Impaired long-term memory retention and working memory in sdy mutant mice with a deletion in Dtnbp1, a susceptibility gene for schizophrenia.

PubMed

Takao, Keizo; Toyama, Keiko; Nakanishi, Kazuo; Hattori, Satoko; Takamura, Hironori; Takeda, Masatoshi; Miyakawa, Tsuyoshi; Hashimoto, Ryota

2008-10-22

Schizophrenia is a complex genetic disorder caused by multiple genetic and environmental factors. The dystrobrevin-binding protein 1 (DTNBP1: dysbindin-1) gene is a major susceptibility gene for schizophrenia. Genetic variations in DTNBP1 are associated with cognitive functions, general cognitive ability and memory function, and clinical features of patients with schizophrenia including negative symptoms and cognitive decline. Since reduced expression of dysbindin-1 has been observed in postmortem brains of patients with schizophrenia, the sandy (sdy) mouse, which has a deletion in the Dtnbp1 gene and expresses no dysbindin-1 protein, could be an animal model of schizophrenia. To address this issue, we have carried out a comprehensive behavioral analysis of the sdy mouse in this study. In a rotarod test, sdy mice did not exhibit motor learning whilst the wild type mice did. In a Barnes circular maze test both sdy mice and wild type mice learned to selectively locate the escape hole during the course of the training period and in the probe trial conducted 24 hours after last training. However, sdy mice did not locate the correct hole in the retention probe tests 7 days after the last training trial, whereas wild type mice did, indicating impaired long-term memory retention. A T-maze forced alternation task, a task of working memory, revealed no effect of training in sdy mice despite the obvious effect of training in wild type mice, suggesting a working memory deficit. Sdy mouse showed impaired long-term memory retention and working memory. Since genetic variation in DTNBP1 is associated with both schizophrenia and memory function, and memory function is compromised in patients with schizophrenia, the sdy mouse may represent a useful animal model to investigate the mechanisms of memory dysfunction in the disorder.

Impaired long-term memory retention and working memory in sdy mutant mice with a deletion in Dtnbp1, a susceptibility gene for schizophrenia

PubMed Central

Takao, Keizo; Toyama, Keiko; Nakanishi, Kazuo; Hattori, Satoko; Takamura, Hironori; Takeda, Masatoshi; Miyakawa, Tsuyoshi; Hashimoto, Ryota

2008-01-01

Background Schizophrenia is a complex genetic disorder caused by multiple genetic and environmental factors. The dystrobrevin-binding protein 1 (DTNBP1: dysbindin-1) gene is a major susceptibility gene for schizophrenia. Genetic variations in DTNBP1 are associated with cognitive functions, general cognitive ability and memory function, and clinical features of patients with schizophrenia including negative symptoms and cognitive decline. Since reduced expression of dysbindin-1 has been observed in postmortem brains of patients with schizophrenia, the sandy (sdy) mouse, which has a deletion in the Dtnbp1 gene and expresses no dysbindin-1 protein, could be an animal model of schizophrenia. To address this issue, we have carried out a comprehensive behavioral analysis of the sdy mouse in this study. Results In a rotarod test, sdy mice did not exhibit motor learning whilst the wild type mice did. In a Barnes circular maze test both sdy mice and wild type mice learned to selectively locate the escape hole during the course of the training period and in the probe trial conducted 24 hours after last training. However, sdy mice did not locate the correct hole in the retention probe tests 7 days after the last training trial, whereas wild type mice did, indicating impaired long-term memory retention. A T-maze forced alternation task, a task of working memory, revealed no effect of training in sdy mice despite the obvious effect of training in wild type mice, suggesting a working memory deficit. Conclusion Sdy mouse showed impaired long-term memory retention and working memory. Since genetic variation in DTNBP1 is associated with both schizophrenia and memory function, and memory function is compromised in patients with schizophrenia, the sdy mouse may represent a useful animal model to investigate the mechanisms of memory dysfunction in the disorder. PMID:18945333

Disseminating sexually transmitted infections diagnostics information: the SDI web publication review series.

PubMed

Kuypers, J; Tam, M R; Holmes, K K; Peeling, R W

2006-12-01

The World Health Organization Sexually Transmitted Diseases Diagnostics Initiative (SDI) website publication review seeks to provide health care providers in all geographic and economic settings with timely, critical, and concise information concerning new developments in laboratory and field diagnosis of sexually transmitted infections (STI). Since 2003, the website (www.who.int/std_diagnostics/literature_reviews) has disseminated information in the form of annotated abstracts and commentaries on articles covering studies of STI laboratory-based and rapid assays that are commercially available or under development. Articles identified through searches of PubMed, specific journals, and by referrals from Editorial Board members are selected for inclusion if they meet pre-specified criteria. The objectives, methods, results, and conclusions for each article are summarised and board members are invited to prepare commentaries addressing study design and applicability of findings to end users. Currently, 91 STI diagnostics experts from 17 countries on six continents serve on the Editorial Board. Twelve quarterly issues have been posted that include summaries of 214 original and 17 review articles published from January 2002 through March 2005, with expert commentaries on 153 articles. Interest in the site has increased every year. In 2005, over 36 700 unique visitors from more than 100 countries viewed over 75,000 pages of information. The SDI Publication Review series has the potential to contribute to SDI's goal of improving care for patients with STI by increasing knowledge and awareness of STI diagnostics. Given the proliferation of internet-based STI testing services, this website may be broadened to meet the needs of a wider range of users.

SDI-based business processes: A territorial analysis web information system in Spain

NASA Astrophysics Data System (ADS)

Béjar, Rubén; Latre, Miguel Á.; Lopez-Pellicer, Francisco J.; Nogueras-Iso, Javier; Zarazaga-Soria, F. J.; Muro-Medrano, Pedro R.

2012-09-01

Spatial Data Infrastructures (SDIs) provide access to geospatial data and operations through interoperable Web services. These data and operations can be chained to set up specialized geospatial business processes, and these processes can give support to different applications. End users can benefit from these applications, while experts can integrate the Web services in their own business processes and developments. This paper presents an SDI-based territorial analysis Web information system for Spain, which gives access to land cover, topography and elevation data, as well as to a number of interoperable geospatial operations by means of a Web Processing Service (WPS). Several examples illustrate how different territorial analysis business processes are supported. The system has been established by the Spanish National SDI (Infraestructura de Datos Espaciales de España, IDEE) both as an experimental platform for geoscientists and geoinformation system developers, and as a mechanism to contribute to the Spanish citizens knowledge about their territory.

SDI increases water use efficiency of grain crops in the Southern High Plains

USDA-ARS?s Scientific Manuscript database

In the semi-arid Southern High Plains, nearly all irrigation water is derived from the declining High Plains (Ogallala) aquifer. As well capacities likewise decline, one tactic for continued irrigation is to install subsurface drip irrigation (SDI) systems with zones sized to accommodate the limited...

Evaluation of the impact of quorum sensing transcriptional regulator SdiA on long-term persistence and fecal shedding of Escherichia coli O157:H7 in weaned calves.

PubMed

Sharma, V K; Bearson, S M D

2013-04-01

Escherichia coli O157:H7 (O157) colonization of bovine intestine is mediated through the locus of enterocyte effacement (LEE)-encoded type III secretion system and secreted virulence proteins that promote colonization of the recto-anal junction (RAJ) of the large intestine of cattle. The quorum sensing transcriptional regulator SdiA, a homolog of LuxR, has been shown in vitro to repress LEE strongly when overexpressed from a multi-copy recombinant plasmid or when its activity is enhanced by the binding of N-acyl-L-homoserine lactones (AHLs), the quorum sensing signals that are detected by SdiA. Since LEE has been shown to be essential for colonization and persistence of O157 in bovine intestine, we examined whether a mutation in sdiA, which normally represses LEE in vitro, would also exert negative effect on colonization and long-term persistence of O157 in weaned calves. Ten-week old weaned calves (n = 4/group) were inoculated orally with 10(10) cfu of either the wild-type or sdiA mutant strain. Initial fecal shedding of the sdiA mutant and the wild-type strain were similar in magnitude and declined during the first 2 weeks post-inoculation. The sdiA mutant was detected in feces of only one of the four calves at low levels (≥10(2) cfu/g feces) from days 19 - 27 post-inoculation, whereas, the fecal shedding of the wild-type strain persisted at approximately 4-logs in all four calves from days 19 - 27. We also confirmed that SdiA represses ler, which encodes a positive transcriptional regulator of LEE, in response to AHLs, and reduces adherence of O157 to HEp-2 cells. In conclusion, this study demonstrates that although in vitro the sdiA gene represses LEE and LEE-mediated adherence to cultured cells, the presence of sdiA is necessary for colonization of bovine large intestine that in turn promotes persistent fecal shedding of O157 by these animals. Published by Elsevier Ltd.

Social Development in Hong Kong: Development Issues Identified by Social Development Index (SDI)

ERIC Educational Resources Information Center

Chua, Hoi-wai; Wong, Anthony K. W.; Shek, Daniel T. L.

2010-01-01

Surviving the aftermaths of the Asian Financial Crisis and SARS in 2003, Hong Kong's economy has re-gained its momentum and its economic growth has been quite remarkable too in recent few years. Nevertheless, as reflected by the Social Development Index (SDI), economic growth in Hong Kong does not seem to have benefited the people of the city at…

Statistical inference for noisy nonlinear ecological dynamic systems.

PubMed

Wood, Simon N

2010-08-26

Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.

SERVIR's Contributions and Benefits to Belize thru Spatial Data Infrastructure (SDI) Development

NASA Technical Reports Server (NTRS)

Irwin, Daniel E.

2006-01-01

Dan Irwin, the SERVIR Project Manager is being honored with the privilege of delivering the opening remarks at Belize s second celebration of GIS Day, a weeklong event to be held at the University of Belize's campus in the nation s capital, Belmopan. The request has been extended by the GIS Day Planning Committee which operates under the auspices of Belize s Ministry of Natural Resources & the Environment, which is the focal ministry for SERVIR. In the 20-30 min. allotted for the opening remarks, the SERVIR Project Manager will expound on how SERVIR, operating under the auspices of NASA s Ecological Forecasting Program, contributes to spatial data infrastructure (SDI) development in Belize. NASA s contributions to the region - particularly work under the Mesoamerican Biological Corridor - will be highlighted. Continuing, the remarks will discuss SERVIR s role in Belize s steadily expanding SDI, particularly in the context of delivering integrated decision support products via web-based infrastructure. The remarks will close with a call to the parties assembled to work together in the application of Earth Observation Systems technologies for the benefit of Belizean society as a whole. NASA s strong presence in Belize s GIS Day celebrations will be highlighted as sustained goodwill of the American people - in partial fulfillment of goals set forth under the Global Earth Observation System of Systems (GEOSS).

An open-source wireless sensor stack: from Arduino to SDI-12 to Water One Flow

NASA Astrophysics Data System (ADS)

Hicks, S.; Damiano, S. G.; Smith, K. M.; Olexy, J.; Horsburgh, J. S.; Mayorga, E.; Aufdenkampe, A. K.

2013-12-01

Implementing a large-scale streaming environmental sensor network has previously been limited by the high cost of the datalogging and data communication infrastructure. The Christina River Basin Critical Zone Observatory (CRB-CZO) is overcoming the obstacles to large near-real-time data collection networks by using Arduino, an open source electronics platform, in combination with XBee ZigBee wireless radio modules. These extremely low-cost and easy-to-use open source electronics are at the heart of the new DIY movement and have provided solutions to countless projects by over half a million users worldwide. However, their use in environmental sensing is in its infancy. At present a primary limitation to widespread deployment of open-source electronics for environmental sensing is the lack of a simple, open-source software stack to manage streaming data from heterogeneous sensor networks. Here we present a functioning prototype software stack that receives sensor data over a self-meshing ZigBee wireless network from over a hundred sensors, stores the data locally and serves it on demand as a CUAHSI Water One Flow (WOF) web service. We highlight a few new, innovative components, including: (1) a versatile open data logger design based the Arduino electronics platform and ZigBee radios; (2) a software library implementing SDI-12 communication protocol between any Arduino platform and SDI12-enabled sensors without the need for additional hardware (https://github.com/StroudCenter/Arduino-SDI-12); and (3) 'midStream', a light-weight set of Python code that receives streaming sensor data, appends it with metadata on the fly by querying a relational database structured on an early version of the Observations Data Model version 2.0 (ODM2), and uses the WOFpy library to serve the data as WaterML via SOAP and REST web services.

Features of statistical dynamics in a finite system

NASA Astrophysics Data System (ADS)

Yan, Shiwei; Sakata, Fumihiko; Zhuo, Yizhong

2002-03-01

We study features of statistical dynamics in a finite Hamilton system composed of a relevant one degree of freedom coupled to an irrelevant multidegree of freedom system through a weak interaction. Special attention is paid on how the statistical dynamics changes depending on the number of degrees of freedom in the irrelevant system. It is found that the macrolevel statistical aspects are strongly related to an appearance of the microlevel chaotic motion, and a dissipation of the relevant motion is realized passing through three distinct stages: dephasing, statistical relaxation, and equilibrium regimes. It is clarified that the dynamical description and the conventional transport approach provide us with almost the same macrolevel and microlevel mechanisms only for the system with a very large number of irrelevant degrees of freedom. It is also shown that the statistical relaxation in the finite system is an anomalous diffusion and the fluctuation effects have a finite correlation time.

Features of statistical dynamics in a finite system.

PubMed

Yan, Shiwei; Sakata, Fumihiko; Zhuo, Yizhong

2002-03-01

We study features of statistical dynamics in a finite Hamilton system composed of a relevant one degree of freedom coupled to an irrelevant multidegree of freedom system through a weak interaction. Special attention is paid on how the statistical dynamics changes depending on the number of degrees of freedom in the irrelevant system. It is found that the macrolevel statistical aspects are strongly related to an appearance of the microlevel chaotic motion, and a dissipation of the relevant motion is realized passing through three distinct stages: dephasing, statistical relaxation, and equilibrium regimes. It is clarified that the dynamical description and the conventional transport approach provide us with almost the same macrolevel and microlevel mechanisms only for the system with a very large number of irrelevant degrees of freedom. It is also shown that the statistical relaxation in the finite system is an anomalous diffusion and the fluctuation effects have a finite correlation time.

A sulphur deficiency-induced gene, sdi1, involved in the utilization of stored sulphate pools under sulphur-limiting conditions has potential as a diagnostic indicator of sulphur nutritional status.

PubMed

Howarth, Jonathan R; Parmar, Saroj; Barraclough, Peter B; Hawkesford, Malcolm J

2009-02-01

A sulphate deficiency-induced gene, sdi1, has been identified by cDNA-amplified fragment length polymorphism (AFLP) analysis utilizing field-grown, nutrient-deficient wheat (Triticum aestivum var. Hereward). The expression of sdi1 was specifically induced in leaf and root tissues in response to sulphate deficiency, but was not induced by nitrogen, phosphorus, potassium or magnesium deficiency. Expression was also shown to increase in plant tissues as the external sulphate concentration in hydroponically grown plants was reduced from 1.0 to 0.0 mm. On this basis, sdi1 gene expression has potential as a sensitive indicator of sulphur nutritional status in wheat. Genome-walking techniques were used to clone the 2.7-kb region upstream of sdi1 from genomic DNA, revealing several cis-element motifs previously identified as being associated with sulphur responses in plants. The Arabidopsis thaliana gene most highly homologous to sdi1 is At5g48850, which was also demonstrated to be induced by sulphur deficiency, an observation confirmed by the analysis of microarray data available in the public domain. The expression of Atsdi1 was induced more rapidly than previously characterized sulphur-responsive genes in the period immediately following the transfer of plants to sulphur-deficient medium. Atsdi1 T-DNA 'knockout' mutants were shown to maintain higher tissue sulphate concentrations than wild-type plants under sulphur-limiting conditions, indicating a role in the utilization of stored sulphate under sulphur-deficient conditions. The structural features of the sdi1 gene and its application in the genetic determination of the sulphur nutritional status of wheat crops are discussed.

Reagan's Political Imagery on Arms Control and SDI: Content Analysis in Political Science Using Washington PressText.

ERIC Educational Resources Information Center

Garson, G. David

While President Reagan and Secretary of State Shultz shared the same policy goals, content analysis shows substantial differences with regard to arms control and the Strategic Defense Initiative (SDI), not only between Reagan and Shultz, but also among Reagan's roles as a political leader, as chief executive, and as statesman to the world…

The scientists' opposition to SDI: How political views affect technical analysis

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

Tait, G.E.

1989-01-01

This study examines the scientists' opposition to President Reagan's Strategic Defense Initiative (1983-1989) with a focus on the relationship between the scientists' political and strategic opposition to ballistic missile defenses (BMD) and their technical doubts about BMD technologies. The study begins with a review of the scientists' increased influence in United State's national security decision making because of the development of atomic weapons. The study then examines the scientists' role in developing and promoting a theory of arms control based upon mutual societal vulnerability. Because of this theory, a large segment of the American scientific community came to believe thatmore » the development of ballistic missile defenses would destabilize the strategic balance and therefore took the lead in arguing against BMD deployments. These background chapters conclude with an analysis of the scientists' involvement in the political campaign to stop the proposed Sentinel and Safeguard Anti-Ballistic Missile defense. The study then turns to the contemporary scientific opposition to BMD deployments and the SDI research program. After examining the polls and petitions that identify the scientists opposed to SDI, the study analyzes the tactics that three scientists use in their political effort to prevent BMD deployments. Next, an examination of the political and strategic assumptions behind the scientists' opposition to BMD reveals that a belief in the arms control process and deterrence by punishment, especially Assured Destruction deterrence, with a fear of an action-reaction arms race inspires much of the contemporary opposition to BMD. Finally, the scientists' technical doubts about BMD technologies are analyzed through the prism of peer critique. These critiques show that the scientists opposed to BMD deployments us pessimistic and unrealistic assumptions to skew their technical analysis of BMD technologies.« less

Teaching the principles of statistical dynamics

PubMed Central

Ghosh, Kingshuk; Dill, Ken A.; Inamdar, Mandar M.; Seitaridou, Effrosyni; Phillips, Rob

2012-01-01

We describe a simple framework for teaching the principles that underlie the dynamical laws of transport: Fick’s law of diffusion, Fourier’s law of heat flow, the Newtonian viscosity law, and the mass-action laws of chemical kinetics. In analogy with the way that the maximization of entropy over microstates leads to the Boltzmann distribution and predictions about equilibria, maximizing a quantity that E. T. Jaynes called “caliber” over all the possible microtrajectories leads to these dynamical laws. The principle of maximum caliber also leads to dynamical distribution functions that characterize the relative probabilities of different microtrajectories. A great source of recent interest in statistical dynamics has resulted from a new generation of single-particle and single-molecule experiments that make it possible to observe dynamics one trajectory at a time. PMID:23585693

Teaching the principles of statistical dynamics.

PubMed

Ghosh, Kingshuk; Dill, Ken A; Inamdar, Mandar M; Seitaridou, Effrosyni; Phillips, Rob

2006-02-01

We describe a simple framework for teaching the principles that underlie the dynamical laws of transport: Fick's law of diffusion, Fourier's law of heat flow, the Newtonian viscosity law, and the mass-action laws of chemical kinetics. In analogy with the way that the maximization of entropy over microstates leads to the Boltzmann distribution and predictions about equilibria, maximizing a quantity that E. T. Jaynes called "caliber" over all the possible microtrajectories leads to these dynamical laws. The principle of maximum caliber also leads to dynamical distribution functions that characterize the relative probabilities of different microtrajectories. A great source of recent interest in statistical dynamics has resulted from a new generation of single-particle and single-molecule experiments that make it possible to observe dynamics one trajectory at a time.

Loss of p21{sup Sdi1} expression in senescent cells after DNA damage accompanied with increase of miR-93 expression and reduced p53 interaction with p21{sup Sdi1} gene promoter

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

Choi, Ok Ran; Lim, In Kyoung, E-mail: iklim@ajou.ac.kr

2011-04-08

Highlights: {yields} Reduced p21 expression in senescent cells treated with DNA damaging agents. {yields} Increase of [{sup 3}H]thymidine and BrdU incorporations in DNA damaged-senescent cells. {yields} Upregulation of miR-93 expression in senescent cells in response to DSB. {yields} Failure of p53 binding to p21 promoter in senescent cells in response to DSB. {yields} Molecular mechanism of increased cancer development in aged than young individuals. -- Abstract: To answer what is a critical event for higher incidence of tumor development in old than young individuals, primary culture of human diploid fibroblasts were employed and DNA damage was induced by doxorubicin ormore » X-ray irradiation. Response to the damage was different between young and old cells; loss of p21{sup sdi1} expression in spite of p53{sup S15} activation in old cells along with [{sup 3}H]thymidine and BrdU incorporation, but not in young cells. The phenomenon was confirmed by other tissue fibroblasts obtained from different donor ages. Induction of miR-93 expression and reduced p53 binding to p21 gene promoter account for loss of p21{sup sdi1} expression in senescent cells after DNA damage, suggesting a mechanism of in vivo carcinogenesis in aged tissue without repair arrest.« less

Statistical errors in molecular dynamics averages

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

Schiferl, S.K.; Wallace, D.C.

1985-11-15

A molecular dynamics calculation produces a time-dependent fluctuating signal whose average is a thermodynamic quantity of interest. The average of the kinetic energy, for example, is proportional to the temperature. A procedure is described for determining when the molecular dynamics system is in equilibrium with respect to a given variable, according to the condition that the mean and the bandwidth of the signal should be sensibly constant in time. Confidence limits for the mean are obtained from an analysis of a finite length of the equilibrium signal. The role of serial correlation in this analysis is discussed. The occurence ofmore » unstable behavior in molecular dynamics data is noted, and a statistical test for a level shift is described.« less

ON THE DYNAMICAL DERIVATION OF EQUILIBRIUM STATISTICAL MECHANICS

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

Prigogine, I.; Balescu, R.; Henin, F.

1960-12-01

Work on nonequilibrium statistical mechanics, which allows an extension of the kinetic proof to all results of equilibrium statistical mechanics involving a finite number of degrees of freedom, is summarized. As an introduction to the general N-body problem, the scattering theory in classical mechanics is considered. The general N-body problem is considered for the case of classical mechanics, quantum mechanics with Boltzmann statistics, and quantum mechanics including quantum statistics. Six basic diagrams, which describe the elementary processes of the dynamics of correlations, were obtained. (M.C.G.)

Effective control of complex turbulent dynamical systems through statistical functionals.

PubMed

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

Statistical-Dynamical Seasonal Forecasts of Central-Southwest Asian Winter Precipitation.

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Goddard, Lisa; Barnston, Anthony G.

2005-06-01

Interannual precipitation variability in central-southwest (CSW) Asia has been associated with East Asian jet stream variability and western Pacific tropical convection. However, atmospheric general circulation models (AGCMs) forced by observed sea surface temperature (SST) poorly simulate the region's interannual precipitation variability. The statistical-dynamical approach uses statistical methods to correct systematic deficiencies in the response of AGCMs to SST forcing. Statistical correction methods linking model-simulated Indo-west Pacific precipitation and observed CSW Asia precipitation result in modest, but statistically significant, cross-validated simulation skill in the northeast part of the domain for the period from 1951 to 1998. The statistical-dynamical method is also applied to recent (winter 1998/99 to 2002/03) multimodel, two-tier December-March precipitation forecasts initiated in October. This period includes 4 yr (winter of 1998/99 to 2001/02) of severe drought. Tercile probability forecasts are produced using ensemble-mean forecasts and forecast error estimates. The statistical-dynamical forecasts show enhanced probability of below-normal precipitation for the four drought years and capture the return to normal conditions in part of the region during the winter of 2002/03.May Kabul be without gold, but not without snow.—Traditional Afghan proverb

SELECTIVE DISSEMINATION OF INFORMATION (SDI). VOLUME II, IMPLEMENTATION MANUAL. FINAL REPORT. ARMY TECHNICAL LIBRARY IMPROVEMENT STUDIES (ATLIS), REPORT NO. 16.

ERIC Educational Resources Information Center

BIVONA, WILLIAM A.

A SET OF GUIDELINES FOR IMPLEMENTING AND OPERATING A REPLICA OF A PROTOTYPE SELECTIVE DISSEMINATION OF INFORMATION (SDI) SYSTEM TESTED AT U.S. ARMY NATICK LABORATORIES, AND REPORTED IN LI 000 273, IS GIVEN IN THIS MANUAL. INFORMATION IS SUPPLIED WHICH IS USEFUL IN THE INITIAL STAGES OF IMPLEMENTATION. THE APPLICATION OF SPECIFIC CRITERIA FOR…

The stock-flow model of spatial data infrastructure development refined by fuzzy logic.

PubMed

Abdolmajidi, Ehsan; Harrie, Lars; Mansourian, Ali

2016-01-01

The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate linguistic variables and their joint effects in an SDI-development model more effectively, we suggest employing fuzzy logic. Not all fuzzy models are able to model the dynamic behavior of SDIs properly. Therefore, this paper aims to investigate different fuzzy models and their suitability for modeling SDIs. To that end, two inference and two defuzzification methods were used for the fuzzification of the joint effect of two variables in an existing SDI model. The results show that the Average-Average inference and Center of Area defuzzification can better model the dynamics of SDI development.

Learning predictive statistics from temporal sequences: Dynamics and strategies.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-10-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

PubMed

Sapsis, Themistoklis P; Majda, Andrew J

2013-08-20

A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

Thrust and parry of the SIOP (single integrated operational plan) and sdi (strategic defense initiative). Research report

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

Zank, G.D.

1989-05-01

The relationship between strategic offensive capabilities (reflected in the SIOP) and emerging strategic defensive capabilities (reflected by SDI) is not being adequately addressed. A summary of the existing nuclear war planning process is provided, and an analagous defensive process is postulated. Parallels and differences between the two processes are discussed. Potential areas for information exchange and cooperation are identified to enhance deterrence and improve war fighting potential. Operational, technical and political issues requiring resolution are raised and recommendations to resolve these issues are made.

Architecture of a spatial data service system for statistical analysis and visualization of regional climate changes

NASA Astrophysics Data System (ADS)

Titov, A. G.; Okladnikov, I. G.; Gordov, E. P.

2017-11-01

The use of large geospatial datasets in climate change studies requires the development of a set of Spatial Data Infrastructure (SDI) elements, including geoprocessing and cartographical visualization web services. This paper presents the architecture of a geospatial OGC web service system as an integral part of a virtual research environment (VRE) general architecture for statistical processing and visualization of meteorological and climatic data. The architecture is a set of interconnected standalone SDI nodes with corresponding data storage systems. Each node runs a specialized software, such as a geoportal, cartographical web services (WMS/WFS), a metadata catalog, and a MySQL database of technical metadata describing geospatial datasets available for the node. It also contains geospatial data processing services (WPS) based on a modular computing backend realizing statistical processing functionality and, thus, providing analysis of large datasets with the results of visualization and export into files of standard formats (XML, binary, etc.). Some cartographical web services have been developed in a system’s prototype to provide capabilities to work with raster and vector geospatial data based on OGC web services. The distributed architecture presented allows easy addition of new nodes, computing and data storage systems, and provides a solid computational infrastructure for regional climate change studies based on modern Web and GIS technologies.

Seasonal drought predictability in Portugal using statistical-dynamical techniques

NASA Astrophysics Data System (ADS)

Ribeiro, A. F. S.; Pires, C. A. L.

2016-08-01

Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical-dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors integrating recent past information prior to the forecast launching. Then, the advantage of combining predictors with both dynamical and statistical background in the prediction of drought conditions at different lags is evaluated. A two-step hybridization procedure is performed, in which both forecasted and observed 500 hPa geopotential height fields are subjected to a PCA in order to use forecasted PCs and persistent PCs as predictors. A second hybridization step consists on a statistical/hybrid downscaling to the regional SPI, based on regression techniques, after the pre-selection of the statistically significant predictors. The SPI forecasts and the added value of combining dynamical and statistical methods are evaluated in cross-validation mode, using the R2 and binary event scores. Results are obtained for the four seasons and it was found that winter is the most predictable season, and that most of the predictive power is on the large-scale fields from past observations. The hybridization improves the downscaling based on the forecasted PCs, since they provide complementary information (though modest) beyond that of persistent PCs. These findings provide clues about the predictability of the SPI, particularly in Portugal, and may contribute to the predictability of crops yields and to some guidance on users (such as farmers) decision making process.

Dynamics of EEG functional connectivity during statistical learning.

PubMed

Tóth, Brigitta; Janacsek, Karolina; Takács, Ádám; Kóbor, Andrea; Zavecz, Zsófia; Nemeth, Dezso

2017-10-01

Statistical learning is a fundamental mechanism of the brain, which extracts and represents regularities of our environment. Statistical learning is crucial in predictive processing, and in the acquisition of perceptual, motor, cognitive, and social skills. Although previous studies have revealed competitive neurocognitive processes underlying statistical learning, the neural communication of the related brain regions (functional connectivity, FC) has not yet been investigated. The present study aimed to fill this gap by investigating FC networks that promote statistical learning in humans. Young adults (N=28) performed a statistical learning task while 128-channels EEG was acquired. The task involved probabilistic sequences, which enabled to measure incidental/implicit learning of conditional probabilities. Phase synchronization in seven frequency bands was used to quantify FC between cortical regions during the first, second, and third periods of the learning task, respectively. Here we show that statistical learning is negatively correlated with FC of the anterior brain regions in slow (theta) and fast (beta) oscillations. These negative correlations increased as the learning progressed. Our findings provide evidence that dynamic antagonist brain networks serve a hallmark of statistical learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamical analogy between economical crisis and earthquake dynamics within the nonextensive statistical mechanics framework

NASA Astrophysics Data System (ADS)

Potirakis, Stelios M.; Zitis, Pavlos I.; Eftaxias, Konstantinos

2013-07-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and the dynamics of economic (financial) systems can be analyzed within similar mathematical frameworks. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up with these different extreme events, in order to support the suggestion that a dynamical analogy exists between a financial crisis (in the form of share or index price collapse) and a single earthquake. We also investigate the existence of such an analogy by means of scale-free statistics (the Gutenberg-Richter distribution of event sizes). We show that the populations of: (i) fracto-electromagnetic events rooted in the activation of a single fault, emerging prior to a significant earthquake, (ii) the trade volume events of different shares/economic indices, prior to a collapse, and (iii) the price fluctuation (considered as the difference of maximum minus minimum price within a day) events of different shares/economic indices, prior to a collapse, follow both the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar parameter values. The obtained results imply the existence of a dynamic analogy between earthquakes and economic crises, which moreover follow the dynamics of seizures, magnetic storms and solar flares.

