Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.

PubMed

Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R

2015-12-01

The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

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.

A model of metastable dynamics during ongoing and evoked cortical activity

NASA Astrophysics Data System (ADS)

La Camera, Giancarlo

The dynamics of simultaneously recorded spike trains in alert animals often evolve through temporal sequences of metastable states. Little is known about the network mechanisms responsible for the genesis of such sequences, or their potential role in neural coding. In the gustatory cortex of alert rates, state sequences can be observed also in the absence of overt sensory stimulation, and thus form the basis of the so-called `ongoing activity'. This activity is characterized by a partial degree of coordination among neurons, sharp transitions among states, and multi-stability of single neurons' firing rates. A recurrent spiking network model with clustered topology can account for both the spontaneous generation of state sequences and the (network-generated) multi-stability. In the model, each network state results from the activation of specific neural clusters with potentiated intra-cluster connections. A mean field solution of the model shows a large number of stable states, each characterized by a subset of simultaneously active clusters. The firing rate in each cluster during ongoing activity depends on the number of active clusters, so that the same neuron can have different firing rates depending on the state of the network. Because of dense intra-cluster connectivity and recurrent inhibition, in finite networks the stable states lose stability due to finite size effects. Simulations of the dynamics show that the model ensemble activity continuously hops among the different states, reproducing the ongoing dynamics observed in the data. Moreover, when probed with external stimuli, the model correctly predicts the quenching of single neuron multi-stability into bi-stability, the reduction of dimensionality of the population activity, the reduction of trial-to-trial variability, and a potential role for metastable states in the anticipation of expected events. Altogether, these results provide a unified mechanistic model of ongoing and evoked cortical dynamics. NSF IIS-1161852, NIDCD K25-DC013557, NIDCD R01-DC010389.

A spatial hazard model for cluster detection on continuous indicators of disease: application to somatic cell score.

PubMed

Gay, Emilie; Senoussi, Rachid; Barnouin, Jacques

2007-01-01

Methods for spatial cluster detection dealing with diseases quantified by continuous variables are few, whereas several diseases are better approached by continuous indicators. For example, subclinical mastitis of the dairy cow is evaluated using a continuous marker of udder inflammation, the somatic cell score (SCS). Consequently, this study proposed to analyze spatialized risk and cluster components of herd SCS through a new method based on a spatial hazard model. The dataset included annual SCS for 34 142 French dairy herds for the year 2000, and important SCS risk factors: mean parity, percentage of winter and spring calvings, and herd size. The model allowed the simultaneous estimation of the effects of known risk factors and of potential spatial clusters on SCS, and the mapping of the estimated clusters and their range. Mean parity and winter and spring calvings were significantly associated with subclinical mastitis risk. The model with the presence of 3 clusters was highly significant, and the 3 clusters were attractive, i.e. closeness to cluster center increased the occurrence of high SCS. The three localizations were the following: close to the city of Troyes in the northeast of France; around the city of Limoges in the center-west; and in the southwest close to the city of Tarbes. The semi-parametric method based on spatial hazard modeling applies to continuous variables, and takes account of both risk factors and potential heterogeneity of the background population. This tool allows a quantitative detection but assumes a spatially specified form for clusters.

Continuous-variable quantum computation with spatial degrees of freedom of photons

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

Tasca, D. S.; Gomes, R. M.; Toscano, F.

2011-05-15

We discuss the use of the transverse spatial degrees of freedom of photons propagating in the paraxial approximation for continuous-variable information processing. Given the wide variety of linear optical devices available, a diverse range of operations can be performed on the spatial degrees of freedom of single photons. Here we show how to implement a set of continuous quantum logic gates which allow for universal quantum computation. In contrast with the usual quadratures of the electromagnetic field, the entire set of single-photon gates for spatial degrees of freedom does not require optical nonlinearity and, in principle, can be performed withmore » a single device: the spatial light modulator. Nevertheless, nonlinear optical processes, such as four-wave mixing, are needed in the implementation of two-photon gates. The efficiency of these gates is at present very low; however, small-scale investigations of continuous-variable quantum computation are within the reach of current technology. In this regard, we show how novel cluster states for one-way quantum computing can be produced using spontaneous parametric down-conversion.« less

An opinion-driven behavioral dynamics model for addictive behaviors

NASA Astrophysics Data System (ADS)

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; Ambrose, Bridget K.; Brodsky, Nancy S.; Brown, Theresa J.; Husten, Corinne; Glass, Robert J.

2015-04-01

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual's behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. This has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

Globular Cluster Variable Stars—Atlas and Coordinate Improvement using AAVSOnet Telescopes (Abstract)

NASA Astrophysics Data System (ADS)

Welch, D.; Henden, A.; Bell, T.; Suen, C.; Fare, I.; Sills, A.

2015-12-01

(Abstract only) The variable stars of globular clusters have played and continue to play a significant role in our understanding of certain classes of variable stars. Since all stars associated with a cluster have the same age, metallicity, distance and usually very similar (if not identical reddenings), such variables can produce uniquely powerful constraints on where certain types of pulsation behaviors are excited. Advanced amateur astronomers are increasingly well-positioned to provide long-term CCD monitoring of globular cluster variable star but are hampered by a long history of poor or inaccessible finder charts and coordinates. Many of variable-rich clusters have published photographic finder charts taken in relatively poor seeing with blue-sensitive photographic plates. While useful signal-to-noise ratios are relatively straightforward to achieve for RR Lyrae, Type 2 Cepheids, and red giant variables, correct identification remains a difficult issue—particularly when images are taken at V or longer wavelengths. We describe the project and report its progress using the OC61, TMO61, and SRO telescopes of AAVSOnet after the first year of image acquisition and demonstrate several of the data products being developed for globular cluster variables.

A clustering-based graph Laplacian framework for value function approximation in reinforcement learning.

PubMed

Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold

2014-12-01

In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.

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

Mixture modelling for cluster analysis.

PubMed

McLachlan, G J; Chang, S U

2004-10-01

Cluster analysis via a finite mixture model approach is considered. With this approach to clustering, the data can be partitioned into a specified number of clusters g by first fitting a mixture model with g components. An outright clustering of the data is then obtained by assigning an observation to the component to which it has the highest estimated posterior probability of belonging; that is, the ith cluster consists of those observations assigned to the ith component (i = 1,..., g). The focus is on the use of mixtures of normal components for the cluster analysis of data that can be regarded as being continuous. But attention is also given to the case of mixed data, where the observations consist of both continuous and discrete variables.

State estimation and prediction using clustered particle filters.

PubMed

Lee, Yoonsang; Majda, Andrew J

2016-12-20

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

State estimation and prediction using clustered particle filters

PubMed Central

Lee, Yoonsang; Majda, Andrew J.

2016-01-01

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

An opinion-driven behavioral dynamics model for addictive behaviors

DOE PAGES

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; ...

2015-04-08

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters providemore » targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.« less

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.

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

Cluster analysis and prediction of treatment outcomes for chronic rhinosinusitis.

PubMed

Soler, Zachary M; Hyer, J Madison; Rudmik, Luke; Ramakrishnan, Viswanathan; Smith, Timothy L; Schlosser, Rodney J

2016-04-01

Current clinical classifications of chronic rhinosinusitis (CRS) have weak prognostic utility regarding treatment outcomes. Simplified discriminant analysis based on unsupervised clustering has identified novel phenotypic subgroups of CRS, but prognostic utility is unknown. We sought to determine whether discriminant analysis allows prognostication in patients choosing surgery versus continued medical management. A multi-institutional prospective study of patients with CRS in whom initial medical therapy failed who then self-selected continued medical management or surgical treatment was used to separate patients into 5 clusters based on a previously described discriminant analysis using total Sino-Nasal Outcome Test-22 (SNOT-22) score, age, and missed productivity. Patients completed the SNOT-22 at baseline and for 18 months of follow-up. Baseline demographic and objective measures included olfactory testing, computed tomography, and endoscopy scoring. SNOT-22 outcomes for surgical versus continued medical treatment were compared across clusters. Data were available on 690 patients. Baseline differences in demographics, comorbidities, objective disease measures, and patient-reported outcomes were similar to previous clustering reports. Three of 5 clusters identified by means of discriminant analysis had improved SNOT-22 outcomes with surgical intervention when compared with continued medical management (surgery was a mean of 21.2 points better across these 3 clusters at 6 months, P < .05). These differences were sustained at 18 months of follow-up. Two of 5 clusters had similar outcomes when comparing surgery with continued medical management. A simplified discriminant analysis based on 3 common clinical variables is able to cluster patients and provide prognostic information regarding surgical treatment versus continued medical management in patients with CRS. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Physical-depth architectural requirements for generating universal photonic cluster states

NASA Astrophysics Data System (ADS)

Morley-Short, Sam; Bartolucci, Sara; Gimeno-Segovia, Mercedes; Shadbolt, Pete; Cable, Hugo; Rudolph, Terry

2018-01-01

Most leading proposals for linear-optical quantum computing (LOQC) use cluster states, which act as a universal resource for measurement-based (one-way) quantum computation. In ballistic approaches to LOQC, cluster states are generated passively from small entangled resource states using so-called fusion operations. Results from percolation theory have previously been used to argue that universal cluster states can be generated in the ballistic approach using schemes which exceed the critical threshold for percolation, but these results consider cluster states with unbounded size. Here we consider how successful percolation can be maintained using a physical architecture with fixed physical depth, assuming that the cluster state is continuously generated and measured, and therefore that only a finite portion of it is visible at any one point in time. We show that universal LOQC can be implemented using a constant-size device with modest physical depth, and that percolation can be exploited using simple pathfinding strategies without the need for high-complexity algorithms.

Determination of Arctic sea ice variability modes on interannual timescales via nonhierarchical clustering

NASA Astrophysics Data System (ADS)

Fučkar, Neven-Stjepan; Guemas, Virginie; Massonnet, François; Doblas-Reyes, Francisco

2015-04-01

Over the modern observational era, the northern hemisphere sea ice concentration, age and thickness have experienced a sharp long-term decline superimposed with strong internal variability. Hence, there is a crucial need to identify robust patterns of Arctic sea ice variability on interannual timescales and disentangle them from the long-term trend in noisy datasets. The principal component analysis (PCA) is a versatile and broadly used method for the study of climate variability. However, the PCA has several limiting aspects because it assumes that all modes of variability have symmetry between positive and negative phases, and suppresses nonlinearities by using a linear covariance matrix. Clustering methods offer an alternative set of dimension reduction tools that are more robust and capable of taking into account possible nonlinear characteristics of a climate field. Cluster analysis aggregates data into groups or clusters based on their distance, to simultaneously minimize the distance between data points in a given cluster and maximize the distance between the centers of the clusters. We extract modes of Arctic interannual sea-ice variability with nonhierarchical K-means cluster analysis and investigate the mechanisms leading to these modes. Our focus is on the sea ice thickness (SIT) as the base variable for clustering because SIT holds most of the climate memory for variability and predictability on interannual timescales. We primarily use global reconstructions of sea ice fields with a state-of-the-art ocean-sea-ice model, but we also verify the robustness of determined clusters in other Arctic sea ice datasets. Applied cluster analysis over the 1958-2013 period shows that the optimal number of detrended SIT clusters is K=3. Determined SIT cluster patterns and their time series of occurrence are rather similar between different seasons and months. Two opposite thermodynamic modes are characterized with prevailing negative or positive SIT anomalies over the Arctic basin. The intermediate mode, with negative anomalies centered on the East Siberian shelf and positive anomalies along the North American side of the basin, has predominately dynamic characteristics. The associated sea ice concentration (SIC) clusters vary more between different seasons and months, but the SIC patterns are physically framed by the SIT cluster patterns.

Sample heterogeneity in unipolar depression as assessed by functional connectivity analyses is dominated by general disease effects.

PubMed

Feder, Stephan; Sundermann, Benedikt; Wersching, Heike; Teuber, Anja; Kugel, Harald; Teismann, Henning; Heindel, Walter; Berger, Klaus; Pfleiderer, Bettina

2017-11-01

Combinations of resting-state fMRI and machine-learning techniques are increasingly employed to develop diagnostic models for mental disorders. However, little is known about the neurobiological heterogeneity of depression and diagnostic machine learning has mainly been tested in homogeneous samples. Our main objective was to explore the inherent structure of a diverse unipolar depression sample. The secondary objective was to assess, if such information can improve diagnostic classification. We analyzed data from 360 patients with unipolar depression and 360 non-depressed population controls, who were subdivided into two independent subsets. Cluster analyses (unsupervised learning) of functional connectivity were used to generate hypotheses about potential patient subgroups from the first subset. The relationship of clusters with demographical and clinical measures was assessed. Subsequently, diagnostic classifiers (supervised learning), which incorporated information about these putative depression subgroups, were trained. Exploratory cluster analyses revealed two weakly separable subgroups of depressed patients. These subgroups differed in the average duration of depression and in the proportion of patients with concurrently severe depression and anxiety symptoms. The diagnostic classification models performed at chance level. It remains unresolved, if subgroups represent distinct biological subtypes, variability of continuous clinical variables or in part an overfitting of sparsely structured data. Functional connectivity in unipolar depression is associated with general disease effects. Cluster analyses provide hypotheses about potential depression subtypes. Diagnostic models did not benefit from this additional information regarding heterogeneity. Copyright © 2017 Elsevier B.V. All rights reserved.

The first search for variable stars in the open cluster NGC 6253 and its surrounding field

NASA Astrophysics Data System (ADS)

de Marchi, F.; Poretti, E.; Montalto, M.; Desidera, S.; Piotto, G.

2010-01-01

Aims: This work presents the first high-precision variability survey in the field of the intermediate-age, metal-rich open cluster NGC 6253. Clusters of this type are benchmarks for stellar evolution models. Methods: Continuous photometric monitoring of the cluster and its surrounding field was performed over a time span of ten nights using the Wide Field Imager mounted at the ESO-MPI 2.2 m telescope. High-quality timeseries, each composed of about 800 datapoints, were obtained for 250 000 stars using ISIS and DAOPHOT packages. Candidate members were selected by using the colour-magnitude diagrams and period-luminosity-colour relations. Membership probabilities based on the proper motions were also used. The membership of all the variables discovered within a radius of 8´ from the centre is discussed by comparing the incidence of the classes in the cluster direction and in the surrounding field. Results: We discovered 595 variables and we also characterized most of them providing their variability classes, periods, and amplitudes. The sample is complete for short periods: we classified 20 pulsating variables, 225 contact systems, 99 eclipsing systems (22 β Lyr type, 59 β Per type, 18 RS CVn type), and 77 rotational variables. The time-baseline hampered the precise characterization of 173 variables with periods longer than 4-5 days. Moreover, we found a cataclysmic system undergoing an outburst of about 2.5 mag. We propose a list of 35 variable stars as probable members of NGC 6253. ARRAY(0x383c870)

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

2016-12-01

State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

Estimating the concrete compressive strength using hard clustering and fuzzy clustering based regression techniques.

PubMed

Nagwani, Naresh Kumar; Deo, Shirish V

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm.

Estimating the Concrete Compressive Strength Using Hard Clustering and Fuzzy Clustering Based Regression Techniques

PubMed Central

Nagwani, Naresh Kumar; Deo, Shirish V.

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm. PMID:25374939

Chimeras and clusters in networks of hyperbolic chaotic oscillators

NASA Astrophysics Data System (ADS)

Cano, A. V.; Cosenza, M. G.

2017-03-01

We show that chimera states, where differentiated subsets of synchronized and desynchronized dynamical elements coexist, can emerge in networks of hyperbolic chaotic oscillators subject to global interactions. As local dynamics we employ Lozi maps, which possess hyperbolic chaotic attractors. We consider a globally coupled system of these maps and use two statistical quantities to describe its collective behavior: the average fraction of elements belonging to clusters and the average standard deviation of state variables. Chimera states, clusters, complete synchronization, and incoherence are thus characterized on the space of parameters of the system. We find that chimera states are related to the formation of clusters in the system. In addition, we show that chimera states arise for a sufficiently long range of interactions in nonlocally coupled networks of these maps. Our results reveal that, under some circumstances, hyperbolicity does not impede the formation of chimera states in networks of coupled chaotic systems, as it had been previously hypothesized.

Quantum phase transition between cluster and antiferromagnetic states

NASA Astrophysics Data System (ADS)

Son, W.; Amico, L.; Fazio, R.; Hamma, A.; Pascazio, S.; Vedral, V.

2011-09-01

We study a Hamiltonian system describing a three-spin-1/2 cluster-like interaction competing with an Ising-like exchange. We show that the ground state in the cluster phase possesses symmetry protected topological order. A continuous quantum phase transition occurs as result of the competition between the cluster and Ising terms. At the critical point the Hamiltonian is self-dual. The geometric entanglement is also studied and used to investigate the quantum phase transition. Our findings in one dimension corroborate the analysis of the two-dimensional generalization of the system, indicating, at a mean-field level, the presence of a direct transition between an antiferromagnetic and a valence bond solid ground state.

Electronic, Magnetic, and Redox Properties of [MFe(3)S(4)] Clusters (M = Cd, Cu, Cr) in Pyrococcus furiosus Ferredoxin.

PubMed

Staples, Christopher R.; Dhawan, Ish K.; Finnegan, Michael G.; Dwinell, Derek A.; Zhou, Zhi Hao; Huang, Heshu; Verhagen, Marc F. J. M.; Adams, Michael W. W.; Johnson, Michael K.

1997-12-03

The ground- and excited-state properties of heterometallic [CuFe(3)S(4)](2+,+), [CdFe(3)S(4)](2+,+), and [CrFe(3)S(4)](2+,+) cubane clusters assembled in Pyrococcus furiosus ferredoxin have been investigated by the combination of EPR and variable-temperature/variable-field magnetic circular dichroism (MCD) studies. The results indicate Cd(2+) incorporation into [Fe(3)S(4)](0,-) cluster fragments to yield S = 2 [CdFe(3)S(4)](2+) and S = (5)/(2) [CdFe(3)S(4)](+) clusters and Cu(+) incorporation into [Fe(3)S(4)](+,0) cluster fragments to yield S = (1)/(2) [CuFe(3)S(4)](2+) and S = 2 [CuFe(3)S(4)](+) clusters. This is the first report of the preparation of cubane type [CrFe(3)S(4)](2+,+) clusters, and the combination of EPR and MCD results indicates S = 0 and S = (3)/(2) ground states for the oxidized and reduced forms, respectively. Midpoint potentials for the [CdFe(3)S(4)](2+,+), [CrFe(3)S(4)](2+,+), and [CuFe(3)S(4)](2+,+) couples, E(m) = -470 +/- 15, -440 +/- 10, and +190 +/- 10 mV (vs NHE), respectively, were determined by EPR-monitored redox titrations or direct electrochemistry at a glassy carbon electrode. The trends in redox potential, ground-state spin, and electron delocalization of [MFe(3)S(4)](2+,+) clusters in P. furiosus ferredoxin are discussed as a function of heterometal (M = Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Tl).

Clustering Multivariate Time Series Using Hidden Markov Models

PubMed Central

Ghassempour, Shima; Girosi, Federico; Maeder, Anthony

2014-01-01

In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers. PMID:24662996

An AO-assisted Variability Study of Four Globular Clusters

NASA Astrophysics Data System (ADS)

Salinas, R.; Contreras Ramos, R.; Strader, J.; Hakala, P.; Catelan, M.; Peacock, M. B.; Simunovic, M.

2016-09-01

The image-subtraction technique applied to study variable stars in globular clusters represented a leap in the number of new detections, with the drawback that many of these new light curves could not be transformed to magnitudes due to severe crowding. In this paper, we present observations of four Galactic globular clusters, M 2 (NGC 7089), M 10 (NGC 6254), M 80 (NGC 6093), and NGC 1261, taken with the ground-layer adaptive optics module at the SOAR Telescope, SAM. We show that the higher image quality provided by SAM allows for the calibration of the light curves of the great majority of the variables near the cores of these clusters as well as the detection of new variables, even in clusters where image-subtraction searches were already conducted. We report the discovery of 15 new variables in M 2 (12 RR Lyrae stars and 3 SX Phe stars), 12 new variables in M 10 (11 SX Phe and 1 long-period variable), and 1 new W UMa-type variable in NGC 1261. No new detections are found in M 80, but previous uncertain detections are confirmed and the corresponding light curves are calibrated into magnitudes. Additionally, based on the number of detected variables and new Hubble Space Telescope/UVIS photometry, we revisit a previous suggestion that M 80 may be the globular cluster with the richest population of blue stragglers in our Galaxy. Based on observations obtained at the Southern Astrophysical Research (SOAR) telescope, which is a joint project of the Ministério da Ciência, Tecnologia, e Inovação (MCTI) da República Federativa do Brasil, the U.S. National Optical Astronomy Observatory (NOAO), the University of North Carolina at Chapel Hill (UNC), and Michigan State University (MSU).

Event-based cluster synchronization of coupled genetic regulatory networks

NASA Astrophysics Data System (ADS)

Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

2017-09-01

In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

Characterization and evaluation of controls on post-fire streamflow response across western US watersheds

NASA Astrophysics Data System (ADS)

Saxe, Samuel; Hogue, Terri S.; Hay, Lauren

2018-02-01

This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two 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. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards-Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. Results show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors strongly influence response. Spearman correlation identified NDVI, aridity index, percent of a watershed's precipitation that falls as rain, and slope as being positively correlated with post-fire streamflow response. This metric also suggested a negative correlation between response and the soil erodibility factor, watershed area, and percent low burn severity. Regression models identified only moderate burn severity and watershed area as being consistently positively/negatively correlated, respectively, with response. The random forest model identified only slope and percent area burned as significant watershed parameters controlling response. Results will help inform post-fire runoff management decisions by helping to identify expected changes to flow regimes, as well as facilitate parameterization for model application in burned watersheds.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review.

PubMed

Kristunas, Caroline; Morris, Tom; Gray, Laura

2017-11-15

To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Any, not limited to healthcare settings. Any taking part in an SW-CRT published up to March 2016. The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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.

Clustering P-Wave Receiver Functions To Constrain Subsurface Seismic Structure

NASA Astrophysics Data System (ADS)

Chai, C.; Larmat, C. S.; Maceira, M.; Ammon, C. J.; He, R.; Zhang, H.

2017-12-01

The acquisition of high-quality data from permanent and temporary dense seismic networks provides the opportunity to apply statistical and machine learning techniques to a broad range of geophysical observations. Lekic and Romanowicz (2011) used clustering analysis on tomographic velocity models of the western United States to perform tectonic regionalization and the velocity-profile clusters agree well with known geomorphic provinces. A complementary and somewhat less restrictive approach is to apply cluster analysis directly to geophysical observations. In this presentation, we apply clustering analysis to teleseismic P-wave receiver functions (RFs) continuing efforts of Larmat et al. (2015) and Maceira et al. (2015). These earlier studies validated the approach with surface waves and stacked EARS RFs from the USArray stations. In this study, we experiment with both the K-means and hierarchical clustering algorithms. We also test different distance metrics defined in the vector space of RFs following Lekic and Romanowicz (2011). We cluster data from two distinct data sets. The first, corresponding to the western US, was by smoothing/interpolation of receiver-function wavefield (Chai et al. 2015). Spatial coherence and agreement with geologic region increase with this simpler, spatially smoothed set of observations. The second data set is composed of RFs for more than 800 stations of the China Digital Seismic Network (CSN). Preliminary results show a first order agreement between clusters and tectonic region and each region cluster includes a distinct Ps arrival, which probably reflects differences in crustal thickness. Regionalization remains an important step to characterize a model prior to application of full waveform and/or stochastic imaging techniques because of the computational expense of these types of studies. Machine learning techniques can provide valuable information that can be used to design and characterize formal geophysical inversion, providing information on spatial variability in the subsurface geology.

Automatic Clustering Using FSDE-Forced Strategy Differential Evolution

NASA Astrophysics Data System (ADS)

Yasid, A.

2018-01-01

Clustering analysis is important in datamining for unsupervised data, cause no adequate prior knowledge. One of the important tasks is defining the number of clusters without user involvement that is known as automatic clustering. This study intends on acquiring cluster number automatically utilizing forced strategy differential evolution (AC-FSDE). Two mutation parameters, namely: constant parameter and variable parameter are employed to boost differential evolution performance. Four well-known benchmark datasets were used to evaluate the algorithm. Moreover, the result is compared with other state of the art automatic clustering methods. The experiment results evidence that AC-FSDE is better or competitive with other existing automatic clustering algorithm.

The potential of clustering methods to define intersection test scenarios: Assessing real-life performance of AEB.

PubMed

Sander, Ulrich; Lubbe, Nils

2018-04-01

Intersection accidents are frequent and harmful. The accident types 'straight crossing path' (SCP), 'left turn across path - oncoming direction' (LTAP/OD), and 'left-turn across path - lateral direction' (LTAP/LD) represent around 95% of all intersection accidents and one-third of all police-reported car-to-car accidents in Germany. The European New Car Assessment Program (Euro NCAP) have announced that intersection scenarios will be included in their rating from 2020; however, how these scenarios are to be tested has not been defined. This study investigates whether clustering methods can be used to identify a small number of test scenarios sufficiently representative of the accident dataset to evaluate Intersection Automated Emergency Braking (AEB). Data from the German In-Depth Accident Study (GIDAS) and the GIDAS-based Pre-Crash Matrix (PCM) from 1999 to 2016, containing 784 SCP and 453 LTAP/OD accidents, were analyzed with principal component methods to identify variables that account for the relevant total variances of the sample. Three different methods for data clustering were applied to each of the accident types, two similarity-based approaches, namely Hierarchical Clustering (HC) and Partitioning Around Medoids (PAM), and the probability-based Latent Class Clustering (LCC). The optimum number of clusters was derived for HC and PAM with the silhouette method. The PAM algorithm was both initiated with random start medoid selection and medoids from HC. For LCC, the Bayesian Information Criterion (BIC) was used to determine the optimal number of clusters. Test scenarios were defined from optimal cluster medoids weighted by their real-life representation in GIDAS. The set of variables for clustering was further varied to investigate the influence of variable type and character. We quantified how accurately each cluster variation represents real-life AEB performance using pre-crash simulations with PCM data and a generic algorithm for AEB intervention. The usage of different sets of clustering variables resulted in substantially different numbers of clusters. The stability of the resulting clusters increased with prioritization of categorical over continuous variables. For each different set of cluster variables, a strong in-cluster variance of avoided versus non-avoided accidents for the specified Intersection AEB was present. The medoids did not predict the most common Intersection AEB behavior in each cluster. Despite thorough analysis using various cluster methods and variable sets, it was impossible to reduce the diversity of intersection accidents into a set of test scenarios without compromising the ability to predict real-life performance of Intersection AEB. Although this does not imply that other methods cannot succeed, it was observed that small changes in the definition of a scenario resulted in a different avoidance outcome. Therefore, we suggest using limited physical testing to validate more extensive virtual simulations to evaluate vehicle safety. Copyright © 2018 Elsevier Ltd. All rights reserved.

Kinetics of binary nucleation of vapors in size and composition space.

PubMed

Fisenko, Sergey P; Wilemski, Gerald

2004-11-01

We reformulate the kinetic description of binary nucleation in the gas phase using two natural independent variables: the total number of molecules g and the molar composition x of the cluster. The resulting kinetic equation can be viewed as a two-dimensional Fokker-Planck equation describing the simultaneous Brownian motion of the clusters in size and composition space. Explicit expressions for the Brownian diffusion coefficients in cluster size and composition space are obtained. For characterization of binary nucleation in gases three criteria are established. These criteria establish the relative importance of the rate processes in cluster size and composition space for different gas phase conditions and types of liquid mixtures. The equilibrium distribution function of the clusters is determined in terms of the variables g and x. We obtain an approximate analytical solution for the steady-state binary nucleation rate that has the correct limit in the transition to unary nucleation. To further illustrate our description, the nonequilibrium steady-state cluster concentrations are found by numerically solving the reformulated kinetic equation. For the reformulated transient problem, the relaxation or induction time for binary nucleation was calculated using Galerkin's method. This relaxation time is affected by processes in both size and composition space, but the contributions from each process can be separated only approximately.

THE MASS-RICHNESS RELATION OF MaxBCG CLUSTERS FROM QUASAR LENSING MAGNIFICATION USING VARIABILITY

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

Bauer, Anne H.; Baltay, Charles; Ellman, Nancy

2012-04-10

Accurate measurement of galaxy cluster masses is an essential component not only in studies of cluster physics but also for probes of cosmology. However, different mass measurement techniques frequently yield discrepant results. The Sloan Digital Sky Survey MaxBCG catalog's mass-richness relation has previously been constrained using weak lensing shear, Sunyaev-Zeldovich (SZ), and X-ray measurements. The mass normalization of the clusters as measured by weak lensing shear is {approx}>25% higher than that measured using SZ and X-ray methods, a difference much larger than the stated measurement errors in the analyses. We constrain the mass-richness relation of the MaxBCG galaxy cluster catalogmore » by measuring the gravitational lensing magnification of type I quasars in the background of the clusters. The magnification is determined using the quasars' variability and the correlation between quasars' variability amplitude and intrinsic luminosity. The mass-richness relation determined through magnification is in agreement with that measured using shear, confirming that the lensing strength of the clusters implies a high mass normalization and that the discrepancy with other methods is not due to a shear-related systematic measurement error. We study the dependence of the measured mass normalization on the cluster halo orientation. As expected, line-of-sight clusters yield a higher normalization; however, this minority of haloes does not significantly bias the average mass-richness relation of the catalog.« less

Stellar Variability at the Main-sequence Turnoff of the Intermediate-age LMC Cluster NGC 1846

NASA Astrophysics Data System (ADS)

Salinas, R.; Pajkos, M. A.; Vivas, A. K.; Strader, J.; Contreras Ramos, R.

2018-04-01

Intermediate-age (IA) star clusters in the Large Magellanic Cloud (LMC) present extended main-sequence turn-offs (MSTO) that have been attributed to either multiple stellar populations or an effect of stellar rotation. Recently it has been proposed that these extended main sequences can also be produced by ill-characterized stellar variability. Here we present Gemini-S/Gemini Multi-Object Spectrometer (GMOS) time series observations of the IA cluster NGC 1846. Using differential image analysis, we identified 73 new variable stars, with 55 of those being of the Delta Scuti type, that is, pulsating variables close the MSTO for the cluster age. Considering completeness and background contamination effects, we estimate the number of δ Sct belonging to the cluster between 40 and 60 members, although this number is based on the detection of a single δ Sct within the cluster half-light radius. This amount of variable stars at the MSTO level will not produce significant broadening of the MSTO, albeit higher-resolution imaging will be needed to rule out variable stars as a major contributor to the extended MSTO phenomenon. Though modest, this amount of δ Sct makes NGC 1846 the star cluster with the highest number of these variables ever discovered. Lastly, our results present a cautionary tale about the adequacy of shallow variability surveys in the LMC (like OGLE) to derive properties of its δ Sct population. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), and Ministério da Ciência, Tecnologia e Inovação (Brazil).

Violation of Bell's Inequality Using Continuous Variable Measurements

NASA Astrophysics Data System (ADS)

Thearle, Oliver; Janousek, Jiri; Armstrong, Seiji; Hosseini, Sara; Schünemann Mraz, Melanie; Assad, Syed; Symul, Thomas; James, Matthew R.; Huntington, Elanor; Ralph, Timothy C.; Lam, Ping Koy

2018-01-01

A Bell inequality is a fundamental test to rule out local hidden variable model descriptions of correlations between two physically separated systems. There have been a number of experiments in which a Bell inequality has been violated using discrete-variable systems. We demonstrate a violation of Bell's inequality using continuous variable quadrature measurements. By creating a four-mode entangled state with homodyne detection, we recorded a clear violation with a Bell value of B =2.31 ±0.02 . This opens new possibilities for using continuous variable states for device independent quantum protocols.

An open-source software package for multivariate modeling and clustering: applications to air quality management.

PubMed

Wang, Xiuquan; Huang, Guohe; Zhao, Shan; Guo, Junhong

2015-09-01

This paper presents an open-source software package, rSCA, which is developed based upon a stepwise cluster analysis method and serves as a statistical tool for modeling the relationships between multiple dependent and independent variables. The rSCA package is efficient in dealing with both continuous and discrete variables, as well as nonlinear relationships between the variables. It divides the sample sets of dependent variables into different subsets (or subclusters) through a series of cutting and merging operations based upon the theory of multivariate analysis of variance (MANOVA). The modeling results are given by a cluster tree, which includes both intermediate and leaf subclusters as well as the flow paths from the root of the tree to each leaf subcluster specified by a series of cutting and merging actions. The rSCA package is a handy and easy-to-use tool and is freely available at http://cran.r-project.org/package=rSCA . By applying the developed package to air quality management in an urban environment, we demonstrate its effectiveness in dealing with the complicated relationships among multiple variables in real-world problems.

Continuously Variable Rating: a new, simple and logical procedure to evaluate original scientific publications

PubMed Central

Silva, Mauricio Rocha e

2011-01-01

OBJECTIVE: Impact Factors (IF) are widely used surrogates to evaluate single articles, in spite of known shortcomings imposed by cite distribution skewness. We quantify this asymmetry and propose a simple computer-based procedure for evaluating individual articles. METHOD: (a) Analysis of symmetry. Journals clustered around nine Impact Factor points were selected from the medical “Subject Categories” in Journal Citation Reports 2010. Citable items published in 2008 were retrieved and ranked by granted citations over the Jan/2008 - Jun/2011 period. Frequency distribution of cites, normalized cumulative cites and absolute cites/decile were determined for each journal cluster. (b) Positive Predictive Value. Three arbitrarily established evaluation classes were generated: LOW (1.3≤IF<2.6); MID: (2.6≤IF<3.9); HIGH: (IF≥3.9). Positive Predictive Value for journal clusters within each class range was estimated. (c) Continuously Variable Rating. An alternative evaluation procedure is proposed to allow the rating of individually published articles in comparison to all articles published in the same journal within the same year of publication. The general guiding lines for the construction of a totally dedicated software program are delineated. RESULTS AND CONCLUSIONS: Skewness followed the Pareto Distribution for (1

Multipartite entanglement in three-mode Gaussian states of continuous-variable systems: Quantification, sharing structure, and decoherence

NASA Astrophysics Data System (ADS)

Adesso, Gerardo; Serafini, Alessio; Illuminati, Fabrizio

2006-03-01

We present a complete analysis of the multipartite entanglement of three-mode Gaussian states of continuous-variable systems. We derive standard forms which characterize the covariance matrix of pure and mixed three-mode Gaussian states up to local unitary operations, showing that the local entropies of pure Gaussian states are bound to fulfill a relationship which is stricter than the general Araki-Lieb inequality. Quantum correlations can be quantified by a proper convex roof extension of the squared logarithmic negativity, the continuous-variable tangle, or contangle. We review and elucidate in detail the proof that in multimode Gaussian states the contangle satisfies a monogamy inequality constraint [G. Adesso and F. Illuminati, New J. Phys8, 15 (2006)]. The residual contangle, emerging from the monogamy inequality, is an entanglement monotone under Gaussian local operations and classical communications and defines a measure of genuine tripartite entanglements. We determine the analytical expression of the residual contangle for arbitrary pure three-mode Gaussian states and study in detail the distribution of quantum correlations in such states. This analysis yields that pure, symmetric states allow for a promiscuous entanglement sharing, having both maximum tripartite entanglement and maximum couplewise entanglement between any pair of modes. We thus name these states GHZ/W states of continuous-variable systems because they are simultaneous continuous-variable counterparts of both the GHZ and the W states of three qubits. We finally consider the effect of decoherence on three-mode Gaussian states, studying the decay of the residual contangle. The GHZ/W states are shown to be maximally robust against losses and thermal noise.

Cluster Analysis of Velocity Field Derived from Dense GNSS Network of Japan

NASA Astrophysics Data System (ADS)

Takahashi, A.; Hashimoto, M.

2015-12-01

Dense GNSS networks have been widely used to observe crustal deformation. Simpson et al. (2012) and Savage and Simpson (2013) have conducted cluster analyses of GNSS velocity field in the San Francisco Bay Area and Mojave Desert, respectively. They have successfully found velocity discontinuities. They also showed an advantage of cluster analysis for classifying GNSS velocity field. Since in western United States, strike-slip events are dominant, geometry is simple. However, the Japanese Islands are tectonically complicated due to subduction of oceanic plates. There are many types of crustal deformation such as slow slip event and large postseismic deformation. We propose a modified clustering method of GNSS velocity field in Japan to separate time variant and static crustal deformation. Our modification is performing cluster analysis every several months or years, then qualifying cluster member similarity. If a GNSS station moved differently from its neighboring GNSS stations, the station will not belong to in the cluster which includes its surrounding stations. With this method, time variant phenomena were distinguished. We applied our method to GNSS data of Japan from 1996 to 2015. According to the analyses, following conclusions were derived. The first is the clusters boundaries are consistent with known active faults. For examples, the Arima-Takatsuki-Hanaore fault system and the Shimane-Tottori segment proposed by Nishimura (2015) are recognized, though without using prior information. The second is improving detectability of time variable phenomena, such as a slow slip event in northern part of Hokkaido region detected by Ohzono et al. (2015). The last one is the classification of postseismic deformation caused by large earthquakes. The result suggested velocity discontinuities in postseismic deformation of the Tohoku-oki earthquake. This result implies that postseismic deformation is not continuously decaying proportional to distance from its epicenter.

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.

Reliability Evaluation for Clustered WSNs under Malware Propagation

PubMed Central

Shen, Shigen; Huang, Longjun; Liu, Jianhua; Champion, Adam C.; Yu, Shui; Cao, Qiying

2016-01-01

We consider a clustered wireless sensor network (WSN) under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC) randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF) of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node’s MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN. PMID:27294934

Reliability Evaluation for Clustered WSNs under Malware Propagation.

PubMed

Shen, Shigen; Huang, Longjun; Liu, Jianhua; Champion, Adam C; Yu, Shui; Cao, Qiying

2016-06-10

We consider a clustered wireless sensor network (WSN) under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC) randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF) of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node's MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN.

Selection of key ambient particulate variables for epidemiological studies - applying cluster and heatmap analyses as tools for data reduction.

PubMed

Gu, Jianwei; Pitz, Mike; Breitner, Susanne; Birmili, Wolfram; von Klot, Stephanie; Schneider, Alexandra; Soentgen, Jens; Reller, Armin; Peters, Annette; Cyrys, Josef

2012-10-01

The success of epidemiological studies depends on the use of appropriate exposure variables. The purpose of this study is to extract a relatively small selection of variables characterizing ambient particulate matter from a large measurement data set. The original data set comprised a total of 96 particulate matter variables that have been continuously measured since 2004 at an urban background aerosol monitoring site in the city of Augsburg, Germany. Many of the original variables were derived from measured particle size distribution (PSD) across the particle diameter range 3 nm to 10 μm, including size-segregated particle number concentration, particle length concentration, particle surface concentration and particle mass concentration. The data set was complemented by integral aerosol variables. These variables were measured by independent instruments, including black carbon, sulfate, particle active surface concentration and particle length concentration. It is obvious that such a large number of measured variables cannot be used in health effect analyses simultaneously. The aim of this study is a pre-screening and a selection of the key variables that will be used as input in forthcoming epidemiological studies. In this study, we present two methods of parameter selection and apply them to data from a two-year period from 2007 to 2008. We used the agglomerative hierarchical cluster method to find groups of similar variables. In total, we selected 15 key variables from 9 clusters which are recommended for epidemiological analyses. We also applied a two-dimensional visualization technique called "heatmap" analysis to the Spearman correlation matrix. 12 key variables were selected using this method. Moreover, the positive matrix factorization (PMF) method was applied to the PSD data to characterize the possible particle sources. Correlations between the variables and PMF factors were used to interpret the meaning of the cluster and the heatmap analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

Different operational meanings of continuous variable Gaussian entanglement criteria and Bell inequalities

NASA Astrophysics Data System (ADS)

Buono, D.; Nocerino, G.; Solimeno, S.; Porzio, A.

2014-07-01

Entanglement, one of the most intriguing aspects of quantum mechanics, marks itself into different features of quantum states. For this reason different criteria can be used for verifying entanglement. In this paper we review some of the entanglement criteria casted for continuous variable states and link them to peculiar aspects of the original debate on the famous Einstein-Podolsky-Rosen (EPR) paradox. We also provide a useful expression for valuating Bell-type non-locality on Gaussian states. We also present the experimental measurement of a particular realization of the Bell operator over continuous variable entangled states produced by a sub-threshold type-II optical parametric oscillators (OPOs).

Multipartite entanglement in three-mode Gaussian states of continuous-variable systems: Quantification, sharing structure, and decoherence

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

Adesso, Gerardo; Centre for Quantum Computation, DAMTP, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA; Serafini, Alessio

2006-03-15

We present a complete analysis of the multipartite entanglement of three-mode Gaussian states of continuous-variable systems. We derive standard forms which characterize the covariance matrix of pure and mixed three-mode Gaussian states up to local unitary operations, showing that the local entropies of pure Gaussian states are bound to fulfill a relationship which is stricter than the general Araki-Lieb inequality. Quantum correlations can be quantified by a proper convex roof extension of the squared logarithmic negativity, the continuous-variable tangle, or contangle. We review and elucidate in detail the proof that in multimode Gaussian states the contangle satisfies a monogamy inequalitymore » constraint [G. Adesso and F. Illuminati, New J. Phys8, 15 (2006)]. The residual contangle, emerging from the monogamy inequality, is an entanglement monotone under Gaussian local operations and classical communications and defines a measure of genuine tripartite entanglements. We determine the analytical expression of the residual contangle for arbitrary pure three-mode Gaussian states and study in detail the distribution of quantum correlations in such states. This analysis yields that pure, symmetric states allow for a promiscuous entanglement sharing, having both maximum tripartite entanglement and maximum couplewise entanglement between any pair of modes. We thus name these states GHZ/W states of continuous-variable systems because they are simultaneous continuous-variable counterparts of both the GHZ and the W states of three qubits. We finally consider the effect of decoherence on three-mode Gaussian states, studying the decay of the residual contangle. The GHZ/W states are shown to be maximally robust against losses and thermal noise.« less

An application of cluster analysis for determining homogeneous subregions: The agroclimatological point of view. [Rio Grande do Sul, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Cappelletti, C. A.

1982-01-01

A stratification oriented to crop area and yield estimation problems was performed using an algorithm of clustering. The variables used were a set of agroclimatological characteristics measured in each one of the 232 municipalities of the State of Rio Grande do Sul, Brazil. A nonhierarchical cluster analysis was used and the pseudo F-statistics criterion was implemented for determining the "cut point" in the number of strata.

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.

Multifocal visual evoked potentials for early glaucoma detection.

PubMed

Weizer, Jennifer S; Musch, David C; Niziol, Leslie M; Khan, Naheed W

2012-07-01

To compare multifocal visual evoked potentials (mfVEP) with other detection methods in early open-angle glaucoma. Ten patients with suspected glaucoma and 5 with early open-angle glaucoma underwent mfVEP, standard automated perimetry (SAP), short-wave automated perimetry, frequency-doubling technology perimetry, and nerve fiber layer optical coherence tomography. Nineteen healthy control subjects underwent mfVEP and SAP for comparison. Comparisons between groups involving continuous variables were made using independent t tests; for categorical variables, Fisher's exact test was used. Monocular mfVEP cluster defects were associated with an increased SAP pattern standard deviation (P = .0195). Visual fields that showed interocular mfVEP cluster defects were more likely to also show superior quadrant nerve fiber layer thinning by OCT (P = .0152). Multifocal visual evoked potential cluster defects are associated with a functional and an anatomic measure that both relate to glaucomatous optic neuropathy. Copyright 2012, SLACK Incorporated.

Associations between Functional Milestones and Psychiatric Admissions in an Urban Area: Utility of a Cluster-Analytical Approach.

PubMed

Montemagni, Cristiana; Frieri, Tiziana; Villari, Vincenzo; Rocca, Paola

2018-06-01

The purpose of the study was to identify homogenous subgroups, based upon achievement of two functional milestones (marriage and employment) and Global Assessment of Functioning (GAF) score in a sample of 848 acute patients admitted to the Psychiatric Emergency Service (PES) of the Città della Salute e della Scienza di Torino, during a 24-months period. A two-step cluster-analysis, using GAF total score and the achievements in the two milestones as input data was performed. In order to examine whether the identified subgroups differed in external variables that were not included in the clustering process, and consequently to validate the found functional profiles, chi-square tests for categorical variables and analyses of variance (ANOVA) for continuous variables were performed. Five clusters were found. Employed patients (Clusters 4 and 5) had more years of education, less illness chronicity (shorter duration of illness and lower proportion of previous voluntary hospitalizations), lower use of mental health resources in the last year yet higher treatment adherence, larger network size, and higher ordinary discharge. Married inpatients (Clusters 3 and 5) had lower frequencies of substance abuse. The remarkably high rate of unemployment in this inpatients' sample, and the evidence of associations between unemployment and poorer functioning, argue for further research and development of evidence-based supported employment programs, that put forth diligent effort in helping people obtain work quickly and sustain; they may also help to reduce health care service use among that clientele.

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

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states.

PubMed

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

NASA Astrophysics Data System (ADS)

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

A stepwise-cluster microbial biomass inference model in food waste composting

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

Sun Wei; Huang, Guo H., E-mail: huangg@iseis.or; Chinese Research Academy of Environmental Science, North China Electric Power University, Beijing 100012-102206

2009-12-15

A stepwise-cluster microbial biomass inference (SMI) model was developed through introducing stepwise-cluster analysis (SCA) into composting process modeling to tackle the nonlinear relationships among state variables and microbial activities. The essence of SCA is to form a classification tree based on a series of cutting or mergence processes according to given statistical criteria. Eight runs of designed experiments in bench-scale reactors in a laboratory were constructed to demonstrate the feasibility of the proposed method. The results indicated that SMI could help establish a statistical relationship between state variables and composting microbial characteristics, where discrete and nonlinear complexities exist. Significance levelsmore » of cutting/merging were provided such that the accuracies of the developed forecasting trees were controllable. Through an attempted definition of input effects on the output in SMI, the effects of the state variables on thermophilic bacteria were ranged in a descending order as: Time (day) > moisture content (%) > ash content (%, dry) > Lower Temperature (deg. C) > pH > NH{sub 4}{sup +}-N (mg/Kg, dry) > Total N (%, dry) > Total C (%, dry); the effects on mesophilic bacteria were ordered as: Time > Upper Temperature (deg. C) > Total N > moisture content > NH{sub 4}{sup +}-N > Total C > pH. This study made the first attempt in applying SCA to mapping the nonlinear and discrete relationships in composting processes.« less

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

PubMed

McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Variable Stars in Large Magellanic Cloud Globular Clusters. II. NGC 1786

NASA Astrophysics Data System (ADS)

Kuehn, Charles A.; Smith, Horace A.; Catelan, Márcio; Pritzl, Barton J.; De Lee, Nathan; Borissova, Jura

2012-12-01

This is the second in a series of papers studying the variable stars in Large Magellanic Cloud globular clusters. The primary goal of this series is to study how RR Lyrae stars in Oosterhoff-intermediate systems compare to their counterparts in Oosterhoff I/II systems. In this paper, we present the results of our new time-series B-V photometric study of the globular cluster NGC 1786. A total of 65 variable stars were identified in our field of view. These variables include 53 RR Lyraes (27 RRab, 18 RRc, and 8 RRd), 3 classical Cepheids, 1 Type II Cepheid, 1 Anomalous Cepheid, 2 eclipsing binaries, 3 Delta Scuti/SX Phoenicis variables, and 2 variables of undetermined type. Photometric parameters for these variables are presented. We present physical properties for some of the RR Lyrae stars, derived from Fourier analysis of their light curves. We discuss several different indicators of Oosterhoff type which indicate that the Oosterhoff classification of NGC 1786 is not as clear cut as what is seen in most globular clusters. Based on observations taken with the SMARTS 1.3 m telescope operated by the SMARTS Consortium and observations taken at the Southern Astrophysical Research (SOAR) telescope, which is a joint project of the Ministério da Ciência, Tecnologia, e Inovação (MCTI) da República Federativa do Brasil, the U.S. National Optical Astronomy Observatory (NOAO), the University of North Carolina at Chapel Hill (UNC), and Michigan State University (MSU).

Cardiac surgery report cards: comprehensive review and statistical critique.

PubMed

Shahian, D M; Normand, S L; Torchiana, D F; Lewis, S M; Pastore, J O; Kuntz, R E; Dreyer, P I

2001-12-01

Public report cards and confidential, collaborative peer education represent distinctly different approaches to cardiac surgery quality assessment and improvement. This review discusses the controversies regarding their methodology and relative effectiveness. Report cards have been the more commonly used approach, typically as a result of state legislation. They are based on the presumption that publication of outcomes effectively motivates providers, and that market forces will reward higher quality. Numerous studies have challenged the validity of these hypotheses. Furthermore, although states with report cards have reported significant decreases in risk-adjusted mortality, it is unclear whether this improvement resulted from public disclosure or, rather, from the development of internal quality programs by hospitals. An additional confounding factor is the nationwide decline in heart surgery mortality, including states without quality monitoring. Finally, report cards may engender negative behaviors such as high-risk case avoidance and "gaming" of the reporting system, especially if individual surgeon results are published. The alternative approach, continuous quality improvement, may provide an opportunity to enhance performance and reduce interprovider variability while avoiding the unintended negative consequences of report cards. This collaborative method, which uses exchange visits between programs and determination of best practice, has been highly effective in northern New England and in the Veterans Affairs Administration. However, despite their potential advantages, quality programs based solely on confidential continuous quality improvement do not address the issue of public accountability. For this reason, some states may continue to mandate report cards. In such instances, it is imperative that appropriate statistical techniques and report formats are used, and that professional organizations simultaneously implement continuous quality improvement programs. The statistical methodology underlying current report cards is flawed, and does not justify the degree of accuracy presented to the public. All existing risk-adjustment methods have substantial inherent imprecision, and this is compounded when the results of such patient-level models are aggregated and used inappropriately to assess provider performance. Specific problems include sample size differences, clustering of observations, multiple comparisons, and failure to account for the random component of interprovider variability. We advocate the use of hierarchical or multilevel statistical models to address these concerns, as well as report formats that emphasize the statistical uncertainty of the results.

Comparing Perceived Adequacy of Help Received Among Different Classes of Individuals with Severe Mental Disorders at Five-Year Follow-Up: A Longitudinal Cluster Analysis.

PubMed

Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie

2017-11-13

This study developed a typology describing change in the perceived adequacy of help received among 204 individuals with severe mental disorders, 5 years after transfer to the community following a major mental health reform in Quebec (Canada). Participant typologies were constructed using a two-step cluster analysis. There were significant differences between T0 and T2 for perceived adequacy of help received and other independent variables, including seriousness of needs, help from services or relatives, and care continuity. Five classes emerged from the analysis. Perceived adequacy of help received at T2 increased for Class 1, mainly comprised of older women with mood disorders. Overall, greater care continuity and levels of help from services and relatives related to higher perceived AHR. Changes in perceived adequacy of help received resulting from several combinations of associated variables indicate that MH service delivery should respond to specific profiles and determinants.

Peeking Network States with Clustered Patterns

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

Kim, Jinoh; Sim, Alex

2015-10-20

Network traffic monitoring has long been a core element for effec- tive network management and security. However, it is still a chal- lenging task with a high degree of complexity for comprehensive analysis when considering multiple variables and ever-increasing traffic volumes to monitor. For example, one of the widely con- sidered approaches is to scrutinize probabilistic distributions, but it poses a scalability concern and multivariate analysis is not gen- erally supported due to the exponential increase of the complexity. In this work, we propose a novel method for network traffic moni- toring based on clustering, one of the powerful deep-learningmore » tech- niques. We show that the new approach enables us to recognize clustered results as patterns representing the network states, which can then be utilized to evaluate “similarity” of network states over time. In addition, we define a new quantitative measure for the similarity between two compared network states observed in dif- ferent time windows, as a supportive means for intuitive analysis. Finally, we demonstrate the clustering-based network monitoring with public traffic traces, and show that the proposed approach us- ing the clustering method has a great opportunity for feasible, cost- effective network monitoring.« less

Practical limitation for continuous-variable quantum cryptography using coherent States.

PubMed

Namiki, Ryo; Hirano, Takuya

2004-03-19

In this Letter, first, we investigate the security of a continuous-variable quantum cryptographic scheme with a postselection process against individual beam splitting attack. It is shown that the scheme can be secure in the presence of the transmission loss owing to the postselection. Second, we provide a loss limit for continuous-variable quantum cryptography using coherent states taking into account excess Gaussian noise on quadrature distribution. Since the excess noise is reduced by the loss mechanism, a realistic intercept-resend attack which makes a Gaussian mixture of coherent states gives a loss limit in the presence of any excess Gaussian noise.

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.

Satisfying the Einstein-Podolsky-Rosen criterion with massive particles

NASA Astrophysics Data System (ADS)

Peise, J.; Kruse, I.; Lange, K.; Lücke, B.; Pezzè, L.; Arlt, J.; Ertmer, W.; Hammerer, K.; Santos, L.; Smerzi, A.; Klempt, C.

2016-03-01

In 1935, Einstein, Podolsky and Rosen (EPR) questioned the completeness of quantum mechanics by devising a quantum state of two massive particles with maximally correlated space and momentum coordinates. The EPR criterion qualifies such continuous-variable entangled states, as shown successfully with light fields. Here, we report on the production of massive particles which meet the EPR criterion for continuous phase/amplitude variables. The created quantum state of ultracold atoms shows an EPR parameter of 0.18(3), which is 2.4 standard deviations below the threshold of 1/4. Our state presents a resource for tests of quantum nonlocality with massive particles and a wide variety of applications in the field of continuous-variable quantum information and metrology.

Extremal entanglement and mixedness in continuous variable systems

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

Adesso, Gerardo; Serafini, Alessio; Illuminati, Fabrizio

2004-08-01

We investigate the relationship between mixedness and entanglement for Gaussian states of continuous variable systems. We introduce generalized entropies based on Schatten p norms to quantify the mixedness of a state and derive their explicit expressions in terms of symplectic spectra. We compare the hierarchies of mixedness provided by such measures with the one provided by the purity (defined as tr {rho}{sup 2} for the state {rho}) for generic n-mode states. We then review the analysis proving the existence of both maximally and minimally entangled states at given global and marginal purities, with the entanglement quantified by the logarithmic negativity.more » Based on these results, we extend such an analysis to generalized entropies, introducing and fully characterizing maximally and minimally entangled states for given global and local generalized entropies. We compare the different roles played by the purity and by the generalized p entropies in quantifying the entanglement and the mixedness of continuous variable systems. We introduce the concept of average logarithmic negativity, showing that it allows a reliable quantitative estimate of continuous variable entanglement by direct measurements of global and marginal generalized p entropies.« less

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

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

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field ismore » chaotic. We argue that this second type of behavior is “extensive” in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.« less

Pre-Deployment Stress, Mental Health, and Help-Seeking Behaviors Among Marines

DTIC Science & Technology

2014-01-01

associations between two categori- cal variables, and Wald tests were conducted to compare mean scores on continuous variables across groups (e.g...Cluster- adjusted wald tests were conducted to determine whether there were significant differences by rank on the average number of potentially...deployed to Iraq or Afghanistan in 2010 or 2011 of rank O6 or lower. a Omnibus rao-Scott chi-square test or adjusted wald test is statistically

Geographical variation of cerebrovascular disease in New York State: the correlation with income

PubMed Central

Han, Daikwon; Carrow, Shannon S; Rogerson, Peter A; Munschauer, Frederick E

2005-01-01

Background Income is known to be associated with cerebrovascular disease; however, little is known about the more detailed relationship between cerebrovascular disease and income. We examined the hypothesis that the geographical distribution of cerebrovascular disease in New York State may be predicted by a nonlinear model using income as a surrogate socioeconomic risk factor. Results We used spatial clustering methods to identify areas with high and low prevalence of cerebrovascular disease at the ZIP code level after smoothing rates and correcting for edge effects; geographic locations of high and low clusters of cerebrovascular disease in New York State were identified with and without income adjustment. To examine effects of income, we calculated the excess number of cases using a non-linear regression with cerebrovascular disease rates taken as the dependent variable and income and income squared taken as independent variables. The resulting regression equation was: excess rate = 32.075 - 1.22*10-4(income) + 8.068*10-10(income2), and both income and income squared variables were significant at the 0.01 level. When income was included as a covariate in the non-linear regression, the number and size of clusters of high cerebrovascular disease prevalence decreased. Some 87 ZIP codes exceeded the critical value of the local statistic yielding a relative risk of 1.2. The majority of low cerebrovascular disease prevalence geographic clusters disappeared when the non-linear income effect was included. For linear regression, the excess rate of cerebrovascular disease falls with income; each $10,000 increase in median income of each ZIP code resulted in an average reduction of 3.83 observed cases. The significant nonlinear effect indicates a lessening of this income effect with increasing income. Conclusion Income is a non-linear predictor of excess cerebrovascular disease rates, with both low and high observed cerebrovascular disease rate areas associated with higher income. Income alone explains a significant amount of the geographical variance in cerebrovascular disease across New York State since both high and low clusters of cerebrovascular disease dissipate or disappear with income adjustment. Geographical modeling, including non-linear effects of income, may allow for better identification of other non-traditional risk factors. PMID:16242043

A Hierarchical Framework for State-Space Matrix Inference and Clustering.

