variables (flow and effort) for elements of flow paths includes information on resistance, net flow, permissible directions of flow, and qualitative potential is discussed. Each type of component model has flow-related variables and an associated internal flow map, connected into an overall flow network of the system. For storage devices, the implicit power transfer to the environment is represented by "virtual" circuits that include an environmental junction. A heterogeneous aggregation method simplifies the path structure. A method determines global flow-path changes during dynamic simulation and analysis, and identifies corresponding local flow state changes that are effects of global configuration changes. Flow-path determination is triggered by any change in a flow-related device variable in a simulation or analysis. Components (path elements) that may be affected are identified, and flow-related attributes favoring flow in the two possible directions are collected for each of them. Next, flow-related attributes are determined for each affected path element, based on possibly conflicting indications of flow direction. Spurious qualitative ambiguities are minimized by using relative magnitudes and permissible directions of flow, and by favoring flow sources over effort sources when comparing flow tendencies. The results are output to local flow states of affected components.

Rocky Mountain spotted fever in Georgia, 1961-75: analysis of social and environmental factors affecting occurrence.

PubMed Central

Newhouse, V F; Choi, K; Holman, R C; Thacker, S B; D'Angelo, L J; Smith, J D

1986-01-01

For the period of 1961 through 1975, 10 geographic and sociologic variables in each of the 159 counties of Georgia were analyzed to determine how they were correlated with the occurrence of Rocky Mountain spotted fever (RMSF). Combinations of variables were transformed into a smaller number of factors using principal-component analysis. Based upon the relative values of these factors, geographic areas of similarity were delineated by cluster analysis. It was found by use of these analyses that the counties of the State formed four similarity clusters, which we called south, central, lower north and upper north. When the incidence of RMSF was subsequently calculated for each of these regions of similarity, the regions had differing RMSF incidence; low in the south and upper north, moderate in the central, and high in the lower north. The four similarity clusters agreed closely with the incidence of RMSF when both were plotted on a map. Thus, when analyzed simultaneously, the 10 variables selected could be used to predict the occurrence of RMSF. The most important variables were those of climate and geography. Of secondary, but still major importance, were the changes over the 15-year period in variables associated with humans and their environmental alterations. Detailed examination of these factors has permitted quantitative evaluation of the simultaneous impacts of the geographic and sociologic variables on the occurrence of RMSF in Georgia. These analyses could be updated to reflect changes in the relevant variables and tested as a means of identifying new high risk areas for RMSF in the State. More generally, this method might be adapted to clarify our understanding of the relative importance of individual variables in the ecology of other diseases or environmental health problems. PMID:3090609

Extended analysis of the Trojan-horse attack in quantum key distribution

NASA Astrophysics Data System (ADS)

Vinay, Scott E.; Kok, Pieter

2018-04-01

The discrete-variable quantum key distribution protocols based on the 1984 protocol of Bennett and Brassard (BB84) are known to be secure against an eavesdropper, Eve, intercepting the flying qubits and performing any quantum operation on them. However, these protocols may still be vulnerable to side-channel attacks. We investigate the Trojan-horse side-channel attack where Eve sends her own state into Alice's apparatus and measures the reflected state to estimate the key. We prove that the separable coherent state is optimal for Eve among the class of multimode Gaussian attack states, even in the presence of thermal noise. We then provide a bound on the secret key rate in the case where Eve may use any separable state.

Estimating the Probability of Elevated Nitrate Concentrations in Ground Water in Washington State

USGS Publications Warehouse

Frans, Lonna M.