Statistical Computations Underlying the Dynamics of Memory Updating

PubMed Central

Gershman, Samuel J.; Radulescu, Angela; Norman, Kenneth A.; Niv, Yael

2014-01-01

Psychophysical and neurophysiological studies have suggested that memory is not simply a carbon copy of our experience: Memories are modified or new memories are formed depending on the dynamic structure of our experience, and specifically, on how gradually or abruptly the world changes. We present a statistical theory of memory formation in a dynamic environment, based on a nonparametric generalization of the switching Kalman filter. We show that this theory can qualitatively account for several psychophysical and neural phenomena, and present results of a new visual memory experiment aimed at testing the theory directly. Our experimental findings suggest that humans can use temporal discontinuities in the structure of the environment to determine when to form new memory traces. The statistical perspective we offer provides a coherent account of the conditions under which new experience is integrated into an old memory versus forming a new memory, and shows that memory formation depends on inferences about the underlying structure of our experience. PMID:25375816

Learning predictive statistics from temporal sequences: Dynamics and strategies

PubMed Central

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E.; Kourtzi, Zoe

2017-01-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics—that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments. PMID:28973111

Material Phase Causality or a Dynamics-Statistical Interpretation of Quantum Mechanics

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

Koprinkov, I. G.

2010-11-25

The internal phase dynamics of a quantum system interacting with an electromagnetic field is revealed in details. Theoretical and experimental evidences of a causal relation of the phase of the wave function to the dynamics of the quantum system are presented sistematically for the first time. A dynamics-statistical interpretation of the quantum mechanics is introduced.

Application of Tube Dynamics to Non-Statistical Reaction Processes

NASA Astrophysics Data System (ADS)

Gabern, F.; Koon, W. S.; Marsden, J. E.; Ross, S. D.; Yanao, T.

2006-06-01

A technique based on dynamical systems theory is introduced for the computation of lifetime distributions and rates of chemical reactions and scattering phenomena, even in systems that exhibit non-statistical behavior. In particular, we merge invariant manifold tube dynamics with Monte Carlo volume determination for accurate rate calculations. This methodology is applied to a three-degree-of-freedom model problem and some ideas on how it might be extended to higher-degree-of-freedom systems are presented.

Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Chen, Y. S.

1986-01-01

The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

Dynamical topology and statistical properties of spatiotemporal chaos.

PubMed

Zhuang, Quntao; Gao, Xun; Ouyang, Qi; Wang, Hongli

2012-12-01

For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a large extent, the location and movement of these topologically special points determine the qualitative structure of the disordered states. We analyze numerically statistical properties of the topologically special points in one-dimensional spatiotemporal chaos. The probability distribution functions for the number of point, the lifespan, and the distance covered during their lifetime are obtained from numerical simulations. Mathematically, we establish a probabilistic model to describe the dynamics of these topologically special points. In spite of the different definitions in different spatiotemporal chaos, the dynamics of these special points can be described in a uniform approach.

An Examination of Statistical Power in Multigroup Dynamic Structural Equation Models

ERIC Educational Resources Information Center

Prindle, John J.; McArdle, John J.

2012-01-01

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

Evaluation of an S.D.I. System Based on "Nuclear Science Abstracts" and the Performance of Matching by Words in Titles Compared With Indexing Terms.

ERIC Educational Resources Information Center

Olive, G.; And Others

A selective dissemination of information service based on computer scanning of Nuclear Science Abstracts tapes has operated at the Atomic Energy Research Establishment, Harwell, England since October, 1968. The performance of the mechanized SDI service has been compared with that of the pre-existing current awareness service which is based on…

Defence SDI - A Useful Current Awareness System (Dissemination Selective de L’Information sur la Defense: Un Systeme Pratique D’Information Permanente).

DTIC Science & Technology

1980-09-01

OF SCIENTIFIC INFORMATION SERVICES L EFENCE SDI - A USEFUL CURRENT AWARENESS SYSTEM (Dissemination Selective de L’Information, Sur la Defense: Un...Dalhousie University, Halifax, Nova Scotia. CAUTION This information is furnished with the express understanding that proprietary and patent rights will be...may add his knowledge of information exchange agreements and Canadian projects covered by these agreements. These exchange agreements are important

Non-Gaussian statistics and nanosecond dynamics of electrostatic fluctuations affecting optical transitions in proteins.

PubMed

Martin, Daniel R; Matyushov, Dmitry V

2012-08-30

We show that electrostatic fluctuations of the protein-water interface are globally non-Gaussian. The electrostatic component of the optical transition energy (energy gap) in a hydrated green fluorescent protein is studied here by classical molecular dynamics simulations. The distribution of the energy gap displays a high excess in the breadth of electrostatic fluctuations over the prediction of the Gaussian statistics. The energy gap dynamics include a nanosecond component. When simulations are repeated with frozen protein motions, the statistics shifts to the expectations of linear response and the slow dynamics disappear. We therefore suggest that both the non-Gaussian statistics and the nanosecond dynamics originate largely from global, low-frequency motions of the protein coupled to the interfacial water. The non-Gaussian statistics can be experimentally verified from the temperature dependence of the first two spectral moments measured at constant-volume conditions. Simulations at different temperatures are consistent with other indicators of the non-Gaussian statistics. In particular, the high-temperature part of the energy gap variance (second spectral moment) scales linearly with temperature and extrapolates to zero at a temperature characteristic of the protein glass transition. This result, violating the classical limit of the fluctuation-dissipation theorem, leads to a non-Boltzmann statistics of the energy gap and corresponding non-Arrhenius kinetics of radiationless electronic transitions, empirically described by the Vogel-Fulcher-Tammann law.

Development of a current collection loss management system for SDI homopolar power supplies

NASA Astrophysics Data System (ADS)

Brown, D. W.

1991-04-01

High speed, high power density current collection systems have been identified as an enabling technology required to construct homopolar power supplies to meet SDI missions. This work is part of a three-year effort directed towards the analysis, experimental verification, and prototype construction of a current collection system designed to operate continuously at 2 kA/sq cm, at a rubbing speed of 200 m/s, and with acceptable losses in a space environment. To date, no system has achieved these conditions simultaneously. This is the final report covering the three year period of performance on DOE contract AC03-86SF-16518. Major areas covered include design, construction and operation of a cryogenically cooled brush test rig, design and construction of a high speed brush test rig, optimization study for homopolar machines, loss analysis of the current collection system, and an application study which defines the air-core homopolar construction necessary to achieve the goal of 80 kW/kg generator power density.

Dynamics of statistical distance: Quantum limits for two-level clocks

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

Braunstein, S.L.; Milburn, G.J.

1995-03-01

We study the evolution of statistical distance on the Bloch sphere under unitary and nonunitary dynamics. This corresponds to studying the limits to clock precision for a clock constructed from a two-state system. We find that the initial motion away from pure states under nonunitary dynamics yields the greatest accuracy for a one-tick'' clock; in this case the clock's precision is not limited by the largest frequency of the system.

SELECTIVE DISSEMINATION OF INFORMATION (SDI). VOLUME I, PILOT TEST AT U.S. ARMY NATICK LABORATORIES. FINAL REPORT. ARMY TECHNICAL LIBRARY IMPROVEMENT STUDIES (ATLIS), REPORT NO. 15.

ERIC Educational Resources Information Center

BIVONA, WILLIAM A.

THIS VOLUME PRESENTS THE RESULTS OF A NINE-MONTH TEST OF A PROTOTYPE SELECTIVE DISSEMINATION OF INFORMATION (SDI) SYSTEM DEVELOPED FOR THE ARMY TECHNICAL LIBRARIES. DURING THE PILOT TEST ONE THOUSAND DOCUMENTS WERE CATALOGED, INDEXED, AND DISSEMINATED TO TWENTY-FIVE SCIENTIFIC AND TECHNICAL PERSONNEL. MATCHING OF THE INTEREST PROFILES OF THESE…

The non-equilibrium statistical mechanics of a simple geophysical fluid dynamics model

NASA Astrophysics Data System (ADS)

Verkley, Wim; Severijns, Camiel

2014-05-01

Lorenz [1] has devised a dynamical system that has proved to be very useful as a benchmark system in geophysical fluid dynamics. The system in its simplest form consists of a periodic array of variables that can be associated with an atmospheric field on a latitude circle. The system is driven by a constant forcing, is damped by linear friction and has a simple advection term that causes the model to behave chaotically if the forcing is large enough. Our aim is to predict the statistics of Lorenz' model on the basis of a given average value of its total energy - obtained from a numerical integration - and the assumption of statistical stationarity. Our method is the principle of maximum entropy [2] which in this case reads: the information entropy of the system's probability density function shall be maximal under the constraints of normalization, a given value of the average total energy and statistical stationarity. Statistical stationarity is incorporated approximately by using `stationarity constraints', i.e., by requiring that the average first and possibly higher-order time-derivatives of the energy are zero in the maximization of entropy. The analysis [3] reveals that, if the first stationarity constraint is used, the resulting probability density function rather accurately reproduces the statistics of the individual variables. If the second stationarity constraint is used as well, the correlations between the variables are also reproduced quite adequately. The method can be generalized straightforwardly and holds the promise of a viable non-equilibrium statistical mechanics of the forced-dissipative systems of geophysical fluid dynamics. [1] E.N. Lorenz, 1996: Predictability - A problem partly solved, in Proc. Seminar on Predictability (ECMWF, Reading, Berkshire, UK), Vol. 1, pp. 1-18. [2] E.T. Jaynes, 2003: Probability Theory - The Logic of Science (Cambridge University Press, Cambridge). [3] W.T.M. Verkley and C.A. Severijns, 2014: The maximum entropy

Vortex dynamics and Lagrangian statistics in a model for active turbulence.

PubMed

James, Martin; Wilczek, Michael

2018-02-14

Cellular suspensions such as dense bacterial flows exhibit a turbulence-like phase under certain conditions. We study this phenomenon of "active turbulence" statistically by using numerical tools. Following Wensink et al. (Proc. Natl. Acad. Sci. U.S.A. 109, 14308 (2012)), we model active turbulence by means of a generalized Navier-Stokes equation. Two-point velocity statistics of active turbulence, both in the Eulerian and the Lagrangian frame, is explored. We characterize the scale-dependent features of two-point statistics in this system. Furthermore, we extend this statistical study with measurements of vortex dynamics in this system. Our observations suggest that the large-scale statistics of active turbulence is close to Gaussian with sub-Gaussian tails.

Statistical-dynamical modeling of the cloud-to-ground lightning activity in Portugal

NASA Astrophysics Data System (ADS)

Sousa, J. F.; Fragoso, M.; Mendes, S.; Corte-Real, J.; Santos, J. A.

2013-10-01

The present study employs a dataset of cloud-to-ground discharges over Portugal, collected by the Portuguese lightning detection network in the period of 2003-2009, to identify dynamically coherent lightning regimes in Portugal and to implement a statistical-dynamical modeling of the daily discharges over the country. For this purpose, the high-resolution MERRA reanalysis is used. Three lightning regimes are then identified for Portugal: WREG, WREM and SREG. WREG is a typical cold-core cut-off low. WREM is connected to strong frontal systems driven by remote low pressure systems at higher latitudes over the North Atlantic. SREG is a combination of an inverted trough and a mid-tropospheric cold-core nearby Portugal. The statistical-dynamical modeling is based on logistic regressions (statistical component) developed for each regime separately (dynamical component). It is shown that the strength of the lightning activity (either strong or weak) for each regime is consistently modeled by a set of suitable dynamical predictors (65-70% of efficiency). The difference of the equivalent potential temperature in the 700-500 hPa layer is the best predictor for the three regimes, while the best 4-layer lifted index is still important for all regimes, but with much weaker significance. Six other predictors are more suitable for a specific regime. For the purpose of validating the modeling approach, a regional-scale climate model simulation is carried out under a very intense lightning episode.

The applications of Complexity Theory and Tsallis Non-extensive Statistics at Solar Plasma Dynamics

NASA Astrophysics Data System (ADS)

Pavlos, George

2015-04-01

As the solar plasma lives far from equilibrium it is an excellent laboratory for testing complexity theory and non-equilibrium statistical mechanics. In this study, we present the highlights of complexity theory and Tsallis non extensive statistical mechanics as concerns their applications at solar plasma dynamics, especially at sunspot, solar flare and solar wind phenomena. Generally, when a physical system is driven far from equilibrium states some novel characteristics can be observed related to the nonlinear character of dynamics. Generally, the nonlinearity in space plasma dynamics can generate intermittent turbulence with the typical characteristics of the anomalous diffusion process and strange topologies of stochastic space plasma fields (velocity and magnetic fields) caused by the strange dynamics and strange kinetics (Zaslavsky, 2002). In addition, according to Zelenyi and Milovanov (2004) the complex character of the space plasma system includes the existence of non-equilibrium (quasi)-stationary states (NESS) having the topology of a percolating fractal set. The stabilization of a system near the NESS is perceived as a transition into a turbulent state determined by self-organization processes. The long-range correlation effects manifest themselves as a strange non-Gaussian behavior of kinetic processes near the NESS plasma state. The complex character of space plasma can also be described by the non-extensive statistical thermodynamics pioneered by Tsallis, which offers a consistent and effective theoretical framework, based on a generalization of Boltzmann - Gibbs (BG) entropy, to describe far from equilibrium nonlinear complex dynamics (Tsallis, 2009). In a series of recent papers, the hypothesis of Tsallis non-extensive statistics in magnetosphere, sunspot dynamics, solar flares, solar wind and space plasma in general, was tested and verified (Karakatsanis et al., 2013; Pavlos et al., 2014; 2015). Our study includes the analysis of solar plasma time

Enterohemorrhagic Escherichia coli O157:H7 requires quorum sensing transcriptional regulators QseA and SdiA for colonization and persistence in the bovine intestinal tract

USDA-ARS?s Scientific Manuscript database

QseA and SdiA are two of several transcriptional regulators that regulate virulence gene expression of enterohemorrhagic Escherichia coli (EHEC) O157:H7 via quorum sensing (QS). QseA regulates the expression of the locus of enterocyte effacement (LEE). LEE encodes for a type III secretion (T3S) sys...

Cardiac resynchronization therapy by multipoint pacing improves response of left ventricular mechanics and fluid dynamics: a three-dimensional and particle image velocimetry echo study.

PubMed

Siciliano, Mariachiara; Migliore, Federico; Badano, Luigi; Bertaglia, Emanuele; Pedrizzetti, Gianni; Cavedon, Stefano; Zorzi, Alessandro; Corrado, Domenico; Iliceto, Sabino; Muraru, Denisa

2017-11-01

To characterize the effect of multipoint pacing (MPP) compared to biventricular pacing (BiV) on left ventricle (LV) mechanics and intraventricular fluid dynamics by three-dimensional echocardiography (3DE) and echocardiographic particle imaging velocimetry (Echo-PIV). In 11 consecutive patients [8 men; median age 65 years (57-75)] receiving cardiac resynchronization therapy (CRT) with a quadripolar LV lead (Quartet,St.Jude Medical,Inc.), 3DE and Echo-PIV data were collected for each pacing configuration (CRT-OFF, BiV, and MPP) at follow-up after 6 months. 3DE data included LV volumes, LV ejection fraction (LVEF), strain, and systolic dyssynchrony index (SDI). Echo-PIV was used to evaluate the directional distribution of global blood flow momentum, ranging from zero, when flow force is predominantly along the base-apex direction, up to 90° when it becomes transversal. MPP resulted in significant reduction in end-diastolic and end-systolic volumes compared with both CRT-OFF (P = 0.02; P = 0.008, respectively) and BiV (P = 0.04; P = 0.03, respectively). LVEF and cardiac output were significant superior in MPP compared with CRT-OFF, but similar between MPP and BiV. Statistical significant differences when comparing global longitudinal and circumferential strain and SDI with MPP vs. CRT-OFF were observed (P = 0.008; P = 0.008; P = 0.01, respectively). There was also a trend towards improvement in strain between BiV and MPP that did not reach statistical significance. MPP reflected into a significant reduction of the deviation of global blood flow momentum compared with both CRT-OFF and BiV (P = 0.002) indicating a systematic increase of longitudinal alignment from the base-apex orientation of the haemodynamic forces. These preliminary results suggest that MPP resulted in significant improvement of LV mechanics and fluid dynamics compared with BiV. However, larger studies are needed to confirm this hypothesis. © Crown copyright 2016.

Development of a current collection loss management system for SDI homopolar power supplies

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

Brown, D.W.

1989-01-01

High speed, high power density current collection systems have been identified as an enabling technology required to construct homopolar power supplies to meet SDI missions. This work is part of a three-year effort directed towards the analysis, experimental verification, and prototype construction of a current collection system designed to operate continuously at 2 kA/cm{sup 2}, at a rubbing speed of 200 m/s, and with acceptable losses in a space environment. To data, no system has achieved these conditions simultaneously. This is the annual report covering the second year period of performance on DOE contract DE-AC03-86SF16518. Major areas covered include design,more » construction and operation of a cryogenically cooled brush test rig, design and construction of a high speed brush test rig, optimization study for homopolar machines, loss analysis of the current collection system, and an application study which defines the air-core homopolar construction necessary to achieve the goal of 80--90 kW/kg generator power density. 17 figs., 2 tabs.« less

Flow Equation Approach to the Statistics of Nonlinear Dynamical Systems

NASA Astrophysics Data System (ADS)

Marston, J. B.; Hastings, M. B.

2005-03-01

The probability distribution function of non-linear dynamical systems is governed by a linear framework that resembles quantum many-body theory, in which stochastic forcing and/or averaging over initial conditions play the role of non-zero . Besides the well-known Fokker-Planck approach, there is a related Hopf functional methodootnotetextUriel Frisch, Turbulence: The Legacy of A. N. Kolmogorov (Cambridge University Press, 1995) chapter 9.5.; in both formalisms, zero modes of linear operators describe the stationary non-equilibrium statistics. To access the statistics, we investigate the method of continuous unitary transformationsootnotetextS. D. Glazek and K. G. Wilson, Phys. Rev. D 48, 5863 (1993); Phys. Rev. D 49, 4214 (1994). (also known as the flow equation approachootnotetextF. Wegner, Ann. Phys. 3, 77 (1994).), suitably generalized to the diagonalization of non-Hermitian matrices. Comparison to the more traditional cumulant expansion method is illustrated with low-dimensional attractors. The treatment of high-dimensional dynamical systems is also discussed.

Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions

PubMed Central

Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-01-01

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics. PMID:24769917

Emergent dynamic structures and statistical law in spherical lattice gas automata

NASA Astrophysics Data System (ADS)

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Emergent dynamic structures and statistical law in spherical lattice gas automata.

PubMed

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Evaluation of the impact of quorum sensing transcriptional regulator SdiA on long-term persistence and fecal shedding of Escherichia coli O157:H7 in weaned calves

USDA-ARS?s Scientific Manuscript database

Quorum sensing transcriptional regulator SdiA has been shown to enhance the survival of Escherichia coli O157:H7 (O157) in the acidic compartment of bovine rumen in response to N-acyl-L-homoserine lactones (AHLs) produced by the rumen bacteria. Bacteria that survive the rumen environment subsequentl...

A Stochastic Fractional Dynamics Model of Rainfall Statistics

NASA Astrophysics Data System (ADS)

Kundu, Prasun; Travis, James

2013-04-01

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.

Statistical and dynamical modeling of heavy-ion fusion-fission reactions

NASA Astrophysics Data System (ADS)

Eslamizadeh, H.; Razazzadeh, H.

2018-02-01

A modified statistical model and a four dimensional dynamical model based on Langevin equations have been used to simulate the fission process of the excited compound nuclei 207At and 216Ra produced in the fusion 19F + 188Os and 19F + 197Au reactions. The evaporation residue cross section, the fission cross section, the pre-scission neutron, proton and alpha multiplicities and the anisotropy of fission fragments angular distribution have been calculated for the excited compound nuclei 207At and 216Ra. In the modified statistical model the effects of spin K about the symmetry axis and temperature have been considered in calculations of the fission widths and the potential energy surfaces. It was shown that the modified statistical model can reproduce the above mentioned experimental data by using appropriate values of the temperature coefficient of the effective potential equal to λ = 0.0180 ± 0.0055, 0.0080 ± 0.0030 MeV-2 and the scaling factor of the fission barrier height equal to rs = 1.0015 ± 0.0025, 1.0040 ± 0.0020 for the compound nuclei 207At and 216Ra, respectively. Three collective shape coordinates plus the projection of total spin of the compound nucleus on the symmetry axis, K, were considered in the four dimensional dynamical model. In the dynamical calculations, dissipation was generated through the chaos weighted wall and window friction formula. Comparison of the theoretical results with the experimental data showed that two models make it possible to reproduce satisfactorily the above mentioned experimental data for the excited compound nuclei 207At and 216Ra.

Exploring Foundation Concepts in Introductory Statistics Using Dynamic Data Points

ERIC Educational Resources Information Center

Ekol, George

2015-01-01

This paper analyses introductory statistics students' verbal and gestural expressions as they interacted with a dynamic sketch (DS) designed using "Sketchpad" software. The DS involved numeric data points built on the number line whose values changed as the points were dragged along the number line. The study is framed on aggregate…

Imprints of dynamical interactions on brown dwarf pairing statistics and kinematics

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.

2003-03-01

We present statistically robust predictions of brown dwarf properties arising from dynamical interactions during their early evolution in small clusters. Our conclusions are based on numerical calculations of the internal cluster dynamics as well as on Monte-Carlo models. Accounting for recent observational constraints on the sub-stellar mass function and initial properties in fragmenting star forming clumps, we derive multiplicity fractions, mass ratios, separation distributions, and velocity dispersions. We compare them with observations of brown dwarfs in the field and in young clusters. Observed brown dwarf companion fractions around 15 +/- 7% for very low-mass stars as reported recently by Close et al. (\\cite{CSFB03}) are consistent with certain dynamical decay models. A significantly smaller mean separation distribution for brown dwarf binaries than for binaries of late-type stars can be explained by similar specific energy at the time of cluster formation for all cluster masses. Due to their higher velocity dispersions, brown-dwarfs and low-mass single stars will undergo time-dependent spatial segregation from higher-mass stars and multiple systems. This will cause mass functions and binary statistics in star forming regions to vary with the age of the region and the volume sampled.

A statistical physics viewpoint on the dynamics of the bouncing ball

NASA Astrophysics Data System (ADS)

Chastaing, Jean-Yonnel; Géminard, Jean-Christophe; Bertin, Eric

2016-06-01

We compute, in a statistical physics perspective, the dynamics of a bouncing ball maintained in a chaotic regime thanks to collisions with a plate experiencing an aperiodic vibration. We analyze in details the energy exchanges between the bead and the vibrating plate, and show that the coupling between the bead and the plate can be modeled in terms of both a dissipative process and an injection mechanism by an energy reservoir. An analysis of the injection statistics in terms of fluctuation relation is also provided.

OneGeology Web Services and Portal as a global geological SDI - latest standards and technology

NASA Astrophysics Data System (ADS)

Duffy, Tim; Tellez-Arenas, Agnes

2014-05-01

The global coverage of OneGeology Web Services (www.onegeology.org and portal.onegeology.org) achieved since 2007 from the 120 participating geological surveys will be reviewed and issues arising discussed. Recent enhancements to the OneGeology Web Services capabilities will be covered including new up to 5 star service accreditation scheme utilising the ISO/OGC Web Mapping Service standard version 1.3, core ISO 19115 metadata additions and Version 2.0 Web Feature Services (WFS) serving the new IUGS-CGI GeoSciML V3.2 geological web data exchange language standard (http://www.geosciml.org/) with its associated 30+ IUGS-CGI available vocabularies (http://resource.geosciml.org/ and http://srvgeosciml.brgm.fr/eXist2010/brgm/client.html). Use of the CGI simpelithology and timescale dictionaries now allow those who wish to do so to offer data harmonisation to query their GeoSciML 3.2 based Web Feature Services and their GeoSciML_Portrayal V2.0.1 (http://www.geosciml.org/) Web Map Services in the OneGeology portal (http://portal.onegeology.org). Contributing to OneGeology involves offering to serve ideally 1:1000,000 scale geological data (in practice any scale now is warmly welcomed) as an OGC (Open Geospatial Consortium) standard based WMS (Web Mapping Service) service from an available WWW server. This may either be hosted within the Geological Survey or a neighbouring, regional or elsewhere institution that offers to serve that data for them i.e. offers to help technically by providing the web serving IT infrastructure as a 'buddy'. OneGeology is a standards focussed Spatial Data Infrastructure (SDI) and works to ensure that these standards work together and it is now possible for European Geological Surveys to register their INSPIRE web services within the OneGeology SDI (e.g. see http://www.geosciml.org/geosciml/3.2/documentation/cookbook/INSPIRE_GeoSciML_Cookbook%20_1.0.pdf). The Onegeology portal (http://portal.onegeology.org) is the first port of call for anyone

The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: validation and parameter optimization

NASA Astrophysics Data System (ADS)

Totz, Sonja; Eliseev, Alexey V.; Petri, Stefan; Flechsig, Michael; Caesar, Levke; Petoukhov, Vladimir; Coumou, Dim

2018-02-01

We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower

Role of quantum statistics in multi-particle decay dynamics

NASA Astrophysics Data System (ADS)

Marchewka, Avi; Granot, Er'el

2015-04-01

The role of quantum statistics in the decay dynamics of a multi-particle state, which is suddenly released from a confining potential, is investigated. For an initially confined double particle state, the exact dynamics is presented for both bosons and fermions. The time-evolution of the probability to measure two-particle is evaluated and some counterintuitive features are discussed. For instance, it is shown that although there is a higher chance of finding the two bosons (as oppose to fermions, and even distinguishable particles) at the initial trap region, there is a higher chance (higher than fermions) of finding them on two opposite sides of the trap as if the repulsion between bosons is higher than the repulsion between fermions. The results are demonstrated by numerical simulations and are calculated analytically in the short-time approximation. Furthermore, experimental validation is suggested.

A statistical state dynamics approach to wall turbulence.

PubMed

Farrell, B F; Gayme, D F; Ioannou, P J

2017-03-13

This paper reviews results obtained using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD approach used in this work employs a second-order closure that retains only the interaction between the streamwise mean flow and the streamwise mean perturbation covariance. This closure restricts nonlinearity in the SSD to that explicitly retained in the streamwise constant mean flow together with nonlinear interactions between the mean flow and the perturbation covariance. This dynamical restriction, in which explicit perturbation-perturbation nonlinearity is removed from the perturbation equation, results in a simplified dynamics referred to as the restricted nonlinear (RNL) dynamics. RNL systems, in which a finite ensemble of realizations of the perturbation equation share the same mean flow, provide tractable approximations to the SSD, which is equivalent to an infinite ensemble RNL system. This infinite ensemble system, referred to as the stochastic structural stability theory system, introduces new analysis tools for studying turbulence. RNL systems provide computationally efficient means to approximate the SSD and produce self-sustaining turbulence exhibiting qualitative features similar to those observed in direct numerical simulations despite greatly simplified dynamics. The results presented show that RNL turbulence can be supported by as few as a single streamwise varying component interacting with the streamwise constant mean flow and that judicious selection of this truncated support or 'band-limiting' can be used to improve quantitative accuracy of RNL turbulence. These results suggest that the SSD approach provides new analytical and computational tools that allow new insights into wall turbulence.This article is part of the themed issue 'Toward the development of high-fidelity models of wall turbulence at large Reynolds number'. © 2017 The Author(s).

A statistical state dynamics approach to wall turbulence

PubMed Central

Gayme, D. F.; Ioannou, P. J.

2017-01-01

This paper reviews results obtained using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD approach used in this work employs a second-order closure that retains only the interaction between the streamwise mean flow and the streamwise mean perturbation covariance. This closure restricts nonlinearity in the SSD to that explicitly retained in the streamwise constant mean flow together with nonlinear interactions between the mean flow and the perturbation covariance. This dynamical restriction, in which explicit perturbation–perturbation nonlinearity is removed from the perturbation equation, results in a simplified dynamics referred to as the restricted nonlinear (RNL) dynamics. RNL systems, in which a finite ensemble of realizations of the perturbation equation share the same mean flow, provide tractable approximations to the SSD, which is equivalent to an infinite ensemble RNL system. This infinite ensemble system, referred to as the stochastic structural stability theory system, introduces new analysis tools for studying turbulence. RNL systems provide computationally efficient means to approximate the SSD and produce self-sustaining turbulence exhibiting qualitative features similar to those observed in direct numerical simulations despite greatly simplified dynamics. The results presented show that RNL turbulence can be supported by as few as a single streamwise varying component interacting with the streamwise constant mean flow and that judicious selection of this truncated support or ‘band-limiting’ can be used to improve quantitative accuracy of RNL turbulence. These results suggest that the SSD approach provides new analytical and computational tools that allow new insights into wall turbulence. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’. PMID

Dynamic Graphics in Excel for Teaching Statistics: Understanding the Probability Density Function

ERIC Educational Resources Information Center

Coll-Serrano, Vicente; Blasco-Blasco, Olga; Alvarez-Jareno, Jose A.

2011-01-01

In this article, we show a dynamic graphic in Excel that is used to introduce an important concept in our subject, Statistics I: the probability density function. This interactive graphic seeks to facilitate conceptual understanding of the main aspects analysed by the learners.

Signals of dynamical and statistical process from IMF-IMF correlation function

NASA Astrophysics Data System (ADS)

Pagano, E. V.; Acosta, L.; Auditore, L.; Baran, V.; Cap, T.; Cardella, G.; Colonna, M.; De Luca, S.; De Filippo, E.; Dell'Aquila, D.; Francalanza, L.; Gnoffo, B.; Lanzalone, G.; Lombardo, I.; Maiolino, C.; Martorana, N. S.; Norella, S.; Pagano, A.; Papa, M.; Piasecki, E.; Pirrone, S.; Politi, G.; Porto, F.; Quattrocchi, L.; Rizzo, F.; Rosato, E.; Russotto, P.; Siwek-Wilczyńska, K.; Trifiro, A.; Trimarchi, M.; Verde, G.; Vigilante, M.; Wilczyńsky, J.