PubMed

Zuo, Chandler; Chen, Kailei; Hewitt, Kyle J; Bresnick, Emery H; Keleş, Sündüz

2016-09-01

In recent years, a large number of genomic and epigenomic studies have been focusing on the integrative analysis of multiple experimental datasets measured over a large number of observational units. The objectives of such studies include not only inferring a hidden state of activity for each unit over individual experiments, but also detecting highly associated clusters of units based on their inferred states. Although there are a number of methods tailored for specific datasets, there is currently no state-of-the-art modeling framework for this general class of problems. In this paper, we develop the MBASIC ( M atrix B ased A nalysis for S tate-space I nference and C lustering) framework. MBASIC consists of two parts: state-space mapping and state-space clustering. In state-space mapping, it maps observations onto a finite state-space, representing the activation states of units across conditions. In state-space clustering, MBASIC incorporates a finite mixture model to cluster the units based on their inferred state-space profiles across all conditions. Both the state-space mapping and clustering can be simultaneously estimated through an Expectation-Maximization algorithm. MBASIC flexibly adapts to a large number of parametric distributions for the observed data, as well as the heterogeneity in replicate experiments. It allows for imposing structural assumptions on each cluster, and enables model selection using information criterion. In our data-driven simulation studies, MBASIC showed significant accuracy in recovering both the underlying state-space variables and clustering structures. We applied MBASIC to two genome research problems using large numbers of datasets from the ENCODE project. The first application grouped genes based on transcription factor occupancy profiles of their promoter regions in two different cell types. The second application focused on identifying groups of loci that are similar to a GATA2 binding site that is functional at its endogenous locus by utilizing transcription factor occupancy data and illustrated applicability of MBASIC in a wide variety of problems. In both studies, MBASIC showed higher levels of raw data fidelity than analyzing these data with a two-step approach using ENCODE results on transcription factor occupancy data.

What Is PG-TRAK90? An Introduction to PGCC's Lifestyle Cluster System for Student Recruitment Targeting and Enrollment Analysis. Market Analysis MA94-1.

ERIC Educational Resources Information Center

Boughan, Karl

PG-TRAK90 is a cluster-based geographic marketing system designed by Maryland's Prince George's Community College (PGCC) to maximize educational marketing objectives. To create it, United States Census Bureau files containing over 200 demographic, housing, and lifecycle variables for 172 tracts in Prince George County (PGC) were reformatted into…

Operational quantification of continuous-variable correlations.

PubMed

Rodó, Carles; Adesso, Gerardo; Sanpera, Anna

2008-03-21

We quantify correlations (quantum and/or classical) between two continuous-variable modes as the maximal number of correlated bits extracted via local quadrature measurements. On Gaussian states, such "bit quadrature correlations" majorize entanglement, reducing to an entanglement monotone for pure states. For non-Gaussian states, such as photonic Bell states, photon-subtracted states, and mixtures of Gaussian states, the bit correlations are shown to be a monotonic function of the negativity. This quantification yields a feasible, operational way to measure non-Gaussian entanglement in current experiments by means of direct homodyne detection, without a complete state tomography.

Generalized quantum kinetic expansion: Higher-order corrections to multichromophoric Förster theory

NASA Astrophysics Data System (ADS)

Wu, Jianlan; Gong, Zhihao; Tang, Zhoufei

2015-08-01

For a general two-cluster energy transfer network, a new methodology of the generalized quantum kinetic expansion (GQKE) method is developed, which predicts an exact time-convolution equation for the cluster population evolution under the initial condition of the local cluster equilibrium state. The cluster-to-cluster rate kernel is expanded over the inter-cluster couplings. The lowest second-order GQKE rate recovers the multichromophoric Förster theory (MCFT) rate. The higher-order corrections to the MCFT rate are systematically included using the continued fraction resummation form, resulting in the resummed GQKE method. The reliability of the GQKE methodology is verified in two model systems, revealing the relevance of higher-order corrections.

Tunability of the circadian action of tetrachromatic solid-state light sources

NASA Astrophysics Data System (ADS)

Žukauskas, A.; Vaicekauskas, R.

2015-01-01

An approach to the optimization of the spectral power distribution of solid-state light sources with the tunable non-image forming photobiological effect on the human circadian rhythm is proposed. For tetrachromatic clusters of model narrow-band (direct-emission) light-emitting diodes (LEDs), the limiting tunability of the circadian action factor (CAF), which is the ratio of the circadian efficacy to luminous efficacy of radiation, was established as a function of constraining color fidelity and luminous efficacy of radiation. For constant correlated color temperatures (CCTs), the CAF of the LED clusters can be tuned above and below that of the corresponding blackbody radiators, whereas for variable CCT, the clusters can have circadian tunability covering that of a temperature-tunable blackbody radiator.

Teleportation of Two-Mode Quantum State of Continuous Variables

NASA Astrophysics Data System (ADS)

Song, Tong-Qiang

2004-03-01

Using two Einstein-Podolsky-Rosen pair eigenstates |η> as quantum channels, we study the teleportation of two-mode quantum state of continuous variables. The project supported by Natural Science Foundation of Zhejiang Province of China and Open Foundation of Laboratory of High-Intensity Optics, Shanghai Institute of Optics and Fine Mechanics

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.

Quantum error correction of continuous-variable states against Gaussian noise

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

Ralph, T. C.

2011-08-15

We describe a continuous-variable error correction protocol that can correct the Gaussian noise induced by linear loss on Gaussian states. The protocol can be implemented using linear optics and photon counting. We explore the theoretical bounds of the protocol as well as the expected performance given current knowledge and technology.

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures

PubMed Central

Chen, Yun; Yang, Hui

2016-01-01

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering. PMID:27966581

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures.

PubMed

Chen, Yun; Yang, Hui

2016-12-14

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering.

Cancer clusters in the USA: What do the last twenty years of state and federal investigations tell us?

PubMed Central

Goodman, Michael; Naiman, Joshua S.; Goodman, Dina; LaKind, Judy S.

2012-01-01

Background Cancer clusters garner considerable public and legislative attention, and there is often an expectation that cluster investigations in a community will reveal a causal link to an environmental exposure. At a 1989 national conference on disease clusters, it was reported that cluster studies conducted in the 1970s and 1980s rarely, if ever, produced important findings. We seek to answer the question: Have cancer cluster investigations conducted by US health agencies in the past 20 years improved our understanding of cancer etiology, or informed cancer prevention and control? Methods We reviewed publicly available cancer cluster investigation reports since 1990, obtained from literature searches and by canvassing all 50 states and the District of Columbia. Investigations were categorized with respect to cancer type(s), hypothesized exposure, whether perceived clusters were confirmed (e.g. by elevated incidence), and conclusions about a link between cancer(s) of concern and hypothesized environmental exposure(s). Results We reviewed 428 investigations evaluating 567 cancers of concern. An increase in incidence was confirmed for 72 (13%) cancer categories (including the category “all sites”). Three of those were linked (with variable degree of certainty) to hypothesized exposures, but only one investigation revealed a clear cause. Conclusions It is fair to state that extensive efforts to find causes of community cancer clusters have not been successful. There are fundamental shortcomings to our current methods of investigating community cancer clusters. We recommend a multidisciplinary national dialogue on creative, innovative approaches to understanding when and why cancer and other chronic diseases cluster in space and time. PMID:22519802

Quantum Teamwork for Unconditional Multiparty Communication with Gaussian States

NASA Astrophysics Data System (ADS)

Zhang, Jing; Adesso, Gerardo; Xie, Changde; Peng, Kunchi

2009-08-01

We demonstrate the capability of continuous variable Gaussian states to communicate multipartite quantum information. A quantum teamwork protocol is presented according to which an arbitrary possibly entangled multimode state can be faithfully teleported between two teams each comprising many cooperative users. We prove that N-mode Gaussian weighted graph states exist for arbitrary N that enable unconditional quantum teamwork implementations for any arrangement of the teams. These perfect continuous variable maximally multipartite entangled resources are typical among pure Gaussian states and are unaffected by the entanglement frustration occurring in multiqubit states.

A comparative analysis of clustering algorithms: O{sub 2} migration in truncated hemoglobin I from transition networks

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

Cazade, Pierre-André; Berezovska, Ganna; Meuwly, Markus, E-mail: m.meuwly@unibas.ch

2015-01-14

The ligand migration network for O{sub 2}–diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k–means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of themore » major differences between k–means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ.« less

A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks.

PubMed

Cazade, Pierre-André; Zheng, Wenwei; Prada-Gracia, Diego; Berezovska, Ganna; Rao, Francesco; Clementi, Cecilia; Meuwly, Markus

2015-01-14

The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ.

Clustering of Variables for Mixed Data

NASA Astrophysics Data System (ADS)

Saracco, J.; Chavent, M.

2016-05-01

This chapter presents clustering of variables which aim is to lump together strongly related variables. The proposed approach works on a mixed data set, i.e. on a data set which contains numerical variables and categorical variables. Two algorithms of clustering of variables are described: a hierarchical clustering and a k-means type clustering. A brief description of PCAmix method (that is a principal component analysis for mixed data) is provided, since the calculus of the synthetic variables summarizing the obtained clusters of variables is based on this multivariate method. Finally, the R packages ClustOfVar and PCAmixdata are illustrated on real mixed data. The PCAmix and ClustOfVar approaches are first used for dimension reduction (step 1) before applying in step 2 a standard clustering method to obtain groups of individuals.

Continuous-variable quantum teleportation with non-Gaussian resources

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

Dell'Anno, F.; Dipartimento di Fisica, Universita degli Studi di Salerno, Via S. Allende, I-84081 Baronissi; CNR-INFM Coherentia, Napoli, Italy and CNISM Unita di Salerno and INFN Sezione di Napoli, Gruppo Collegato di Salerno, Baronissi

2007-08-15

We investigate continuous variable quantum teleportation using non-Gaussian states of the radiation field as entangled resources. We compare the performance of different classes of degaussified resources, including two-mode photon-added and two-mode photon-subtracted squeezed states. We then introduce a class of two-mode squeezed Bell-like states with one-parameter dependence for optimization. These states interpolate between and include as subcases different classes of degaussified resources. We show that optimized squeezed Bell-like resources yield a remarkable improvement in the fidelity of teleportation both for coherent and nonclassical input states. The investigation reveals that the optimal non-Gaussian resources for continuous variable teleportation are those thatmore » most closely realize the simultaneous maximization of the content of entanglement, the degree of affinity with the two-mode squeezed vacuum, and the, suitably measured, amount of non-Gaussianity.« less

Satisfying the Einstein–Podolsky–Rosen criterion with massive particles

PubMed Central

Peise, J.; Kruse, I.; Lange, K.; Lücke, B.; Pezzè, L.; Arlt, J.; Ertmer, W.; Hammerer, K.; Santos, L.; Smerzi, A.; Klempt, C.

2015-01-01

In 1935, Einstein, Podolsky and Rosen (EPR) questioned the completeness of quantum mechanics by devising a quantum state of two massive particles with maximally correlated space and momentum coordinates. The EPR criterion qualifies such continuous-variable entangled states, where a measurement of one subsystem seemingly allows for a prediction of the second subsystem beyond the Heisenberg uncertainty relation. Up to now, continuous-variable EPR correlations have only been created with photons, while the demonstration of such strongly correlated states with massive particles is still outstanding. Here we report on the creation of an EPR-correlated two-mode squeezed state in an ultracold atomic ensemble. The state shows an EPR entanglement parameter of 0.18(3), which is 2.4 s.d. below the threshold 1/4 of the EPR criterion. We also present a full tomographic reconstruction of the underlying many-particle quantum state. The state presents a resource for tests of quantum nonlocality and a wide variety of applications in the field of continuous-variable quantum information and metrology. PMID:26612105

Satisfying the Einstein-Podolsky-Rosen criterion with massive particles.

PubMed

Peise, J; Kruse, I; Lange, K; Lücke, B; Pezzè, L; Arlt, J; Ertmer, W; Hammerer, K; Santos, L; Smerzi, A; Klempt, C

2015-11-27

In 1935, Einstein, Podolsky and Rosen (EPR) questioned the completeness of quantum mechanics by devising a quantum state of two massive particles with maximally correlated space and momentum coordinates. The EPR criterion qualifies such continuous-variable entangled states, where a measurement of one subsystem seemingly allows for a prediction of the second subsystem beyond the Heisenberg uncertainty relation. Up to now, continuous-variable EPR correlations have only been created with photons, while the demonstration of such strongly correlated states with massive particles is still outstanding. Here we report on the creation of an EPR-correlated two-mode squeezed state in an ultracold atomic ensemble. The state shows an EPR entanglement parameter of 0.18(3), which is 2.4 s.d. below the threshold 1/4 of the EPR criterion. We also present a full tomographic reconstruction of the underlying many-particle quantum state. The state presents a resource for tests of quantum nonlocality and a wide variety of applications in the field of continuous-variable quantum information and metrology.

Satisfying the Einstein-Podolsky-Rosen criterion with massive particles

NASA Astrophysics Data System (ADS)

Peise, J.; Kruse, I.; Lange, K.; Lücke, B.; Pezzè, L.; Arlt, J.; Ertmer, W.; Hammerer, K.; Santos, L.; Smerzi, A.; Klempt, C.

2015-11-01

In 1935, Einstein, Podolsky and Rosen (EPR) questioned the completeness of quantum mechanics by devising a quantum state of two massive particles with maximally correlated space and momentum coordinates. The EPR criterion qualifies such continuous-variable entangled states, where a measurement of one subsystem seemingly allows for a prediction of the second subsystem beyond the Heisenberg uncertainty relation. Up to now, continuous-variable EPR correlations have only been created with photons, while the demonstration of such strongly correlated states with massive particles is still outstanding. Here we report on the creation of an EPR-correlated two-mode squeezed state in an ultracold atomic ensemble. The state shows an EPR entanglement parameter of 0.18(3), which is 2.4 s.d. below the threshold 1/4 of the EPR criterion. We also present a full tomographic reconstruction of the underlying many-particle quantum state. The state presents a resource for tests of quantum nonlocality and a wide variety of applications in the field of continuous-variable quantum information and metrology.

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

Socio-economic and environmental effects influencing the development of leprosy in Bahia, north-eastern Brazil.

PubMed

Cabral-Miranda, William; Chiaravalloti Neto, Francisco; Barrozo, Ligia V

2014-12-01

To investigate spatial clusters and possible associations between relative risks of leprosy with socio-economic and environmental factors, taking into account diagnosed cases in children under 15 years old. An ecological study was conceived using data aggregated by municipality to identify possible spatial clusters of leprosy from 2005 to 2011. Relative risks were calculated accounting for the respective covariate gender. The second stage of the analysis consisted of verifying possible associations between the relative risks of leprosy as a dependent variable, and socio-economic and environmental variables as independent. This was performed using a multivariate regression analysis according to a previously defined conceptual framework. Overall rates have decreased from 0.88/10 000 in 2005 to 0.52 in 2011. Spatial scan statistics identified 4 high-risk and 6 low-risk clusters. In the regression model, after allowing for spatial dependence, relative risks were associated with higher percentage of water bodies, higher Gini index, higher percentage of urban population, larger average number of dwellers by permanent residence and smaller percentage of residents born in Bahia. Although relative risks of leprosy in Bahia have been decreasing, they remain very high. The association between relative risks of leprosy and water bodies in the proposed geographic scale indicates that hypothesis linking M. leprae and humid environments cannot be discarded. Socio-economic conditions such as inequality, a greater number of dwellers by residence and migration are derived from the urbanisation process carried out in this State. Precarious settlements and poor living conditions in the cities would favour the continuity of leprosy transmission. © 2014 John Wiley & Sons Ltd.

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

Equivalence between entanglement and the optimal fidelity of continuous variable teleportation.

PubMed

Adesso, Gerardo; Illuminati, Fabrizio

2005-10-07

We devise the optimal form of Gaussian resource states enabling continuous-variable teleportation with maximal fidelity. We show that a nonclassical optimal fidelity of N-user teleportation networks is necessary and sufficient for N-party entangled Gaussian resources, yielding an estimator of multipartite entanglement. The entanglement of teleportation is equivalent to the entanglement of formation in a two-user protocol, and to the localizable entanglement in a multiuser one. Finally, we show that the continuous-variable tangle, quantifying entanglement sharing in three-mode Gaussian states, is defined operationally in terms of the optimal fidelity of a tripartite teleportation network.

Employment relations and global health: a typological study of world labor markets.

PubMed

Chung, Haejoo; Muntaner, Carles; Benach, Joan

2010-01-01

In this study, the authors investigate the global labor market and employment relations, which are central building blocks of the welfare state; the aim is to propose a global typology of labor markets to explain global inequalities in population health. Countries are categorized into core (21), semi-peripheral (42), and peripheral (71) countries, based on gross national product per capita (Atlas method). Labor market-related variables and factors are then used to generate clusters of countries with principal components and cluster analysis methods. The authors then examine the relationship between the resulting clusters and health outcomes. The clusters of countries are largely geographically defined, each cluster with similar historical background and developmental strategy. However, there are interesting exceptions, which warrant further elaboration. The relationship between health outcomes and clusters largely follows the authors' expectations (except for communicable diseases): more egalitarian labor institutions have better health outcomes. The world system, then, can be divided according to different types of labor markets that are predictive of population health outcomes at each level of economic development. As is the case for health and social policies, variability in labor market characteristics is likely to reflect, in part, the relative strength of a country's political actors.

Teleportation of a Kind of Three-Mode Entangled States of Continuous Variables

NASA Astrophysics Data System (ADS)

Fan, Hong-Yi; Liang, Xian-Ting

2005-11-01

A quantum teleportation scheme to teleport a kind of tripartite entangled states of continuous variables by using a quantum channel composed of three bipartite entangled states is proposed. The joint Bell measurement is feasible because the bipartite entangled states are complete and the squeezed state has a natural representation in the entangled state basis. The calculation is greatly simplified by using the Schmidt decomposition of the entangled states. The project supported by the President Funds of the Chinese Academy of Sciences and National Natural Science Foundation of China under Grant No. 10475056

Composable security proof for continuous-variable quantum key distribution with coherent States.

PubMed

Leverrier, Anthony

2015-02-20

We give the first composable security proof for continuous-variable quantum key distribution with coherent states against collective attacks. Crucially, in the limit of large blocks the secret key rate converges to the usual value computed from the Holevo bound. Combining our proof with either the de Finetti theorem or the postselection technique then shows the security of the protocol against general attacks, thereby confirming the long-standing conjecture that Gaussian attacks are optimal asymptotically in the composable security framework. We expect that our parameter estimation procedure, which does not rely on any assumption about the quantum state being measured, will find applications elsewhere, for instance, for the reliable quantification of continuous-variable entanglement in finite-size settings.

Continuous-variable quantum key distribution with a leakage from state preparation

NASA Astrophysics Data System (ADS)

Derkach, Ivan; Usenko, Vladyslav C.; Filip, Radim

2017-12-01

We address side-channel leakage in a trusted preparation station of continuous-variable quantum key distribution with coherent and squeezed states. We consider two different scenarios: multimode Gaussian modulation, directly accessible to an eavesdropper, or side-channel loss of the signal states prior to the modulation stage. We show the negative impact of excessive modulation on both the coherent- and squeezed-state protocols. The impact is more pronounced for squeezed-state protocols and may require optimization of squeezing in the case of noisy quantum channels. Further, we demonstrate that the coherent-state protocol is immune to side-channel signal state leakage prior to modulation, while the squeezed-state protocol is vulnerable to such attacks, becoming more sensitive to the noise in the channel. In the general case of noisy quantum channels the signal squeezing can be optimized to provide best performance of the protocol in the presence of side-channel leakage prior to modulation. Our results demonstrate that leakage from the trusted source in continuous-variable quantum key distribution should not be underestimated and squeezing optimization is needed to overcome coherent state protocols.

Robust and compact entanglement generation from diode-laser-pumped four-wave mixing

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

Lawrie, B. J.; Yang, Y.; Eaton, M.

Four-wave-mixing processes are now routinely used to demonstrate multi-spatial-mode Einstein- Podolsky-Rosen entanglement and intensity difference squeezing. Recently, diode-laser-pumped four-wave mixing processes have been shown to provide an affordable, compact, and stable source for intensity difference squeezing, but it was unknown if excess phase noise present in power amplifier pump configurations would be an impediment to achieving quadrature entanglement. Here, we demonstrate the operating regimes under which these systems are capable of producing entanglement and under which excess phase noise produced by the amplifier contaminates the output state. We show that Einstein-Podolsky-Rosen entanglement in two mode squeezed states can be generatedmore » by a four-wave-mixing source deriving both the pump field and the local oscillators from a tapered-amplifier diode-laser. In conclusion, this robust continuous variable entanglement source is highly scalable and amenable to miniaturization, making it a critical step toward the development of integrated quantum sensors and scalable quantum information processors, such as spatial comb cluster states.« less

Robust and compact entanglement generation from diode-laser-pumped four-wave mixing

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

Lawrie, B. J., E-mail: lawriebj@ornl.gov; Pooser, R. C.; Yang, Y.

Four-wave-mixing processes are now routinely used to demonstrate multi-spatial-mode Einstein-Podolsky-Rosen entanglement and intensity difference squeezing. Diode-laser-pumped four-wave mixing processes have recently been shown to provide an affordable, compact, and stable source for intensity difference squeezing, but it was unknown if excess phase noise present in power amplifier pump configurations would be an impediment to achieving quadrature entanglement. Here, we demonstrate the operating regimes under which these systems are capable of producing entanglement and under which excess phase noise produced by the amplifier contaminates the output state. We show that Einstein-Podolsky-Rosen entanglement in two mode squeezed states can be generated bymore » a four-wave-mixing source deriving both the pump field and the local oscillators from a tapered-amplifier diode-laser. This robust continuous variable entanglement source is highly scalable and amenable to miniaturization, making it a critical step toward the development of integrated quantum sensors and scalable quantum information processors, such as spatial comb cluster states.« less

Robust and compact entanglement generation from diode-laser-pumped four-wave mixing

DOE PAGES

Lawrie, B. J.; Yang, Y.; Eaton, M.; ...

2016-04-11

Four-wave-mixing processes are now routinely used to demonstrate multi-spatial-mode Einstein- Podolsky-Rosen entanglement and intensity difference squeezing. Recently, diode-laser-pumped four-wave mixing processes have been shown to provide an affordable, compact, and stable source for intensity difference squeezing, but it was unknown if excess phase noise present in power amplifier pump configurations would be an impediment to achieving quadrature entanglement. Here, we demonstrate the operating regimes under which these systems are capable of producing entanglement and under which excess phase noise produced by the amplifier contaminates the output state. We show that Einstein-Podolsky-Rosen entanglement in two mode squeezed states can be generatedmore » by a four-wave-mixing source deriving both the pump field and the local oscillators from a tapered-amplifier diode-laser. In conclusion, this robust continuous variable entanglement source is highly scalable and amenable to miniaturization, making it a critical step toward the development of integrated quantum sensors and scalable quantum information processors, such as spatial comb cluster states.« less

Common Variable Immunodeficiency Non-Infectious Disease Endotypes Redefined Using Unbiased Network Clustering in Large Electronic Datasets.

PubMed

Farmer, Jocelyn R; Ong, Mei-Sing; Barmettler, Sara; Yonker, Lael M; Fuleihan, Ramsay; Sullivan, Kathleen E; Cunningham-Rundles, Charlotte; Walter, Jolan E

2017-01-01

Common variable immunodeficiency (CVID) is increasingly recognized for its association with autoimmune and inflammatory complications. Despite recent advances in immunophenotypic and genetic discovery, clinical care of CVID remains limited by our inability to accurately model risk for non-infectious disease development. Herein, we demonstrate the utility of unbiased network clustering as a novel method to analyze inter-relationships between non-infectious disease outcomes in CVID using databases at the United States Immunodeficiency Network (USIDNET), the centralized immunodeficiency registry of the United States, and Partners, a tertiary care network in Boston, MA, USA, with a shared electronic medical record amenable to natural language processing. Immunophenotypes were comparable in terms of native antibody deficiencies, low titer response to pneumococcus, and B cell maturation arrest. However, recorded non-infectious disease outcomes were more substantial in the Partners cohort across the spectrum of lymphoproliferation, cytopenias, autoimmunity, atopy, and malignancy. Using unbiased network clustering to analyze 34 non-infectious disease outcomes in the Partners cohort, we further identified unique patterns of lymphoproliferative (two clusters), autoimmune (two clusters), and atopic (one cluster) disease that were defined as CVID non-infectious endotypes according to discrete and non-overlapping immunophenotypes. Markers were both previously described {high serum IgE in the atopic cluster [odds ratio (OR) 6.5] and low class-switched memory B cells in the total lymphoproliferative cluster (OR 9.2)} and novel [low serum C3 in the total lymphoproliferative cluster (OR 5.1)]. Mortality risk in the Partners cohort was significantly associated with individual non-infectious disease outcomes as well as lymphoproliferative cluster 2, specifically (OR 5.9). In contrast, unbiased network clustering failed to associate known comorbidities in the adult USIDNET cohort. Together, these data suggest that unbiased network clustering can be used in CVID to redefine non-infectious disease inter-relationships; however, applicability may be limited to datasets well annotated through mechanisms such as natural language processing. The lymphoproliferative, autoimmune, and atopic Partners CVID endotypes herein described can be used moving forward to streamline genetic and biomarker discovery and to facilitate early screening and intervention in CVID patients at highest risk for autoimmune and inflammatory progression.

The electronic structure of Au25 clusters: between discrete and continuous.

PubMed

Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Sai Krishna, Katla; Li, Ruipeng; Mei, Wai-Ning; Skrabalak, Sara E; Kumar, Challa S S R; Losovyj, Yaroslav

2016-08-21

Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies.

The Reactivity and Structure of Size Selected VxO y Clusters on a TiO2 (110)-(1 X 1) Surface of Variable Oxidation State

NASA Astrophysics Data System (ADS)

Neilson, Hunter L.

The Reactivity and Structure of Size Selected VxOy Clusters on a TiO2 (110) Surface of Variable Oxidation State by Hunter L Neilson The selective oxidative dehydrogenation of methanol by vanadium oxide/TiO2 model systems has received a great deal of interest in the surface science community. Previous studies using temperature programmed desorption and reaction (TPD/R) to probe the oxidation of methanol to formaldehyde by vanadia/TiO2 model catalysts have shown that the activity of these systems vary considerably based on the way in which the model system is prepared with formaldehyde desorption temperatures observed anywhere from room temperature to 660 K. The principle reason for this variation is that the preparation of sub-monolayer films of vanadia on TiO2 produces clusters with a multitude of VxOy structures and a mixture of vanadium oxidation states. As a result the stoichiometry of the active vanadium oxide catalyst as well as the oxidation state of vanadium in the active catalyst remain unknown. To better understand this system, our group has probed the reactivity and structure of size-selected Vx, VOy and VxOy clusters on a reduced TiO2 (110) support in ultra-high vacuum (UHV) via TPD/R and scanning tunneling microscopy (STM). Ex situ preparation of these clusters in the gas phase prior to deposition has allowed us to systematically vary the stoichiometry of the vanadia clusters; a layer of control not available via the usual routes to vanadium oxide. The most active catalysts are shown to have (VO3)n stoichiometry in agreement with the theoretical models of the Metiu group. We have shown that both the activity and selectivity of V2O6 and V3O9 cluster catalysts depend sensitively on the oxidation state of the TiO2 (110) support. For example, V2O6 on a reduced surface is selective for the oxidation of methanol to formaldehyde while the selectivity shifts to favor methyl formate as the surface becomes increasingly oxidized. STM studies show that the structure of size-selected V2O6 clusters, upon adsorption to the surface, varies considerably with the oxidation state of the support, in good agreement with our reactivity studies. V 3O9 was shown to catalyze the oxidation of methanol to both formaldehyde and methyl formate on a reduced surface while STM suggests that, unlike V2O6, these clusters are prone to decomposition upon adsorption to the surface. Furthermore, TPD/R of size selected V 2O5 and V2O7 on TiO2 suggests that altering the stoichiometry of the (VO3)n clusters by a single oxygen atom significantly inhibits the activity of these catalysts.

Compact near-IR and mid-IR cavity ring down spectroscopy device

NASA Technical Reports Server (NTRS)

Miller, J. Houston (Inventor)

2011-01-01

This invention relates to a compact cavity ring down spectrometer for detection and measurement of trace species in a sample gas using a tunable solid-state continuous-wave mid-infrared PPLN OPO laser or a tunable low-power solid-state continuous wave near-infrared diode laser with an algorithm for reducing the periodic noise in the voltage decay signal which subjects the data to cluster analysis or by averaging of the interquartile range of the data.

Consensus of satellite cluster flight using an energy-matching optimal control method

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Zhou, Liang; Zhang, Bo

2017-11-01

This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

Field-induced cluster spin glass and inverse symmetry breaking enhanced by frustration

NASA Astrophysics Data System (ADS)

Schmidt, M.; Zimmer, F. M.; Magalhaes, S. G.

2018-03-01

We consider a cluster disordered model to study the interplay between short- and long-range interactions in geometrically frustrated spin systems under an external magnetic field (h). In our approach, the intercluster long-range disorder (J) is analytically treated to get an effective cluster model that is computed exactly. The clusters follow a checkerboard lattice with first-neighbor (J1) and second-neighbor (J2) interactions. We find a reentrant transition from the cluster spin-glass (CSG) state to a paramagnetic (PM) phase as the temperature decreases for a certain range of h. This inverse symmetry breaking (ISB) appears as a consequence of both quenched disorder with frustration and h, that introduce a CSG state with higher entropy than the polarized PM phase. The competitive scenario introduced by antiferromagnetic (AF) short-range interactions increases the CSG state entropy, leading to continuous ISB transitions and enhancing the ISB regions, mainly in the geometrically frustrated case (J1 =J2). Remarkably, when strong AF intracluster couplings are present, field-induced CSG phases can be found. These CSG regions are strongly related to the magnetization plateaus observed in this cluster disordered system. In fact, it is found that each field-induced magnetization jump brings a CSG region. We notice that geometrical frustration, as well as cluster size, play an important role in the magnetization plateaus and, therefore, are also relevant in the field-induced glassy states. Our findings suggest that competing interactions support ISB and field-induced CSG phases in disordered cluster systems under an external magnetic field.

Craniometric examination of Longxian and Qi Li Cun archaeological sites to assess population continuity in ancient northern China.

PubMed

Gibbon, Victoria E; Porter, Tarun A; Wu, Xiujie; Liu, Wu

2016-10-01

In this paper, population continuity and discontinuity in northern China are explored using craniometric analyses from two archaeological sites, Longxian (Warring States) and Qi Li Cun (Han Dynasty). Neither population has been previously studied. Artefactual evidence shows the individuals from Qi Li Cun were Xianbei, descendants from Mongolia. Longxian is from further south in the central plains at an earlier time, thus, we expect to observe variability between these groups. In total, 24 cranial measurements were obtained on 66 crania from these sites. Howells's cranial measurements on Anyang (42 crania) and Hainan (83 crania) Chinese samples were included for comparative purposes. Less variability is expected between Longxian and Howells's Chinese data due to geographic and temporal similarity. With closer geographic and temporal affinity with Anyang, the expectation is for Longxian and Anyang to be similar. Few statistical differences exist between Longxian and Qi Li Cun; this was supported by the similarity found through principal components analysis (PCA). Regardless of sex, canonical discriminant analysis shows clustering of Longxian and Qi Li Cun separate from those of Anyang and Hainan. Their similarity indicates the people from Longxian and Qi Li Cun likely share Mongolian ancestry. Our results, supported by other studies, suggest that despite temporal differences, Mongolians living in China during the Warring States and Han dynasty retained their cultural and genetic Mongolian identity. These data add valuable bioarchaeological information regarding the peopling of northern China during a crucial period of cultural and political change in the Early Bronze Age and Iron Age. Copyright © 2016 Elsevier GmbH. All rights reserved.

Anonymous broadcasting of classical information with a continuous-variable topological quantum code

NASA Astrophysics Data System (ADS)

Menicucci, Nicolas C.; Baragiola, Ben Q.; Demarie, Tommaso F.; Brennen, Gavin K.

2018-03-01

Broadcasting information anonymously becomes more difficult as surveillance technology improves, but remarkably, quantum protocols exist that enable provably traceless broadcasting. The difficulty is making scalable entangled resource states that are robust to errors. We propose an anonymous broadcasting protocol that uses a continuous-variable surface-code state that can be produced using current technology. High squeezing enables large transmission bandwidth and strong anonymity, and the topological nature of the state enables local error mitigation.

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.

Distribution of squeezed states through an atmospheric channel.

PubMed

Peuntinger, Christian; Heim, Bettina; Müller, Christian R; Gabriel, Christian; Marquardt, Christoph; Leuchs, Gerd

2014-08-08

Continuous variable quantum states of light are used in quantum information protocols and quantum metrology and known to degrade with loss and added noise. We were able to show the distribution of bright polarization squeezed quantum states of light through an urban free-space channel of 1.6 km length. To measure the squeezed states in this extreme environment, we utilize polarization encoding and a postselection protocol that is taking into account classical side information stemming from the distribution of transmission values. The successful distribution of continuous variable squeezed states is accentuated by a quantum state tomography, allowing for determining the purity of the state.

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.

Universal Quantum Computing with Arbitrary Continuous-Variable Encoding.

PubMed

Lau, Hoi-Kwan; Plenio, Martin B

2016-09-02

Implementing a qubit quantum computer in continuous-variable systems conventionally requires the engineering of specific interactions according to the encoding basis states. In this work, we present a unified formalism to conduct universal quantum computation with a fixed set of operations but arbitrary encoding. By storing a qubit in the parity of two or four qumodes, all computing processes can be implemented by basis state preparations, continuous-variable exponential-swap operations, and swap tests. Our formalism inherits the advantages that the quantum information is decoupled from collective noise, and logical qubits with different encodings can be brought to interact without decoding. We also propose a possible implementation of the required operations by using interactions that are available in a variety of continuous-variable systems. Our work separates the "hardware" problem of engineering quantum-computing-universal interactions, from the "software" problem of designing encodings for specific purposes. The development of quantum computer architecture could hence be simplified.

Universal Quantum Computing with Arbitrary Continuous-Variable Encoding

NASA Astrophysics Data System (ADS)

Lau, Hoi-Kwan; Plenio, Martin B.

2016-09-01

Implementing a qubit quantum computer in continuous-variable systems conventionally requires the engineering of specific interactions according to the encoding basis states. In this work, we present a unified formalism to conduct universal quantum computation with a fixed set of operations but arbitrary encoding. By storing a qubit in the parity of two or four qumodes, all computing processes can be implemented by basis state preparations, continuous-variable exponential-swap operations, and swap tests. Our formalism inherits the advantages that the quantum information is decoupled from collective noise, and logical qubits with different encodings can be brought to interact without decoding. We also propose a possible implementation of the required operations by using interactions that are available in a variety of continuous-variable systems. Our work separates the "hardware" problem of engineering quantum-computing-universal interactions, from the "software" problem of designing encodings for specific purposes. The development of quantum computer architecture could hence be simplified.

Stronger steerability criterion for more uncertain continuous-variable systems

NASA Astrophysics Data System (ADS)

Chowdhury, Priyanka; Pramanik, Tanumoy; Majumdar, A. S.

2015-10-01

We derive a fine-grained uncertainty relation for the measurement of two incompatible observables on a single quantum system of continuous variables, and show that continuous-variable systems are more uncertain than discrete-variable systems. Using the derived fine-grained uncertainty relation, we formulate a stronger steering criterion that is able to reveal the steerability of NOON states that has hitherto not been possible using other criteria. We further obtain a monogamy relation for our steering inequality which leads to an, in principle, improved lower bound on the secret key rate of a one-sided device independent quantum key distribution protocol for continuous variables.

Soil moisture response to snowmelt and rainfall in a Sierra Nevada mixed-conifer forest

Treesearch

Roger C. Bales; Jan W. Hopmans; Anthony T. O’Geen; Matthew Meadows; Peter C. Hartsough; Peter Kirchner; Carolyn T. Hunsaker; Dylan Beaudette

2011-01-01

Using data from a water-balance instrument cluster with spatially distributed sensors we determined the magnitude and within-catchment variability of components of the catchment-scale water balance, focusing on the relationship of seasonal evapotranspiration to changes in snowpack and soil moisture storage. Co-located, continuous snow depth and soil moisture...

Simulation studies of glassy nanoclusters

NASA Astrophysics Data System (ADS)

Bowles, Richard

2015-03-01

Glassy materials are amorphous solids usually formed by rapidly cooling a liquid below its equilibrium freezing temperature, trapping the particles in a liquid-like structure at the glass transition temperature. While appearing throughout nature and industry, these systems continue to challenge the way we think about the dynamics and thermodynamics of condensed matter and a fundamental understanding of the glass state remains elusive. This talk describes molecular simulation studies of glassy behaviour in binary Lennard-Jones nanoclusters. We show that the relaxation dynamics of the clusters is nonuniform and the core of the cluster goes through a glass transition at higher temperatures than at the surface. As the nanoclusters are cooled, they also exhibit a fragile-strong crossover in their dynamics and we explore how this phenomena is linked to the potential energy landscape of the clusters. Finally, we compare the properties of nanoclusters formed through vapour condensation, directly to the glassy state, with those of glassy clusters formed through traditional supercooling. The condensation clusters are shown to form ultra-stable glassy states analogous to the ultra-stable glasses formed by thin film vapour deposition onto a cold substrate. In all, our work suggests that nanoscale clusters exhibit some unique glassy features, while also offering potential insights into the fundamental nature of the glass transition.

Geographic Variation and Factors Associated with Female Genital Mutilation among Reproductive Age Women in Ethiopia: A National Population Based Survey

PubMed Central

Setegn, Tesfaye; Lakew, Yihunie; Deribe, Kebede

2016-01-01

Background Female genital mutilation (FGM) is a common traditional practice in developing nations including Ethiopia. It poses complex and serious long-term health risks for women and girls and can lead to death. In Ethiopia, the geographic distribution and factors associated with FGM practices are poorly understood. Therefore, we assessed the spatial distribution and factors associated with FGM among reproductive age women in the country. Method We used population based national representative surveys. Data from two (2000 and 2005) Ethiopian demographic and health surveys (EDHS) were used in this analysis. Briefly, EDHS used a stratified, two-stage cluster sampling design. A total of 15,367 (from EDHS 2000) and 14,070 (from EDHS 2005) women of reproductive age (15–49 years) were included in the analysis. Three outcome variables were used (prevalence of FGM among women, prevalence of FGM among daughters and support for the continuation of FGM). The data were weighted and descriptive statistics (percentage change), bivariate and multivariable logistic regression analyses were carried out. Multicollinearity of variables was assessed using variance inflation factors (VIF) with a reference value of 10 before interpreting the final output. The geographic variation and clustering of weighted FGM prevalence were analyzed and visualized on maps using ArcGIS. Z-scores were used to assess the statistical difference of geographic clustering of FGM prevalence spots. Result The trend of FGM weighted prevalence has been decreasing. Being wealthy, Muslim and in higher age categories are associated with increased odds of FGM among women. Similarly, daughters from Muslim women have increased odds of experiencing FGM. Women in the higher age categories have increased odds of having daughters who experience FGM. The odds of FGM among daughters decrease with increased maternal education. Mass media exposure, being wealthy and higher paternal and maternal education are associated with decreased odds of women’s support of FGM continuation. FGM prevalence and geographic clustering showed variation across regions in Ethiopia. Conclusion Individual, economic, socio-demographic, religious and cultural factors played major roles in the existing practice and continuation of FGM. The significant geographic clustering of FGM was observed across regions in Ethiopia. Therefore, targeted and integrated interventions involving religious leaders in high FGM prevalence spot clusters and addressing the socio-economic and geographic inequalities are recommended to eliminate FGM. PMID:26741488

Geographic Variation and Factors Associated with Female Genital Mutilation among Reproductive Age Women in Ethiopia: A National Population Based Survey.

PubMed

Setegn, Tesfaye; Lakew, Yihunie; Deribe, Kebede

2016-01-01

Female genital mutilation (FGM) is a common traditional practice in developing nations including Ethiopia. It poses complex and serious long-term health risks for women and girls and can lead to death. In Ethiopia, the geographic distribution and factors associated with FGM practices are poorly understood. Therefore, we assessed the spatial distribution and factors associated with FGM among reproductive age women in the country. We used population based national representative surveys. Data from two (2000 and 2005) Ethiopian demographic and health surveys (EDHS) were used in this analysis. Briefly, EDHS used a stratified, two-stage cluster sampling design. A total of 15,367 (from EDHS 2000) and 14,070 (from EDHS 2005) women of reproductive age (15-49 years) were included in the analysis. Three outcome variables were used (prevalence of FGM among women, prevalence of FGM among daughters and support for the continuation of FGM). The data were weighted and descriptive statistics (percentage change), bivariate and multivariable logistic regression analyses were carried out. Multicollinearity of variables was assessed using variance inflation factors (VIF) with a reference value of 10 before interpreting the final output. The geographic variation and clustering of weighted FGM prevalence were analyzed and visualized on maps using ArcGIS. Z-scores were used to assess the statistical difference of geographic clustering of FGM prevalence spots. The trend of FGM weighted prevalence has been decreasing. Being wealthy, Muslim and in higher age categories are associated with increased odds of FGM among women. Similarly, daughters from Muslim women have increased odds of experiencing FGM. Women in the higher age categories have increased odds of having daughters who experience FGM. The odds of FGM among daughters decrease with increased maternal education. Mass media exposure, being wealthy and higher paternal and maternal education are associated with decreased odds of women's support of FGM continuation. FGM prevalence and geographic clustering showed variation across regions in Ethiopia. Individual, economic, socio-demographic, religious and cultural factors played major roles in the existing practice and continuation of FGM. The significant geographic clustering of FGM was observed across regions in Ethiopia. Therefore, targeted and integrated interventions involving religious leaders in high FGM prevalence spot clusters and addressing the socio-economic and geographic inequalities are recommended to eliminate FGM.

Coexistence of unlimited bipartite and genuine multipartite entanglement: Promiscuous quantum correlations arising from discrete to continuous-variable systems

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

Adesso, Gerardo; CNR-INFM Coherentia , Naples; Grup d'Informacio Quantica, Universitat Autonoma de Barcelona, E-08193 Bellaterra

2007-08-15

Quantum mechanics imposes 'monogamy' constraints on the sharing of entanglement. We show that, despite these limitations, entanglement can be fully 'promiscuous', i.e., simultaneously present in unlimited two-body and many-body forms in states living in an infinite-dimensional Hilbert space. Monogamy just bounds the divergence rate of the various entanglement contributions. This is demonstrated in simple families of N-mode (N{>=}4) Gaussian states of light fields or atomic ensembles, which therefore enable infinitely more freedom in the distribution of information, as opposed to systems of individual qubits. Such a finding is of importance for the quantification, understanding, and potential exploitation of shared quantummore » correlations in continuous variable systems. We discuss how promiscuity gradually arises when considering simple families of discrete variable states, with increasing Hilbert space dimension towards the continuous variable limit. Such models are somehow analogous to Gaussian states with asymptotically diverging, but finite, squeezing. In this respect, we find that non-Gaussian states (which in general are more entangled than Gaussian states) exhibit also the interesting feature that their entanglement is more shareable: in the non-Gaussian multipartite arena, unlimited promiscuity can be already achieved among three entangled parties, while this is impossible for Gaussian, even infinitely squeezed states.« less

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Guiding the study of brain dynamics by using first-person data: Synchrony patterns correlate with ongoing conscious states during a simple visual task

PubMed Central

Lutz, Antoine; Lachaux, Jean-Philippe; Martinerie, Jacques; Varela, Francisco J.

2002-01-01

Even during well-calibrated cognitive tasks, successive brain responses to repeated identical stimulations are highly variable. The source of this variability is believed to reside mainly in fluctuations of the subject's cognitive “context” defined by his/her attentive state, spontaneous thought process, strategy to carry out the task, and so on … As these factors are hard to manipulate precisely, they are usually not controlled, and the variability is discarded by averaging techniques. We combined first-person data and the analysis of neural processes to reduce such noise. We presented the subjects with a three-dimensional illusion and recorded their electrical brain activity and their own report about their cognitive context. Trials were clustered according to these first-person data, and separate dynamical analyses were conducted for each cluster. We found that (i) characteristic patterns of endogenous synchrony appeared in frontal electrodes before stimulation. These patterns depended on the degree of preparation and the immediacy of perception as verbally reported. (ii) These patterns were stable for several recordings. (iii) Preparatory states modulate both the behavioral performance and the evoked and induced synchronous patterns that follow. (iv) These results indicated that first-person data can be used to detect and interpret neural processes. PMID:11805299

Quantification and scaling of multipartite entanglement in continuous variable systems.

PubMed

Adesso, Gerardo; Serafini, Alessio; Illuminati, Fabrizio

2004-11-26

We present a theoretical method to determine the multipartite entanglement between different partitions of multimode, fully or partially symmetric Gaussian states of continuous variable systems. For such states, we determine the exact expression of the logarithmic negativity and show that it coincides with that of equivalent two-mode Gaussian states. Exploiting this reduction, we demonstrate the scaling of the multipartite entanglement with the number of modes and its reliable experimental estimate by direct measurements of the global and local purities.

Health and disease phenotyping in old age using a cluster network analysis.

PubMed

Valenzuela, Jesus Felix; Monterola, Christopher; Tong, Victor Joo Chuan; Ng, Tze Pin; Larbi, Anis

2017-11-15

Human ageing is a complex trait that involves the synergistic action of numerous biological processes that interact to form a complex network. Here we performed a network analysis to examine the interrelationships between physiological and psychological functions, disease, disability, quality of life, lifestyle and behavioural risk factors for ageing in a cohort of 3,270 subjects aged ≥55 years. We considered associations between numerical and categorical descriptors using effect-size measures for each variable pair and identified clusters of variables from the resulting pairwise effect-size network and minimum spanning tree. We show, by way of a correspondence analysis between the two sets of clusters, that they correspond to coarse-grained and fine-grained structure of the network relationships. The clusters obtained from the minimum spanning tree mapped to various conceptual domains and corresponded to physiological and syndromic states. Hierarchical ordering of these clusters identified six common themes based on interactions with physiological systems and common underlying substrates of age-associated morbidity and disease chronicity, functional disability, and quality of life. These findings provide a starting point for indepth analyses of ageing that incorporate immunologic, metabolomic and proteomic biomarkers, and ultimately offer low-level-based typologies of healthy and unhealthy ageing.

Continuous Variable Quantum Key Distribution Using Polarized Coherent States

NASA Astrophysics Data System (ADS)

Vidiella-Barranco, A.; Borelli, L. F. M.

We discuss a continuous variables method of quantum key distribution employing strongly polarized coherent states of light. The key encoding is performed using the variables known as Stokes parameters, rather than the field quadratures. Their quantum counterpart, the Stokes operators Ŝi (i=1,2,3), constitute a set of non-commuting operators, being the precision of simultaneous measurements of a pair of them limited by an uncertainty-like relation. Alice transmits a conveniently modulated two-mode coherent state, and Bob randomly measures one of the Stokes parameters of the incoming beam. After performing reconciliation and privacy amplification procedures, it is possible to distill a secret common key. We also consider a non-ideal situation, in which coherent states with thermal noise, instead of pure coherent states, are used for encoding.

Ab initio metadynamics simulations of oxygen/ligand interactions in organoaluminum clusters

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

Alnemrat, Sufian; Hooper, Joseph P., E-mail: jphooper@nps.edu

2014-10-14

Car-Parrinello molecular dynamics combined with a metadynamics algorithm is used to study the initial interaction of O{sub 2} with the low-valence organoaluminum clusters Al{sub 4}Cp{sub 4} (Cp=C{sub 5}H{sub 5}) and Al{sub 4}Cp{sub 4}{sup *} (Cp{sup *}=C{sub 5}[CH{sub 3}]{sub 5}). Prior to reaction with the aluminum core, simulations suggest that the oxygen undergoes a hindered crossing of the steric barrier presented by the outer ligand monolayer. A combination of two collective variables based on aluminum/oxygen distance and lateral oxygen displacement was found to produce distinct reactant, product, and transition states for this process. In the methylated cluster with Cp{sup *} ligands,more » a broad transition state of 45 kJ/mol was observed due to direct steric interactions with the ligand groups and considerable oxygen reorientation. In the non-methylated cluster the ligands distort away from the oxidizer, resulting in a barrier of roughly 34 kJ/mol with minimal O{sub 2} reorientation. A study of the oxygen/cluster system fixed in a triplet multiplicity suggests that the spin state does not affect the initial steric interaction with the ligands. The metadynamics approach appears to be a promising means of analyzing the initial steps of such oxidation reactions for ligand-protected clusters.« less

Population coding in sparsely connected networks of noisy neurons.

PubMed

Tripp, Bryan P; Orchard, Jeff

2012-01-01

This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

Continuous-variable controlled-Z gate using an atomic ensemble

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

Wang Mingfeng; Jiang Nianquan; Jin Qingli

2011-06-15

The continuous-variable controlled-Z gate is a canonical two-mode gate for universal continuous-variable quantum computation. It is considered as one of the most fundamental continuous-variable quantum gates. Here we present a scheme for realizing continuous-variable controlled-Z gate between two optical beams using an atomic ensemble. The gate is performed by simply sending the two beams propagating in two orthogonal directions twice through a spin-squeezed atomic medium. Its fidelity can run up to one if the input atomic state is infinitely squeezed. Considering the noise effects due to atomic decoherence and light losses, we show that the observed fidelities of the schememore » are still quite high within presently available techniques.« less

Light clusters in nuclear matter: Excluded volume versus quantum many-body approaches

NASA Astrophysics Data System (ADS)

Hempel, Matthias; Schaffner-Bielich, Jürgen; Typel, Stefan; Röpke, Gerd

2011-11-01

The formation of clusters in nuclear matter is investigated, which occurs, e.g., in low-energy heavy-ion collisions or core-collapse supernovae. In astrophysical applications, the excluded volume concept is commonly used for the description of light clusters. Here we compare a phenomenological excluded volume approach to two quantum many-body models, the quantum statistical model and the generalized relativistic mean-field model. All three models contain bound states of nuclei with mass number A≤4. It is explored to which extent the complex medium effects can be mimicked by the simpler excluded volume model, regarding the chemical composition and thermodynamic variables. Furthermore, the role of heavy nuclei and excited states is investigated by use of the excluded volume model. At temperatures of a few MeV the excluded volume model gives a poor description of the medium effects on the light clusters, but there the composition is actually dominated by heavy nuclei. At larger temperatures there is a rather good agreement, whereas some smaller differences and model dependencies remain.

Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies.

PubMed

Friesen, Melissa C; Shortreed, Susan M; Wheeler, David C; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S; Baris, Dalsu; Karagas, Margaret R; Schwenn, Molly; Johnson, Alison; Armenti, Karla R; Silverman, Debra T; Yu, Kai

2015-05-01

Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster. Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.

Disentanglement in bipartite continuous-variable systems

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

Barbosa, F. A. S.; Coelho, A. S.; Nussenzveig, P.

2011-11-15

Entanglement in bipartite continuous-variable systems is investigated in the presence of partial losses such as those introduced by a realistic quantum communication channel, e.g., by propagation in an optical fiber. We find that entanglement can vanish completely for partial losses, in a situation reminiscent of so-called entanglement sudden death. Even states with extreme squeezing may become separable after propagation in lossy channels. Having in mind the potential applications of such entangled light beams to optical communications, we investigate the conditions under which entanglement can survive for all partial losses. Different loss scenarios are examined, and we derive criteria to testmore » the robustness of entangled states. These criteria are necessary and sufficient for Gaussian states. Our study provides a framework to investigate the robustness of continuous-variable entanglement in more complex multipartite systems.« less

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Spatiotemporal characteristics of severe dry and wet conditions in the Free State Province, South Africa

NASA Astrophysics Data System (ADS)

Mbiriri, M.; Mukwada, G.; Manatsa, D.

2018-02-01

This paper assesses the spatiotemporal characteristics of agricultural droughts and wet conditions in the Free State Province of South Africa for the period between 1960 and 2013. Since agriculturally, the Free State Province is considered the bread basket of the country, understanding the variability of drought and wet conditions becomes necessary. The Standardised Precipitation Index (SPI) computed from gridded monthly precipitation data was used to assess the rainfall extreme conditions. Hot spot analysis was used to divide the province into five homogenous clusters where the spatiotemporal characteristics for each cluster were analysed. The results show a west to east increase in seasonal average total precipitation. However, the eastern part of the province demonstrates higher occurrences of droughts, with SPI ≤ - 1.282. This is despite the observation that the region shows a recent increase in droughts unlike the western region. It is also noted that significant differences in drought/wet intensities between clusters are more pronounced during the early compared to the late summer period.

Mixture Distribution Latent State-Trait Analysis: Basic Ideas and Applications

ERIC Educational Resources Information Center

Courvoisier, Delphine S.; Eid, Michael; Nussbeck, Fridtjof W.

2007-01-01

Extensions of latent state-trait models for continuous observed variables to mixture latent state-trait models with and without covariates of change are presented that can separate individuals differing in their occasion-specific variability. An empirical application to the repeated measurement of mood states (N = 501) revealed that a model with 2…

Quantum correlations for bipartite continuous-variable systems

NASA Astrophysics Data System (ADS)

Ma, Ruifen; Hou, Jinchuan; Qi, Xiaofei; Wang, Yangyang

2018-04-01

Two quantum correlations Q and Q_P for (m+n)-mode continuous-variable systems are introduced in terms of average distance between the reduced states under the local Gaussian positive operator-valued measurements, and analytical formulas of these quantum correlations for bipartite Gaussian states are provided. It is shown that the product states do not contain these quantum correlations, and conversely, all (m+n)-mode Gaussian states with zero quantum correlations are product states. Generally, Q≥ Q_{P}, but for the symmetric two-mode squeezed thermal states, these quantum correlations are the same and a computable formula is given. In addition, Q is compared with Gaussian geometric discord for symmetric squeezed thermal states.

Using Hierarchical Cluster Models to Systematically Identify Groups of Jobs With Similar Occupational Questionnaire Response Patterns to Assist Rule-Based Expert Exposure Assessment in Population-Based Studies

PubMed Central

Friesen, Melissa C.; Shortreed, Susan M.; Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Silverman, Debra T.; Yu, Kai

2015-01-01

Objectives: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Methods: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m−3 respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters’ homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job’s estimate and the mean estimate for all jobs within the cluster. Results: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. Conclusions: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. PMID:25477475

Revisiting the leading drivers of Pacific coastal drought variability in the Contiguous United States

NASA Astrophysics Data System (ADS)

Cook, B.; Williams, P.; Mankin, J. S.; Seager, R.; Smerdon, J. E.; Singh, D.