2008-01-01

Logistic regression was used to relate anthropogenic (manmade) and natural variables to the occurrence of elevated nitrate concentrations in ground water in Washington State. Variables that were analyzed included well depth, ground-water recharge rate, precipitation, population density, fertilizer application amounts, soil characteristics, hydrogeomorphic regions, and land-use types. Two models were developed: one with and one without the hydrogeomorphic regions variable. The variables in both models that best explained the occurrence of elevated nitrate concentrations (defined as concentrations of nitrite plus nitrate as nitrogen greater than 2 milligrams per liter) were the percentage of agricultural land use in a 4-kilometer radius of a well, population density, precipitation, soil drainage class, and well depth. Based on the relations between these variables and measured nitrate concentrations, logistic regression models were developed to estimate the probability of nitrate concentrations in ground water exceeding 2 milligrams per liter. Maps of Washington State were produced that illustrate these estimated probabilities for wells drilled to 145 feet below land surface (median well depth) and the estimated depth to which wells would need to be drilled to have a 90-percent probability of drawing water with a nitrate concentration less than 2 milligrams per liter. Maps showing the estimated probability of elevated nitrate concentrations indicated that the agricultural regions are most at risk followed by urban areas. The estimated depths to which wells would need to be drilled to have a 90-percent probability of obtaining water with nitrate concentrations less than 2 milligrams per liter exceeded 1,000 feet in the agricultural regions; whereas, wells in urban areas generally would need to be drilled to depths in excess of 400 feet.

Prey-mediated behavioral responses of feeding blue whales in controlled sound exposure experiments.

PubMed

Friedlaender, A S; Hazen, E L; Goldbogen, J A; Stimpert, A K; Calambokidis, J; Southall, B L

2016-06-01

Behavioral response studies provide significant insights into the nature, magnitude, and consequences of changes in animal behavior in response to some external stimulus. Controlled exposure experiments (CEEs) to study behavioral response have faced challenges in quantifying the importance of and interaction among individual variability, exposure conditions, and environmental covariates. To investigate these complex parameters relative to blue whale behavior and how it may change as a function of certain sounds, we deployed multi-sensor acoustic tags and conducted CEEs using simulated mid-frequency active sonar (MFAS) and pseudo-random noise (PRN) stimuli, while collecting synoptic, quantitative prey measures. In contrast to previous approaches that lacked such prey data, our integrated approach explained substantially more variance in blue whale dive behavioral responses to mid-frequency sounds (r2 = 0.725 vs. 0.14 previously). Results demonstrate that deep-feeding whales respond more clearly and strongly to CEEs than those in other behavioral states, but this was only evident with the increased explanatory power provided by incorporating prey density and distribution as contextual covariates. Including contextual variables increases the ability to characterize behavioral variability and empirically strengthens previous findings that deep-feeding blue whales respond significantly to mid-frequency sound exposure. However, our results are only based on a single behavioral state with a limited sample size, and this analytical framework should be applied broadly across behavioral states. The increased capability to describe and account for individual response variability by including environmental variables, such as prey, that drive foraging behavior underscores the importance of integrating these and other relevant contextual parameters in experimental designs. Our results suggest the need to measure and account for the ecological dynamics of predator-prey interactions when studying the effects of anthropogenic disturbance in feeding animals.

Implementation of continuous-variable quantum key distribution with discrete modulation

NASA Astrophysics Data System (ADS)

Hirano, Takuya; Ichikawa, Tsubasa; Matsubara, Takuto; Ono, Motoharu; Oguri, Yusuke; Namiki, Ryo; Kasai, Kenta; Matsumoto, Ryutaroh; Tsurumaru, Toyohiro

2017-06-01

We have developed a continuous-variable quantum key distribution (CV-QKD) system that employs discrete quadrature-amplitude modulation and homodyne detection of coherent states of light. We experimentally demonstrated automated secure key generation with a rate of 50 kbps when a quantum channel is a 10 km optical fibre. The CV-QKD system utilises a four-state and post-selection protocol and generates a secure key against the entangling cloner attack. We used a pulsed light source of 1550 nm wavelength with a repetition rate of 10 MHz. A commercially available balanced receiver is used to realise shot-noise-limited pulsed homodyne detection. We used a non-binary LDPC code for error correction (reverse reconciliation) and the Toeplitz matrix multiplication for privacy amplification. A graphical processing unit card is used to accelerate the software-based post-processing.

Exact simulation of integrate-and-fire models with exponential currents.