2017-11-01

In this paper we briefly discuss about a novel application of the IMF-IMF correlation function to the physical case of binary massive projectile-like (PLF) splitting for dynamical and statistical breakup/fission in heavy ion collisions at Fermi energy. Theoretical simulations are also shown for comparisons with the data. These preliminary results have been obtained for the reverse kinematics reaction 124Sn + 64Ni at 35 AMeV that was studied using the forward part of CHIMERA detector. In that reaction a strong competition between a dynamical and a statistical components and its evolution with the charge asymmetry of the binary break up was already shown. In this work we show that the IMF-IMF correlation function can be used to pin down the timescale of the fragments production in binary fission-like phenomena. We also made simulations with the CoMDII model in order to compare to the experimental IMF-IMF correlation function. In future we plan to extend these studies to different reaction mechanisms and nuclear systems and to compare with different theoretical transport simulations.

The effect on prospective teachers of the learning environment supported by dynamic statistics software

NASA Astrophysics Data System (ADS)

Koparan, Timur

2016-02-01

In this study, the effect on the achievement and attitudes of prospective teachers is examined. With this aim ahead, achievement test, attitude scale for statistics and interviews were used as data collection tools. The achievement test comprises 8 problems based on statistical data, and the attitude scale comprises 13 Likert-type items. The study was carried out in 2014-2015 academic year fall semester at a university in Turkey. The study, which employed the pre-test-post-test control group design of quasi-experimental research method, was carried out on a group of 80 prospective teachers, 40 in the control group and 40 in the experimental group. Both groups had four-hour classes about descriptive statistics. The classes with the control group were carried out through traditional methods while dynamic statistics software was used in the experimental group. Five prospective teachers from the experimental group were interviewed clinically after the application for a deeper examination of their views about application. Qualitative data gained are presented under various themes. At the end of the study, it was found that there is a significant difference in favour of the experimental group in terms of achievement and attitudes, the prospective teachers have affirmative approach to the use of dynamic software and see it as an effective tool to enrich maths classes. In accordance with the findings of the study, it is suggested that dynamic software, which offers unique opportunities, be used in classes by teachers and students.

Statistical-mechanical predictions and Navier-Stokes dynamics of two-dimensional flows on a bounded domain.

PubMed

Brands, H; Maassen, S R; Clercx, H J

1999-09-01

In this paper the applicability of a statistical-mechanical theory to freely decaying two-dimensional (2D) turbulence on a bounded domain is investigated. We consider an ensemble of direct numerical simulations in a square box with stress-free boundaries, with a Reynolds number that is of the same order as in experiments on 2D decaying Navier-Stokes turbulence. The results of these simulations are compared with the corresponding statistical equilibria, calculated from different stages of the evolution. It is shown that the statistical equilibria calculated from early times of the Navier-Stokes evolution do not correspond to the dynamical quasistationary states. At best, the global topological structure is correctly predicted from a relatively late time in the Navier-Stokes evolution, when the quasistationary state has almost been reached. This failure of the (basically inviscid) statistical-mechanical theory is related to viscous dissipation and net leakage of vorticity in the Navier-Stokes dynamics at moderate values of the Reynolds number.

Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui.

PubMed

Newton, Richard; Deonarine, Andrew; Wernisch, Lorenz

2012-09-24

The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an

Fragment size distribution statistics in dynamic fragmentation of laser shock-loaded tin

NASA Astrophysics Data System (ADS)

He, Weihua; Xin, Jianting; Zhao, Yongqiang; Chu, Genbai; Xi, Tao; Shui, Min; Lu, Feng; Gu, Yuqiu

2017-06-01

This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.

OPEN PROBLEM: Orbits' statistics in chaotic dynamical systems

NASA Astrophysics Data System (ADS)

Arnold, V.

2008-07-01

This paper shows how the measurement of the stochasticity degree of a finite sequence of real numbers, published by Kolmogorov in Italian in a journal of insurances' statistics, can be usefully applied to measure the objective stochasticity degree of sequences, originating from dynamical systems theory and from number theory. Namely, whenever the value of Kolmogorov's stochasticity parameter of a given sequence of numbers is too small (or too big), one may conclude that the conjecture describing this sequence as a sample of independent values of a random variables is highly improbable. Kolmogorov used this strategy fighting (in a paper in 'Doklady', 1940) against Lysenko, who had tried to disprove the classical genetics' law of Mendel experimentally. Calculating his stochasticity parameter value for the numbers from Lysenko's experiment reports, Kolmogorov deduced, that, while these numbers were different from the exact fulfilment of Mendel's 3 : 1 law, any smaller deviation would be a manifestation of the report's number falsification. The calculation of the values of the stochasticity parameter would be useful for many other generators of pseudorandom numbers and for many other chaotically looking statistics, including even the prime numbers distribution (discussed in this paper as an example).

Reaction Event Counting Statistics of Biopolymer Reaction Systems with Dynamic Heterogeneity.

PubMed

Lim, Yu Rim; Park, Seong Jun; Park, Bo Jung; Cao, Jianshu; Silbey, Robert J; Sung, Jaeyoung

2012-04-10

We investigate the reaction event counting statistics (RECS) of an elementary biopolymer reaction in which the rate coefficient is dependent on states of the biopolymer and the surrounding environment and discover a universal kinetic phase transition in the RECS of the reaction system with dynamic heterogeneity. From an exact analysis for a general model of elementary biopolymer reactions, we find that the variance in the number of reaction events is dependent on the square of the mean number of the reaction events when the size of measurement time is small on the relaxation time scale of rate coefficient fluctuations, which does not conform to renewal statistics. On the other hand, when the size of the measurement time interval is much greater than the relaxation time of rate coefficient fluctuations, the variance becomes linearly proportional to the mean reaction number in accordance with renewal statistics. Gillespie's stochastic simulation method is generalized for the reaction system with a rate coefficient fluctuation. The simulation results confirm the correctness of the analytic results for the time dependent mean and variance of the reaction event number distribution. On the basis of the obtained results, we propose a method of quantitative analysis for the reaction event counting statistics of reaction systems with rate coefficient fluctuations, which enables one to extract information about the magnitude and the relaxation times of the fluctuating reaction rate coefficient, without a bias that can be introduced by assuming a particular kinetic model of conformational dynamics and the conformation dependent reactivity. An exact relationship is established between a higher moment of the reaction event number distribution and the multitime correlation of the reaction rate for the reaction system with a nonequilibrium initial state distribution as well as for the system with the equilibrium initial state distribution.

Statistical analysis of dynamic fibrils observed from NST/BBSO observations

NASA Astrophysics Data System (ADS)

Gopalan Priya, Thambaje; Su, Jiang-Tao; Chen, Jie; Deng, Yuan-Yong; Prasad Choudhury, Debi

2018-02-01

We present the results obtained from the analysis of dynamic fibrils in NOAA active region (AR) 12132, using high resolution Hα observations from the New Solar Telescope operating at Big Bear Solar Observatory. The dynamic fibrils are seen to be moving up and down, and most of these dynamic fibrils are periodic and have a jet-like appearance. We found from our observations that the fibrils follow almost perfect parabolic paths in many cases. A statistical analysis on the properties of the parabolic paths showing an analysis on deceleration, maximum velocity, duration and kinetic energy of these fibrils is presented here. We found the average maximum velocity to be around 15 kms‑1 and mean deceleration to be around 100 ms‑2. The observed deceleration appears to be a fraction of gravity of the Sun and is not compatible with the path of ballistic motion due to gravity of the Sun. We found a positive correlation between deceleration and maximum velocity. This correlation is consistent with simulations done earlier on magnetoacoustic shock waves propagating upward.

Neutral dynamics with environmental noise: Age-size statistics and species lifetimes

NASA Astrophysics Data System (ADS)

Kessler, David; Suweis, Samir; Formentin, Marco; Shnerb, Nadav M.

2015-08-01

Neutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to demographic [O (√{N }) ] noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems. Here we analyze two of these problems—age-size relationships and species extinction time—in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of "zero mean" environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics.

Dynamic Statistical Characterization of Variation in Source Processes of Microseismic Events

NASA Astrophysics Data System (ADS)

Smith-Boughner, L.; Viegas, G. F.; Urbancic, T.; Baig, A. M.

2015-12-01

During a hydraulic fracture, water is pumped at high pressure into a formation. A proppant, typically sand is later injected in the hope that it will make its way into a fracture, keep it open and provide a path for the hydrocarbon to enter the well. This injection can create micro-earthquakes, generated by deformation within the reservoir during treatment. When these injections are monitored, thousands of microseismic events are recorded within several hundred cubic meters. For each well-located event, many source parameters are estimated e.g. stress drop, Savage-Wood efficiency and apparent stress. However, because we are evaluating outputs from a power-law process, the extent to which the failure is impacted by fluid injection or stress triggering is not immediately clear. To better detect differences in source processes, we use a set of dynamic statistical parameters which characterize various force balance assumptions using the average distance to the nearest event, event rate, volume enclosed by the events, cumulative moment and energy from a group of events. One parameter, the Fracability index, approximates the ratio of viscous to elastic forcing and highlights differences in the response time of a rock to changes in stress. These dynamic parameters are applied to a database of more than 90 000 events in a shale-gas play in the Horn River Basin to characterize spatial-temporal variations in the source processes. In order to resolve these differences, a moving window, nearest neighbour approach was used. First, the center of mass of the local distribution was estimated for several source parameters. Then, a set of dynamic parameters, which characterize the response of the rock were estimated. These techniques reveal changes in seismic efficiency and apparent stress and often coincide with marked changes in the Fracability index and other dynamic statistical parameters. Utilizing these approaches allowed for the characterization of fluid injection related

Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui

PubMed Central

2012-01-01

Background The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. Methods This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Results Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. Conclusions This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics

Dynamic whole body PET parametric imaging: II. Task-oriented statistical estimation

PubMed Central

Karakatsanis, Nicolas A.; Lodge, Martin A.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-01-01

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15–20cm) of a single bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study

Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.

PubMed

Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-10-21

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study

Statistical and dynamical remastering of classic exoplanet systems

NASA Astrophysics Data System (ADS)

Nelson, Benjamin Earl

The most powerful constraints on planet formation will come from characterizing the dynamical state of complex multi-planet systems. Unfortunately, with that complexity comes a number of factors that make analyzing these systems a computationally challenging endeavor: the sheer number of model parameters, a wonky shaped posterior distribution, and hundreds to thousands of time series measurements. In this dissertation, I will review our efforts to improve the statistical analyses of radial velocity (RV) data and their applications to some renown, dynamically complex exoplanet system. In the first project (Chapters 2 and 4), we develop a differential evolution Markov chain Monte Carlo (RUN DMC) algorithm to tackle the aforementioned difficult aspects of data analysis. We test the robustness of the algorithm in regards to the number of modeled planets (model dimensionality) and increasing dynamical strength. We apply RUN DMC to a couple classic multi-planet systems and one highly debated system from radial velocity surveys. In the second project (Chapter 5), we analyze RV data of 55 Cancri, a wide binary system known to harbor five planetary orbiting the primary. We find the inner-most planet "e" must be coplanar to within 40 degrees of the outer planets, otherwise Kozai-like perturbations will cause the planet to enter the stellar photosphere through its periastron passage. We find the orbits of planets "b" and "c" are apsidally aligned and librating with low to median amplitude (50+/-6 10 degrees), but they are not orbiting in a mean-motion resonance. In the third project (Chapters 3, 4, 6), we analyze RV data of Gliese 876, a four planet system with three participating in a multi-body resonance, i.e. a Laplace resonance. From a combined observational and statistical analysis computing Bayes factors, we find a four-planet model is favored over one with three-planets. Conditioned on this preferred model, we meaningfully constrain the three-dimensional orbital

An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics

NASA Astrophysics Data System (ADS)

Turkington, Bruce

2013-08-01

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.

PubMed

Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems

PubMed Central

Timmis, Jon; Qwarnstrom, Eva E.

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414

Dynamic causal modelling: a critical review of the biophysical and statistical foundations.

PubMed

Daunizeau, J; David, O; Stephan, K E

2011-09-15

The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. Copyright © 2009 Elsevier Inc. All rights reserved.

A Statistical Description of Neural Ensemble Dynamics

PubMed Central

Long, John D.; Carmena, Jose M.

2011-01-01

The growing use of multi-channel neural recording techniques in behaving animals has produced rich datasets that hold immense potential for advancing our understanding of how the brain mediates behavior. One limitation of these techniques is they do not provide important information about the underlying anatomical connections among the recorded neurons within an ensemble. Inferring these connections is often intractable because the set of possible interactions grows exponentially with ensemble size. This is a fundamental challenge one confronts when interpreting these data. Unfortunately, the combination of expert knowledge and ensemble data is often insufficient for selecting a unique model of these interactions. Our approach shifts away from modeling the network diagram of the ensemble toward analyzing changes in the dynamics of the ensemble as they relate to behavior. Our contribution consists of adapting techniques from signal processing and Bayesian statistics to track the dynamics of ensemble data on time-scales comparable with behavior. We employ a Bayesian estimator to weigh prior information against the available ensemble data, and use an adaptive quantization technique to aggregate poorly estimated regions of the ensemble data space. Importantly, our method is capable of detecting changes in both the magnitude and structure of correlations among neurons missed by firing rate metrics. We show that this method is scalable across a wide range of time-scales and ensemble sizes. Lastly, the performance of this method on both simulated and real ensemble data is used to demonstrate its utility. PMID:22319486

a Statistical Dynamic Approach to Structural Evolution of Complex Capital Market Systems

NASA Astrophysics Data System (ADS)

Shao, Xiao; Chai, Li H.

As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.

Activity statistics in a colloidal glass former: Experimental evidence for a dynamical transition

NASA Astrophysics Data System (ADS)

Abou, Bérengère; Colin, Rémy; Lecomte, Vivien; Pitard, Estelle; van Wijland, Frédéric

2018-04-01

In a dense colloidal suspension at a volume fraction below the glass transition, we follow the trajectories of an assembly of tracers over a large time window. We define a local activity, which quantifies the local tendency of the system to rearrange. We determine the statistics of the time integrated activity, and we argue that it develops a low activity tail that comes together with the onset of glassy-like behavior and heterogeneous dynamics. These rare events may be interpreted as the reflection of an underlying dynamic phase transition.

Hydrological responses to dynamically and statistically downscaled climate model output

USGS Publications Warehouse

Wilby, R.L.; Hay, L.E.; Gutowski, W.J.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.

2000-01-01

Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

Application of Dynamic naïve Bayesian classifier to comprehensive drought assessment

NASA Astrophysics Data System (ADS)

Park, D. H.; Lee, J. Y.; Lee, J. H.; KIm, T. W.

2017-12-01

Drought monitoring has already been extensively studied due to the widespread impacts and complex causes of drought. The most important component of drought monitoring is to estimate the characteristics and extent of drought by quantitatively measuring the characteristics of drought. Drought assessment considering different aspects of the complicated drought condition and uncertainty of drought index is great significance in accurate drought monitoring. This study used the dynamic Naïve Bayesian Classifier (DNBC) which is an extension of the Hidden Markov Model (HMM), to model and classify drought by using various drought indices for integrated drought assessment. To provide a stable model for combined use of multiple drought indices, this study employed the DNBC to perform multi-index drought assessment by aggregating the effect of different type of drought and considering the inherent uncertainty. Drought classification was performed by the DNBC using several drought indices: Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Normalized Vegetation Supply Water Index (NVSWI)) that reflect meteorological, hydrological, and agricultural drought characteristics. Overall results showed that in comparison unidirectional (SPI, SDI, and NVSWI) or multivariate (Composite Drought Index, CDI) drought assessment, the proposed DNBC was able to synthetically classify of drought considering uncertainty. Model provided method for comprehensive drought assessment with combined use of different drought indices.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Do You Need to See It to Believe It? Let's See Statistics and Geometry Dynamically Together!

ERIC Educational Resources Information Center

Martins, José Alexandre; Roca, Assumpta Estrada; Nascimento, Maria Manuel

2014-01-01

Statistical graphs, measures of central tendency and measures of spread are key concepts in the statistics curriculum, so we present here a dynamic method (software) that may be used in the classroom. In this work we begin with an introductory approach. This is done to emphasize the importance of stimulating the visualization of statistical…

Tracking solutes and water from subsurface drip irrigation application of coalbed methane-produced waters, Powder River Basin, Wyoming

USGS Publications Warehouse

Engle, M.A.; Bern, C.R.; Healy, R.W.; Sams, J.I.; Zupancic, J.W.; Schroeder, K.T.

2011-01-01

One method to beneficially use water produced from coalbed methane (CBM) extraction is subsurface drip irrigation (SDI) of croplands. In SDI systems, treated CBMwater (injectate) is supplied to the soil at depth, with the purpose of preventing the buildup of detrimental salts near the surface. The technology is expanding within the Powder River Basin, but little research has been published on its environmental impacts. This article reports on initial results from tracking water and solutes from the injected CBM-produced waters at an SDI system in Johnson County, Wyoming. In the first year of SDI operation, soil moisture significantly increased in the SDI areas, but well water levels increased only modestly, suggesting that most of the water added was stored in the vadose zone or lost to evapotranspiration. The injectate has lower concentrations of most inorganic constituents relative to ambient groundwater at the site but exhibits a high sodium adsorption ratio. Changes in groundwater chemistry during the same period of SDI operation were small; the increase in groundwater-specific conductance relative to pre-SDI conditions was observed in a single well. Conversely, groundwater samples collected beneath another SDI field showed decreased concentrations of several constituents since the SDI operation.Groundwater-specific conductance at the 12 other wells showed no significant changes. Major controls on and compositional variability of groundwater, surface water, and soil water chemistry are discussed in detail. Findings from this research provide an understanding of water and salt dynamics associated with SDI systems using CBM-produced water. Copyright ??2011. The American Association of Petroleum Geologists/Division of Environmental Geosciences. All rights reserved.

Pasta Nucleosynthesis: Molecular dynamics simulations of nuclear statistical equilibrium

NASA Astrophysics Data System (ADS)

Caplan, Matthew; Horowitz, Charles; da Silva Schneider, Andre; Berry, Donald

2014-09-01

We simulate the decompression of cold dense nuclear matter, near the nuclear saturation density, in order to study the role of nuclear pasta in r-process nucleosynthesis in neutron star mergers. Our simulations are performed using a classical molecular dynamics model with 51 200 and 409 600 nucleons, and are run on GPUs. We expand our simulation region to decompress systems from initial densities of 0.080 fm-3 down to 0.00125 fm-3. We study proton fractions of YP = 0.05, 0.10, 0.20, 0.30, and 0.40 at T = 0.5, 0.75, and 1 MeV. We calculate the composition of the resulting systems using a cluster algorithm. This composition is in good agreement with nuclear statistical equilibrium models for temperatures of 0.75 and 1 MeV. However, for proton fractions greater than YP = 0.2 at a temperature of T = 0.5 MeV, the MD simulations produce non-equilibrium results with large rod-like nuclei. Our MD model is valid at higher densities than simple nuclear statistical equilibrium models and may help determine the initial temperatures and proton fractions of matter ejected in mergers.

Accurately Characterizing the Importance of Wave-Particle Interactions in Radiation Belt Dynamics: The Pitfalls of Statistical Wave Representations

NASA Technical Reports Server (NTRS)

Murphy, Kyle R.; Mann, Ian R.; Rae, I. Jonathan; Sibeck, David G.; Watt, Clare E. J.

2016-01-01

Wave-particle interactions play a crucial role in energetic particle dynamics in the Earths radiation belts. However, the relative importance of different wave modes in these dynamics is poorly understood. Typically, this is assessed during geomagnetic storms using statistically averaged empirical wave models as a function of geomagnetic activity in advanced radiation belt simulations. However, statistical averages poorly characterize extreme events such as geomagnetic storms in that storm-time ultralow frequency wave power is typically larger than that derived over a solar cycle and Kp is a poor proxy for storm-time wave power.

Statistical variances of diffusional properties from ab initio molecular dynamics simulations

NASA Astrophysics Data System (ADS)

He, Xingfeng; Zhu, Yizhou; Epstein, Alexander; Mo, Yifei

2018-12-01

Ab initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.

A statistical model for interpreting computerized dynamic posturography data

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Metter, E. Jeffrey; Paloski, William H.

2002-01-01

Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.

A response surface methodology based damage identification technique

NASA Astrophysics Data System (ADS)

Fang, S. E.; Perera, R.

2009-06-01

Response surface methodology (RSM) is a combination of statistical and mathematical techniques to represent the relationship between the inputs and outputs of a physical system by explicit functions. This methodology has been widely employed in many applications such as design optimization, response prediction and model validation. But so far the literature related to its application in structural damage identification (SDI) is scarce. Therefore this study attempts to present a systematic SDI procedure comprising four sequential steps of feature selection, parameter screening, primary response surface (RS) modeling and updating, and reference-state RS modeling with SDI realization using the factorial design (FD) and the central composite design (CCD). The last two steps imply the implementation of inverse problems by model updating in which the RS models substitute the FE models. The proposed method was verified against a numerical beam, a tested reinforced concrete (RC) frame and an experimental full-scale bridge with the modal frequency being the output responses. It was found that the proposed RSM-based method performs well in predicting the damage of both numerical and experimental structures having single and multiple damage scenarios. The screening capacity of the FD can provide quantitative estimation of the significance levels of updating parameters. Meanwhile, the second-order polynomial model established by the CCD provides adequate accuracy in expressing the dynamic behavior of a physical system.

Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane

NASA Astrophysics Data System (ADS)

He, W.; Song, H.; Su, Y.; Geng, L.; Ackerson, B. J.; Peng, H. B.; Tong, P.

2016-05-01

The Brownian motion of molecules at thermal equilibrium usually has a finite correlation time and will eventually be randomized after a long delay time, so that their displacement follows the Gaussian statistics. This is true even when the molecules have experienced a complex environment with a finite correlation time. Here, we report that the lateral motion of the acetylcholine receptors on live muscle cell membranes does not follow the Gaussian statistics for normal Brownian diffusion. From a careful analysis of a large volume of the protein trajectories obtained over a wide range of sampling rates and long durations, we find that the normalized histogram of the protein displacements shows an exponential tail, which is robust and universal for cells under different conditions. The experiment indicates that the observed non-Gaussian statistics and dynamic heterogeneity are inherently linked to the slow-active remodelling of the underlying cortical actin network.

Pasta nucleosynthesis: Molecular dynamics simulations of nuclear statistical equilibrium

NASA Astrophysics Data System (ADS)

Caplan, M. E.; Schneider, A. S.; Horowitz, C. J.; Berry, D. K.

2015-06-01

Background: Exotic nonspherical nuclear pasta shapes are expected in nuclear matter at just below saturation density because of competition between short-range nuclear attraction and long-range Coulomb repulsion. Purpose: We explore the impact nuclear pasta may have on nucleosynthesis during neutron star mergers when cold dense nuclear matter is ejected and decompressed. Methods: We use a hybrid CPU/GPU molecular dynamics (MD) code to perform decompression simulations of cold dense matter with 51 200 and 409 600 nucleons from 0.080 fm-3 down to 0.00125 fm-3 . Simulations are run for proton fractions YP= 0.05, 0.10, 0.20, 0.30, and 0.40 at temperatures T = 0.5, 0.75, and 1.0 MeV. The final composition of each simulation is obtained using a cluster algorithm and compared to a constant density run. Results: Size of nuclei in the final state of decompression runs are in good agreement with nuclear statistical equilibrium (NSE) models for temperatures of 1 MeV while constant density runs produce nuclei smaller than the ones obtained with NSE. Our MD simulations produces unphysical results with large rod-like nuclei in the final state of T =0.5 MeV runs. Conclusions: Our MD model is valid at higher densities than simple nuclear statistical equilibrium models and may help determine the initial temperatures and proton fractions of matter ejected in mergers.

Recent updates in developing a statistical pseudo-dynamic source-modeling framework to capture the variability of earthquake rupture scenarios

NASA Astrophysics Data System (ADS)

Song, Seok Goo; Kwak, Sangmin; Lee, Kyungbook; Park, Donghee

2017-04-01

It is a critical element to predict the intensity and variability of strong ground motions in seismic hazard assessment. The characteristics and variability of earthquake rupture process may be a dominant factor in determining the intensity and variability of near-source strong ground motions. Song et al. (2014) demonstrated that the variability of earthquake rupture scenarios could be effectively quantified in the framework of 1-point and 2-point statistics of earthquake source parameters, constrained by rupture dynamics and past events. The developed pseudo-dynamic source modeling schemes were also validated against the recorded ground motion data of past events and empirical ground motion prediction equations (GMPEs) at the broadband platform (BBP) developed by the Southern California Earthquake Center (SCEC). Recently we improved the computational efficiency of the developed pseudo-dynamic source-modeling scheme by adopting the nonparametric co-regionalization algorithm, introduced and applied in geostatistics initially. We also investigated the effect of earthquake rupture process on near-source ground motion characteristics in the framework of 1-point and 2-point statistics, particularly focusing on the forward directivity region. Finally we will discuss whether the pseudo-dynamic source modeling can reproduce the variability (standard deviation) of empirical GMPEs and the efficiency of 1-point and 2-point statistics to address the variability of ground motions.

The SdiA-Regulated Gene srgE Encodes a Type III Secreted Effector

PubMed Central

Habyarimana, Fabien; Sabag-Daigle, Anice

2014-01-01

Salmonella enterica serovar Typhimurium is a food-borne pathogen that causes severe gastroenteritis. The ability of Salmonella to cause disease depends on two type III secretion systems (T3SSs) encoded in two distinct Salmonella pathogenicity islands, 1 and 2 (SPI1 and SPI2, respectively). S. Typhimurium encodes a solo LuxR homolog, SdiA, which can detect the acyl-homoserine lactones (AHLs) produced by other bacteria and upregulate the rck operon and the srgE gene. SrgE is predicted to encode a protein of 488 residues with a coiled-coil domain between residues 345 and 382. In silico studies have provided conflicting predictions as to whether SrgE is a T3SS substrate. Therefore, in this work, we tested the hypothesis that SrgE is a T3SS effector by two methods, a β-lactamase activity assay and a split green fluorescent protein (GFP) complementation assay. SrgE with β-lactamase fused to residue 40, 100, 150, or 300 was indeed expressed and translocated into host cells, but SrgE with β-lactamase fused to residue 400 or 488 was not expressed, suggesting interference by the coiled-coil domain. Similarly, SrgE with GFP S11 fused to residue 300, but not to residue 488, was expressed and translocated into host cells. With both systems, translocation into host cells was dependent upon SPI2. A phylogenetic analysis indicated that srgE is found only within Salmonella enterica subspecies. It is found sporadically within both typhoidal and nontyphoidal serovars, although the SrgE protein sequences found within typhoidal serovars tend to cluster separately from those found in nontyphoidal serovars, suggesting functional diversification. PMID:24727228

Statistical and dynamical forecast of regional precipitation after mature phase of ENSO

NASA Astrophysics Data System (ADS)

Sohn, S.; Min, Y.; Lee, J.; Tam, C.; Ahn, J.

2010-12-01

While the seasonal predictability of general circulation models (GCMs) has been improved, the current model atmosphere in the mid-latitude does not respond correctly to external forcing such as tropical sea surface temperature (SST), particularly over the East Asia and western North Pacific summer monsoon regions. In addition, the time-scale of prediction scope is considerably limited and the model forecast skill still is very poor beyond two weeks. Although recent studies indicate that coupled model based multi-model ensemble (MME) forecasts show the better performance, the long-lead forecasts exceeding 9 months still show a dramatic decrease of the seasonal predictability. This study aims at diagnosing the dynamical MME forecasts comprised of the state of art 1-tier models as well as comparing them with the statistical model forecasts, focusing on the East Asian summer precipitation predictions after mature phase of ENSO. The lagged impact of El Nino as major climate contributor on the summer monsoon in model environments is also evaluated, in the sense of the conditional probabilities. To evaluate the probability forecast skills, the reliability (attributes) diagram and the relative operating characteristics following the recommendations of the World Meteorological Organization (WMO) Standardized Verification System for Long-Range Forecasts are used in this study. The results should shed light on the prediction skill for dynamical model and also for the statistical model, in forecasting the East Asian summer monsoon rainfall with a long-lead time.

Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics.

PubMed

Ocone, Andrea; Millar, Andrew J; Sanguinetti, Guido

2013-04-01

Computational modelling of the dynamics of gene regulatory networks is a central task of systems biology. For networks of small/medium scale, the dominant paradigm is represented by systems of coupled non-linear ordinary differential equations (ODEs). ODEs afford great mechanistic detail and flexibility, but calibrating these models to data is often an extremely difficult statistical problem. Here, we develop a general statistical inference framework for stochastic transcription-translation networks. We use a coarse-grained approach, which represents the system as a network of stochastic (binary) promoter and (continuous) protein variables. We derive an exact inference algorithm and an efficient variational approximation that allows scalable inference and learning of the model parameters. We demonstrate the power of the approach on two biological case studies, showing that the method allows a high degree of flexibility and is capable of testable novel biological predictions. http://homepages.inf.ed.ac.uk/gsanguin/software.html. Supplementary data are available at Bioinformatics online.

OSSOS: X. How to use a Survey Simulator: Statistical Testing of Dynamical Models Against the Real Kuiper Belt

NASA Astrophysics Data System (ADS)

Lawler, Samantha M.; Kavelaars, J. J.; Alexandersen, Mike; Bannister, Michele T.; Gladman, Brett; Petit, Jean-Marc; Shankman, Cory

2018-05-01

All surveys include observational biases, which makes it impossible to directly compare properties of discovered trans-Neptunian Objects (TNOs) with dynamical models. However, by carefully keeping track of survey pointings on the sky, detection limits, tracking fractions, and rate cuts, the biases from a survey can be modelled in Survey Simulator software. A Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so that the biased simulated objects can be directly compared with real discoveries. This methodology has been used with great success in the Outer Solar System Origins Survey (OSSOS) and its predecessor surveys. In this chapter, we give four examples of ways to use the OSSOS Survey Simulator to gain knowledge about the true structure of the Kuiper Belt. We demonstrate how to statistically compare different dynamical model outputs with real TNO discoveries, how to quantify detection biases within a TNO population, how to measure intrinsic population sizes, and how to use upper limits from non-detections. We hope this will provide a framework for dynamical modellers to statistically test the validity of their models.