2017-12-01

Coastal droughts simultaneously affecting California, Oregon, and Washington are rare, but have extensive and severe impacts (e.g., wildfire, agriculture). To better understand these events, we use historical observations to investigate: (1) drought variability along the Pacific Coast of the Contiguous United States and (2) years when extreme drought affects the entire coast. The leading pattern of cold-season (October-March) precipitation variability along the Pacific Coast favors spatially coherent moisture anomalies, accounts for >40% of the underlying variance, and is forced primarily by internal atmospheric dynamics. This contrasts with a much weaker dipole mode ( 20% of precipitation variability) characterized by anti-phased moisture anomalies across 40N and strong correlations with tropical Pacific sea surface temperatures (SSTs). Sixteen coastal-wide summer droughts occurred from 1895-2016 (clustering in the 1920s-1930s and post-2000), events most strongly linked with the leading precipitation mode and internal atmospheric variability. The frequency of landfalling atmospheric rivers south of 40N is sharply reduced during coastal droughts, but not north of this boundary where their frequency is more strongly influenced by the dipole. The lack of a consistent pattern of SST forcing during coastal droughts suggests little potential for skillful predictions of these events at the seasonal scale. However, their tendency to cluster in time and the impact of warming during recent droughts may help inform decadal and longer-term drought risks.

Strong influence of variable treatment on the performance of numerically defined ecological regions.

PubMed

Snelder, Ton; Lehmann, Anthony; Lamouroux, Nicolas; Leathwick, John; Allenbach, Karin

2009-10-01

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale "sub-domains" defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.

Hierarchical clusters of phytoplankton variables in dammed water bodies

NASA Astrophysics Data System (ADS)

Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

2017-06-01

In this paper a dataset containing biological variables of the water column of several Portuguese reservoirs is analyzed. Hierarchical cluster analysis is used to obtain clusters of phytoplankton variables of the phylum Cyanophyta, with the objective of validating the classification of Portuguese reservoirs previewly presented in [1] which were divided into three clusters: (1) Interior Tagus and Aguieira; (2) Douro; and (3) Other rivers. Now three new clusters of Cyanophyta variables were found. Kruskal-Wallis and Mann-Whitney tests are used to compare the now obtained Cyanophyta clusters and the previous Reservoirs clusters, in order to validate the classification of the water quality of reservoirs. The amount of Cyanophyta algae present in the reservoirs from the three clusters is significantly different, which validates the previous classification.

Using Clustering to Establish Climate Regimes from PCM Output

NASA Technical Reports Server (NTRS)

Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.

2002-01-01

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

PubMed

Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

2017-01-01

Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

Variable Screening for Cluster Analysis.

ERIC Educational Resources Information Center

Donoghue, John R.

Inclusion of irrelevant variables in a cluster analysis adversely affects subgroup recovery. This paper examines using moment-based statistics to screen variables; only variables that pass the screening are then used in clustering. Normal mixtures are analytically shown often to possess negative kurtosis. Two related measures, "m" and…

Hypervirulent emm59 Clone in Invasive Group A Streptococcus Outbreak, Southwestern United States.

PubMed

Engelthaler, David M; Valentine, Michael; Bowers, Jolene; Pistole, Jennifer; Driebe, Elizabeth M; Terriquez, Joel; Nienstadt, Linus; Carroll, Mark; Schumacher, Mare; Ormsby, Mary Ellen; Brady, Shane; Livar, Eugene; Yazzie, Del; Waddell, Victor; Peoples, Marie; Komatsu, Kenneth; Keim, Paul

2016-04-01

The hyper-virulent emm59 genotype of invasive group A Streptococcus was identified in northern Arizona in 2015. Eighteen isolates belonging to a genomic cluster grouped most closely with recently identified isolates in New Mexico. The continued transmission of emm59 in the southwestern United States poses a public health concern.

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

Continuous-variable teleportation of a negative Wigner function

NASA Astrophysics Data System (ADS)

Mišta, Ladislav, Jr.; Filip, Radim; Furusawa, Akira

2010-07-01

Teleportation is a basic primitive for quantum communication and quantum computing. We address the problem of continuous-variable (unconditional and conditional) teleportation of a pure single-photon state and a mixed attenuated single-photon state generally in a nonunity-gain regime. Our figure of merit is the maximum negativity of the Wigner function, which demonstrates a highly nonclassical feature of the teleported state. We find that the negativity of the Wigner function of the single-photon state can be unconditionally teleported for an arbitrarily weak squeezed state used to create the entangled state shared in teleportation. In contrast, for the attenuated single-photon state there is a strict threshold squeezing one has to surpass to successfully teleport the negativity of its Wigner function. The conditional teleportation allows one to approach perfect transmission of the single photon for an arbitrarily low squeezing at a cost of decrease of the success rate. In contrast, for the attenuated single photon state, conditional teleportation cannot overcome the squeezing threshold of the unconditional teleportation and it approaches negativity of the input state only if the squeezing increases simultaneously. However, as soon as the threshold squeezing is surpassed, conditional teleportation still pronouncedly outperforms the unconditional one. The main consequences for quantum communication and quantum computing with continuous variables are discussed.

Continuous-variable teleportation of a negative Wigner function

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

Mista, Ladislav Jr.; Filip, Radim; Furusawa, Akira

2010-07-15

Teleportation is a basic primitive for quantum communication and quantum computing. We address the problem of continuous-variable (unconditional and conditional) teleportation of a pure single-photon state and a mixed attenuated single-photon state generally in a nonunity-gain regime. Our figure of merit is the maximum negativity of the Wigner function, which demonstrates a highly nonclassical feature of the teleported state. We find that the negativity of the Wigner function of the single-photon state can be unconditionally teleported for an arbitrarily weak squeezed state used to create the entangled state shared in teleportation. In contrast, for the attenuated single-photon state there ismore » a strict threshold squeezing one has to surpass to successfully teleport the negativity of its Wigner function. The conditional teleportation allows one to approach perfect transmission of the single photon for an arbitrarily low squeezing at a cost of decrease of the success rate. In contrast, for the attenuated single photon state, conditional teleportation cannot overcome the squeezing threshold of the unconditional teleportation and it approaches negativity of the input state only if the squeezing increases simultaneously. However, as soon as the threshold squeezing is surpassed, conditional teleportation still pronouncedly outperforms the unconditional one. The main consequences for quantum communication and quantum computing with continuous variables are discussed.« less

Theory of the vortex-clustering transition in a confined two-dimensional quantum fluid

NASA Astrophysics Data System (ADS)

Yu, Xiaoquan; Billam, Thomas P.; Nian, Jun; Reeves, Matthew T.; Bradley, Ashton S.

2016-08-01

Clustering of like-sign vortices in a planar bounded domain is known to occur at negative temperature, a phenomenon that Onsager demonstrated to be a consequence of bounded phase space. In a confined superfluid, quantized vortices can support such an ordered phase, provided they evolve as an almost isolated subsystem containing sufficient energy. A detailed theoretical understanding of the statistical mechanics of such states thus requires a microcanonical approach. Here we develop an analytical theory of the vortex clustering transition in a neutral system of quantum vortices confined to a two-dimensional disk geometry, within the microcanonical ensemble. The choice of ensemble is essential for identifying the correct thermodynamic limit of the system, enabling a rigorous description of clustering in the language of critical phenomena. As the system energy increases above a critical value, the system develops global order via the emergence of a macroscopic dipole structure from the homogeneous phase of vortices, spontaneously breaking the Z2 symmetry associated with invariance under vortex circulation exchange, and the rotational SO (2 ) symmetry due to the disk geometry. The dipole structure emerges characterized by the continuous growth of the macroscopic dipole moment which serves as a global order parameter, resembling a continuous phase transition. The critical temperature of the transition, and the critical exponent associated with the dipole moment, are obtained exactly within mean-field theory. The clustering transition is shown to be distinct from the final state reached at high energy, known as supercondensation. The dipole moment develops via two macroscopic vortex clusters and the cluster locations are found analytically, both near the clustering transition and in the supercondensation limit. The microcanonical theory shows excellent agreement with Monte Carlo simulations, and signatures of the transition are apparent even for a modest system of 100 vortices, accessible in current Bose-Einstein condensate experiments.

Sample size calculations for the design of cluster randomized trials: A summary of methodology.

PubMed

Gao, Fei; Earnest, Arul; Matchar, David B; Campbell, Michael J; Machin, David

2015-05-01

Cluster randomized trial designs are growing in popularity in, for example, cardiovascular medicine research and other clinical areas and parallel statistical developments concerned with the design and analysis of these trials have been stimulated. Nevertheless, reviews suggest that design issues associated with cluster randomized trials are often poorly appreciated and there remain inadequacies in, for example, describing how the trial size is determined and the associated results are presented. In this paper, our aim is to provide pragmatic guidance for researchers on the methods of calculating sample sizes. We focus attention on designs with the primary purpose of comparing two interventions with respect to continuous, binary, ordered categorical, incidence rate and time-to-event outcome variables. Issues of aggregate and non-aggregate cluster trials, adjustment for variation in cluster size and the effect size are detailed. The problem of establishing the anticipated magnitude of between- and within-cluster variation to enable planning values of the intra-cluster correlation coefficient and the coefficient of variation are also described. Illustrative examples of calculations of trial sizes for each endpoint type are included. Copyright © 2015 Elsevier Inc. All rights reserved.

Some applications of uncertainty relations in quantum information

NASA Astrophysics Data System (ADS)

Majumdar, A. S.; Pramanik, T.

2016-08-01

We discuss some applications of various versions of uncertainty relations for both discrete and continuous variables in the context of quantum information theory. The Heisenberg uncertainty relation enables demonstration of the Einstein, Podolsky and Rosen (EPR) paradox. Entropic uncertainty relations (EURs) are used to reveal quantum steering for non-Gaussian continuous variable states. EURs for discrete variables are studied in the context of quantum memory where fine-graining yields the optimum lower bound of uncertainty. The fine-grained uncertainty relation is used to obtain connections between uncertainty and the nonlocality of retrieval games for bipartite and tripartite systems. The Robertson-Schrödinger (RS) uncertainty relation is applied for distinguishing pure and mixed states of discrete variables.

Intercenter Differences in Bronchopulmonary Dysplasia or Death Among Very Low Birth Weight Infants

PubMed Central

Walsh, Michele; Bobashev, Georgiy; Das, Abhik; Levine, Burton; Carlo, Waldemar A.; Higgins, Rosemary D.

2011-01-01

OBJECTIVES: To determine (1) the magnitude of clustering of bronchopulmonary dysplasia (36 weeks) or death (the outcome) across centers of the Eunice Kennedy Shriver National Institute of Child and Human Development National Research Network, (2) the infant-level variables associated with the outcome and estimate their clustering, and (3) the center-specific practices associated with the differences and build predictive models. METHODS: Data on neonates with a birth weight of <1250 g from the cluster-randomized benchmarking trial were used to determine the magnitude of clustering of the outcome according to alternating logistic regression by using pairwise odds ratio and predictive modeling. Clinical variables associated with the outcome were identified by using multivariate analysis. The magnitude of clustering was then evaluated after correction for infant-level variables. Predictive models were developed by using center-specific and infant-level variables for data from 2001 2004 and projected to 2006. RESULTS: In 2001–2004, clustering of bronchopulmonary dysplasia/death was significant (pairwise odds ratio: 1.3; P < .001) and increased in 2006 (pairwise odds ratio: 1.6; overall incidence: 52%; range across centers: 32%–74%); center rates were relatively stable over time. Variables that varied according to center and were associated with increased risk of outcome included lower body temperature at NICU admission, use of prophylactic indomethacin, specific drug therapy on day 1, and lack of endotracheal intubation. Center differences remained significant even after correction for clustered variables. CONCLUSION: Bronchopulmonary dysplasia/death rates demonstrated moderate clustering according to center. Clinical variables associated with the outcome were also clustered. Center differences after correction of clustered variables indicate presence of as-yet unmeasured center variables. PMID:21149431

The electronic structure of Au25 clusters: between discrete and continuous

NASA Astrophysics Data System (ADS)

Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Sai Krishna, Katla; Li, Ruipeng; Mei, Wai-Ning; Skrabalak, Sara E.; Kumar, Challa S. S. R.; Losovyj, Yaroslav

2016-08-01

Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies.Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies. Electronic supplementary information (ESI) available: Experimental details including chemicals, sample preparation, and characterization methods. Computation techniques, SV-AUC, GIWAXS, XPS, UPS, MALDI-TOF, ESI data of Au25 clusters. See DOI: 10.1039/c6nr02374f

Variable Stars in Large Magellanic Cloud Globular Clusters. III. Reticulum

NASA Astrophysics Data System (ADS)

Kuehn, Charles A.; Dame, Kyra; Smith, Horace A.; Catelan, Márcio; Jeon, Young-Beom; Nemec, James M.; Walker, Alistair R.; Kunder, Andrea; Pritzl, Barton J.; De Lee, Nathan; Borissova, Jura

2013-06-01

This is the third in a series of papers studying the variable stars in old globular clusters in the Large Magellanic Cloud. The primary goal of this series is to look at how the characteristics and behavior of RR Lyrae stars in Oosterhoff-intermediate systems compare to those of their counterparts in Oosterhoff-I/II systems. In this paper we present the results of our new time-series BVI photometric study of the globular cluster Reticulum. We found a total of 32 variables stars (22 RRab, 4 RRc, and 6 RRd stars) in our field of view. We present photometric parameters and light curves for these stars. We also present physical properties, derived from Fourier analysis of light curves, for some of the RR Lyrae stars. We discuss the Oosterhoff classification of Reticulum and use our results to re-derive the distance modulus and age of the cluster. Based on observations taken with the SMARTS 1.3 m telescope operated by the SMARTS Consortium and observations taken at the Southern Astrophysical Research (SOAR) telescope, which is a joint project of the Ministério da Ciência, Tecnologia, e Inovação (MCTI) da República Federativa do Brasil, the U.S. National Optical Astronomy Observatory (NOAO), the University of North Carolina at Chapel Hill (UNC), and Michigan State University (MSU).

Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel-based "mouse pup syllable classification calculator".

PubMed

Grimsley, Jasmine M S; Gadziola, Marie A; Wenstrup, Jeffrey J

2012-01-01

Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified 10 syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices.

PubMed

Wilderjans, Tom F; Ceulemans, Eva; Van Mechelen, Iven; Depril, Dirk

2011-03-01

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.

High-fidelity teleportation beyond the no-cloning limit and entanglement swapping for continuous variables.

PubMed

Takei, Nobuyuki; Yonezawa, Hidehiro; Aoki, Takao; Furusawa, Akira

2005-06-10

We experimentally demonstrate continuous-variable quantum teleportation beyond the no-cloning limit. We teleport a coherent state and achieve the fidelity of 0.70 +/- 0.02 that surpasses the no-cloning limit of 2/3. Surpassing the limit is necessary to transfer the nonclassicality of an input quantum state. By using our high-fidelity teleporter, we demonstrate entanglement swapping, namely, teleportation of quantum entanglement, as an example of transfer of nonclassicality.

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.

Spin incommensurability and two phase competition in cobaltites.

PubMed

Phelan, D; Louca, Despina; Kamazawa, K; Lee, S-H; Ancona, S N; Rosenkranz, S; Motome, Y; Hundley, M F; Mitchell, J F; Moritomo, Y

2006-12-08

The perovskite LaCoO3 evolves from a nonmagnetic Mott insulator to a spin cluster ferromagnet (FM) with the substitution of Sr2+ for La3+ in La1-xSrxCoO3. The clusters increase in size and number with x and the charge percolation through the clusters leads to a metallic state. Using elastic neutron scattering on La1-xSrxCoO3 single crystals, we show that an incommensurate spin superstructure coexists with the FM spin clusters. The incommensurability increases continuously with x, with the intensity rising in the insulating phase and dropping in the metallic phase as it directly competes with the commensurate FM, itinerant clusters. The spin incommensurability arises from local order of Co3+-Co4+ clusters but no long-range static or dynamic spin stripes develop. The coexistence and competition of the two magnetic phases explain the residual resistivity at low temperatures in samples with metalliclike transport.

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.

Two Cepheid variables in the Fornax dwarf galaxy

NASA Technical Reports Server (NTRS)

Light, R. M.; Armandroff, T. E.; Zinn, R.

1986-01-01

Two fields surrounding globular clusters 2 and 3 in the Fornax dwarf spheroidal galaxy have been searched for short-period variable stars that are brighter than the horizontal branch. This survey confirmed as variable the two suspected suprahorizontal-branch variables discovered by Buonanno et al. (1985) in their photometry of the clusters. The observations show that the star in cluster 2 is a W Virginis variable of 14.4 day period. It is the first W Vir variable to be found in a dwarf spheroidal galaxy, and its proximity to the center of cluster 2 suggests that it is a cluster member. The other star appears to be an anomalous Cephpeid of 0.78 day period. It lies outside or very near the boundary of cluster 3, and is therefore probably a member of the field population of Fornax. Although no other suprahorizontal-branch variables were discovered in the survey, it did confirm as variable two of the RR Lyrae candidates of Buonanno et al., which appeared at the survey limit. The implications of these observations for the understanding of the stellar content at Fornax are discussed.

Phenology of Honey Bee Swarm Departure in New Jersey, United States.

PubMed

Gilley, D C; Courtright, T J; Thom, C

2018-03-31

Departure of swarms from honey bee (Apis mellifera Linnaeus (Hymenoptera: Apidae)) nests is an important reproductive event for wild honey bee colonies and economically costly in managed bee colonies. The seasonal timing of swarm departure varies regionally and annually, creating challenges for honey bee management and emphasizing the potential for swarming behavior to be affected by plant-pollinator phenological mismatch. In this study, we first document variability in the timing of swarm departure across the large and heterogeneous geographical area of New Jersey over 4 years using 689 swarm-cluster observations. Second, hypothesizing that honey bee colonies adaptively tune the timing of swarm departure to match floral food-resource availability, we predicted that growing degree-days could be used to account for regional and annual variability. To test this idea, we used local weather records to determine the growing degree-day on which each swarm cluster was observed and tested for differences among climate regions and years. The state-wide mean swarm cluster date was May 15 (± 0.6 d), with moderate but significant differences among the state's five climate regions and between years. Use of degree-day information suggests that local heat accumulation can account for some climate-region differences in swarm-departure timing. Annual variation existed on a scale of only several days and was not accounted for by growing degree-days, suggesting little adaptive tuning of swarm-departure timing with respect to local heat accumulation.

Prediction of biological integrity based on environmental similarity--revealing the scale-dependent link between study area and top environmental predictors.

PubMed

Bedoya, David; Manolakos, Elias S; Novotny, Vladimir

2011-03-01

Indices of Biological integrity (IBI) are considered valid indicators of the overall health of a water body because the biological community is an endpoint within natural systems. However, prediction of biological integrity using information from multi-parameter environmental observations is a challenging problem due to the hierarchical organization of the natural environment, the existence of nonlinear inter-dependencies among variables as well as natural stochasticity and measurement noise. We present a method for predicting the Fish Index of Biological Integrity (IBI) using multiple environmental observations at the state-scale in Ohio. Instream (chemical and physical quality) and offstream parameters (regional and local upstream land uses, stream fragmentation, and point source density and intensity) are used for this purpose. The IBI predictions are obtained using the environmental site-similarity concept and following a simple to implement leave-one-out cross validation approach. An IBI prediction for a sampling site is calculated by averaging the observed IBI scores of observations clustered in the most similar branch of a dendrogram--a hierarchical clustering tree of environmental observations--built using the rest of the observations. The standardized Euclidean distance is used to assess dissimilarity between observations. The constructed predictive model was able to explain 61% of the IBI variability statewide. Stream fragmentation and regional land use explained 60% of the variability; the remaining 1% was explained by instream habitat quality. Metrics related to local land use, water quality, and point source density and intensity did not improve the predictive model at the state-scale. The impact of local environmental conditions was evaluated by comparing local characteristics between well- and mispredicted sites. Significant differences in local land use patterns and upstream fragmentation density explained some of the model's over-predictions. Local land use conditions explained some of the model's IBI under-predictions at the state-scale since none of the variables within this group were included in the best final predictive model. Under-predicted sites also had higher levels of downstream fragmentation. The proposed variables ranking and predictive modeling methodology is very well suited for the analysis of hierarchical environments, such as natural fresh water systems, with many cross-correlated environmental variables. It is computationally efficient, can be fully automated, does not make any pre-conceived assumptions on the variables interdependency structure (such as linearity), and it is able to rank variables in a database and generate IBI predictions using only non-parametric easy to implement hierarchical clustering. Copyright © 2011 Elsevier Ltd. All rights reserved.

Temperature variability analysis using wavelets and multiscale entropy in patients with systemic inflammatory response syndrome, sepsis, and septic shock.

PubMed

Papaioannou, Vasilios E; Chouvarda, Ioanna G; Maglaveras, Nikos K; Pneumatikos, Ioannis A

2012-12-12

Even though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature complexity in patients with systemic inflammation during a suspected ICU-acquired infection, by using wavelets transformation and multiscale entropy of temperature signals, in a cohort of mixed critically ill patients. Twenty-two patients were enrolled in the study. In five, systemic inflammatory response syndrome (SIRS, group 1) developed, 10 had sepsis (group 2), and seven had septic shock (group 3). All temperature curves were studied during the first 24 hours of an inflammatory state. A wavelet transformation was applied, decomposing the signal in different frequency components (scales) that have been found to reflect neurogenic and metabolic inputs on temperature oscillations. Wavelet energy and entropy per different scales associated with complexity in specific frequency bands and multiscale entropy of the whole signal were calculated. Moreover, a clustering technique and a linear discriminant analysis (LDA) were applied for permitting pattern recognition in data sets and assessing diagnostic accuracy of different wavelet features among the three classes of patients. Statistically significant differences were found in wavelet entropy between patients with SIRS and groups 2 and 3, and in specific ultradian bands between SIRS and group 3, with decreased entropy in sepsis. Cluster analysis using wavelet features in specific bands revealed concrete clusters closely related with the groups in focus. LDA after wrapper-based feature selection was able to classify with an accuracy of more than 80% SIRS from the two sepsis groups, based on multiparametric patterns of entropy values in the very low frequencies and indicating reduced metabolic inputs on local thermoregulation, probably associated with extensive vasodilatation. We suggest that complexity analysis of temperature signals can assess inherent thermoregulatory dynamics during systemic inflammation and has increased discriminating value in patients with infectious versus noninfectious conditions, probably associated with severity of illness.

Temperature variability analysis using wavelets and multiscale entropy in patients with systemic inflammatory response syndrome, sepsis, and septic shock

PubMed Central

2012-01-01

Background Even though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature complexity in patients with systemic inflammation during a suspected ICU-acquired infection, by using wavelets transformation and multiscale entropy of temperature signals, in a cohort of mixed critically ill patients. Methods Twenty-two patients were enrolled in the study. In five, systemic inflammatory response syndrome (SIRS, group 1) developed, 10 had sepsis (group 2), and seven had septic shock (group 3). All temperature curves were studied during the first 24 hours of an inflammatory state. A wavelet transformation was applied, decomposing the signal in different frequency components (scales) that have been found to reflect neurogenic and metabolic inputs on temperature oscillations. Wavelet energy and entropy per different scales associated with complexity in specific frequency bands and multiscale entropy of the whole signal were calculated. Moreover, a clustering technique and a linear discriminant analysis (LDA) were applied for permitting pattern recognition in data sets and assessing diagnostic accuracy of different wavelet features among the three classes of patients. Results Statistically significant differences were found in wavelet entropy between patients with SIRS and groups 2 and 3, and in specific ultradian bands between SIRS and group 3, with decreased entropy in sepsis. Cluster analysis using wavelet features in specific bands revealed concrete clusters closely related with the groups in focus. LDA after wrapper-based feature selection was able to classify with an accuracy of more than 80% SIRS from the two sepsis groups, based on multiparametric patterns of entropy values in the very low frequencies and indicating reduced metabolic inputs on local thermoregulation, probably associated with extensive vasodilatation. Conclusions We suggest that complexity analysis of temperature signals can assess inherent thermoregulatory dynamics during systemic inflammation and has increased discriminating value in patients with infectious versus noninfectious conditions, probably associated with severity of illness. PMID:22424316

Variability in research ethics review of cluster randomized trials: a scenario-based survey in three countries

PubMed Central

2014-01-01

Background Cluster randomized trials (CRTs) present unique ethical challenges. In the absence of a uniform standard for their ethical design and conduct, problems such as variability in procedures and requirements by different research ethics committees will persist. We aimed to assess the need for ethics guidelines for CRTs among research ethics chairs internationally, investigate variability in procedures for research ethics review of CRTs within and among countries, and elicit research ethics chairs’ perspectives on specific ethical issues in CRTs, including the identification of research subjects. The proper identification of research subjects is a necessary requirement in the research ethics review process, to help ensure, on the one hand, that subjects are protected from harm and exploitation, and on the other, that reviews of CRTs are completed efficiently. Methods A web-based survey with closed- and open-ended questions was administered to research ethics chairs in Canada, the United States, and the United Kingdom. The survey presented three scenarios of CRTs involving cluster-level, professional-level, and individual-level interventions. For each scenario, a series of questions was posed with respect to the type of review required (full, expedited, or no review) and the identification of research subjects at cluster and individual levels. Results A total of 189 (35%) of 542 chairs responded. Overall, 144 (84%, 95% CI 79 to 90%) agreed or strongly agreed that there is a need for ethics guidelines for CRTs and 158 (92%, 95% CI 88 to 96%) agreed or strongly agreed that research ethics committees could be better informed about distinct ethical issues surrounding CRTs. There was considerable variability among research ethics chairs with respect to the type of review required, as well as the identification of research subjects. The cluster-cluster and professional-cluster scenarios produced the most disagreement. Conclusions Research ethics committees identified a clear need for ethics guidelines for CRTs and education about distinct ethical issues in CRTs. There is disagreement among committees, even within the same countries, with respect to key questions in the ethics review of CRTs. This disagreement reflects variability of opinion and practices pointing toward possible gaps in knowledge, and supports the need for explicit guidelines for the ethical conduct and review of CRTs. PMID:24495542

Problem decomposition by mutual information and force-based clustering

NASA Astrophysics Data System (ADS)

Otero, Richard Edward

The scale of engineering problems has sharply increased over the last twenty years. Larger coupled systems, increasing complexity, and limited resources create a need for methods that automatically decompose problems into manageable sub-problems by discovering and leveraging problem structure. The ability to learn the coupling (inter-dependence) structure and reorganize the original problem could lead to large reductions in the time to analyze complex problems. Such decomposition methods could also provide engineering insight on the fundamental physics driving problem solution. This work forwards the current state of the art in engineering decomposition through the application of techniques originally developed within computer science and information theory. The work describes the current state of automatic problem decomposition in engineering and utilizes several promising ideas to advance the state of the practice. Mutual information is a novel metric for data dependence and works on both continuous and discrete data. Mutual information can measure both the linear and non-linear dependence between variables without the limitations of linear dependence measured through covariance. Mutual information is also able to handle data that does not have derivative information, unlike other metrics that require it. The value of mutual information to engineering design work is demonstrated on a planetary entry problem. This study utilizes a novel tool developed in this work for planetary entry system synthesis. A graphical method, force-based clustering, is used to discover related sub-graph structure as a function of problem structure and links ranked by their mutual information. This method does not require the stochastic use of neural networks and could be used with any link ranking method currently utilized in the field. Application of this method is demonstrated on a large, coupled low-thrust trajectory problem. Mutual information also serves as the basis for an alternative global optimizer, called MIMIC, which is unrelated to Genetic Algorithms. Advancement to the current practice demonstrates the use of MIMIC as a global method that explicitly models problem structure with mutual information, providing an alternate method for globally searching multi-modal domains. By leveraging discovered problem inter- dependencies, MIMIC may be appropriate for highly coupled problems or those with large function evaluation cost. This work introduces a useful addition to the MIMIC algorithm that enables its use on continuous input variables. By leveraging automatic decision tree generation methods from Machine Learning and a set of randomly generated test problems, decision trees for which method to apply are also created, quantifying decomposition performance over a large region of the design space.

Cluster geometry and survival probability in systems driven by reaction diffusion dynamics

NASA Astrophysics Data System (ADS)

Windus, Alastair; Jensen, Henrik J.

2008-11-01

We consider a reaction-diffusion model incorporating the reactions A→phi, A→2A and 2A→3A. Depending on the relative rates for sexual and asexual reproduction of the quantity A, the model exhibits either a continuous or first-order absorbing phase transition to an extinct state. A tricritical point separates the two phase lines. While we comment on this critical behaviour, the main focus of the paper is on the geometry of the population clusters that form. We observe the different cluster structures that arise at criticality for the three different types of critical behaviour and show that there exists a linear relationship for the survival probability against initial cluster size at the tricritical point only.

Ligand Rearrangements at Fe/S Cofactors: Slow Isomerization of a Biomimetic [2Fe-2S] Cluster.

PubMed

Bergner, Marie; Roy, Lisa; Dechert, Sebastian; Neese, Frank; Ye, Shengfa; Meyer, Franc

2017-04-18

Ligand exchange plays an important role in the biogenesis of Fe/S clusters, most prominently during cluster transfer from a scaffold protein to its target protein. Although in vivo and in vitro studies have provided some insight into this process, the microscopic details of the ligand exchange steps are mostly unknown. In this work, the kinetics of the ligand rearrangement in a biomimetic [2Fe-2S] cluster with mixed S/N capping ligands have been studied. Two geometrical isomers of the cluster are present in solution, and mechanistic insight into the isomerization process was obtained by variable-temperature 1 H NMR spectroscopy. Combined experimental and computational results reveal that this is an associative process that involves the coordination of a solvent molecule to one of the ferric ions. The cluster isomerizes at least two orders of magnitude faster in its protonated and mixed-valent states. These findings may contribute to a deeper understanding of cluster transfer and sensing processes occurring in Fe/S cluster biogenesis. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Continuous Security and Configuration Monitoring of HPC Clusters

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

Garcia-Lomeli, H. D.; Bertsch, A. D.; Fox, D. M.

Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration managementmore » systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking can be managed from one central location.« less

Economic and Demographic Factors Impacting Placement of Students with Autism

ERIC Educational Resources Information Center

Kurth, Jennifer A.; Mastergeorge, Ann M.; Paschall, Katherine

2016-01-01

Educational placement of students with autism is often associated with child factors, such as IQ and communication skills. However, variability in placement patterns across states suggests that other factors are at play. This study used hierarchical cluster analysis techniques to identify demographic, economic, and educational covariates…

Comprehension priming as rational expectation for repetition: Evidence from syntactic processing.

PubMed

Myslín, Mark; Levy, Roger

2016-02-01

Why do comprehenders process repeated stimuli more rapidly than novel stimuli? We consider an adaptive explanation for why such facilitation may be beneficial: priming is a consequence of expectation for repetition due to rational adaptation to the environment. If occurrences of a stimulus cluster in time, given one occurrence it is rational to expect a second occurrence closely following. Leveraging such knowledge may be particularly useful in online processing of language, where pervasive clustering may help comprehenders negotiate the considerable challenge of continual expectation update at multiple levels of linguistic structure and environmental variability. We test this account in the domain of structural priming in syntax, making use of the sentential complement-direct object (SC-DO) ambiguity. We first show that sentences containing SC continuations cluster in natural language, motivating an expectation for repetition of this structure. Second, we show that comprehenders are indeed sensitive to the syntactic clustering properties of their current environment. In a series of between-groups self-paced reading studies, we find that participants who are exposed to clusters of SC sentences subsequently process repetitions of SC structure more rapidly than participants who are exposed to the same number of SCs spaced in time, and attribute the difference to the learned degree of expectation for repetition. We model this behavior through Bayesian belief update, showing that (the optimal degree of) sensitivity to clustering properties of syntactic structures is indeed learnable through experience. Comprehension priming effects are thus consistent with rational expectation for repetition based on adaptation to the linguistic environment. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Comprehension priming as rational expectation for repetition: Evidence from syntactic processing

PubMed Central

Levy, Roger

2015-01-01

Why do comprehenders process repeated stimuli more rapidly than novel stimuli? We consider an adaptive explanation for why such facilitation may be beneficial: priming is a consequence of expectation for repetition due to rational adaptation to the environment. If occurrences of a stimulus cluster in time, given one occurrence it is rational to expect a second occurrence closely following. Leveraging such knowledge may be particularly useful in online processing of language, where pervasive clustering may help comprehenders negotiate the considerable challenge of continual expectation update at multiple levels of linguistic structure and environmental variability. We test this account in the domain of structural priming in syntax, making use of the sentential complement-direct object (SC-DO) ambiguity. We first show that sentences containing SC continuations cluster in natural language, motivating an expectation for repetition of this structure. Second, we show that comprehenders are indeed sensitive to the syntactic clustering properties of their current environment. In a series of between-groups self-paced reading studies, we find that participants who are exposed to clusters of SC sentences subsequently process repetitions of SC structure more rapidly than participants who are exposed to the same number of SCs spaced in time, and attribute the difference to the learned degree of expectation for repetition. We model this behavior through Bayesian belief update, showing that (the optimal degree of) sensitivity to clustering properties of syntactic structures is indeed learnable through experience. Comprehension priming effects are thus consistent with rational expectation for repetition based on adaptation to the linguistic environment. PMID:26605963

Continuous-variable entanglement and quantum-state teleportation between optical and macroscopic vibrational modes through radiation pressure

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

Pirandola, Stefano; Mancini, Stefano; Vitali, David

2003-12-01

We study an isolated, perfectly reflecting, mirror illuminated by an intense laser pulse. We show that the resulting radiation pressure efficiently entangles a mirror vibrational mode with the two reflected optical sideband modes of the incident carrier beam. The entanglement of the resulting three-mode state is studied in detail and it is shown to be robust against the mirror mode temperature. We then show how this continuous-variable entanglement can be profitably used to teleport an unknown quantum state of an optical mode onto the vibrational mode of the mirror.

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.

Relaxation dynamics of maximally clustered networks

NASA Astrophysics Data System (ADS)

Klaise, Janis; Johnson, Samuel

2018-01-01

We study the relaxation dynamics of fully clustered networks (maximal number of triangles) to an unclustered state under two different edge dynamics—the double-edge swap, corresponding to degree-preserving randomization of the configuration model, and single edge replacement, corresponding to full randomization of the Erdős-Rényi random graph. We derive expressions for the time evolution of the degree distribution, edge multiplicity distribution and clustering coefficient. We show that under both dynamics networks undergo a continuous phase transition in which a giant connected component is formed. We calculate the position of the phase transition analytically using the Erdős-Rényi phenomenology.

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.

Analysis of suicide mortality in Brazil: spatial distribution and socioeconomic context.

PubMed

Dantas, Ana P; Azevedo, Ulicélia N de; Nunes, Aryelly D; Amador, Ana E; Marques, Marilane V; Barbosa, Isabelle R

2018-01-01

To perform a spatial analysis of suicide mortality and its correlation with socioeconomic indicators in Brazilian municipalities. This is an ecological study with Brazilian municipalities as a unit of analysis. Data on deaths from suicide and contextual variables were analyzed. The spatial distribution, intensity and significance of the clusters were analyzed with the global Moran index, MoranMap and local indicators of spatial association (LISA), seeking to identify patterns through geostatistical analysis. A total of 50,664 deaths from suicide were registered in Brazil between 2010 and 2014. The average suicide mortality rate in Brazil was 5.23/100,000 population. The Brazilian municipalities presenting the highest rates were Taipas do Tocantins, state of Tocantins (79.68 deaths per 100,000 population), Itaporã, state of Mato Grosso do Sul (75.15 deaths per 100,000 population), Mampituba, state of Rio Grande do Sul (52.98 deaths per 100,000 population), Paranhos, state of Mato Grosso do Sul (52.41 deaths per 100,000 population), and Monjolos, state of Minas Gerais (52.08 deaths per 100,000 population). Although weak spatial autocorrelation was observed for suicide mortality (I = 0.2608), there was a formation of clusters in the South. In the bivariate spatial and classical analysis, no correlation was observed between suicide mortality and contextual variables. Suicide mortality in Brazil presents a weak spatial correlation and low or no spatial relationship with socioeconomic factors.

Identification and Description of Healthcare Customer Communication Patterns Among Individuals with Diabetes in Clalit Health Services: A Retrospective Database Study.

PubMed

Benis, Arriel; Harel, Nissim; Barkan, Refael; Sela, Tomer; Feldman, Becca

2017-01-01

HMOs record medical data and their interactions with patients. Using this data we strive to identify sub-populations of healthcare customers based on their communication patterns and characterize these sub-populations by their socio-demographic, medical, treatment effectiveness, and treatment adherence profiles. This work will be used to develop tools and interventions aimed at improving patient care. The process included: (1) Extracting socio-demographic, clinical, laboratory, and communication data of 309,460 patients with diabetes in 2015, aged 32+ years, having 7+ years of the disease treated by Clalit Healthcare Services; (2) Reducing dimensions of continuous variables; (3) Finding the K communication-patterns clusters; (4) Building a hierarchical clustering and its associated heatmap to summarize the discovered clusters; (5) Analyzing the clusters found; (6) Validating results epidemiologically. Such a process supports understanding different communication-channel usage and the implementation of personalized services focusing on patients' needs and preferences.

The WIYN Open Cluster Study: A 15-Year Report

NASA Astrophysics Data System (ADS)

Mathieu, Robert D.; WOCS Collaboration

2013-06-01

The WIYN 3.5m telescope combines large aperture, wide field of view and superb image quality. The WIYN consortium includes investigators in numerous areas of open cluster research. The combination spawned the WIYN Open Cluster Study (WOCS) over a decade ago, with the goals of producing 1) comprehensive photometric, astrometric and spectroscopic data for new fundamental open clusters and 2) addressing key astrophysical problems with these data. The set of core WOCS open clusters spans age and metallicity. Low reddening, solar proximity and richness were also desirable features in selecting core open clusters. More than 50 WIYN Open Cluster Study papers have been published in refereed journals. Highlights include: deep and wide-field photometry of NGC 188, NGC 2168 (M35), and NGC 6819 (WOCS I, II, XI and LII); deep and wide-field proper-motion studies of the old open clusters NGC 188, NGC 2682 (M67) and NGC 6791 (WOCS XVII, XXXIII and XLVI); comprehensive radial-velocity surveys of NGC 188, NGC 2168 and NGC 6819 (WOCS XXXII, XXIV, and XXXVIII); metallicity and lithium abundances in NGC 2168 (WOCS V); comprehensive definition of the hard-binary populations of NGC 188 and NGC 2168 (WOCS XXII and XLVIII); rotation period distributions in NGC 1039 (M34) and NGC 2168 (WOCS XXXV, XLIII, and XLV); study of chromospheric activity in NGC 2682 (WOCS XVIII); photometric variability surveys in NGC 188 and NGC 2682 (IX and XV); new Bayesian techniques for determination of cluster parameters (WOCS XXIII); a new infrared age-diagnostic for open clusters (WOCS XL); theoretical studies of stellar rotation (WOCS XIII and XIV); sophisticated N-body simulations of NGC 188 (WOCS LI); and the discovery of a high binary frequency and white dwarf companions among NGC 188 blue stragglers. While the WIYN 3.5m telescope remains at its heart, today the WIYN Open Cluster Study collaboration extends beyond both the WIYN observatory and consortium, and continues as a vital and productive exploration into these fundamental stellar systems. Publication list can be found at http://www.astro.ufl.edu ata/wocs/pubs.html. The WIYN Open Cluster Study has been continuously supported by grants from the National Science Foundation.

Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States

PubMed Central

Trout Fryxell, R. T.; Moore, J. E.; Collins, M. D.; Kwon, Y.; Jean-Philippe, S. R.; Schaeffer, S. M.; Odoi, A.; Kennedy, M.; Houston, A. E.

2015-01-01

Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum) and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis). There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas. PMID:26656122

CTPPL: A Continuous Time Probabilistic Programming Language

DTIC Science & Technology

2009-07-01

recent years there has been a flurry of interest in continuous time models, mostly focused on continuous time Bayesian networks ( CTBNs ) [Nodelman, 2007... CTBNs are built on homogenous Markov processes. A homogenous Markov pro- cess is a finite state, continuous time process, consisting of an initial...q1 : xn()] ... Some state transitions can produce emissions. In a CTBN , each variable has a conditional inten- sity matrix Qu for every combination of

A Variable-Selection Heuristic for K-Means Clustering.

ERIC Educational Resources Information Center

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Observation of two-photon interference with continuous variables by homodyne detection

NASA Astrophysics Data System (ADS)

Wu, Daohua; Kawamoto, Kota; Guo, Xiaomin; Kasai, Katsuyuki; Watanabe, Masayoshi; Zhang, Yun

2017-10-01

We experimentally observed a two-photon interference between a squeezed vacuum state from an optical parametric amplifier and a weak coherent state on a beam splitter with continuous variables. The photon statistics properties of the mixed field were investigated by calculating the correlations among four permutations of measured quadratures components, which were obtained by two homodyne detection systems. This also means that the two-photon interference occurred at analysis frequency differing from the previous two-photon interference reports. The nonclassical effect of photon anti-bunching occurred when an amplitude squeezed vacuum state acted as one of interference sources. On the other hand, the photon bunching effect appeared when a phase squeezed vacuum state was employed.

Evaluating physical habitat and water chemistry data from statewide stream monitoring programs to establish least-impacted conditions in Washington State

USGS Publications Warehouse

Wilmoth, Siri K.; Irvine, Kathryn M.; Larson, Chad

2015-01-01

Various GIS-generated land-use predictor variables, physical habitat metrics, and water chemistry variables from 75 reference streams and 351 randomly sampled sites throughout Washington State were evaluated for effectiveness at discriminating reference from random sites within level III ecoregions. A combination of multivariate clustering and ordination techniques were used. We describe average observed conditions for a subset of predictor variables as well as proposing statistical criteria for establishing reference conditions for stream habitat in Washington. Using these criteria, we determined whether any of the random sites met expectations for reference condition and whether any of the established reference sites failed to meet expectations for reference condition. Establishing these criteria will set a benchmark from which future data will be compared.

Linear self-focusing of continuous UV laser beam in photo-thermo-refractive glasses.

PubMed

Sidorov, Alexander I; Gorbyak, Veronika V; Nikonorov, Nikolay V

2018-03-19

The experimental and theoretical study of continuous UV laser beam propagation through thick silver-containing photo-thermo-refractive glass is presented. It is shown for the first time that self-action of UV Gaussian beam in glass results in its self-focusing. The observed linear effect is non-reversible and is caused by the transformation of subnanosized charged silver molecular clusters to neutral state under UV laser radiation. Such transformation is accompanied by the increase of molecular clusters polarizability and the refractive index increase in irradiated area. As a result, an extended positive lens is formed in glass bulk. In a theoretical study of linear self-focusing effect, the "aberration-free" approximation was used, taking into account spatial distribution of induced absorption.

Cluster analysis applied to the spatial and temporal variability of monthly rainfall in Mato Grosso do Sul State, Brazil

NASA Astrophysics Data System (ADS)

Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; da Cunha, Elias Rodrigues; Correa, Caio Cezar Guedes; Torres, Francisco Eduardo; Bacani, Vitor Matheus; Gois, Givanildo; Ribeiro, Larissa Pereira

2016-04-01

The State of Mato Grosso do Sul (MS) located in Brazil Midwest is devoid of climatological studies, mainly in the characterization of rainfall regime and producers' meteorological systems and rain inhibitors. This state has different soil and climatic characteristics distributed among three biomes: Cerrado, Atlantic Forest and Pantanal. This study aimed to apply the cluster analysis using Ward's algorithm and identify those meteorological systems that affect the rainfall regime in the biomes. The rainfall data of 32 stations (sites) of the MS State were obtained from the Agência Nacional de Águas (ANA) database, collected from 1954 to 2013. In each of the 384 monthly rainfall temporal series was calculated the average and applied the Ward's algorithm to identify spatial and temporal variability of rainfall. Bartlett's test revealed only in January homogeneous variance at all sites. Run test showed that there was no increase or decrease in trend of monthly rainfall. Cluster analysis identified five rainfall homogeneous regions in the MS State, followed by three seasons (rainy, transitional and dry). The rainy season occurs during the months of November, December, January, February and March. The transitional season ranges between the months of April and May, September and October. The dry season occurs in June, July and August. The groups G1, G4 and G5 are influenced by South Atlantic Subtropical Anticyclone (SASA), Chaco's Low (CL), Bolivia's High (BH), Low Levels Jet (LLJ) and South Atlantic Convergence Zone (SACZ) and Maden-Julian Oscillation (MJO). Group G2 is influenced by Upper Tropospheric Cyclonic Vortex (UTCV) and Front Systems (FS). The group G3 is affected by UTCV, FS and SACZ. The meteorological systems' interaction that operates in each biome and the altitude causes the rainfall spatial and temporal diversity in MS State.

Progressive reactivation of the volcanic plumbing system beneath Tolbachik volcano (Kamchatka, Russia) revealed by long-period seismicity

NASA Astrophysics Data System (ADS)

Frank, William B.; Shapiro, Nikolaï M.; Gusev, Alexander A.

2018-07-01

After lying dormant for 36 yr, the Tolbachik volcano of the Klyuchevskoy group started to erupt on 27 November 2012. We investigate the preparatory phase of this eruption via a statistical analysis of the temporal behavior of long-period (LP) earthquakes that occurred beneath this volcanic system. The LP seismicity occurs close to the surface beneath the main volcanic edifices and at 30 km depth in the vicinity of a deep magmatic reservoir. The deep LP earthquakes and those beneath the Klyuchevskoy volcano occur quasi-periodically, while the LP earthquakes beneath Tolbachik are clustered in time. As the seismicity rate increased beneath Tolbachik days before the eruption, the level of the time clustering decreased. We interpret this as a manifestation of the evolution of the volcano plumbing system. We suggest that when a plumbing system awakes after quiescence, multiple cracks and channels are reactivated simultaneously and their interaction results in the strong time clustering of LP earthquakes. With time, this network of channels and cracks evolves into a more stable state with an overall increased permeability, where fluids flow uninhibited throughout the plumbing system except for a few remaining impediments that continue to generate seismic radiation. The inter-seismic source interaction and the level of earthquake time clustering in this latter state is weak. This scenario suggests that the observed evolution of the statistical behavior of the shallow LP seismicity beneath Tolbachik is an indicator of the reactivation and consolidation of the near-surface plumbing system prior to the Tolbachik eruption. The parts of the plumbing system above the deep magmatic reservoir and beneath the Klyuchevskoy volcano remain in nearly permanent activity, as demonstrated by the continuous occurrence of the deep LP earthquakes and very frequent Klyuchevskoy eruptions. This implies that these parts of the plumbing system remain in a stable permeable state and contain a few weakly interacting seismogenic sources. Our results provide new constraints on future mechanical models of the magmatic plumbing systems and demonstrate that the level of time clustering of LP earthquakes can be a useful parameter to infer information about the state of the plumbing system.

Spatiotemporal Analysis of Corn Phenoregions in the Continental United States

NASA Astrophysics Data System (ADS)

Konduri, V. S.; Kumar, J.; Hoffman, F. M.; Ganguly, A. R.; Hargrove, W. W.

2017-12-01

The delineation of regions exhibiting similar crop performance has potential benefits for agricultural planning and management, policymaking and natural resource conservation. Studies of natural ecosystems have used multivariate clustering algorithms based on environmental characteristics to identify ecoregions for species range prediction and habitat conservation. However, few studies have used clustering to delineate regions based on crop phenology. The aim of this study was to perform a spatiotemporal analysis of phenologically self-similar clusters, or phenoregions, for the major corn growing areas in the Continental United States (CONUS) for the period 2008-2016. Annual trajectories of remotely sensed normalized difference vegetation index (NDVI), a useful proxy for land surface phenology, derived from Moderate Resolution Spectroradiometer (MODIS) instruments at 8-day intervals and 250 m resolution was used as the phenological metric. Because of the large data volumes involved, the phenoregion delineation was performed using a highly scalable, unsupervised clustering technique with the help of high performance computing. These phenoregions capture the spatial variability in the timing of important crop phenological stages (like emergence and maturity dates) and thus could be used to develop more accurate parameterizations for crop models applied at regional to global scales. Moreover, historical crop performance from phenoregions, in combination with climate and soils data, could be used to improve production forecasts. The temporal variability in NDVI at each location could also be used to develop an early warning system to identify locations where the crop deviates from its expected phenological behavior. Such deviations may indicate a need for irrigation or fertilization or suggest where pest outbreaks or other disturbances have occurred.

Pigs in Space: Determining the Environmental Justice Landscape of Swine Concentrated Animal Feeding Operations (CAFOs) in Iowa

PubMed Central

Carrel, Margaret; Young, Sean G.; Tate, Eric

2016-01-01

Given the primacy of Iowa in pork production for the U.S. and global markets, we sought to understand if the same relationship with traditional environmental justice (EJ) variables such as low income and minority populations observed in other concentrated animal feeding operation (CAFO) studies exists in the relationship with swine CAFO densities in Iowa. We examined the potential for spatial clustering of swine CAFOs in certain parts of the state and used spatial regression techniques to determine the relationships of high swine concentrations to these EJ variables. We found that while swine CAFOs do cluster in certain regions and watersheds of Iowa, these high densities of swine are not associated with traditional EJ populations of low income and minority race/ethnicity. Instead, the potential for environmental injustice in the negative impacts of intensive swine production require a more complex appraisal. The clustering of swine production in watersheds, the presence of antibiotics used in swine production in public waterways, the clustering of manure spills, and other findings suggest that a more literal and figurative “downstream” approach is necessary. We document the presence and location of antibiotics used in animal production in the public waterways of the state. At the same time, we suggest a more “upstream” understanding of the structural, political and economic factors that create an environmentally unjust landscape of swine production in Iowa and the Upper Midwest is also crucial. Finally, we highlight the important role of publicly accessible and high quality data in the analysis of these upstream and downstream EJ questions. PMID:27571091

Prediction of sea ice thickness cluster in the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Fuckar, Neven-Stjepan; Guemas, Virginie; Johnson, Nathaniel; Doblas-Reyes, Francisco

2016-04-01

Sea ice thickness (SIT) has a potential to contain substantial climate memory and predictability in the northern hemisphere (NH) sea ice system. We use 5-member NH SIT, reconstructed with an ocean-sea-ice general circulation model (NEMOv3.3 with LIM2) with a simple data assimilation routine, to determine NH SIT modes of variability disentangled from the long-term climate change. Specifically, we apply the K-means cluster analysis - one of nonhierarchical clustering methods that partition data into modes or clusters based on their distances in the physical - to determine optimal number of NH SIT clusters (K=3) and their historical variability. To examine prediction skill of NH SIT clusters in EC-Earth2.3, a state-of-the-art coupled climate forecast system, we use 5-member ocean and sea ice initial conditions (IC) from the same ocean-sea-ice historical reconstruction and atmospheric IC from ERA-Interim reanalysis. We focus on May 1st and Nov 1st start dates from 1979 to 2010. Common skill metrics of probability forecast, such as rank probability skill core and ROC (relative operating characteristics - hit rate versus false alarm rate) and reliability diagrams show that our dynamical model predominately perform better than the 1st order Marko chain forecast (that beats climatological forecast) over the first forecast year. On average May 1st start dates initially have lower skill than Nov 1st start dates, but their skill is degraded at slower rate than skill of forecast started on Nov 1st.

Revealing the first uridyl peptide antibiotic biosynthetic gene cluster and probing pacidamycin biosynthesis.

PubMed

Rackham, Emma J; Grüschow, Sabine; Goss, Rebecca J M

2011-01-01

There is an urgent need for new antibiotics with resistance continuing to emerge toward existing classes. The pacidamycin antibiotics possess a novel scaffold and exhibit unexploited bioactivity rendering them attractive research targets. We recently reported the first identification of a biosynthetic cluster encoding uridyl peptide antibiotic assembly and the engineering of pacidamycin biosynthesis into a heterologous host. We report here our methods toward identifying the biosynthetic cluster. Our initial experiments employed conventional methods of probing a cosmid library using PCR and Southern blotting, however it became necessary to adopt a state-of-the-art genome scanning  and in silico hybridization approach  to pin point the cluster. Here we describe our "real" and "virtual" probing methods and contrast the benefits and pitfalls of each approach. 

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.

Network Disruption in the Preclinical Stages of Alzheimer's Disease: From Subjective Cognitive Decline to Mild Cognitive Impairment.

PubMed

López-Sanz, David; Garcés, Pilar; Álvarez, Blanca; Delgado-Losada, María Luisa; López-Higes, Ramón; Maestú, Fernando

2017-12-01

Subjective Cognitive Decline (SCD) is a largely unknown state thought to represent a preclinical stage of Alzheimer's Disease (AD) previous to mild cognitive impairment (MCI). However, the course of network disruption in these stages is scarcely characterized. We employed resting state magnetoencephalography in the source space to calculate network smallworldness, clustering, modularity and transitivity. Nodal measures (clustering and node degree) as well as modular partitions were compared between groups. The MCI group exhibited decreased smallworldness, clustering and transitivity and increased modularity in theta and beta bands. SCD showed similar but smaller changes in clustering and transitivity, while exhibiting alterations in the alpha band in opposite direction to those showed by MCI for modularity and transitivity. At the node level, MCI disrupted both clustering and nodal degree while SCD showed minor changes in the latter. Additionally, we observed an increase in modular partition variability in both SCD and MCI in theta and beta bands. SCD elders exhibit a significant network disruption, showing intermediate values between HC and MCI groups in multiple parameters. These results highlight the relevance of cognitive concerns in the clinical setting and suggest that network disorganization in AD could start in the preclinical stages before the onset of cognitive symptoms.

Investigating the Spatial Dimension of Food Access.

PubMed

Yenerall, Jackie; You, Wen; Hill, Jennie

2017-08-02

The purpose of this article is to investigate the sensitivity of food access models to a dataset's spatial distribution and the empirical definition of food access, which contributes to understanding the mixed findings of previous studies. Data was collected in the Dan River Region in the United States using a telephone survey for individual-level variables ( n = 784) and a store audit for the location of food retailers and grocery store quality. Spatial scanning statistics assessed the spatial distribution of obesity and detected a cluster of grocery stores overlapping with a cluster of obesity centered on a grocery store suggesting that living closer to a grocery store increased the likelihood of obesity. Logistic regression further examined this relationship while controlling for demographic and other food environment variables. Similar to the cluster analysis results, increased distance to a grocery store significantly decreased the likelihood of obesity in the urban subsample (average marginal effects, AME = -0.09, p -value = 0.02). However, controlling for grocery store quality nullified these results (AME = -0.12, p -value = 0.354). Our findings suggest that measuring grocery store accessibility as the distance to the nearest grocery store captures variability in the spatial distribution of the health outcome of interest that may not reflect a causal relationship between the food environment and health.

Clusters of Healthy and Unhealthy Eating Behaviors are Associated with Body Mass Index Among Adults

PubMed Central

Heerman, William J.; Jackson, Natalie; Hargreaves, Margaret; Mulvaney, Shelagh A.; Schlundt, David; Wallston, Kenneth A.; Rothman, Russell L.