PubMed

Brette, Romain

2007-10-01

Neural networks can be simulated exactly using event-driven strategies, in which the algorithm advances directly from one spike to the next spike. It applies to neuron models for which we have (1) an explicit expression for the evolution of the state variables between spikes and (2) an explicit test on the state variables that predicts whether and when a spike will be emitted. In a previous work, we proposed a method that allows exact simulation of an integrate-and-fire model with exponential conductances, with the constraint of a single synaptic time constant. In this note, we propose a method, based on polynomial root finding, that applies to integrate-and-fire models with exponential currents, with possibly many different synaptic time constants. Models can include biexponential synaptic currents and spike-triggered adaptation currents.

RF-subcarrier-assisted four-state continuous-variable QKD based on coherent detection.

PubMed

Qu, Zhen; Djordjevic, Ivan B; Neifeld, Mark A

2016-12-01

We theoretically investigate and experimentally demonstrate a RF-assisted four-state continuous-variable quantum key distribution (CV-QKD) system. Classical coherent detection is implemented with a simple digital phase noise cancelation scheme. In the proposed system, there is no need for frequency and phase locking between the quantum signals and the local oscillator laser. Moreover, in principle, there is no residual phase noise, and a mean excess noise of 0.0115 (in shot-noise units) can be acquired experimentally. In addition, the minimum transmittance of 0.45 is reached experimentally for secure transmission with commercial photodetectors, and the maximum secret key rate (SKR) of >12  Mbit/s can be obtained. The proposed RF-assisted CV-QKD system opens the door of incorporating microwave photonics into a CV-QKD system and improving the SKR significantly.

Scaling cosmology with variable dark-energy equation of state

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

Castro, David R.; Velten, Hermano; Zimdahl, Winfried, E-mail: drodriguez-ufes@hotmail.com, E-mail: velten@physik.uni-bielefeld.de, E-mail: winfried.zimdahl@pq.cnpq.br

2012-06-01

Interactions between dark matter and dark energy which result in a power-law behavior (with respect to the cosmic scale factor) of the ratio between the energy densities of the dark components (thus generalizing the ΛCDM model) have been considered as an attempt to alleviate the cosmic coincidence problem phenomenologically. We generalize this approach by allowing for a variable equation of state for the dark energy within the CPL-parametrization. Based on analytic solutions for the Hubble rate and using the Constitution and Union2 SNIa sets, we present a statistical analysis and classify different interacting and non-interacting models according to the Akaikemore » (AIC) and the Bayesian (BIC) information criteria. We do not find noticeable evidence for an alleviation of the coincidence problem with the mentioned type of interaction.« less

Enhancing Important Fluctuations: Rare Events and Metadynamics from a Conceptual Viewpoint

NASA Astrophysics Data System (ADS)

Valsson, Omar; Tiwary, Pratyush; Parrinello, Michele

2016-05-01

Atomistic simulations play a central role in many fields of science. However, their usefulness is often limited by the fact that many systems are characterized by several metastable states separated by high barriers, leading to kinetic bottlenecks. Transitions between metastable states are thus rare events that occur on significantly longer timescales than one can simulate in practice. Numerous enhanced sampling methods have been introduced to alleviate this timescale problem, including methods based on identifying a few crucial order parameters or collective variables and enhancing the sampling of these variables. Metadynamics is one such method that has proven successful in a great variety of fields. Here we review the conceptual and theoretical foundations of metadynamics. As demonstrated, metadynamics is not just a practical tool but can also be considered an important development in the theory of statistical mechanics.

Spectral Generation from the Ames Mars GCM for the Study of Martian Clouds

NASA Astrophysics Data System (ADS)

Klassen, David R.; Kahre, Melinda A.; Wolff, Michael J.; Haberle, Robert; Hollingsworth, Jeffery L.