Statistical physics of language dynamics

NASA Astrophysics Data System (ADS)

Loreto, Vittorio; Baronchelli, Andrea; Mukherjee, Animesh; Puglisi, Andrea; Tria, Francesca

2011-04-01

Language dynamics is a rapidly growing field that focuses on all processes related to the emergence, evolution, change and extinction of languages. Recently, the study of self-organization and evolution of language and meaning has led to the idea that a community of language users can be seen as a complex dynamical system, which collectively solves the problem of developing a shared communication framework through the back-and-forth signaling between individuals. We shall review some of the progress made in the past few years and highlight potential future directions of research in this area. In particular, the emergence of a common lexicon and of a shared set of linguistic categories will be discussed, as examples corresponding to the early stages of a language. The extent to which synthetic modeling is nowadays contributing to the ongoing debate in cognitive science will be pointed out. In addition, the burst of growth of the web is providing new experimental frameworks. It makes available a huge amount of resources, both as novel tools and data to be analyzed, allowing quantitative and large-scale analysis of the processes underlying the emergence of a collective information and language dynamics.

Path integral molecular dynamics for exact quantum statistics of multi-electronic-state systems.

PubMed

Liu, Xinzijian; Liu, Jian

2018-03-14

An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD), Liu et al. [J. Chem. Phys. 145, 024103 (2016)] and Zhang et al. [J. Chem. Phys. 147, 034109 (2017)], for quantum statistical mechanics when a single potential energy surface is involved. We first define an effective potential function that is numerically favorable for MES-PIMD and then derive corresponding estimators in MES-PIMD for evaluating various physical properties. Its application to several representative one-dimensional and multi-dimensional models demonstrates that MES-PIMD in principle offers a practical tool in either of the diabatic and adiabatic representations for studying exact quantum statistics of complex/large MES systems when the Born-Oppenheimer approximation, Condon approximation, and harmonic bath approximation are broken.

Path integral molecular dynamics for exact quantum statistics of multi-electronic-state systems

NASA Astrophysics Data System (ADS)

Liu, Xinzijian; Liu, Jian

2018-03-01

An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD), Liu et al. [J. Chem. Phys. 145, 024103 (2016)] and Zhang et al. [J. Chem. Phys. 147, 034109 (2017)], for quantum statistical mechanics when a single potential energy surface is involved. We first define an effective potential function that is numerically favorable for MES-PIMD and then derive corresponding estimators in MES-PIMD for evaluating various physical properties. Its application to several representative one-dimensional and multi-dimensional models demonstrates that MES-PIMD in principle offers a practical tool in either of the diabatic and adiabatic representations for studying exact quantum statistics of complex/large MES systems when the Born-Oppenheimer approximation, Condon approximation, and harmonic bath approximation are broken.

More Than Filaments and Cores: Statistical Study of Structure Formation and Dynamics in Nearby Molecular Clouds

NASA Astrophysics Data System (ADS)

Chen, How-Huan; Goodman, Alyssa

2018-01-01

In the past decade, multiple attempts at understanding the connection between filaments and star forming cores have been made using observations across the entire epectrum. However, the filaments and the cores are usually treated as predefined--and well-defined--entities, instead of structures that often come at different sizes, shapes, with substantially different dynamics, and inter-connected at different scales. In my dissertation, I present an array of studies using different statistical methods, including the dendrogram and the probability distribution function (PDF), of structures at different size scales within nearby molecular clouds. These structures are identified using observations of different density tracers, and where possible, in the multi-dimensional parameter space of key dynamic properties--the LSR velocity, the velocity dispersion, and the column density. The goal is to give an overview of structure formation in nearby star-forming clouds, as well as of the dynamics in these structures. I find that the overall statistical properties of a larger structure is often the summation/superposition of sub-structures within, and that there could be significant variations due to local physical processes. I also find that the star formation process within molecular clouds could in fact take place in a non-monolithic manner, connecting potentially merging and/or transient structures, at different scales.

Delayed expression of hpS2 and prolonged expression of CIP1/WAF1/SDI1 in human tumour cells irradiated with X-rays, fission neutrons or 1 GeV/nucleon Fe ions

NASA Technical Reports Server (NTRS)

Balcer-Kubiczek, E. K.; Zhang, X. F.; Harrison, G. H.; Zhou, X. J.; Vigneulle, R. M.; Ove, R.; McCready, W. A.; Xu, J. F.

1999-01-01

PURPOSE: Differences in gene expression underlie the phenotypic differences between irradiated and unirradiated cells. The goal was to identify late-transcribed genes following irradiations differing in quality, and to determine the RBE of 1 GeV/n Fe ions. MATERIALS AND METHODS: Clonogenic assay was used to determine the RBE of Fe ions. Differential hybridization to cDNA target clones was used to detect differences in expression of corresponding genes in mRNA samples isolated from MCF7 cells irradiated with iso-survival doses of Fe ions (0 or 2.5 Gy) or fission neutrons (0 or 1.2 Gy) 7 days earlier. Northern analysis was used to confirm differential expression of cDNA-specific mRNA and to examine expression kinetics up to 2 weeks after irradiation. RESULTS: Fe ion RBE values were between 2.2 and 2.6 in the lines examined. Two of 17 differentially expressed cDNA clones were characterized. hpS2 mRNA was elevated from 1 to 14 days after irradiation, whereas CIP1/WAF1/SDI1 remained elevated from 3 h to 14 days after irradiation. Induction of hpS2 mRNA by irradiation was independent of p53, whereas induction of CIP1/WAF1/SDI1 was observed only in wild-type p53 lines. CONCLUSIONS: A set of coordinately regulated genes, some of which are independent of p53, is associated with change in gene expression during the first 2 weeks post-irradiation.

Statistical modelling of subdiffusive dynamics in the cytoplasm of living cells: A FARIMA approach

NASA Astrophysics Data System (ADS)

Burnecki, K.; Muszkieta, M.; Sikora, G.; Weron, A.

2012-04-01

Golding and Cox (Phys. Rev. Lett., 96 (2006) 098102) tracked the motion of individual fluorescently labelled mRNA molecules inside live E. coli cells. They found that in the set of 23 trajectories from 3 different experiments, the automatically recognized motion is subdiffusive and published an intriguing microscopy video. Here, we extract the corresponding time series from this video by image segmentation method and present its detailed statistical analysis. We find that this trajectory was not included in the data set already studied and has different statistical properties. It is best fitted by a fractional autoregressive integrated moving average (FARIMA) process with the normal-inverse Gaussian (NIG) noise and the negative memory. In contrast to earlier studies, this shows that the fractional Brownian motion is not the best model for the dynamics documented in this video.

Statistical Mechanical Derivation of Jarzynski's Identity for Thermostated Non-Hamiltonian Dynamics

NASA Astrophysics Data System (ADS)

Cuendet, Michel A.

2006-03-01

The recent Jarzynski identity (JI) relates thermodynamic free energy differences to nonequilibrium work averages. Several proofs of the JI have been provided on the thermodynamic level. They rely on assumptions such as equivalence of ensembles in the thermodynamic limit or weakly coupled infinite heat baths. However, the JI is widely applied to NVT computer simulations involving finite numbers of particles, whose equations of motion are strongly coupled to a few extra degrees of freedom modeling a thermostat. In this case, the above assumptions are no longer valid. We propose a statistical mechanical approach to the JI solely based on the specific equations of motion, without any further assumption. We provide a detailed derivation for the non-Hamiltonian Nosé-Hoover dynamics, which is routinely used in computer simulations to produce canonical sampling.

North American Extreme Temperature Events and Related Large Scale Meteorological Patterns: A Review of Statistical Methods, Dynamics, Modeling, and Trends

NASA Technical Reports Server (NTRS)

Grotjahn, Richard; Black, Robert; Leung, Ruby; Wehner, Michael F.; Barlow, Mathew; Bosilovich, Michael G.; Gershunov, Alexander; Gutowski, William J., Jr.; Gyakum, John R.; Katz, Richard W.;

Statistical benchmark for BosonSampling

NASA Astrophysics Data System (ADS)

Walschaers, Mattia; Kuipers, Jack; Urbina, Juan-Diego; Mayer, Klaus; Tichy, Malte Christopher; Richter, Klaus; Buchleitner, Andreas

2016-03-01

Boson samplers—set-ups that generate complex many-particle output states through the transmission of elementary many-particle input states across a multitude of mutually coupled modes—promise the efficient quantum simulation of a classically intractable computational task, and challenge the extended Church-Turing thesis, one of the fundamental dogmas of computer science. However, as in all experimental quantum simulations of truly complex systems, one crucial problem remains: how to certify that a given experimental measurement record unambiguously results from enforcing the claimed dynamics, on bosons, fermions or distinguishable particles? Here we offer a statistical solution to the certification problem, identifying an unambiguous statistical signature of many-body quantum interference upon transmission across a multimode, random scattering device. We show that statistical analysis of only partial information on the output state allows to characterise the imparted dynamics through particle type-specific features of the emerging interference patterns. The relevant statistical quantifiers are classically computable, define a falsifiable benchmark for BosonSampling, and reveal distinctive features of many-particle quantum dynamics, which go much beyond mere bunching or anti-bunching effects.

Developing a Web-based system by integrating VGI and SDI for real estate management and marketing

NASA Astrophysics Data System (ADS)

Salajegheh, J.; Hakimpour, F.; Esmaeily, A.

2014-10-01

Property importance of various aspects, especially the impact on various sectors of the economy and the country's macroeconomic is clear. Because of the real, multi-dimensional and heterogeneous nature of housing as a commodity, the lack of an integrated system includes comprehensive information of property, the lack of awareness of some actors in this field about comprehensive information about property and the lack of clear and comprehensive rules and regulations for the trading and pricing, several problems arise for the people involved in this field. In this research implementation of a crowd-sourced Web-based real estate support system is desired. Creating a Spatial Data Infrastructure (SDI) in this system for collecting, updating and integrating all official data about property is also desired in this study. In this system a Web2.0 broker and technologies such as Web services and service composition has been used. This work aims to provide comprehensive and diverse information about property from different sources. For this purpose five-level real estate support system architecture is used. PostgreSql DBMS is used to implement the desired system. Geoserver software is also used as map server and reference implementation of OGC (Open Geospatial Consortium) standards. And Apache server is used to run web pages and user interfaces. Integration introduced methods and technologies provide a proper environment for various users to use the system and share their information. This goal is only achieved by cooperation between all involved organizations in real estate with implementation their required infrastructures in interoperability Web services format.

Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

USGS Publications Warehouse

Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.

2015-01-01

Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total

Statistical and dynamical properties of a dissipative kicked rotator

NASA Astrophysics Data System (ADS)

Oliveira, Diego F. M.; Leonel, Edson D.

2014-11-01

Some dynamical and statistical properties for a conservative as well as the dissipative problem of relativistic particles in a waveguide are considered. For the first time, two different types of dissipation namely: (i) due to viscosity and; (ii) due to inelastic collision (upon the kick) are considered individually and acting together. For the first case, and contrary to what is expected for the original Zaslavsky’s relativistic model, we show there is a critical parameter where a transition from local to global chaos occurs. On the other hand, after considering the introduction of dissipation also on the kick, the structure of the phase space changes in the sense that chaotic and periodic attractors appear. We study also the chaotic sea by using scaling arguments and we proposed an analytical argument to reinforce the validity of the scaling exponents obtained numerically. In principle such an approach can be extended to any two-dimensional map. Finally, based on the Lyapunov exponent, we show that the parameter space exhibits infinite families of self-similar shrimp-shape structures, corresponding to periodic attractors, embedded in a large region corresponding to chaotic attractors.

Protein electron transfer: Dynamics and statistics

NASA Astrophysics Data System (ADS)

Matyushov, Dmitry V.

2013-07-01

Electron transfer between redox proteins participating in energy chains of biology is required to proceed with high energetic efficiency, minimizing losses of redox energy to heat. Within the standard models of electron transfer, this requirement, combined with the need for unidirectional (preferably activationless) transitions, is translated into the need to minimize the reorganization energy of electron transfer. This design program is, however, unrealistic for proteins whose active sites are typically positioned close to the polar and flexible protein-water interface to allow inter-protein electron tunneling. The high flexibility of the interfacial region makes both the hydration water and the surface protein layer act as highly polar solvents. The reorganization energy, as measured by fluctuations, is not minimized, but rather maximized in this region. Natural systems in fact utilize the broad breadth of interfacial electrostatic fluctuations, but in the ways not anticipated by the standard models based on equilibrium thermodynamics. The combination of the broad spectrum of static fluctuations with their dispersive dynamics offers the mechanism of dynamical freezing (ergodicity breaking) of subsets of nuclear modes on the time of reaction/residence of the electron at a redox cofactor. The separation of time-scales of nuclear modes coupled to electron transfer allows dynamical freezing. In particular, the separation between the relaxation time of electro-elastic fluctuations of the interface and the time of conformational transitions of the protein caused by changing redox state results in dynamical freezing of the latter for sufficiently fast electron transfer. The observable consequence of this dynamical freezing is significantly different reorganization energies describing the curvature at the bottom of electron-transfer free energy surfaces (large) and the distance between their minima (Stokes shift, small). The ratio of the two reorganization energies

Protein electron transfer: Dynamics and statistics.

PubMed

Matyushov, Dmitry V

2013-07-14

Electron transfer between redox proteins participating in energy chains of biology is required to proceed with high energetic efficiency, minimizing losses of redox energy to heat. Within the standard models of electron transfer, this requirement, combined with the need for unidirectional (preferably activationless) transitions, is translated into the need to minimize the reorganization energy of electron transfer. This design program is, however, unrealistic for proteins whose active sites are typically positioned close to the polar and flexible protein-water interface to allow inter-protein electron tunneling. The high flexibility of the interfacial region makes both the hydration water and the surface protein layer act as highly polar solvents. The reorganization energy, as measured by fluctuations, is not minimized, but rather maximized in this region. Natural systems in fact utilize the broad breadth of interfacial electrostatic fluctuations, but in the ways not anticipated by the standard models based on equilibrium thermodynamics. The combination of the broad spectrum of static fluctuations with their dispersive dynamics offers the mechanism of dynamical freezing (ergodicity breaking) of subsets of nuclear modes on the time of reaction/residence of the electron at a redox cofactor. The separation of time-scales of nuclear modes coupled to electron transfer allows dynamical freezing. In particular, the separation between the relaxation time of electro-elastic fluctuations of the interface and the time of conformational transitions of the protein caused by changing redox state results in dynamical freezing of the latter for sufficiently fast electron transfer. The observable consequence of this dynamical freezing is significantly different reorganization energies describing the curvature at the bottom of electron-transfer free energy surfaces (large) and the distance between their minima (Stokes shift, small). The ratio of the two reorganization energies

Minimal agent based model for financial markets II. Statistical properties of the linear and multiplicative dynamics

NASA Astrophysics Data System (ADS)

Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

2009-02-01

We present a detailed study of the statistical properties of the Agent Based Model introduced in paper I [Eur. Phys. J. B, DOI: 10.1140/epjb/e2009-00028-4] and of its generalization to the multiplicative dynamics. The aim of the model is to consider the minimal elements for the understanding of the origin of the stylized facts and their self-organization. The key elements are fundamentalist agents, chartist agents, herding dynamics and price behavior. The first two elements correspond to the competition between stability and instability tendencies in the market. The herding behavior governs the possibility of the agents to change strategy and it is a crucial element of this class of models. We consider a linear approximation for the price dynamics which permits a simple interpretation of the model dynamics and, for many properties, it is possible to derive analytical results. The generalized non linear dynamics results to be extremely more sensible to the parameter space and much more difficult to analyze and control. The main results for the nature and self-organization of the stylized facts are, however, very similar in the two cases. The main peculiarity of the non linear dynamics is an enhancement of the fluctuations and a more marked evidence of the stylized facts. We will also discuss some modifications of the model to introduce more realistic elements with respect to the real markets.

Defect-phase-dynamics approach to statistical domain-growth problem of clock models

NASA Technical Reports Server (NTRS)

Kawasaki, K.

1985-01-01

The growth of statistical domains in quenched Ising-like p-state clock models with p = 3 or more is investigated theoretically, reformulating the analysis of Ohta et al. (1982) in terms of a phase variable and studying the dynamics of defects introduced into the phase field when the phase variable becomes multivalued. The resulting defect/phase domain-growth equation is applied to the interpretation of Monte Carlo simulations in two dimensions (Kaski and Gunton, 1983; Grest and Srolovitz, 1984), and problems encountered in the analysis of related Potts models are discussed. In the two-dimensional case, the problem is essentially that of a purely dissipative Coulomb gas, with a sq rt t growth law complicated by vertex-pinning effects at small t.

Statistical Ensemble of Large Eddy Simulations

NASA Technical Reports Server (NTRS)

Carati, Daniele; Rogers, Michael M.; Wray, Alan A.; Mansour, Nagi N. (Technical Monitor)

2001-01-01

A statistical ensemble of large eddy simulations (LES) is run simultaneously for the same flow. The information provided by the different large scale velocity fields is used to propose an ensemble averaged version of the dynamic model. This produces local model parameters that only depend on the statistical properties of the flow. An important property of the ensemble averaged dynamic procedure is that it does not require any spatial averaging and can thus be used in fully inhomogeneous flows. Also, the ensemble of LES's provides statistics of the large scale velocity that can be used for building new models for the subgrid-scale stress tensor. The ensemble averaged dynamic procedure has been implemented with various models for three flows: decaying isotropic turbulence, forced isotropic turbulence, and the time developing plane wake. It is found that the results are almost independent of the number of LES's in the statistical ensemble provided that the ensemble contains at least 16 realizations.

Tsallis statistics and neurodegenerative disorders

NASA Astrophysics Data System (ADS)

Iliopoulos, Aggelos C.; Tsolaki, Magdalini; Aifantis, Elias C.

2016-08-01

In this paper, we perform statistical analysis of time series deriving from four neurodegenerative disorders, namely epilepsy, amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), Huntington's disease (HD). The time series are concerned with electroencephalograms (EEGs) of healthy and epileptic states, as well as gait dynamics (in particular stride intervals) of the ALS, PD and HDs. We study data concerning one subject for each neurodegenerative disorder and one healthy control. The analysis is based on Tsallis non-extensive statistical mechanics and in particular on the estimation of Tsallis q-triplet, namely {qstat, qsen, qrel}. The deviation of Tsallis q-triplet from unity indicates non-Gaussian statistics and long-range dependencies for all time series considered. In addition, the results reveal the efficiency of Tsallis statistics in capturing differences in brain dynamics between healthy and epileptic states, as well as differences between ALS, PD, HDs from healthy control subjects. The results indicate that estimations of Tsallis q-indices could be used as possible biomarkers, along with others, for improving classification and prediction of epileptic seizures, as well as for studying the gait complex dynamics of various diseases providing new insights into severity, medications and fall risk, improving therapeutic interventions.

Dynamic statistical optimization of GNSS radio occultation bending angles: advanced algorithm and performance analysis

NASA Astrophysics Data System (ADS)

Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.

2015-08-01

We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.

A Theory of Density Layering in Stratified Turbulence using Statistical State Dynamics

NASA Astrophysics Data System (ADS)

Fitzgerald, J.; Farrell, B.

2016-12-01

Stably stratified turbulent fluids commonly develop density structures that are layered in the vertical direction (e.g., Manucharyan et al., 2015). Within layers, density is approximately constant and stratification is weak. Between layers, density varies rapidly and stratification is strong. A common explanation for the existence of layers invokes the negative diffusion mechanism of Phillips (1972) & Posmentier (1977). The physical principle underlying this mechanism is that the flux-gradient relationship connecting the turbulent fluxes of buoyancy to the background stratification must have the special property of weakening fluxes with strengthening gradient. Under these conditions, the evolution of the stratification is governed by a negative diffusion problem which gives rise to spontaneous layer formation. In previous work on stratified layering, this flux-gradient property is often assumed (e.g, Posmentier, 1977) or drawn from phenomenological models of turbulence (e.g., Balmforth et al., 1998).In this work we develop the theoretical underpinnings of layer formation by applying stochastic turbulence modeling and statistical state dynamics (SSD) to predict the flux-gradient relation and analyze layer formation directly from the equations of motion. We show that for stochastically-forced homogeneous 2D Boussinesq turbulence, the flux-gradient relation can be obtained analytically and indicates that the fluxes always strengthen with stratification. The Phillips mechanism thus does not operate in this maximally simplified scenario. However, when the problem is augmented to include a large scale background shear, we show that the flux-gradient relationship is modified so that the fluxes weaken with stratification. Sheared and stratified 2D Boussinesq turbulence thus spontaneously forms density layers through the Phillips mechanism. Using SSD (Farrell & Ioannou 2003), we obtain a closed, deterministic dynamics for the stratification and the statistical turbulent

An Embedded Statistical Method for Coupling Molecular Dynamics and Finite Element Analyses

NASA Technical Reports Server (NTRS)

Saether, E.; Glaessgen, E.H.; Yamakov, V.

2008-01-01

The coupling of molecular dynamics (MD) simulations with finite element methods (FEM) yields computationally efficient models that link fundamental material processes at the atomistic level with continuum field responses at higher length scales. The theoretical challenge involves developing a seamless connection along an interface between two inherently different simulation frameworks. Various specialized methods have been developed to solve particular classes of problems. Many of these methods link the kinematics of individual MD atoms with FEM nodes at their common interface, necessarily requiring that the finite element mesh be refined to atomic resolution. Some of these coupling approaches also require simulations to be carried out at 0 K and restrict modeling to two-dimensional material domains due to difficulties in simulating full three-dimensional material processes. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the standard boundary value problem used to define a coupled domain. The method replaces a direct linkage of individual MD atoms and finite element (FE) nodes with a statistical averaging of atomistic displacements in local atomic volumes associated with each FE node in an interface region. The FEM and MD computational systems are effectively independent and communicate only through an iterative update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM). ESCM provides an enhanced coupling methodology that is inherently applicable to three-dimensional domains, avoids discretization of the continuum model to atomic scale resolution, and permits finite temperature states to be applied.

Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

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

Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.

Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan wasmore » performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and

Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs.

PubMed

Ingber, Lester; Nunez, Paul L

2011-02-01

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model. Copyright © 2010 Elsevier Inc. All rights reserved.

The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

PubMed

Bahlmann, Claus; Burkhardt, Hans

2004-03-01

In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution.

PubMed

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-08

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al . 2012 Proc. R. Soc. A 468 , 1799-1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi-Dirac or Bose-Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas.

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution

PubMed Central

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-01

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al. 2012 Proc. R. Soc. A 468, 1799–1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi–Dirac or Bose–Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas. PMID:24399919

A new spiral dental implant: a tool for oral rehabilitation of difficult cases.

PubMed

Balan, I; Calcaterra, R; Lauritano, D; Grecchi, E; Carinci, F

2017-01-01

Spiral dental implant (SDI) is an implant with a conical internal helix that confers the characteristic of self-drilling, self-tapping, and self-bone condensing. These proprieties offer better control during insertion of SDI giving a high primary stabilization, even in poor quality bone. A shorter diameter of SDI results in reduced drilling during insertion and consequently less trauma and minimal bone loss. To address the research purpose, the investigators designed a retrospective cohort study. The study population was composed of 25 patients, 11 males and 14 females that have been treated by Dr. Balan with 187 SDI positioned in mandible and into maxilla bone. The implants were placed during the years 2013 to 2014 in Dr. Balan clinic. All patients underwent the same surgical protocol. Several variables are investigated: demographic (age and gender), anatomic (upper/lower jaws and tooth site), implant (length and diameter and type) variables, edentulism (partial or total), and comorbid status of health (i.e.: hypothyroidism, parodontitis, hypertension, diabetes, presence of cancer, heart disease, hepatitis and rheumatologic disease). Pearson Chi-Square test was used to investigate variables and p < 0.05 was considered statistically significant. Statistically it has been shown that females have a higher possibility of unsuccessful respect of male, with a "p value" of 0.014. Another important impact factor for success of implant insertion has been represented by concomitants pathologies: cancer represents the most negative high factor risk with a percentage of unsuccessful of 50%, followed by heart disease (15%), and diabetes (3.7%). SDIs are reliable tools for difficult cases of oral rehabilitation. They have a higher success and survival rate, which means stable results over time. No differences were detected among SDI lengths, implant/crown ratio. In addition, the insertion of SDIs in banked bone can be performed without adverse effects. Finally, flapless and

Refining calibration and predictions of a Bayesian statistical-dynamical model for long term avalanche forecasting using dendrochronological reconstructions

NASA Astrophysics Data System (ADS)

Eckert, Nicolas; Schläppy, Romain; Jomelli, Vincent; Naaim, Mohamed

2013-04-01

A crucial step for proposing relevant long-term mitigation measures in long term avalanche forecasting is the accurate definition of high return period avalanches. Recently, "statistical-dynamical" approach combining a numerical model with stochastic operators describing the variability of its inputs-outputs have emerged. Their main interests is to take into account the topographic dependency of snow avalanche runout distances, and to constrain the correlation structure between model's variables by physical rules, so as to simulate the different marginal distributions of interest (pressure, flow depth, etc.) with a reasonable realism. Bayesian methods have been shown to be well adapted to achieve model inference, getting rid of identifiability problems thanks to prior information. An important problem which has virtually never been considered before is the validation of the predictions resulting from a statistical-dynamical approach (or from any other engineering method for computing extreme avalanches). In hydrology, independent "fossil" data such as flood deposits in caves are sometimes confronted to design discharges corresponding to high return periods. Hence, the aim of this work is to implement a similar comparison between high return period avalanches obtained with a statistical-dynamical approach and independent validation data resulting from careful dendrogeomorphological reconstructions. To do so, an up-to-date statistical model based on the depth-averaged equations and the classical Voellmy friction law is used on a well-documented case study. First, parameter values resulting from another path are applied, and the dendrological validation sample shows that this approach fails in providing realistic prediction for the case study. This may be due to the strongly bounded behaviour of runouts in this case (the extreme of their distribution is identified as belonging to the Weibull attraction domain). Second, local calibration on the available avalanche

Chandrasekhar's dynamical friction and non-extensive statistics

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

Silva, J.M.; Lima, J.A.S.; De Souza, R.E.

2016-05-01

The motion of a point like object of mass M passing through the background potential of massive collisionless particles ( m || M ) suffers a steady deceleration named dynamical friction. In his classical work, Chandrasekhar assumed a Maxwellian velocity distribution in the halo and neglected the self gravity of the wake induced by the gravitational focusing of the mass M . In this paper, by relaxing the validity of the Maxwellian distribution due to the presence of long range forces, we derive an analytical formula for the dynamical friction in the context of the q -nonextensive kinetic theory. Inmore » the extensive limiting case ( q = 1), the classical Gaussian Chandrasekhar result is recovered. As an application, the dynamical friction timescale for Globular Clusters spiraling to the galactic center is explicitly obtained. Our results suggest that the problem concerning the large timescale as derived by numerical N -body simulations or semi-analytical models can be understood as a departure from the standard extensive Maxwellian regime as measured by the Tsallis nonextensive q -parameter.« less

A comparison of dynamical and statistical downscaling methods for regional wave climate projections along French coastlines.

NASA Astrophysics Data System (ADS)

Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando

2013-04-01

Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical downscaling of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical downscaling method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at

Statistical State Dynamics Based Study of the Role of Nonlinearity in the Maintenance of Turbulence in Couette Flow

NASA Astrophysics Data System (ADS)

Farrell, Brian; Ioannou, Petros; Nikolaidis, Marios-Andreas

2017-11-01

While linear non-normality underlies the mechanism of energy transfer from the externally driven flow to the perturbation field, nonlinearity is also known to play an essential role in sustaining turbulence. We report a study based on the statistical state dynamics of Couette flow turbulence with the goal of better understanding the role of nonlinearity in sustaining turbulence. The statistical state dynamics implementations used are ensemble closures at second order in a cumulant expansion of the Navier-Stokes equations in which the averaging operator is the streamwise mean. Two fundamentally non-normal mechanisms potentially contributing to maintaining the second cumulant are identified. These are essentially parametric perturbation growth arising from interaction of the perturbations with the fluctuating mean flow and transient growth of perturbations arising from nonlinear interaction between components of the perturbation field. By the method of selectively including these mechanisms parametric growth is found to maintain the perturbation field in the turbulent state while the more commonly invoked mechanism associated with transient growth of perturbations arising from scattering by nonlinear interaction is found to suppress perturbation variance. Funded by ERC Coturb Madrid Summer Program and NSF AGS-1246929.

Uptake and biodegradation of the antimicrobial sulfadimidine by the species Tripolium pannonicum acting as biofilter and its further biodegradation by anaerobic digestion and concomitant biogas production.

PubMed

Turcios, Ariel E; Weichgrebe, Dirk; Papenbrock, Jutta

2016-11-01

This project analyses the uptake and biodegradation of the antimicrobial sulfadimidine (SDI) from the culture medium and up to the anaerobic digestion. Tripolium pannonicum was grown under hydroponic conditions with different concentrations of SDI (0, 5 and 10mg·L(-1)) and the fresh biomass, containing different amounts of SDI taken up, was used as substrate for biogas production. SDI was analyzed by liquid chromatography coupled to positive ion electrospray mass spectrometry (ESI LC-MS). Based on the findings, T. pannonicum is able to uptake SDI. The more SDI is in the culture medium, the higher the SDI content in the plant tissue. According to this study, it is possible to produce high yields of biogas using biomass of T. pannonicum containing SDI and at the same time biodegradation of SDI is carried out. The highest specific biogas yield is obtained using shoots as substrate of the plants cultivated at 5mg·L(-1) SDI. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments

PubMed Central

Avalappampatty Sivasamy, Aneetha; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

PubMed

Sivasamy, Aneetha Avalappampatty; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

A Statistical Approach for the Concurrent Coupling of Molecular Dynamics and Finite Element Methods

NASA Technical Reports Server (NTRS)

Saether, E.; Yamakov, V.; Glaessgen, E.