2017-01-01

Objective To identify eating styles from 6 eating behaviors and test their association with Body Mass Index (BMI) among adults. Design Cross-sectional analysis of self-report survey data Setting 12 primary care and specialty clinics in 5 states Participants 11,776 adult patients consented to participate; 9,977 completed survey questions. Variables measured Frequency of eating healthy food; frequency of eating unhealthy food; breakfast frequency; frequency of snacking; overall diet quality; and problem eating behaviors. The primary dependent variable was BMI, calculated from self-reported height and weight data. Analysis Kmeans cluster analysis of eating behaviors was used to determine eating styles. A categorical variable representing each eating style cluster was entered in a multivariate linear regression predicting BMI, controlling for covariates. Results Four eating styles were identified and defined by healthy vs. unhealthy diet patterns and engagement in problem eating behaviors. Each group had significantly higher average BMI than the healthy eating style: healthy with problem eating behaviors (β=1.9, p<0.001); unhealthy (β=2.5, p<0.001), and unhealthy with problem eating behaviors (β=5.1, p<0.001). Conclusions Future attempts to improve eating styles should address not only the consumption of healthy foods, but also snacking behaviors and the emotional component of eating. PMID:28363804

Investigating the Spatial Dimension of Food Access

PubMed Central

Yenerall, Jackie; You, Wen

2017-01-01

The purpose of this article is to investigate the sensitivity of food access models to a dataset’s spatial distribution and the empirical definition of food access, which contributes to understanding the mixed findings of previous studies. Data was collected in the Dan River Region in the United States using a telephone survey for individual-level variables (n = 784) and a store audit for the location of food retailers and grocery store quality. Spatial scanning statistics assessed the spatial distribution of obesity and detected a cluster of grocery stores overlapping with a cluster of obesity centered on a grocery store suggesting that living closer to a grocery store increased the likelihood of obesity. Logistic regression further examined this relationship while controlling for demographic and other food environment variables. Similar to the cluster analysis results, increased distance to a grocery store significantly decreased the likelihood of obesity in the urban subsample (average marginal effects, AME = −0.09, p-value = 0.02). However, controlling for grocery store quality nullified these results (AME = −0.12, p-value = 0.354). Our findings suggest that measuring grocery store accessibility as the distance to the nearest grocery store captures variability in the spatial distribution of the health outcome of interest that may not reflect a causal relationship between the food environment and health. PMID:28767093

Cluster Analysis to Identify Possible Subgroups in Tinnitus Patients.

PubMed

van den Berge, Minke J C; Free, Rolien H; Arnold, Rosemarie; de Kleine, Emile; Hofman, Rutger; van Dijk, J Marc C; van Dijk, Pim

2017-01-01

In tinnitus treatment, there is a tendency to shift from a "one size fits all" to a more individual, patient-tailored approach. Insight in the heterogeneity of the tinnitus spectrum might improve the management of tinnitus patients in terms of choice of treatment and identification of patients with severe mental distress. The goal of this study was to identify subgroups in a large group of tinnitus patients. Data were collected from patients with severe tinnitus complaints visiting our tertiary referral tinnitus care group at the University Medical Center Groningen. Patient-reported and physician-reported variables were collected during their visit to our clinic. Cluster analyses were used to characterize subgroups. For the selection of the right variables to enter in the cluster analysis, two approaches were used: (1) variable reduction with principle component analysis and (2) variable selection based on expert opinion. Various variables of 1,783 tinnitus patients were included in the analyses. Cluster analysis (1) included 976 patients and resulted in a four-cluster solution. The effect of external influences was the most discriminative between the groups, or clusters, of patients. The "silhouette measure" of the cluster outcome was low (0.2), indicating a "no substantial" cluster structure. Cluster analysis (2) included 761 patients and resulted in a three-cluster solution, comparable to the first analysis. Again, a "no substantial" cluster structure was found (0.2). Two cluster analyses on a large database of tinnitus patients revealed that clusters of patients are mostly formed by a different response of external influences on their disease. However, both cluster outcomes based on this dataset showed a poor stability, suggesting that our tinnitus population comprises a continuum rather than a number of clearly defined subgroups.

Planck Cosmology, Planck Clusters, and What is to Come

NASA Astrophysics Data System (ADS)

Rozo, Eduardo

2015-08-01

Planck's view of the Cosmic Microwave Background (CMB) has ushered in a new era of precision cosmology. In the process, hints of tension with local universe cosmological probes have appeared, including not only tension between the CMB and local Hubble constant measurements, but between the CMB and Planck's own analysis of the SZ galaxy clusters discovered by Planck. We will discuss the state of cluster cosmology in light of these results, and comment on what is to come. Should these tensions continue to exist with ever future measurements of ever increasing precision, the current Planck results will stand as some of the first lines of evidence towards finally breaking the standard LCDM cosmological model!

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.

Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

Eight different variable selection techniques for model-based and non-model-based clustering are evaluated across a wide range of cluster structures. It is shown that several methods have difficulties when non-informative variables (i.e., random noise) are included in the model. Furthermore, the distribution of the random noise greatly impacts the…

Assessment of economic status in trauma registries: A new algorithm for generating population-specific clustering-based models of economic status for time-constrained low-resource settings.

PubMed

Eyler, Lauren; Hubbard, Alan; Juillard, Catherine

2016-10-01

Low and middle-income countries (LMICs) and the world's poor bear a disproportionate share of the global burden of injury. Data regarding disparities in injury are vital to inform injury prevention and trauma systems strengthening interventions targeted towards vulnerable populations, but are limited in LMICs. We aim to facilitate injury disparities research by generating a standardized methodology for assessing economic status in resource-limited country trauma registries where complex metrics such as income, expenditures, and wealth index are infeasible to assess. To address this need, we developed a cluster analysis-based algorithm for generating simple population-specific metrics of economic status using nationally representative Demographic and Health Surveys (DHS) household assets data. For a limited number of variables, g, our algorithm performs weighted k-medoids clustering of the population using all combinations of g asset variables and selects the combination of variables and number of clusters that maximize average silhouette width (ASW). In simulated datasets containing both randomly distributed variables and "true" population clusters defined by correlated categorical variables, the algorithm selected the correct variable combination and appropriate cluster numbers unless variable correlation was very weak. When used with 2011 Cameroonian DHS data, our algorithm identified twenty economic clusters with ASW 0.80, indicating well-defined population clusters. This economic model for assessing health disparities will be used in the new Cameroonian six-hospital centralized trauma registry. By describing our standardized methodology and algorithm for generating economic clustering models, we aim to facilitate measurement of health disparities in other trauma registries in resource-limited countries. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Molecular dynamics investigation of dynamical heterogeneity and local structure in the supercooled liquid and glass states of Al

NASA Astrophysics Data System (ADS)

Li, Maozhi; Wang, Cai-Zhuang; Mendelev, Mikhail I.; Ho, Kai-Ming

2008-05-01

Molecular dynamics simulations are performed to study the structure and dynamical heterogeneity in the liquid and glass states of Al using a frequently employed embedded atom potential. While the pair correlation function of the glass and liquid states displays only minor differences, the icosahedral short-range order (ISRO) and the dynamics of the two states are very different. The ISRO is much stronger in the glass than in the liquid. It is also found that both the most mobile and the most immobile atoms in the glass state tend to form clusters, and the clusters formed by the immobile atoms are more compact. In order to investigate the local environment of each atom in the liquid and glass states, a local density is defined to characterize the local atomic packing. There is a strong correlation between the local packing density and the mobility of the atoms. These results indicate that dynamical heterogeneity in glasses is directly correlated to the local structure. We also analyze the diffusion mechanisms of atoms in the liquid and glass states. It is found that for the mobile atoms in the glass state, initially they are confined in the cages formed by their nearest neighbors and vibrating. On the time scale of β relaxation, the mobile atoms try to break up the cage confinement and hop into new cages. In the supercooled liquid states, however, atoms continuously diffuse. Furthermore, it is found that on the time scale of β relaxation, some of the mobile atoms in the glass state cooperatively hop, which is facilitated by the stringlike cluster structures. On the longer time scale, it is found that a certain fraction of atoms can simultaneously hop, although they are not nearest neighbors. Further analysis shows that these hopping atoms form big and more compact clusters than the characterized most mobile atoms. The cooperative rearrangement of these big compact clusters might facilitate the simultaneous hopping of atoms in the glass states on the long time scale.

Entanglement transfer from two-mode continuous variable SU(2) cat states to discrete qubits systems in Jaynes-Cummings Dimers

PubMed Central

Ran, Du; Hu, Chang-Sheng; Yang, Zhen-Biao

2016-01-01

We study the entanglement transfer from a two-mode continuous variable system (initially in the two-mode SU(2) cat states) to a couple of discrete two-state systems (initially in an arbitrary mixed state), by use of the resonant Jaynes-Cummings (JC) interaction. We first quantitatively connect the entanglement transfer to non-Gaussianity of the two-mode SU(2) cat states and find a positive correlation between them. We then investigate the behaviors of the entanglement transfer and find that it is dependent on the initial state of the discrete systems. We also find that the largest possible value of the transferred entanglement exhibits a variety of behaviors for different photon number as well as for the phase angle of the two-mode SU(2) cat states. We finally consider the influences of the noise on the transferred entanglement. PMID:27553881

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.

Are dark energy models with variable EoS parameter w compatible with the late inhomogeneous Universe?

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

Akarsu, Özgür; Bouhmadi-López, Mariam; Brilenkov, Maxim

We study the late-time evolution of the Universe where dark energy (DE) is presented by a barotropic fluid on top of cold dark matter (CDM) . We also take into account the radiation content of the Universe. Here by the late stage of the evolution we refer to the epoch where CDM is already clustered into inhomogeneously distributed discrete structures (galaxies, groups and clusters of galaxies). Under this condition the mechanical approach is an adequate tool to study the Universe deep inside the cell of uniformity. More precisely, we study scalar perturbations of the FLRW metric due to inhomogeneities ofmore » CDM as well as fluctuations of radiation and DE. For an arbitrary equation of state for DE we obtain a system of equations for the scalar perturbations within the mechanical approach. First, in the case of a constant DE equation of state parameter w, we demonstrate that our method singles out the cosmological constant as the only viable dark energy candidate. Then, we apply our approach to variable equation of state parameters in the form of three different linear parametrizations of w, e.g., the Chevallier-Polarski-Linder perfect fluid model. We conclude that all these models are incompatible with the theory of scalar perturbations in the late Universe.« less

Quantitative Tomography for Continuous Variable Quantum Systems

NASA Astrophysics Data System (ADS)

Landon-Cardinal, Olivier; Govia, Luke C. G.; Clerk, Aashish A.

2018-03-01

We present a continuous variable tomography scheme that reconstructs the Husimi Q function (Wigner function) by Lagrange interpolation, using measurements of the Q function (Wigner function) at the Padua points, conjectured to be optimal sampling points for two dimensional reconstruction. Our approach drastically reduces the number of measurements required compared to using equidistant points on a regular grid, although reanalysis of such experiments is possible. The reconstruction algorithm produces a reconstructed function with exponentially decreasing error and quasilinear runtime in the number of Padua points. Moreover, using the interpolating polynomial of the Q function, we present a technique to directly estimate the density matrix elements of the continuous variable state, with only a linear propagation of input measurement error. Furthermore, we derive a state-independent analytical bound on this error, such that our estimate of the density matrix is accompanied by a measure of its uncertainty.

Path Entanglement of Continuous-Variable Quantum Microwaves

NASA Astrophysics Data System (ADS)

Menzel, E. P.; Deppe, F.; Eder, P.; Zhong, L.; Haeberlein, M.; Baust, A.; Hoffmann, E.; Marx, A.; Gross, R.; di Candia, R.; Solano, E.; Ballester, D.; Ihmig, M.; Inomata, K.; Yamamoto, T.; Nakamura, Y.

2013-03-01

Entanglement is a quantum mechanical phenomenon playing a key role in quantum communication and information processing protocols. Here, we report on frequency-degenerate entanglement between continuous-variable quantum microwaves propagating along two separated paths. In our experiment, we combine a squeezed and a vacuum state via a beam splitter. Overcoming the challenges imposed by the low photon energies in the microwave regime, we reconstruct the squeezed state and, independently from this, detect and quantify the produced entanglement via correlation measurements (E. P. Menzel et al., arXiv:1210.4413). Our work paves the way towards quantum communication and teleportation with continuous variables in the microwave regime. This work is supported by SFB 631, German Excellence Initiative via NIM, EU projects SOLID, CCQED and PROMISCE, MEXT Kakenhi ``Quantum Cybernetics'', JSPS FIRST Program, the NICT Commissioned Research, EPSRC EP/H050434/1, Basque Government IT472-10, and Spanish MICINN FIS2009-12773-C02-01.

Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach.

PubMed

Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan

2018-08-01

Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1-2, 3-8, and 9-13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and North Atlantic Oscillation (NAO), indeces. The results revealed that all climatic features except NAO influenced precipitation in Iran during the 1960-2010 period. Copyright © 2018 Elsevier Inc. All rights reserved.

Sorting Five Human Tumor Types Reveals Specific Biomarkers and Background Classification Genes.

PubMed

Roche, Kimberly E; Weinstein, Marvin; Dunwoodie, Leland J; Poehlman, William L; Feltus, Frank A

2018-05-25

We applied two state-of-the-art, knowledge independent data-mining methods - Dynamic Quantum Clustering (DQC) and t-Distributed Stochastic Neighbor Embedding (t-SNE) - to data from The Cancer Genome Atlas (TCGA). We showed that the RNA expression patterns for a mixture of 2,016 samples from five tumor types can sort the tumors into groups enriched for relevant annotations including tumor type, gender, tumor stage, and ethnicity. DQC feature selection analysis discovered 48 core biomarker transcripts that clustered tumors by tumor type. When these transcripts were removed, the geometry of tumor relationships changed, but it was still possible to classify the tumors using the RNA expression profiles of the remaining transcripts. We continued to remove the top biomarkers for several iterations and performed cluster analysis. Even though the most informative transcripts were removed from the cluster analysis, the sorting ability of remaining transcripts remained strong after each iteration. Further, in some iterations we detected a repeating pattern of biological function that wasn't detectable with the core biomarker transcripts present. This suggests the existence of a "background classification" potential in which the pattern of gene expression after continued removal of "biomarker" transcripts could still classify tumors in agreement with the tumor type.

A Detailed Survey of Pulsating Variables in Five Globular Clusters (Abstract)

NASA Astrophysics Data System (ADS)

Murphy, B. W.

2016-12-01

(Abstract only) Globular clusters are ideal laboratories for conducting a stellar census. Of particular interest are pulsating variables, which provide astronomers with a tool to probe the properties of the stars and the cluster. We observed each of five globular clusters hundreds to thousands of times over a time span ranging from 2 to 4 years in B, V, and I filters using the SARA 0.6-meter telescope located at Cerro Tololo Interamerican Observatory and the 0.9-meter telescope located at Kitt Peak, Arizona. The images were analyzed using difference image analysis to identify and produce light curves of all variables found in each cluster. In total we identified 377 variables with 140 of these being newly discovered increasing the number of known variables stars in these clusters by 60%. Of the total we have identified 319 RR Lyrae variables (193 RR0, 18 RR01, 101 RR1, 7 RR2), 9 SX Phe stars, 5 Cepheid variables, 11 eclipsing variables, and 33 long period variables. For IC4499 we identified 64 RR0, 18 RR01, 14 RR1, 4 RR2, 1 SX Phe, 1 eclipsing binary, and 2 long period variables. For NGC4833 we identified 10 RR0, 7 RR1, 3 RR2, 6 SX Phe, 5 eclipsing binaries, and 9 long period variables. For NGC6171 (M107) we identified 14 RR0, 7 RR1, and 1 SX Phe. For NGC6402 (M14) we identified 55 RR0, 57 RR1, 1 RR2, 1 SX Phe, 6 Cepheids, 1 eclipsing binary, and 15 long period variables. For NGC6584 we identified 50 RR0, 16 RR1, 4 eclipsing binaries, and 7 long period variables. From our extensive data set we were able to obtain sufficient temporal and complete phase coverage of the RR Lyrae variables. This has allowed us not only to properly classify each of the RR Lyrae variables but also to use Fourier decomposition of the B, V, and I light curves to further analyze the properties of the variable stars and hence the physical properties of each globular cluster.

[Cardiac risk profile in diabetes mellitus and impaired fasting glucose].

PubMed

Schaan, Beatriz D'Agord; Harzheim, Erno; Gus, Iseu

2004-08-01

Mortality of diabetic patients is higher than that of the population at large, and mainly results from cardiovascular diseases. The purpose of the present study was to identify the prevalence of cardiovascular risk factors in subjects with diabetes mellitus (DM) or abnormal fasting glucose (FG) in order to guide health actions. A population-based cross-sectional study was carried out in a representative random cluster sampling of 1,066 adult urban population (> or =20 years) in the state of Rio Grande do Sul between 1999 and 2000. A structured questionnaire on coronary risk factors was applied and sociodemographic characteristics of all adults older than 20 years living in the same dwelling were collected. Subjects were clinically evaluated and blood samples were obtained for measuring total cholesterol and fasting glycemia. Statistical analysis was performed using Stata 7 and a 5% significance level was set. Categorical variables were compared by Pearson's chi-square and continuous variables were compared using Student's t-test or Anova and multivariate analysis, all controlled for the cluster effect. Of 992 subjects, 12.4% were diabetic and 7.4% had impaired fasting glucose. Among the risk factors evaluated, subjects who presented any kind of glucose homeostasis abnormality were at a higher prevalence of obesity (17.8, 29.2 and 35.3% in healthy subjects, impaired fasting glucose and DM respectively, p<0.001), hypertension (30.1, 56.3 and 50.5% in healthy subjects, impaired fasting glucose and DM, respectively, p<0.001), and hypercholesterolemia (23.2, 35.1 and 39.5 in healthy subjects, impaired fasting glucose and DM respectively, p=0.01). Subjects with any kind of glucose homeostasis abnormality represent a group, which preventive individual and population health policies should target since they have higher prevalence of coronary artery disease risk factors.

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.

A comparison of regional flood frequency analysis approaches in a simulation framework

NASA Astrophysics Data System (ADS)

Ganora, D.; Laio, F.

2016-07-01

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve at ungauged (or scarcely gauged) sites. Different RFA approaches exist, depending on the way the information is transferred to the site of interest, but it is not clear in the literature if a specific method systematically outperforms the others. The aim of this study is to provide a framework wherein carrying out the intercomparison by building up a virtual environment based on synthetically generated data. The considered regional approaches include: (i) a unique regional curve for the whole region; (ii) a multiple-region model where homogeneous subregions are determined through cluster analysis; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially smooth estimation procedure where the parameters of the regional model vary continuously along the space. Virtual environments are generated considering different patterns of heterogeneity, including step change and smooth variations. If the region is heterogeneous, with the parent distribution changing continuously within the region, the spatially smooth regional approach outperforms the others, with overall errors 10-50% lower than the other methods. In the case of a step-change, the spatially smooth and clustering procedures perform similarly if the heterogeneity is moderate, while clustering procedures work better when the step-change is severe. To extend our findings, an extensive sensitivity analysis has been performed to investigate the effect of sample length, number of virtual stations, return period of the predicted quantile, variability of the scale parameter of the parent distribution, number of predictor variables and different parent distribution. Overall, the spatially smooth approach appears as the most robust approach as its performances are more stable across different patterns of heterogeneity, especially when short records are considered.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations

NASA Astrophysics Data System (ADS)

Wu, Hao; Nüske, Feliks; Paul, Fabian; Klus, Stefan; Koltai, Péter; Noé, Frank

2017-04-01

Markov state models (MSMs) and master equation models are popular approaches to approximate molecular kinetics, equilibria, metastable states, and reaction coordinates in terms of a state space discretization usually obtained by clustering. Recently, a powerful generalization of MSMs has been introduced, the variational approach conformation dynamics/molecular kinetics (VAC) and its special case the time-lagged independent component analysis (TICA), which allow us to approximate slow collective variables and molecular kinetics by linear combinations of smooth basis functions or order parameters. While it is known how to estimate MSMs from trajectories whose starting points are not sampled from an equilibrium ensemble, this has not yet been the case for TICA and the VAC. Previous estimates from short trajectories have been strongly biased and thus not variationally optimal. Here, we employ the Koopman operator theory and the ideas from dynamic mode decomposition to extend the VAC and TICA to non-equilibrium data. The main insight is that the VAC and TICA provide a coefficient matrix that we call Koopman model, as it approximates the underlying dynamical (Koopman) operator in conjunction with the basis set used. This Koopman model can be used to compute a stationary vector to reweight the data to equilibrium. From such a Koopman-reweighted sample, equilibrium expectation values and variationally optimal reversible Koopman models can be constructed even with short simulations. The Koopman model can be used to propagate densities, and its eigenvalue decomposition provides estimates of relaxation time scales and slow collective variables for dimension reduction. Koopman models are generalizations of Markov state models, TICA, and the linear VAC and allow molecular kinetics to be described without a cluster discretization.

Dynamics of Multistable States during Ongoing and Evoked Cortical Activity

PubMed Central

Mazzucato, Luca

2015-01-01

Single-trial analyses of ensemble activity in alert animals demonstrate that cortical circuits dynamics evolve through temporal sequences of metastable states. Metastability has been studied for its potential role in sensory coding, memory, and decision-making. Yet, very little is known about the network mechanisms responsible for its genesis. It is often assumed that the onset of state sequences is triggered by an external stimulus. Here we show that state sequences can be observed also in the absence of overt sensory stimulation. Analysis of multielectrode recordings from the gustatory cortex of alert rats revealed ongoing sequences of states, where single neurons spontaneously attain several firing rates across different states. This single-neuron multistability represents a challenge to existing spiking network models, where typically each neuron is at most bistable. We present a recurrent spiking network model that accounts for both the spontaneous generation of state sequences and the multistability in single-neuron firing rates. Each state results from the activation of neural clusters with potentiated intracluster connections, with the firing rate in each cluster depending on the number of active clusters. Simulations show that the model's ensemble activity hops among the different states, reproducing the ongoing dynamics observed in the data. When probed with external stimuli, the model predicts the quenching of single-neuron multistability into bistability and the reduction of trial-by-trial variability. Both predictions were confirmed in the data. Together, these results provide a theoretical framework that captures both ongoing and evoked network dynamics in a single mechanistic model. PMID:26019337

The Clusters AgeS Experiment (CASE). Variable stars in the field of the globular cluster NGC 362

NASA Astrophysics Data System (ADS)

Rozyczka, M.; Thompson, I. B.; Narloch, W.; Pych, W.; Schwarzenberg-Czerny, A.

2016-09-01

The field of the globular cluster NGC 362 was monitored between 1997 and 2015 in a search for variable stars. BV light curves were obtained for 151 periodic or likely periodic variable stars, over a hundred of which are new detections. Twelve newly detected variable stars are proper-motion members of the cluster: two SX Phe and two RR Lyr pulsators, one contact binary, three detached or semi-detached eclipsing binaries, and four spotted variable stars. The most interesting objects among these are the binary blue straggler V20 with an asymmetric light curve, and the 8.1 d semidetached binary V24 located on the red giant branch of NGC 362, which is a Chandra X-ray source. We also provide substantial new data for 24 previously known variable stars.

Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

PubMed Central

Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

2013-01-01

Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

Identification of piecewise affine systems based on fuzzy PCA-guided robust clustering technique

NASA Astrophysics Data System (ADS)

Khanmirza, Esmaeel; Nazarahari, Milad; Mousavi, Alireza

2016-12-01

Hybrid systems are a class of dynamical systems whose behaviors are based on the interaction between discrete and continuous dynamical behaviors. Since a general method for the analysis of hybrid systems is not available, some researchers have focused on specific types of hybrid systems. Piecewise affine (PWA) systems are one of the subsets of hybrid systems. The identification of PWA systems includes the estimation of the parameters of affine subsystems and the coefficients of the hyperplanes defining the partition of the state-input domain. In this paper, we have proposed a PWA identification approach based on a modified clustering technique. By using a fuzzy PCA-guided robust k-means clustering algorithm along with neighborhood outlier detection, the two main drawbacks of the well-known clustering algorithms, i.e., the poor initialization and the presence of outliers, are eliminated. Furthermore, this modified clustering technique enables us to determine the number of subsystems without any prior knowledge about system. In addition, applying the structure of the state-input domain, that is, considering the time sequence of input-output pairs, provides a more efficient clustering algorithm, which is the other novelty of this work. Finally, the proposed algorithm has been evaluated by parameter identification of an IGV servo actuator. Simulation together with experiment analysis has proved the effectiveness of the proposed method.

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

How to decompose arbitrary continuous-variable quantum operations.

PubMed

Sefi, Seckin; van Loock, Peter

2011-10-21

We present a general, systematic, and efficient method for decomposing any given exponential operator of bosonic mode operators, describing an arbitrary multimode Hamiltonian evolution, into a set of universal unitary gates. Although our approach is mainly oriented towards continuous-variable quantum computation, it may be used more generally whenever quantum states are to be transformed deterministically, e.g., in quantum control, discrete-variable quantum computation, or Hamiltonian simulation. We illustrate our scheme by presenting decompositions for various nonlinear Hamiltonians including quartic Kerr interactions. Finally, we conclude with two potential experiments utilizing offline-prepared optical cubic states and homodyne detections, in which quantum information is processed optically or in an atomic memory using quadratic light-atom interactions. © 2011 American Physical Society

Current Directions in Mediation Analysis

PubMed Central

MacKinnon, David P.; Fairchild, Amanda J.

2010-01-01

Mediating variables continue to play an important role in psychological theory and research. A mediating variable transmits the effect of an antecedent variable on to a dependent variable, thereby providing more detailed understanding of relations among variables. Methods to assess mediation have been an active area of research for the last two decades. This paper describes the current state of methods to investigate mediating variables. PMID:20157637

Solid-state NMR/NQR and first-principles study of two niobium halide cluster compounds.

PubMed

Perić, Berislav; Gautier, Régis; Pickard, Chris J; Bosiočić, Marko; Grbić, Mihael S; Požek, Miroslav

2014-01-01

Two hexanuclear niobium halide cluster compounds with a [Nb6X12](2+) (X=Cl, Br) diamagnetic cluster core, have been studied by a combination of experimental solid-state NMR/NQR techniques and PAW/GIPAW calculations. For niobium sites the NMR parameters were determined by using variable Bo field static broadband NMR measurements and additional NQR measurements. It was found that they possess large positive chemical shifts, contrary to majority of niobium compounds studied so far by solid-state NMR, but in accordance with chemical shifts of (95)Mo nuclei in structurally related compounds containing [Mo6Br8](4+) cluster cores. Experimentally determined δiso((93)Nb) values are in the range from 2,400 to 3,000 ppm. A detailed analysis of geometrical relations between computed electric field gradient (EFG) and chemical shift (CS) tensors with respect to structural features of cluster units was carried out. These tensors on niobium sites are almost axially symmetric with parallel orientation of the largest EFG and the smallest CS principal axes (Vzz and δ33) coinciding with the molecular four-fold axis of the [Nb6X12](2+) unit. Bridging halogen sites are characterized by large asymmetry of EFG and CS tensors, the largest EFG principal axis (Vzz) is perpendicular to the X-Nb bonds, while intermediate EFG principal axis (Vyy) and the largest CS principal axis (δ11) are oriented in the radial direction with respect to the center of the cluster unit. For more symmetrical bromide compound the PAW predictions for EFG parameters are in better correspondence with the NMR/NQR measurements than in the less symmetrical chlorine compound. Theoretically predicted NMR parameters of bridging halogen sites were checked by (79/81)Br NQR and (35)Cl solid-state NMR measurements. Copyright © 2014 Elsevier Inc. All rights reserved.

YSOVAR: MID-INFRARED VARIABILITY OF YOUNG STELLAR OBJECTS AND THEIR DISKS IN THE CLUSTER IRAS 20050+2720

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

Poppenhaeger, K.; Wolk, S. J.; Hora, J. L.

2015-10-15

We present a time-variability study of young stellar objects (YSOs) in the cluster IRAS 20050+2720, performed at 3.6 and 4.5 μm with the Spitzer Space Telescope; this study is part of the Young Stellar Object VARiability (YSOVAR) project. We have collected light curves for 181 cluster members over 60 days. We find a high variability fraction among embedded cluster members of ca. 70%, whereas young stars without a detectable disk display variability less often (in ca. 50% of the cases) and with lower amplitudes. We detect periodic variability for 33 sources with periods primarily in the range of 2–6 days.more » Practically all embedded periodic sources display additional variability on top of their periodicity. Furthermore, we analyze the slopes of the tracks that our sources span in the color–magnitude diagram (CMD). We find that sources with long variability time scales tend to display CMD slopes that are at least partially influenced by accretion processes, while sources with short variability timescales tend to display extinction-dominated slopes. We find a tentative trend of X-ray detected cluster members to vary on longer timescales than the X-ray undetected members.« less

A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…

Optimal continuous variable quantum teleportation protocol for realistic settings

NASA Astrophysics Data System (ADS)

Luiz, F. S.; Rigolin, Gustavo

2015-03-01

We show the optimal setup that allows Alice to teleport coherent states | α > to Bob giving the greatest fidelity (efficiency) when one takes into account two realistic assumptions. The first one is the fact that in any actual implementation of the continuous variable teleportation protocol (CVTP) Alice and Bob necessarily share non-maximally entangled states (two-mode finitely squeezed states). The second one assumes that Alice's pool of possible coherent states to be teleported to Bob does not cover the whole complex plane (| α | < ∞). The optimal strategy is achieved by tuning three parameters in the original CVTP, namely, Alice's beam splitter transmittance and Bob's displacements in position and momentum implemented on the teleported state. These slight changes in the protocol are currently easy to be implemented and, as we show, give considerable gain in performance for a variety of possible pool of input states with Alice.

Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics.

PubMed

Harris, Kenneth D; Hochgerner, Hannah; Skene, Nathan G; Magno, Lorenza; Katona, Linda; Bengtsson Gonzales, Carolina; Somogyi, Peter; Kessaris, Nicoletta; Linnarsson, Sten; Hjerling-Leffler, Jens

2018-06-18

Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

PubMed

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review

PubMed Central

Morris, Tom; Gray, Laura

2017-01-01

Objectives To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Setting Any, not limited to healthcare settings. Participants Any taking part in an SW-CRT published up to March 2016. Primary and secondary outcome measures The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Results Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22–0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Conclusions Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. PMID:29146637

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.

Theoretical characterization on the size-dependent electron and hole trapping activity of chloride-passivated CdSe nanoclusters

NASA Astrophysics Data System (ADS)

Cui, Yingqi; Cui, Xianhui; Zhang, Li; Xie, Yujuan; Yang, Mingli

2018-04-01

Ligand passivation is often used to suppress the surface trap states of semiconductor quantum dots (QDs) for their continuous photoluminescence output. The suppression process is related to the electrophilic/nucleophilic activity of surface atoms that varies with the structure and size of QD and the electron donating/accepting nature of ligand. Based on first-principles-based descriptors and cluster models, the electrophilic/nucleophilic activities of bare and chloride-coated CdSe clusters were studied to reveal the suppression mechanism of Cl-passivated QDs and compared to experimental observations. The surface atoms of bare clusters have higher activity than inner atoms and their activity decreases with cluster size. In the ligand-coated clusters, the Cd atom remains as the electrophilic site, while the nucleophilic site of Se atoms is replaced by Cl atoms. The activities of Cd and Cl atoms in the coated clusters are, however, remarkably weaker than those in bare clusters. Cluster size, dangling atoms, ligand coverage, electronegativity of ligand atoms, and solvent (water) were found to have considerable influence on the activity of surface atoms. The suppression of surface trap states in Cl-passivated QDs was attributed to the reduction of electrophilic/nucleophilic activity of Cd/Se/Cl atoms. Both saturation to under-coordinated surface atoms and proper selection for the electron donating/accepting strength of ligands are crucial for eliminating the charge carrier traps. Our calculations predicted a similar suppressing effect of chloride ligands with experiments and provided a simple but effective approach to assess the charge carrier trapping behaviors of semiconductor QDs.

Secure Continuous Variable Teleportation and Einstein-Podolsky-Rosen Steering

NASA Astrophysics Data System (ADS)

He, Qiongyi; Rosales-Zárate, Laura; Adesso, Gerardo; Reid, Margaret D.

2015-10-01

We investigate the resources needed for secure teleportation of coherent states. We extend continuous variable teleportation to include quantum teleamplification protocols that allow nonunity classical gains and a preamplification or postattenuation of the coherent state. We show that, for arbitrary Gaussian protocols and a significant class of Gaussian resources, two-way steering is required to achieve a teleportation fidelity beyond the no-cloning threshold. This provides an operational connection between Gaussian steerability and secure teleportation. We present practical recipes suggesting that heralded noiseless preamplification may enable high-fidelity heralded teleportation, using minimally entangled yet steerable resources.

The SWIFT AGN and Cluster Survey. I. Number Counts of AGNs and Galaxy Clusters

NASA Astrophysics Data System (ADS)

Dai, Xinyu; Griffin, Rhiannon D.; Kochanek, Christopher S.; Nugent, Jenna M.; Bregman, Joel N.

2015-05-01

The Swift active galactic nucleus (AGN) and Cluster Survey (SACS) uses 125 deg2 of Swift X-ray Telescope serendipitous fields with variable depths surrounding γ-ray bursts to provide a medium depth (4× {{10}-15} erg cm-2 s-1) and area survey filling the gap between deep, narrow Chandra/XMM-Newton surveys and wide, shallow ROSAT surveys. Here, we present a catalog of 22,563 point sources and 442 extended sources and examine the number counts of the AGN and galaxy cluster populations. SACS provides excellent constraints on the AGN number counts at the bright end with negligible uncertainties due to cosmic variance, and these constraints are consistent with previous measurements. We use Wide-field Infrared Survey Explorer mid-infrared (MIR) colors to classify the sources. For AGNs we can roughly separate the point sources into MIR-red and MIR-blue AGNs, finding roughly equal numbers of each type in the soft X-ray band (0.5-2 keV), but fewer MIR-blue sources in the hard X-ray band (2-8 keV). The cluster number counts, with 5% uncertainties from cosmic variance, are also consistent with previous surveys but span a much larger continuous flux range. Deep optical or IR follow-up observations of this cluster sample will significantly increase the number of higher-redshift (z\\gt 0.5) X-ray-selected clusters.

The contribution of psychological factors to recovery after mild traumatic brain injury: is cluster analysis a useful approach?

PubMed

Snell, Deborah L; Surgenor, Lois J; Hay-Smith, E Jean C; Williman, Jonathan; Siegert, Richard J

2015-01-01

Outcomes after mild traumatic brain injury (MTBI) vary, with slow or incomplete recovery for a significant minority. This study examines whether groups of cases with shared psychological factors but with different injury outcomes could be identified using cluster analysis. This is a prospective observational study following 147 adults presenting to a hospital-based emergency department or concussion services in Christchurch, New Zealand. This study examined associations between baseline demographic, clinical, psychological variables (distress, injury beliefs and symptom burden) and outcome 6 months later. A two-step approach to cluster analysis was applied (Ward's method to identify clusters, K-means to refine results). Three meaningful clusters emerged (high-adapters, medium-adapters, low-adapters). Baseline cluster-group membership was significantly associated with outcomes over time. High-adapters appeared recovered by 6-weeks and medium-adapters revealed improvements by 6-months. The low-adapters continued to endorse many symptoms, negative recovery expectations and distress, being significantly at risk for poor outcome more than 6-months after injury (OR (good outcome) = 0.12; CI = 0.03-0.53; p < 0.01). Cluster analysis supported the notion that groups could be identified early post-injury based on psychological factors, with group membership associated with differing outcomes over time. Implications for clinical care providers regarding therapy targets and cases that may benefit from different intensities of intervention are discussed.

The spatial clustering of obesity: does the built environment matter?

PubMed

Huang, R; Moudon, A V; Cook, A J; Drewnowski, A

2015-12-01

Obesity rates in the USA show distinct geographical patterns. The present study used spatial cluster detection methods and individual-level data to locate obesity clusters and to analyse them in relation to the neighbourhood built environment. The 2008-2009 Seattle Obesity Study provided data on the self-reported height, weight, and sociodemographic characteristics of 1602 King County adults. Home addresses were geocoded. Clusters of high or low body mass index were identified using Anselin's Local Moran's I and a spatial scan statistic with regression models that searched for unmeasured neighbourhood-level factors from residuals, adjusting for measured individual-level covariates. Spatially continuous values of objectively measured features of the local neighbourhood built environment (SmartMaps) were constructed for seven variables obtained from tax rolls and commercial databases. Both the Local Moran's I and a spatial scan statistic identified similar spatial concentrations of obesity. High and low obesity clusters were attenuated after adjusting for age, gender, race, education and income, and they disappeared once neighbourhood residential property values and residential density were included in the model. Using individual-level data to detect obesity clusters with two cluster detection methods, the present study showed that the spatial concentration of obesity was wholly explained by neighbourhood composition and socioeconomic characteristics. These characteristics may serve to more precisely locate obesity prevention and intervention programmes. © 2014 The British Dietetic Association Ltd.

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.

Observations and analysis of the contact binary H 235 in the open cluster NGC 752

NASA Astrophysics Data System (ADS)

Milone, E. F.; Stagg, C. R.; Sugars, B. A.; McVean, J. R.; Schiller, S. J.; Kallrath, J.; Bradstreet, D. H.

1995-01-01

The short-period variable star Heinemann 235 in the open cluster NGC 752 has been identified as a contact binary with a variable period of about 0 d 4118. BVRI light curves and radial velocity curves have been obtained and analyzed with enhanced versions of the Wilson-Devinney light curve program. We find that the system is best modeled as an A-type W UMa system, with a contact parameter of 0.21 +/- 0.11. The masses of the components are found to be 1.18 +/- 0.17 and 0.24 +/- 0.04 solar mass, with bolometric magnitudes of 3.60 +/- 0.10 and 5.21 +/- 0.13, for the hotter (6500 K, assumed) and cooler (6421 K) components, respectively, with Delta T=79 +/- 25 K. The distance to the binary is established at 381 +/- 17 pc. H235 becomes one of a relatively small number of open-cluster contact systems with detailed light curve analysis for which an age may be estimated. If it is coeval with the cluster, and with the detached eclipsing and double-lined spectroscopic binary H219 (DS And), H235 is approximately 1.8 Gyr old, and may provide a fiducial point for the evolution of contact systems. There is, however, evidence for dynamical evolution of the cluster and the likelihood of weak interactions over the age of the binary precludes the determination of its initial state with certainty.

The Clusters AgeS Experiment (CASE). Variable Stars in the Field of the Globular Cluster NGC 6362

NASA Astrophysics Data System (ADS)

Kaluzny, J.; Thompson, I. B.; Rozyczka, M.; Pych, W.; Narloch, W.

2014-12-01

The field of the globular cluster NGC 6362 was monitored between 1995 and 2009 in a search for variable stars. BV light curves were obtained for 69 periodic variable stars including 34 known RR Lyr stars, 10 known objects of other types and 25 newly detected variable stars. Among the latter we identified 18 proper-motion members of the cluster: seven detached eclipsing binaries (DEBs), six SX Phe stars, two W UMa binaries, two spotted red giants, and a very interesting eclipsing binary composed of two red giants - the first example of such a system found in a globular cluster. Five of the DEBs are located at the turnoff region, and the remaining two are redward of the lower main sequence. Eighty-four objects from the central 9×9 arcmin2 of the cluster were found in the region of cluster blue stragglers. Of these 70 are proper motion (PM) members of NGC 6362 (including all SX Phe and two W UMa stars), and five are field stars. The remaining nine objects lacking PM information are located at the very core of the cluster, and as such they are likely genuine blue stragglers.

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

Path integrals and large deviations in stochastic hybrid systems.

PubMed

Bressloff, Paul C; Newby, Jay M

2014-04-01

We construct a path-integral representation of solutions to a stochastic hybrid system, consisting of one or more continuous variables evolving according to a piecewise-deterministic dynamics. The differential equations for the continuous variables are coupled to a set of discrete variables that satisfy a continuous-time Markov process, which means that the differential equations are only valid between jumps in the discrete variables. Examples of stochastic hybrid systems arise in biophysical models of stochastic ion channels, motor-driven intracellular transport, gene networks, and stochastic neural networks. We use the path-integral representation to derive a large deviation action principle for a stochastic hybrid system. Minimizing the associated action functional with respect to the set of all trajectories emanating from a metastable state (assuming that such a minimization scheme exists) then determines the most probable paths of escape. Moreover, evaluating the action functional along a most probable path generates the so-called quasipotential used in the calculation of mean first passage times. We illustrate the theory by considering the optimal paths of escape from a metastable state in a bistable neural network.

Spatial modelling and mapping of female genital mutilation in Kenya.

PubMed

Achia, Thomas N O

2014-03-25

Female genital mutilation/cutting (FGM/C) is still prevalent in several communities in Kenya and other areas in Africa, as well as being practiced by some migrants from African countries living in other parts of the world. This study aimed at detecting clustering of FGM/C in Kenya, and identifying those areas within the country where women still intend to continue the practice. A broader goal of the study was to identify geographical areas where the practice continues unabated and where broad intervention strategies need to be introduced. The prevalence of FGM/C was investigated using the 2008 Kenya Demographic and Health Survey (KDHS) data. The 2008 KDHS used a multistage stratified random sampling plan to select women of reproductive age (15-49 years) and asked questions concerning their FGM/C status and their support for the continuation of FGM/C. A spatial scan statistical analysis was carried out using SaTScan™ to test for statistically significant clustering of the practice of FGM/C in the country. The risk of FGM/C was also modelled and mapped using a hierarchical spatial model under the Integrated Nested Laplace approximation approach using the INLA library in R. The prevalence of FGM/C stood at 28.2% and an estimated 10.3% of the women interviewed indicated that they supported the continuation of FGM. On the basis of the Deviance Information Criterion (DIC), hierarchical spatial models with spatially structured random effects were found to best fit the data for both response variables considered. Age, region, rural-urban classification, education, marital status, religion, socioeconomic status and media exposure were found to be significantly associated with FGM/C. The current FGM/C status of a woman was also a significant predictor of support for the continuation of FGM/C. Spatial scan statistics confirm FGM clusters in the North-Eastern and South-Western regions of Kenya (p<0.001). This suggests that the fight against FGM/C in Kenya is not yet over. There are still deep cultural and religious beliefs to be addressed in a bid to eradicate the practice. Interventions by government and other stakeholders must address these challenges and target the identified clusters.

Thermodynamics of gravitational clustering phenomena: N-body self-gravitating gas on the sphere {{{S}}^{3}}\\subset {{{R}}^{4}}

NASA Astrophysics Data System (ADS)

Tello-Ortiz, F.; Velazquez, L.

2016-10-01

This work is devoted to the thermodynamics of gravitational clustering, a collective phenomenon with a great relevance in the N-body cosmological problem. We study a classical self-gravitating gas of identical non-relativistic particles defined on the sphere {{{S}}3}\\subset {{{R}}4} by considering gravitational interaction that corresponds to this geometric space. The analysis is performed within microcanonical description of an isolated Hamiltonian system by combining continuum approximation and the steepest descend method. According to numerical solution of resulting equations, the gravitational clustering can be associated with two microcanonical phase transitions. A first phase transition with a continuous character is associated with breakdown of SO(4) symmetry of this model. The second one is the gravitational collapse, whose continuous or discontinuous character crucially depends on the regularization of short-range divergence of gravitation potential. We also derive the thermodynamic limit of this model system, the astrophysical counterpart of the Gibbs-Duhem relation, the order parameters that characterize its phase transitions and the equation of state. Other interesting behavior is the existence of states with negative heat capacities, which appear when the effects of gravitation turn dominant for energies sufficiently low. Finally, we comment on the relevance of some of these results in the study of astrophysical and cosmological situations. Special interest deserves the gravitational modification of the equation of state due to the local inhomogeneities of matter distribution. Although this feature is systematically neglected in studies about universe expansion, the same one is able to mimic an effect that is attributed to the dark energy: a negative pressure.

Image-Subtraction Photometry of Variable Stars in the Field of the Globular Cluster NGC 6934

NASA Astrophysics Data System (ADS)

Kaluzny, J.; Olech, A.; Stanek, K. Z.

2001-03-01

We present CCD BVI photometry of 85 variable stars from the field of the globular cluster NGC 6934. The photometry was obtained with the image subtraction package ISIS. 35 variables are new identifications: 24 RRab stars, five RRc stars, two eclipsing binaries of W UMa-type, one SX Phe star, and three variables of other types. Both detected contact binaries are foreground stars. The SX Phe variable belongs most likely to the group of cluster blue stragglers. Large number of newly found RR Lyr variables in this cluster, as well as in other clusters recently observed by us, indicates that total RR Lyr population identified up to date in nearby galactic globular clusters is significantly (>30%) incomplete. Fourier decomposition of the light curves of RR Lyr variables was used to estimate the basic properties of these stars. From the analysis of RRc variables we obtain a mean mass of M=0.63 Msolar, luminosity logL/Lsolar=1.72, effective temperature Teff=7300 and helium abundance Y=0.27. The mean values of the absolute magnitude, metallicity (on Zinn's scale) and effective temperature for RRab variables are MV=0.81, [Fe/H]=-1.53 and Teff=6450, respectively. From the B-V color at minimum light of the RRab variables we obtained the color excess to NGC 6934 equal to E(B-V)=0.09+/-0.01. Different calibrations of absolute magnitudes of RRab and RRc available in literature were used to estimate apparent distance modulus of the cluster: (m-M)V=16.09+/-0.06. We note a likely error in the zero point of the HST-based V-band photometry of NGC 6934 recently presented by Piotto et al. Among analyzed sample of RR Lyr stars we have detected a short period and low amplitude variable which possibly belongs to the group of second overtone pulsators (RRe subtype variables). The BVI photometry of all variables is available electronically via anonymous ftp. The complete set of the CCD frames is available upon request. Based on observations obtained with the 1.2 m Telescope at the F. L. Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics.

Clustering "N" Objects into "K" Groups under Optimal Scaling of Variables.

ERIC Educational Resources Information Center

van Buuren, Stef; Heiser, Willem J.

1989-01-01

A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)

Gaussian private quantum channel with squeezed coherent states

PubMed Central

Jeong, Kabgyun; Kim, Jaewan; Lee, Su-Yong

2015-01-01

While the objective of conventional quantum key distribution (QKD) is to secretly generate and share the classical bits concealed in the form of maximally mixed quantum states, that of private quantum channel (PQC) is to secretly transmit individual quantum states concealed in the form of maximally mixed states using shared one-time pad and it is called Gaussian private quantum channel (GPQC) when the scheme is in the regime of continuous variables. We propose a GPQC enhanced with squeezed coherent states (GPQCwSC), which is a generalization of GPQC with coherent states only (GPQCo) [Phys. Rev. A 72, 042313 (2005)]. We show that GPQCwSC beats the GPQCo for the upper bound on accessible information. As a subsidiary example, it is shown that the squeezed states take an advantage over the coherent states against a beam splitting attack in a continuous variable QKD. It is also shown that a squeezing operation can be approximated as a superposition of two different displacement operations in the small squeezing regime. PMID:26364893

Gaussian private quantum channel with squeezed coherent states.

PubMed

Jeong, Kabgyun; Kim, Jaewan; Lee, Su-Yong

2015-09-14

While the objective of conventional quantum key distribution (QKD) is to secretly generate and share the classical bits concealed in the form of maximally mixed quantum states, that of private quantum channel (PQC) is to secretly transmit individual quantum states concealed in the form of maximally mixed states using shared one-time pad and it is called Gaussian private quantum channel (GPQC) when the scheme is in the regime of continuous variables. We propose a GPQC enhanced with squeezed coherent states (GPQCwSC), which is a generalization of GPQC with coherent states only (GPQCo) [Phys. Rev. A 72, 042313 (2005)]. We show that GPQCwSC beats the GPQCo for the upper bound on accessible information. As a subsidiary example, it is shown that the squeezed states take an advantage over the coherent states against a beam splitting attack in a continuous variable QKD. It is also shown that a squeezing operation can be approximated as a superposition of two different displacement operations in the small squeezing regime.

Virtual continuity of measurable functions and its applications

NASA Astrophysics Data System (ADS)

Vershik, A. M.; Zatitskii, P. B.; Petrov, F. V.

2014-12-01

A classical theorem of Luzin states that a measurable function of one real variable is `almost' continuous. For measurable functions of several variables the analogous statement (continuity on a product of sets having almost full measure) does not hold in general. The search for a correct analogue of Luzin's theorem leads to a notion of virtually continuous functions of several variables. This apparently new notion implicitly appears in the statements of embedding theorems and trace theorems for Sobolev spaces. In fact it reveals the nature of such theorems as statements about virtual continuity. The authors' results imply that under the conditions of Sobolev theorems there is a well-defined integration of a function with respect to a wide class of singular measures, including measures concentrated on submanifolds. The notion of virtual continuity is also used for the classification of measurable functions of several variables and in some questions on dynamical systems, the theory of polymorphisms, and bistochastic measures. In this paper the necessary definitions and properties of admissible metrics are recalled, several definitions of virtual continuity are given, and some applications are discussed. Bibliography: 24 titles.

Identifying socioeconomic, epidemiological and operational scenarios for tuberculosis control in Brazil: an ecological study.

PubMed

Pelissari, Daniele Maria; Rocha, Marli Souza; Bartholomay, Patricia; Sanchez, Mauro Niskier; Duarte, Elisabeth Carmen; Arakaki-Sanchez, Denise; Dantas, Cíntia Oliveira; Jacobs, Marina Gasino; Andrade, Kleydson Bonfim; Codenotti, Stefano Barbosa; Andrade, Elaine Silva Nascimento; Araújo, Wildo Navegantes de; Costa, Fernanda Dockhorn; Ramalho, Walter Massa; Diaz-Quijano, Fredi Alexander

2018-06-06

To identify scenarios based on socioeconomic, epidemiological and operational healthcare factors associated with tuberculosis incidence in Brazil. Ecological study. The study was based on new patients with tuberculosis and epidemiological/operational variables of the disease from the Brazilian National Information System for Notifiable Diseases and the Mortality Information System. We also analysed socioeconomic and demographic variables. The units of analysis were the Brazilian municipalities, which in 2015 numbered 5570 but 5 were excluded due to the absence of socioeconomic information. Tuberculosis incidence rate in 2015. We evaluated as independent variables the socioeconomic (2010), epidemiological and operational healthcare indicators of tuberculosis (2014 or 2015) using negative binomial regression. Municipalities were clustered by the k-means method considering the variables identified in multiple regression models. We identified two clusters according to socioeconomic variables associated with the tuberculosis incidence rate (unemployment rate and household crowding): a higher socioeconomic scenario (n=3482 municipalities) with a mean tuberculosis incidence rate of 16.3/100 000 population and a lower socioeconomic scenario (2083 municipalities) with a mean tuberculosis incidence rate of 22.1/100 000 population. In a second stage of clusterisation, we defined four subgroups in each of the socioeconomic scenarios using epidemiological and operational variables such as tuberculosis mortality rate, AIDS case detection rate and proportion of vulnerable population among patients with tuberculosis. Some of the subscenarios identified were characterised by fragility in their information systems, while others were characterised by the concentration of tuberculosis cases in key populations. Clustering municipalities in scenarios allowed us to classify them according to the socioeconomic, epidemiological and operational variables associated with tuberculosis risk. This classification can support targeted evidence-based decisions such as monitoring data quality for improving the information system or establishing integrative social protective policies for key populations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Synchronization states and multistability in a ring of periodic oscillators: Experimentally variable coupling delays

NASA Astrophysics Data System (ADS)

Williams, Caitlin R. S.; Sorrentino, Francesco; Murphy, Thomas E.; Roy, Rajarshi

2013-12-01

We experimentally study the complex dynamics of a unidirectionally coupled ring of four identical optoelectronic oscillators. The coupling between these systems is time-delayed in the experiment and can be varied over a wide range of delays. We observe that as the coupling delay is varied, the system may show different synchronization states, including complete isochronal synchrony, cluster synchrony, and two splay-phase states. We analyze the stability of these solutions through a master stability function approach, which we show can be effectively applied to all the different states observed in the experiment. Our analysis supports the experimentally observed multistability in the system.

Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

PubMed

Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia

2018-07-14

In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Approaches to Identifying the Emerging Innovative Water Technology Industry in the United States.

PubMed

Wood, Allison R; Harten, Teresa; Gutierrez, Sally C

2018-04-25

Clean water is vital to sustaining our natural environment, human health, and our economy. As infrastructure continues to deteriorate and water resources become increasingly threatened, new technologies will be needed to ensure safe and sustainable water in the future. Though the US water industry accounts for approximately 1% gross domestic product and regional "clusters" for water technology exist throughout the country, this emerging industry has not been captured by recent studies. As use of the term "cluster" becomes more prevalent, regional mapping efforts have revealed international differences in definition yet showcase this industry's economic impact. In reality, institutional processes may inhibit altering industry coding to better describe water technology. Forgoing the benefits of national economic tracking, alternative data sets are available, which may support new ways of identifying these clusters. This work provides cluster definitions; summarizes current approaches to identifying industry activity using data, interviews, and literature; and sets a foundation for future research.

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.

Breast cancer and symptom clusters during radiotherapy.

PubMed

Matthews, Ellyn E; Schmiege, Sarah J; Cook, Paul F; Sousa, Karen H

2012-01-01

Symptom clusters assessment shifts the clinical focus from a specific symptom to the patient's experience as a whole. Few studies have examined breast cancer symptom clusters during treatment, and fewer studies have addressed symptom clusters during radiation therapy (RT). The theoretical underpinning of this study is the Symptoms Experience Model. Research is needed to identify antecedents and consequences of cancer-related symptom clusters. The present study was intended to determine the clustering of symptoms during RT in women with breast cancer and significant correlations among the symptoms, individual characteristics, and mood. A secondary data analysis from a descriptive correlational study of 93 women at weeks 3 to 7 of RT from centers in the mid-Atlantic region of the United States, Symptom Distress Scale, the subscales of the Positive and Negative Affect Scale, Life Orientation Test, and Self-transcendence Scale were completed. Confirmatory factor analysis revealed symptoms grouped into 3 distinct clusters: pain-insomnia-fatigue, cognitive disturbance-outlook, and gastrointestinal. The pain-insomnia-fatigue and cognitive disturbance-outlook clusters were associated with individual characteristics, optimism, self-transcendence, and positive and negative mood. The gastrointestinal cluster correlated significantly only with positive mood. This study provides insight into symptoms that group together and the relationship of symptom clusters to antecedents and mood. These findings underscore the need to define and standardize the measurement of symptom clusters and understand variability in concurrent symptoms. Attention to symptom clusters shifts the clinical focus from a specific symptom to the patient's experience as a whole and helps identify the most effective interventions.

Predicting declines in perceived relationship continuity using practice deprivation scores: a longitudinal study in primary care.

PubMed

Levene, Louis S; Baker, Richard; Walker, Nicola; Williams, Christopher; Wilson, Andrew; Bankart, John

2018-06-01

Increased relationship continuity in primary care is associated with better health outcomes, greater patient satisfaction, and fewer hospital admissions. Greater socioeconomic deprivation is associated with lower levels of continuity, as well as poorer health outcomes. To investigate whether deprivation scores predicted variations in the decline over time of patient-perceived relationship continuity of care, after adjustment for practice organisational and population factors. An observational study in 6243 primary care practices with more than one GP, in England, using a longitudinal multilevel linear model, 2012-2017 inclusive. Patient-perceived relationship continuity was calculated using two questions from the GP Patient Survey. The effect of deprivation on the linear slope of continuity over time was modelled, adjusting for nine confounding variables (practice population and organisational factors). Clustering of measurements within general practices was adjusted for by using a random intercepts and random slopes model. Descriptive statistics and univariable analyses were also undertaken. Relationship continuity declined by 27.5% between 2012 and 2017, and at all deprivation levels. Deprivation scores from 2012 did not predict variations in the decline of relationship continuity at practice level, after accounting for the effects of organisational and population confounding variables, which themselves did not predict, or weakly predicted with very small effect sizes, the decline of continuity. Cross-sectionally, continuity and deprivation were negatively correlated within each year. The decline in relationship continuity of care has been marked and widespread. Measures to maximise continuity will need to be feasible for individual practices with diverse population and organisational characteristics. © British Journal of General Practice 2018.

Continuous-variable protocol for oblivious transfer in the noisy-storage model.

PubMed

Furrer, Fabian; Gehring, Tobias; Schaffner, Christian; Pacher, Christoph; Schnabel, Roman; Wehner, Stephanie

2018-04-13

Cryptographic protocols are the backbone of our information society. This includes two-party protocols which offer protection against distrustful players. Such protocols can be built from a basic primitive called oblivious transfer. We present and experimentally demonstrate here a quantum protocol for oblivious transfer for optical continuous-variable systems, and prove its security in the noisy-storage model. This model allows us to establish security by sending more quantum signals than an attacker can reliably store during the protocol. The security proof is based on uncertainty relations which we derive for continuous-variable systems, that differ from the ones used in quantum key distribution. We experimentally demonstrate in a proof-of-principle experiment the proposed oblivious transfer protocol for various channel losses by using entangled two-mode squeezed states measured with balanced homodyne detection. Our work enables the implementation of arbitrary two-party quantum cryptographic protocols with continuous-variable communication systems.