2017-10-01

Studies of martian clouds come from two distinct groups of researchers: those modeling the martian system from first principles and those observing Mars from ground-based and orbital platforms. The model-view begins with global circulation models (GCMs) or mesoscale models to track a multitude of state variables over a prescribed set of spatial and temporal resolutions. The state variables can then be processed into distinct maps of derived product variables, such as integrated optical depth of aerosol (e.g., water ice cloud, dust) or column integrated water vapor for comparison to observational results. The observer view begins, typically, with spectral images or imaging spectra, calibrated to some form of absolute units then run through some form of radiative transfer model to also produce distinct maps of derived product variables. Both groups of researchers work to adjust model parameters and assumptions until some level of agreement in derived product variables is achieved. While this system appears to work well, it is in some sense only an implicit confirmation of the model assumptions that attribute to the work from both sides. We have begun a project of testing the NASA Ames Mars GCM and key aerosol model assumptions more directly by taking the model output and creating synthetic TES-spectra from them for comparison to actual raw-reduced TES spectra. We will present some preliminary generated GCM spectra and TES comparisons.

Understanding the weather signal in national crop-yield variability

NASA Astrophysics Data System (ADS)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

State-dependent rotations of spins by weak measurements

NASA Astrophysics Data System (ADS)

Miller, D. J.

2011-03-01

It is shown that a weak measurement of a quantum system produces a new state of the quantum system which depends on the prior state, as well as the (uncontrollable) measured position of the pointer variable of the weak-measurement apparatus. The result imposes a constraint on hidden-variable theories which assign a different state to a quantum system than standard quantum mechanics. The constraint means that a crypto-nonlocal hidden-variable theory can be ruled out in a more direct way than previously done.

Theory of Genuine Tripartite Nonlocality of Gaussian States

NASA Astrophysics Data System (ADS)

Adesso, Gerardo; Piano, Samanta

2014-01-01

We investigate the genuine multipartite nonlocality of three-mode Gaussian states of continuous variable systems. For pure states, we present a simplified procedure to obtain the maximum violation of the Svetlichny inequality based on displaced parity measurements, and we analyze its interplay with genuine tripartite entanglement measured via Rényi-2 entropy. The maximum Svetlichny violation admits tight upper and lower bounds at fixed tripartite entanglement. For mixed states, no violation is possible when the purity falls below 0.86. We also explore a set of recently derived weaker inequalities for three-way nonlocality, finding violations for all tested pure states. Our results provide a strong signature for the nonclassical and nonlocal nature of Gaussian states despite their positive Wigner function, and lead to precise recipes for its experimental verification.

Singular vector-based targeted observations of chemical constituents: description and first application of the EURAD-IM-SVA v1.0

NASA Astrophysics Data System (ADS)

Goris, N.; Elbern, H.

2015-12-01

Measurements of the large-dimensional chemical state of the atmosphere provide only sparse snapshots of the state of the system due to their typically insufficient temporal and spatial density. In order to optimize the measurement configurations despite those limitations, the present work describes the identification of sensitive states of the chemical system as optimal target areas for adaptive observations. For this purpose, the technique of singular vector analysis (SVA), which has proven effective for targeted observations in numerical weather prediction, is implemented in the EURAD-IM (EURopean Air pollution and Dispersion - Inverse Model) chemical transport model, yielding the EURAD-IM-SVA v1.0. Besides initial values, emissions are investigated as critical simulation controlling targeting variables. For both variants, singular vectors are applied to determine the optimal placement for observations and moreover to quantify which chemical compounds have to be observed with preference. Based on measurements of the airship based ZEPTER-2 campaign, the EURAD-IM-SVA v1.0 has been evaluated by conducting a comprehensive set of model runs involving different initial states and simulation lengths. For the sake of brevity, we concentrate our attention on the following chemical compounds, O3, NO, NO2, HCHO, CO, HONO, and OH, and focus on their influence on selected O3 profiles. Our analysis shows that the optimal placement for observations of chemical species is not entirely determined by mere transport and mixing processes. Rather, a combination of initial chemical concentrations, chemical conversions, and meteorological processes determines the influence of chemical compounds and regions. We furthermore demonstrate that the optimal placement of observations of emission strengths is highly dependent on the location of emission sources and that the benefit of including emissions as target variables outperforms the value of initial value optimization with growing simulation length. The obtained results confirm the benefit of considering both initial values and emission strengths as target variables and of applying the EURAD-IM-SVA v1.0 for measurement decision guidance with respect to chemical compounds.