2007-01-01

Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, increasing the size of the MD domain quickly presents intractable computational demands. A robust approach to surmount this computational limitation has been to unite continuum modeling procedures such as the finite element method (FEM) with MD analyses thereby reducing the region of atomic scale refinement. The challenging problem is to seamlessly connect the two inherently different simulation techniques at their interface. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the typical boundary value problem used to define a coupled domain. The method uses statistical averaging of the atomistic MD domain to provide displacement interface boundary conditions to the surrounding continuum FEM region, which, in return, generates interface reaction forces applied as piecewise constant traction boundary conditions to the MD domain. The two systems are computationally disconnected and communicate only through a continuous update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM) as opposed to a direct coupling method where interface atoms and FEM nodes are individually related. The methodology is inherently applicable to three-dimensional domains, avoids discretization of the continuum model down to atomic scales, and permits arbitrary temperatures to be applied.

The non-statistical dynamics of the 18O + 32O2 isotope exchange reaction at two energies

NASA Astrophysics Data System (ADS)

Van Wyngarden, Annalise L.; Mar, Kathleen A.; Quach, Jim; Nguyen, Anh P. Q.; Wiegel, Aaron A.; Lin, Shi-Ying; Lendvay, Gyorgy; Guo, Hua; Lin, Jim J.; Lee, Yuan T.; Boering, Kristie A.

2014-08-01

The dynamics of the 18O(3P) + 32O2 isotope exchange reaction were studied using crossed atomic and molecular beams at collision energies (Ecoll) of 5.7 and 7.3 kcal/mol, and experimental results were compared with quantum statistical (QS) and quasi-classical trajectory (QCT) calculations on the O3(X1A') potential energy surface (PES) of Babikov et al. [D. Babikov, B. K. Kendrick, R. B. Walker, R. T. Pack, P. Fleurat-Lesard, and R. Schinke, J. Chem. Phys. 118, 6298 (2003)]. In both QS and QCT calculations, agreement with experiment was markedly improved by performing calculations with the experimental distribution of collision energies instead of fixed at the average collision energy. At both collision energies, the scattering displayed a forward bias, with a smaller bias at the lower Ecoll. Comparisons with the QS calculations suggest that 34O2 is produced with a non-statistical rovibrational distribution that is hotter than predicted, and the discrepancy is larger at the lower Ecoll. If this underprediction of rovibrational excitation by the QS method is not due to PES errors and/or to non-adiabatic effects not included in the calculations, then this collision energy dependence is opposite to what might be expected based on collision complex lifetime arguments and opposite to that measured for the forward bias. While the QCT calculations captured the experimental product vibrational energy distribution better than the QS method, the QCT results underpredicted rotationally excited products, overpredicted forward-bias and predicted a trend in the strength of forward-bias with collision energy opposite to that measured, indicating that it does not completely capture the dynamic behavior measured in the experiment. Thus, these results further underscore the need for improvement in theoretical treatments of dynamics on the O3(X1A') PES and perhaps of the PES itself in order to better understand and predict non-statistical effects in this reaction and in the formation

Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties

PubMed Central

Braun, Efrem; Carraro, Carlo; Smit, Berend

2017-01-01

Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes. PMID:28049851

Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties.

PubMed

Simon, Cory M; Braun, Efrem; Carraro, Carlo; Smit, Berend

2017-01-17

Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes.

Statistical analysis of dimer formation in supersaturated metal vapor based on molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Korenchenko, Anna E.; Vorontsov, Alexander G.; Gelchinski, Boris R.; Sannikov, Grigorii P.

2018-04-01

We discuss the problem of dimer formation during the homogeneous nucleation of atomic metal vapor in an inert gas environment. We simulated nucleation with molecular dynamics and carried out the statistical analysis of double- and triple-atomic collisions as the two ways of long-lived diatomic complex formation. Close pair of atoms with lifetime greater than the mean time interval between atom-atom collisions is called a long-lived diatomic complex. We found that double- and triple-atomic collisions gave approximately the same probabilities of long-lived diatomic complex formation, but internal energy of the resulted state was essentially lower in the second case. Some diatomic complexes formed in three-particle collisions are stable enough to be a critical nucleus.

Revealing physical interaction networks from statistics of collective dynamics

PubMed Central

Nitzan, Mor; Casadiego, Jose; Timme, Marc

2017-01-01

Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630

Communication Dynamics of Blog Networks

NASA Astrophysics Data System (ADS)

Goldberg, Mark; Kelley, Stephen; Magdon-Ismail, Malik; Mertsalov, Konstantin; Wallace, William (Al)

We study the communication dynamics of Blog networks, focusing on the Russian section of LiveJournal as a case study. Communication (blogger-to-blogger links) in such online communication networks is very dynamic: over 60% of the links in the network are new from one week to the next, though the set of bloggers remains approximately constant. Two fundamental questions are: (i) what models adequately describe such dynamic communication behavior; and (ii) how does one detect the phase transitions, i.e. the changes that go beyond the standard high-level dynamics? We approach these questions through the notion of stable statistics. We give strong experimental evidence to the fact that, despite the extreme amount of communication dynamics, several aggregate statistics are remarkably stable. We use stable statistics to test our models of communication dynamics postulating that any good model should produce values for these statistics which are both stable and close to the observed ones. Stable statistics can also be used to identify phase transitions, since any change in a normally stable statistic indicates a substantial change in the nature of the communication dynamics. We describe models of the communication dynamics in large social networks based on the principle of locality of communication: a node's communication energy is spent mostly within its own "social area," the locality of the node.

p21{sup WAF1/Cip1/Sdi1} knockout mice respond to doxorubicin with reduced cardiotoxicity

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

Terrand, Jerome; Xu, Beibei; Morrissy, Steve

2011-11-15

Doxorubicin (Dox) is an antineoplastic agent that can cause cardiomyopathy in humans and experimental animals. As an inducer of reactive oxygen species and a DNA damaging agent, Dox causes elevated expression of p21{sup WAF1/Cip1/Sdi1} (p21) gene. Elevated levels of p21 mRNA and p21 protein have been detected in the myocardium of mice following Dox treatment. With chronic treatment of Dox, wild type (WT) animals develop cardiomyopathy evidenced by elongated nuclei, mitochondrial swelling, myofilamental disarray, reduced cardiac output, reduced ejection fraction, reduced left ventricular contractility, and elevated expression of ANF gene. In contrast, p21 knockout (p21KO) mice did not show significantmore » changes in the same parameters in response to Dox treatment. In an effort to understand the mechanism of the resistance against Dox induced cardiomyopathy, we measured levels of antioxidant enzymes and found that p21KO mice did not contain elevated basal or inducible levels of glutathione peroxidase and catalase. Measurements of 6 circulating cytokines indicated elevation of IL-6, IL-12, IFN{gamma} and TNF{alpha} in Dox treated WT mice but not p21KO mice. Dox induced elevation of IL-6 mRNA was detected in the myocardium of WT mice but not p21KO mice. While the mechanism of the resistance against Dox induced cardiomyopathy remains unclear, lack of inflammatory response may contribute to the observed cardiac protection in p21KO mice. -- Highlights: Black-Right-Pointing-Pointer Doxorubicin induces p21 elevation in the myocardium. Black-Right-Pointing-Pointer Doxorubicin causes dilated cardiomyopathy in wild type mice. Black-Right-Pointing-Pointer p21 Knockout mice are resistant against doxorubicin induced cardiomyopathy. Black-Right-Pointing-Pointer Lack of inflammatory response correlates with the resistance in p21 knockout mice.« less

Infant Statistical Learning

PubMed Central

Saffran, Jenny R.; Kirkham, Natasha Z.

2017-01-01

Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories. PMID:28793812

Temporal scaling and spatial statistical analyses of groundwater level fluctuations

NASA Astrophysics Data System (ADS)

Sun, H.; Yuan, L., Sr.; Zhang, Y.

2017-12-01

Natural dynamics such as groundwater level fluctuations can exhibit multifractionality and/or multifractality due likely to multi-scale aquifer heterogeneity and controlling factors, whose statistics requires efficient quantification methods. This study explores multifractionality and non-Gaussian properties in groundwater dynamics expressed by time series of daily level fluctuation at three wells located in the lower Mississippi valley, after removing the seasonal cycle in the temporal scaling and spatial statistical analysis. First, using the time-scale multifractional analysis, a systematic statistical method is developed to analyze groundwater level fluctuations quantified by the time-scale local Hurst exponent (TS-LHE). Results show that the TS-LHE does not remain constant, implying the fractal-scaling behavior changing with time and location. Hence, we can distinguish the potentially location-dependent scaling feature, which may characterize the hydrology dynamic system. Second, spatial statistical analysis shows that the increment of groundwater level fluctuations exhibits a heavy tailed, non-Gaussian distribution, which can be better quantified by a Lévy stable distribution. Monte Carlo simulations of the fluctuation process also show that the linear fractional stable motion model can well depict the transient dynamics (i.e., fractal non-Gaussian property) of groundwater level, while fractional Brownian motion is inadequate to describe natural processes with anomalous dynamics. Analysis of temporal scaling and spatial statistics therefore may provide useful information and quantification to understand further the nature of complex dynamics in hydrology.

An online tool for Operational Probabilistic Drought Forecasting System (OPDFS): a Statistical-Dynamical Framework

NASA Astrophysics Data System (ADS)

Zarekarizi, M.; Moradkhani, H.; Yan, H.

2017-12-01

The Operational Probabilistic Drought Forecasting System (OPDFS) is an online tool recently developed at Portland State University for operational agricultural drought forecasting. This is an integrated statistical-dynamical framework issuing probabilistic drought forecasts monthly for the lead times of 1, 2, and 3 months. The statistical drought forecasting method utilizes copula functions in order to condition the future soil moisture values on the antecedent states. Due to stochastic nature of land surface properties, the antecedent soil moisture states are uncertain; therefore, data assimilation system based on Particle Filtering (PF) is employed to quantify the uncertainties associated with the initial condition of the land state, i.e. soil moisture. PF assimilates the satellite soil moisture data to Variable Infiltration Capacity (VIC) land surface model and ultimately updates the simulated soil moisture. The OPDFS builds on the NOAA's seasonal drought outlook by offering drought probabilities instead of qualitative ordinal categories and provides the user with the probability maps associated with a particular drought category. A retrospective assessment of the OPDFS showed that the forecasting of the 2012 Great Plains and 2014 California droughts were possible at least one month in advance. The OPDFS offers a timely assistance to water managers, stakeholders and decision-makers to develop resilience against uncertain upcoming droughts.

A probabilistic drought forecasting framework: A combined dynamical and statistical approach

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

Yan, Hongxiang; Moradkhani, Hamid; Zarekarizi, Mahkameh

In order to improve drought forecasting skill, this study develops a probabilistic drought forecasting framework comprised of dynamical and statistical modeling components. The novelty of this study is to seek the use of data assimilation to quantify initial condition uncertainty with the Monte Carlo ensemble members, rather than relying entirely on the hydrologic model or land surface model to generate a single deterministic initial condition, as currently implemented in the operational drought forecasting systems. Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function. The initialmore » condition at each forecast start date are sampled from the data assimilation ensembles for forecast initialization. Finally, seasonal drought forecasting products are generated with the updated initial conditions. This study introduces the theory behind the proposed drought forecasting system, with an application in Columbia River Basin, Pacific Northwest, United States. Results from both synthetic and real case studies suggest that the proposed drought forecasting system significantly improves the seasonal drought forecasting skills and can facilitate the state drought preparation and declaration, at least three months before the official state drought declaration.« less

Modeling Statistics of Fish Patchiness and Predicting Associated Influence on Statistics of Acoustic Echoes

DTIC Science & Technology

2014-12-01

moving relative to the water in which they are immersed, reflecting the true school movement dynamics . There has also been work to implement this...Engineering Department Woods Hole Oceanographic Institution 98 Water Street, MS #11 Woods Hole, MA 02543 9. SPONSORING/MONITORING AGENCY NAME(S) AND...were measured with multi-beam sonars and quantified in terms of important aspects offish dynamics ; and predictions were made of echo statistics of a

A new spiral dental implant: a tool for oral rehabilitation of difficult cases

PubMed Central

BALAN, I.; CALCATERRA, R.; LAURITANO, D.; GRECCHI, E.; CARINCI, F.

2017-01-01

SUMMARY Spiral dental implant (SDI) is an implant with a conical internal helix that confers the characteristic of self-drilling, self-tapping, and self-bone condensing. These proprieties offer better control during insertion of SDI giving a high primary stabilization, even in poor quality bone. A shorter diameter of SDI results in reduced drilling during insertion and consequently less trauma and minimal bone loss. To address the research purpose, the investigators designed a retrospective cohort study. The study population was composed of 25 patients, 11 males and 14 females that have been treated by Dr. Balan with 187 SDI positioned in mandible and into maxilla bone. The implants were placed during the years 2013 to 2014 in Dr. Balan clinic. All patients underwent the same surgical protocol. Several variables are investigated: demographic (age and gender), anatomic (upper/lower jaws and tooth site), implant (length and diameter and type) variables, edentulism (partial or total), and comorbid status of health (i.e.: hypothyroidism, parodontitis, hypertension, diabetes, presence of cancer, heart disease, hepatitis and rheumatologic disease). Pearson Chi-Square test was used to investigate variables and p < 0.05 was considered statistically significant. Statistically it has been shown that females have a higher possibility of unsuccessful respect of male, with a “p value” of 0.014. Another important impact factor for success of implant insertion has been represented by concomitants pathologies: cancer represents the most negative high factor risk with a percentage of unsuccessful of 50%, followed by heart disease (15%), and diabetes (3.7%). SDIs are reliable tools for difficult cases of oral rehabilitation. They have a higher success and survival rate, which means stable results over time. No differences were detected among SDI lengths, implant/crown ratio. In addition, the insertion of SDIs in banked bone can be performed without adverse effects. Finally

Contingency and statistical laws in replicate microbial closed ecosystems.

PubMed

Hekstra, Doeke R; Leibler, Stanislas

2012-05-25

Contingency, the persistent influence of past random events, pervades biology. To what extent, then, is each course of ecological or evolutionary dynamics unique, and to what extent are these dynamics subject to a common statistical structure? Addressing this question requires replicate measurements to search for emergent statistical laws. We establish a readily replicated microbial closed ecosystem (CES), sustaining its three species for years. We precisely measure the local population density of each species in many CES replicates, started from the same initial conditions and kept under constant light and temperature. The covariation among replicates of the three species densities acquires a stable structure, which could be decomposed into discrete eigenvectors, or "ecomodes." The largest ecomode dominates population density fluctuations around the replicate-average dynamics. These fluctuations follow simple power laws consistent with a geometric random walk. Thus, variability in ecological dynamics can be studied with CES replicates and described by simple statistical laws. Copyright © 2012 Elsevier Inc. All rights reserved.

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

NASA Astrophysics Data System (ADS)

Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling.

PubMed

Onisko, Agnieszka; Druzdzel, Marek J; Austin, R Marshall

2016-01-01

Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data. The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data. This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years. The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation. Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.

Segmenting Dynamic Human Action via Statistical Structure

ERIC Educational Resources Information Center

Baldwin, Dare; Andersson, Annika; Saffran, Jenny; Meyer, Meredith

2008-01-01

Human social, cognitive, and linguistic functioning depends on skills for rapidly processing action. Identifying distinct acts within the dynamic motion flow is one basic component of action processing; for example, skill at segmenting action is foundational to action categorization, verb learning, and comprehension of novel action sequences. Yet…

Zubarev's Nonequilibrium Statistical Operator Method in the Generalized Statistics of Multiparticle Systems

NASA Astrophysics Data System (ADS)

Glushak, P. A.; Markiv, B. B.; Tokarchuk, M. V.

2018-01-01

We present a generalization of Zubarev's nonequilibrium statistical operator method based on the principle of maximum Renyi entropy. In the framework of this approach, we obtain transport equations for the basic set of parameters of the reduced description of nonequilibrium processes in a classical system of interacting particles using Liouville equations with fractional derivatives. For a classical systems of particles in a medium with a fractal structure, we obtain a non-Markovian diffusion equation with fractional spatial derivatives. For a concrete model of the frequency dependence of a memory function, we obtain generalized Kettano-type diffusion equation with the spatial and temporal fractality taken into account. We present a generalization of nonequilibrium thermofield dynamics in Zubarev's nonequilibrium statistical operator method in the framework of Renyi statistics.

Statistical dynamics of religion evolutions

NASA Astrophysics Data System (ADS)

Ausloos, M.; Petroni, F.

2009-10-01

A religion affiliation can be considered as a “degree of freedom” of an agent on the human genre network. A brief review is given on the state of the art in data analysis and modelization of religious “questions” in order to suggest and if possible initiate further research, after using a “statistical physics filter”. We present a discussion of the evolution of 18 so-called religions, as measured through their number of adherents between 1900 and 2000. Some emphasis is made on a few cases presenting a minimum or a maximum in the investigated time range-thereby suggesting a competitive ingredient to be considered, besides the well accepted “at birth” attachment effect. The importance of the “external field” is still stressed through an Avrami late stage crystal growth-like parameter. The observed features and some intuitive interpretations point to opinion based models with vector, rather than scalar, like agents.

Universal renormalization-group dynamics at the onset of chaos in logistic maps and nonextensive statistical mechanics

NASA Astrophysics Data System (ADS)

Baldovin, F.; Robledo, A.

2002-10-01

We uncover the dynamics at the chaos threshold μ∞ of the logistic map and find that it consists of trajectories made of intertwined power laws that reproduce the entire period-doubling cascade that occurs for μ<μ∞. We corroborate this structure analytically via the Feigenbaum renormalization-group (RG) transformation and find that the sensitivity to initial conditions has precisely the form of a q exponential, of which we determine the q index and the q-generalized Lyapunov coefficient λq. Our results are an unequivocal validation of the applicability of the nonextensive generalization of Boltzmann-Gibbs statistical mechanics to critical points of nonlinear maps.

Andreev Bound States Formation and Quasiparticle Trapping in Quench Dynamics Revealed by Time-Dependent Counting Statistics.

PubMed

Souto, R Seoane; Martín-Rodero, A; Yeyati, A Levy

2016-12-23

We analyze the quantum quench dynamics in the formation of a phase-biased superconducting nanojunction. We find that in the absence of an external relaxation mechanism and for very general conditions the system gets trapped in a metastable state, corresponding to a nonequilibrium population of the Andreev bound states. The use of the time-dependent full counting statistics analysis allows us to extract information on the asymptotic population of even and odd many-body states, demonstrating that a universal behavior, dependent only on the Andreev state energy, is reached in the quantum point contact limit. These results shed light on recent experimental observations on quasiparticle trapping in superconducting atomic contacts.

Temperature- and composition-dependent hydrogen diffusivity in palladium from statistically-averaged molecular dynamics

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

Zhou, Xiaowang; Heo, Tae Wook; Wood, Brandon C.

Solid-state hydrogen storage materials undergo complex phase transformations whose kinetics is often limited by hydrogen diffusion. Among metal hydrides, palladium hydride undergoes a diffusional phase transformation upon hydrogen uptake, during which the hydrogen diffusivity varies with hydrogen composition and temperature. Here we perform robust statistically-averaged molecular dynamics simulations to obtain a well-converged analytical expression for hydrogen diffusivity in bulk palladium that is valid throughout all stages of the reaction. Our studies confirm significant dependence of the diffusivity on composition and temperature that elucidate key trends in the available experimental measurements. Whereas at low hydrogen compositions, a single process dominates, atmore » high hydrogen compositions, diffusion is found to exhibit behavior consistent with multiple hopping barriers. Further analysis, supported by nudged elastic band computations, suggests that the multi-barrier diffusion can be interpreted as two distinct mechanisms corresponding to hydrogen-rich and hydrogen-poor local environments.« less

Temperature- and composition-dependent hydrogen diffusivity in palladium from statistically-averaged molecular dynamics

DOE PAGES

Zhou, Xiaowang; Heo, Tae Wook; Wood, Brandon C.; ...

2018-03-09

Solid-state hydrogen storage materials undergo complex phase transformations whose kinetics is often limited by hydrogen diffusion. Among metal hydrides, palladium hydride undergoes a diffusional phase transformation upon hydrogen uptake, during which the hydrogen diffusivity varies with hydrogen composition and temperature. Here we perform robust statistically-averaged molecular dynamics simulations to obtain a well-converged analytical expression for hydrogen diffusivity in bulk palladium that is valid throughout all stages of the reaction. Our studies confirm significant dependence of the diffusivity on composition and temperature that elucidate key trends in the available experimental measurements. Whereas at low hydrogen compositions, a single process dominates, atmore » high hydrogen compositions, diffusion is found to exhibit behavior consistent with multiple hopping barriers. Further analysis, supported by nudged elastic band computations, suggests that the multi-barrier diffusion can be interpreted as two distinct mechanisms corresponding to hydrogen-rich and hydrogen-poor local environments.« less

Sensing water from subsurface drip irrigation laterals: In situ sensors, weighing lysimeters and COSMOS under vegetated and bare conditions

USDA-ARS?s Scientific Manuscript database

Characterization of soil water dynamics in the root zone under subsurface drip irrigated (SDI) is complicated by the three dimensional nature of water fluxes from drip emitters plus the fluxes, if any, of water from precipitation. In addition, soil water sensing systems may differ in their operating...

Statistical and dynamical assessment of land-ocean-atmosphere interactions across North Africa

NASA Astrophysics Data System (ADS)

Yu, Yan

North Africa is highly vulnerable to hydrologic variability and extremes, including impacts of climate change. The current understanding of oceanic versus terrestrial drivers of North African droughts and pluvials is largely model-based, with vast disagreement among models in terms of the simulated oceanic impacts and vegetation feedbacks. Regarding oceanic impacts, the relative importance of the tropical Pacific, tropical Indian, and tropical Atlantic Oceans in regulating the North African rainfall variability, as well as the underlying mechanism, remains debated among different modeling studies. Classic theory of land-atmosphere interactions across the Sahel ecotone, largely based on climate modeling experiments, has promoted positive vegetation-rainfall feedbacks associated with a dominant surface albedo mechanism. However, neither the proposed positive vegetation-rainfall feedback with its underlying albedo mechanism, nor its relative importance compared with oceanic drivers, has been convincingly demonstrated up to now using observational data. Here, the multivariate Generalized Equilibrium Feedback Assessment (GEFA) is applied in order to identify the observed oceanic and terrestrial drivers of North African climate and quantify their impacts. The reliability of the statistical GEFA method is first evaluated against dynamical experiments within the Community Earth System Model (CESM). In order to reduce the sampling error caused by short data records, the traditional GEFA approach is refined through stepwise GEFA, in which unimportant forcings are dropped through stepwise selection. In order to evaluate GEFA's reliability in capturing oceanic impacts, the atmospheric response to a sea-surface temperature (SST) forcing across the tropical Pacific, tropical Indian, and tropical Atlantic Ocean is estimated independently through ensembles of dynamical experiments and compared with GEFA-based assessments. Furthermore, GEFA's performance in capturing terrestrial

Predicting and attributing recent East African Spring droughts with dynamical-statistical climate model ensembles

NASA Astrophysics Data System (ADS)

Funk, C. C.; Shukla, S.; Hoerling, M. P.; Robertson, F. R.; Hoell, A.; Liebmann, B.

2013-12-01

During boreal spring, eastern portions of Kenya and Somalia have experienced more frequent droughts since 1999. Given the region's high levels of food insecurity, better predictions of these droughts could provide substantial humanitarian benefits. We show that dynamical-statistical seasonal climate forecasts, based on the latest generation of coupled atmosphere-ocean and uncoupled atmospheric models, effectively predict boreal spring rainfall in this area. Skill sources are assessed by comparing ensembles driven with full-ocean forcing with ensembles driven with ENSO-only sea surface temperatures (SSTs). Our analysis suggests that both ENSO and non-ENSO Indo-Pacific SST forcing have played an important role in the increase in drought frequencies. Over the past 30 years, La Niña drought teleconnections have strengthened, while non-ENSO Indo-Pacific convection patterns have also supported increased (decreased) Western Pacific (East African) rainfall. To further examine the relative contribution of ENSO, low frequency warming and the Pacific Decadal Oscillation, we present decompositions of ECHAM5, GFS, CAM4 and GMAO AMIP simulations. These decompositions suggest that rapid warming in the western Pacific and steeper western-to-central Pacific SST gradients have likely played an important role in the recent intensification of the Walker circulation, and the associated increase in East African aridity. A linear combination of time series describing the Pacific Decadal Oscillation and the strength of Indo-Pacific warming are shown to track East African rainfall reasonably well. The talk concludes with a few thoughts linking the potentially important interplay of attribution and prediction. At least for recent East African droughts, it appears that a characteristic Indo-Pacific SST and precipitation anomaly pattern can be linked statistically to support forecasts and attribution analyses. The combination of traditional AGCM attribution analyses with simple yet

Tsallis non-extensive statistics and solar wind plasma complexity

NASA Astrophysics Data System (ADS)

Pavlos, G. P.; Iliopoulos, A. C.; Zastenker, G. N.; Zelenyi, L. M.; Karakatsanis, L. P.; Riazantseva, M. O.; Xenakis, M. N.; Pavlos, E. G.

2015-03-01

This article presents novel results revealing non-equilibrium phase transition processes in the solar wind plasma during a strong shock event, which took place on 26th September 2011. Solar wind plasma is a typical case of stochastic spatiotemporal distribution of physical state variables such as force fields (B → , E →) and matter fields (particle and current densities or bulk plasma distributions). This study shows clearly the non-extensive and non-Gaussian character of the solar wind plasma and the existence of multi-scale strong correlations from the microscopic to the macroscopic level. It also underlines the inefficiency of classical magneto-hydro-dynamic (MHD) or plasma statistical theories, based on the classical central limit theorem (CLT), to explain the complexity of the solar wind dynamics, since these theories include smooth and differentiable spatial-temporal functions (MHD theory) or Gaussian statistics (Boltzmann-Maxwell statistical mechanics). On the contrary, the results of this study indicate the presence of non-Gaussian non-extensive statistics with heavy tails probability distribution functions, which are related to the q-extension of CLT. Finally, the results of this study can be understood in the framework of modern theoretical concepts such as non-extensive statistical mechanics (Tsallis, 2009), fractal topology (Zelenyi and Milovanov, 2004), turbulence theory (Frisch, 1996), strange dynamics (Zaslavsky, 2002), percolation theory (Milovanov, 1997), anomalous diffusion theory and anomalous transport theory (Milovanov, 2001), fractional dynamics (Tarasov, 2013) and non-equilibrium phase transition theory (Chang, 1992).

Oncogenic functions of tumour suppressor p21(Waf1/Cip1/Sdi1): association with cell senescence and tumour-promoting activities of stromal fibroblasts.

PubMed

Roninson, Igor B

2002-05-08

p21(Waf1/Cip1/Sdi1) is best known as a broad-specificity inhibitor of cyclin/cyclin-dependent kinase complexes, but p21 also interacts with many other regulators of transcription or signal transduction. p21 induction, which is mediated by p53 and by p53-independent mechanisms, is essential for the onset of cell cycle arrest in damage response and cell senescence. The effects of p21 knockout in mice and its expression patterns in human cancer are consistent with a role for p21 as both a tumour suppressor and an oncogene. Several functions of p21 are likely to promote carcinogenesis and tumour progression. These include endoreduplication and abnormal mitosis that develop in tumour cells after release from p21-induced growth arrest, the ability of p21 to inhibit apoptosis through several different mechanisms, and its ability to stimulate transcription of secreted factors with mitogenic and anti-apoptotic activities. The latter effects of p21 show close resemblance to paracrine activities of senescent cells and to tumour-promoting functions of stromal fibroblasts. Therapeutic strategies targeting the oncogenic consequences of p21 expression may provide a new approach to chemoprevention and treatment of cancer.

Exploring the String Landscape: The Dynamics, Statistics, and Cosmology of Parallel Worlds

NASA Astrophysics Data System (ADS)

Ahlqvist, Stein Pontus

This dissertation explores various facets of the low-energy solutions in string theory known as the string landscape. Three separate questions are addressed - the tunneling dynamics between these vacua, the statistics of their location in moduli space, and the potential realization of slow-roll inflation in the flux potentials generated in string theory. We find that the tunneling transitions that occur between a certain class of supersymmetric vacua related to each other via monodromies around the conifold point are sensitive to the details of warping in the near-conifold regime. We also study the impact of warping on the distribution of vacua near the conifold and determine that while previous work has concluded that the conifold point acts as an accumulation point for vacua, warping highly dilutes the distribution in precisely this regime. Finally we investigate a novel form of inflation dubbed spiral inflation to see if it can be realized near the conifold point. We conclude that for our particular models, spiral inflation seems to rely on a de Sitter-like vacuum energy. As a result, whenever spiral inflation is realized, the inflation is actually driven by a vacuum energy.

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. Part 2: Theoretical development of a dynamic model and application to rain fade durations and tolerable control delays for fade countermeasures

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1987-01-01

A dynamic rain attenuation prediction model is developed for use in obtaining the temporal characteristics, on time scales of minutes or hours, of satellite communication link availability. Analagous to the associated static rain attenuation model, which yields yearly attenuation predictions, this dynamic model is applicable at any location in the world that is characterized by the static rain attenuation statistics peculiar to the geometry of the satellite link and the rain statistics of the location. Such statistics are calculated by employing the formalism of Part I of this report. In fact, the dynamic model presented here is an extension of the static model and reduces to the static model in the appropriate limit. By assuming that rain attenuation is dynamically described by a first-order stochastic differential equation in time and that this random attenuation process is a Markov process, an expression for the associated transition probability is obtained by solving the related forward Kolmogorov equation. This transition probability is then used to obtain such temporal rain attenuation statistics as attenuation durations and allowable attenuation margins versus control system delay.

Statistical dependency in visual scanning

NASA Technical Reports Server (NTRS)

Ellis, Stephen R.; Stark, Lawrence

1986-01-01

A method to identify statistical dependencies in the positions of eye fixations is developed and applied to eye movement data from subjects who viewed dynamic displays of air traffic and judged future relative position of aircraft. Analysis of approximately 23,000 fixations on points of interest on the display identified statistical dependencies in scanning that were independent of the physical placement of the points of interest. Identification of these dependencies is inconsistent with random-sampling-based theories used to model visual search and information seeking.