Teaching Gene Technology in an Outreach Lab: Students' Assigned Cognitive Load Clusters and the Clusters' Relationships to Learner Characteristics, Laboratory Variables, and Cognitive Achievement

ERIC Educational Resources Information Center

Scharfenberg, Franz-Josef; Bogner, Franz X.

2013-01-01

This study classified students into different cognitive load (CL) groups by means of cluster analysis based on their experienced CL in a gene technology outreach lab which has instructionally been designed with regard to CL theory. The relationships of the identified student CL clusters to learner characteristics, laboratory variables, and…

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

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

Eisenbach, Markus; Li, Ying Wai

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage ofmore » avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.« less

Divergence-free approach for obtaining decompositions of quantum-optical processes

NASA Astrophysics Data System (ADS)

Sabapathy, K. K.; Ivan, J. S.; García-Patrón, R.; Simon, R.

2018-02-01

Operator-sum representations of quantum channels can be obtained by applying the channel to one subsystem of a maximally entangled state and deploying the channel-state isomorphism. However, for continuous-variable systems, such schemes contain natural divergences since the maximally entangled state is ill defined. We introduce a method that avoids such divergences by utilizing finitely entangled (squeezed) states and then taking the limit of arbitrary large squeezing. Using this method, we derive an operator-sum representation for all single-mode bosonic Gaussian channels where a unique feature is that both quantum-limited and noisy channels are treated on an equal footing. This technique facilitates a proof that the rank-1 Kraus decomposition for Gaussian channels at its respective entanglement-breaking thresholds, obtained in the overcomplete coherent-state basis, is unique. The methods could have applications to simulation of continuous-variable channels.

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.

Nature of phase transitions in Axelrod-like coupled Potts models in two dimensions

NASA Astrophysics Data System (ADS)

Gandica, Yerali; Chiacchiera, Silvia

2016-03-01

We study F coupled q -state Potts models in a two-dimensional square lattice. The interaction between the different layers is attractive to favor a simultaneous alignment in all of them, and its strength is fixed. The nature of the phase transition for zero field is numerically determined for F =2 ,3 . Using the Lee-Kosterlitz method, we find that it is continuous for F =2 and q =2 , whereas it is abrupt for higher values of q and/or F . When a continuous or a weakly first-order phase transition takes place, we also analyze the properties of the geometrical clusters. This allows us to determine the fractal dimension D of the incipient infinite cluster and to examine the finite-size scaling of the cluster number density via data collapse. A mean-field approximation of the model, from which some general trends can be determined, is presented too. Finally, since this lattice model has been recently considered as a thermodynamic counterpart of the Axelrod model of social dynamics, we discuss our results in connection with this one.

Nature of phase transitions in Axelrod-like coupled Potts models in two dimensions.

PubMed

Gandica, Yerali; Chiacchiera, Silvia

2016-03-01

We study F coupled q-state Potts models in a two-dimensional square lattice. The interaction between the different layers is attractive to favor a simultaneous alignment in all of them, and its strength is fixed. The nature of the phase transition for zero field is numerically determined for F = 2,3. Using the Lee-Kosterlitz method, we find that it is continuous for F = 2 and q = 2, whereas it is abrupt for higher values of q and/or F. When a continuous or a weakly first-order phase transition takes place, we also analyze the properties of the geometrical clusters. This allows us to determine the fractal dimension D of the incipient infinite cluster and to examine the finite-size scaling of the cluster number density via data collapse. A mean-field approximation of the model, from which some general trends can be determined, is presented too. Finally, since this lattice model has been recently considered as a thermodynamic counterpart of the Axelrod model of social dynamics, we discuss our results in connection with this one.

Genetic divergence of physiological-quality traits of seeds in a population of peppers.

PubMed

Pessoa, A M S; Barroso, P A; do Rêgo, E R; Medeiros, G D A; Bruno, R L A; do Rêgo, M M

2015-10-16

Brazil has a great diversity of Capsicum peppers that can be used in breeding programs. The objective of this study was to evaluate genetic variation in traits related to the physiological quality of seeds of Capsicum annuum L. in a segregating F2 population and its parents. A total of 250 seeds produced by selfing in the F1 generation resulting from crosses between UFPB 77.3 and UFPB 76 were used, with 100 seeds of both parents used as additional controls, totaling 252 genotypes. The seeds were germinated in gerboxes containing substrate blotting paper moistened with distilled water. Germination and the following vigor tests were evaluated: first count, germination velocity index, and root and shoot lengths. Data were subjected to analysis of variance, and means were compared by Scott and Knott's method at 1% probability. Tocher's clustering based on Mahalanobis distance and canonical variable analysis with graphic dispersion of genotypes were performed, and genetic parameters were estimated. All variables were found to be significant by the F test (P ≤ 0.01) and showed high heritability and a CVg/CVe ratio higher than 1.0, indicating genetic differences among genotypes. Parents (genotypes 1 and 2) formed distinct groups in all clustering methods. Genotypes 3, 104, 153, and 232 were found to be the most divergent according to Tocher's clustering method, and this was mainly due to early germination, which was observed on day 14, and would therefore be selected. Understanding the phenotypic variability among these 252 genotypes will serve as a basis for continuing the breeding program within this family.

Crossover from Polaronic to Magnetically Phase-Separated Behavior in La1-xSrxCoO3

NASA Astrophysics Data System (ADS)

Phelan, D.; El Khatib, S.; Wang, S.; Barker, J.; Zhao, J.; Zheng, H.; Mitchell, J. F.; Leighton, C.

2013-03-01

Dilute hole-doping in La1-xSrxCoO3 leads to the formation of ``spin-state polarons'' where a non-zero spin-state is stabilized on the nearest Co3+ ions surrounding a hole. Here, we discuss the development of electronic/magnetic properties of this system from non-magnetic x=0, through the regime of spin-state polarons, and into the region where longer-range spin correlations and phase separation develop. We present magnetometry, transport, heat capacity, and small-angle neutron scattering (SANS) on single crystals. Magnetometry indicates a crossover with x from Langevin-like behavior (polaronic) to a state with a freezing temperature and finite coercivity. Fascinating correlations with this behavior are seen in transport measurements, the evolution from polaronic to clustered states being accompanied by a crossover from Mott variable range hopping to intercluster hopping. SANS data shows Lorentzian scattering from short-range ferromagnetic clusters first emerging around x = 0.03 with correlation lengths of order two unit cells. We argue that this system provides a unique opportunity to understand in detail the crossover from polaronic to truly phase-separated states.

New SX Phoenicis Variables in the Globular Cluster NGC 4833

NASA Astrophysics Data System (ADS)

Darragh, A. N.; Murphy, B. W.

2012-07-01

We report the discovery of 6 SX Phoenicis stars in the southern globular cluster NGC 4833. Images were obtained from January through June 2011 with the Southeastern Association for Research in Astronomy 0.6 meter telescope located at Cerro Tololo Interamerican Observatory. The ISIS image subtraction method was used to search for variable stars in the cluster. We confirmed 17 previously cataloged variables and have identified 10 new variables. Of the total number of confirmed variables in our 10×10 arcmin^2 field, we classified 10 RRab variables, with a mean period of 0.69591 days, 7 RRc, with a mean period of 0.39555 days, 2 possible RRe variables with a mean period of 0.30950 days, a W Ursae Majoris contact binary, an Algol-type binary, and the 6 SX Phoenicis stars with a mean period of 0.05847 days. The periods, relative numbers of RRab and RRc variables, and Bailey diagram are indicative of the cluster being of the Oosterhoff type II. We present the phased-light curves, periods of previously known variables and the periods and classifications of the newly discovered variables, and their location on the color-magnitude diagram.

Nonequilibrium thermodynamic potentials for continuous-time Markov chains.

PubMed

Verley, Gatien

2016-01-01

We connect the rare fluctuations of an equilibrium (EQ) process and the typical fluctuations of a nonequilibrium (NE) stationary process. In the framework of large deviation theory, this observation allows us to introduce NE thermodynamic potentials. For continuous-time Markov chains, we identify the relevant pairs of conjugated variables and propose two NE ensembles: one with fixed dynamics and fluctuating time-averaged variables, and another with fixed time-averaged variables, but a fluctuating dynamics. Accordingly, we show that NE processes are equivalent to conditioned EQ processes ensuring that NE potentials are Legendre dual. We find a variational principle satisfied by the NE potentials that reach their maximum in the NE stationary state and whose first derivatives produce the NE equations of state and second derivatives produce the NE Maxwell relations generalizing the Onsager reciprocity relations.

Continuous-variable quantum key distribution with Gaussian source noise

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

Shen Yujie; Peng Xiang; Yang Jian

2011-05-15

Source noise affects the security of continuous-variable quantum key distribution (CV QKD) and is difficult to analyze. We propose a model to characterize Gaussian source noise through introducing a neutral party (Fred) who induces the noise with a general unitary transformation. Without knowing Fred's exact state, we derive the security bounds for both reverse and direct reconciliations and show that the bound for reverse reconciliation is tight.

Clustering by neurocognition for fine-mapping of the schizophrenia susceptibility loci on chromosome 6p

PubMed Central

Lin, Sheng-Hsiang; Liu, Chih-Min; Liu, Yu-Li; Fann, Cathy Shen-Jang; Hsiao, Po-Chang; Wu, Jer-Yuarn; Hung, Shuen-Iu; Chen, Chun-Houh; Wu, Han-Ming; Jou, Yuh-Shan; Liu, Shi K.; Hwang, Tzung J.; Hsieh, Ming H.; Chang, Chien-Ching; Yang, Wei-Chih; Lin, Jin-Jia; Chou, Frank Huang-Chih; Faraone, Stephen V.; Tsuang, Ming T.; Hwu, Hai-Gwo; Chen, Wei J.

2009-01-01

Chromosome 6p is one of the most commonly implicated regions in the genome-wide linkage scans of schizophrenia, whereas further association studies for markers in this region were inconsistent likely due to heterogeneity. This study aimed to identify more homogeneous subgroups of families for fine mapping on regions around markers D6S296 and D6S309 (both in 6p24.3) as well as D6S274 (in 6p22.3) by means of similarity in neurocognitive functioning. A total of 160 families of patients with schizophrenia comprising at least two affected siblings who had data for 8 neurocognitive test variables of the Continuous Performance Test (CPT) and the Wisconsin Card Sorting Test (WCST) were subjected to cluster analysis with data visualization using the test scores of both affected siblings. Family clusters derived were then used separately in family-based association tests for 64 single nucleotide polymorphisms covering the region of 6p24.3 and 6p22.3. Three clusters were derived from the family-based clustering, with deficit cluster 1 representing deficit on the CPT, deficit cluster 2 representing deficit on both the CPT and the WCST, and a third cluster of non-deficit. After adjustment using false discovery rate for multiple testing, SNP rs13873 and haplotype rs1225934-rs13873 on BMP6-TXNDC5 genes were significantly associated with schizophrenia for the deficit cluster 1 but not for the deficit cluster 2 or non-deficit cluster. Our results provide further evidence that the BMP6-TXNDC5 locus on 6p24.3 may play a role in the selective impairments on sustained attention of schizophrenia. PMID:19694819

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

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

Tjong, Harianto; Li, Wenyuan; Kalhor, Reza

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Here, our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm themore » presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.« less

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

DOE PAGES

Tjong, Harianto; Li, Wenyuan; Kalhor, Reza; ...

2016-03-07

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Here, our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm themore » presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.« less

Dollars for lives: the effect of highway capital investments on traffic fatalities.

PubMed

Nguyen-Hoang, Phuong; Yeung, Ryan

2014-12-01

This study examines the effect of highway capital investments on highway fatalities. We used state-level data from the 48 contiguous states in the United States from 1968 through 2010 to estimate the effects on highway fatalities of capital expenditures and highway capital stock. We estimated these effects by controlling for a set of control variables together with state and year dummy variables and state-specific linear time trends. We found that capital expenditures and capital stock had significant and negative effects on highway fatalities. States faced with declines in gas tax revenues have already cut back drastically on spending on roads including on maintenance and capital outlay. If this trend continues, it may undermine traffic safety. While states and local governments are currently fiscally strained, it is important for them to continue investments in roadways to enhance traffic safety and, more significantly, to save lives. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

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.

Slab Geometry and Stress State of the Southwestern Colombia Subduction Zone

NASA Astrophysics Data System (ADS)

Chang, Ying

A high rate of intermediate-depth earthquakes is concentrates in the Cauca cluster (3.5°N-5.5°N) and isolated from nearby seismicity in the southwestern Colombia subduction zone. Previously-studied nests of intermediate-depth earthquakes show that a high seismicity rate is often associated with a slab tear, detachment, or contortion. The cause of the less-studied Cauca cluster is unknown. To investigate the cause, we image the slab geometry using precise relative locations of intermediate-depth earthquakes. We use the earthquake catalog produced and seismic waveforms recorded by the Colombian National Seismic Network from January 2010 to March 2014. We calculate the focal mechanisms to examine whether the earthquakes reactivate pre-existing faults or form new fractures. The focal mechanisms are inverted for the intraslab stress field to check the stress guide hypothesis and to evaluate the stress orientations with regard to the change in the slab geometry. The earthquake relocations indicate that the Cauca segment has a continuous 20 km thick seismic zone and increases in dip angle from north to south. Two 40-km-tall fingers of earthquakes extend out of the slab and into the mantle wedge. Different from the previously-studied nests, the Cauca cluster does not correspond to slab contortions or tearing. The cluster may be associated with a high amount of dehydrated fluid. The determined focal mechanisms of 69 earthquakes have various types and variably-oriented nodal planes, corresponding to the reactivation of pre-existing faults and the formation of new fractures. The results of stress inversion show that the extensional axis in the northern Cauca segment is in the plane of the slab and 25° from the downdip direction, and the southern part has along-strike extension. The compression is subnormal to the plane of the slab. The stress field supports the stress guide hypothesis and shows a consistent rotation with increase in slab dip angle.

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

Marlow, W.H.

An aerosol here is understood to be a two-component system comprised of gaseous and condensed phases with the characteristic that the condensed phase is not an equilibrium subsystem. In contrast to the usual definitions based upon geometrical or mechanical variables, this quasi-thermodynamic formulation is framed to emphasize the dynamical behavior of aerosols by allowing for coagulation and other aerosol evolutionary processes as natural consequences of the interactions and state variables appropriate to the system. As will become clear later, it also provides a point of departure for distinguishing aerosol particles from unstable gas-phase cluster systems. The question of accommodation inmore » particle collisions must be addressed as a prelude to the discussion of the role of long-range forces. Microscopic reversibility is frequently assumed for molecular collisions with either molecules or solid surfaces. In the case of aerosol collisions, the implication of this assumption is that collisions are elastic, which is contrary to the evidence from coagulation experiments and the conventional operational assumption of sticking upon collision. Gay and Berne have performed computer simulations of the collision of two clusters consisting of a total of 135 molecules interacting via Lennard-Jones potentials. That work showed that complete accommodation, accompanied by overall heating of the unified cluster, occurred. Since heating represents an irreversible degradation of the kinetic energy of the collision, the hamiltonian of the two-cluster system should be considered as dissipative and therefore microscopic reversibility does not apply.« less

A Detailed Study of the Variable Stars in Five Galactic Globular Clusters: IC4499, NGC4833, NGC6171 (M107), NGC6402 (M14), and NGC6584

NASA Astrophysics Data System (ADS)

Murphy, Brian W.; Darragh, Andrew; Hettinger, Paul; Hibshman, Adam; Johnson, Elliott W.; Liu, Z. J.; Pajkos, Michael A.; Stephenson, Hunter R.; Vondersaar, John R.; Conroy, Kyle E.; McCombs, Thayne A.; Reinhardt, Erik D.; Toddy, Joseph

2015-08-01

We present the results of an extensive study intended to search for and properly classify the variable stars in five galactic globular clusters. Each of the five clusters was observed hundreds to thousands of times over a time span ranging from 2 to 4 years using the SARA 0.6m located at Cerro Tololo Interamerican Observatory. The images were analyzed using the image subtract method of Alard (2000) to identify and produce light curves of all variables found in each cluster. In total we identified 373 variables with 140 of these being newly discovered increasing the number of known variables stars in these clusters by 60%. Of the total we have identified 312 RR Lyrae variables (187 RR0, 18 RR01, 99 RR1, 8 RR2), 9 SX Phe stars, 6 Cepheid variables, 11 eclipsing variables, and 35 long period variables. For IC4499 we identified 64 RR0, 18 RR01, 14 RR1, 4 RR2, 1 SX Phe, 1 eclipsing binary, and 2 long period variables. For NGC4833 we identified 10 RR0, 7 RR1, 2 RR2, 6 SX Phe, 5 eclipsing binaries, and 9 long period variables. For NGC6171 (M107) we identified 13 RR0, 7 RR1, and 1 SX Phe. For NGC6402 (M14) we identified 52 RR0, 56 RR1, 1 RR2, 1 SX Phe, 6 Cepheids, 1 eclipsing binary, and 15 long period variables. For NGC6584 we identified 48 RR0, 15 RR1, 1 RR2, 5 eclipsing binaries, and 9 long period variables. Using the RR Lyrae variables we found the mean V magnitude of the horizontal branch to be VHB = ⟨V ⟩RR = 17.63, 15.51, 15.72, 17.13, and 16.37 magnitudes for IC4499, NGC4833, NGC6171 (M107), NGC6402 (M14), and NGC6584, respectively. From our extensive data set we were able to obtain sufficient temporal and complete phase coverage of the RR Lyrae variables. This has allowed us not only to properly classify each of the RR Lyrae variables but also to use Fourier decomposition of the light curves to further analyze the properties of the variable stars and hence physical properties of each clusters. In this poster we will give the temperature, radius, stellar mass, metallicity, and helium abundance of the set of RR Lyrae variable stars found in each of the five globular clusters.

Multivariate generalized hidden Markov regression models with random covariates: Physical exercise in an elderly population.

PubMed

Punzo, Antonio; Ingrassia, Salvatore; Maruotti, Antonello

2018-04-22

A time-varying latent variable model is proposed to jointly analyze multivariate mixed-support longitudinal data. The proposal can be viewed as an extension of hidden Markov regression models with fixed covariates (HMRMFCs), which is the state of the art for modelling longitudinal data, with a special focus on the underlying clustering structure. HMRMFCs are inadequate for applications in which a clustering structure can be identified in the distribution of the covariates, as the clustering is independent from the covariates distribution. Here, hidden Markov regression models with random covariates are introduced by explicitly specifying state-specific distributions for the covariates, with the aim of improving the recovering of the clusters in the data with respect to a fixed covariates paradigm. The hidden Markov regression models with random covariates class is defined focusing on the exponential family, in a generalized linear model framework. Model identifiability conditions are sketched, an expectation-maximization algorithm is outlined for parameter estimation, and various implementation and operational issues are discussed. Properties of the estimators of the regression coefficients, as well as of the hidden path parameters, are evaluated through simulation experiments and compared with those of HMRMFCs. The method is applied to physical activity data. Copyright © 2018 John Wiley & Sons, Ltd.

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

PubMed Central

2013-01-01

Background Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only. Results In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification. Conclusions This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation. PMID:24010718

[The users of centers for AIDS information and prevention in the Comunidad Valenciana, Spain: a study based on cluster analysis].

PubMed

González Aracil, J; Ruiz Pérez, I; Aviñó Rico, M J; Hernández Aguado, I

1999-01-01

To measure the usefulness of multiple correspondence analysis (MCA) and cluster analysis applied to the epidemiological research of HIV infection. The specific are to explore the relationships between the different variables that characterize the users of the AIDS Information and Prevention Center (CIPS) and to identify clusters of characteristics which in terms of the attendance to these centers, could be considered similar. The clinical history the CIPS in the Valencian region in Spain was used as data source. The target population target were intravenous drug users (IDUSs) attending these centers between 1987 and 1994 (n = 6211). Information about socio-demographic and HIV type I infection-related variables (drug use and sexual behaviour) was collected by means of a semistructured questionnaire. A MCA was carried out to obtain a group of quantitative factors that were used in a cluster analysis. A 44.8% HIV type I prevalence was found. Five factors were detected by MCA that explain 51.14% of the total variability, of which sex, age and the usual sexual partner were the variables best explained. Cluster analysis allowed to describe 5 different subgroups of CIPS users according to their socio-demographics characteristics, risk behaviours and serologic status. It is necessary to highlight the categories 1 and 2, which collect the serologic status and the most relevant characteristics of HIV infection. Category I contains users with a negative serology and characterized by being mainly single adolescent men, with a low educational level; they stated that they have no steady sexual partner, do not share syringes and have been intravenous drug users between 3 and 10 years. They mainly come from the city of Alicante. Category 2 contains mainly people that are HIV positive and older. They also share syringes and have been intravenous drug users for a longer time; they have a higher education level and most of them come from the city of Valencia. The proposed method of analysis was able to characterise the CIPS users, identifying those socio-demographic variables and risk behaviours that are more related to the serologic status. The applicability of these techniques to epidemiologic studies of HIV type I infection is discussed.

Effectiveness of a stepped primary care smoking cessation intervention: cluster randomized clinical trial (ISTAPS study).

PubMed

Cabezas, Carmen; Advani, Mamta; Puente, Diana; Rodriguez-Blanco, Teresa; Martin, Carlos

2011-09-01

To evaluate the effectiveness in primary care of a stepped smoking cessation intervention based on the transtheoretical model of change. Cluster randomized trial; unit of randomization: basic care unit (family physician and nurse who care for the same group of patients); and intention-to-treat analysis. All interested basic care units (n = 176) that worked in 82 primary care centres belonging to the Spanish Preventive Services and Health Promotion Research Network in 13 regions of Spain. A total of 2,827 smokers (aged 14-85 years) who consulted a primary care centre for any reason, provided written informed consent and had valid interviews. The outcome variable was the 1-year continuous abstinence rate at the 2-year follow-up. The main variable was the study group (intervention/control). Intervention involved 6-month implementation of recommendations from a Clinical Practice Guideline which included brief motivational interviews for smokers at the precontemplation-contemplation stage, brief intervention for smokers in preparation-action who do not want help, intensive intervention with pharmacotherapy for smokers in preparation-action who want help and reinforcing intervention in the maintenance stage. Control group involved usual care. Among others, characteristics of tobacco use and motivation to quit variables were also collected. The 1-year continuous abstinence rate at the 2-year follow-up was 8.1% in the intervention group and 5.8% in the control group (P = 0.014). In the multivariate logistic regression, the odds of quitting of the intervention versus control group was 1.50 (95% confidence interval = 1.05-2.14). A stepped smoking cessation intervention based on the transtheoretical model significantly increased smoking abstinence at a 2-year follow-up among smokers visiting primary care centres. © 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.

MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC-MS metabolomic datasets.

PubMed

Edmands, William M B; Barupal, Dinesh K; Scalbert, Augustin

2015-03-01

MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker-MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R). All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC-MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository. © The Author 2014. Published by Oxford University Press.

MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC–MS metabolomic datasets

PubMed Central

Edmands, William M. B.; Barupal, Dinesh K.; Scalbert, Augustin

2015-01-01

Summary: MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker—MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R). Availability and implementation: All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC–MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository. Contact: ScalbertA@iarc.fr PMID:25348215

Integrating continuous stocks and flows into state-and-transition simulation models of landscape change

USGS Publications Warehouse

Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie-Josée

2018-01-01

State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete.Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a state-and-transition simulation model with stocks and flows (STSM-SF). The STSM-SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete-time stochastic process. The method differs from the traditional systems dynamics approach to stock-flow modelling in that the stocks and flows can be spatially-explicit, and the flows can be expressed as a function of the STSM states and transitions.We demonstrate the STSM-SF method by integrating a spatially-explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years.The new STSM-SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between them. With the addition of stocks and flows, STSMs provide a conceptually simple yet powerful approach for characterizing uncertainties in projections of a wide range of questions regarding landscape change.

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.

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

Stellar Variability in the Intermediate Age Cluster NGC 1846

NASA Astrophysics Data System (ADS)

Pajkos, Michael A.; Salinas, Ricardo; Vivas, Anna Katherina; Strader, Jay; Contreras, Rodrigo

2017-01-01

The existence of multiple stellar populations in Galactic globular clusters is considered a widespread phenomenon, with only a few possible exceptions. In the LMC intermediate-age globular clusters, the presence of extended main sequence turn off points (MSTOs), initially interpreted as evidence for multiple stellar populations, is now under scrutiny and stellar rotation has emerged as an alternative explanation. Here we propose yet another ingredient to this puzzle: the fact that the MSTO of these clusters passes through the instability strip making stellar variability a new alternative to explain this phenomenon. We report the first in-depth characterization of the variability, at the MSTO level, in any LMC cluster, and assess the role of variability masquerading as multiple stellar populations. We used the Gemini-S/GMOS to obtain time series photometry of NGC 1846. Using differencing image analysis, we identified 90 variables in the r-band, 68 of which were also found in the g-band. Of these 68, 57 were δ-scuti—with 35 having full phase coverage and 22 without. The average full period (Pfull) was 1.93 ± 0.79 hours. Furthermore, two eclipsing binaries and two RR Lyrae identified by OGLE were recovered. We conclude that not enough variables were found to provide a statistically significant impact on the extended MSTO, nor to explain the bifurcation of MSTO in NGC 1846. But the effect of variable stars could still be a viable explanation on clusters where only a hint of a MS extension is seen.

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.

Model-based Clustering of Categorical Time Series with Multinomial Logit Classification

NASA Astrophysics Data System (ADS)

Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Winter-Ebmer, Rudolf; Weber, Andrea

2010-09-01

A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance-based clustering methods cannot easily be extended to time series data, where an appropriate distance-measure is rather difficult to define, particularly for discrete-valued time series. Markov chain clustering, proposed by Pamminger and Frühwirth-Schnatter [6], is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This model-based clustering method is based on finite mixtures of first-order time-homogeneous Markov chain models. In order to further explain group membership we present an extension to the approach of Pamminger and Frühwirth-Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model. The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov chain Monte Carlo (MCMC) sampling scheme representing a (full) Gibbs-type sampler which involves only draws from standard distributions. Finally, an application to a panel of Austrian wage mobility data is presented which leads to an interesting segmentation of the Austrian labour market.

Under-Five Mortality in High Focus States in India: A District Level Geospatial Analysis

PubMed Central

Kumar, Chandan; Singh, Prashant Kumar; Rai, Rajesh Kumar

2012-01-01

Background This paper examines if, when controlling for biophysical and geographical variables (including rainfall, productivity of agricultural lands, topography/temperature, and market access through road networks), socioeconomic and health care indicators help to explain variations in the under-five mortality rate across districts from nine high focus states in India. The literature on this subject is inconclusive because the survey data, upon which most studies of child mortality rely, rarely include variables that measure these factors. This paper introduces these variables into an analysis of 284 districts from nine high focus states in India. Methodology/Principal Findings Information on the mortality indicator was accessed from the recently conducted Annual Health Survey of 2011 and other socioeconomic and geographic variables from Census 2011, District Level Household and Facility Survey (2007–08), Department of Economics and Statistics Divisions of the concerned states. Displaying high spatial dependence (spatial autocorrelation) in the mortality indicator (outcome variable) and its possible predictors used in the analysis, the paper uses the Spatial-Error Model in an effort to negate or reduce the spatial dependence in model parameters. The results evince that the coverage gap index (a mixed indicator of district wise coverage of reproductive and child health services), female literacy, urbanization, economic status, the number of newborn care provided in Primary Health Centers in the district transpired as significant correlates of under-five mortality in the nine high focus states in India. The study identifies three clusters with high under-five mortality rate including 30 districts, and advocates urgent attention. Conclusion Even after controlling the possible biophysical and geographical variables, the study reveals that the health program initiatives have a major role to play in reducing under-five mortality rate in the high focus states in India. PMID:22629412

An X-ray method for detecting substructure in galaxy clusters - Application to Perseus, A2256, Centaurus, Coma, and Sersic 40/6

NASA Technical Reports Server (NTRS)

Mohr, Joseph J.; Fabricant, Daniel G.; Geller, Margaret J.

1993-01-01

We use the moments of the X-ray surface brightness distribution to constrain the dynamical state of a galaxy cluster. Using X-ray observations from the Einstein Observatory IPC, we measure the first moment FM, the ellipsoidal orientation angle, and the axial ratio at a sequence of radii in the cluster. We argue that a significant variation in the image centroid FM as a function of radius is evidence for a nonequilibrium feature in the intracluster medium (ICM) density distribution. In simple terms, centroid shifts indicate that the center of mass of the ICM varies with radius. This variation is a tracer of continuing dynamical evolution. For each cluster, we evaluate the significance of variations in the centroid of the IPC image by computing the same statistics on an ensemble of simulated cluster images. In producing these simulated images we include X-ray point source emission, telescope vignetting, Poisson noise, and characteristics of the IPC. Application of this new method to five Abell clusters reveals that the core of each one has significant substructure. In addition, we find significant variations in the orientation angle and the axial ratio for several of the clusters.

Stellar-mass black holes in young massive and open stellar clusters and their role in gravitational-wave generation - II

NASA Astrophysics Data System (ADS)

Banerjee, Sambaran

2018-01-01

The study of stellar-remnant black holes (BH) in dense stellar clusters is now in the spotlight, especially due to their intrinsic ability to form binary black holes (BBH) through dynamical encounters, which potentially coalesce via gravitational-wave (GW) radiation. In this work, which is a continuation from a recent study (Paper I), additional models of compact stellar clusters with initial masses ≲ 105 M⊙ and also those with small fractions of primordial binaries (≲ 10 per cent) are evolved for long term, applying the direct N-body approach, assuming state-of-the-art stellar-wind and remnant-formation prescriptions. That way, a substantially broader range of computed models than that in Paper I is achieved. As in Paper I, the general-relativistic BBH mergers continue to be mostly mediated by triples that are bound to the clusters rather than happen among the ejected BBHs. In fact, the number of such in situ BBH mergers, per cluster, tends to increase significantly with the introduction of a small population of primordial binaries. Despite the presence of massive primordial binaries, the merging BBHs, especially the in situ ones, are found to be exclusively dynamically assembled and hence would be spin-orbit misaligned. The BBHs typically traverse through both the LISA's and the LIGO's detection bands, being audible to both instruments. The 'dynamical heating' of the BHs keeps the electron-capture-supernova (ECS) neutron stars (NS) from effectively mass segregating and participating in exchange interactions; the dynamically active BHs would also exchange into any NS binary within ≲1 Gyr. Such young massive and open clusters have the potential to contribute to the dynamical BBH merger detection rate to a similar extent as their more massive globular-cluster counterparts.

KmL3D: a non-parametric algorithm for clustering joint trajectories.

PubMed

Genolini, C; Pingault, J B; Driss, T; Côté, S; Tremblay, R E; Vitaro, F; Arnaud, C; Falissard, B

2013-01-01

In cohort studies, variables are measured repeatedly and can be considered as trajectories. A classic way to work with trajectories is to cluster them in order to detect the existence of homogeneous patterns of evolution. Since cohort studies usually measure a large number of variables, it might be interesting to study the joint evolution of several variables (also called joint-variable trajectories). To date, the only way to cluster joint-trajectories is to cluster each trajectory independently, then to cross the partitions obtained. This approach is unsatisfactory because it does not take into account a possible co-evolution of variable-trajectories. KmL3D is an R package that implements a version of k-means dedicated to clustering joint-trajectories. It provides facilities for the management of missing values, offers several quality criteria and its graphic interface helps the user to select the best partition. KmL3D can work with any number of joint-variable trajectories. In the restricted case of two joint trajectories, it proposes 3D tools to visualize the partitioning and then export 3D dynamic rotating-graphs to PDF format. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

PubMed

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

2015-05-01

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2015-01-01

Abstract To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice. PMID:25560745

Variable Stars in M13. II.The Red Variables and the Globular Cluster Period-Luminosity Relation

NASA Astrophysics Data System (ADS)

Osborn, W.; Layden, A.; Kopacki, G.; Smith, H.; Anderson, M.; Kelly, A.; McBride, K.; Pritzl, B.

2017-06-01

New CCD observations have been combined with archival data to investigate the nature of the red variables in the globular cluster M13. Mean magnitudes, colors and variation ranges on the UBVIC system have been determined for the 17 cataloged red variables. 15 of the stars are irregular or semi-regular variables that lie at the top of the red giant branch in the color-magnitude diagram. Two stars are not, including one with a well-defined period and a light curve shape indicating it is an ellipsoidal or eclipsing variable. All stars redder than (V-IC)0=1.38 mag vary, with the amplitudes being larger with increased stellar luminosity and with bluer filter passband. Searches of the data for periodicities yielded typical variability cycle times ranging from 30 d up to 92 d for the most luminous star. Several stars have evidence of multiple periods. The stars' period-luminosity diagram compared to those from microlensing survey data shows that most M13 red variables are overtone pulsators. Comparison with the diagrams for other globular clusters shows a correlation between red variable luminosity and cluster metallicity.

Typology of patients with fibromyalgia: cluster analysis of duloxetine study patients.

PubMed

Lipkovich, Ilya A; Choy, Ernest H; Van Wambeke, Peter; Deberdt, Walter; Sagman, Doron

2014-12-23

To identify distinct groups of patients with fibromyalgia (FM) with respect to multiple outcome measures. Data from 631 duloxetine-treated women in 4 randomized, placebo-controlled trials were included in a cluster analysis based on outcomes after up to 12 weeks of treatment. Corresponding classification rules were constructed using a classification tree method. Probabilities for transitioning from baseline to Week 12 category were estimated for placebo and duloxetine patients (Ntotal = 1188) using logistic regression. Five clusters were identified, from "worst" (high pain levels and severe mental/physical impairment) to "best" (low pain levels and nearly normal mental/physical function). For patients with moderate overall severity, mental and physical symptoms were less correlated, resulting in 2 distinct clusters based on these 2 symptom domains. Three key variables with threshold values were identified for classification of patients: Brief Pain Inventory (BPI) pain interference overall scores of <3.29 and <7.14, respectively, a Fibromyalgia Impact Questionnaire (FIQ) interference with work score of <2, and an FIQ depression score of ≥5. Patient characteristics and frequencies per baseline category were similar between treatments; >80% of patients were in the 3 worst categories. Duloxetine patients were significantly more likely to improve after 12 weeks than placebo patients. A sustained effect was seen with continued duloxetine treatment. FM patients are heterogeneous and can be classified into distinct subgroups by simple descriptive rules derived from only 3 variables, which may guide individual patient management. Duloxetine showed higher improvement rates than placebo and had a sustained effect beyond 12 weeks.

Pedagogical introduction to the entropy of entanglement for Gaussian states

NASA Astrophysics Data System (ADS)

Demarie, Tommaso F.

2018-05-01

In quantum information theory, the entropy of entanglement is a standard measure of bipartite entanglement between two partitions of a composite system. For a particular class of continuous variable quantum states, the Gaussian states, the entropy of entanglement can be expressed elegantly in terms of symplectic eigenvalues, elements that characterise a Gaussian state and depend on the correlations of the canonical variables. We give a rigorous step-by-step derivation of this result and provide physical insights, together with an example that can be useful in practice for calculations.

State fusion entropy for continuous and site-specific analysis of landslide stability changing regularities

NASA Astrophysics Data System (ADS)

Liu, Yong; Qin, Zhimeng; Hu, Baodan; Feng, Shuai

2018-04-01

Stability analysis is of great significance to landslide hazard prevention, especially the dynamic stability. However, many existing stability analysis methods are difficult to analyse the continuous landslide stability and its changing regularities in a uniform criterion due to the unique landslide geological conditions. Based on the relationship between displacement monitoring data, deformation states and landslide stability, a state fusion entropy method is herein proposed to derive landslide instability through a comprehensive multi-attribute entropy analysis of deformation states, which are defined by a proposed joint clustering method combining K-means and a cloud model. Taking Xintan landslide as the detailed case study, cumulative state fusion entropy presents an obvious increasing trend after the landslide entered accelerative deformation stage and historical maxima match highly with landslide macroscopic deformation behaviours in key time nodes. Reasonable results are also obtained in its application to several other landslides in the Three Gorges Reservoir in China. Combined with field survey, state fusion entropy may serve for assessing landslide stability and judging landslide evolutionary stages.

Factors driving stable growth of He clusters in W: first-principles study

NASA Astrophysics Data System (ADS)

Feng, Y. J.; Xin, T. Y.; Xu, Q.; Wang, Y. X.

2018-07-01

The evolution of helium (He) bubbles is responsible for the surface morphology variation and subsequent degradation of the properties of plasma-facing materials (PFMs) in nuclear fusion reactors. These severe problems unquestionably trace back to the behavior of He in PFMs, which is closely associated with the interaction between He and the matrix. In this paper, we decomposed the binding energy of the He cluster into three parts, those from W–W, W–He, and He–He interactions, using density functional theory. As a result, we clearly identified the main factors that determine a steplike decrease in the binding energy with increasing number of He atoms, which explains the process of self-trapping and athermal vacancy generation during He cluster growth in the PFM tungsten. The three interactions were found to synergetically shape the features of the steplike decrease in the binding energy. Fairly strong He–He repulsive forces at a short distance, which stem from antibonding states between He atoms, need to be released when additional He atoms are continuously bonded to the He cluster. This causes the steplike feature in the binding energy. The bonding states between W and He atoms in principle facilitate the decreasing trend of the binding energy. The decrease in binding energy with increasing number of He atoms implies that He clusters can grow stably.

Robust continuous clustering

PubMed Central

Shah, Sohil Atul

2017-01-01

Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank. PMID:28851838

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets.

PubMed

Naegle, Kristen M; Welsch, Roy E; Yaffe, Michael B; White, Forest M; Lauffenburger, Douglas A

2011-07-01

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems. © 2011 Naegle et al.

Subgroups of physically abusive parents based on cluster analysis of parenting behavior and affect.

PubMed

Haskett, Mary E; Smith Scott, Susan; Sabourin Ward, Caryn

2004-10-01

Cluster analysis of observed parenting and self-reported discipline was used to categorize 83 abusive parents into subgroups. A 2-cluster solution received support for validity. Cluster 1 parents were relatively warm, positive, sensitive, and engaged during interactions with their children, whereas Cluster 2 parents were relatively negative, disengaged or intrusive, and insensitive. Further, clusters differed in emotional health, parenting stress, perceptions of children, and problem solving. Children of parents in the 2 clusters differed on several indexes of social adjustment. Cluster 1 parents were similar to nonabusive parents (n = 66) on parenting and related constructs, but Cluster 2 parents differed from nonabusive parents on all clustering variables and many validation variables. Results highlight clinically relevant diversity in parenting practices and functioning among abusive parents. ((c) 2004 APA, all rights reserved).

K-Means Algorithm Performance Analysis With Determining The Value Of Starting Centroid With Random And KD-Tree Method

NASA Astrophysics Data System (ADS)

Sirait, Kamson; Tulus; Budhiarti Nababan, Erna

2017-12-01

Clustering methods that have high accuracy and time efficiency are necessary for the filtering process. One method that has been known and applied in clustering is K-Means Clustering. In its application, the determination of the begining value of the cluster center greatly affects the results of the K-Means algorithm. This research discusses the results of K-Means Clustering with starting centroid determination with a random and KD-Tree method. The initial determination of random centroid on the data set of 1000 student academic data to classify the potentially dropout has a sse value of 952972 for the quality variable and 232.48 for the GPA, whereas the initial centroid determination by KD-Tree has a sse value of 504302 for the quality variable and 214,37 for the GPA variable. The smaller sse values indicate that the result of K-Means Clustering with initial KD-Tree centroid selection have better accuracy than K-Means Clustering method with random initial centorid selection.

A Locus Encoding Variable Defense Systems against Invading DNA Identified in Streptococcus suis

PubMed Central

Okura, Masatoshi; Nozawa, Takashi; Watanabe, Takayasu; Murase, Kazunori; Nakagawa, Ichiro; Takamatsu, Daisuke; Osaki, Makoto; Sekizaki, Tsutomu; Gottschalk, Marcelo; Hamada, Shigeyuki

2017-01-01

Streptococcus suis, an important zoonotic pathogen, is known to have an open pan-genome and to develop a competent state. In S. suis, limited genetic lineages are suggested to be associated with zoonosis. However, little is known about the evolution of diversified lineages and their respective phenotypic or ecological characteristics. In this study, we performed comparative genome analyses of S. suis, with a focus on the competence genes, mobile genetic elements, and genetic elements related to various defense systems against exogenous DNAs (defense elements) that are associated with gene gain/loss/exchange mediated by horizontal DNA movements and their restrictions. Our genome analyses revealed a conserved competence-inducing peptide type (pherotype) of the competence system and large-scale genome rearrangements in certain clusters based on the genome phylogeny of 58 S. suis strains. Moreover, the profiles of the defense elements were similar or identical to each other among the strains belonging to the same genomic clusters. Our findings suggest that these genetic characteristics of each cluster might exert specific effects on the phenotypic or ecological differences between the clusters. We also found certain loci that shift several types of defense elements in S. suis. Of note, one of these loci is a previously unrecognized variable region in bacteria, at which strains of distinct clusters code for different and various defense elements. This locus might represent a novel defense mechanism that has evolved through an arms race between bacteria and invading DNAs, mediated by mobile genetic elements and genetic competence. PMID:28379509

Evolution and Determinants of Health-Related Quality-of-Life in Kidney Transplant Patients Over the First 3 Years After Transplantation.

PubMed

Villeneuve, Claire; Laroche, Marie-Laure; Essig, Marie; Merville, Pierre; Kamar, Nassim; Coubret, Anne; Lacroix, Isabelle; Bouchet, Stéphane; Fruit, Dorothée; Marquet, Pierre; Rousseau, Annick

2016-03-01

Health-related quality of life (HRQOL) usually improved after kidney transplantation; however, a non-negligible number of patients did not benefit from transplantation in HRQOL. The aims of this cohort study were to describe the evolution of HRQOL in kidney transplant recipients to search for subgroups with distinct time profiles and to investigate these determinants. Three hundred thirty-seven adult patients were followed up from 1 to 36 months after kidney transplantation. Each patient completed repeated HRQOL assessments (median, 5; range, 2-9). K-means for longitudinal data was used to identify homogeneous clusters of HRQOL time profiles obtained for the mental and physical composite scores (MCS and PCS) and for the 8 dimensions of the short-form 36 scale. Covariates associated with these clusters were investigated using random forest analysis. Magnitude and shape of the HRQOL variations over time were investigated using linear regression mixed models. Two longitudinal clusters were identified for the time profiles of PCS and MCS. Patients classified in the higher cluster (ie, 60% of the population) exhibited a steady-state HRQOL, similar on average to the general population, whereas in the lower cluster, PCS and MCS scores were significantly lower than in the general population. Muscular weakness in the first year after transplantation explained 19% of the interpatient variability of PCS 3 months after transplantation, whereas associated with anxiety, it explained 24% of interpatient MCS variability. This work suggests to promote (i) physical rehabilitation programs after transplantation to curb the muscular loss and (ii) systematic attention to the patient's anxiety.

[Biodiversity and depressive symptoms in Mexican adults: Exploration of beneficial environmental effects].

PubMed

Duarte-Tagles, Héctor; Salinas-Rodríguez, Aarón; Idrovo, Álvaro J; Búrquez, Alberto; Corral-Verdugo, Víctor

2015-08-01

Depression is a highly prevalent illness among adults, and it is the second most frequently reported mental disorder in urban settings in México. Exposure to natural environments and its components may improve the mental health of the population. To evaluate the association between biodiversity indicators and the prevalence of depressive symptoms among the adult population (20 to 65 years of age) in México. Information from the Encuesta Nacional de Salud y Nutrición 2006 (ENSANUT 2006) and the Compendio de Estadísticas Ambientales 2008 was analyzed. A biodiversity index was constructed based on the species richness and ecoregions in each state. A multilevel logistic regression model was built with random intercepts and a multiple logistic regression was generated with clustering by state. The factors associated with depressive symptoms were being female, self-perceived as indigenous, lower education level, not living with a partner, lack of steady paid work, having a chronic illness and drinking alcohol. The biodiversity index was found to be inversely associated with the prevalence of depressive symptoms when defined as a continuous variable, and the results from the regression were grouped by state (OR=0.71; 95% CI = 0.59-0.87). Although the design was cross-sectional, this study adds to the evidence of the potential benefits to mental health from contact with nature and its components.

Photoelectron Spectroscopy Study of [Ta2B6]-: a Hexagonal Bipyramdial Cluster

NASA Astrophysics Data System (ADS)

Jian, Tian; Li, Weili; Romanescu, Constantin; Wang, Lai-Sheng

2014-06-01

It has been a long-sought goal in cluster science to discover stable atomic clusters as building blocks for cluster-assembled nanomaterials, as exemplified by the fullerenes and their subsequent bulk syntheses.[1,2] Clusters have also been considered as models to understand bulk properties, providing a bridge between molecular and solid-state chemistry.[3] Herein we report a joint photoelectron spectroscopy and theoretical study on the [Ta2B6]- and [Ta2B6] clusters.[4] The photoelectron spectrum of [Ta2B6]- displays a simple spectral pattern and a large HOMO-LUMO gap, suggesting its high symmetry. Theoretical calculations show that both the neutral and anion are D6h pyramidal. The chemical bonding analyses for [Ta2B6] revealed the nature of the B6 and Ta interactions and uncovered strong covalent bonding between B6 and Ta. The D6h-[TaB6Ta] gaseous cluster is reminiscent of the structural pattern in the ReB6X6Re core in the [(Cp*Re)2B6H4Cl2] and the TiB6Ti motif in the newly synthesized Ti7Rh4Ir2B8 solid-state compound.[5,6] The current work provides an intrinsic link between a gaseous cluster and motifs for solid materials. Continued investigations of the transition-metal boron clusters may lead to the discovery of new structural motifs involving pure boron clusters for the design of novel boride materials. Reference [1] H.W. Kroto, J. R. Heath, S. C. OBrien, R. F. Curl, R. E. Smalley, Nature 1985, 318, 162 - 163. [2] W. Krtschmer, L. D. Lamb, K. Fostiropoulos, D. R. Huffman, Nature 1990, 347, 354 - 358. [3] T. P. Fehlner, J.-F. Halet, J.-Y. Saillard, Molecular Clusters: A Bridge to Solid-State Chemitry, Cambridge University Press, UK, 2007. [4] W. L. Li, L. Xie, T. Jian, C. Romanescu, X. Huang, L.-S. Wang, Angew. Chem. Int. Ed. 2014, 126, 1312 - 1316. [5] B. Le Guennic, H. Jiao, S. Kahlal, J.-Y. Saillard, J.-F. Halet, S. Ghosh, M. Shang, A. M. Beatty, A. L. Rheingold, T. P. Fehlner, J. Am. Chem. Soc. 2004, 126, 3203 - 3217. [6] B. P. T. Fokwa, M. Hermus, Angew. Chem. 2012, 124, 1734 - 1737; Angew. Chem. Int. Ed. 2012, 51, 1702 - 1705.

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).

Distillation of mixed-state continuous-variable entanglement by photon subtraction

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

Zhang Shengli; Loock, Peter van

2010-12-15

We present a detailed theoretical analysis for the distillation of one copy of a mixed two-mode continuous-variable entangled state using beam splitters and coherent photon-detection techniques, including conventional on-off detectors and photon-number-resolving detectors. The initial Gaussian mixed-entangled states are generated by transmitting a two-mode squeezed state through a lossy bosonic channel, corresponding to the primary source of errors in current approaches to optical quantum communication. We provide explicit formulas to calculate the entanglement in terms of logarithmic negativity before and after distillation, including losses in the channel and the photon detection, and show that one-copy distillation is still possible evenmore » for losses near the typical fiber channel attenuation length. A lower bound for the transmission coefficient of the photon-subtraction beam splitter is derived, representing the minimal value that still allows to enhance the entanglement.« less

Order-parameter model for unstable multilane traffic flow

NASA Astrophysics Data System (ADS)

Lubashevsky, Ihor A.; Mahnke, Reinhard

2000-11-01

We discuss a phenomenological approach to the description of unstable vehicle motion on multilane highways that explains in a simple way the observed sequence of the ``free flow <--> synchronized mode <--> jam'' phase transitions as well as the hysteresis in these transitions. We introduce a variable called an order parameter that accounts for possible correlations in the vehicle motion at different lanes. So, it is principally due to the ``many-body'' effects in the car interaction in contrast to such variables as the mean car density and velocity being actually the zeroth and first moments of the ``one-particle'' distribution function. Therefore, we regard the order parameter as an additional independent state variable of traffic flow. We assume that these correlations are due to a small group of ``fast'' drivers and by taking into account the general properties of the driver behavior we formulate a governing equation for the order parameter. In this context we analyze the instability of homogeneous traffic flow that manifested itself in the above-mentioned phase transitions and gave rise to the hysteresis in both of them. Besides, the jam is characterized by the vehicle flows at different lanes which are independent of one another. We specify a certain simplified model in order to study the general features of the car cluster self-formation under the ``free flow <--> synchronized motion'' phase transition. In particular, we show that the main local parameters of the developed cluster are determined by the state characteristics of vehicle motion only.

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

NASA Technical Reports Server (NTRS)

Koslovsky, Matthew; Arellano, John; Schaefer, Caroline; Feiveson, Alan; Young, Millennia; Lee, Stuart

2017-01-01

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.

Resemblance profiles as clustering decision criteria: Estimating statistical power, error, and correspondence for a hypothesis test for multivariate structure.

PubMed

Kilborn, Joshua P; Jones, David L; Peebles, Ernst B; Naar, David F

2017-04-01

Clustering data continues to be a highly active area of data analysis, and resemblance profiles are being incorporated into ecological methodologies as a hypothesis testing-based approach to clustering multivariate data. However, these new clustering techniques have not been rigorously tested to determine the performance variability based on the algorithm's assumptions or any underlying data structures. Here, we use simulation studies to estimate the statistical error rates for the hypothesis test for multivariate structure based on dissimilarity profiles (DISPROF). We concurrently tested a widely used algorithm that employs the unweighted pair group method with arithmetic mean (UPGMA) to estimate the proficiency of clustering with DISPROF as a decision criterion. We simulated unstructured multivariate data from different probability distributions with increasing numbers of objects and descriptors, and grouped data with increasing overlap, overdispersion for ecological data, and correlation among descriptors within groups. Using simulated data, we measured the resolution and correspondence of clustering solutions achieved by DISPROF with UPGMA against the reference grouping partitions used to simulate the structured test datasets. Our results highlight the dynamic interactions between dataset dimensionality, group overlap, and the properties of the descriptors within a group (i.e., overdispersion or correlation structure) that are relevant to resemblance profiles as a clustering criterion for multivariate data. These methods are particularly useful for multivariate ecological datasets that benefit from distance-based statistical analyses. We propose guidelines for using DISPROF as a clustering decision tool that will help future users avoid potential pitfalls during the application of methods and the interpretation of results.

Clustering Binary Data in the Presence of Masking Variables

ERIC Educational Resources Information Center

Brusco, Michael J.

2004-01-01

A number of important applications require the clustering of binary data sets. Traditional nonhierarchical cluster analysis techniques, such as the popular K-means algorithm, can often be successfully applied to these data sets. However, the presence of masking variables in a data set can impede the ability of the K-means algorithm to recover the…

Cluster synchronization in networks of identical oscillators with α-function pulse coupling.

PubMed

Chen, Bolun; Engelbrecht, Jan R; Mirollo, Renato

2017-02-01

We study a network of N identical leaky integrate-and-fire model neurons coupled by α-function pulses, weighted by a coupling parameter K. Studies of the dynamics of this system have mostly focused on the stability of the fully synchronized and the fully asynchronous splay states, which naturally depends on the sign of K, i.e., excitation vs inhibition. We find that there is also a rich set of attractors consisting of clusters of fully synchronized oscillators, such as fixed (N-1,1) states, which have synchronized clusters of sizes N-1 and 1, as well as splay states of clusters with equal sizes greater than 1. Additionally, we find limit cycles that clarify the stability of previously observed quasiperiodic behavior. Our framework exploits the neutrality of the dynamics for K=0 which allows us to implement a dimensional reduction strategy that simplifies the dynamics to a continuous flow on a codimension 3 subspace with the sign of K determining the flow direction. This reduction framework naturally incorporates a hierarchy of partially synchronized subspaces in which the new attracting states lie. Using high-precision numerical simulations, we describe completely the sequence of bifurcations and the stability of all fixed points and limit cycles for N=2-4. The set of possible attracting states can be used to distinguish different classes of neuron models. For instance from our previous work [Chaos 24, 013114 (2014)CHAOEH1054-150010.1063/1.4858458] we know that of the types of partially synchronized states discussed here, only the (N-1,1) states can be stable in systems of identical coupled sinusoidal (i.e., Kuramoto type) oscillators, such as θ-neuron models. Upon introducing a small variation in individual neuron parameters, the attracting fixed points we discuss here generalize to equivalent fixed points in which neurons need not fire coincidently.

Cluster synchronization in networks of identical oscillators with α -function pulse coupling

NASA Astrophysics Data System (ADS)

Chen, Bolun; Engelbrecht, Jan R.; Mirollo, Renato

2017-02-01

We study a network of N identical leaky integrate-and-fire model neurons coupled by α -function pulses, weighted by a coupling parameter K . Studies of the dynamics of this system have mostly focused on the stability of the fully synchronized and the fully asynchronous splay states, which naturally depends on the sign of K , i.e., excitation vs inhibition. We find that there is also a rich set of attractors consisting of clusters of fully synchronized oscillators, such as fixed (N -1 ,1 ) states, which have synchronized clusters of sizes N -1 and 1, as well as splay states of clusters with equal sizes greater than 1. Additionally, we find limit cycles that clarify the stability of previously observed quasiperiodic behavior. Our framework exploits the neutrality of the dynamics for K =0 which allows us to implement a dimensional reduction strategy that simplifies the dynamics to a continuous flow on a codimension 3 subspace with the sign of K determining the flow direction. This reduction framework naturally incorporates a hierarchy of partially synchronized subspaces in which the new attracting states lie. Using high-precision numerical simulations, we describe completely the sequence of bifurcations and the stability of all fixed points and limit cycles for N =2 -4 . The set of possible attracting states can be used to distinguish different classes of neuron models. For instance from our previous work [Chaos 24, 013114 (2014), 10.1063/1.4858458] we know that of the types of partially synchronized states discussed here, only the (N -1 ,1 ) states can be stable in systems of identical coupled sinusoidal (i.e., Kuramoto type) oscillators, such as θ -neuron models. Upon introducing a small variation in individual neuron parameters, the attracting fixed points we discuss here generalize to equivalent fixed points in which neurons need not fire coincidently.

Asymmetric DNA methylation of CpG dyads is a feature of secondary DMRs associated with the Dlk1/Gtl2 imprinting cluster in mouse.

PubMed

Guntrum, Megan; Vlasova, Ekaterina; Davis, Tamara L

2017-01-01

Differential DNA methylation plays a critical role in the regulation of imprinted genes. The differentially methylated state of the imprinting control region is inherited via the gametes at fertilization, and is stably maintained in somatic cells throughout development, influencing the expression of genes across the imprinting cluster. In contrast, DNA methylation patterns are more labile at secondary differentially methylated regions which are established at imprinted loci during post-implantation development. To investigate the nature of these more variably methylated secondary differentially methylated regions, we adopted a hairpin linker bisulfite mutagenesis approach to examine CpG dyad methylation at differentially methylated regions associated with the murine Dlk1/Gtl2 imprinting cluster on both complementary strands. We observed homomethylation at greater than 90% of the methylated CpG dyads at the IG-DMR, which serves as the imprinting control element. In contrast, homomethylation was only observed at 67-78% of the methylated CpG dyads at the secondary differentially methylated regions; the remaining 22-33% of methylated CpG dyads exhibited hemimethylation. We propose that this high degree of hemimethylation could explain the variability in DNA methylation patterns at secondary differentially methylated regions associated with imprinted loci. We further suggest that the presence of 5-hydroxymethylation at secondary differentially methylated regions may result in hemimethylation and methylation variability as a result of passive and/or active demethylation mechanisms.