Applying the Expectancy-Value Model to understand health values.

PubMed

Zhang, Xu-Hao; Xie, Feng; Wee, Hwee-Lin; Thumboo, Julian; Li, Shu-Chuen

2008-03-01

Expectancy-Value Model (EVM) is the most structured model in psychology to predict attitudes by measuring attitudinal attributes (AAs) and relevant external variables. Because health value could be categorized as attitude, we aimed to apply EVM to explore its usefulness in explaining variances in health values and investigate underlying factors. Focus group discussion was carried out to identify the most common and significant AAs toward 5 different health states (coded as 11111, 11121, 21221, 32323, and 33333 in EuroQol Five-Dimension (EQ-5D) descriptive system). AAs were measured in a sum of multiplications of subjective probability (expectancy) and perceived value of attributes with 7-point Likert scales. Health values were measured using visual analog scales (VAS, range 0-1). External variables (age, sex, ethnicity, education, housing, marital status, and concurrent chronic diseases) were also incorporated into survey questionnaire distributed by convenience sampling among eligible respondents. Univariate analyses were used to identify external variables causing significant differences in VAS. Multiple linear regression model (MLR) and hierarchical regression model were used to investigate the explanatory power of AAs and possible significant external variable(s) separately or in combination, for each individual health state and a mixed scenario of five states, respectively. Four AAs were identified, namely, "worsening your quality of life in terms of health" (WQoL), "adding a burden to your family" (BTF), "making you less independent" (MLI) and "unable to work or study" (UWS). Data were analyzed based on 232 respondents (mean [SD] age: 27.7 [15.07] years, 49.1% female). Health values varied significantly across 5 health states, ranging from 0.12 (33333) to 0.97 (11111). With no significant external variables identified, EVM explained up to 62% of the variances in health values across 5 health states. The explanatory power of 4 AAs were found to be between 13% and 28% in separate MLR models (P < 0.05). When data were analyzed for each health state, variances in health values became small and explanatory power of EVM was reduced to a range between 8% and 23%. EVM was useful in explaining variances of health values and predicting important factors. Its power to explain small variances might be restricted due to limitations of 7-point Likert scale to measure AAs accurately. With further improvement and validation of a compatible continuous scale for more accurate measurement, EVM is expected to explain health values to a larger extent.

Localization of one-photon state in space and Einstein-Podolsky-Rosen paradox in spontaneous parametric down conversion

NASA Technical Reports Server (NTRS)

Penin, A. N.; Reutova, T. A.; Sergienko, A. V.

1992-01-01

An experiment on one-photon state localization in space using a correlation technique in Spontaneous Parametric Down Conversion (SPDC) process is discussed. Results of measurements demonstrate an idea of the Einstein-Podolsky-Rosen (EPR) paradox for coordinate and momentum variables of photon states. Results of the experiment can be explained with the help of an advanced wave technique. The experiment is based on the idea that two-photon states of optical electromagnetic fields arising in the nonlinear process of the spontaneous parametric down conversion (spontaneous parametric light scattering) can be explained by quantum mechanical theory with the help of a single wave function.

Localization of one-photon state in space and Einstein-Podolsky-Rosen paradox in spontaneous parametric down conversion

NASA Astrophysics Data System (ADS)

Penin, A. N.; Reutova, T. A.; Sergienko, A. V.

1992-02-01

An experiment on one-photon state localization in space using a correlation technique in Spontaneous Parametric Down Conversion (SPDC) process is discussed. Results of measurements demonstrate an idea of the Einstein-Podolsky-Rosen (EPR) paradox for coordinate and momentum variables of photon states. Results of the experiment can be explained with the help of an advanced wave technique. The experiment is based on the idea that two-photon states of optical electromagnetic fields arising in the nonlinear process of the spontaneous parametric down conversion (spontaneous parametric light scattering) can be explained by quantum mechanical theory with the help of a single wave function.