Forecasting experiments of a dynamical-statistical model of the sea surface temperature anomaly field based on the improved self-memorization principle

NASA Astrophysics Data System (ADS)

Hong, Mei; Chen, Xi; Zhang, Ren; Wang, Dong; Shen, Shuanghe; Singh, Vijay P.

2018-04-01

With the objective of tackling the problem of inaccurate long-term El Niño-Southern Oscillation (ENSO) forecasts, this paper develops a new dynamical-statistical forecast model of the sea surface temperature anomaly (SSTA) field. To avoid single initial prediction values, a self-memorization principle is introduced to improve the dynamical reconstruction model, thus making the model more appropriate for describing such chaotic systems as ENSO events. The improved dynamical-statistical model of the SSTA field is used to predict SSTA in the equatorial eastern Pacific and during El Niño and La Niña events. The long-term step-by-step forecast results and cross-validated retroactive hindcast results of time series T1 and T2 are found to be satisfactory, with a Pearson correlation coefficient of approximately 0.80 and a mean absolute percentage error (MAPE) of less than 15 %. The corresponding forecast SSTA field is accurate in that not only is the forecast shape similar to the actual field but also the contour lines are essentially the same. This model can also be used to forecast the ENSO index. The temporal correlation coefficient is 0.8062, and the MAPE value of 19.55 % is small. The difference between forecast results in spring and those in autumn is not high, indicating that the improved model can overcome the spring predictability barrier to some extent. Compared with six mature models published previously, the present model has an advantage in prediction precision and length, and is a novel exploration of the ENSO forecast method.

Modeling of adsorption dynamics at air-liquid interfaces using statistical rate theory (SRT).

PubMed

Biswas, M E; Chatzis, I; Ioannidis, M A; Chen, P

2005-06-01

A large number of natural and technological processes involve mass transfer at interfaces. Interfacial properties, e.g., adsorption, play a key role in such applications as wetting, foaming, coating, and stabilizing of liquid films. The mechanistic understanding of surface adsorption often assumes molecular diffusion in the bulk liquid and subsequent adsorption at the interface. Diffusion is well described by Fick's law, while adsorption kinetics is less understood and is commonly described using Langmuir-type empirical equations. In this study, a general theoretical model for adsorption kinetics/dynamics at the air-liquid interface is developed; in particular, a new kinetic equation based on the statistical rate theory (SRT) is derived. Similar to many reported kinetic equations, the new kinetic equation also involves a number of parameters, but all these parameters are theoretically obtainable. In the present model, the adsorption dynamics is governed by three dimensionless numbers: psi (ratio of adsorption thickness to diffusion length), lambda (ratio of square of the adsorption thickness to the ratio of adsorption to desorption rate constant), and Nk (ratio of the adsorption rate constant to the product of diffusion coefficient and bulk concentration). Numerical simulations for surface adsorption using the proposed model are carried out and verified. The difference in surface adsorption between the general and the diffusion controlled model is estimated and presented graphically as contours of deviation. Three different regions of adsorption dynamics are identified: diffusion controlled (deviation less than 10%), mixed diffusion and transfer controlled (deviation in the range of 10-90%), and transfer controlled (deviation more than 90%). These three different modes predominantly depend on the value of Nk. The corresponding ranges of Nk for the studied values of psi (10(-2)

[Statistical approach to evaluate the occurrence of out-of acceptable ranges and accuracy for antimicrobial susceptibility tests in inter-laboratory quality control program].

PubMed

Ueno, Tamio; Matuda, Junichi; Yamane, Nobuhisa

2013-03-01

To evaluate the occurrence of out-of acceptable ranges and accuracy of antimicrobial susceptibility tests, we applied a new statistical tool to the Inter-Laboratory Quality Control Program established by the Kyushu Quality Control Research Group. First, we defined acceptable ranges of minimum inhibitory concentration (MIC) for broth microdilution tests and inhibitory zone diameter for disk diffusion tests on the basis of Clinical and Laboratory Standards Institute (CLSI) M100-S21. In the analysis, more than two out-of acceptable range results in the 20 tests were considered as not allowable according to the CLSI document. Of the 90 participating laboratories, 46 (51%) experienced one or more occurrences of out-of acceptable range results. Then, a binomial test was applied to each participating laboratory. The results indicated that the occurrences of out-of acceptable range results in the 11 laboratories were significantly higher when compared to the CLSI recommendation (allowable rate < or = 0.05). The standard deviation indices(SDI) were calculated by using reported results, mean and standard deviation values for the respective antimicrobial agents tested. In the evaluation of accuracy, mean value from each laboratory was statistically compared with zero using a Student's t-test. The results revealed that 5 of the 11 above laboratories reported erroneous test results that systematically drifted to the side of resistance. In conclusion, our statistical approach has enabled us to detect significantly higher occurrences and source of interpretive errors in antimicrobial susceptibility tests; therefore, this approach can provide us with additional information that can improve the accuracy of the test results in clinical microbiology laboratories.

Predicting and downscaling ENSO impacts on intraseasonal precipitation statistics in California: The 1997/98 event

USGS Publications Warehouse

Gershunov, A.; Barnett, T.P.; Cayan, D.R.; Tubbs, T.; Goddard, L.

2000-01-01

Three long-range forecasting methods have been evaluated for prediction and downscaling of seasonal and intraseasonal precipitation statistics in California. Full-statistical, hybrid-dynamical - statistical and full-dynamical approaches have been used to forecast El Nin??o - Southern Oscillation (ENSO) - related total precipitation, daily precipitation frequency, and average intensity anomalies during the January - March season. For El Nin??o winters, the hybrid approach emerges as the best performer, while La Nin??a forecasting skill is poor. The full-statistical forecasting method features reasonable forecasting skill for both La Nin??a and El Nin??o winters. The performance of the full-dynamical approach could not be evaluated as rigorously as that of the other two forecasting schemes. Although the full-dynamical forecasting approach is expected to outperform simpler forecasting schemes in the long run, evidence is presented to conclude that, at present, the full-dynamical forecasting approach is the least viable of the three, at least in California. The authors suggest that operational forecasting of any intraseasonal temperature, precipitation, or streamflow statistic derivable from the available records is possible now for ENSO-extreme years.

Statistical Model of Dynamic Markers of the Alzheimer's Pathological Cascade.

PubMed

Balsis, Steve; Geraci, Lisa; Benge, Jared; Lowe, Deborah A; Choudhury, Tabina K; Tirso, Robert; Doody, Rachelle S

2018-05-05

Alzheimer's disease (AD) is a progressive disease reflected in markers across assessment modalities, including neuroimaging, cognitive testing, and evaluation of adaptive function. Identifying a single continuum of decline across assessment modalities in a single sample is statistically challenging because of the multivariate nature of the data. To address this challenge, we implemented advanced statistical analyses designed specifically to model complex data across a single continuum. We analyzed data from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1,056), focusing on indicators from the assessments of magnetic resonance imaging (MRI) volume, fluorodeoxyglucose positron emission tomography (FDG-PET) metabolic activity, cognitive performance, and adaptive function. Item response theory was used to identify the continuum of decline. Then, through a process of statistical scaling, indicators across all modalities were linked to that continuum and analyzed. Findings revealed that measures of MRI volume, FDG-PET metabolic activity, and adaptive function added measurement precision beyond that provided by cognitive measures, particularly in the relatively mild range of disease severity. More specifically, MRI volume, and FDG-PET metabolic activity become compromised in the very mild range of severity, followed by cognitive performance and finally adaptive function. Our statistically derived models of the AD pathological cascade are consistent with existing theoretical models.

A neural network model of metaphor understanding with dynamic interaction based on a statistical language analysis: targeting a human-like model.

PubMed

Terai, Asuka; Nakagawa, Masanori

2007-08-01

The purpose of this paper is to construct a model that represents the human process of understanding metaphors, focusing specifically on similes of the form an "A like B". Generally speaking, human beings are able to generate and understand many sorts of metaphors. This study constructs the model based on a probabilistic knowledge structure for concepts which is computed from a statistical analysis of a large-scale corpus. Consequently, this model is able to cover the many kinds of metaphors that human beings can generate. Moreover, the model implements the dynamic process of metaphor understanding by using a neural network with dynamic interactions. Finally, the validity of the model is confirmed by comparing model simulations with the results from a psychological experiment.

Nonequilibrium Statistical Operator Method and Generalized Kinetic Equations

NASA Astrophysics Data System (ADS)

Kuzemsky, A. L.

2018-01-01

We consider some principal problems of nonequilibrium statistical thermodynamics in the framework of the Zubarev nonequilibrium statistical operator approach. We present a brief comparative analysis of some approaches to describing irreversible processes based on the concept of nonequilibrium Gibbs ensembles and their applicability to describing nonequilibrium processes. We discuss the derivation of generalized kinetic equations for a system in a heat bath. We obtain and analyze a damped Schrödinger-type equation for a dynamical system in a heat bath. We study the dynamical behavior of a particle in a medium taking the dissipation effects into account. We consider the scattering problem for neutrons in a nonequilibrium medium and derive a generalized Van Hove formula. We show that the nonequilibrium statistical operator method is an effective, convenient tool for describing irreversible processes in condensed matter.

Computationally efficient statistical differential equation modeling using homogenization

USGS Publications Warehouse

Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.

2013-01-01

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Effects of the magnetic field direction on the Tsallis statistic

NASA Astrophysics Data System (ADS)

González-Casanova, Diego F.; Lazarian, A.; Cho, J.

2018-04-01

We extend the use of the Tsallis statistic to measure the differences in gas dynamics relative to the mean magnetic field present from natural eddy-type motions existing in magnetohydrodynamical (MHD) turbulence. The variation in gas dynamics was estimated using the Tsallis parameters on the incremental probability distribution function of the observables (intensity and velocity centroid) obtained from compressible MHD simulations. We find that the Tsallis statistic is susceptible to the anisotropy produced by the magnetic field, even when anisotropy is present the Tsallis statistic can be used to determine MHD parameters such as the Sonic Mach number. We quantize the goodness of the Tsallis parameters using the coefficient of determination to measure the differences in the gas dynamics. These parameters also determine the level of magnetization and compressibility of the medium. To further simulate realistic spectroscopic observational data, we introduced smoothing, noise, and cloud boundaries to the MHD simulations.

Dynamically biased statistical model for the ortho/para conversion in the H2+H3+ --> H3++ H2 reaction

NASA Astrophysics Data System (ADS)

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-01

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007), 10.1063/1.2430711]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H_5^+ complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H_5^+ complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011), 10.1063/1.3587246] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Dynamic Statistical Models for Pyroclastic Density Current Generation at Soufrière Hills Volcano

NASA Astrophysics Data System (ADS)

Wolpert, Robert L.; Spiller, Elaine T.; Calder, Eliza S.

2018-05-01

To mitigate volcanic hazards from pyroclastic density currents, volcanologists generate hazard maps that provide long-term forecasts of areas of potential impact. Several recent efforts in the field develop new statistical methods for application of flow models to generate fully probabilistic hazard maps that both account for, and quantify, uncertainty. However a limitation to the use of most statistical hazard models, and a key source of uncertainty within them, is the time-averaged nature of the datasets by which the volcanic activity is statistically characterized. Where the level, or directionality, of volcanic activity frequently changes, e.g. during protracted eruptive episodes, or at volcanoes that are classified as persistently active, it is not appropriate to make short term forecasts based on longer time-averaged metrics of the activity. Thus, here we build, fit and explore dynamic statistical models for the generation of pyroclastic density current from Soufrière Hills Volcano (SHV) on Montserrat including their respective collapse direction and flow volumes based on 1996-2008 flow datasets. The development of this approach allows for short-term behavioral changes to be taken into account in probabilistic volcanic hazard assessments. We show that collapses from the SHV lava dome follow a clear pattern, and that a series of smaller flows in a given direction often culminate in a larger collapse and thereafter directionality of the flows change. Such models enable short term forecasting (weeks to months) that can reflect evolving conditions such as dome and crater morphology changes and non-stationary eruptive behavior such as extrusion rate variations. For example, the probability of inundation of the Belham Valley in the first 180 days of a forecast period is about twice as high for lava domes facing Northwest toward that valley as it is for domes pointing East toward the Tar River Valley. As rich multi-parametric volcano monitoring dataset become

Reineke’s stand density index: a quantitative and non-unitless measure of stand density

Treesearch

Curtis L. VanderSchaaf

2013-01-01

When used as a measure of relative density, Reineke’s stand density index (SDI) can be made unitless by relating the current SDI to a standard density but when used as a quantitative measure of stand density SDI is not unitless. Reineke’s SDI relates the current stand density to an equivalent number of trees per unit area in a stand with a quadratic mean diameter (Dq)...

Statistical ecology comes of age

PubMed Central

Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-01-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data. PMID:25540151

Statistical ecology comes of age.

PubMed

Gimenez, Olivier; Buckland, Stephen T; Morgan, Byron J T; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-12-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

Are self-thinning contraints needed in a tree-specific mortality model.

Treesearch

Robert A. Monserud; Thomas Ledermann; Hubert Sterba

2005-01-01

Can a tree-specific mortality model elicit expected forest stand density dynamics without imposing stand-level constraints such as Reineke's maximum stand density index (SDI,) or the -312 power law of self-thinning? We examine this emergent properties question using the Austrian stand simulator PROGNAUS. This simulator was chosen specifically because it does not...

Dynamical Systems Theory in Quantitative Psychology and Cognitive Science: A Fair Discrimination between Deterministic and Statistical Counterparts is Required.

PubMed

Gadomski, Adam; Ausloos, Marcel; Casey, Tahlia

2017-04-01

This article addresses a set of observations framed in both deterministic as well as statistical formal guidelines. It operates within the framework of nonlinear dynamical systems theory (NDS). It is argued that statistical approaches can manifest themselves ambiguously, creating practical discrepancies in psychological and cognitive data analyses both quantitatively and qualitatively. This is sometimes termed in literature as 'questionable research practices.' This communication points to the demand for a deeper awareness of the data 'initial conditions, allowing to focus on pertinent evolution constraints in such systems.' It also considers whether the exponential (Malthus-type) or the algebraic (Pareto-type) statistical distribution ought to be effectively considered in practical interpretations. The role of repetitive specific behaviors by patients seeking treatment is examined within the NDS frame. The significance of these behaviors, involving a certain memory effect seems crucial in determining a patient's progression or regression. With this perspective, it is discussed how a sensitively applied hazardous or triggering factor can be helpful for well-controlled psychological strategic treatments; those attributable to obsessive-compulsive disorders or self-injurious behaviors are recalled in particular. There are both inherent criticality- and complexity-exploiting (reduced-variance based) relations between a therapist and a patient that can be intrinsically included in NDS theory.

Long-term organ damage accrual and safety in patients with SLE treated with belimumab plus standard of care.

PubMed

Bruce, I N; Urowitz, M; van Vollenhoven, R; Aranow, C; Fettiplace, J; Oldham, M; Wilson, B; Molta, C; Roth, D; Gordon, D

2016-06-01

To examine long-term organ damage and safety following treatment with belimumab plus standard of care (SoC) in patients with systemic lupus erythematosus (SLE). Pooled data were examined from two ongoing open-label studies that enrolled patients who completed BLISS-52 or BLISS-76. Patients received belimumab every four weeks plus SoC. SLICC Damage Index (SDI) values were assessed every 48 weeks (study years) following belimumab initiation (baseline). The primary endpoint was change in SDI from baseline at study years 5-6. Incidences of adverse events (AEs) were reported for the entire study period. The modified intent-to-treat (MITT) population comprised 998 patients. At baseline, 940 (94.2%) were female, mean (SD) age was 38.7 (11.49) years, and disease duration was 6.7 (6.24) years. The mean (SD) SELENA-SLEDAI and SDI scores were 8.2 (4.18) and 0.7 (1.19), respectively; 411 (41.2%) patients had organ damage (SDI = 1: 235 (23.5%); SDI ≥ 2: 176 (17.6%)) prior to belimumab. A total of 427 (42.8%) patients withdrew overall; the most common reasons were patient request (16.8%) and AEs (8.5%).The mean (SD) change in SDI was +0.2 (0.48) at study years 5-6 (n = 403); 343 (85.1%) patients had no change from baseline in SDI score (SDI +1: 46 (11.4%), SDI +2: 13 (3.2%), SDI +3: 1 (0.2%)). Of patients without organ damage at baseline, 211/241 (87.6%) had no change in SDI and the mean change (SD) in SDI was +0.2 (0.44). Of patients with organ damage at baseline, 132/162 (81.5%) had no change in SDI and the mean (SD) change in SDI was +0.2 (0.53). The probability of not having a worsening in SDI score was 0.88 (95% CI: 0.85, 0.91) and 0.75 (0.67, 0.81) in those without and with baseline damage, respectively (post hoc analysis).Drug-related AEs were reported for 433 (43.4%) patients; infections/infestations (282, 28.3%) and gastrointestinal disorders (139, 13.9%) were the most common. Patients with SLE treated with long-term belimumab plus SoC had a low incidence

Effect of air injection under subsurface drip irrigation on yield and water use efficiency of corn in a sandy clay loam soil

PubMed Central

Abuarab, Mohamed; Mostafa, Ehab; Ibrahim, Mohamed

2012-01-01

Subsurface drip irrigation (SDI) can substantially reduce the amount of irrigation water needed for corn production. However, corn yields need to be improved to offset the initial cost of drip installation. Air-injection is at least potentially applicable to the (SDI) system. However, the vertical stream of emitted air moving above the emitter outlet directly toward the surface creates a chimney effect, which should be avoided, and to ensure that there are adequate oxygen for root respiration. A field study was conducted in 2010 and 2011, to evaluate the effect of air-injection into the irrigation stream in SDI on the performance of corn. Experimental treatments were drip irrigation (DI), SDI, and SDI with air injection. The leaf area per plant with air injected was 1.477 and 1.0045 times greater in the aerated treatment than in DI and SDI, respectively. Grain filling was faster, and terminated earlier under air-injected drip system, than in DI. Root distribution, stem diameter, plant height and number of grains per plant were noticed to be higher under air injection than DI and SDI. Air injection had the highest water use efficiency (WUE) and irrigation water use efficiency (IWUE) in both growing seasons; with values of 1.442 and 1.096 in 2010 and 1.463 and 1.112 in 2011 for WUE and IWUE respectively. In comparison with DI and SDI, the air injection treatment achieved a significantly higher productivity through the two seasons. Yield increases due to air injection were 37.78% and 12.27% greater in 2010 and 38.46% and 12.5% in 2011 compared to the DI and SDI treatments, respectively. Data from this study indicate that corn yield can be improved under SDI if the drip water is aerated. PMID:25685457

Kinetic Analysis of Dynamic Positron Emission Tomography Data using Open-Source Image Processing and Statistical Inference Tools.

PubMed

Hawe, David; Hernández Fernández, Francisco R; O'Suilleabháin, Liam; Huang, Jian; Wolsztynski, Eric; O'Sullivan, Finbarr

2012-05-01

In dynamic mode, positron emission tomography (PET) can be used to track the evolution of injected radio-labelled molecules in living tissue. This is a powerful diagnostic imaging technique that provides a unique opportunity to probe the status of healthy and pathological tissue by examining how it processes substrates. The spatial aspect of PET is well established in the computational statistics literature. This article focuses on its temporal aspect. The interpretation of PET time-course data is complicated because the measured signal is a combination of vascular delivery and tissue retention effects. If the arterial time-course is known, the tissue time-course can typically be expressed in terms of a linear convolution between the arterial time-course and the tissue residue. In statistical terms, the residue function is essentially a survival function - a familiar life-time data construct. Kinetic analysis of PET data is concerned with estimation of the residue and associated functionals such as flow, flux, volume of distribution and transit time summaries. This review emphasises a nonparametric approach to the estimation of the residue based on a piecewise linear form. Rapid implementation of this by quadratic programming is described. The approach provides a reference for statistical assessment of widely used one- and two-compartmental model forms. We illustrate the method with data from two of the most well-established PET radiotracers, (15)O-H(2)O and (18)F-fluorodeoxyglucose, used for assessment of blood perfusion and glucose metabolism respectively. The presentation illustrates the use of two open-source tools, AMIDE and R, for PET scan manipulation and model inference.

Dynamical-statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models

NASA Astrophysics Data System (ADS)

Kim, Ok-Yeon; Kim, Hye-Mi; Lee, Myong-In; Min, Young-Mi

2017-01-01

This study aims at predicting the seasonal number of typhoons (TY) over the western North Pacific with an Asia-Pacific Climate Center (APCC) multi-model ensemble (MME)-based dynamical-statistical hybrid model. The hybrid model uses the statistical relationship between the number of TY during the typhoon season (July-October) and the large-scale key predictors forecasted by APCC MME for the same season. The cross validation result from the MME hybrid model demonstrates high prediction skill, with a correlation of 0.67 between the hindcasts and observation for 1982-2008. The cross validation from the hybrid model with individual models participating in MME indicates that there is no single model which consistently outperforms the other models in predicting typhoon number. Although the forecast skill of MME is not always the highest compared to that of each individual model, the skill of MME presents rather higher averaged correlations and small variance of correlations. Given large set of ensemble members from multi-models, a relative operating characteristic score reveals an 82 % (above-) and 78 % (below-normal) improvement for the probabilistic prediction of the number of TY. It implies that there is 82 % (78 %) probability that the forecasts can successfully discriminate between above normal (below-normal) from other years. The forecast skill of the hybrid model for the past 7 years (2002-2008) is more skillful than the forecast from the Tropical Storm Risk consortium. Using large set of ensemble members from multi-models, the APCC MME could provide useful deterministic and probabilistic seasonal typhoon forecasts to the end-users in particular, the residents of tropical cyclone-prone areas in the Asia-Pacific region.

A Hierarchical Multivariate Bayesian Approach to Ensemble Model output Statistics in Atmospheric Prediction

DTIC Science & Technology

2017-09-01

efficacy of statistical post-processing methods downstream of these dynamical model components with a hierarchical multivariate Bayesian approach to...Bayesian hierarchical modeling, Markov chain Monte Carlo methods , Metropolis algorithm, machine learning, atmospheric prediction 15. NUMBER OF PAGES...scale processes. However, this dissertation explores the efficacy of statistical post-processing methods downstream of these dynamical model components

Statistics of initial density perturbations in heavy ion collisions and their fluid dynamic response

NASA Astrophysics Data System (ADS)

Floerchinger, Stefan; Wiedemann, Urs Achim

2014-08-01

An interesting opportunity to determine thermodynamic and transport properties in more detail is to identify generic statistical properties of initial density perturbations. Here we study event-by-event fluctuations in terms of correlation functions for two models that can be solved analytically. The first assumes Gaussian fluctuations around a distribution that is fixed by the collision geometry but leads to non-Gaussian features after averaging over the reaction plane orientation at non-zero impact parameter. In this context, we derive a three-parameter extension of the commonly used Bessel-Gaussian event-by-event distribution of harmonic flow coefficients. Secondly, we study a model of N independent point sources for which connected n-point correlation functions of initial perturbations scale like 1 /N n-1. This scaling is violated for non-central collisions in a way that can be characterized by its impact parameter dependence. We discuss to what extent these are generic properties that can be expected to hold for any model of initial conditions, and how this can improve the fluid dynamical analysis of heavy ion collisions.

Dynamically biased statistical model for the ortho/para conversion in the H2 + H3+ → H3+ + H2 reaction.

PubMed

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-07

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007)]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H(5)(+) complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H(5)(+) complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011)] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Hunting statistics: what data for what use? An account of an international workshop

USGS Publications Warehouse

Nichols, J.D.; Lancia, R.A.; Lebreton, J.D.

2001-01-01

Hunting interacts with the underlying dynamics of game species in several different ways and is, at the same time, a source of valuable information not easily obtained from populations that are not subjected to hunting. Specific questions, including the sustainability of hunting activities, can be addressed using hunting statistics. Such investigations will frequently require that hunting statistics be combined with data from other sources of population-level information. Such reflections served as a basis for the meeting, ?Hunting Statistics: What Data for What Use,? held on January 15-18, 2001 in Saint-Benoist, France. We review here the 20 talks held during the workshop and the contribution of hunting statistics to our knowledge of the population dynamics of game species. Three specific topics (adaptive management, catch-effort models, and dynamics of exploited populations) were highlighted as important themes and are more extensively presented as boxes.

Tunneling Statistics for Analysis of Spin-Readout Fidelity

NASA Astrophysics Data System (ADS)

Gorman, S. K.; He, Y.; House, M. G.; Keizer, J. G.; Keith, D.; Fricke, L.; Hile, S. J.; Broome, M. A.; Simmons, M. Y.

2017-09-01

We investigate spin and charge dynamics of a quantum dot of phosphorus atoms coupled to a radio-frequency single-electron transistor (SET) using full counting statistics. We show how the magnetic field plays a role in determining the bunching or antibunching tunneling statistics of the donor dot and SET system. Using the counting statistics, we show how to determine the lowest magnetic field where spin readout is possible. We then show how such a measurement can be used to investigate and optimize single-electron spin-readout fidelity.

Statistical analysis of modeling error in structural dynamic systems

NASA Technical Reports Server (NTRS)

Hasselman, T. K.; Chrostowski, J. D.

1990-01-01

The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.

Person-Job-Match (PJM) Beyond the More is Better Paradigm

DTIC Science & Technology

2008-10-01

6 Attracting the RIGHT Applicants...The SDI+ -- A Strategic Solution Attracting the RIGHT Applicants The SDI+ vision is a multi-phase strategic solution. The proposed SDI...much impact in AFSCs with physically demanding training, the impact on academics for in-service personnel may be significant. Consider a scenario

Disorders of interstitial cells of Cajal in a neonate with segmental dilatation of the intestine.

PubMed

Okada, Tadao; Sasaki, Fumiaki; Honda, Shohei; Cho, Kazutosi; Matsuno, Yoshihiro; Itoh, Tomoo; Kubota, Kanako C; Todo, Satoru

2010-06-01

Localized myopathy of the muscular layers may be an important factor contributing to segmental dilatation of the intestine (SDI). Only one report has described SDI of the jejunum in a neonate showing no abnormality of the interstitial cells of Cajal (ICC). The present report describes the very rare case of a neonatal girl with segmental dilatation of the distal duodenum and proximal jejunum with irregular arrangements of Auerbach's plexus and ICC and the successful surgical treatment of SDI. We review the literature on this type of relationship between abnormality of ICC and SDI and discuss the clinical features of this complication. Furthermore, the possible neuropathic cause of SDI complicated with disorders of ICC was explored in this report. Copyright 2010 Elsevier Inc. All rights reserved.

STATWIZ - AN ELECTRONIC STATISTICAL TOOL (ABSTRACT)

EPA Science Inventory

StatWiz is a web-based, interactive, and dynamic statistical tool for researchers. It will allow researchers to input information and/or data and then receive experimental design options, or outputs from data analysis. StatWiz is envisioned as an expert system that will walk rese...

Inferring epidemiological dynamics of infectious diseases using Tajima's D statistic on nucleotide sequences of pathogens.

PubMed

Kim, Kiyeon; Omori, Ryosuke; Ito, Kimihito

2017-12-01

The estimation of the basic reproduction number is essential to understand epidemic dynamics, and time series data of infected individuals are usually used for the estimation. However, such data are not always available. Methods to estimate the basic reproduction number using genealogy constructed from nucleotide sequences of pathogens have been proposed so far. Here, we propose a new method to estimate epidemiological parameters of outbreaks using the time series change of Tajima's D statistic on the nucleotide sequences of pathogens. To relate the time evolution of Tajima's D to the number of infected individuals, we constructed a parsimonious mathematical model describing both the transmission process of pathogens among hosts and the evolutionary process of the pathogens. As a case study we applied this method to the field data of nucleotide sequences of pandemic influenza A (H1N1) 2009 viruses collected in Argentina. The Tajima's D-based method estimated basic reproduction number to be 1.55 with 95% highest posterior density (HPD) between 1.31 and 2.05, and the date of epidemic peak to be 10th July with 95% HPD between 22nd June and 9th August. The estimated basic reproduction number was consistent with estimation by birth-death skyline plot and estimation using the time series of the number of infected individuals. These results suggested that Tajima's D statistic on nucleotide sequences of pathogens could be useful to estimate epidemiological parameters of outbreaks. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

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

Michalski, D; Huq, M; Bednarz, G

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same ismore » for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so

Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces.

PubMed

Spezia, Riccardo; Martínez-Nuñez, Emilio; Vazquez, Saulo; Hase, William L

2017-04-28

In this Introduction, we show the basic problems of non-statistical and non-equilibrium phenomena related to the papers collected in this themed issue. Over the past few years, significant advances in both computing power and development of theories have allowed the study of larger systems, increasing the time length of simulations and improving the quality of potential energy surfaces. In particular, the possibility of using quantum chemistry to calculate energies and forces 'on the fly' has paved the way to directly study chemical reactions. This has provided a valuable tool to explore molecular mechanisms at given temperatures and energies and to see whether these reactive trajectories follow statistical laws and/or minimum energy pathways. This themed issue collects different aspects of the problem and gives an overview of recent works and developments in different contexts, from the gas phase to the condensed phase to excited states.This article is part of the themed issue 'Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces'. © 2017 The Author(s).

Drip irrigation research update at NPRL

USDA-ARS?s Scientific Manuscript database

Drip irrigation research has been conducted since 1998 at NPRL. Systems include deep subsurface drip irrigation (SSDI), surface drip irrigation (SDI), and shallow subsurface drip irrigation (S3DI). Results have shown that SDI and S3DI are more economical to install than SSDI. SDI systems have more r...