A CCD Search for Variable Stars of Spectral Type B in the Northern Hemisphere Open Clusters. IX. NGC 457

NASA Astrophysics Data System (ADS)

Moździerski, D.; Pigulski, A.; Kopacki, G.; Kołaczkowski, Z.; Stęślicki, M.

2014-06-01

We present results of a BVIC variability survey in the young open cluster NGC 457 based on observations obtained during three separate runs spanning almost 20 years. In total, we found 79 variable stars, of which 66 are new. The BVIC photometry was transformed to the standard system and used to derive cluster parameters by means of isochrone fitting. The cluster is about 20 Myr old, the mean reddening amounts to about 0.48 mag in terms of the color excess E(B-V). Depending on the metallicity, the isochrone fitting yields a distance between 2.3 kpc and 2.9 kpc, which locates the cluster in the Perseus arm of the Galaxy. Using the complementary Hα photometry carried out in two seasons separated by over 10 years, we find that the cluster is very rich in Be stars. In total, 15 stars in the observed field of which 14 are cluster members showed Hα in emission either during our observations or in the past. Most of the Be stars vary in brightness on different time scales including short-period variability related most likely to g-mode pulsations. A single-epoch spectrum of NGC 457-6 shows that this Be star is presently in the shell phase. The inventory of variable stars in the observed field consists of a single β Cep-type star, NGC 457-8, 13 Be stars, 21 slowly pulsating B stars, seven δ Sct stars, one γ Dor star, 16 unclassified periodic stars, 8 eclipsing systems and a dozen of stars with irregular variability, of which six are also B-type stars. As many as 45 variable stars are of spectral type B which is the largest number in all open clusters presented in this series of papers. The most interesting is the discovery of a large group of slowly pulsating B stars which occupy the cluster main sequence in the range between V=11 mag and 14.5 mag, corresponding to spectral types B3 to B8. They all have very low amplitudes and about half show pulsations with frequencies higher than 3 d-1. We argue that these are most likely fast-rotating slowly pulsating B stars, observed also in other open clusters.

Identification of Hard X-ray Sources in Galactic Globular Clusters: Simbol-X Simulations

NASA Astrophysics Data System (ADS)

Servillat, M.

2009-05-01

Globular clusters harbour an excess of X-ray sources compared to the number of X-ray sources in the Galactic plane. It has been proposed that many of these X-ray sources are cataclysmic variables that have an intermediate magnetic field, i.e. intermediate polars, which remains to be confirmed and understood. We present here several methods to identify intermediate polars in globular clusters from multiwavelength analysis. First, we report on XMM-Newton, Chandra and HST observations of the very dense Galactic globular cluster NGC 2808. By comparing UV and X-ray properties of the cataclysmic variable candidates, the fraction of intermediate polars in this cluster can be estimated. We also present the optical spectra of two cataclysmic variables in the globular cluster M 22. The HeII (4868 Å) emission line in these spectra could be related to the presence of a magnetic field in these objects. Simulations of Simbol-X observations indicate that the angular resolution is sufficient to study X-ray sources in the core of close, less dense globular clusters, such as M 22. The sensitivity of Simbol-X in an extended energy band up to 80 keV will allow us to discriminate between hard X-ray sources (such as magnetic cataclysmic variables) and soft X-ray sources (such as chromospherically active binaries).

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

Chen, Haixia; Zhang, Jing

We propose a scheme for continuous-variable quantum cloning of coherent states with phase-conjugate input modes using linear optics. The quantum cloning machine yields M identical optimal clones from N replicas of a coherent state and N replicas of its phase conjugate. This scheme can be straightforwardly implemented with the setups accessible at present since its optical implementation only employs simple linear optical elements and homodyne detection. Compared with the original scheme for continuous-variable quantum cloning with phase-conjugate input modes proposed by Cerf and Iblisdir [Phys. Rev. Lett. 87, 247903 (2001)], which utilized a nondegenerate optical parametric amplifier, our scheme losesmore » the output of phase-conjugate clones and is regarded as irreversible quantum cloning.« less

Scheme for generating distillation-favorable continuous-variable entanglement via three concurrent parametric down-conversions in a single χ⁽²⁾ nonlinear photonic crystal.

PubMed

Gong, Yan-Xiao; Zhang, ShengLi; Xu, P; Zhu, S N

2016-03-21

We propose to generate a single-mode-squeezing two-mode squeezed vacuum state via a single χ⁽²⁾ nonlinear photonic crystal. The state is favorable for existing Gaussian entanglement distillation schemes, since local squeezing operations can enhance the final entanglement and the success probability. The crystal is designed for enabling three concurrent quasi-phase-matching parametric-down conversions, and hence relieves the auxiliary on-line bi-side local squeezing operations. The compact source opens up a way for continuous-variable quantum technologies and could find more potential applications in future large-scale quantum networks.

Genetic variability of garlic accessions as revealed by agro-morphological traits evaluated under different environments.

PubMed

Hoogerheide, E S S; Azevedo Filho, J A; Vencovsky, R; Zucchi, M I; Zago, B W; Pinheiro, J B

2017-05-31

The cultivated garlic (Allium sativum L.) displays a wide phenotypic diversity, which is derived from natural mutations and phenotypic plasticity, due to dependence on soil type, moisture, latitude, altitude and cultural practices, leading to a large number of cultivars. This study aimed to evaluate the genetic variability shown by 63 garlic accessions belonging to Instituto Agronômico de Campinas and the Escola Superior de Agricultura "Luiz de Queiroz" germplasm collections. We evaluated ten quantitative characters in experimental trials conducted under two localities of the State of São Paulo: Monte Alegre do Sul and Piracicaba, during the agricultural year of 2007, in a randomized blocks design with five replications. The Mahalanobis distance was used to measure genetic dissimilarities. The UPGMA method and Tocher's method were used as clustering procedures. Results indicated significant variation among accessions (P < 0.01) for all evaluated characters, except for the percentage of secondary bulb growth in MAS, indicating the existence of genetic variation for bulb production, and germplasm evaluation considering different environments is more reliable for the characterization of the genotypic variability among garlic accessions, since it diminishes the environmental effects in the clustering of genotypes.

Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow

NASA Astrophysics Data System (ADS)

Ho, Michelle; Lall, Upmanu; Sun, Xun; Cook, Edward R.

2017-04-01

The development of paleoclimate streamflow reconstructions in the conterminous United States (CONUS) has provided water resource managers with improved insights into multidecadal and centennial scale variability that cannot be reliably detected using shorter instrumental records. Paleoclimate streamflow reconstructions have largely focused on individual catchments limiting the ability to quantify variability across the CONUS. The Living Blended Drought Atlas (LBDA), a spatially and temporally complete 555 year long paleoclimate record of summer drought across the CONUS, provides an opportunity to reconstruct and characterize streamflow variability at a continental scale. We explore the validity of the first paleoreconstructions of streamflow that span the CONUS informed by the LBDA targeting a set of U.S. Geological Survey streamflow sites. The reconstructions are skillful under cross validation across most of the country, but the variance explained is generally low. Spatial and temporal structures of streamflow variability are analyzed using hierarchical clustering, principal component analysis, and wavelet analyses. Nine spatially coherent clusters are identified. The reconstructions show signals of contemporary droughts such as the Dust Bowl (1930s) and 1950s droughts. Decadal-scale variability was detected in the late 1900s in the western U.S., however, similar modes of temporal variability were rarely present prior to the 1950s. The twentieth century featured longer wet spells and shorter dry spells compared with the preceding 450 years. Streamflows in the Pacific Northwest and Northeast are negatively correlated with the central U.S. suggesting the potential to mitigate some drought impacts by balancing economic activities and insurance pools across these regions during major droughts.

Influence of Carbon Nanotube Clustering on Mechanical and Electrical Properties of Cement Pastes

PubMed Central

Jang, Sung-Hwan; Kawashima, Shiho; Yin, Huiming

2016-01-01

Given the continued challenge of dispersion, for practical purposes, it is of interest to evaluate the impact of multi-walled carbon nanotubes (MWCNTs) at different states of clustering on the eventual performance properties of cement paste. This study evaluated the clustering of MWCNTs and the resultant effect on the mechanical and electrical properties when incorporated into cement paste. Cement pastes containing different concentrations of MWCNTs (up to 0.5% by mass of cement) with/without surfactant were characterized. MWCNT clustering was assessed qualitatively in an aqueous solution through visual observation, and quantitatively in cement matrices using a scanning electron microscopy technique. Additionally, the corresponding 28-day compressive strength, tensile strength, and electrical conductivity were measured. Results showed that the use of surfactant led to a downward shift in the MWCNT clustering size distribution in the matrices of MWCNT/cement paste, indicating improved dispersion of MWCNTs. The compressive strength, tensile strength, and electrical conductivity of the composites with surfactant increased with MWCNT concentration and were higher than those without surfactant at all concentrations. PMID:28773348

Hierarchical clustering using correlation metric and spatial continuity constraint

DOEpatents

Stork, Christopher L.; Brewer, Luke N.

2012-10-02

Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

Attention-based classification pattern, a research domain criteria framework, in youths with bipolar disorder and attention-deficit/hyperactivity disorder.

PubMed

Kleinman, Ana; Caetano, Sheila Cavalcante; Brentani, Helena; Rocca, Cristiana Castanho de Almeida; dos Santos, Bernardo; Andrade, Enio Roberto; Zeni, Cristian Patrick; Tramontina, Silzá; Rohde, Luis Augusto Paim; Lafer, Beny

2015-03-01

The National Institute of Mental Health has initiated the Research Domain Criteria (RDoC) project. Instead of using disorder categories as the basis for grouping individuals, the RDoC suggests finding relevant dimensions that can cut across traditional disorders. Our aim was to use the RDoC's framework to study patterns of attention deficit based on results of Conners' Continuous Performance Test (CPT II) in youths diagnosed with bipolar disorder (BD), attention-deficit/hyperactivity disorder (ADHD), BD+ADHD and controls. Eighteen healthy controls, 23 patients with ADHD, 10 with BD and 33 BD+ADHD aged 12-17 years old were assessed. Pattern recognition was used to partition subjects into clusters based simultaneously on their performance in all CPT II variables. A Fisher's linear discriminant analysis was used to build a classifier. Using cluster analysis, the entire sample set was best clustered into two new groups, A and B, independently of the original diagnoses. ADHD and BD+ADHD were divided almost 50% in each subgroup, and there was an agglomeration of controls and BD in group B. Group A presented a greater impairment with higher means in all CPT II variables and lower Children's Global Assessment Scale. We found a high cross-validated classification accuracy for groups A and B: 95.2%. Variability of response time was the strongest CPT II measure in the discriminative pattern between groups A and B. Our classificatory exercise supports the concept behind new approaches, such as the RDoC framework, for child and adolescent psychiatry. Our approach was able to define clinical subgroups that could be used in future pathophysiological and treatment studies. © The Royal Australian and New Zealand College of Psychiatrists 2014.

Congested traffic states in empirical observations and microscopic simulations

NASA Astrophysics Data System (ADS)

Treiber, Martin; Hennecke, Ansgar; Helbing, Dirk

2000-08-01

We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. 82, 4360 (1999)]. We simulate these situations with a continuous microscopic single-lane model, the ``intelligent driver model,'' using empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.

Explaining Variability in High School Students' Access to and Enrollment in Career Academies and Career Theme Clusters in Florida: Multi-Level Analyses of Student and School Factors

ERIC Educational Resources Information Center

Evan, Aimee J.; Burden, Frances F.; Gheen, Margaret H.; Smerdon, Becky A.

2013-01-01

Career academies have been effective in reducing the high school dropout rates and increasing academic course taking and course credit accumulation among students (Kemple & Willner, 2008; Kemple & Snipes, 2000). However, not all students have access to career academy programs as they are not universally implemented across the state of…

Observing Globular Cluster RR Lyrae Variables with the BYU West Mountain Observatory

NASA Astrophysics Data System (ADS)

Jeffery, E. J.; Joner, M. D.

2016-06-01

We have utilized the 0.9-meter telescope of the Brigham Young University West Mountain Observatory to secure data on six northern hemisphere globular clusters. Here we present representative observations of RR Lyrae stars located in these clusters, including light curves. We compare light curves produced using both DAOPHOT and ISIS software packages. Light curve fitting is done with FITLC. We find that for well-separated stars, DAOPHOT and ISIS provide comparable results. However, for stars within the cluster core, ISIS provides superior results. These improved techniques will allow us to better measure the properties of cluster variable stars.

Cooperative epidemics on multiplex networks.

PubMed

Azimi-Tafreshi, N

2016-04-01

The spread of one disease, in some cases, can stimulate the spreading of another infectious disease. Here, we treat analytically a symmetric coinfection model for spreading of two diseases on a two-layer multiplex network. We allow layer overlapping, but we assume that each layer is random and locally loopless. Infection with one of the diseases increases the probability of getting infected with the other. Using the generating function method, we calculate exactly the fraction of individuals infected with both diseases (so-called coinfected clusters) in the stationary state, as well as the epidemic spreading thresholds and the phase diagram of the model. With increasing cooperation, we observe a tricritical point and the type of transition changes from continuous to hybrid. Finally, we compare the coinfected clusters in the case of cooperating diseases with the so-called "viable" clusters in networks with dependencies.

Cooperative epidemics on multiplex networks

NASA Astrophysics Data System (ADS)

Azimi-Tafreshi, N.

2016-04-01

The spread of one disease, in some cases, can stimulate the spreading of another infectious disease. Here, we treat analytically a symmetric coinfection model for spreading of two diseases on a two-layer multiplex network. We allow layer overlapping, but we assume that each layer is random and locally loopless. Infection with one of the diseases increases the probability of getting infected with the other. Using the generating function method, we calculate exactly the fraction of individuals infected with both diseases (so-called coinfected clusters) in the stationary state, as well as the epidemic spreading thresholds and the phase diagram of the model. With increasing cooperation, we observe a tricritical point and the type of transition changes from continuous to hybrid. Finally, we compare the coinfected clusters in the case of cooperating diseases with the so-called "viable" clusters in networks with dependencies.

Performance improvement of eight-state continuous-variable quantum key distribution with an optical amplifier

NASA Astrophysics Data System (ADS)

Guo, Ying; Li, Renjie; Liao, Qin; Zhou, Jian; Huang, Duan

2018-02-01

Discrete modulation is proven to be beneficial to improving the performance of continuous-variable quantum key distribution (CVQKD) in long-distance transmission. In this paper, we suggest a construct to improve the maximal generated secret key rate of discretely modulated eight-state CVQKD using an optical amplifier (OA) with a slight cost of transmission distance. In the proposed scheme, an optical amplifier is exploited to compensate imperfection of Bob's apparatus, so that the generated secret key rate of eight-state protocol is enhanced. Specifically, we investigate two types of optical amplifiers, phase-insensitive amplifier (PIA) and phase-sensitive amplifier (PSA), and thereby obtain approximately equivalent improved performance for eight-state CVQKD system when applying these two different amplifiers. Numeric simulation shows that the proposed scheme can well improve the generated secret key rate of eight-state CVQKD in both asymptotic limit and finite-size regime. We also show that the proposed scheme can achieve the relatively high-rate transmission at long-distance communication system.

VizieR Online Data Catalog: Updated catalog of variable stars in globular clusters (Clement+ 2017)

NASA Astrophysics Data System (ADS)

Clement, C. M.

2017-02-01

This Catalogue is an update to Helen Sawyer Hogg's Third Catalogue on Variable Stars in Globular Clusters (1973, David Dunlap Observatory Publications, Volume 3, Number 6: 1973PDDO....3....6S; see Cat V/97; see also Clement+, 2001AJ....122.2587C). This catalogue is based on the individual cluster files downloaded on http://www.astro.utoronto.ca/~cclement/cat/listngc.html on the 01-Feb-2017. Later updates are indicated in clusters.dat; column "Update". (7 data files).

Cross-Contextual Variability in Parents' and School Tutors' Conflict Resolution Styles and Positive Development

ERIC Educational Resources Information Center

Rodríguez-Ruiz, Beatriz; Rodrigo, María José; Martínez-González, Raquel-Amaya

2015-01-01

The authors examined how the variability in adult conflict resolution styles in family and school contexts was related to adolescents' positive development. Cluster analysis classified 440 fathers, 440 mothers, and 125 tutors into 4 clusters, based on self-reports of their conflict resolution styles. Adolescents exposed to Cluster 1 (inconsistency…

Blind Quantum Signature with Controlled Four-Particle Cluster States

NASA Astrophysics Data System (ADS)

Li, Wei; Shi, Jinjing; Shi, Ronghua; Guo, Ying

2017-08-01

A novel blind quantum signature scheme based on cluster states is introduced. Cluster states are a type of multi-qubit entangled states and it is more immune to decoherence than other entangled states. The controlled four-particle cluster states are created by acting controlled-Z gate on particles of four-particle cluster states. The presented scheme utilizes the above entangled states and simplifies the measurement basis to generate and verify the signature. Security analysis demonstrates that the scheme is unconditional secure. It can be employed to E-commerce systems in quantum scenario.

Integrating K-means Clustering with Kernel Density Estimation for the Development of a Conditional Weather Generation Downscaling Model

NASA Astrophysics Data System (ADS)

Chen, Y.; Ho, C.; Chang, L.

2011-12-01

In previous decades, the climate change caused by global warming increases the occurrence frequency of extreme hydrological events. Water supply shortages caused by extreme events create great challenges for water resource management. To evaluate future climate variations, general circulation models (GCMs) are the most wildly known tools which shows possible weather conditions under pre-defined CO2 emission scenarios announced by IPCC. Because the study area of GCMs is the entire earth, the grid sizes of GCMs are much larger than the basin scale. To overcome the gap, a statistic downscaling technique can transform the regional scale weather factors into basin scale precipitations. The statistic downscaling technique can be divided into three categories include transfer function, weather generator and weather type. The first two categories describe the relationships between the weather factors and precipitations respectively based on deterministic algorithms, such as linear or nonlinear regression and ANN, and stochastic approaches, such as Markov chain theory and statistical distributions. In the weather type, the method has ability to cluster weather factors, which are high dimensional and continuous variables, into weather types, which are limited number of discrete states. In this study, the proposed downscaling model integrates the weather type, using the K-means clustering algorithm, and the weather generator, using the kernel density estimation. The study area is Shihmen basin in northern of Taiwan. In this study, the research process contains two steps, a calibration step and a synthesis step. Three sub-steps were used in the calibration step. First, weather factors, such as pressures, humidities and wind speeds, obtained from NCEP and the precipitations observed from rainfall stations were collected for downscaling. Second, the K-means clustering grouped the weather factors into four weather types. Third, the Markov chain transition matrixes and the conditional probability density function (PDF) of precipitations approximated by the kernel density estimation are calculated respectively for each weather types. In the synthesis step, 100 patterns of synthesis data are generated. First, the weather type of the n-th day are determined by the results of K-means clustering. The associated transition matrix and PDF of the weather type were also determined for the usage of the next sub-step in the synthesis process. Second, the precipitation condition, dry or wet, can be synthesized basing on the transition matrix. If the synthesized condition is dry, the quantity of precipitation is zero; otherwise, the quantity should be further determined in the third sub-step. Third, the quantity of the synthesized precipitation is assigned as the random variable of the PDF defined above. The synthesis efficiency compares the gap of the monthly mean curves and monthly standard deviation curves between the historical precipitation data and the 100 patterns of synthesis data.

Clustering methods for the optimization of atomic cluster structure

NASA Astrophysics Data System (ADS)

Bagattini, Francesco; Schoen, Fabio; Tigli, Luca

2018-04-01

In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.

Evolutionary sequences of very hot, low-mass, accreting white dwarfs with application to symbiotic variables and ultrasoft/supersoft low-luminosity x-ray sources

NASA Technical Reports Server (NTRS)

Sion, Edward M.; Starrfield, Sumner G.

1994-01-01

We present the first detailed model results of quasi-static evolutionary sequences of very hot low-mass white dwarfs accreting hydrogen-rich material at rates between 1 x 10(exp -7) and 1 x 10(exp -9) solar mass/yr. Most of the sequences were generated from starting models whose core thermal structures were not thermally relaxed in the thermal pulse cycle-averaged sense of an asymptotic giant branch stellar core. Hence, the evolution at constant accretion rate was not invariably characterized by series of identical shell flashes. Sequences exhibiting stable steady state nuclear burning at the accretion supply rate as well as sequences exhibiting recurrent thermonuclear shell flashes are presented and discussed. In some cases, the white dwarf accretors remain small (less than 10(exp 11) cm) and very hot even during the shell flash episode. They then experience continued but reduced hydrogen shell burning during the longer quiescent intervals while their surface temperatures increase both because of compressional heating and envelope structure readjustment in response to accretion over thousands of years. Both accretion and continued hydrogen burning power these models with luminosities of a few times 10(exp 37) ergs/s. We suggest that the physical properties of these model sequences are of considerable relevance to the observed outburst and quiescent behavior of those symbiotic variables and symbiotic novae containing low-mass white dwarfs. We also suggest that our models are relevant to the observational characteristics of the growing class of low-luminosity, supersoft/ultrasoft X-ray sources in globular clusters, and the Magellanic Clouds.

Fuel-Mediated Transient Clustering of Colloidal Building Blocks.

PubMed

van Ravensteijn, Bas G P; Hendriksen, Wouter E; Eelkema, Rienk; van Esch, Jan H; Kegel, Willem K

2017-07-26

Fuel-driven assembly operates under the continuous influx of energy and results in superstructures that exist out of equilibrium. Such dissipative processes provide a route toward structures and transient behavior unreachable by conventional equilibrium self-assembly. Although perfected in biological systems like microtubules, this class of assembly is only sparsely used in synthetic or colloidal analogues. Here, we present a novel colloidal system that shows transient clustering driven by a chemical fuel. Addition of fuel causes an increase in hydrophobicity of the building blocks by actively removing surface charges, thereby driving their aggregation. Depletion of fuel causes reappearance of the charged moieties and leads to disassembly of the formed clusters. This reassures that the system returns to its initial, equilibrium state. By taking advantage of the cyclic nature of our system, we show that clustering can be induced several times by simple injection of new fuel. The fuel-mediated assembly of colloidal building blocks presented here opens new avenues to the complex landscape of nonequilibrium colloidal structures, guided by biological design principles.

Clustering of samples and variables with mixed-type data

PubMed Central

Edelmann, Dominic; Kopp-Schneider, Annette

2017-01-01

Analysis of data measured on different scales is a relevant challenge. Biomedical studies often focus on high-throughput datasets of, e.g., quantitative measurements. However, the need for integration of other features possibly measured on different scales, e.g. clinical or cytogenetic factors, becomes increasingly important. The analysis results (e.g. a selection of relevant genes) are then visualized, while adding further information, like clinical factors, on top. However, a more integrative approach is desirable, where all available data are analyzed jointly, and where also in the visualization different data sources are combined in a more natural way. Here we specifically target integrative visualization and present a heatmap-style graphic display. To this end, we develop and explore methods for clustering mixed-type data, with special focus on clustering variables. Clustering of variables does not receive as much attention in the literature as does clustering of samples. We extend the variables clustering methodology by two new approaches, one based on the combination of different association measures and the other on distance correlation. With simulation studies we evaluate and compare different clustering strategies. Applying specific methods for mixed-type data proves to be comparable and in many cases beneficial as compared to standard approaches applied to corresponding quantitative or binarized data. Our two novel approaches for mixed-type variables show similar or better performance than the existing methods ClustOfVar and bias-corrected mutual information. Further, in contrast to ClustOfVar, our methods provide dissimilarity matrices, which is an advantage, especially for the purpose of visualization. Real data examples aim to give an impression of various kinds of potential applications for the integrative heatmap and other graphical displays based on dissimilarity matrices. We demonstrate that the presented integrative heatmap provides more information than common data displays about the relationship among variables and samples. The described clustering and visualization methods are implemented in our R package CluMix available from https://cran.r-project.org/web/packages/CluMix. PMID:29182671

Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

PubMed

Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

2017-07-01

Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

Visual analytics of large multidimensional data using variable binned scatter plots

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Sharma, Ratnesh K.; Keim, Daniel A.; Janetzko, Halldór

2010-01-01

The scatter plot is a well-known method of visualizing pairs of two-dimensional continuous variables. Multidimensional data can be depicted in a scatter plot matrix. They are intuitive and easy-to-use, but often have a high degree of overlap which may occlude a significant portion of data. In this paper, we propose variable binned scatter plots to allow the visualization of large amounts of data without overlapping. The basic idea is to use a non-uniform (variable) binning of the x and y dimensions and plots all the data points that fall within each bin into corresponding squares. Further, we map a third attribute to color for visualizing clusters. Analysts are able to interact with individual data points for record level information. We have applied these techniques to solve real-world problems on credit card fraud and data center energy consumption to visualize their data distribution and cause-effect among multiple attributes. A comparison of our methods with two recent well-known variants of scatter plots is included.

Spatial modelling and mapping of female genital mutilation in Kenya

PubMed Central

2014-01-01

Background Female genital mutilation/cutting (FGM/C) is still prevalent in several communities in Kenya and other areas in Africa, as well as being practiced by some migrants from African countries living in other parts of the world. This study aimed at detecting clustering of FGM/C in Kenya, and identifying those areas within the country where women still intend to continue the practice. A broader goal of the study was to identify geographical areas where the practice continues unabated and where broad intervention strategies need to be introduced. Methods The prevalence of FGM/C was investigated using the 2008 Kenya Demographic and Health Survey (KDHS) data. The 2008 KDHS used a multistage stratified random sampling plan to select women of reproductive age (15–49 years) and asked questions concerning their FGM/C status and their support for the continuation of FGM/C. A spatial scan statistical analysis was carried out using SaTScan™ to test for statistically significant clustering of the practice of FGM/C in the country. The risk of FGM/C was also modelled and mapped using a hierarchical spatial model under the Integrated Nested Laplace approximation approach using the INLA library in R. Results The prevalence of FGM/C stood at 28.2% and an estimated 10.3% of the women interviewed indicated that they supported the continuation of FGM. On the basis of the Deviance Information Criterion (DIC), hierarchical spatial models with spatially structured random effects were found to best fit the data for both response variables considered. Age, region, rural–urban classification, education, marital status, religion, socioeconomic status and media exposure were found to be significantly associated with FGM/C. The current FGM/C status of a woman was also a significant predictor of support for the continuation of FGM/C. Spatial scan statistics confirm FGM clusters in the North-Eastern and South-Western regions of Kenya (p < 0.001). Conclusion This suggests that the fight against FGM/C in Kenya is not yet over. There are still deep cultural and religious beliefs to be addressed in a bid to eradicate the practice. Interventions by government and other stakeholders must address these challenges and target the identified clusters. PMID:24661558

Effect of Selected Variables on Funding State Compensatory and Regular Education in Texas

ERIC Educational Resources Information Center

Wiesman, Karen Wheeler

2009-01-01

Funding public schools has been an ongoing struggle since the inception of the United States. Beginning with Jefferson's "A General Diffusion of Knowledge" that charged the states with properly funding public schools, to the current day legal battles that continue in states across the Union, America struggles with finding a solution to…

The Public-Good Variable: Can Public Engagement Boost State Support for Higher Education?

ERIC Educational Resources Information Center

Weerts, David J.

2015-01-01

As state support for higher education has continued its downward slide, several commissions, declarations, and association reports have called on colleges and universities to be more productively engaged with state and regional needs. An underlying subtext of these reports is that the future of state support for higher education hinges on the…

Hybrid Discrete-Continuous Markov Decision Processes

NASA Technical Reports Server (NTRS)

Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich

2003-01-01

This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.

Semi-supervised clustering methods.

PubMed

Bair, Eric

2013-01-01

Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as "semi-supervised clustering" methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided.

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.

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.

MULTIMODE quantum calculations of vibrational energies and IR spectrum of the NO⁺(H₂O) cluster using accurate potential energy and dipole moment surfaces.

PubMed

Homayoon, Zahra

2014-09-28

A new, full (nine)-dimensional potential energy surface and dipole moment surface to describe the NO(+)(H2O) cluster is reported. The PES is based on fitting of roughly 32,000 CCSD(T)-F12/aug-cc-pVTZ electronic energies. The surface is a linear least-squares fit using a permutationally invariant basis with Morse-type variables. The PES is used in a Diffusion Monte Carlo study of the zero-point energy and wavefunction of the NO(+)(H2O) and NO(+)(D2O) complexes. Using the calculated ZPE the dissociation energies of the clusters are reported. Vibrational configuration interaction calculations of NO(+)(H2O) and NO(+)(D2O) using the MULTIMODE program are performed. The fundamental, a number of overtone, and combination states of the clusters are reported. The IR spectrum of the NO(+)(H2O) cluster is calculated using 4, 5, 7, and 8 modes VSCF/CI calculations. The anharmonic, coupled vibrational calculations, and IR spectrum show very good agreement with experiment. Mode coupling of the water "antisymmetric" stretching mode with the low-frequency intermolecular modes results in intensity borrowing.

MULTIMODE quantum calculations of vibrational energies and IR spectrum of the NO+(H2O) cluster using accurate potential energy and dipole moment surfaces

NASA Astrophysics Data System (ADS)

Homayoon, Zahra

2014-09-01

A new, full (nine)-dimensional potential energy surface and dipole moment surface to describe the NO+(H2O) cluster is reported. The PES is based on fitting of roughly 32 000 CCSD(T)-F12/aug-cc-pVTZ electronic energies. The surface is a linear least-squares fit using a permutationally invariant basis with Morse-type variables. The PES is used in a Diffusion Monte Carlo study of the zero-point energy and wavefunction of the NO+(H2O) and NO+(D2O) complexes. Using the calculated ZPE the dissociation energies of the clusters are reported. Vibrational configuration interaction calculations of NO+(H2O) and NO+(D2O) using the MULTIMODE program are performed. The fundamental, a number of overtone, and combination states of the clusters are reported. The IR spectrum of the NO+(H2O) cluster is calculated using 4, 5, 7, and 8 modes VSCF/CI calculations. The anharmonic, coupled vibrational calculations, and IR spectrum show very good agreement with experiment. Mode coupling of the water "antisymmetric" stretching mode with the low-frequency intermolecular modes results in intensity borrowing.

High-Threshold Fault-Tolerant Quantum Computation with Analog Quantum Error Correction

NASA Astrophysics Data System (ADS)

Fukui, Kosuke; Tomita, Akihisa; Okamoto, Atsushi; Fujii, Keisuke

2018-04-01

To implement fault-tolerant quantum computation with continuous variables, the Gottesman-Kitaev-Preskill (GKP) qubit has been recognized as an important technological element. However, it is still challenging to experimentally generate the GKP qubit with the required squeezing level, 14.8 dB, of the existing fault-tolerant quantum computation. To reduce this requirement, we propose a high-threshold fault-tolerant quantum computation with GKP qubits using topologically protected measurement-based quantum computation with the surface code. By harnessing analog information contained in the GKP qubits, we apply analog quantum error correction to the surface code. Furthermore, we develop a method to prevent the squeezing level from decreasing during the construction of the large-scale cluster states for the topologically protected, measurement-based, quantum computation. We numerically show that the required squeezing level can be relaxed to less than 10 dB, which is within the reach of the current experimental technology. Hence, this work can considerably alleviate this experimental requirement and take a step closer to the realization of large-scale quantum computation.

Age-Related Differences in Profiles of Mood-Change Trajectories

PubMed Central

Stanley, Jennifer Tehan; Isaacowitz, Derek M.

2010-01-01

As a group, older adults report positive affective lives. The extent to which there are subgroups of older adults whose moods are less positive, however, is unclear. The aim of the present study was to identify and characterize different subgroups of adults who exhibit distinct trajectories of mood-change across a relatively short time period. Seventy-nine young and 103 older adults continuously reported their moods while viewing emotional and neutral faces. Cluster analysis revealed four subgroups of mood-change trajectories. Both the most positive and the most negative subgroups included more older than younger adults (ps < .05), suggesting that not all older adults exhibit higher positive affect than young adults. Analyses of variance revealed that the most negative group exhibited slower processing speed, more state anxiety and neuroticism, and looked less at happy faces, than the other groups (ps < .05). The results are discussed from an adult developmental perspective, focusing on the increased variability of mood trajectories in the older adults and whether this is a reflection of adaptive functioning, or a potential harbinger of dysfunction. PMID:21171749

[When and where motorcyclists have accidents and die in Belo Horizonte, Minas Gerais State, Brazil].

PubMed

Diniz, Eugênio Paceli Hatem; Pinheiro, Letícia Cavalari; Proietti, Fernando Augusto

2015-12-01

The objective of this study was to analyze traffic accidents involving motorcycles in Belo Horizonte, Minas Gerais State, Brazil, from 2007 to 2011 and to identify clusters of high-risk and hazardous intersections in and around the city. Data were provided by the Military Police Brigade and the Emergency Medical Service (SAMU). Accident severity rates were used to identify critical intersections. Two techniques were used: kernel analysis and scan statistics (continuous Poisson model). High-risk clusters were located in the downtown area and on major thoroughfares. Surprisingly, the highest risk of accidents and death occurred not at intersections, but between them. Hazardous intersections are part of routes used to access regions around Greater Metropolitan Belo Horizonte. Two distinct trends in mortality rates and accidents were identified. Most motorcycle deaths occurred after 7:00 PM. The study concludes that there is an urgent need to improve motorcycle and public transportation routes.

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)].

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

Morra, Simone; Maurelli, Sara; Chiesa, Mario

A conserved cysteine located in the signature motif of the catalytic center (H-cluster) of [FeFe]-hydrogenases functions in proton transfer. This residue corresponds to C298 in Clostridium acetobutylicum CaHydA. Despite the chemical and structural difference, the mutant C298D retains fast catalytic activity, while replacement with any other amino acid caused significant activity loss. Given the proximity of C298 to the H-cluster, the effect of the C298D mutation on the catalytic center was studied by continuous wave (CW) and pulse electron paramagnetic resonance (EPR) and by Fourier transform infrared (FTIR) spectroscopies. Comparison of the C298D mutant with the wild type CaHydA bymore » CW and pulse EPR showed that the electronic structure of the center is not altered. FTIR spectroscopy confirmed that absorption peak values observed in the mutant are virtually identical to those observed in the wild type, indicating that the H-cluster is not generally affected by the mutation. Significant differences were observed only in the inhibited state Hox-CO: the vibrational modes assigned to the COexo and Fed-CO in this state are shifted to lower values in C298D, suggesting different interaction of these ligands with the protein moiety when C298 is changed to D298. More relevant to the catalytic cycle, the redox equilibrium between the Hox and Hred states is modified by the mutation, causing a prevalence of the oxidized state. This work highlights how the interactions between the protein environment and the H-cluster, a dynamic closely interconnected system, can be engineered and studied in the perspective of designing bio-inspired catalysts and mimics.« less

Vehicle energy conservation indicating device and process for use

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

Crump, J.M.

A vehicle energy conservation indicating device comprises an integrated instrument cluster functioning basically as a nomographic computing mechanism. The odometer distance traveled indicator computing mechanism is linked with the fuel indicating gauge mechanism such that a three variable equation computing mechanism is obtained. The three variables are distance traveled, quantity of fuel consumed and distance traveled per unit of fuel consumed. Energy conservation is achieved by operating the vehicle under such performance conditions as to produce the highest possible value for distance traveled per unit of fuel consumed. The instrument panel cluster brings the operator's attention to focus upon andmore » continuously stimulated to conserving energy. Furthermore, the vehicle energy conservation indicating device can be adapted for recording these performance variables on tape type print out. The speedometer advises the vehicle operator when he is obeying or breaking the speed laws which are enforced and monitored by the police with specific punishment prescribed for violations of the law. At this time there is no comparable procedure for enforcing vehicle energy conservation. Thus, this direct read out of distance traveled per unit of energy will moderate the operation in an analogous manner similar to subliminal advertising. This device becomes the focal point of the instrument panel along with the speedometer, thereby providing constant motivation to obey both the speed and energy conservation laws.« less

[Application of Kohonen Self-Organizing Feature Maps in QSAR of human ADMET and kinase data sets].

PubMed

Hegymegi-Barakonyi, Bálint; Orfi, László; Kéri, György; Kövesdi, István

2013-01-01

QSAR predictions have been proven very useful in a large number of studies for drug design, such as kinase inhibitor design as targets for cancer therapy, however the overall predictability often remains unsatisfactory. To improve predictability of ADMET features and kinase inhibitory data, we present a new method using Kohonen's Self-Organizing Feature Map (SOFM) to cluster molecules based on explanatory variables (X) and separate dissimilar ones. We calculated SOFM clusters for a large number of molecules with human ADMET and kinase inhibitory data, and we showed that chemically similar molecules were in the same SOFM cluster, and within such clusters the QSAR models had significantly better predictability. We used also target variables (Y, e.g. ADMET) jointly with X variables to create a novel type of clustering. With our method, cells of loosely coupled XY data could be identified and separated into different model building sets.

The link between eddy-driven jet variability and weather regimes in the North Atlantic-European sector

NASA Astrophysics Data System (ADS)

Madonna, E.; Li, C.; Grams, C. M.; Woollings, T.

2017-12-01

Understanding the variability of the North Atlantic eddy-driven jet is key to unravelling the dynamics, predictability and climate change response of extratropical weather in the region. This study aims to 1) reconcile two perspectives on wintertime variability in the North Atlantic-European sector and 2) clarify their link to atmospheric blocking. Two common views of wintertime variability in the North Atlantic are the zonal-mean framework comprising three preferred locations of the eddy-driven jet (southern, central, northern), and the weather regime framework comprising four classical North Atlantic-European regimes (Atlantic ridge AR, zonal ZO, European/Scandinavian blocking BL, Greenland anticyclone GA). We use a k-means clustering algorithm to characterize the two-dimensional variability of the eddy-driven jet stream, defined by the lower tropospheric zonal wind in the ERA-Interim reanalysis. The first three clusters capture the central jet and northern jet, along with a new mixed jet configuration; a fourth cluster is needed to recover the southern jet. The mixed cluster represents a split or strongly tilted jet, neither of which is well described in the zonal-mean framework, and has a persistence of about one week, similar to the other clusters. Connections between the preferred jet locations and weather regimes are corroborated - southern to GA, central to ZO, and northern to AR. In addition, the new mixed cluster is found to be linked to European/Scandinavian blocking, whose relation to the eddy-driven jet was previously unclear. The results highlight the necessity of bridging from weather to climate scales for a deeper understanding of atmospheric circulation variability.

The Search for Bright Variable Stars in Open Cluster NGC 6819.

NASA Astrophysics Data System (ADS)

Talamantes, Antonio; Sandquist, E. L.

2009-01-01

During this research period data was taken for seven nights at the 1m telescope at Mt. Laguna Observatory for the open cluster NGC 6819. For four of the nights data was taken using a V-band filter. For the three nights remaining nights the data was taken using an R-band filter. Photometry was done using the ISIS image subtraction package. Six new variable stars were located using these techniques. These variable types include a pulsating variable, five detached eclipsing binaries. Of the detached eclipsing binaries, three are near the cluster turnoff and two in the blue straggler region(and one of these has total eclipses). Nine previously known variables(six contact binaries, two detached eclipsing binaries and one near-contact binary) were also studied.

Variables en la región central del cúmulo globular NGC 3201: descomposición de Fourier de las curvas de luz de las RR Lyrae y análisis de la relación período-luminosidad de las SX Phoenicis

NASA Astrophysics Data System (ADS)

Ahumada, J. A.; Arellano Ferro, A.; Calderón, J. H.; Kains, N.

2015-08-01

We present CCD time-series observations of the central region of the globular cluster NGC 3201, collected from CASLEO in March 2013, with the aim of performing the Fourier decomposition of the light curves of the RR Lyrae variables. This procedure, applied to the RRab-type stars, gave a mean value [Fe/H], for the cluster metallicity, and 5.00 0.22 kpc, for the cluster distance. The values found from two RRc stars are consistent with those derived previously. Because of differential reddening across the cluster field, individual reddenings for the RRab stars were estimated from their curves, resulting in an average value . An investigation of the light curves of stars in the blue straggler region led to the discovery of three new SX Phoenicis variables. The period-luminosity relation of the SX Phoenicis was used for an independent determination of the distance to the cluster and of the individual reddenings of these variables.

Compositional variability in Mediterranean archaeofaunas from Upper Paleolithic Southwest Europe

NASA Astrophysics Data System (ADS)

Jones, Emily Lena

2018-03-01

Recent meta-analyses of Upper Paleolithic Southwestern European archaeofaunas (Jones, 2015, 2016) have identified a consistent "Mediterranean" cluster from the Last Glacial Maximum through the early Holocene, suggesting similarities in environment and/or consistency in hunting strategy across this region through time despite radical changes in climate. However, while these archaeofaunas from this cluster all derive from sites located within today's Mediterranean bioclimatic region, many of them are from locations far from the Mediterranean Sea - Atlantic Portugal, the Spanish Meseta - which today differ significantly from each other in biotic composition. In this paper, I explore clustering (through cluster analysis and non-metric multidimensional scaling) within the Mediterranean archaeofaunal group. I test for the influence of sample size as well as the geographic variables of site elevation, latitude, and longitude on variability in the large mammal portions of archaeofaunal assemblages. ANOVA shows no relationship between cluster-defined groups and site elevation or longitude; instead, site latitude appears to be a primary contributor to patterning. However, the overall compositional similarity of the Mediterranean archaeofaunas in this dataset suggests more consistency than variability in Upper Paleolithic hunting strategy in this region.

Uncovering state-dependent relationships in shallow lakes using Bayesian latent variable regression.

PubMed

Vitense, Kelsey; Hanson, Mark A; Herwig, Brian R; Zimmer, Kyle D; Fieberg, John

2018-03-01

Ecosystems sometimes undergo dramatic shifts between contrasting regimes. Shallow lakes, for instance, can transition between two alternative stable states: a clear state dominated by submerged aquatic vegetation and a turbid state dominated by phytoplankton. Theoretical models suggest that critical nutrient thresholds differentiate three lake types: highly resilient clear lakes, lakes that may switch between clear and turbid states following perturbations, and highly resilient turbid lakes. For effective and efficient management of shallow lakes and other systems, managers need tools to identify critical thresholds and state-dependent relationships between driving variables and key system features. Using shallow lakes as a model system for which alternative stable states have been demonstrated, we developed an integrated framework using Bayesian latent variable regression (BLR) to classify lake states, identify critical total phosphorus (TP) thresholds, and estimate steady state relationships between TP and chlorophyll a (chl a) using cross-sectional data. We evaluated the method using data simulated from a stochastic differential equation model and compared its performance to k-means clustering with regression (KMR). We also applied the framework to data comprising 130 shallow lakes. For simulated data sets, BLR had high state classification rates (median/mean accuracy >97%) and accurately estimated TP thresholds and state-dependent TP-chl a relationships. Classification and estimation improved with increasing sample size and decreasing noise levels. Compared to KMR, BLR had higher classification rates and better approximated the TP-chl a steady state relationships and TP thresholds. We fit the BLR model to three different years of empirical shallow lake data, and managers can use the estimated bifurcation diagrams to prioritize lakes for management according to their proximity to thresholds and chance of successful rehabilitation. Our model improves upon previous methods for shallow lakes because it allows classification and regression to occur simultaneously and inform one another, directly estimates TP thresholds and the uncertainty associated with thresholds and state classifications, and enables meaningful constraints to be built into models. The BLR framework is broadly applicable to other ecosystems known to exhibit alternative stable states in which regression can be used to establish relationships between driving variables and state variables. © 2017 by the Ecological Society of America.

Drinker Types, Harm, and Policy-Related Variables: Results from the 2011 International Alcohol Control Study in New Zealand.

PubMed

Wall, Martin; Casswell, Sally

2017-05-01

The aim was to identify a typology of drinkers in New Zealand based on alcohol consumption, beverage choice, and public versus private drinking locations and investigate the relationship between drinker types, harms experienced, and policy-related variables. Model-based cluster analysis of male and female drinkers including volumes of alcohol consumed in the form of beer, wine, spirits, and ready-to-drinks (RTDs) in off- and on-premise settings. Cluster membership was then related to harm measures: alcohol dependence, self-rated health; and to 3 policy-relevant variables: liking for alcohol adverts, price paid for alcohol, and time of purchase. Males and females were analyzed separately. Men fell into 4 and women into 14 clearly discriminated clusters. The male clusters consumed a relatively high proportion of alcohol in the form of beer. Women had a number of small extreme clusters and some consumed mainly spirits-based RTDs, while others drank mainly wine. Those in the higher consuming clusters were more likely to have signs of alcohol dependency, to report lower satisfaction with their health, to like alcohol ads, and to have purchased late at night. Consumption patterns are sufficiently distinctive to identify typologies of male and female alcohol consumers. Women drinkers are more heterogeneous than men. The clusters relate differently to policy-related variables. Copyright © 2017 by the Research Society on Alcoholism.

Location Matters: Geographic Location and Educational Placement of Students with Developmental Disabilities

ERIC Educational Resources Information Center

Brock, Matthew E.; Schaefer, John M.

2015-01-01

Despite decades of advocacy, most students with developmental disabilities continue to spend the majority of the school day in self-contained special education classrooms. However, there is tremendous variability of educational placement across the United States. Identification of geographic trends that explain this variability could provide…

A NEW CENSUS OF THE VARIABLE STAR POPULATION IN THE GLOBULAR CLUSTER NGC 2419

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

Di Criscienzo, M.; Greco, C.; Ripepi, V.

We present B, V, and I CCD light curves for 101 variable stars belonging to the globular cluster NGC 2419, 60 of which are new discoveries, based on data sets obtained at the Telescopio Nazionale Galileo, the Subaru telescope, and the Hubble Space Telescope. The sample includes 75 RR Lyrae stars (38 RRab, 36 RRc, and one RRd), one Population II Cepheid, 12 SX Phoenicis variables, two {delta} Scuti stars, three binary systems, five long-period variables, and three variables of uncertain classification. The pulsation properties of the RR Lyrae variables are close to those of Oosterhoff type II clusters, consistentmore » with the low metal abundance and the cluster horizontal branch morphology, disfavoring (but not totally ruling out) an extragalactic hypothesis for the origin of NGC 2419. The observed properties of RR Lyrae and SX Phoenicis stars are used to estimate the cluster reddening and distance, using a number of different methods. Our final value is {mu}{sub 0} (NGC 2419) = 19.71 {+-} 0.08 mag (D = 87.5 {+-} 3.3 kpc), with E(B - V) = 0.08 {+-} 0.01 mag, [Fe/H] = -2.1 dex on the Zinn and West metallicity scale, and a value of M{sub V} that sets {mu}{sub 0} (LMC) = 18.52 mag. This value is in good agreement with the most recent literature estimates of the distance to NGC 2419.« less

Neuroimaging paradigms for tonotopic mapping (II): the influence of acquisition protocol.

PubMed

Langers, Dave R M; Sanchez-Panchuelo, Rosa M; Francis, Susan T; Krumbholz, Katrin; Hall, Deborah A

2014-10-15

Numerous studies on the tonotopic organisation of auditory cortex in humans have employed a wide range of neuroimaging protocols to assess cortical frequency tuning. In the present functional magnetic resonance imaging (fMRI) study, we made a systematic comparison between acquisition protocols with variable levels of interference from acoustic scanner noise. Using sweep stimuli to evoke travelling waves of activation, we measured sound-evoked response signals using sparse, clustered, and continuous imaging protocols that were characterised by inter-scan intervals of 8.8, 2.2, or 0.0 s, respectively. With regard to sensitivity to sound-evoked activation, the sparse and clustered protocols performed similarly, and both detected more activation than the continuous method. Qualitatively, tonotopic maps in activated areas proved highly similar, in the sense that the overall pattern of tonotopic gradients was reproducible across all three protocols. However, quantitatively, we observed substantial reductions in response amplitudes to moderately low stimulus frequencies that coincided with regions of strong energy in the scanner noise spectrum for the clustered and continuous protocols compared to the sparse protocol. At the same time, extreme frequencies became over-represented for these two protocols, and high best frequencies became relatively more abundant. Our results indicate that although all three scanning protocols are suitable to determine the layout of tonotopic fields, an exact quantitative assessment of the representation of various sound frequencies is substantially confounded by the presence of scanner noise. In addition, we noticed anomalous signal dynamics in response to our travelling wave paradigm that suggest that the assessment of frequency-dependent tuning is non-trivially influenced by time-dependent (hemo)dynamics when using sweep stimuli. Copyright © 2014. Published by Elsevier Inc.

Continuous noninvasive orthostatic blood pressure measurements and their relationship with orthostatic intolerance, falls, and frailty in older people.

PubMed

Romero-Ortuno, Roman; Cogan, Lisa; Foran, Tim; Kenny, Rose Anne; Fan, Chie Wei

2011-04-01

To identify morphological orthostatic blood pressure (BP) phenotypes in older people and assess their correlation with orthostatic intolerance (OI), falls, and frailty and to compare the discriminatory performance of a morphological classification with two established orthostatic hypotension (OH) definitions: consensus (COH) and initial (IOH). Cross-sectional. Geriatric research clinic. Four hundred forty-two participants (mean age 72, 72% female) without dementia or risk factors for autonomic neuropathy. Active lying-to-standing test monitored using a continuous noninvasive BP monitor. For the morphological classification, four orthostatic systolic BP variables were extracted (delta (baseline - nadir) and maximum percentage of baseline recovered by 30 seconds and 1 and 2 minutes) using the 5-second averages method and entered in K-means cluster analysis (three clusters). Main outcomes were OI, falls (≥1 in past 6 months), and frailty (modified Fried criteria). The morphological clusters were small drop, fast overrecovery (n=112); medium drop, slow recovery (n=238); and large drop, nonrecovery (n=92). Their characterization revealed an increasing OI gradient (17.9%, 27.5%, and 44.6% respectively, P<.001) but no significant gradients in falls or frailty. The COH definition failed to reveal clinical differences between COH+ (n=416) and COH- (n=26) participants. The IOH definition resulted in a clinically meaningful separation between IOH+ (n=85) and IOH- (n=357) subgroups, as assessed according to OI (100% vs 11.5%, P<.001), falls (24.7% vs 10.4%, P<.001), and frailty (14.1% vs 5.4%, P=.005). It is recommended that the IOH definition be applied when taking continuous noninvasive orthostatic BP measurements in older people. © 2011, Copyright the Authors. Journal compilation © 2011, The American Geriatrics Society.

Using estimates of natural variation to detect ecologically important change in forest spatial patterns: a case study, Cascade Range, eastern Washington.

Treesearch

Paul F. Hessburg; Bradley G. Smith; R. Brion Salter

1999-01-01

Using hierarchical clustering techniques, we grouped subwatersheds on the eastern slope of the Cascade Range in Washington State into ecological subregions by similarity of area in potential vegetation and climate attributes. We then built spatially continuous historical and current vegetation maps for 48 randomly selected subwatersheds from interpretations of 1938-49...

SciSpark: In-Memory Map-Reduce for Earth Science Algorithms

NASA Astrophysics Data System (ADS)

Ramirez, P.; Wilson, B. D.; Whitehall, K. D.; Palamuttam, R. S.; Mattmann, C. A.; Shah, S.; Goodman, A.; Burke, W.

2016-12-01

We are developing a lightning fast Big Data technology called SciSpark based on ApacheTM Spark under a NASA AIST grant (PI Mattmann). Spark implements the map-reduce paradigm for parallel computing on a cluster, but emphasizes in-memory computation, "spilling" to disk only as needed, and so outperforms the disk-based Apache Hadoop by 100x in memory and by 10x on disk. SciSpark extends Spark to support Earth Science use in three ways: Efficient ingest of N-dimensional geo-located arrays (physical variables) from netCDF3/4, HDF4/5, and/or OPeNDAP URLS; Array operations for dense arrays in scala and Java using the ND4S/ND4J or Breeze libraries; Operations to "split" datasets across a Spark cluster by time or space or both. For example, a decade-long time-series of geo-variables can be split across time to enable parallel "speedups" of analysis by day, month, or season. Similarly, very high-resolution climate grids can be partitioned into spatial tiles for parallel operations across rows, columns, or blocks. In addition, using Spark's gateway into python, PySpark, one can utilize the entire ecosystem of numpy, scipy, etc. Finally, SciSpark Notebooks provide a modern eNotebook technology in which scala, python, or spark-sql codes are entered into cells in the Notebook and executed on the cluster, with results, plots, or graph visualizations displayed in "live widgets". We have exercised SciSpark by implementing three complex Use Cases: discovery and evolution of Mesoscale Convective Complexes (MCCs) in storms, yielding a graph of connected components; PDF Clustering of atmospheric state using parallel K-Means; and statistical "rollups" of geo-variables or model-to-obs. differences (i.e. mean, stddev, skewness, & kurtosis) by day, month, season, year, and multi-year. Geo-variables are ingested and split across the cluster using methods on the sciSparkContext object including netCDFVariables() for spatial decomposition and wholeNetCDFVariables() for time-series. The presentation will cover the architecture of SciSpark, the design of the scientific RDD (sRDD) data structures for N-dim. arrays, results from the three science Use Cases, example Notebooks, lessons learned from the algorithm implementations, and parallel performance metrics.

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.

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.

Long-distance continuous-variable quantum key distribution using non-Gaussian state-discrimination detection

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Huang, Duan; Huang, Peng; Zeng, Guihua

2018-02-01

We propose a long-distance continuous-variable quantum key distribution (CVQKD) with a four-state protocol using non-Gaussian state-discrimination detection. A photon subtraction operation, which is deployed at the transmitter, is used for splitting the signal required for generating the non-Gaussian operation to lengthen the maximum transmission distance of the CVQKD. Whereby an improved state-discrimination detector, which can be deemed as an optimized quantum measurement that allows the discrimination of nonorthogonal coherent states beating the standard quantum limit, is applied at the receiver to codetermine the measurement result with the conventional coherent detector. By tactfully exploiting the multiplexing technique, the resulting signals can be simultaneously transmitted through an untrusted quantum channel, and subsequently sent to the state-discrimination detector and coherent detector, respectively. Security analysis shows that the proposed scheme can lengthen the maximum transmission distance up to hundreds of kilometers. Furthermore, by taking the finite-size effect and composable security into account we obtain the tightest bound of the secure distance, which is more practical than that obtained in the asymptotic limit.

Semi-supervised clustering methods

PubMed Central

Bair, Eric

2013-01-01

Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as “semi-supervised clustering” methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided. PMID:24729830

Research on Damage Models for Continuous Fiber Composites

DTIC Science & Technology

1988-07-01

r ~.F (~ Mechanics and Materials Center TEXAS A&M UNIVERSITY College Station, Texas RESEARCH ON DAMAGE MODELS FOR CONTINUOUS FIBER COMPOSITES Final...Washington, DC 20332 11. TITLE (Include Security Clas=fication) Research on Damage Models for Continuous Fiber Composites - Final Technical Report 1...GROUP SUB-GROU ::=, COMPOsites ) continuum mechanics , ~ idamage, internal state variables V experimental mechanics, laminated composites o 19. ABSTRACT

Comparative study of feature selection with ensemble learning using SOM variants

NASA Astrophysics Data System (ADS)

Filali, Ameni; Jlassi, Chiraz; Arous, Najet

2017-03-01

Ensemble learning has succeeded in the growth of stability and clustering accuracy, but their runtime prohibits them from scaling up to real-world applications. This study deals the problem of selecting a subset of the most pertinent features for every cluster from a dataset. The proposed method is another extension of the Random Forests approach using self-organizing maps (SOM) variants to unlabeled data that estimates the out-of-bag feature importance from a set of partitions. Every partition is created using a various bootstrap sample and a random subset of the features. Then, we show that the process internal estimates are used to measure variable pertinence in Random Forests are also applicable to feature selection in unsupervised learning. This approach aims to the dimensionality reduction, visualization and cluster characterization at the same time. Hence, we provide empirical results on nineteen benchmark data sets indicating that RFS can lead to significant improvement in terms of clustering accuracy, over several state-of-the-art unsupervised methods, with a very limited subset of features. The approach proves promise to treat with very broad domains.