Comparing five modelling techniques for predicting forest characteristics

Treesearch

Gretchen G. Moisen; Tracey S. Frescino

2002-01-01

Broad-scale maps of forest characteristics are needed throughout the United States for a wide variety of forest land management applications. Inexpensive maps can be produced by modelling forest class and structure variables collected in nationwide forest inventories as functions of satellite-based information. But little work has been directed at comparing modelling...

A Culture of Success--Examining School Culture and Student Outcomes via a Performance Framework

ERIC Educational Resources Information Center

Ohlson, Matthew; Swanson, Anne; Adams-Manning, Andrea; Byrd, Anna

2016-01-01

This study is a report of the relationship between a collaborative school culture, teacher quality and the influence these variables have upon student attendance and suspensions. The research is based upon data gathered from 50 public schools throughout the southeastern United States. Surveys were administered to examine teacher quality…

Selection of single chain variable fragments (scFv) against Xylella fastidiosa subsp. pauca by phage display

USDA-ARS?s Scientific Manuscript database

Xylella fastidiosa is a gram-negative member of the gamma proteobacteria. Xylella fastidiosa subsp pauca causes citrus variegated chlorosis in Brazil and enjoys ‘select agent’ status in the United States. Antibody based detection assays are commercially available for Xylella fastidiosa, and are ef...

Developing an Adequately Specified Model of State Level Student Achievement with Multilevel Data.

ERIC Educational Resources Information Center

Bernstein, Lawrence

Limitations of using linear, unilevel regression procedures in modeling student achievement are discussed. This study is a part of a broader study that is developing an empirically-based predictive model of variables associated with academic achievement from a multilevel perspective and examining the differences by which parameters are estimated…

The Historical Development of Educational Assessment in Chile: 1810-2014

ERIC Educational Resources Information Center

Gysling, Jacqueline

2016-01-01

This article examines the historical development of the state's actions in educational assessment in Chile from the nineteenth century to the present day, based on the analysis of governmental decrees and regulations related to assessment, and their variability over time. The research identifies six distinctive periods, each of which expresses a…

SEASONAL NH3 EMISSION ESTIMATES FOR THE EASTERN UNITED STATES BASED ON AMMONIUM WET CONCENTRATIONS AND AN INVERSE MODELING METHOD

EPA Science Inventory

Significant uncertainty exists in the magnitude and variability of ammonia (NH3) emissions. NH3 emissions are needed as input for air quality modeling of aerosols and deposition of nitrogen compounds. Approximately 85% of NH3 emissions are estimated to come from agricultural ...

The Social Competence of Highly Gifted Math and Science Adolescents

ERIC Educational Resources Information Center

Lee, Seon-Young; Olszewski-Kubilius, Paula; Thomson, Dana

2012-01-01

Involving 740 highly gifted math and science students from two different countries, Korea and the United States, this study examined how these gifted adolescents perceived their interpersonal ability and peer relationships and whether there were differences between these two groups by demographic variables. Based on the survey data, results showed…

Leaf temperature of maize and crop water stress index with variable irrigation and nitrogen supply

USDA-ARS?s Scientific Manuscript database

Water scarcity due to changing climate, population growth, and economic development is a major threat to the sustainability of irrigated agriculture in the Western United States and other regions around the world. Water stress indices based on crop canopy temperature can be useful for assessing plan...