Statistical Investigations on Solar Wind Dynamic Pressure Pulses:Basic features and Their Impacts on Geosynchronous Magnetic Fields

NASA Astrophysics Data System (ADS)

Zuo, Pingbing; Feng, Xueshang

2016-07-01

Solar wind dynamic pressure pulse (DPP) structures, across which the dynamic pressure abruptly changes over timescales from a few seconds to several minutes, are often observed in the near-Earth space environment. Recently we have developed a novel procedure that is able to rapidly identify the DPPs from the plasma data stream, and simultaneously define the transition region and smartly select the upstream and downstream region for analysis. The plasma data with high time-resolution from 3DP instrument on board the WIND spacecraft are inspected with this automatic DPP-searching code, and a complete list of solar wind DPPs of historic WIND observations are built up. We perform a statistical survey on the properties of DPPs near 1 AU based on this event list. It is found that overwhelming majority of DPPs are associated with the solar wind disturbances including the CME-related flows, the corotating interaction regions, as well as the complex ejecta. The annual variations of the averaged occurrence rate of DPPs are roughly in phase with the solar activities. Although the variabilities of geosynchronous magnetic fields (GMFs) due to the impact of positive DPPs have been well established, there appears no systematic investigations on the response of GMFs to negative DPPs. Here we also study the decompression/compression effects of very strong negative/positive DPPs on GMFs under northward IMFs. In response to the decompression of strong negative DPPs, GMFs on dayside, near the dawn and dusk on nightside are generally depressed. But near the midnight region, the responses of GMF are very diverse, being either positive or negative. For part of events when GOES is located at the midnight sector, GMF is found to abnormally increase as the result of magnetospheric decompression caused by negative DPPs. It is known that on certain conditions magnetic depression of nightside GMFs can be caused by the impact of positive DPPs. Statistically, both the decompression effect of

North American extreme temperature events and related large scale meteorological patterns: A review of statistical methods, dynamics, modeling, and trends

DOE PAGES

Grotjahn, Richard; Black, Robert; Leung, Ruby; ...

2015-05-22

This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic tomore » planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so

Developing a Planetary Spatial Data Infrastructure for Evaluating Landing Sites and Performing Surface Operations for the Mars 2020 Lander

NASA Astrophysics Data System (ADS)

Fergason, R. L.; Laura, J.; Hare, T. M.; Otero, R.; Edgar, L. A.

2017-12-01

A Spatial Data Infrastructure (SDI) is a robust framework for data and data products, metadata, data access mechanisms, standards, policy, and a user community that helps to define and standardize the data necessary to meet some specified goal. The primary objective of an SDI is to improve communication, to enhance data access, and to aid in identifying gaps in knowledge. We are developing an SDI that describes the foundational data sets and accuracy requirements to evaluate landing site safety, facilitate the successful operation of Terrain Relative Navigation (TRN), and assist in the operation of the rover once it has successfully landed on Mars. Thru current development efforts, an implicit SDI exists for the Mars 2020 mission. An explicit SDI will allow us to identify any potential gaps in knowledge, facilitate communication between the different institutions involved in landing site evaluation and TRN development, and help ensure a smooth transition from landing to surface operations. This SDI is currently relevant to the Mars 2020 rover mission, but can also serve as a means to document current requirements for foundational data products and standards for future landed missions to Mars and other planetary bodies. To generate a Mars 2020-specific SDI, we must first document and rationalize data set and accuracy requirements for evaluating landing sites, performing surface operations, and inventorying Mars 2020 mission needs in terms of an SDI framework. This step will allow us to 1) evaluate and define what is needed for the acquisition of data and the generation and validation of data products, 2) articulate the accuracy and co-registration requirements, and 3) identify needs for data access (and eventual archiving). This SDI document will serve as a means to communicate the existing foundational products, standards that were followed in producing these products, and where and how these products can be accessed by the planetary community. This SDI will also

Dynamical and statistical behavior of discrete combustion waves: a theoretical and numerical study.

PubMed

Bharath, Naine Tarun; Rashkovskiy, Sergey A; Tewari, Surya P; Gundawar, Manoj Kumar

2013-04-01

We present a detailed theoretical and numerical study of combustion waves in a discrete one-dimensional disordered system. The distances between neighboring reaction cells were modeled with a gamma distribution. The results show that the random structure of the microheterogeneous system plays a crucial role in the dynamical and statistical behavior of the system. This is a consequence of the nonlinear interaction of the random structure of the system with the thermal wave. An analysis of the experimental data on the combustion of a gasless system (Ti + xSi) and a wide range of thermite systems was performed in view of the developed model. We have shown that the burning rate of the powder system sensitively depends on its internal structure. The present model allows for reproducing theoretically the experimental data for a wide range of pyrotechnic mixtures. We show that Arrhenius' macrokinetics at combustion of disperse systems can take place even in the absence of Arrhenius' microkinetics; it can have a purely thermal nature and be related to their heterogeneity and to the existence of threshold temperature. It is also observed that the combustion of disperse systems always occurs in the microheterogeneous mode according to the relay-race mechanism.

Dynamical and statistical behavior of discrete combustion waves: A theoretical and numerical study

NASA Astrophysics Data System (ADS)

Bharath, Naine Tarun; Rashkovskiy, Sergey A.; Tewari, Surya P.; Gundawar, Manoj Kumar

2013-04-01

We present a detailed theoretical and numerical study of combustion waves in a discrete one-dimensional disordered system. The distances between neighboring reaction cells were modeled with a gamma distribution. The results show that the random structure of the microheterogeneous system plays a crucial role in the dynamical and statistical behavior of the system. This is a consequence of the nonlinear interaction of the random structure of the system with the thermal wave. An analysis of the experimental data on the combustion of a gasless system (Ti + xSi) and a wide range of thermite systems was performed in view of the developed model. We have shown that the burning rate of the powder system sensitively depends on its internal structure. The present model allows for reproducing theoretically the experimental data for a wide range of pyrotechnic mixtures. We show that Arrhenius’ macrokinetics at combustion of disperse systems can take place even in the absence of Arrhenius’ microkinetics; it can have a purely thermal nature and be related to their heterogeneity and to the existence of threshold temperature. It is also observed that the combustion of disperse systems always occurs in the microheterogeneous mode according to the relay-race mechanism.

Statistical analysis of Geopotential Height (GH) timeseries based on Tsallis non-extensive statistical mechanics

NASA Astrophysics Data System (ADS)

Karakatsanis, L. P.; Iliopoulos, A. C.; Pavlos, E. G.; Pavlos, G. P.

2018-02-01

In this paper, we perform statistical analysis of time series deriving from Earth's climate. The time series are concerned with Geopotential Height (GH) and correspond to temporal and spatial components of the global distribution of month average values, during the period (1948-2012). The analysis is based on Tsallis non-extensive statistical mechanics and in particular on the estimation of Tsallis' q-triplet, namely {qstat, qsens, qrel}, the reconstructed phase space and the estimation of correlation dimension and the Hurst exponent of rescaled range analysis (R/S). The deviation of Tsallis q-triplet from unity indicates non-Gaussian (Tsallis q-Gaussian) non-extensive character with heavy tails probability density functions (PDFs), multifractal behavior and long range dependences for all timeseries considered. Also noticeable differences of the q-triplet estimation found in the timeseries at distinct local or temporal regions. Moreover, in the reconstructive phase space revealed a lower-dimensional fractal set in the GH dynamical phase space (strong self-organization) and the estimation of Hurst exponent indicated multifractality, non-Gaussianity and persistence. The analysis is giving significant information identifying and characterizing the dynamical characteristics of the earth's climate.

Variable-focus microscopy and UV surface dissolution imaging as complementary techniques in intrinsic dissolution rate determination.

PubMed

Ward, Adam; Walton, Karl; Box, Karl; Østergaard, Jesper; Gillie, Lisa J; Conway, Barbara R; Asare-Addo, Kofi

2017-09-15

This work reports a novel approach to the assessment of the surface properties of compacts used in Surface Dissolution Imaging (SDI). SDI is useful for determining intrinsic dissolution rate (IDR), an important parameter in early stage drug development. Surface topography, post-compaction and post-SDI run, have been measured using a non-contact, optical, three-dimensional microscope based on focus variation, the Alicona Infinite Focus Microscope, with the aim of correlating the IDRs to the surface properties. Ibuprofen (IBU) was used as a model poorly-soluble drug. DSC and XRD were used to monitor possible polymorphic changes that may have occurred post-compaction and post-SDI run. IBUs IDR decreased from 0.033mg/min/cm 2 to 0.022mg/min/cm 2 from 10 to 20min, respectively, during the experiment. XRD and DSC showed no form changes during the SDI run. The surface topography images showed that a distinct imprint was embossed on the surfaces of some compacts which could affect IDRs. Surface parameter values were associated with the SDI experiments which showed strong correlations with the IDR values. The variable-focus microscope can be used as a complimentary tool in the determination of IDR values from the SDI. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Statistical properties of Chinese phonemic networks

NASA Astrophysics Data System (ADS)

Yu, Shuiyuan; Liu, Haitao; Xu, Chunshan

2011-04-01

The study of properties of speech sound systems is of great significance in understanding the human cognitive mechanism and the working principles of speech sound systems. Some properties of speech sound systems, such as the listener-oriented feature and the talker-oriented feature, have been unveiled with the statistical study of phonemes in human languages and the research of the interrelations between human articulatory gestures and the corresponding acoustic parameters. With all the phonemes of speech sound systems treated as a coherent whole, our research, which focuses on the dynamic properties of speech sound systems in operation, investigates some statistical parameters of Chinese phoneme networks based on real text and dictionaries. The findings are as follows: phonemic networks have high connectivity degrees and short average distances; the degrees obey normal distribution and the weighted degrees obey power law distribution; vowels enjoy higher priority than consonants in the actual operation of speech sound systems; the phonemic networks have high robustness against targeted attacks and random errors. In addition, for investigating the structural properties of a speech sound system, a statistical study of dictionaries is conducted, which shows the higher frequency of shorter words and syllables and the tendency that the longer a word is, the shorter the syllables composing it are. From these structural properties and dynamic properties one can derive the following conclusion: the static structure of a speech sound system tends to promote communication efficiency and save articulation effort while the dynamic operation of this system gives preference to reliable transmission and easy recognition. In short, a speech sound system is an effective, efficient and reliable communication system optimized in many aspects.

Is quantum theory a form of statistical mechanics?

NASA Astrophysics Data System (ADS)

Adler, S. L.

2007-05-01

We give a review of the basic themes of my recent book: Adler S L 2004 Quantum Theory as an Emergent Phenomenon (Cambridge: Cambridge University Press). We first give motivations for considering the possibility that quantum mechanics is not exact, but is instead an accurate asymptotic approximation to a deeper level theory. For this deeper level, we propose a non-commutative generalization of classical mechanics, that we call "trace dynamics", and we give a brief survey of how it works, considering for simplicity only the bosonic case. We then discuss the statistical mechanics of trace dynamics and give our argument that with suitable approximations, the Ward identities for trace dynamics imply that ensemble averages in the canonical ensemble correspond to Wightman functions in quantum field theory. Thus, quantum theory emerges as the statistical thermodynamics of trace dynamics. Finally, we argue that Brownian motion corrections to this thermodynamics lead to stochastic corrections to the Schrödinger equation, of the type that have been much studied in the "continuous spontaneous localization" model of objective state vector reduction. In appendices to the talk, we give details of the existence of a conserved operator in trace dynamics that encodes the structure of the canonical algebra, of the derivation of the Ward identities, and of the proof that the stochastically-modified Schrödinger equation leads to state vector reduction with Born rule probabilities.

Statistical complexity measure of pseudorandom bit generators

NASA Astrophysics Data System (ADS)

González, C. M.; Larrondo, H. A.; Rosso, O. A.

2005-08-01

Pseudorandom number generators (PRNG) are extensively used in Monte Carlo simulations, gambling machines and cryptography as substitutes of ideal random number generators (RNG). Each application imposes different statistical requirements to PRNGs. As L’Ecuyer clearly states “the main goal for Monte Carlo methods is to reproduce the statistical properties on which these methods are based whereas for gambling machines and cryptology, observing the sequence of output values for some time should provide no practical advantage for predicting the forthcoming numbers better than by just guessing at random”. In accordance with different applications several statistical test suites have been developed to analyze the sequences generated by PRNGs. In a recent paper a new statistical complexity measure [Phys. Lett. A 311 (2003) 126] has been defined. Here we propose this measure, as a randomness quantifier of a PRNGs. The test is applied to three very well known and widely tested PRNGs available in the literature. All of them are based on mathematical algorithms. Another PRNGs based on Lorenz 3D chaotic dynamical system is also analyzed. PRNGs based on chaos may be considered as a model for physical noise sources and important new results are recently reported. All the design steps of this PRNG are described, and each stage increase the PRNG randomness using different strategies. It is shown that the MPR statistical complexity measure is capable to quantify this randomness improvement. The PRNG based on the chaotic 3D Lorenz dynamical system is also evaluated using traditional digital signal processing tools for comparison.

Stand density index in uneven-aged ponderosa pine stands

Treesearch

C.W. Woodall; C.E. Fiedler; K.S. Milner

2003-01-01

Stand density index (SDI) was developed to quantify relative stand density in even-aged stands. Application of SDI in uneven-aged stands has been described mathematically but not justified biologically. Diameter-class trends in SDI and sapwood area across 14 uneven-aged ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws.) stands in eastern...

Determining maximum stand density index in mixed species stands for strategic-scale stocking assessments

Treesearch

Chris W. Woodall; Patrick D. Miles; John S. Vissage

2005-01-01

Stand density index (SDI), although developed for use in even-aged monocultures, has been used for assessing stand density in large-scale forest inventories containing diverse tree species and size distributions. To improve application of SDI in unevenaged, mixed species stands present in large-scale forest inventories, trends in maximum SDI across diameter classes...

Cotton, tomato, corn, and onion production with subsurface drip irrigation – a review

USDA-ARS?s Scientific Manuscript database

The usage of subsurface drip irrigation (SDI) has increased by 89% in the USA during the last ten years according to USDA NASS estimates and over 93% of the SDI land area is located in just ten states. Combining public entity and private industry perceptions of SDI in these ten states, the major cro...

Compendium of Abstracts on Statistical Applications in Geotechnical Engineering.

DTIC Science & Technology

1983-09-01

research in the application of probabilistic and statistical methods to soil mechanics, rock mechanics, and engineering geology problems have grown markedly...probability, statistics, soil mechanics, rock mechanics, and engineering geology. 2. The purpose of this report is to make available to the U. S...Deformation Dynamic Response Analysis Seepage, Soil Permeability and Piping Earthquake Engineering, Seismology, Settlement and Heave Seismic Risk Analysis

Alternating event processes during lifetimes: population dynamics and statistical inference.

PubMed

Shinohara, Russell T; Sun, Yifei; Wang, Mei-Cheng

2018-01-01

In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes.

The relative density of forests in the United States

Treesearch

Christopher W. Woodall; Charles H. Perry; Patrick D. Miles

2006-01-01

A relative stand density assessment technique, using the mean specific gravity of all trees in a stand to predict its maximum stand density index (SDI) and subsequently its relative stand density (current SDI divided by maximum SDI), was used to estimate the relative density of forests across the United States using a national-scale forest inventory. Live tree biomass...

Structure of sheared and rotating turbulence: Multiscale statistics of Lagrangian and Eulerian accelerations and passive scalar dynamics.

PubMed

Jacobitz, Frank G; Schneider, Kai; Bos, Wouter J T; Farge, Marie

2016-01-01

The acceleration statistics of sheared and rotating homogeneous turbulence are studied using direct numerical simulation results. The statistical properties of Lagrangian and Eulerian accelerations are considered together with the influence of the rotation to shear ratio, as well as the scale dependence of their statistics. The probability density functions (pdfs) of both Lagrangian and Eulerian accelerations show a strong and similar dependence on the rotation to shear ratio. The variance and flatness of both accelerations are analyzed and the extreme values of the Eulerian acceleration are observed to be above those of the Lagrangian acceleration. For strong rotation it is observed that flatness yields values close to three, corresponding to Gaussian-like behavior, and for moderate and vanishing rotation the flatness increases. Furthermore, the Lagrangian and Eulerian accelerations are shown to be strongly correlated for strong rotation due to a reduced nonlinear term in this case. A wavelet-based scale-dependent analysis shows that the flatness of both Eulerian and Lagrangian accelerations increases as scale decreases, which provides evidence for intermittent behavior. For strong rotation the Eulerian acceleration is even more intermittent than the Lagrangian acceleration, while the opposite result is obtained for moderate rotation. Moreover, the dynamics of a passive scalar with gradient production in the direction of the mean velocity gradient is analyzed and the influence of the rotation to shear ratio is studied. Concerning the concentration of a passive scalar spread by the flow, the pdf of its Eulerian time rate of change presents higher extreme values than those of its Lagrangian time rate of change. This suggests that the Eulerian time rate of change of scalar concentration is mainly due to advection, while its Lagrangian counterpart is only due to gradient production and viscous dissipation.

Early years of Computational Statistical Mechanics

NASA Astrophysics Data System (ADS)

Mareschal, Michel

2018-05-01

Evidence that a model of hard spheres exhibits a first-order solid-fluid phase transition was provided in the late fifties by two new numerical techniques known as Monte Carlo and Molecular Dynamics. This result can be considered as the starting point of computational statistical mechanics: at the time, it was a confirmation of a counter-intuitive (and controversial) theoretical prediction by J. Kirkwood. It necessitated an intensive collaboration between the Los Alamos team, with Bill Wood developing the Monte Carlo approach, and the Livermore group, where Berni Alder was inventing Molecular Dynamics. This article tells how it happened.

Characteristics of level-spacing statistics in chaotic graphene billiards.

PubMed

Huang, Liang; Lai, Ying-Cheng; Grebogi, Celso

2011-03-01

A fundamental result in nonrelativistic quantum nonlinear dynamics is that the spectral statistics of quantum systems that possess no geometric symmetry, but whose classical dynamics are chaotic, are described by those of the Gaussian orthogonal ensemble (GOE) or the Gaussian unitary ensemble (GUE), in the presence or absence of time-reversal symmetry, respectively. For massless spin-half particles such as neutrinos in relativistic quantum mechanics in a chaotic billiard, the seminal work of Berry and Mondragon established the GUE nature of the level-spacing statistics, due to the combination of the chirality of Dirac particles and the confinement, which breaks the time-reversal symmetry. A question is whether the GOE or the GUE statistics can be observed in experimentally accessible, relativistic quantum systems. We demonstrate, using graphene confinements in which the quasiparticle motions are governed by the Dirac equation in the low-energy regime, that the level-spacing statistics are persistently those of GOE random matrices. We present extensive numerical evidence obtained from the tight-binding approach and a physical explanation for the GOE statistics. We also find that the presence of a weak magnetic field switches the statistics to those of GUE. For a strong magnetic field, Landau levels become influential, causing the level-spacing distribution to deviate markedly from the random-matrix predictions. Issues addressed also include the effects of a number of realistic factors on level-spacing statistics such as next nearest-neighbor interactions, different lattice orientations, enhanced hopping energy for atoms on the boundary, and staggered potential due to graphene-substrate interactions.

The use and misuse of aircraft and missile RCS statistics

NASA Astrophysics Data System (ADS)

Bishop, Lee R.

1991-07-01

Both static and dynamic radar cross sections measurements are used for RCS predictions, but the static data are less complete than the dynamic. Integrated dynamics RCS data also have limitations for prediction radar detection performance. When raw static data are properly used, good first-order detection estimates are possible. The research to develop more-usable RCS statistics is reviewed, and windowing techniques for creating probability density functions from static RCS data are discussed.

Design for Connecting Spatial Data Infrastructures with Sensor Web (sensdi)

NASA Astrophysics Data System (ADS)

Bhattacharya, D.; M., M.

2016-06-01

Integrating Sensor Web With Spatial Data Infrastructures (SENSDI) aims to extend SDIs with sensor web enablement, converging geospatial and built infrastructure, and implement test cases with sensor data and SDI. It is about research to harness the sensed environment by utilizing domain specific sensor data to create a generalized sensor webframework. The challenges being semantic enablement for Spatial Data Infrastructures, and connecting the interfaces of SDI with interfaces of Sensor Web. The proposed research plan is to Identify sensor data sources, Setup an open source SDI, Match the APIs and functions between Sensor Web and SDI, and Case studies like hazard applications, urban applications etc. We take up co-operative development of SDI best practices to enable a new realm of a location enabled and semantically enriched World Wide Web - the "Geospatial Web" or "Geosemantic Web" by setting up one to one correspondence between WMS, WFS, WCS, Metadata and 'Sensor Observation Service' (SOS); 'Sensor Planning Service' (SPS); 'Sensor Alert Service' (SAS); a service that facilitates asynchronous message interchange between users and services, and between two OGC-SWE services, called the 'Web Notification Service' (WNS). Hence in conclusion, it is of importance to geospatial studies to integrate SDI with Sensor Web. The integration can be done through merging the common OGC interfaces of SDI and Sensor Web. Multi-usability studies to validate integration has to be undertaken as future research.

The selective digital integrator: A new device for modulated polarization spectroscopy

NASA Astrophysics Data System (ADS)

Vrancic, Aljosa

1998-12-01

A new device, a selective digital integrator (SDI), for the acquisition of modulated polarization spectroscopy (MPS) signals is described. Special attention is given to the accurate measurement of very small (AC component of interest <10-3 x DC component), rapidly modulated (~50 kHz) signals at or below noise levels. Various data acquisition methods and problems associated with the collection of modulated signals are discussed. The SDI solves most of these problems and has the following advantages: it provides the average-time resolved profile of a modulated signal; it eliminates errors if the modulation is not sinusoidal; it enables separate measurements of the various phases of the signal modulation cycle; it permits simultaneous measurement of absorption, circular dichroism (CD) and linear dichroism (LD) spectra; it facilitates 3-D absorbance measurements; it has a wide gain-switching-free dynamic range (10 orders of magnitude or more); it offers a constant S/N ratio mode of operation; it eliminates the need for photomultiplier voltage feedback, and it has faster scanning speeds. The time-resolution, selectivity, wide dynamic range, and low-overhead on-the-fly data processing are useful for other modulated spectroscopy (MS) and non-MS experiments such as pulse height distribution and time-resolved pulse counting measurements. The advantages of the MPS-SDI method are tested on the first Rydberg electronic transitions of (+)-3- methylcyclopentanone. The experimental results validate the predicted SDI capabilities. However, they also point to two difficulties that had not been noted previously: the presence of LD in a gaseous sample and a pressure- dependence of the relative peak heights of the CD spectrum. Models for these anomalies are proposed. The presence of the oscillatory LD (but not an LD background) is explained with a sample cell model based on the observed polarization-dependent time-resolved profiles of transmitted light intensity. To obtain expressions

Visualizing statistical significance of disease clusters using cartograms.

PubMed

Kronenfeld, Barry J; Wong, David W S

2017-05-15

Health officials and epidemiological researchers often use maps of disease rates to identify potential disease clusters. Because these maps exaggerate the prominence of low-density districts and hide potential clusters in urban (high-density) areas, many researchers have used density-equalizing maps (cartograms) as a basis for epidemiological mapping. However, we do not have existing guidelines for visual assessment of statistical uncertainty. To address this shortcoming, we develop techniques for visual determination of statistical significance of clusters spanning one or more districts on a cartogram. We developed the techniques within a geovisual analytics framework that does not rely on automated significance testing, and can therefore facilitate visual analysis to detect clusters that automated techniques might miss. On a cartogram of the at-risk population, the statistical significance of a disease cluster is determinate from the rate, area and shape of the cluster under standard hypothesis testing scenarios. We develop formulae to determine, for a given rate, the area required for statistical significance of a priori and a posteriori designated regions under certain test assumptions. Uniquely, our approach enables dynamic inference of aggregate regions formed by combining individual districts. The method is implemented in interactive tools that provide choropleth mapping, automated legend construction and dynamic search tools to facilitate cluster detection and assessment of the validity of tested assumptions. A case study of leukemia incidence analysis in California demonstrates the ability to visually distinguish between statistically significant and insignificant regions. The proposed geovisual analytics approach enables intuitive visual assessment of statistical significance of arbitrarily defined regions on a cartogram. Our research prompts a broader discussion of the role of geovisual exploratory analyses in disease mapping and the appropriate

Detector noise statistics in the non-linear regime

NASA Technical Reports Server (NTRS)

Shopbell, P. L.; Bland-Hawthorn, J.

1992-01-01

The statistical behavior of an idealized linear detector in the presence of threshold and saturation levels is examined. It is assumed that the noise is governed by the statistical fluctuations in the number of photons emitted by the source during an exposure. Since physical detectors cannot have infinite dynamic range, our model illustrates that all devices have non-linear regimes, particularly at high count rates. The primary effect is a decrease in the statistical variance about the mean signal due to a portion of the expected noise distribution being removed via clipping. Higher order statistical moments are also examined, in particular, skewness and kurtosis. In principle, the expected distortion in the detector noise characteristics can be calibrated using flatfield observations with count rates matched to the observations. For this purpose, some basic statistical methods that utilize Fourier analysis techniques are described.

Structural uncertainty of downscaled climate model output in a difficult-to-resolve environment: data sparseness and parameterization error contribution to statistical and dynamical downscaling output in the U.S. Caribbean region

NASA Astrophysics Data System (ADS)

Terando, A. J.; Grade, S.; Bowden, J.; Henareh Khalyani, A.; Wootten, A.; Misra, V.; Collazo, J.; Gould, W. A.; Boyles, R.

2016-12-01

Sub-tropical island nations may be particularly vulnerable to anthropogenic climate change because of predicted changes in the hydrologic cycle that would lead to significant drying in the future. However, decision makers in these regions have seen their adaptation planning efforts frustrated by the lack of island-resolving climate model information. Recently, two investigations have used statistical and dynamical downscaling techniques to develop climate change projections for the U.S. Caribbean region (Puerto Rico and U.S. Virgin Islands). We compare the results from these two studies with respect to three commonly downscaled CMIP5 global climate models (GCMs). The GCMs were dynamically downscaled at a convective-permitting scale using two different regional climate models. The statistical downscaling approach was conducted at locations with long-term climate observations and then further post-processed using climatologically aided interpolation (yielding two sets of projections). Overall, both approaches face unique challenges. The statistical approach suffers from a lack of observations necessary to constrain the model, particularly at the land-ocean boundary and in complex terrain. The dynamically downscaled model output has a systematic dry bias over the island despite ample availability of moisture in the atmospheric column. Notwithstanding these differences, both approaches are consistent in projecting a drier climate that is driven by the strong global-scale anthropogenic forcing.

Synchronization from Second Order Network Connectivity Statistics

PubMed Central

Zhao, Liqiong; Beverlin, Bryce; Netoff, Theoden; Nykamp, Duane Q.

2011-01-01

We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections, and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by their increasing the effective coupling strength. The decrease of synchrony with convergent connections is primarily due to the resulting heterogeneity in firing rates. PMID:21779239

Statistical characteristics of dynamics for population migration driven by the economic interests

NASA Astrophysics Data System (ADS)

Huo, Jie; Wang, Xu-Ming; Zhao, Ning; Hao, Rui

2016-06-01

Population migration typically occurs under some constraints, which can deeply affect the structure of a society and some other related aspects. Therefore, it is critical to investigate the characteristics of population migration. Data from the China Statistical Yearbook indicate that the regional gross domestic product per capita relates to the population size via a linear or power-law relation. In addition, the distribution of population migration sizes or relative migration strength introduced here is dominated by a shifted power-law relation. To reveal the mechanism that creates the aforementioned distributions, a dynamic model is proposed based on the population migration rule that migration is facilitated by higher financial gains and abated by fewer employment opportunities at the destination, considering the migration cost as a function of the migration distance. The calculated results indicate that the distribution of the relative migration strength is governed by a shifted power-law relation, and that the distribution of migration distances is dominated by a truncated power-law relation. These results suggest the use of a power-law to fit a distribution may be not always suitable. Additionally, from the modeling framework, one can infer that it is the randomness and determinacy that jointly create the scaling characteristics of the distributions. The calculation also demonstrates that the network formed by active nodes, representing the immigration and emigration regions, usually evolves from an ordered state with a non-uniform structure to a disordered state with a uniform structure, which is evidenced by the increasing structural entropy.

Laboratory evaluation of the Design Analysis Associates DAA H-3613i radar water-level sensor—Results of temperature, distance, and SDI-12 tests

USGS Publications Warehouse

Carnley, Mark V.

2016-09-30

The Design Analysis Associates (DAA) DAA H-3613i radar water-level sensor (DAA H-3613i), manufactured by Xylem Incorporated, was evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to manufacturer’s accuracy specifications for measuring a distance throughout the sensor’s operating temperature range, for measuring distances from 3 to 15 feet at ambient temperatures, and for compliance with the SDI-12 serial-to-digital interface at 1200-baud communication standard. The DAA H-3613i is a noncontact water-level sensor that uses pulsed radar to measure the distance between the radar and the water surface from 0.75 to 131 feet over a temperature range of −40 to 60 degrees Celsius (°C). Manufacturer accuracy specifications that were evaluated, the test procedures that followed, and the results obtained are described in this report. The sensor’s accuracy specification of ± 0.01 feet (± 3 millimeters) meets USGS requirements for a primary water-stage sensor used in the operation of a streamgage. The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during temperature testing at a distance of 8 feet from the target over its temperature-compensated operating range of −40 to 60 °C, except at 60 °C. At 60 °C, about half the measurements exceeded the manufacturer’s accuracy specification by not more than 0.005 feet.The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during distance-accuracy testing at the tested distances from 3 to 15 feet above the water surface at the HIF.

J-adaptive estimation with estimated noise statistics

NASA Technical Reports Server (NTRS)

Jazwinski, A. H.; Hipkins, C.

1973-01-01

The J-adaptive sequential estimator is extended to include simultaneous estimation of the noise statistics in a model for system dynamics. This extension completely automates the estimator, eliminating the requirement of an analyst in the loop. Simulations in satellite orbit determination demonstrate the efficacy of the sequential estimation algorithm.

Statistical transmutation in doped quantum dimer models.

PubMed

Lamas, C A; Ralko, A; Cabra, D C; Poilblanc, D; Pujol, P

2012-07-06

We prove a "statistical transmutation" symmetry of doped quantum dimer models on the square, triangular, and kagome lattices: the energy spectrum is invariant under a simultaneous change of statistics (i.e., bosonic into fermionic or vice versa) of the holes and of the signs of all the dimer resonance loops. This exact transformation enables us to define the duality equivalence between doped quantum dimer Hamiltonians and provides the analytic framework to analyze dynamical statistical transmutations. We investigate numerically the doping of the triangular quantum dimer model with special focus on the topological Z(2) dimer liquid. Doping leads to four (instead of two for the square lattice) inequivalent families of Hamiltonians. Competition between phase separation, superfluidity, supersolidity, and fermionic phases is investigated in the four families.