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

PubMed

Zhao, Zhibiao

2011-06-01

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

Observational tests for stellar evolution and pulsation theory. I - The globular clusters M 4 and M 15

NASA Astrophysics Data System (ADS)

Caputo, F.

1987-01-01

It is shown that the pulsational properties of RR Lyrae variables in globular clusters can be used together with the Red Giant Branch location to derive reliable information on the cluster reddening and distance modulus. By demanding full agreement with some key observables, the reddening and distance modulus of the globular clusters M4 and M15 are derived as a function of the mass of the variables and of the adopted cluster metallicity. Thus, from the comparison between observations and theoretical isochrones, the cluster age can be evaluated. A best guess for the age of M4 and M15 can be presented: 16×109yr, with a total uncertainty of 2 billion years.

A census of variability in globular cluster M 68 (NGC 4590)

NASA Astrophysics Data System (ADS)

Kains, N.; Arellano Ferro, A.; Figuera Jaimes, R.; Bramich, D. M.; Skottfelt, J.; Jørgensen, U. G.; Tsapras, Y.; Street, R. A.; Browne, P.; Dominik, M.; Horne, K.; Hundertmark, M.; Ipatov, S.; Snodgrass, C.; Steele, I. A.; Lcogt/Robonet Consortium; Alsubai, K. A.; Bozza, V.; Calchi Novati, S.; Ciceri, S.; D'Ago, G.; Galianni, P.; Gu, S.-H.; Harpsøe, K.; Hinse, T. C.; Juncher, D.; Korhonen, H.; Mancini, L.; Popovas, A.; Rabus, M.; Rahvar, S.; Southworth, J.; Surdej, J.; Vilela, C.; Wang, X.-B.; Wertz, O.; Mindstep Consortium

2015-06-01

Aims: We analyse 20 nights of CCD observations in the V and I bands of the globular cluster M 68 (NGC 4590) and use them to detect variable objects. We also obtained electron-multiplying CCD (EMCCD) observations for this cluster in order to explore its core with unprecedented spatial resolution from the ground. Methods: We reduced our data using difference image analysis to achieve the best possible photometry in the crowded field of the cluster. In doing so, we show that when dealing with identical networked telescopes, a reference image from any telescope may be used to reduce data from any other telescope, which facilitates the analysis significantly. We then used our light curves to estimate the properties of the RR Lyrae (RRL) stars in M 68 through Fourier decomposition and empirical relations. The variable star properties then allowed us to derive the cluster's metallicity and distance. Results: M 68 had 45 previously confirmed variables, including 42 RRL and 2 SX Phoenicis (SX Phe) stars. In this paper we determine new periods and search for new variables, especially in the core of the cluster where our method performs particularly well. We detect 4 additional SX Phe stars and confirm the variability of another star, bringing the total number of confirmed variable stars in this cluster to 50. We also used archival data stretching back to 1951 to derive period changes for some of the single-mode RRL stars, and analyse the significant number of double-mode RRL stars in M 68. Furthermore, we find evidence for double-mode pulsation in one of the SX Phe stars in this cluster. Using the different classes of variables, we derived values for the metallicity of the cluster of [Fe/H] = -2.07 ± 0.06 on the ZW scale, or -2.20 ± 0.10 on the UVES scale, and found true distance moduli μ0 = 15.00 ± 0.11 mag (using RR0 stars), 15.00 ± 0.05 mag (using RR1 stars), 14.97 ± 0.11 mag (using SX Phe stars), and 15.00 ± 0.07 mag (using the MV -[Fe/H] relation for RRL stars), corresponding to physical distances of 10.00 ± 0.49, 9.99 ± 0.21, 9.84 ± 0.50, and 10.00 ± 0.30 kpc, respectively. Thanks to the first use of difference image analysis on time-series observations of M 68, we are now confident that we have a complete census of the RRL stars in this cluster. The full Table 2 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/578/A128

Predicting Future Suicide Attempts among Depressed Suicide Ideators: A 10-year Longitudinal Study

PubMed Central

May, Alexis M.; Klonsky, E. David; Klein, Daniel N.

2012-01-01

Suicidal ideation and attempts are a major public health problem. Research has identified many risk factors for suicidality; however, most fail to identify which suicide ideators are at greatest risk of progressing to a suicide attempt. Thus, the present study identified predictors of future suicide attempts in a sample of psychiatric patients reporting suicidal ideation. The sample comprised 49 individuals who met full DSM-IV criteria for major depressive disorder and/or dysthymic disorder and reported suicidal ideation at baseline. Participants were followed for 10 years. Demographic, psychological, personality, and psychosocial risk factors were assessed using validated questionnaires and structured interviews. Phi coefficients and point-biserial correlations were used to identify prospective predictors of attempts, and logistic regressions were used to identify which variables predicted future attempts over and above past suicide attempts. Six significant predictors of future suicide attempts were identified – cluster A personality disorder, cluster B personality disorder, lifetime substance abuse, baseline anxiety disorder, poor maternal relationship, and poor social adjustment. Finally, exploratory logistic regressions were used to examine the unique contribution of each significant predictor controlling for the others. Co-morbid cluster B personality disorder emerged as the only robust, unique predictor of future suicide attempts among depressed suicide ideators. Future research should continue to identify variables that predict transition from suicidal thoughts to suicide attempts, as such work will enhance clinical assessment of suicide risk as well as theoretical models of suicide. PMID:22575331

Geomorphology of Impact Features on Tethys Using High Resolution Mosaics

DTIC Science & Technology

2017-03-01

Space Exploration, Arizona State University, Tempe, AZ 85282 NIA 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM...8217 coorbital moons are very likely to impact Tethys. The distribution, impact velocities, and impact angles of the debris are spatially-variable. In...particular, high-velocity debris (>5 km/s) with low impact angles are highly clustered along the equator in Tethys’ leading hemisphere. Slower impacts

Gaussian maximally multipartite-entangled states

NASA Astrophysics Data System (ADS)

Facchi, Paolo; Florio, Giuseppe; Lupo, Cosmo; Mancini, Stefano; Pascazio, Saverio

2009-12-01

We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7 .

The role of boundary variability in polycrystalline grain-boundary diffusion

NASA Astrophysics Data System (ADS)

Moghadam, M. M.; Rickman, J. M.; Harmer, M. P.; Chan, H. M.

2015-01-01

We investigate the impact of grain-boundary variability on mass transport in a polycrystal. More specifically, we perform both numerical and analytical studies of steady-state diffusion in prototypical microstructures in which there is either a discrete spectrum of grain-boundary activation energies or else a complex distribution of grain-boundary character, and hence a continuous spectrum of boundary activation energies. An effective diffusivity is calculated for these structures using simplified multi-state models and, for the case of a continuous spectrum, employing experimentally obtained grain-boundary energy data. We identify different diffusive regimes for these cases and quantify deviations from Arrhenius behavior using effective medium theory. Finally, we examine the diffusion kinetics of a simplified model of an interfacial layering (i.e., complexion) transition.

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.

The Clusters AgeS Experiment (CASE). Variable Stars in the Field of the Globular Cluster NGC 3201

NASA Astrophysics Data System (ADS)

Kaluzny, J.; Rozyczka, M.; Thompson, I. B.; Narloch, W.; Mazur, B.; Pych, W.; Schwarzenberg-Czerny, A.

2016-01-01

The field of the globular cluster NGC 3201 was monitored between 1998 and 2009 in a search for variable stars. BV light curves were obtained for 152 periodic or likely periodic variables, fifty-seven of which are new detections. Thirty-seven newly detected variables are proper motion members of the cluster. Among them we found seven detached or semi-detached eclipsing binaries, four contact binaries, and eight SX Phe pulsators. Four of the eclipsing binaries are located in the turnoff region, one on the lower main sequence and the remaining two slightly above the subgiant branch. Two contact systems are blue stragglers, and another two reside in the turnoff region. In the blue straggler region a total of 266 objects were found, of which 140 are proper motion (PM) members of NGC 3201, and another nineteen are field stars. Seventy-eight of the remaining objects for which we do not have PM data are located within the half-light radius from the center of the cluster, and most of them are likely genuine blue stragglers. Four variable objects in our field of view were found to coincide with X-ray sources: three chromospherically active stars and a quasar at a redshift z≍0.5.

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.

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.

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

Method of Continuous Variations: Applications of Job Plots to the Study of Molecular Associations in Organometallic Chemistry[**

PubMed Central

Renny, Joseph S.; Tomasevich, Laura L.; Tallmadge, Evan H.; Collum, David B.

2014-01-01

Applications of the method of continuous variations—MCV or the Method of Job—to problems of interest to organometallic chemists are described. MCV provides qualitative and quantitative insights into the stoichiometries underlying association of m molecules of A and n molecules of B to form AmBn. Applications to complex ensembles probe associations that form metal clusters and aggregates. Job plots in which reaction rates are monitored provide relative stoichiometries in rate-limiting transition structures. In a specialized variant, ligand- or solvent-dependent reaction rates are dissected into contributions in both the ground states and transition states, which affords insights into the full reaction coordinate from a single Job plot. Gaps in the literature are identified and critiqued. PMID:24166797

Landscape, demographic and climatic associations with human West Nile virus occurrence regionally in 2012 in the United States of America.

PubMed

DeGroote, John P; Sugumaran, Ramanathan; Ecker, Mark

2014-11-01

After several years of low West Nile virus (WNV) occurrence in the United States of America (USA), 2012 witnessed large outbreaks in several parts of the country. In order to understand the outbreak dynamics, spatial clustering and landscape, demographic and climatic associations with WNV occurrence were investigated at a regional level in the USA. Previous research has demonstrated that there are a handful of prominent WNV mosquito vectors with varying ecological requirements responsible for WNV transmission in the USA. Published range maps of these important vectors were georeferenced and used to define eight functional ecological regions in the coterminous USA. The number of human WNV cases and human populations by county were attained in order to calculate a WNV rate for each county in 2012. Additionally, a binary value (high/low) was calculated for each county based on whether the county WNV rate was above or below the rate for the region it fell in. Global Moran's I and Anselin Local Moran's I statistics of spatial association were used per region to examine and visualize clustering of the WNV rate and the high/low rating. Spatial data on landscape, demographic and climatic variables were compiled and derived from a variety of sources and then investigated in relation to human WNV using both Spearman rho correlation coefficients and Poisson regression models. Findings demonstrated significant spatial clustering of WNV and substantial inter-regional differences in relationships between WNV occurrence and landscape, demographic and climatically related variables. The regional associations were consistent with the ecologies of the dominant vectors for those regions. The large outbreak in the Southeast region was preceded by higher than normal winter and spring precipitation followed by dry and hot conditions in the summer.

Image-Subtraction Photometry of Variable Stars in the Globular Clusters NGC 6388 and NGC 6441

NASA Technical Reports Server (NTRS)

Corwin, Michael T.; Sumerel, Andrew N.; Pritzl, Barton J.; Smith, Horace A.; Catelan, M.; Sweigart, Allen V.; Stetson, Peter B.

2006-01-01

We have applied Alard's image subtraction method (ISIS v2.1) to the observations of the globular clusters NGC 6388 and NGC 6441 previously analyzed using standard photometric techniques (DAOPHOT, ALLFRAME). In this reanalysis of observations obtained at CTIO, besides recovering the variables previously detected on the basis of our ground-based images, we have also been able to recover most of the RR Lyrae variables previously detected only in the analysis of Hubble Space Telescope WFPC2 observations of the inner region of NGC 6441. In addition, we report five possible new variables not found in the analysis of the EST observations of NGC 6441. This dramatically illustrates the capabilities of image subtraction techniques applied to ground-based data to recover variables in extremely crowded fields. We have also detected twelve new variables and six possible variables in NGC 6388 not found in our previous groundbased studies. Revised mean periods for RRab stars in NGC 6388 and NGC 6441 are 0.676 day and 0.756 day, respectively. These values are among the largest known for any galactic globular cluster. Additional probable type II Cepheids were identified in NGC 6388, confirming its status as a metal-rich globular cluster rich in Cepheids.

Quantum frequency up-conversion of continuous variable entangled states

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

Liu, Wenyuan; Wang, Ning; Li, Zongyang

We demonstrate experimentally quantum frequency up-conversion of a continuous variable entangled optical field via sum-frequency-generation process. The two-color entangled state initially entangled at 806 and 1518 nm with an amplitude quadrature difference squeezing of 3.2 dB and phase quadrature sum squeezing of 3.1 dB is converted to a new entangled state at 530 and 1518 nm with the amplitude quadrature difference squeezing of 1.7 dB and phase quadrature sum squeezing of 1.8 dB. Our implementation enables the observation of entanglement between two light fields spanning approximately 1.5 octaves in optical frequency. The presented scheme is robust to the excess amplitude and phase noises of the pumpmore » field, making it a practical building block for quantum information processing and communication networks.« less

Systematic Correlation Matrix Evaluation (SCoMaE) - a bottom-up, science-led approach to identifying indicators

NASA Astrophysics Data System (ADS)

Mengis, Nadine; Keller, David P.; Oschlies, Andreas

2018-01-01

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

Analysis of heart rate variability signal in meditation using second-order difference plot

NASA Astrophysics Data System (ADS)

Goswami, Damodar Prasad; Tibarewala, Dewaki Nandan; Bhattacharya, Dilip Kumar

2011-06-01

In this article, the heart rate variability signal taken from subjects practising different types of meditations have been investigated to find the underlying similarity among them and how they differ from the non-meditative condition. Four different groups of subjects having different meditation techniques are involved. The data have been obtained from the Physionet and also collected with our own ECG machine. For data analysis, the second order difference plot is applied. Each of the plots obtained from the second order differences form a single cluster which is nearly elliptical in shape except for some outliers. In meditation, the axis of the elliptical cluster rotates anticlockwise from the cluster formed from the premeditation data, although the amount of rotation is not of the same extent in every case. This form study reveals definite and specific changes in the heart rate variability of the subjects during meditation. All the four groups of subjects followed different procedures but surprisingly the resulting physiological effect is the same to some extent. It indicates that there is some commonness among all the meditative techniques in spite of their apparent dissimilarity and it may be hoped that each of them leads to the same result as preached by the masters of meditation. The study shows that meditative state has a completely different physiology and that it can be achieved by any meditation technique we have observed. Possible use of this tool in clinical setting such as in stress management and in the treatment of hypertension is also mentioned.

Entanglement-distillation attack on continuous-variable quantum key distribution in a turbulent atmospheric channel

NASA Astrophysics Data System (ADS)

Guo, Ying; Xie, Cailang; Liao, Qin; Zhao, Wei; Zeng, Guihua; Huang, Duan

2017-08-01

The survival of Gaussian quantum states in a turbulent atmospheric channel is of crucial importance in free-space continuous-variable (CV) quantum key distribution (QKD), in which the transmission coefficient will fluctuate in time, thus resulting in non-Gaussian quantum states. Different from quantum hacking of the imperfections of practical devices, here we propose a different type of attack by exploiting the security loopholes that occur in a real lossy channel. Under a turbulent atmospheric environment, the Gaussian states are inevitably afflicted by decoherence, which would cause a degradation of the transmitted entanglement. Therefore, an eavesdropper can perform an intercept-resend attack by applying an entanglement-distillation operation on the transmitted non-Gaussian mixed states, which allows the eavesdropper to bias the estimation of the parameters and renders the final keys shared between the legitimate parties insecure. Our proposal highlights the practical CV QKD vulnerabilities with free-space quantum channels, including the satellite-to-earth links, ground-to-ground links, and a link from moving objects to ground stations.

Near-optimal, asymptotic tracking in control problems involving state-variable inequality constraints

NASA Technical Reports Server (NTRS)

Markopoulos, N.; Calise, A. J.

1993-01-01

The class of all piecewise time-continuous controllers tracking a given hypersurface in the state space of a dynamical system can be split by the present transformation technique into two disjoint classes; while the first of these contains all controllers which track the hypersurface in finite time, the second contains all controllers that track the hypersurface asymptotically. On this basis, a reformulation is presented for optimal control problems involving state-variable inequality constraints. If the state constraint is regarded as 'soft', there may exist controllers which are asymptotic, two-sided, and able to yield the optimal value of the performance index.

The gamma-ray pulsar population of globular clusters: implications for the GeV excess

NASA Astrophysics Data System (ADS)

Hooper, Dan; Linden, Tim

2016-08-01

It has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecond pulsars in the Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.

The gamma-ray pulsar population of globular clusters: implications for the GeV excess

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

Hooper, Dan; Linden, Tim, E-mail: dhooper@fnal.gov, E-mail: linden.70@osu.edu

It has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecond pulsars in themore » Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.« less

The gamma-ray pulsar population of globular clusters: Implications for the GeV excess

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

Hooper, Dan; Linden, Tim

In this study, it has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecondmore » pulsars in the Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.« less

The gamma-ray pulsar population of globular clusters: Implications for the GeV excess

DOE PAGES

Hooper, Dan; Linden, Tim

2016-08-09

In this study, it has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecondmore » pulsars in the Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.« less

Cluster-guided imaging-based CFD analysis of airflow and particle deposition in asthmatic human lungs

NASA Astrophysics Data System (ADS)

Choi, Jiwoong; Leblanc, Lawrence; Choi, Sanghun; Haghighi, Babak; Hoffman, Eric; Lin, Ching-Long

2017-11-01

The goal of this study is to assess inter-subject variability in delivery of orally inhaled drug products to small airways in asthmatic lungs. A recent multiscale imaging-based cluster analysis (MICA) of computed tomography (CT) lung images in an asthmatic cohort identified four clusters with statistically distinct structural and functional phenotypes associating with unique clinical biomarkers. Thus, we aimed to address inter-subject variability via inter-cluster variability. We selected a representative subject from each of the 4 asthma clusters as well as 1 male and 1 female healthy controls, and performed computational fluid and particle simulations on CT-based airway models of these subjects. The results from one severe and one non-severe asthmatic cluster subjects characterized by segmental airway constriction had increased particle deposition efficiency, as compared with the other two cluster subjects (one non-severe and one severe asthmatics) without airway constriction. Constriction-induced jets impinging on distal bifurcations led to excessive particle deposition. The results emphasize the impact of airway constriction on regional particle deposition rather than disease severity, demonstrating the potential of using cluster membership to tailor drug delivery. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837. XSEDE.

Assessment of Social Vulnerability Identification at Local Level around Merapi Volcano - A Self Organizing Map Approach

NASA Astrophysics Data System (ADS)

Lee, S.; Maharani, Y. N.; Ki, S. J.

2015-12-01

The application of Self-Organizing Map (SOM) to analyze social vulnerability to recognize the resilience within sites is a challenging tasks. The aim of this study is to propose a computational method to identify the sites according to their similarity and to determine the most relevant variables to characterize the social vulnerability in each cluster. For this purposes, SOM is considered as an effective platform for analysis of high dimensional data. By considering the cluster structure, the characteristic of social vulnerability of the sites identification can be fully understand. In this study, the social vulnerability variable is constructed from 17 variables, i.e. 12 independent variables which represent the socio-economic concepts and 5 dependent variables which represent the damage and losses due to Merapi eruption in 2010. These variables collectively represent the local situation of the study area, based on conducted fieldwork on September 2013. By using both independent and dependent variables, we can identify if the social vulnerability is reflected onto the actual situation, in this case, Merapi eruption 2010. However, social vulnerability analysis in the local communities consists of a number of variables that represent their socio-economic condition. Some of variables employed in this study might be more or less redundant. Therefore, SOM is used to reduce the redundant variable(s) by selecting the representative variables using the component planes and correlation coefficient between variables in order to find the effective sample size. Then, the selected dataset was effectively clustered according to their similarities. Finally, this approach can produce reliable estimates of clustering, recognize the most significant variables and could be useful for social vulnerability assessment, especially for the stakeholder as decision maker. This research was supported by a grant 'Development of Advanced Volcanic Disaster Response System considering Potential Volcanic Risk around Korea' [MPSS-NH-2015-81] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea. Keywords: Self-organizing map, Component Planes, Correlation coefficient, Cluster analysis, Sites identification, Social vulnerability, Merapi eruption 2010

A taxonomy of state public health preparedness units: an empirical examination of organizational structure.

PubMed

Menachemi, Nir; Yeager, Valerie A; Duncan, W Jack; Katholi, Charles R; Ginter, Peter M

2012-01-01

State public health preparedness units (SPHPUs) were developed in response to federal funding to improve response to disasters: a responsibility that had not traditionally been within the purview of public health. The SPHPUs were created within the existing public health organizational structure, and their placement may have implications for how the unit functions, how communication takes place, and ultimately how well the key responsibilities are performed. This study empirically identifies a taxonomy of similarly structured SPHPUs and examines whether this structure is associated with state geographic, demographic, and threat-vulnerability characteristics. Data representing each SPHPU were extracted from publically available sources, including organizational charts and emergency preparedness plans for 2009. A cross-sectional segmentation analysis was conducted of variables representing structural attributes. Fifty state public health departments. Variables representing "span of control" and "hierarchal levels" were extracted from organizational charts. Structural "complexity" and "centralization" were extracted from state emergency preparedness documents and other secondary sources. On average, 6.6 people report to the same manager as the SPHPU director; 2.1 levels separate the SPHPU director from the state health officer; and a mean of 13.5 agencies collaborate with SPHPU during a disaster. Despite considerable variability in how SPHPUs had been structured, results of the cluster and principal component analysis identified 7 similarly structured groups. Neither the taxonomic groups nor the individual variables representing structure were found to be associated with state characteristics, including threat vulnerabilities. Our finding supports the hypothesis that SPHPUs are seemingly inadvertently (eg, not strategically) organized. This taxonomy provides the basis for which future research can examine how SPHPU structure relates to performance measures and preparedness strategies.

Internet Gamblers Differ on Social Variables: A Latent Class Analysis.

PubMed

Khazaal, Yasser; Chatton, Anne; Achab, Sophia; Monney, Gregoire; Thorens, Gabriel; Dufour, Magali; Zullino, Daniele; Rothen, Stephane

2017-09-01

Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression-Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression-Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

Variability among Cucurbitaceae species (melon, cucumber and watermelon) in a genomic region containing a cluster of NBS-LRR genes.

PubMed

Morata, Jordi; Puigdomènech, Pere

2017-02-08

Cucurbitaceae species contain a significantly lower number of genes coding for proteins with similarity to plant resistance genes belonging to the NBS-LRR family than other plant species of similar genome size. A large proportion of these genes are organized in clusters that appear to be hotspots of variability. The genomes of the Cucurbitaceae species measured until now are intermediate in size (between 350 and 450 Mb) and they apparently have not undergone any genome duplications beside those at the origin of eudicots. The cluster containing the largest number of NBS-LRR genes has previously been analyzed in melon and related species and showed a high degree of interspecific and intraspecific variability. It was of interest to study whether similar behavior occurred in other cluster of the same family of genes. The cluster of NBS-LRR genes located in melon chromosome 9 was analyzed and compared with the syntenic regions in other cucurbit genomes. This is the second cluster in number within this species and it contains nine sequences with a NBS-LRR annotation including two genes, Fom1 and Prv, providing resistance against Fusarium and Ppapaya ring-spot virus (PRSV). The variability within the melon species appears to consist essentially of single nucleotide polymorphisms. Clusters of similar genes are present in the syntenic regions of the two species of Cucurbitaceae that were sequenced, cucumber and watermelon. Most of the genes in the syntenic clusters can be aligned between species and a hypothesis of generation of the cluster is proposed. The number of genes in the watermelon cluster is similar to that in melon while a higher number of genes (12) is present in cucumber, a species with a smaller genome than melon. After comparing genome resequencing data of 115 cucumber varieties, deletion of a group of genes is observed in a group of varieties of Indian origin. Clusters of genes coding for NBS-LRR proteins in cucurbits appear to have specific variability in different regions of the genome and between different species. This observation is in favour of considering that the adaptation of plant species to changing environments is based upon the variability that may occur at any location in the genome and that has been produced by specific mechanisms of sequence variation acting on plant genomes. This information could be useful both to understand the evolution of species and for plant breeding.

Variable stars around selected open clusters in the VVV area: Young Stellar Objects

NASA Astrophysics Data System (ADS)

Medina, Nicolas; Borissova, Jura; Bayo, Amelia; Kurtev, Radostin; Lucas, Philip

2017-09-01

Time-varying phenomena are one of the most substantial sources of astrophysical information, and led to many fundamental discoveries in modern astronomy. We have developed an automated tool to search and analyze variable sources in the near infrared Ks band, using the data from the Vista Variables in the Vía Láctea (VVV) ESO Public Survey ([5, 8]). One of our main goals is to investigate the Young Stellar Objects (YSOs) in the Galactic star forming regions, looking for: •Variability. •New pre-main sequence star clusters. Here we present the newly discovered YSOs within some selected stellar clusters in our Galaxy.

On the complexity of some quadratic Euclidean 2-clustering problems

NASA Astrophysics Data System (ADS)

Kel'manov, A. V.; Pyatkin, A. V.

2016-03-01

Some problems of partitioning a finite set of points of Euclidean space into two clusters are considered. In these problems, the following criteria are minimized: (1) the sum over both clusters of the sums of squared pairwise distances between the elements of the cluster and (2) the sum of the (multiplied by the cardinalities of the clusters) sums of squared distances from the elements of the cluster to its geometric center, where the geometric center (or centroid) of a cluster is defined as the mean value of the elements in that cluster. Additionally, another problem close to (2) is considered, where the desired center of one of the clusters is given as input, while the center of the other cluster is unknown (is the variable to be optimized) as in problem (2). Two variants of the problems are analyzed, in which the cardinalities of the clusters are (1) parts of the input or (2) optimization variables. It is proved that all the considered problems are strongly NP-hard and that, in general, there is no fully polynomial-time approximation scheme for them (unless P = NP).

Variable Stars In the Unusual, Metal-Rich Globular Cluster

NASA Technical Reports Server (NTRS)

Pritzl, Barton J.; Smith, Horace A.; Catelan, Marcio; Sweigart, Allen V.; Oegerle, William R. (Technical Monitor)

2002-01-01

We have undertaken a search for variable stars in the metal-rich globular cluster NGC 6388 using time-series BV photometry. Twenty-eight new variables were found in this survey, increasing the total number of variables found near NGC 6388 to approx. 57. A significant number of the variables are RR Lyrae (approx. 14), most of which are probable cluster members. The periods of the fundamental mode RR Lyrae are shown to be unusually long compared to metal-rich field stars. The existence of these long period RRab stars suggests that the horizontal branch of NGC 6388 is unusually bright. This implies that the metallicity-luminosity relationship for RR Lyrae stars is not universal if the RR Lyrae in NGC 6388 are indeed metal-rich. We consider the alternative possibility that the stars in NGC 6388 may span a range in [Fe/H]. Four candidate Population II Cepheids were also found. If they are members of the cluster, NGC 6388 would be the most metal-rich globular cluster to contain Population II Cepheids. The mean V magnitude of the RR Lyrae is found to be 16.85 +/- 0.05 resulting in a distance of 9.0 to 10.3 kpc, for a range of assumed values of (M(sub V)) for RR Lyrae. We determine the reddening of the cluster to be E(B - V) = 0.40 +/- 0.03 mag, with differential reddening across the face of the cluster. We discuss the difficulty in determining the Oosterhoff classification of NGC 6388 and NGC 6441 due to the unusual nature of their RR Lyrae, and address evolutionary constraints on a recent suggestion that they are of Oosterhoff type II.

Synthesis and Characterization of Platinum-Ruthenium-Tin Catalysts

NASA Astrophysics Data System (ADS)

Uffalussy, Karen

Magnesia-supported trimetallic Pt-Ru-Sn catalysts prepared through a cluster and a conventional synthetic route have been investigated in terms of their structural properties and their catalytic activity for the hydrogenation of citral and crotonaldehyde. FTIR results indicate that the majority of the stabilizing ligands remain attached to the PtRu5(μ-SnPh 2)(C)(CO)15 cluster used following impregnation onto the MgO support. Under H2 reduction conditions, partial and full ligand removal are both observed at 473 and 573 K, respectively. HRSTEM analysis shows that cluster-derived samples exhibit significantly smaller average metal particle sizes, as well as narrower particle size distributions than the corresponding conventionally prepared ones. EDX measurements show that in the cluster-derived catalysts, the majority of the metal particles present are trimetallic in nature, with metal compositions similar to those of the original cluster. In contrast, the conventionally prepared materials contain mostly bimetallic and monometallic particles with variable compositions. XPS was used to determine how the variation in method of Sn addition to bimetallic Pt-Ru affects the electronic state for the trimetallic Pt-Ru-Sn/MgO system prepared by impregnation using multimetallic clusters, metal-salts, and the combination of both precursor types. Results show that the PtRu5Sn/MgO material has a significantly higher percentage of Sn0 in comparison to Pt-Ru-Sn/MgO and PtRu5-Sn/MgO, and a corresponding shift in both Pt and Ru peaks can be correlated to this relative change in Sn oxidation state. The formation of smaller metal particles and electronic modification of Pt and Ru by Sn in the cluster-derived catalysts and the presence of the three metals in these particles in close proximity result in higher activity and selectivity to the unsaturated alcohols for the hydrogenation of both citral and crotonaldehyde.

Assessment of the Status of Measles Elimination in the United States, 2001-2014.

PubMed

Gastañaduy, Paul A; Paul, Prabasaj; Fiebelkorn, Amy Parker; Redd, Susan B; Lopman, Ben A; Gambhir, Manoj; Wallace, Gregory S

2017-04-01

We assessed the status of measles elimination in the United States using outbreak notification data. Measles transmissibility was assessed by estimation of the reproduction number, R, the average number of secondary cases per infection, using 4 methods; elimination requires maintaining R at <1. Method 1 estimates R as 1 minus the proportion of cases that are imported. Methods 2 and 3 estimate R by fitting a model of the spread of infection to data on the sizes and generations of chains of transmission, respectively. Method 4 assesses transmissibility before public health interventions, by estimating R for the case with the earliest symptom onset in each cluster (Rindex). During 2001-2014, R and Rindex estimates obtained using methods 1-4 were 0.72 (95% confidence interval (CI): 0.68, 0.76), 0.66 (95% CI: 0.62, 0.70), 0.45 (95% CI: 0.40, 0.49), and 0.63 (95% CI: 0.57, 0.69), respectively. Year-to-year variability in the values of R and Rindex and an increase in transmissibility in recent years were noted with all methods. Elimination of endemic measles transmission is maintained in the United States. A suggested increase in measles transmissibility since elimination warrants continued monitoring and emphasizes the importance of high measles vaccination coverage throughout the population. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Accretion disc wind variability in the states of the microquasar GRS 1915+105

NASA Astrophysics Data System (ADS)

Neilsen, Joseph; Petschek, Andrew J.; Lee, Julia C.

2012-03-01

Continuing our study of the role and evolution of accretion disc winds in the microquasar GRS 1915+105, we present high-resolution spectral variability analysis of the β and γ states with the Chandra High-Energy Transmission Grating Spectrometer. By tracking changes in the absorption lines from the accretion disc wind, we find new evidence that radiation links the inner and outer accretion discs on a range of time-scales. As the central X-ray flux rises during the high-luminosity γ state, we observe the progressive overionization of the wind. In the β state, we argue that changes in the inner disc leading to the ejection of a transient 'baby jet' also quench the highly ionized wind from the outer disc. Our analysis reveals how the state, structure and X-ray luminosity of the inner accretion disc all conspire to drive the formation and variability of highly ionized accretion disc winds.

Measuring P-V-T Phase Behavior with a Variable Volume View Cell

ERIC Educational Resources Information Center

Hoffmann, Markus M.; Salter, Jason D.

2004-01-01

An experiment using a variable volume cell is presented where students actively control and directly observe the phase equilibrium inside the view cell. Measuring and exploring P-V-T phase behavior through dielectric constant measurements conveys the important concept that solvent behavior can be changed continuously in the sc fluid state.

Demographic and Lifestyle Variables Associated with Obesity

ERIC Educational Resources Information Center

Worthy, Sheri L.; Lokken, Kristine; Pilcher, Kenneth; Boeka, Abbe

2010-01-01

Objective: Overweight and obesity rates are associated with chronic diseases and higher rates of disability and continue to rise in the United States and worldwide. The purpose of this study was to build on past research and further investigate demographic and lifestyle variables associated with increased body mass index (BMI: kg/m[squared]).…

Reddening, distance modulus and age of the globular cluster NGC 6121 (M4) from the properties of RR Lyrae variables

NASA Astrophysics Data System (ADS)

Caputo, F.; Castellani, V.; Quarta, M. L.

1985-02-01

It is shown that pulsational properties of RR Lyrae variables in globular clusters can be used to put theoretical constraints on the values of cluster reddening and distance modulus. By requiring that the HR diagram location of pulsators agrees with the period distribution observed and with the theoretical boundaries of the instability strip, reddening and distance modulus of the globular cluster M4 are derived as a (slow) function of the pulsator masses. Thus, a best guess is presented for the cluster age (t = 12.2 billion years), some evidence for a non-canonical evolutionary having been taken into account.

NanoClusters Enhance Drug Delivery in Mechanical Ventilation

NASA Astrophysics Data System (ADS)

Pornputtapitak, Warangkana

The overall goal of this thesis was to develop a dry powder delivery system for patients on mechanical ventilation. The studies were divided into two parts: the formulation development and the device design. The pulmonary system is an attractive route for drug delivery since the lungs have a large accessible surface area for treatment or drug absorption. For ventilated patients, inhaled drugs have to successfully navigate ventilator tubing and an endotracheal tube. Agglomerates of drug nanoparticles (also known as 'NanoClusters') are fine dry powder aerosols that were hypothesized to enable drug delivery through ventilator circuits. This Thesis systematically investigated formulations of NanoClusters and their aerosol performance in a conventional inhaler and a device designed for use during mechanical ventilation. These engineered powders of budesonide (NC-Bud) were delivered via a MonodoseRTM inhaler or a novel device through commercial endotracheal tubes, and analyzed by cascade impaction. NC-Bud had a higher efficiency of aerosol delivery compared to micronized stock budesonide. The delivery efficiency was independent of ventilator parameters such as inspiration patterns, inspiration volumes, and inspiration flow rates. A novel device designed to fit directly to the ventilator and endotracheal tubing connections and the MonodoseRTM inhaler showed the same efficiency of drug delivery. The new device combined with NanoCluster formulation technology, therefore, allowed convenient and efficient drug delivery through endotracheal tubes. Furthermore, itraconazole (ITZ), a triazole antifungal agent, was formulated as a NanoCluster powder via milling (top-down process) or precipitation (bottom-up process) without using any excipients. ITZ NanoClusters prepared by wet milling showed better aerosol performance compared to micronized stock ITZ and ITZ NanoClusters prepared by precipitation. ITZ NanoClusters prepared by precipitation methods also showed an amorphous state while milled ITZ NanoClusters maintained the crystalline character. Overall, NanoClusters prepared by various processes represent a potential engineered drug particle approach for inhalation therapy since they provide effective aerosol properties and stability due to the crystalline state of the drug powders. Future work will continue to explore formulation and delivery performance in vitro and in vivo..

The Cluster AgeS Experiment (CASE). Variable Stars in the Field of the Globular Cluster M22

NASA Astrophysics Data System (ADS)

Rozyczka, M.; Thompson, I. B.; Pych, W.; Narloch, W.; Poleski, R.; Schwarzenberg-Czerny, A.

2017-09-01

The field of the globular cluster M22 (NGC 6656) was monitored between 2000 and 2008 in a search for variable stars. BV light curves were obtained for 359 periodic, likely periodic, and long-term variables, 238 of which are new detections. 39 newly detected variables, and 63 previously known ones are members or likely members of the cluster, including 20 SX Phe, 10 RRab and 16 RRc type pulsators, one BL Her type pulsator, 21 contact binaries, and 9 detached or semi-detached eclipsing binaries. The most interesting among the identified objects are V112 - a bright multimode SX Phe pulsator, V125 - a β Lyr type binary on the blue horizontal branch, V129 - a blue/yellow straggler with a W UMa-like light curve, located halfway between the extreme horizontal branch and red giant branch, and V134 - an extreme horizontal branch object with P=2.33 d and a nearly sinusoidal light curve. All four of them are proper motion members of the cluster. Among nonmembers, a P=2.83 d detached eclipsing binary hosting a δ Sct type pulsator was found, and a peculiar P=0.93 d binary with ellipsoidal modulation and narrow minimum in the middle of one of the descending shoulders of the sinusoid. We also collected substantial new data for previously known variables. In particular we revise the statistics of the occurrence of the Blazhko effect in RR Lyr type variables of M22.

MEASURING LENSING MAGNIFICATION OF QUASARS BY LARGE SCALE STRUCTURE USING THE VARIABILITY-LUMINOSITY RELATION

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

Bauer, Anne H.; Seitz, Stella; Jerke, Jonathan

2011-05-10

We introduce a technique to measure gravitational lensing magnification using the variability of type I quasars. Quasars' variability amplitudes and luminosities are tightly correlated, on average. Magnification due to gravitational lensing increases the quasars' apparent luminosity, while leaving the variability amplitude unchanged. Therefore, the mean magnification of an ensemble of quasars can be measured through the mean shift in the variability-luminosity relation. As a proof of principle, we use this technique to measure the magnification of quasars spectroscopically identified in the Sloan Digital Sky Survey (SDSS), due to gravitational lensing by galaxy clusters in the SDSS MaxBCG catalog. The Palomar-QUESTmore » Variability Survey, reduced using the DeepSky pipeline, provides variability data for the sources. We measure the average quasar magnification as a function of scaled distance (r/R{sub 200}) from the nearest cluster; our measurements are consistent with expectations assuming Navarro-Frenk-White cluster profiles, particularly after accounting for the known uncertainty in the clusters' centers. Variability-based lensing measurements are a valuable complement to shape-based techniques because their systematic errors are very different, and also because the variability measurements are amenable to photometric errors of a few percent and to depths seen in current wide-field surveys. Given the volume data of the expected from current and upcoming surveys, this new technique has the potential to be competitive with weak lensing shear measurements of large-scale structure.« less

Continuous-variable quantum cryptography with an untrusted relay: Detailed security analysis of the symmetric configuration

NASA Astrophysics Data System (ADS)

Ottaviani, Carlo; Spedalieri, Gaetana; Braunstein, Samuel L.; Pirandola, Stefano

2015-02-01

We consider the continuous-variable protocol of Pirandola et al. [arXiv:1312.4104] where the secret key is established by the measurement of an untrusted relay. In this network protocol, two authorized parties are connected to an untrusted relay by insecure quantum links. Secret correlations are generated by a continuous-variable Bell detection performed on incoming coherent states. In the present work we provide a detailed study of the symmetric configuration, where the relay is midway between the parties. We analyze symmetric eavesdropping strategies against the quantum links explicitly showing that, at fixed transmissivity and thermal noise, two-mode coherent attacks are optimal, manifestly outperforming one-mode collective attacks based on independent entangling cloners. Such an advantage is shown both in terms of security threshold and secret-key rate.

Continuous-variable quantum key distribution based on a plug-and-play dual-phase-modulated coherent-states protocol

NASA Astrophysics Data System (ADS)

Huang, Duan; Huang, Peng; Wang, Tao; Li, Huasheng; Zhou, Yingming; Zeng, Guihua

2016-09-01

We propose and experimentally demonstrate a continuous-variable quantum key distribution (CV-QKD) protocol using dual-phase-modulated coherent states. We show that the modulation scheme of our protocol works equivalently to that of the Gaussian-modulated coherent-states (GMCS) protocol, but shows better experimental feasibility in the plug-and-play configuration. Besides, it waives the necessity of propagation of a local oscillator (LO) between legitimate users and generates a real local LO for quantum measurement. Our protocol is proposed independent of the one-way GMCS QKD without sending a LO [Opt. Lett. 40, 3695 (2015), 10.1364/OL.40.003695; Phys. Rev. X 5, 041009 (2015), 10.1103/PhysRevX.5.041009; Phys. Rev. X 5, 041010 (2015), 10.1103/PhysRevX.5.041010]. In those recent works, the system stability will suffer the impact of polarization drifts induced by environmental perturbations, and two independent frequency-locked laser sources are necessary to achieve reliable coherent detection. In the proposed protocol, these previous problems can be resolved. We derive the security bounds for our protocol against collective attacks, and we also perform a proof-of-principle experiment to confirm the utility of our proposal in real-life applications. Such an efficient scheme provides a way of removing the security loopholes associated with the transmitting LO, which have been a notoriously hard problem in continuous-variable quantum communication.

Realistic continuous-variable quantum teleportation with non-Gaussian resources

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

Dell'Anno, F.; De Siena, S.; CNR-INFM Coherentia, Napoli, Italy, and CNISM and INFN Sezione di Napoli, Gruppo Collegato di Salerno, Baronissi, SA

2010-01-15

We present a comprehensive investigation of nonideal continuous-variable quantum teleportation implemented with entangled non-Gaussian resources. We discuss in a unified framework the main decoherence mechanisms, including imperfect Bell measurements and propagation of optical fields in lossy fibers, applying the formalism of the characteristic function. By exploiting appropriate displacement strategies, we compute analytically the success probability of teleportation for input coherent states and two classes of non-Gaussian entangled resources: two-mode squeezed Bell-like states (that include as particular cases photon-added and photon-subtracted de-Gaussified states), and two-mode squeezed catlike states. We discuss the optimization procedure on the free parameters of the non-Gaussian resourcesmore » at fixed values of the squeezing and of the experimental quantities determining the inefficiencies of the nonideal protocol. It is found that non-Gaussian resources enhance significantly the efficiency of teleportation and are more robust against decoherence than the corresponding Gaussian ones. Partial information on the alphabet of input states allows further significant improvement in the performance of the nonideal teleportation protocol.« less

Thermodynamics of confined gallium clusters.

PubMed

Chandrachud, Prachi

2015-11-11

We report the results of ab initio molecular dynamics simulations of Ga13 and Ga17 clusters confined inside carbon nanotubes with different diameters. The cluster-tube interaction is simulated by the Lennard-Jones (LJ) potential. We discuss the geometries, the nature of the bonding and the thermodynamics under confinement. The geometries as well as the isomer spectra of both the clusters are significantly affected. The degree of confinement decides the dimensionality of the clusters. We observe that a number of low-energy isomers appear under moderate confinement while some isomers seen in the free space disappear. Our finite-temperature simulations bring out interesting aspects, namely that the heat capacity curve is flat, even though the ground state is symmetric. Such a flat nature indicates that the phase change is continuous. This effect is due to the restricted phase space available to the system. These observations are supported by the mean square displacement of individual atoms, which are significantly smaller than in free space. The nature of the bonding is found to be approximately jellium-like. Finally we note the relevance of the work to the problem of single file diffusion for the case of the highest confinement.

What variables affect public perceptions for EMS meeting general community needs?

PubMed

Blau, Gary; Hochner, Arthur; Portwood, James

2012-01-01

In the fall, 2010, a phone survey of 928 respondents examined two research questions: does the general public perceive Emergency Medical Services (EMS) as meeting their community needs? And what factors or correlates help to explain EMS meeting community needs? To maximize geographical representation across the contiguous United States, a clustered stratified sampling strategy was used based upon zip codes across the 48 states. Results showed strong support by the sample for perceiving that EMS was meeting their general community needs. 17 percent of the variance in EMS meeting community needs was collectively explained by the demographic and perceptual variables in the regression model. Of the correlates tested, the strongest relationship was found between greater admiration for EMS professionals and higher perception of EMS meeting community needs. Study limitations included sampling households with only landline (no cell) phones, using a simulated emergency situation, and not collecting gender data.

Search for Pulsating Stars in the Open Cluster NGC 1502

NASA Astrophysics Data System (ADS)

Stęślicki, M.

2006-04-01

We present results of a variability search in the field of the young open cluster NGC 1502. We confirm that a beta Cephei suspect WEBDA 26 is indeed pulsating with a period of 0.09612 d and semi-amplitude of about 3 mmag in V. A new VI light curve of the bright eclipsing binary and cluster member SZ Cam was obtained. In addition, we found two new variable stars. One is an interesting eclipsing binary showing total eclipses, which can be used to derive the distance to the cluster once radial velocities of the components will be obtained.

Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

PubMed

Yokoyama, Eiji; Uchimura, Masako

2007-11-01

Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

TIME-RESOLVED SPECTROSCOPY OF THE POLAR EU CANCRI IN THE OPEN CLUSTER MESSIER 67

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

Williams, Kurtis A.; Howell, Steve B.; Liebert, James

2013-05-15

We present time-resolved spectroscopic and polarimetric observations of the AM Her system EU Cnc. EU Cnc is located near the core of the old open cluster Messier 67; new proper motion measurements indicate that EU Cnc is indeed a member of the star cluster, and this system therefore is useful to constrain the formation and evolution of magnetic cataclysmic variables. The spectra exhibit two-component emission features with independent radial velocity variations as well as time-variable cyclotron emission indicating a magnetic field strength of 41 MG. The period of the radial velocity and cyclotron hump variations are consistent with the previouslymore » known photometric period, and the spectroscopic flux variations are consistent in amplitude with previous photometric amplitude measurements. The secondary star is also detected in the spectrum. We also present polarimetric imaging measurements of EU Cnc that show a clear detection of polarization, and the degree of polarization drops below our detection threshold at phases when the cyclotron emission features are fading or not evident. The combined data are all consistent with the interpretation that EU Cnc is a low-state polar in the cluster Messier 67. The mass function of the system gives an estimate of the accretor mass of M{sub WD} {>=} 0.68 M{sub Sun} with M{sub WD} Almost-Equal-To 0.83 M{sub Sun} for an average inclination. We are thus able to place a lower limit on the progenitor mass of the accreting white dwarf of {>=}1.43 M{sub Sun }.« less

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.

Continuous-variable quantum-key-distribution protocols with a non-Gaussian modulation

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

Leverrier, Anthony; Grangier, Philippe; Laboratoire Charles Fabry, Institut d'Optique, CNRS, Univ. Paris-Sud, Campus Polytechnique, RD 128, F-91127 Palaiseau Cedex

2011-04-15

In this paper, we consider continuous-variable quantum-key-distribution (QKD) protocols which use non-Gaussian modulations. These specific modulation schemes are compatible with very efficient error-correction procedures, hence allowing the protocols to outperform previous protocols in terms of achievable range. In their simplest implementation, these protocols are secure for any linear quantum channels (hence against Gaussian attacks). We also show how the use of decoy states makes the protocols secure against arbitrary collective attacks, which implies their unconditional security in the asymptotic limit.

Synthesis of MFe3S4 clusters containing a planar M(II) site (M = Ni, Pd, Pt), a structural element in the C-cluster of carbon monoxide dehydrogenase.

PubMed

Panda, Rashmishree; Berlinguette, Curtis P; Zhang, Yugen; Holm, Richard H

2005-08-10

Synthesis of an analogue of the C-cluster of C. hydrogenoformans carbon monoxide dehydrogenase requires formation of a planar Ni(II) site and attachment of an exo iron atom in the core unit NiFe(4)S(5). The first objective has been achieved by two reactions: (i) displacement of Ph(3)P or Bu(t)()NC at tetrahedral Ni(II) sites of cubane-type [NiFe(3)S(4)](+) clusters with chelating diphosphines, and (ii) metal atom incorporation into a cuboidal [Fe(3)S(4)](0) cluster with a M(0) reactant in the presence of bis(1,2-dimethylphosphino)ethane (dmpe). The isolated product clusters [(dmpe)MFe(3)S(4)(LS(3))](2-) (M = Ni(II) (9), Pd(II) (12), Pt(II) (13); LS(3) = 1,3,5-tris((4,6-dimethyl-3-mercaptophenyl)thio)-2,4,6-tris(p-tolylthio)benzene(3-)) contain the cores [MFe(3)(mu(2)-S)(mu(3)-S)(3)](+) having planar M(II)P(2)S(2) sites and variable nonbonding M...S distances of 2.6-3.4 A. Reaction (i) involves a tetrahedral --> planar Ni(II) structural change between isomeric cubane and cubanoid [NiFe(3)S(4)](+) cores. Based on the magnetic properties of 12 and earlier considerations, the S = (5)/(2) ground state of the cubanoid cluster arises from the [Fe(3)S(4)](-) fragment, whereas the S = (3)/(2) ground state of the cubane cluster is a consequence of antiferromagnetic coupling between the spins of Ni(2+) (S = 1) and [Fe(3)S(4)](-). Other substitution reactions of [NiFe(3)S(4)](+) clusters and 1:3 site-differentiated [Fe(4)S(4)](2+) clusters are described, as are the structures of 12, 13, [(Me(3)P)NiFe(3)S(4)(LS(3))](2-), and [Fe(4)S(4)(LS(3))L'](2-) (L' = Me(2)NC(2)H(4)S(-), Ph(2)P(O)C(2)H(4)S(-)). This work significantly expands our initial report of cluster 9 (Panda et al. J. Am. Chem. Soc. 2004, 126, 6448-6459) and further demonstrates that a planar M(II) site can be stabilized within a cubanoid [NiFe(3)S(4)](+) core.

Inferring HIV-1 Transmission Dynamics in Germany From Recently Transmitted Viruses.

PubMed

Pouran Yousef, Kaveh; Meixenberger, Karolin; Smith, Maureen R; Somogyi, Sybille; Gromöller, Silvana; Schmidt, Daniel; Gunsenheimer-Bartmeyer, Barbara; Hamouda, Osamah; Kücherer, Claudia; von Kleist, Max

2016-11-01

Although HIV continues to spread globally, novel intervention strategies such as treatment as prevention (TasP) may bring the epidemic to a halt. However, their effective implementation requires a profound understanding of the underlying transmission dynamics. We analyzed parameters of the German HIV epidemic based on phylogenetic clustering of viral sequences from recently infected seroconverters with known infection dates. Viral baseline and follow-up pol sequences (n = 1943) from 1159 drug-naïve individuals were selected from a nationwide long-term observational study initiated in 1997. Putative transmission clusters were computed based on a maximum likelihood phylogeny. Using individual follow-up sequences, we optimized our clustering threshold to maximize the likelihood of co-clustering individuals connected by direct transmission. The sizes of putative transmission clusters scaled inversely with their abundance and their distribution exhibited a heavy tail. Clusters based on the optimal clustering threshold were significantly more likely to contain members of the same or bordering German federal states. Interinfection times between co-clustered individuals were significantly shorter (26 weeks; interquartile range: 13-83) than in a null model. Viral intraindividual evolution may be used to select criteria that maximize co-clustering of transmission pairs in the absence of strong adaptive selection pressure. Interinfection times of co-clustered individuals may then be an indicator of the typical time to onward transmission. Our analysis suggests that onward transmission may have occurred early after infection, when individuals are typically unaware of their serological status. The latter argues that TasP should be combined with HIV testing campaigns to reduce the possibility of transmission before TasP initiation.

VizieR Online Data Catalog: Catalogue of variable stars in open clusters (Zejda+, 2012)

NASA Astrophysics Data System (ADS)

Zejda, M.; Paunzen, E.; Baumann, B.; Mikulasek, Z.; Liska, J.

2012-08-01

The catalogue of variable stars in open clusters were prepared by cross-matching of Variable Stars Index (http://www.aavso.org/vsx) version Apr 29, 2012 (available online, Cat. B/vsx) against the version 3.1. catalogue of open clusters DAML02 (Dias et al. 2002A&A...389..871D, Cat. B/ocl) available on the website http://www.astro.iag.usp.br/~wilton. The open clusters were divided into two categories according to their size, where the limiting diameter was 60 arcmin. The list of all suspected variables and variable stars located within the fields of open clusters up to two times of given cluster radius were generated (Table 1). 8938 and 9127 variable stars are given in 461 "smaller" and 74 "larger" clusters, respectively. All found variable stars were matched against the PPMXL catalog of positions and proper motions within the ICRS (Roeser et al., 2010AJ....139.2440R, Cat. I/317). Proper motion data were included in our catalogue. Unfortunately, a homogeneous data set of mean cluster proper motions has not been available until now. Therefore we used the following sources (sorted alphabetically) to compile a new catalogue: Baumgardt et al. (2000, Cat. J/A+AS/146/251): based on the Hipparcos catalogue Beshenov & Loktin (2004A&AT...23..103B): based on the Tycho-2 catalogue Dias et al. (2001, Cat. J/A+A/376/441, 2002A&A...389..871D, Cat. B/ocl): based on the Tycho-2 catalogue Dias et al. (2006, Cat. J/A+A/446/949): based on the UCAC2 catalog (Zacharias et al., 2004AJ....127.3043Z, Cat. I/289) Frinchaboy & Majewski (2008, Cat. J/AJ/136/118): based on the Tycho-2 catalogue Kharchenko et al. (2005, J/A+A/438/1163): based on the ASCC2.5 catalogue (Kharchenko, 2001KFNT...17..409K, Cat. I/280) Krone-Martins et al. (2010, Cat. J/A+A/516/A3): based on the Bordeaux PM2000 proper motion catalogue (Ducourant et al., 2006A&A...448.1235D, Cat. I/300) Robichon et al. (1999, Cat. J/A+A/345/471): based on the Hipparcos catalogue van Leeuwen (2009A&A...497..209V): based on the new Hipparcos catalogue. In total, a catalogue of proper motions for 879 open clusters (Table 2), from which 436 have more than one available measurement, was compiled. (3 data files).

The Metabolic Syndrome

PubMed Central

Cornier, Marc-Andre; Dabelea, Dana; Hernandez, Teri L.; Lindstrom, Rachel C.; Steig, Amy J.; Stob, Nicole R.; Van Pelt, Rachael E.; Wang, Hong; Eckel, Robert H.

2008-01-01

The “metabolic syndrome” (MetS) is a clustering of components that reflect overnutrition, sedentary lifestyles, and resultant excess adiposity. The MetS includes the clustering of abdominal obesity, insulin resistance, dyslipidemia, and elevated blood pressure and is associated with other comorbidities including the prothrombotic state, proinflammatory state, nonalcoholic fatty liver disease, and reproductive disorders. Because the MetS is a cluster of different conditions, and not a single disease, the development of multiple concurrent definitions has resulted. The prevalence of the MetS is increasing to epidemic proportions not only in the United States and the remainder of the urbanized world but also in developing nations. Most studies show that the MetS is associated with an approximate doubling of cardiovascular disease risk and a 5-fold increased risk for incident type 2 diabetes mellitus. Although it is unclear whether there is a unifying pathophysiological mechanism resulting in the MetS, abdominal adiposity and insulin resistance appear to be central to the MetS and its individual components. Lifestyle modification and weight loss should, therefore, be at the core of treating or preventing the MetS and its components. In addition, there is a general consensus that other cardiac risk factors should be aggressively managed in individuals with the MetS. Finally, in 2008 the MetS is an evolving concept that continues to be data driven and evidence based with revisions forthcoming. PMID:18971485

Topology-energy relationships and lowest energy configurations for pentagonal dodecahedral (H2O)20X clusters, X=empty, H2O, NH3, H3O+: The importance of O-topology

NASA Astrophysics Data System (ADS)

Anick, David J.

2010-04-01

For (H2O)20X water clusters consisting of X enclosed by the 512 dodecahedral cage, X=empty, H2O, NH3, and H3O+, databases are made consisting of 55-82 isomers optimized via B3LYP/6-311++G∗∗. Correlations are explored between ground state electronic energy (Ee) or electronic energy plus zero point energy (Ee+ZPE) and the clusters' topology, defined as the set of directed H-bonds. Linear regression is done to identify topological features that correlate with cluster energy. For each X, variables are found that account for 99% of the variance in Ee and predict it with a rms error under 0.2 kcal/mol. The method of analysis emphasizes the importance of an intermediate level of structure, the "O-topology," consisting of O-types and a list of O pairs that are bonded but omitting H-bond directions, as a device to organize the databases and reduce the number of structures one needs to consider. Relevant variables include three parameters, which count the number of H-bonds having particular donor and acceptor types; |M|2, where M is the cluster's vector dipole moment; and the projection of M onto the symmetry axis of X. Scatter diagrams for Ee or Ee+ZPE versus |M| show that clusters fall naturally into "families" defined by the values of certain discrete parameters, the "major parameters," for each X. Combining "family" analysis and O-topologies, a small group of clusters is identified for each X that are candidates to be the global minimum, and the minimum is determined. For X=H3O+, one cluster with central hydronium lies just 2.08 kcal/mol above the lowest isomer with surface hydronium. Implications of the methodology for dodecahedral (H2O)20(NH4+) and (H2O)20(NH4+)(OH-) are discussed, and new lower energy isomers are found. For MP2/TZVP, the lowest-energy (H2O)20(NH4+) isomer features a trifurcated H-bond. The results suggest a much more efficient and comprehensive way of seeking low-energy water cluster geometries that may have wide applicability.