Potential of space-borne GNSS reflectometry to constrain simulations of the ocean circulation. A case study for the South African current system

NASA Astrophysics Data System (ADS)

Saynisch, Jan; Semmling, Maximilian; Wickert, Jens; Thomas, Maik

2015-11-01

The Agulhas current system transports warm and salty water masses from the Indian Ocean into the Southern Ocean and into the Atlantic. The transports impact past, present, and future climate on local and global scales. The size and variability, however, of the respective transports are still much debated. In this study, an idealized model based twin experiment is used to study whether sea surface height (SSH) anomalies estimated from reflected signals of the Global Navigation Satellite System reflectometry (GNSS-R) can be used to determine the internal water mass properties and transports of the Agulhas region. A space-borne GNSS-R detector on the International Space Station (ISS) is assumed and simulated. The detector is able to observe daily SSH fields with a spatial resolution of 1-5∘. Depending on reflection geometry, the precision of a single SSH observation is estimated to reach 3 cm (20 cm) when the carrier phase (code delay) information of the reflected GNSS signal is used. The average precision over the Agulhas region is 7 cm (42 cm). The proposed GNSS-R measurements surpass the radar-based satellite altimetry missions in temporal and spatial resolution but are less precise. Using the estimated GNSS-R characteristics, measurements of SSH are generated by sampling a regional nested general circulation model of the South African oceans. The artificial observations are subsequently assimilated with a 4DVAR adjoint data assimilation method into the same ocean model but with a different initial state and forcing. The assimilated and the original, i.e., the sampled model state, are compared to systematically identify improvements and degradations in the model variables that arise due to the assimilation of GNSS-R based SSH observations. We show that SSH and the independent, i.e., not assimilated model variables velocity, temperature, and salinity improve by the assimilation of GNSS-R based SSH observations. After the assimilation of 90 days of SSH observations, improvements in the independent variables cover the whole water column. Locally, up to 39 % of the original model state are recovered. Shorter assimilation windows result in enhanced reproduction of the observed and assimilated SSH but are accompanied by an insufficient or wrong recovery of sub-surface water properties. The assimilation of real GNSS-R observations, when available, and consequently the estimation of Agulhas water mass properties and the leakage of heat and salt into the Atlantic will benefit from this model-based study.

A novel multivariate STeady-state index during general ANesthesia (STAN).

PubMed

Castro, Ana; de Almeida, Fernando Gomes; Amorim, Pedro; Nunes, Catarina S

2017-08-01

The assessment of the adequacy of general anesthesia for surgery, namely the nociception/anti-nociception balance, has received wide attention from the scientific community. Monitoring systems based on the frontal EEG/EMG, or autonomic state reactions (e.g. heart rate and blood pressure) have been developed aiming to objectively assess this balance. In this study a new multivariate indicator of patients' steady-state during anesthesia (STAN) is proposed, based on wavelet analysis of signals linked to noxious activation. A clinical protocol was designed to analyze precise noxious stimuli (laryngoscopy/intubation, tetanic, and incision), under three different analgesic doses; patients were randomized to receive either remifentanil 2.0, 3.0 or 4.0 ng/ml. ECG, PPG, BP, BIS, EMG and [Formula: see text] were continuously recorded. ECG, PPG and BP were processed to extract beat-to-beat information, and [Formula: see text] curve used to estimate the respiration rate. A combined steady-state index based on wavelet analysis of these variables, was applied and compared between the three study groups and stimuli (Wilcoxon signed ranks, Kruskal-Wallis and Mann-Whitney tests). Following institutional approval and signing the informed consent thirty four patients were enrolled in this study (3 excluded due to signal loss during data collection). The BIS index of the EEG, frontal EMG, heart rate, BP, and PPG wave amplitude changed in response to different noxious stimuli. Laryngoscopy/intubation was the stimulus with the more pronounced response [Formula: see text]. These variables were used in the construction of the combined index STAN; STAN responded adequately to noxious stimuli, with a more pronounced response to laryngoscopy/intubation (18.5-43.1 %, [Formula: see text]), and the attenuation provided by the analgesic, detecting steady-state periods in the different physiological signals analyzed (approximately 50 % of the total study time). A new multivariate approach for the assessment of the patient steady-state during general anesthesia was developed. The proposed wavelet based multivariate index responds adequately to different noxious stimuli, and attenuation provided by the analgesic in a dose-dependent manner for each stimulus analyzed in this study.

Monthly hydroclimatology of the continental United States

NASA Astrophysics Data System (ADS)

Petersen, Thomas; Devineni, Naresh; Sankarasubramanian, A.

2018-04-01

Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly hydroclimatology of ungauged basins using regional parameters.

Characterization of depressive States in bipolar patients using wearable textile technology and instantaneous heart rate variability assessment.

PubMed

Valenza, Gaetano; Citi, Luca; Gentili, Claudio; Lanata, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

2015-01-01

The analysis of cognitive and autonomic responses to emotionally relevant stimuli could provide a viable solution for the automatic recognition of different mood states, both in normal and pathological conditions. In this study, we present a methodological application describing a novel system based on wearable textile technology and instantaneous nonlinear heart rate variability assessment, able to characterize the autonomic status of bipolar patients by considering only electrocardiogram recordings. As a proof of this concept, our study presents results obtained from eight bipolar patients during their normal daily activities and being elicited according to a specific emotional protocol through the presentation of emotionally relevant pictures. Linear and nonlinear features were computed using a novel point-process-based nonlinear autoregressive integrative model and compared with traditional algorithmic methods. The estimated indices were used as the input of a multilayer perceptron to discriminate the depressive from the euthymic status. Results show that our system achieves much higher accuracy than the traditional techniques. Moreover, the inclusion of instantaneous higher order spectra features significantly improves the accuracy in successfully recognizing depression from euthymia.

Utilizing multiple state variables to improve the dynamic range of analog switching in a memristor

NASA Astrophysics Data System (ADS)

Jeong, YeonJoo; Kim, Sungho; Lu, Wei D.

2015-10-01

Memristors and memristive systems have been extensively studied for data storage and computing applications such as neuromorphic systems. To act as synapses in neuromorphic systems, the memristor needs to exhibit analog resistive switching (RS) behavior with incremental conductance change. In this study, we show that the dynamic range of the analog RS behavior can be significantly enhanced in a tantalum-oxide-based memristor. By controlling different state variables enabled by different physical effects during the RS process, the gradual filament expansion stage can be selectively enhanced without strongly affecting the abrupt filament length growth stage. Detailed physics-based modeling further verified the observed experimental effects and revealed the roles of oxygen vacancy drift and diffusion processes, and how the diffusion process can be selectively enhanced during the filament expansion stage. These findings lead to more desirable and reliable memristor behaviors for analog computing applications. Additionally, the ability to selectively control different internal physical processes demonstrated in the current study provides guidance for continued device optimization of memristor devices in general.

A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System.

PubMed

Zhang, Zhen; Ma, Cheng; Zhu, Rong

2017-08-23

Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System

PubMed Central

Zhang, Zhen; Zhu, Rong

2017-01-01

Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas. PMID:28832522

Observability-based Local Path Planning and Collision Avoidance Using Bearing-only Measurements

DTIC Science & Technology

2012-01-20

Clark N. Taylorb aDepartment of Electrical and Computer Engineering, Brigham Young University , Provo, Utah, 84602 bSensors Directorate, Air Force Research...NAME(S) AND ADDRESS(ES) Brigham Young University ,Department of Electrical and Computer Engineering,Provo,UT,84602 8. PERFORMING ORGANIZATION... vit is the measurement noise that is assumed to be a zero-mean Gaus- sian random variable. Based on the state transition model expressed by Eqs. (1

A Fuzzy Aproach For Facial Emotion Recognition

NASA Astrophysics Data System (ADS)

Gîlcă, Gheorghe; Bîzdoacă, Nicu-George

2015-09-01

This article deals with an emotion recognition system based on the fuzzy sets. Human faces are detected in images with the Viola - Jones algorithm and for its tracking in video sequences we used the Camshift algorithm. The detected human faces are transferred to the decisional fuzzy system, which is based on the variable fuzzyfication measurements of the face: eyebrow, eyelid and mouth. The system can easily determine the emotional state of a person.