Topology-energy relationships and lowest energy configurations for pentagonal dodecahedral (H2O)20X clusters, X = empty, H2O, NH3, H3O+: the importance of O-topology.

PubMed

Anick, David J

2010-04-28

For (H(2)O)(20)X water clusters consisting of X enclosed by the 5(12) dodecahedral cage, X = empty, H(2)O, NH(3), and H(3)O(+), databases are made consisting of 55-82 isomers optimized via B3LYP/6-311++G(**). Correlations are explored between ground state electronic energy (Ee) or electronic energy plus zero point energy (Ee+ZPE) and the clusters' topology, defined as the set of directed H-bonds. Linear regression is done to identify topological features that correlate with cluster energy. For each X, variables are found that account for 99% of the variance in Ee and predict it with a rms error under 0.2 kcal/mol. The method of analysis emphasizes the importance of an intermediate level of structure, the "O-topology," consisting of O-types and a list of O pairs that are bonded but omitting H-bond directions, as a device to organize the databases and reduce the number of structures one needs to consider. Relevant variables include three parameters, which count the number of H-bonds having particular donor and acceptor types; absolute value(M)(2), where M is the cluster's vector dipole moment; and the projection of M onto the symmetry axis of X. Scatter diagrams for Ee or Ee+ZPE versus absolute value(M) show that clusters fall naturally into "families" defined by the values of certain discrete parameters, the "major parameters," for each X. Combining "family" analysis and O-topologies, a small group of clusters is identified for each X that are candidates to be the global minimum, and the minimum is determined. For X = H(3)O(+), one cluster with central hydronium lies just 2.08 kcal/mol above the lowest isomer with surface hydronium. Implications of the methodology for dodecahedral (H(2)O)(20)(NH(4)(+)) and (H(2)O)(20)(NH(4)(+))(OH(-)) are discussed, and new lower energy isomers are found. For MP2/TZVP, the lowest-energy (H(2)O)(20)(NH(4)(+)) isomer features a trifurcated H-bond. The results suggest a much more efficient and comprehensive way of seeking low-energy water cluster geometries that may have wide applicability.

An {alpha}-cluster model for {sub {Lambda}}{sup 9}Be spectroscopy

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

Filikhin, I. N., E-mail: ifilikhin@nccu.edu; Suslov, V. M.; Vlahovic, B.

An {alpha}-cluster model is applied to study low-lying spectrum of the {sub {Lambda}}{sup 9}Be hypernucleus. The three-body {alpha}{alpha}{Lambda} problem is numerically solved by the Faddeev equations in configuration space using phenomenological pair potentials. We found a set of the potentials that reproduces experimental data for the ground state (1/2{sup +}) binding energy and excitation energy of the 5/2{sup +} and 3/2{sup +} states, simultaneously. This set includes the Ali-Bodmer potential of the version 'e' for {alpha}{alpha} and modified Tang-Herndon potential for {alpha}{Lambda} interactions. The spin-orbit {alpha}{Lambda} interaction is given by modified Scheerbaum potential. Low-lying energy levels are evaluated applying amore » variant of the analytical continuation method in the coupling constant. It is shown that the spectral properties of {sub {Lambda}}{sup 9}Be can be classified as an analog of {sup 9}Be spectrum with the exception of several 'genuine hypernuclear states'. This agrees qualitatively with previous studies. The results are compared with experimental data and new interpretation of the spectral structure is discussed.« less

Emergent causality and the N-photon scattering matrix in waveguide QED

NASA Astrophysics Data System (ADS)

Sánchez-Burillo, E.; Cadarso, A.; Martín-Moreno, L.; García-Ripoll, J. J.; Zueco, D.

2018-01-01

In this work we discuss the emergence of approximate causality in a general setup from waveguide QED—i.e. a one-dimensional propagating field interacting with a scatterer. We prove that this emergent causality translates into a structure for the N-photon scattering matrix. Our work builds on the derivation of a Lieb-Robinson-type bound for continuous models and for all coupling strengths, as well as on several intermediate results, of which we highlight: (i) the asymptotic independence of space-like separated wave packets, (ii) the proper definition of input and output scattering states, and (iii) the characterization of the ground state and correlations in the model. We illustrate our formal results by analyzing the two-photon scattering from a quantum impurity in the ultrastrong coupling regime, verifying the cluster decomposition and ground-state nature. Besides, we generalize the cluster decomposition if inelastic or Raman scattering occurs, finding the structure of the S-matrix in momentum space for linear dispersion relations. In this case, we compute the decay of the fluorescence (photon-photon correlations) caused by this S-matrix.

Continuous-variable measurement-device-independent quantum key distribution with virtual photon subtraction

NASA Astrophysics Data System (ADS)

Zhao, Yijia; Zhang, Yichen; Xu, Bingjie; Yu, Song; Guo, Hong

2018-04-01

The method of improving the performance of continuous-variable quantum key distribution protocols by postselection has been recently proposed and verified. In continuous-variable measurement-device-independent quantum key distribution (CV-MDI QKD) protocols, the measurement results are obtained from untrusted third party Charlie. There is still not an effective method of improving CV-MDI QKD by the postselection with untrusted measurement. We propose a method to improve the performance of coherent-state CV-MDI QKD protocol by virtual photon subtraction via non-Gaussian postselection. The non-Gaussian postselection of transmitted data is equivalent to an ideal photon subtraction on the two-mode squeezed vacuum state, which is favorable to enhance the performance of CV-MDI QKD. In CV-MDI QKD protocol with non-Gaussian postselection, two users select their own data independently. We demonstrate that the optimal performance of the renovated CV-MDI QKD protocol is obtained with the transmitted data only selected by Alice. By setting appropriate parameters of the virtual photon subtraction, the secret key rate and tolerable excess noise are both improved at long transmission distance. The method provides an effective optimization scheme for the application of CV-MDI QKD protocols.

Photonic multipartite entanglement conversion using nonlocal operations

NASA Astrophysics Data System (ADS)

Tashima, T.; Tame, M. S.; Özdemir, Ş. K.; Nori, F.; Koashi, M.; Weinfurter, H.

2016-11-01

We propose a simple setup for the conversion of multipartite entangled states in a quantum network with restricted access. The scheme uses nonlocal operations to enable the preparation of states that are inequivalent under local operations and classical communication, but most importantly does not require full access to the states. It is based on a flexible linear optical conversion gate that uses photons, which are ideally suited for distributed quantum computation and quantum communication in extended networks. In order to show the basic working principles of the gate, we focus on converting a four-qubit entangled cluster state to other locally inequivalent four-qubit states, such as the Greenberger-Horne-Zeilinger and symmetric Dicke states. We also show how the gate can be incorporated into extended graph state networks and can be used to generate variable entanglement and quantum correlations without entanglement but nonvanishing quantum discord.

Transfer of non-Gaussian quantum states of mechanical oscillator to light

NASA Astrophysics Data System (ADS)

Filip, Radim; Rakhubovsky, Andrey A.

2015-11-01

Non-Gaussian quantum states are key resources for quantum optics with continuous-variable oscillators. The non-Gaussian states can be deterministically prepared by a continuous evolution of the mechanical oscillator isolated in a nonlinear potential. We propose feasible and deterministic transfer of non-Gaussian quantum states of mechanical oscillators to a traveling light beam, using purely all-optical methods. The method relies on only basic feasible and high-quality elements of quantum optics: squeezed states of light, linear optics, homodyne detection, and electro-optical feedforward control of light. By this method, a wide range of novel non-Gaussian states of light can be produced in the future from the mechanical states of levitating particles in optical tweezers, including states necessary for the implementation of an important cubic phase gate.

Photometric search for variable stars in the young open cluster Berkeley 59

NASA Astrophysics Data System (ADS)

Lata, Sneh; Pandey, A. K.; Maheswar, G.; Mondal, Soumen; Kumar, Brijesh

2011-12-01

We present the time series photometry of stars located in the extremely young open cluster Berkeley 59. Using the 1.04-m telescope at Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital, we have identified 42 variables in a field of ˜13 × 13 arcmin2 around the cluster. The probable members of the cluster have been identified using a (V, V-I) colour-magnitude diagram and a (J-H, H-K) colour-colour diagram. 31 variables have been found to be pre-main-sequence stars associated with the cluster. The ages and masses of the pre-main-sequence stars have been derived from the colour-magnitude diagram by fitting theoretical models to the observed data points. The ages of the majority of the probable pre-main-sequence variable candidates range from 1 to 5 Myr. The masses of these pre-main-sequence variable stars have been found to be in the range of ˜0.3 to ˜3.5 M⊙, and these could be T Tauri stars. The present statistics reveal that about 90 per cent T Tauri stars have period <15 d. The classical T Tauri stars are found to have a larger amplitude than the weak-line T Tauri stars. There is an indication that the amplitude decreases with an increase in mass, which could be due to the dispersal of the discs of relatively massive stars.

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

PubMed Central

Zhao, Zhibiao

2011-01-01

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

Who Visits a National Park and What do They Get Out of It?: A Joint Visitor Cluster Analysis and Travel Cost Model for Yellowstone National Park

NASA Astrophysics Data System (ADS)

Benson, Charles; Watson, Philip; Taylor, Garth; Cook, Philip; Hollenhorst, Steve

2013-10-01

Yellowstone National Park visitor data were obtained from a survey collected for the National Park Service by the Park Studies Unit at the University of Idaho. Travel cost models have been conducted for national parks in the United States; however, this study builds on these studies and investigates how benefits vary by types of visitors who participate in different activities while at the park. Visitor clusters were developed based on activities in which a visitor participated while at the park. The clusters were analyzed and then incorporated into a travel cost model to determine the economic value (consumer surplus) that the different visitor groups received from visiting the park. The model was estimated using a zero-truncated negative binomial regression corrected for endogenous stratification. The travel cost price variable was estimated using both 1/3 and 1/4 the wage rate to test for sensitivity to opportunity cost specification. The average benefit across all visitor cluster groups was estimated at between 235 and 276 per person per trip. However, per trip benefits varied substantially across clusters; from 90 to 103 for the "value picnickers," to 185-263 for the "backcountry enthusiasts," 189-278 for the "do it all adventurists," 204-303 for the "windshield tourists," and 323-714 for the "creature comfort" cluster group.

Optimal control on hybrid ode systems with application to a tick disease model.

PubMed

Ding, Wandi

2007-10-01

We are considering an optimal control problem for a type of hybrid system involving ordinary differential equations and a discrete time feature. One state variable has dynamics in only one season of the year and has a jump condition to obtain the initial condition for that corresponding season in the next year. The other state variable has continuous dynamics. Given a general objective functional, existence, necessary conditions and uniqueness for an optimal control are established. We apply our approach to a tick-transmitted disease model with age structure in which the tick dynamics changes seasonally while hosts have continuous dynamics. The goal is to maximize disease-free ticks and minimize infected ticks through an optimal control strategy of treatment with acaricide. Numerical examples are given to illustrate the results.

Probabilistic Reasoning for Plan Robustness

NASA Technical Reports Server (NTRS)

Schaffer, Steve R.; Clement, Bradley J.; Chien, Steve A.

2005-01-01

A planning system must reason about the uncertainty of continuous variables in order to accurately project the possible system state over time. A method is devised for directly reasoning about the uncertainty in continuous activity duration and resource usage for planning problems. By representing random variables as parametric distributions, computing projected system state can be simplified in some cases. Common approximation and novel methods are compared for over-constrained and lightly constrained domains. The system compares a few common approximation methods for an iterative repair planner. Results show improvements in robustness over the conventional non-probabilistic representation by reducing the number of constraint violations witnessed by execution. The improvement is more significant for larger problems and problems with higher resource subscription levels but diminishes as the system is allowed to accept higher risk levels.

Cosmological Studies with Galaxy Clusters, Active Galactic Nuclei, and Strongly Lensed Quasars

NASA Astrophysics Data System (ADS)

Rumbaugh, Nicholas Andrew

The large-scale structure (LSS) of the universe provides scientists with one of the best laboratories for studying Lambda Cold Dark Matter (LambdaCDM) cosmology. Especially at high redshift, we see increased rates of galaxy cluster and galaxy merging in LSS relative to the field, which is useful for studying the hierarchical merging predicted by LambdaCDM. The largest identified bound structures, superclusters, have not yet virialized. Despite the wide range of dynamical states of their constituent galaxies, groups, and clusters, they are all still actively evolving, providing an ideal laboratory in which to study cluster and galaxy evolution. In this dissertation, I present original research on several aspects of LSS and LambdaCDM cosmology. Three separate studies are included, each one focusing on a different aspect. In the first study, we use X-ray and optical observations from nine galaxy clusters at high redshift, some embedded in larger structures and some isolated, to study their evolutionary states. We extract X-ray gas temperatures and luminosities as well as optical velocity dispersions. These cluster properties are compared using low-redshift scaling relations. In addition, we employ several tests of substructure, using velocity histograms, Dressler-Shectman tests, and centroiding offsets. We conclude that two clusters out of our sample are most likely unrelaxed, and find support for deviations from self-similarity in the redshift evolution of the Lx-T relation. Our numerous complementary tests of the evolutionary state of clusters suggest potential under-estimations of systematic error in studies employing only a single such test. In the second study, we use multi-band imaging and spectroscopy to study active galactic nuclei (AGN) in high-redshift LSS. The AGN were identified using X-ray imaging and matched to optical catalogs that contained spectroscopic redshifts to identify members of the structures. AGN host galaxies tended to be associated with the transitional `green valley' on a color-magnitude diagram. Spectral analysis of the AGN hosts showed that the average host galaxy had either on-going or recent star formation, and was younger than the average galaxy, across all LSS in our sample. We further subdivided our sample in two based on the average evolutionary state of the LSS. The AGN in the more evolved structures had lower X-ray luminosities and longer times since last starburst. These results provide some evidence for merger-based AGN triggering, although other mechanisms, and possibly more than one, could be responsible. In the third study, we probed LambdaCDM cosmology from a different angle. An important part of the model is the cosmological parameters that define our universe. As such, probes that can more accurately and precisely measure these parameters, such as H0 and the dark energy equation of state, w, can allow us to more closely inspect the model. Strongly-lensed quasars provide one such probe, and we sought to perform the first step in using them for cosmological inference, which is to measure the time delays between strongly lensed images. We performed radio monitoring campaigns on six strongly lensed quasars using the Very Large Array. Lightcurves were extracted for each lensed image and analyzed for intrinsic variability. Two lensed quasars showed strong time variations, but the variations were linear in time, preventing precise time delay measurements due to a degeneracy with the magnifications. These results suggest most of the systems should be targeted for followup monitoring, and we estimate that time delays can be measured for the most variable systems with precision of 0.5 to 3.5 days with two more seasons of monitoring. In a joint fit with previously studied systems, these measurements could tighten constraints on H 0 by up to ~1.4.

Mycobacterium tuberculosis Transmission in a Country with Low Tuberculosis Incidence: Role of Immigration and HIV Infection

PubMed Central

Gagneux, Sebastien; Helbling, Peter; Battegay, Manuel; Rieder, Hans L.; Pfyffer, Gaby E.; Zwahlen, Marcel; Furrer, Hansjakob; Siegrist, Hans H.; Fehr, Jan; Dolina, Marisa; Calmy, Alexandra; Stucki, David; Jaton, Katia; Janssens, Jean-Paul; Stalder, Jesica Mazza; Bodmer, Thomas; Ninet, Beatrice; Böttger, Erik C.; Egger, Matthias; Barth, J.; Battegay, M.; Bernasconi, E.; Böni, J.; Bucher, H. C.; Burton-Jeangros, A. Calmy; Cavassini, M.; Cellerai, C.; Egger, M.; Elzi, L.; Fehr, J.; Fellay, J.; Flepp, M.; Francioli, P.; Furrer, H.; Fux, C. A.; Gorgievski, M.; Günthard, H.; Haerry, D.; Hasse, B.; Hirschel, B.; Hirsch, H. H.; Hirschel, B.; Hoffmann, M.; Hösli, I.; Kahlert, C.; Kaiser, L.; Kaiser, O.; Kind, C.; Klimkait, T.; Kovari, H.; Ledergerber, B.; Lugano, A. P.; Martinetti, G.; Martinez de Tejada, B.; Metzner, K.; Müller, N.; Nadal, D.; Pantaleo, G.; Rauch, A.; Regenass, S.; Rickenbach, M.; Rudin, C.; Schmid, P.; Schultze, D.; Schöni-Affolter, F.; Schüpbach, J.; Speck, R.; Taffé, P.; Tarr, P.; Telenti, A.; Trkola, A.; Vernazza, P.; Weber, R.; Yerly, S.

2012-01-01

Immigrants from high-burden countries and HIV-coinfected individuals are risk groups for tuberculosis (TB) in countries with low TB incidence. Therefore, we studied their role in transmission of Mycobacterium tuberculosis in Switzerland. We included all TB patients from the Swiss HIV Cohort and a sample of patients from the national TB registry. We identified molecular clusters by spoligotyping and mycobacterial interspersed repetitive-unit–variable-number tandem-repeat (MIRU-VNTR) analysis and used weighted logistic regression adjusted for age and sex to identify risk factors for clustering, taking sampling proportions into account. In total, we analyzed 520 TB cases diagnosed between 2000 and 2008; 401 were foreign born, and 113 were HIV coinfected. The Euro-American M. tuberculosis lineage dominated throughout the study period (378 strains; 72.7%), with no evidence for another lineage, such as the Beijing genotype, emerging. We identified 35 molecular clusters with 90 patients, indicating recent transmission; 31 clusters involved foreign-born patients, and 15 involved HIV-infected patients. Birth origin was not associated with clustering (adjusted odds ratio [aOR], 1.58; 95% confidence interval [CI], 0.73 to 3.43; P = 0.25, comparing Swiss-born with foreign-born patients), but clustering was reduced in HIV-infected patients (aOR, 0.49; 95% CI, 0.26 to 0.93; P = 0.030). Cavitary disease, male sex, and younger age were all associated with molecular clustering. In conclusion, most TB patients in Switzerland were foreign born, but transmission of M. tuberculosis was not more common among immigrants and was reduced in HIV-infected patients followed up in the national HIV cohort study. Continued access to health services and clinical follow-up will be essential to control TB in this population. PMID:22116153

Scalable clustering algorithms for continuous environmental flow cytometry.

PubMed

Hyrkas, Jeremy; Clayton, Sophie; Ribalet, Francois; Halperin, Daniel; Armbrust, E Virginia; Howe, Bill

2016-02-01

Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. hyrkas@cs.washington.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Distillation of squeezing from non-Gaussian quantum states.

PubMed

Heersink, J; Marquardt, Ch; Dong, R; Filip, R; Lorenz, S; Leuchs, G; Andersen, U L

2006-06-30

We show that single copy distillation of squeezing from continuous variable non-Gaussian states is possible using linear optics and conditional homodyne detection. A specific non-Gaussian noise source, corresponding to a random linear displacement, is investigated experimentally. Conditioning the signal on a tap measurement, we observe probabilistic recovery of squeezing.

Characterization of collective Gaussian attacks and security of coherent-state quantum cryptography.

PubMed

Pirandola, Stefano; Braunstein, Samuel L; Lloyd, Seth

2008-11-14

We provide a simple description of the most general collective Gaussian attack in continuous-variable quantum cryptography. In the scenario of such general attacks, we analyze the asymptotic secret-key rates which are achievable with coherent states, joint measurements of the quadratures and one-way classical communication.

ENVIRONMENTAL VARIABLES CONTROLLING NITRIC OXIDE EMISSIONS FROM AGRICULTURAL SOILS IN THE SOUTHEAST UNITED STATES

EPA Science Inventory

Fluxes of nitric oxide (NO) were measured during the summer of 1994 (12 July to 11 August) in the Upper Coastal Plain of North Carolina in a continuing effort to characterize NO emissions from intensively managed agricultural soils in the southeastern United States. Previous work...

Impacts of storm chronology on the morphological changes of the Formby beach and dune system, UK

NASA Astrophysics Data System (ADS)

Dissanayake, P.; Brown, J.; Karunarathna, H.

2015-07-01

Impacts of storm chronology within a storm cluster on beach/dune erosion are investigated by applying the state-of-the-art numerical model XBeach to the Sefton coast, northwest England. Six temporal storm clusters of different storm chronologies were formulated using three storms observed during the 2013/2014 winter. The storm power values of these three events nearly halve from the first to second event and from the second to third event. Cross-shore profile evolution was simulated in response to the tide, surge and wave forcing during these storms. The model was first calibrated against the available post-storm survey profiles. Cumulative impacts of beach/dune erosion during each storm cluster were simulated by using the post-storm profile of an event as the pre-storm profile for each subsequent event. For the largest event the water levels caused noticeable retreat of the dune toe due to the high water elevation. For the other events the greatest evolution occurs over the bar formations (erosion) and within the corresponding troughs (deposition) of the upper-beach profile. The sequence of events impacting the size of this ridge-runnel feature is important as it consequently changes the resilience of the system to the most extreme event that causes dune retreat. The highest erosion during each single storm event was always observed when that storm initialised the storm cluster. The most severe storm always resulted in the most erosion during each cluster, no matter when it occurred within the chronology, although the erosion volume due to this storm was reduced when it was not the primary event. The greatest cumulative cluster erosion occurred with increasing storm severity; however, the variability in cumulative cluster impact over a beach/dune cross section due to storm chronology is minimal. Initial storm impact can act to enhance or reduce the system resilience to subsequent impact, but overall the cumulative impact is controlled by the magnitude and number of the storms. This model application provides inter-survey information about morphological response to repeated storm impact. This will inform local managers of the potential beach response and dune vulnerability to variable storm configurations.

Impacts of storm chronology on the morphological changes of the Formby beach and dune system, UK

NASA Astrophysics Data System (ADS)

Dissanayake, P.; Brown, J.; Karunarathna, H.

2015-04-01

Impacts of storm chronology within a storm cluster on beach/dune erosion are investigated by applying the state-of-the-art numerical model XBeach to the Sefton coast, northwest England. Six temporal storm clusters of different storm chronologies were formulated using three storms observed during the 2013/14 winter. The storm power values of these three events nearly halve from the first to second event and from the second to third event. Cross-shore profile evolution was simulated in response to the tide, surge and wave forcing during these storms. The model was first calibrated against the available post-storm survey profiles. Cumulative impacts of beach/dune erosion during each storm cluster were simulated by using the post-storm profile of an event as the pre-storm profile for each subsequent event. For the largest event the water levels caused noticeable retreat of the dune toe due to the high water elevation. For the other events the greatest evolution occurs over the bar formations (erosion) and within the corresponding troughs (deposition) of the upper beach profile. The sequence of events impacting the size of this ridge-runnel feature is important as it consequently changes the resilience of the system to the most extreme event that causes dune retreat. The highest erosion during each single storm event was always observed when that storm initialised the storm cluster. The most severe storm always resulted in the most erosion during each cluster, no matter when it occurred within the chronology, although the erosion volume due to this storm was reduced when it was not the primary event. The greatest cumulative cluster erosion occurred with increasing storm severity; however, the variability in cumulative cluster impact over a beach/dune cross-section due to storm chronology is minimal. Initial storm impact can act to enhance or reduce the system resilience to subsequent impact, but overall the cumulative impact is controlled by the magnitude and number of the storms. This model application provides inter-survey information about morphological response to repeated storm impact. This will inform local managers of the potential beach response and dune vulnerability to variable storm configurations.

Clusters of Healthy and Unhealthy Eating Behaviors Are Associated With Body Mass Index Among Adults.

PubMed

Heerman, William J; Jackson, Natalie; Hargreaves, Margaret; Mulvaney, Shelagh A; Schlundt, David; Wallston, Kenneth A; Rothman, Russell L

2017-05-01

To identify eating styles from 6 eating behaviors and test their association with body mass index (BMI) among adults. Cross-sectional analysis of self-report survey data. Twelve primary care and specialty clinics in 5 states. Of 11,776 adult patients who consented to participate, 9,977 completed survey questions. Frequency of eating healthy food, frequency of eating unhealthy food, breakfast frequency, frequency of snacking, overall diet quality, and problem eating behaviors. The primary dependent variable was BMI, calculated from self-reported height and weight data. k-Means cluster analysis of eating behaviors was used to determine eating styles. A categorical variable representing each eating style cluster was entered in a multivariate linear regression predicting BMI, controlling for covariates. Four eating styles were identified and defined by healthy vs unhealthy diet patterns and engagement in problem eating behaviors. Each group had significantly higher average BMI than the healthy eating style: healthy with problem eating behaviors (β = 1.9; P < .001), unhealthy (β = 2.5; P < .001), and unhealthy with problem eating behaviors (β = 5.1; P < .001). Future attempts to improve eating styles should address not only the consumption of healthy foods but also snacking behaviors and the emotional component of eating. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Mass loss

NASA Technical Reports Server (NTRS)

Goldberg, Leo

1987-01-01

Observational evidence for mass loss from cool stars is reviewed. Spectra line profiles are used for the derivation of mass-loss rates with the aid of the equation of continuity. This equation implies steady mass loss with spherical symmetry. Data from binary stars, Mira variables, and red giants in globular clusters are examined. Silicate emission is discussed as a useful indicator of mass loss in the middle infrared spectra. The use of thermal millimeter-wave radiation, Very Large Array (VLA) measurement of radio emission, and OH/IR masers are discussed as a tool for mass loss measurement. Evidence for nonsteady mass loss is also reviewed.

Digital Breast Tomosynthesis: Observer Performance of Clustered Microcalcification Detection on Breast Phantom Images Acquired with an Experimental System Using Variable Scan Angles, Angular Increments, and Number of Projection Views

PubMed Central

Goodsitt, Mitchell M.; Helvie, Mark A.; Zelakiewicz, Scott; Schmitz, Andrea; Noroozian, Mitra; Paramagul, Chintana; Roubidoux, Marilyn A.; Nees, Alexis V.; Neal, Colleen H.; Carson, Paul; Lu, Yao; Hadjiiski, Lubomir; Wei, Jun

2014-01-01

Purpose To investigate the dependence of microcalcification cluster detectability on tomographic scan angle, angular increment, and number of projection views acquired at digital breast tomosynthesis (DBTdigital breast tomosynthesis). Materials and Methods A prototype DBTdigital breast tomosynthesis system operated in step-and-shoot mode was used to image breast phantoms. Four 5-cm-thick phantoms embedded with 81 simulated microcalcification clusters of three speck sizes (subtle, medium, and obvious) were imaged by using a rhodium target and rhodium filter with 29 kV, 50 mAs, and seven acquisition protocols. Fixed angular increments were used in four protocols (denoted as scan angle, angular increment, and number of projection views, respectively: 16°, 1°, and 17; 24°, 3°, and nine; 30°, 3°, and 11; and 60°, 3°, and 21), and variable increments were used in three (40°, variable, and 13; 40°, variable, and 15; and 60°, variable, and 21). The reconstructed DBTdigital breast tomosynthesis images were interpreted by six radiologists who located the microcalcification clusters and rated their conspicuity. Results The mean sensitivity for detection of subtle clusters ranged from 80% (22.5 of 28) to 96% (26.8 of 28) for the seven DBTdigital breast tomosynthesis protocols; the highest sensitivity was achieved with the 16°, 1°, and 17 protocol (96%), but the difference was significant only for the 60°, 3°, and 21 protocol (80%, P < .002) and did not reach significance for the other five protocols (P = .01–.15). The mean sensitivity for detection of medium and obvious clusters ranged from 97% (28.2 of 29) to 100% (24 of 24), but the differences fell short of significance (P = .08 to >.99). The conspicuity of subtle and medium clusters with the 16°, 1°, and 17 protocol was rated higher than those with other protocols; the differences were significant for subtle clusters with the 24°, 3°, and nine protocol and for medium clusters with 24°, 3°, and nine; 30°, 3°, and 11; 60°, 3° and 21; and 60°, variable, and 21 protocols (P < .002). Conclusion With imaging that did not include x-ray source motion or patient motion during acquisition of the projection views, narrow-angle DBTdigital breast tomosynthesis provided higher sensitivity and conspicuity than wide-angle DBTdigital breast tomosynthesis for subtle microcalcification clusters. © RSNA, 2014 PMID:25007048

Noninvasive health condition monitoring device for workers at high altitudes conditions.

PubMed

Aqueveque, Pablo; Gutierrez, Cristopher; Saavedra, Francisco; Pino, Esteban J

2016-08-01

This work presents the design and implementation of a continuous monitoring device to control the health state of workers, for instance miners, at high altitudes. The extreme ambient conditions are harmful for peoples' health; therefore a continuous control of the workers' vital signs is necessary. The developed system includes physiological variables: electrocardiogram (ECG), respiratory activity and body temperature (BT), and ambient variables: ambient temperature (AT) and relative humidity (RH). The noninvasive sensors are incorporated in a t-shirt to deliver a functional device, and maximum comfort to the users. The device is able to continuously calculate heart rate (HR) and respiration rate (RR), and establish a wireless data transmission to a central monitoring station.

Security proof of continuous-variable quantum key distribution using three coherent states

NASA Astrophysics Data System (ADS)

Brádler, Kamil; Weedbrook, Christian

2018-02-01

We introduce a ternary quantum key distribution (QKD) protocol and asymptotic security proof based on three coherent states and homodyne detection. Previous work had considered the binary case of two coherent states and here we nontrivially extend this to three. Our motivation is to leverage the practical benefits of both discrete and continuous (Gaussian) encoding schemes creating a best-of-both-worlds approach; namely, the postprocessing of discrete encodings and the hardware benefits of continuous ones. We present a thorough and detailed security proof in the limit of infinite signal states which allows us to lower bound the secret key rate. We calculate this is in the context of collective eavesdropping attacks and reverse reconciliation postprocessing. Finally, we compare the ternary coherent state protocol to other well-known QKD schemes (and fundamental repeaterless limits) in terms of secret key rates and loss.

Investigación observacional sobre el papel de las estrellas binarias en la ecología de cúmulos estelares

NASA Astrophysics Data System (ADS)

González, J. F.; Levato, H.; Grosso, M.

We present preliminary results of a long-term project devoted to the observational study of the binary star population in open clusters and its connection with the dynamical and evolutionary properties of the clusters. We report the discovery of 17 double-lined spectroscopic binaries, 30 radial velocity variables and about 30 suspected variables. In the 17 clusters of our sample the binary frequency ranges between 20 and 40 %, and reaches typically 60 % if all suspected binaries are included. We study the spatial distribution of the binary stars with respect to the cluster center and we discuss the statistical correlation of the mass-ratio distribution with the cluster age.

Clustering performance comparison using K-means and expectation maximization algorithms.

PubMed

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

Mothers of young children cluster into 4 groups based on psychographic food decision influencers.

PubMed

Byrd-Bredbenner, Carol; Abbot, Jaclyn Maurer; Cussler, Ellen

2008-08-01

This study explored how mothers grouped into clusters according to multiple psychographic food decision influencers and how the clusters differed in nutrient intake and nutrient content of their household food supply. Mothers (n = 201) completed a survey assessing basic demographic characteristics, food shopping and meal preparation activities, self and spouse employment, exposure to formal food or nutrition education, education level and occupation, weight status, nutrition and food preparation knowledge and skill, family member health and nutrition status, food decision influencer constructs, and dietary intake. In addition, an in-home inventory of 100 participants' household food supplies was conducted. Four distinct clusters presented when 26 psychographic food choice influencers were evaluated. These clusters appear to be valid and robust classifications of mothers in that they discriminated well on the psychographic variables used to construct the clusters as well as numerous other variables not used in the cluster analysis. In addition, the clusters appear to transcend demographic variables that often segment audiences (eg, race, mother's age, socioeconomic status), thereby adding a new dimension to the way in which this audience can be characterized. Furthermore, psychographically defined clusters predicted dietary quality. This study demonstrates that mothers are not a homogenous group and need to have their unique characteristics taken into consideration when designing strategies to promote health. These results can help health practitioners better understand factors affecting food decisions and tailor interventions to better meet the needs of mothers.

Definition of variables required for comprehensive description of drug dosage and clinical pharmacokinetics.

PubMed

Medem, Anna V; Seidling, Hanna M; Eichler, Hans-Georg; Kaltschmidt, Jens; Metzner, Michael; Hubert, Carina M; Czock, David; Haefeli, Walter E

2017-05-01

Electronic clinical decision support systems (CDSS) require drug information that can be processed by computers. The goal of this project was to determine and evaluate a compilation of variables that comprehensively capture the information contained in the summary of product characteristic (SmPC) and unequivocally describe the drug, its dosage options, and clinical pharmacokinetics. An expert panel defined and structured a set of variables and drafted a guideline to extract and enter information on dosage and clinical pharmacokinetics from textual SmPCs as published by the European Medicines Agency (EMA). The set of variables was iteratively revised and evaluated by data extraction and variable allocation of roughly 7% of all centrally approved drugs. The information contained in the SmPC was allocated to three information clusters consisting of 260 variables. The cluster "drug characterization" specifies the nature of the drug. The cluster "dosage" provides information on approved drug dosages and defines corresponding specific conditions. The cluster "clinical pharmacokinetics" includes pharmacokinetic parameters of relevance for dosing in clinical practice. A first evaluation demonstrated that, despite the complexity of the current free text SmPCs, dosage and pharmacokinetic information can be reliably extracted from the SmPCs and comprehensively described by a limited set of variables. By proposing a compilation of variables well describing drug dosage and clinical pharmacokinetics, the project represents a step forward towards the development of a comprehensive database system serving as information source for sophisticated CDSS.

A fuzzy adaptive network approach to parameter estimation in cases where independent variables come from an exponential distribution

NASA Astrophysics Data System (ADS)

Dalkilic, Turkan Erbay; Apaydin, Aysen

2009-11-01

In a regression analysis, it is assumed that the observations come from a single class in a data cluster and the simple functional relationship between the dependent and independent variables can be expressed using the general model; Y=f(X)+[epsilon]. However; a data cluster may consist of a combination of observations that have different distributions that are derived from different clusters. When faced with issues of estimating a regression model for fuzzy inputs that have been derived from different distributions, this regression model has been termed the [`]switching regression model' and it is expressed with . Here li indicates the class number of each independent variable and p is indicative of the number of independent variables [J.R. Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Transaction on Systems, Man and Cybernetics 23 (3) (1993) 665-685; M. Michel, Fuzzy clustering and switching regression models using ambiguity and distance rejects, Fuzzy Sets and Systems 122 (2001) 363-399; E.Q. Richard, A new approach to estimating switching regressions, Journal of the American Statistical Association 67 (338) (1972) 306-310]. In this study, adaptive networks have been used to construct a model that has been formed by gathering obtained models. There are methods that suggest the class numbers of independent variables heuristically. Alternatively, in defining the optimal class number of independent variables, the use of suggested validity criterion for fuzzy clustering has been aimed. In the case that independent variables have an exponential distribution, an algorithm has been suggested for defining the unknown parameter of the switching regression model and for obtaining the estimated values after obtaining an optimal membership function, which is suitable for exponential distribution.

Exploring relationships between Dairy Herd Improvement monitors of performance and the Transition Cow Index in Wisconsin dairy herds.

PubMed

Schultz, K K; Bennett, T B; Nordlund, K V; Döpfer, D; Cook, N B

2016-09-01

Transition cow management has been tracked via the Transition Cow Index (TCI; AgSource Cooperative Services, Verona, WI) since 2006. Transition Cow Index was developed to measure the difference between actual and predicted milk yield at first test day to evaluate the relative success of the transition period program. This project aimed to assess TCI in relation to all commonly used Dairy Herd Improvement (DHI) metrics available through AgSource Cooperative Services. Regression analysis was used to isolate variables that were relevant to TCI, and then principal components analysis and network analysis were used to determine the relative strength and relatedness among variables. Finally, cluster analysis was used to segregate herds based on similarity of relevant variables. The DHI data were obtained from 2,131 Wisconsin dairy herds with test-day mean ≥30 cows, which were tested ≥10 times throughout the 2014 calendar year. The original list of 940 DHI variables was reduced through expert-driven selection and regression analysis to 23 variables. The K-means cluster analysis produced 5 distinct clusters. Descriptive statistics were calculated for the 23 variables per cluster grouping. Using principal components analysis, cluster analysis, and network analysis, 4 parameters were isolated as most relevant to TCI; these were energy-corrected milk, 3 measures of intramammary infection (dry cow cure rate, linear somatic cell count score in primiparous cows, and new infection rate), peak ratio, and days in milk at peak milk production. These variables together with cow and newborn calf survival measures form a group of metrics that can be used to assist in the evaluation of overall transition period performance. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

In situ study of emerging metallicity on ion-bombarded SrTiO3 surface

NASA Astrophysics Data System (ADS)

Gross, Heiko; Bansal, Namrata; Kim, Yong-Seung; Oh, Seongshik

2011-10-01

We report how argon bombardment induces metallic states on the surface of insulating SrTiO3 at different temperatures by combining in situ conductance measurements and model calculations. At cryogenic temperatures, ionic bombardment created a thin-but much thicker than the argon-penetration depth-steady-state oxygen-vacant layer, leading to a highly-concentric metallic state. Near room temperatures, however, significant thermal diffusion occurred and the metallic state continuously diffused into the bulk, leaving only low concentration of electron carriers on the surface. Analysis of the discrepancy between the experiments and the models also provided evidence for vacancy clustering, which seems to occur during any vacancy formation process and affects the observed conductance.

Development of an automated energy audit protocol for office buildings

NASA Astrophysics Data System (ADS)

Deb, Chirag

This study aims to enhance the building energy audit process, and bring about reduction in time and cost requirements in the conduction of a full physical audit. For this, a total of 5 Energy Service Companies in Singapore have collaborated and provided energy audit reports for 62 office buildings. Several statistical techniques are adopted to analyse these reports. These techniques comprise cluster analysis and development of prediction models to predict energy savings for buildings. The cluster analysis shows that there are 3 clusters of buildings experiencing different levels of energy savings. To understand the effect of building variables on the change in EUI, a robust iterative process for selecting the appropriate variables is developed. The results show that the 4 variables of GFA, non-air-conditioning energy consumption, average chiller plant efficiency and installed capacity of chillers should be taken for clustering. This analysis is extended to the development of prediction models using linear regression and artificial neural networks (ANN). An exhaustive variable selection algorithm is developed to select the input variables for the two energy saving prediction models. The results show that the ANN prediction model can predict the energy saving potential of a given building with an accuracy of +/-14.8%.

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

Static sampling of dynamic processes - a paradox?

NASA Astrophysics Data System (ADS)

Mälicke, Mirko; Neuper, Malte; Jackisch, Conrad; Hassler, Sibylle; Zehe, Erwin

2017-04-01

Environmental systems monitoring aims at its core at the detection of spatio-temporal patterns of processes and system states, which is a pre-requisite for understanding and explaining their baffling heterogeneity. Most observation networks rely on distributed point sampling of states and fluxes of interest, which is combined with proxy-variables from either remote sensing or near surface geophysics. The cardinal question on the appropriate experimental design of such a monitoring network has up to now been answered in many different ways. Suggested approaches range from sampling in a dense regular grid using for the so-called green machine, transects along typical catenas, clustering of several observations sensors in presumed functional units or HRUs, arrangements of those cluster along presumed lateral flow paths to last not least a nested, randomized stratified arrangement of sensors or samples. Common to all these approaches is that they provide a rather static spatial sampling, while state variables and their spatial covariance structure dynamically change in time. It is hence of key interest how much of our still incomplete understanding stems from inappropriate sampling and how much needs to be attributed to an inappropriate analysis of spatial data sets. We suggest that it is much more promising to analyze the spatial variability of processes, for instance changes in soil moisture values, than to investigate the spatial variability of soil moisture states themselves. This is because wetting of the soil, reflected in a soil moisture increase, is causes by a totally different meteorological driver - rainfall - than drying of the soil. We hence propose that the rising and the falling limbs of soil moisture time series belong essentially to different ensembles, as they are influenced by different drivers. Positive and negative temporal changes in soil moisture need, hence, to be analyzed separately. We test this idea using the CAOS data set as a benchmark. Specifically, we expect the covariance structure of the positive temporal changes of soil moisture to be dominated by the spatial structure of rain- and through-fall and saturated hydraulic conductivity. The covariance in temporarily decreasing soil moisture during radiation driven conditions is expect to be dominated by the spatial structure of retention properties and plant transpiration. An analysis of soil moisture changes has furthermore the advantage that those are free from systematic measurement errors.

Pre-main sequence variables in young cluster Stock 18

NASA Astrophysics Data System (ADS)

Sinha, Tirthendu; Sharma, Saurabh; Pandey, Rakesh; Pandey, Anil Kumar

2018-04-01

We have carried out multi-epoch deep I band photometry of the open cluster Stock 18 to search for variable stars in star forming regions. In the present study, we identified 65 periodic and 217 non-periodic variable stars. The periods of most of the periodic variables are between 2 hours to 15 days and their magnitude varies between 0.05 to 0.6 mag. We have derived spectral energy distributions for 48 probable pre-main sequence variables. Their average age and mass are 2.7 ± 0.3 Myrs and 2.7 ± 0.2 Mo, respectively.

Quantum state engineering by a coherent superposition of photon subtraction and addition

NASA Astrophysics Data System (ADS)

Lee, Su-Yong; Nha, Hyunchul

2011-10-01

We study a coherent superposition tâ+r↠of field annihilation and creation operator acting on continuous variable systems and propose its application for quantum state engineering. We propose an experimental scheme to implement this elementary coherent operation and discuss its usefulness to produce an arbitrary superposition of number states involving up to two photons.

Distinct Phenotypes of Cigarette Smokers Identified by Cluster Analysis of Patients with Severe Asthma.

PubMed

Konno, Satoshi; Taniguchi, Natsuko; Makita, Hironi; Nakamaru, Yuji; Shimizu, Kaoruko; Shijubo, Noriharu; Fuke, Satoshi; Takeyabu, Kimihiro; Oguri, Mitsuru; Kimura, Hirokazu; Maeda, Yukiko; Suzuki, Masaru; Nagai, Katsura; Ito, Yoichi M; Wenzel, Sally E; Nishimura, Masaharu

2015-12-01

Smoking may have multifactorial effects on asthma phenotypes, particularly in severe asthma. Cluster analysis has been applied to explore novel phenotypes, which are not based on any a priori hypotheses. To explore novel severe asthma phenotypes by cluster analysis when including cigarette smokers. We recruited a total of 127 subjects with severe asthma, including 59 current or ex-smokers, from our university hospital and its 29 affiliated hospitals/pulmonary clinics. Twelve clinical variables obtained during a 2-day hospital stay were used for cluster analysis. After clustering using clinical variables, the sputum levels of 14 molecules were measured to biologically characterize the clinical clusters. Five clinical clusters were identified, including two characterized by high pack-year exposure to cigarette smoking and low FEV1/FVC. There were marked differences between the two clusters of cigarette smokers. One had high levels of circulating eosinophils, high IgE levels, and a high sinus disease score. The other was characterized by low levels of the same parameters. Sputum analysis revealed increased levels of IL-5 in the former cluster and increased levels of IL-6 and osteopontin in the latter. The other three clusters were similar to those previously reported: young onset/atopic, nonsmoker/less eosinophilic, and female/obese. Key clinical variables were confirmed to be stable and consistent 1 year later. This study reveals two distinct phenotypes of severe asthma in current and former cigarette smokers with potentially different biological pathways contributing to fixed airflow limitation. Clinical trial registered with www.umin.ac.jp (000003254).

Person mobility in the design and analysis of cluster-randomized cohort prevention trials.

PubMed

Vuchinich, Sam; Flay, Brian R; Aber, Lawrence; Bickman, Leonard

2012-06-01

Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.

Extreme Quiescent Variability of the Transient Neutron Star Low-mass X-ray Binary EXO 1745-248 in Terzan 5

NASA Astrophysics Data System (ADS)

Sandoval, L. E. Rivera; Wijnands, R.; Degenaar, N.; Cavecchi, Y.; Heinke, C. O.; Cackett, E. M.; Homan, J.; Altamirano, D.; Bahramian, A.; Sivakoff, G. R.; Miller, J. M.; Parikh, A. S.

2018-06-01

EXO 1745-248 is a transient neutron-star low-mass X-ray binary that resides in the globular cluster Terzan 5. We studied the transient during its quiescent state using 18 Chandra observations of the cluster acquired between 2003 and 2016. We found an extremely variable source, with a luminosity variation in the 0.5-10 keV energy range of ˜3 orders of magnitude (between 3 × 1031 erg s-1 and 2 × 1034 erg s-1) on time scales from years down to only a few days. Using an absorbed power-law model to fit its quiescent spectra, we obtained a typical photon index of ˜1.4, indicating that the source is even harder than during outburst and much harder than typical quiescent neutron stars if their quiescent X-ray spectra are also described by a single power-law model. This indicates that EXO 1745-248 is very hard throughout the entire observed X-ray luminosity range. At the highest luminosity, the spectrum fits better when an additional (soft) component is added to the model. All these quiescent properties are likely related to strong variability in the low-level accretion rate in the system. However, its extreme variable behavior is strikingly different from the one observed for other neutron star transients that are thought to still accrete in quiescence. We compare our results to these systems. We also discuss similarities and differences between our target and the transitional millisecond pulsar IGR J18245-2452, which also has hard spectra and strong variability during quiescence.

Microscopic evidence of a strain-enhanced ferromagnetic state in LaCoO3 thin films

NASA Astrophysics Data System (ADS)

Park, S.; Ryan, P.; Karapetrova, E.; Kim, J. W.; Ma, J. X.; Shi, J.; Freeland, J. W.; Wu, Weida

2009-08-01

Strain-induced modification of magnetic properties of lightly hole doped epitaxial LaCoO3 thin films on different substrates were studied with variable temperature magnetic force microscopy (MFM). Real space observation at 10 K reveals the formation of the local magnetic clusters on a relaxed film grown on LaAlO3 (001). In contrast, a ferromagnetic ground state has been confirmed for tensile-strained film on SrTiO3 (001), indicating that strain is an important factor in creating the ferromagnetic state. Simultaneous atomic force microscopy and MFM measurements reveal nanoscale defect lines for the tensile-strained films, where the structural defects have a large impact on the local magnetic properties.

[Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses].

PubMed

Ning, P; Guo, Y F; Sun, T Y; Zhang, H S; Chai, D; Li, X M

2016-09-01

To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis. A population sample of adult patients in Donghuamen community, Dongcheng district and Qinghe community, Haidian district, Beijing from April 2012 to January 2015, who had wheeze within the last 12 months, underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, total serum IgE levels, blood eosinophil level and a peak flow diary. Nine variables were chosen as evaluating parameters, including pre-salbutamol forced expired volume in one second(FEV1)/forced vital capacity(FVC) ratio, pre-salbutamol FEV1, percentage of post-salbutamol change in FEV1, residual capacity, diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level, peak expiratory flow(PEF) variability, serum IgE level, cumulative tobacco cigarette consumption (pack-years) and respiratory symptoms (cough and expectoration). Subjects' different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified. (1) Four clusters were identified by hierarchical cluster analysis. Cluster 1 was chronic bronchitis in smokers with normal pulmonary function. Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease (COPD) patients with mild airflow limitation. Cluster 3 included COPD patients with heavy smoking, poor quality of life and severe airflow limitation. Cluster 4 recognized atopic patients with mild airflow limitation, elevated serum IgE and clinical features of asthma. Significant differences were revealed regarding pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, maximal mid-expiratory flow curve(MMEF)% pred, carbon monoxide diffusing capacity per liter of alveolar(DLCO)/(VA)% pred, residual volume(RV)% pred, total serum IgE level, smoking history (pack-years), St.George's respiratory questionnaire(SGRQ) score, acute exacerbation in the past one year, PEF variability and allergic dermatitis (P<0.05). (2) Four clusters were also identified by two-step cluster analysis as followings, cluster 1, COPD patients with moderate to severe airflow limitation; cluster 2, asthma and COPD patients with heavy smoking, airflow limitation and increased airways reversibility; cluster 3, patients having less smoking and normal pulmonary function with wheezing but no chronic cough; cluster 4, chronic bronchitis patients with normal pulmonary function and chronic cough. Significant differences were revealed regarding gender distribution, respiratory symptoms, pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, MMEF% pred, DLCO/VA% pred, RV% pred, PEF variability, total serum IgE level, cumulative tobacco cigarette consumption (pack-years), and SGRQ score (P<0.05). By different cluster analyses, distinct clinical phenotypes of chronic airway diseases are identified. Thus, individualized treatments may guide doctors to provide based on different phenotypes.

Diary Data Subjected to Cluster Analysis of Intake/Output/Void Habits with Resulting Clusters Compared by Continence Status, Age, Race

PubMed Central

Miller, Janis M; Guo, Ying; Rodseth, Sarah Becker

2011-01-01

Background Data that incorporate the full complexity of healthy beverage intake and voiding frequency do not exist; therefore, clinicians reviewing bladder habits or voiding diaries for continence care must rely on expert opinion recommendations. Objective To use data-driven cluster analyses to reduce complex voiding diary variables into discrete patterns or data cluster profiles, descriptively name the clusters, and perform validity testing. Method Participants were 352 community women who filled out a 3-day voiding diary. Six variables (void frequency during daytime hours, void frequency during nighttime hours, modal output, total output, total intake, and body mass index) were entered into cluster analyses. The clusters were analyzed for differences by continence status, age, race (Black women, n = 196 White women, n = 156), and for those who were incontinent, by leakage episode severity. Results Three clusters emerged, labeled descriptively as Conventional, Benchmark, and Superplus. The Conventional cluster (68% of the sample) demonstrated mean daily intake of 45 ±13 ounces; mean daily output of 37 ± 15 ounces, mean daily voids 5 ± 2 times, mean modal daytime output 10±0.5 ounces, and mean nighttime voids 1±1 times. The Superplus cluster (7% of the sample) showed double or triple these values across the 5 variables, and the Benchmark cluster (25%) showed values consistent with current popular recommendations on intake and output (e.g., meeting or exceeding the 8 × 8 fluid intake rule of thumb). The clusters differed significantly (p < .05) by age, race, amount of irritating beverages consumed, and incontinence status. Discussion Identification of three discrete clusters provides for a potential parsimonious but data-driven means of classifying individuals for additional epidemiological or clinical study. The clinical utility rests with potential for intervening to move an individual from a high risk to low risk cluster with regards to incontinence. PMID:21317828

Competition between surface chemisorption and cage formation in Fe12O12 clusters

NASA Astrophysics Data System (ADS)

Gutsev, G. L.; Weatherford, C. A.; Jena, P.; Johnson, E.; Ramachandran, B. R.

2013-01-01

The electronic and geometrical structures of the clusters composed of 12 iron and 12 oxygen atoms are obtained using all-electron density functional theory. It is found that the states with geometrical structures corresponding to oxygen chemisorbed on the ground-state Fe12 cluster surface (Fe12O12) are close in total energy to the states whose geometrical configurations are hollow cages (FeO)12. The lowest total energy state is the ferrimagnetic triplet state of Fe12O12. A ferrimagnetic nonet state of (FeO)12 is only marginally higher in total energy. The clusters are rich in nearly degenerate isomers. Oxygen adsorption dramatically quenches the spin of Fe12 clusters.

Cluster-enriched Yang-Baxter equation from SUSY gauge theories

NASA Astrophysics Data System (ADS)

Yamazaki, Masahito

2018-04-01

We propose a new generalization of the Yang-Baxter equation, where the R-matrix depends on cluster y-variables in addition to the spectral parameters. We point out that we can construct solutions to this new equation from the recently found correspondence between Yang-Baxter equations and supersymmetric gauge theories. The S^2 partition function of a certain 2d N=(2,2) quiver gauge theory gives an R-matrix, whereas its FI parameters can be identified with the cluster y-variables.

Phenotypes determined by cluster analysis in severe or difficult-to-treat asthma.

PubMed

Schatz, Michael; Hsu, Jin-Wen Y; Zeiger, Robert S; Chen, Wansu; Dorenbaum, Alejandro; Chipps, Bradley E; Haselkorn, Tmirah

2014-06-01

Asthma phenotyping can facilitate understanding of disease pathogenesis and potential targeted therapies. To further characterize the distinguishing features of phenotypic groups in difficult-to-treat asthma. Children ages 6-11 years (n = 518) and adolescents and adults ages ≥12 years (n = 3612) with severe or difficult-to-treat asthma from The Epidemiology and Natural History of Asthma: Outcomes and Treatment Regimens (TENOR) study were evaluated in this post hoc cluster analysis. Analyzed variables included sex, race, atopy, age of asthma onset, smoking (adolescents and adults), passive smoke exposure (children), obesity, and aspirin sensitivity. Cluster analysis used the hierarchical clustering algorithm with the Ward minimum variance method. The results were compared among clusters by χ(2) analysis; variables with significant (P < .05) differences among clusters were considered as distinguishing feature candidates. Associations among clusters and asthma-related health outcomes were assessed in multivariable analyses by adjusting for socioeconomic status, environmental exposures, and intensity of therapy. Five clusters were identified in each age stratum. Sex, atopic status, and nonwhite race were distinguishing variables in both strata; passive smoke exposure was distinguishing in children and aspirin sensitivity in adolescents and adults. Clusters were not related to outcomes in children, but 2 adult and adolescent clusters distinguished by nonwhite race and aspirin sensitivity manifested poorer quality of life (P < .0001), and the aspirin-sensitive cluster experienced more frequent asthma exacerbations (P < .0001). Distinct phenotypes appear to exist in patients with severe or difficult-to-treat asthma, which is related to outcomes in adolescents and adults but not in children. The study of the therapeutic implications of these phenotypes is warranted. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Understanding the rural population migration pattern of Uttarakhand using Geophysical, Geological and Socio-Economical BigData

NASA Astrophysics Data System (ADS)

Chattopadhyay, Kausik; Chattopadhyay, Pallavi

2017-04-01

Uttarakhand, a Himalayan state of India is facing a worst scenario of rural population migration for the past few decades from hill regions to the planes. While urbanization is believed to be one of the major factors for migration, how geo scientific parameters can impact the population to redraw the demographies of the hills is studied in this research. An attempt is made using density based clustering and Apriori association rule mining on 45 derived variables with a time series of 30 years to understand the rural population migration pattern. Both zone identification and origin-destination pair extraction are formulated as spatial-temporal point clustering problem and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is applied to solve them. Specifically the population migration is formulated as a 4D point clustering problem and the relative distance between two origin - destination pair with a preference factor is used to fine tune the cluster length. In Apriori, threshold values for confidence and J-measure are kept same as for rule extraction. Rules with maximum confidence level and J-measure are obtained for an antecedent window of 18 months, consequent window of 4 months and time lag of 2 months. From the rules extracted, it can be demonstrated that almost all the geoscience indices are occurring as antecedents for migration episodes. The result demonstrates that the three districts that have registered the highest migration rates are also the districts that have witnessed maximum depletion in water sources. Even though some districts have higher number of landslide incidents, their out migration is less compared to other hill districts. However districts experiencing higher number of earthquakes are experiencing higher out migration. Upper hill region with higher precipitation experience higher migration compared to their lower hill counterpart. However this is not true when compared to the counter parts in the plane regions. Even though temperature fluctuation results in seasonal out migration, it does not have any long term impact. Resource and logistical constraints limit the frequency and extent of observations, necessitating the development of a systematic computational framework that objectively represents environmental variability at the desired spatial scale and such comprehensive big data model can be instrumental in arresting the rural migration which has been posing major threat to the livelihood of this Himalayan state.