Dynamic Optimization

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

Statistical description and transport in stochastic magnetic fields

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

Vanden Eijnden, E.; Balescu, R.

1996-03-01

The statistical description of particle motion in a stochastic magnetic field is presented. Starting form the stochastic Liouville equation (or, hybrid kinetic equation) associated with the equations of motion of a test particle, the probability distribution function of the system is obtained for various magnetic fields and collisional processes. The influence of these two ingredients on the statistics of the particle dynamics is stressed. In all cases, transport properties of the system are discussed. {copyright} {ital 1996 American Institute of Physics.}

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All

Statistical Mechanical Theory of Coupled Slow Dynamics in Glassy Polymer-Molecule Mixtures

NASA Astrophysics Data System (ADS)

Zhang, Rui; Schweizer, Kenneth

The microscopic Elastically Collective Nonlinear Langevin Equation theory of activated relaxation in one-component supercooled liquids and glasses is generalized to polymer-molecule mixtures. The key idea is to account for dynamic coupling between molecule and polymer segment motion. For describing the molecule hopping event, a temporal casuality condition is formulated to self-consistently determine a dimensionless degree of matrix distortion relative to the molecule jump distance based on the concept of coupled dynamic free energies. Implementation for real materials employs an established Kuhn sphere model of the polymer liquid and a quantitative mapping to a hard particle reference system guided by the experimental equation-of-state. The theory makes predictions for the mixture dynamic shear modulus, activated relaxation time and diffusivity of both species, and mixture glass transition temperature as a function of molecule-Kuhn segment size ratio and attraction strength, composition and temperature. Model calculations illustrate the dynamical behavior in three distinct mixture regimes (fully miscible, bridging, clustering) controlled by the molecule-polymer interaction or chi-parameter. Applications to specific experimental systems will be discussed.

Evaluation of Theoretical and Empirical Characteristics of the Communication, Language, and Statistics Survey (CLASS)

ERIC Educational Resources Information Center

Wagler, Amy E.; Lesser, Lawrence M.

2018-01-01

The interaction between language and the learning of statistical concepts has been receiving increased attention. The Communication, Language, And Statistics Survey (CLASS) was developed in response to the need to focus on dynamics of language in light of the culturally and linguistically diverse environments of introductory statistics classrooms.…

Providing Geographic Datasets as Linked Data in Sdi

NASA Astrophysics Data System (ADS)

Hietanen, E.; Lehto, L.; Latvala, P.

2016-06-01

In this study, a prototype service to provide data from Web Feature Service (WFS) as linked data is implemented. At first, persistent and unique Uniform Resource Identifiers (URI) are created to all spatial objects in the dataset. The objects are available from those URIs in Resource Description Framework (RDF) data format. Next, a Web Ontology Language (OWL) ontology is created to describe the dataset information content using the Open Geospatial Consortium's (OGC) GeoSPARQL vocabulary. The existing data model is modified in order to take into account the linked data principles. The implemented service produces an HTTP response dynamically. The data for the response is first fetched from existing WFS. Then the Geographic Markup Language (GML) format output of the WFS is transformed on-the-fly to the RDF format. Content Negotiation is used to serve the data in different RDF serialization formats. This solution facilitates the use of a dataset in different applications without replicating the whole dataset. In addition, individual spatial objects in the dataset can be referred with URIs. Furthermore, the needed information content of the objects can be easily extracted from the RDF serializations available from those URIs. A solution for linking data objects to the dataset URI is also introduced by using the Vocabulary of Interlinked Datasets (VoID). The dataset is divided to the subsets and each subset is given its persistent and unique URI. This enables the whole dataset to be explored with a web browser and all individual objects to be indexed by search engines.

Summary of inorganic compositional data for groundwater, soil-water, and surface-water samples collected at the Headgate Draw subsurface drip irrigation site, Johnson County, Wyoming

USGS Publications Warehouse

Geboy, Nicholas J.; Engle, Mark A.; Schroeder, Karl T.; Zupancic, John W.

2011-01-01

As part of a 5-year project on the impact of subsurface drip irrigation (SDI) application of coalbed-methane (CBM) produced waters, water samples were collected from the Headgate Draw SDI site in the Powder River Basin, Wyoming, USA. This research is part of a larger study to understand short- and long-term impacts on both soil and water quality from the beneficial use of CBM waters to grow forage crops through use of SDI. This document provides a summary of the context, sampling methodology, and quality assurance and quality control documentation of samples collected prior to and over the first year of SDI operation at the site (May 2008-October 2009). This report contains an associated database containing inorganic compositional data, water-quality criteria parameters, and calculated geochemical parameters for samples of groundwater, soil water, surface water, treated CBM waters, and as-received CBM waters collected at the Headgate Draw SDI site.

Improved Statistical Sampling and Accuracy with Accelerated Molecular Dynamics on Rotatable Torsions.

PubMed

Doshi, Urmi; Hamelberg, Donald

2012-11-13

In enhanced sampling techniques, the precision of the reweighted ensemble properties is often decreased due to large variation in statistical weights and reduction in the effective sampling size. To abate this reweighting problem, here, we propose a general accelerated molecular dynamics (aMD) approach in which only the rotatable dihedrals are subjected to aMD (RaMD), unlike the typical implementation wherein all dihedrals are boosted (all-aMD). Nonrotatable and improper dihedrals are marginally important to conformational changes or the different rotameric states. Not accelerating them avoids the sharp increases in the potential energies due to small deviations from their minimum energy conformations and leads to improvement in the precision of RaMD. We present benchmark studies on two model dipeptides, Ace-Ala-Nme and Ace-Trp-Nme, simulated with normal MD, all-aMD, and RaMD. We carry out a systematic comparison between the performances of both forms of aMD using a theory that allows quantitative estimation of the effective number of sampled points and the associated uncertainty. Our results indicate that, for the same level of acceleration and simulation length, as used in all-aMD, RaMD results in significantly less loss in the effective sample size and, hence, increased accuracy in the sampling of φ-ψ space. RaMD yields an accuracy comparable to that of all-aMD, from simulation lengths 5 to 1000 times shorter, depending on the peptide and the acceleration level. Such improvement in speed and accuracy over all-aMD is highly remarkable, suggesting RaMD as a promising method for sampling larger biomolecules.

Statistical similarities of pre-earthquake electromagnetic emissions to biological and economic extreme events

NASA Astrophysics Data System (ADS)

Potirakis, Stelios M.; Contoyiannis, Yiannis; Kopanas, John; Kalimeris, Anastasios; Antonopoulos, George; Peratzakis, Athanasios; Eftaxias, Konstantinos; Nomicos, Costantinos

2014-05-01

When one considers a phenomenon that is "complex" refers to a system whose phenomenological laws that describe the global behavior of the system, are not necessarily directly related to the "microscopic" laws that regulate the evolution of its elementary parts. The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe disparate problems ranging from particle physics to economies of societies. Several authors have suggested that earthquake (EQ) dynamics can be analyzed within similar mathematical frameworks with economy dynamics, and neurodynamics. A central property of the EQ preparation process is the occurrence of coherent large-scale collective behavior with a very rich structure, resulting from repeated nonlinear interactions among the constituents of the system. As a result, nonextensive statistics is an appropriate, physically meaningful, tool for the study of EQ dynamics. Since the fracture induced electromagnetic (EM) precursors are observable manifestations of the underlying EQ preparation process, the analysis of a fracture induced EM precursor observed prior to the occurrence of a large EQ can also be conducted within the nonextensive statistics framework. Within the frame of the investigation for universal principles that may hold for different dynamical systems that are related to the genesis of extreme events, we present here statistical similarities of the pre-earthquake EM emissions related to an EQ, with the pre-ictal electrical brain activity related to an epileptic seizure, and with the pre-crisis economic observables related to the collapse of a share. It is demonstrated the all three dynamical systems' observables can be analyzed in the frame of nonextensive statistical mechanics, while the frequency-size relations of appropriately defined "events" that precede the extreme event related to each one of these different systems present striking quantitative

A statistical model of the human core-temperature circadian rhythm

NASA Technical Reports Server (NTRS)

Brown, E. N.; Choe, Y.; Luithardt, H.; Czeisler, C. A.

2000-01-01

We formulate a statistical model of the human core-temperature circadian rhythm in which the circadian signal is modeled as a van der Pol oscillator, the thermoregulatory response is represented as a first-order autoregressive process, and the evoked effect of activity is modeled with a function specific for each circadian protocol. The new model directly links differential equation-based simulation models and harmonic regression analysis methods and permits statistical analysis of both static and dynamical properties of the circadian pacemaker from experimental data. We estimate the model parameters by using numerically efficient maximum likelihood algorithms and analyze human core-temperature data from forced desynchrony, free-run, and constant-routine protocols. By representing explicitly the dynamical effects of ambient light input to the human circadian pacemaker, the new model can estimate with high precision the correct intrinsic period of this oscillator ( approximately 24 h) from both free-run and forced desynchrony studies. Although the van der Pol model approximates well the dynamical features of the circadian pacemaker, the optimal dynamical model of the human biological clock may have a harmonic structure different from that of the van der Pol oscillator.

Emergent Irreversibility and Entanglement Spectrum Statistics

NASA Astrophysics Data System (ADS)

Chamon, Claudio; Hamma, Alioscia; Mucciolo, Eduardo R.

2014-06-01

We study the problem of irreversibility when the dynamical evolution of a many-body system is described by a stochastic quantum circuit. Such evolution is more general than a Hamiltonian one, and since energy levels are not well defined, the well-established connection between the statistical fluctuations of the energy spectrum and irreversibility cannot be made. We show that the entanglement spectrum provides a more general connection. Irreversibility is marked by a failure of a disentangling algorithm and is preceded by the appearance of Wigner-Dyson statistical fluctuations in the entanglement spectrum. This analysis can be done at the wave-function level and offers an alternative route to study quantum chaos and quantum integrability.

Thermostatistically approaching living systems: Boltzmann Gibbs or nonextensive statistical mechanics?

NASA Astrophysics Data System (ADS)

Tsallis, Constantino

2006-03-01

Boltzmann-Gibbs ( BG) statistical mechanics is, since well over one century, successfully used for many nonlinear dynamical systems which, in one way or another, exhibit strong chaos. A typical case is a classical many-body short-range-interacting Hamiltonian system (e.g., the Lennard-Jones model for a real gas at moderately high temperature). Its Lyapunov spectrum (which characterizes the sensitivity to initial conditions) includes positive values. This leads to ergodicity, the stationary state being thermal equilibrium, hence standard applicability of the BG theory is verified. The situation appears to be of a different nature for various phenomena occurring in living organisms. Indeed, such systems exhibit a complexity which does not really accommodate with this standard dynamical behavior. Life appears to emerge and evolve in a kind of delicate situation, at the frontier between large order (low adaptability and long memory; typically characterized by regular dynamics, hence only nonpositive Lyapunov exponents) and large disorder (high adaptability and short memory; typically characterized by strong chaos, hence at least one positive Lyapunov exponent). Along this frontier, the maximal relevant Lyapunov exponents are either zero or close to that, characterizing what is currently referred to as weak chaos. This type of situation is shared by a great variety of similar complex phenomena in economics, linguistics, to cite but a few. BG statistical mechanics is built upon the entropy S=-k∑plnp. A generalization of this form, S=k(1-∑piq)/(q-1) (with S=S), has been proposed in 1988 as a basis for formulating what is nowadays currently called nonextensive statistical mechanics. This theory appears to be particularly adapted for nonlinear dynamical systems exhibiting, precisely, weak chaos. Here, we briefly review the theory, its dynamical foundation, its applications in a variety of disciplines (with special emphasis to living systems), and its connections with

Environmental statistics and optimal regulation

NASA Astrophysics Data System (ADS)

Sivak, David; Thomson, Matt

2015-03-01

The precision with which an organism can detect its environment, and the timescale for and statistics of environmental change, will affect the suitability of different strategies for regulating protein levels in response to environmental inputs. We propose a general framework--here applied to the enzymatic regulation of metabolism in response to changing nutrient concentrations--to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, and the costs associated with enzyme production. We find: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones.

Medical facility statistics in Japan

PubMed Central

Hamajima, Nobuyuki; Sugimoto, Takuya; Hasebe, Ryo; Myat Cho, Su; Khaing, Moe; Kariya, Tetsuyoshi; Mon Saw, Yu; Yamamoto, Eiko

2017-01-01

ABSTRACT Medical facility statistics provide essential information to policymakers, administrators, academics, and practitioners in the field of health services. In Japan, the Health Statistics Office of the Director-General for Statistics and Information Policy at the Ministry of Health, Labour and Welfare is generating these statistics. Although the statistics are widely available in both Japanese and English, the methodology described in the technical reports are primarily in Japanese, and are not fully described in English. This article aimed to describe these processes for readers in the English-speaking world. The Health Statistics Office routinely conduct two surveys called the Hospital Report and the Survey of Medical Institutions. The subjects of the former are all the hospitals and clinics with long-term care beds in Japan. It comprises a Patient Questionnaire focusing on the numbers of inpatients, admissions, discharges, and outpatients in one month, and an Employee Questionnaire, which asks about the number of employees as of October 1. The Survey of Medical Institutions consists of the Dynamic Survey, which focuses on the opening and closing of facilities every month, and the Static Survey, which focuses on staff, facilities, and services as of October 1, as well as the number of inpatients as of September 30 and the total number of outpatients during September. All hospitals, clinics, and dental clinics are requested to submit the Static Survey questionnaire every three years. These surveys are useful tools for collecting essential information, as well as providing occasions to implicitly inform facilities of the movements of government policy. PMID:29238108

Medical facility statistics in Japan.

PubMed

Hamajima, Nobuyuki; Sugimoto, Takuya; Hasebe, Ryo; Myat Cho, Su; Khaing, Moe; Kariya, Tetsuyoshi; Mon Saw, Yu; Yamamoto, Eiko

2017-11-01

Medical facility statistics provide essential information to policymakers, administrators, academics, and practitioners in the field of health services. In Japan, the Health Statistics Office of the Director-General for Statistics and Information Policy at the Ministry of Health, Labour and Welfare is generating these statistics. Although the statistics are widely available in both Japanese and English, the methodology described in the technical reports are primarily in Japanese, and are not fully described in English. This article aimed to describe these processes for readers in the English-speaking world. The Health Statistics Office routinely conduct two surveys called the Hospital Report and the Survey of Medical Institutions. The subjects of the former are all the hospitals and clinics with long-term care beds in Japan. It comprises a Patient Questionnaire focusing on the numbers of inpatients, admissions, discharges, and outpatients in one month, and an Employee Questionnaire, which asks about the number of employees as of October 1. The Survey of Medical Institutions consists of the Dynamic Survey, which focuses on the opening and closing of facilities every month, and the Static Survey, which focuses on staff, facilities, and services as of October 1, as well as the number of inpatients as of September 30 and the total number of outpatients during September. All hospitals, clinics, and dental clinics are requested to submit the Static Survey questionnaire every three years. These surveys are useful tools for collecting essential information, as well as providing occasions to implicitly inform facilities of the movements of government policy.

Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

PubMed Central

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

Uniting statistical and individual-based approaches for animal movement modelling.

PubMed

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Management of Limited Vertical Bone Height in the Posterior Mandible: Short Dental Implants Versus Nerve Lateralization With Standard Length Implants.

PubMed

Dursun, Erhan; Keceli, Huseyin Gencay; Uysal, Serdar; Güngör, Hamiyet; Muhtarogullari, Mehmet; Tözüm, Tolga Fikret

2016-05-01

Inferior alveolar nerve lateralization (IANL) and short dental implants (SDI) are 2 viable implant-based treatment approaches in the presence of atrophied posterior mandible. Despite the risks of dysfunction, infection, and pathologic fractures in IANL, it becomes possible to place standard implants. The purpose of this study was to compare SDI and IANL approaches from clinical and radiographic aspects. Fifteen subjects having unilateral atrophic mandibles were allocated to SDI and IANL treatment groups. Following surgical procedures, early postoperative complications, implant survival, and periimplant clinical and radiographic parameters including probing pocket depth, attachment level, keratinized tissue amount, vertical tissue recession, and marginal bone loss were recorded at baseline and 1-year after prosthetic rehabilitation. In both groups, no implant was lost. Except usual postoperative complications, 2 patients had transient paraesthesia after IANL. According to time-dependent evaluation, both groups showed significant increase in probing pocket depth and attachment level at 1-year follow-up compared with baseline (P < 0.05). Except a slight but significant increase in mesial surface of SDI group (P < 0.05), no remarkable time-dependent change was identified in vertical tissue recession. Keratinized tissue amount did not exhibit any inter- or intragroup difference during whole study period. Marginal bone loss did not show any difference between IANL and SDI groups at follow-up. SDI placement or standard length implant placement with IANL can be considered promising alternatives in the treatment of atrophic mandibular posterior regions. However, SDI may be preferred in terms of lower complication risk.

Statistical inference to advance network models in epidemiology.

PubMed

Welch, David; Bansal, Shweta; Hunter, David R

2011-03-01

Contact networks are playing an increasingly important role in the study of epidemiology. Most of the existing work in this area has focused on considering the effect of underlying network structure on epidemic dynamics by using tools from probability theory and computer simulation. This work has provided much insight on the role that heterogeneity in host contact patterns plays on infectious disease dynamics. Despite the important understanding afforded by the probability and simulation paradigm, this approach does not directly address important questions about the structure of contact networks such as what is the best network model for a particular mode of disease transmission, how parameter values of a given model should be estimated, or how precisely the data allow us to estimate these parameter values. We argue that these questions are best answered within a statistical framework and discuss the role of statistical inference in estimating contact networks from epidemiological data. Copyright © 2011 Elsevier B.V. All rights reserved.

On the statistical mechanics of species abundance distributions.

PubMed

Bowler, Michael G; Kelly, Colleen K

2012-09-01

A central issue in ecology is that of the factors determining the relative abundance of species within a natural community. The proper application of the principles of statistical physics to species abundance distributions (SADs) shows that simple ecological properties could account for the near universal features observed. These properties are (i) a limit on the number of individuals in an ecological guild and (ii) per capita birth and death rates. They underpin the neutral theory of Hubbell (2001), the master equation approach of Volkov et al. (2003, 2005) and the idiosyncratic (extreme niche) theory of Pueyo et al. (2007); they result in an underlying log series SAD, regardless of neutral or niche dynamics. The success of statistical mechanics in this application implies that communities are in dynamic equilibrium and hence that niches must be flexible and that temporal fluctuations on all sorts of scales are likely to be important in community structure. Copyright © 2012 Elsevier Inc. All rights reserved.

A Unified Statistical Rain-Attenuation Model for Communication Link Fade Predictions and Optimal Stochastic Fade Control Design Using a Location-Dependent Rain-Statistic Database

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1990-01-01

A static and dynamic rain-attenuation model is presented which describes the statistics of attenuation on an arbitrarily specified satellite link for any location for which there are long-term rainfall statistics. The model may be used in the design of the optimal stochastic control algorithms to mitigate the effects of attenuation and maintain link reliability. A rain-statistics data base is compiled, which makes it possible to apply the model to any location in the continental U.S. with a resolution of 0-5 degrees in latitude and longitude. The model predictions are compared with experimental observations, showing good agreement.

Long-range memory and non-Markov statistical effects in human sensorimotor coordination

NASA Astrophysics Data System (ADS)

M. Yulmetyev, Renat; Emelyanova, Natalya; Hänggi, Peter; Gafarov, Fail; Prokhorov, Alexander

2002-12-01

In this paper, the non-Markov statistical processes and long-range memory effects in human sensorimotor coordination are investigated. The theoretical basis of this study is the statistical theory of non-stationary discrete non-Markov processes in complex systems (Phys. Rev. E 62, 6178 (2000)). The human sensorimotor coordination was experimentally studied by means of standard dynamical tapping test on the group of 32 young peoples with tap numbers up to 400. This test was carried out separately for the right and the left hand according to the degree of domination of each brain hemisphere. The numerical analysis of the experimental results was made with the help of power spectra of the initial time correlation function, the memory functions of low orders and the first three points of the statistical spectrum of non-Markovity parameter. Our observations demonstrate, that with the regard to results of the standard dynamic tapping-test it is possible to divide all examinees into five different dynamic types. We have introduced the conflict coefficient to estimate quantitatively the order-disorder effects underlying life systems. The last one reflects the existence of disbalance between the nervous and the motor human coordination. The suggested classification of the neurophysiological activity represents the dynamic generalization of the well-known neuropsychological types and provides the new approach in a modern neuropsychology.

Recurrence time statistics for finite size intervals

NASA Astrophysics Data System (ADS)

Altmann, Eduardo G.; da Silva, Elton C.; Caldas, Iberê L.

2004-12-01

We investigate the statistics of recurrences to finite size intervals for chaotic dynamical systems. We find that the typical distribution presents an exponential decay for almost all recurrence times except for a few short times affected by a kind of memory effect. We interpret this effect as being related to the unstable periodic orbits inside the interval. Although it is restricted to a few short times it changes the whole distribution of recurrences. We show that for systems with strong mixing properties the exponential decay converges to the Poissonian statistics when the width of the interval goes to zero. However, we alert that special attention to the size of the interval is required in order to guarantee that the short time memory effect is negligible when one is interested in numerically or experimentally calculated Poincaré recurrence time statistics.

Spatio-Temporal Dynamic Analysis of Sustainable Development in China Based on the Footprint Family.

PubMed

Zhao, Jing; Ma, Caihong; Zhao, Xiangui; Wang, Xiaoyu

2018-02-01

The existing index systems on sustainable evaluation are mostly based on a multi index comprehensive evaluation method. The main disadvantage of this approach is that the selection and assignment of evaluation indexes are greatly influenced by subjective factors, which can result in poor comparability of results. By contrast, the Footprint Family (including ecological footprint, carbon footprint, and water footprint) is not affected by subjective factors. The Footprint Family also covers the basic tenets of sustainable development. This paper proposes use of a sustainable development evaluation index system based on the principle of the Footprint Family, and including the ecological pressure index ( EPI ), the ecological occupancy index ( EOI ), the ecological economic coordination index ( EECI ), the GHG (Greenhouse Gas) emission index ( CEI ), the water resources stress index ( WSI ), and the sustainable development index ( SDI ). Furthermore, a standard for grading the evaluated results based on global benchmarks is formulated. The results of an empirical study in China were the following. The development situation deteriorated from 1990 to 2015. The results showed that the SDI decreased from a medium level (grade 5) to a lower-medium level (grade 4). The results of this empirical study also showed that the method of evaluation can avoid the influence of subjective factors and can be used in the evaluation of sustainable development for various temporal and spatial conditions.

Spatio-Temporal Dynamic Analysis of Sustainable Development in China Based on the Footprint Family

PubMed Central

Ma, Caihong; Zhao, Xiangui; Wang, Xiaoyu

2018-01-01

The existing index systems on sustainable evaluation are mostly based on a multi index comprehensive evaluation method. The main disadvantage of this approach is that the selection and assignment of evaluation indexes are greatly influenced by subjective factors, which can result in poor comparability of results. By contrast, the Footprint Family (including ecological footprint, carbon footprint, and water footprint) is not affected by subjective factors. The Footprint Family also covers the basic tenets of sustainable development. This paper proposes use of a sustainable development evaluation index system based on the principle of the Footprint Family, and including the ecological pressure index (EPI), the ecological occupancy index (EOI), the ecological economic coordination index (EECI), the GHG (Greenhouse Gas) emission index (CEI), the water resources stress index (WSI), and the sustainable development index (SDI). Furthermore, a standard for grading the evaluated results based on global benchmarks is formulated. The results of an empirical study in China were the following. The development situation deteriorated from 1990 to 2015. The results showed that the SDI decreased from a medium level (grade 5) to a lower-medium level (grade 4). The results of this empirical study also showed that the method of evaluation can avoid the influence of subjective factors and can be used in the evaluation of sustainable development for various temporal and spatial conditions. PMID:29389886

Quantifying economic fluctuations by adapting methods of statistical physics

NASA Astrophysics Data System (ADS)

Plerou, Vasiliki

2001-09-01

The first focus of this thesis is the investigation of cross-correlations between the price fluctuations of different stocks using the conceptual framework of random matrix theory (RMT), developed in physics to describe the statistical properties of energy-level spectra of complex nuclei. RMT makes predictions for the statistical properties of matrices that are universal, i.e., do not depend on the interactions between the elements comprising the system. In physical systems, deviations from the predictions of RMT provide clues regarding the mechanisms controlling the dynamics of a given system so this framework is of potential value if applied to economic systems. This thesis compares the statistics of cross-correlation matrix C-whose elements Cij are the correlation coefficients of price fluctuations of stock i and j-against the ``null hypothesis'' of a random matrix having the same symmetry properties. It is shown that comparison of the eigenvalue statistics of C with RMT results can be used to distinguish random and non-random parts of C. The non-random part of C which deviates from RMT results, provides information regarding genuine cross-correlations between stocks. The interpretations and potential practical utility of these deviations are also investigated. The second focus is the characterization of the dynamics of stock price fluctuations. The statistical properties of the changes G Δt in price over a time interval Δ t are quantified and the statistical relation between G Δt and the trading activity-measured by the number of transactions NΔ t in the interval Δt is investigated. The statistical properties of the volatility, i.e., the time dependent standard deviation of price fluctuations, is related to two microscopic quantities: NΔt and the variance W2Dt of the price changes for all transactions in the interval Δ t. In addition, the statistical relationship between G Δt and the number of

Peripheral vascular damage in systemic lupus erythematosus: data from LUMINA, a large multi-ethnic U.S. cohort (LXIX).

PubMed

Burgos, P I; Vilá, L M; Reveille, J D; Alarcón, G S

2009-12-01

To determine the factors associated with peripheral vascular damage in systemic lupus erythematosus patients and its impact on survival from Lupus in Minorities, Nature versus Nurture, a longitudinal US multi-ethnic cohort. Peripheral vascular damage was defined by the Systemic Lupus International Collaborating Clinics Damage Index (SDI). Factors associated with peripheral vascular damage were examined by univariable and multi-variable logistic regression models and its impact on survival by a Cox multi-variable regression. Thirty-four (5.3%) of 637 patients (90% women, mean [SD] age 36.5 [12.6] [16-87] years) developed peripheral vascular damage. Age and the SDI (without peripheral vascular damage) were statistically significant (odds ratio [OR] = 1.05, 95% confidence interval [CI] 1.01-1.08; P = 0.0107 and OR = 1.30, 95% CI 0.09-1.56; P = 0.0043, respectively) in multi-variable analyses. Azathioprine, warfarin and statins were also statistically significant, and glucocorticoid use was borderline statistically significant (OR = 1.03, 95% CI 0.10-1.06; P = 0.0975). In the survival analysis, peripheral vascular damage was independently associated with a diminished survival (hazard ratio = 2.36; 95% CI 1.07-5.19; P = 0.0334). In short, age was independently associated with peripheral vascular damage, but so was the presence of damage in other organs (ocular, neuropsychiatric, renal, cardiovascular, pulmonary, musculoskeletal and integument) and some medications (probably reflecting more severe disease). Peripheral vascular damage also negatively affected survival.

Capturing rogue waves by multi-point statistics

NASA Astrophysics Data System (ADS)

Hadjihosseini, A.; Wächter, Matthias; Hoffmann, N. P.; Peinke, J.

2016-01-01

As an example of a complex system with extreme events, we investigate ocean wave states exhibiting rogue waves. We present a statistical method of data analysis based on multi-point statistics which for the first time allows the grasping of extreme rogue wave events in a highly satisfactory statistical manner. The key to the success of the approach is mapping the complexity of multi-point data onto the statistics of hierarchically ordered height increments for different time scales, for which we can show that a stochastic cascade process with Markov properties is governed by a Fokker-Planck equation. Conditional probabilities as well as the Fokker-Planck equation itself can be estimated directly from the available observational data. With this stochastic description surrogate data sets can in turn be generated, which makes it possible to work out arbitrary statistical features of the complex sea state in general, and extreme rogue wave events in particular. The results also open up new perspectives for forecasting the occurrence probability of extreme rogue wave events, and even for forecasting the occurrence of individual rogue waves based on precursory dynamics.

Nonlinear Dynamics, Chaotic and Complex Systems

NASA Astrophysics Data System (ADS)

Infeld, E.; Zelazny, R.; Galkowski, A.

2011-04-01

Part I. Dynamic Systems Bifurcation Theory and Chaos: 1. Chaos in random dynamical systems V. M. Gunldach; 2. Controlling chaos using embedded unstable periodic orbits: the problem of optimal periodic orbits B. R. Hunt and E. Ott; 3. Chaotic tracer dynamics in open hydrodynamical flows G. Karolyi, A. Pentek, T. Tel and Z. Toroczkai; 4. Homoclinic chaos L. P. Shilnikov; Part II. Spatially Extended Systems: 5. Hydrodynamics of relativistic probability flows I. Bialynicki-Birula; 6. Waves in ionic reaction-diffusion-migration systems P. Hasal, V. Nevoral, I. Schreiber, H. Sevcikova, D. Snita, and M. Marek; 7. Anomalous scaling in turbulence: a field theoretical approach V. Lvov and I. Procaccia; 8. Abelian sandpile cellular automata M. Markosova; 9. Transport in an incompletely chaotic magnetic field F. Spineanu; Part III. Dynamical Chaos Quantum Physics and Foundations Of Statistical Mechanics: 10. Non-equilibrium statistical mechanics and ergodic theory L. A. Bunimovich; 11. Pseudochaos in statistical physics B. Chirikov; 12. Foundations of non-equilibrium statistical mechanics J. P. Dougherty; 13. Thermomechanical particle simulations W. G. Hoover, H. A. Posch, C. H. Dellago, O. Kum, C. G. Hoover, A. J. De Groot and B. L. Holian; 14. Quantum dynamics on a Markov background and irreversibility B. Pavlov; 15. Time chaos and the laws of nature I. Prigogine and D. J. Driebe; 16. Evolutionary Q and cognitive systems: dynamic entropies and predictability of evolutionary processes W. Ebeling; 17. Spatiotemporal chaos information processing in neural networks H. Szu; 18. Phase transitions and learning in neural networks C. Van den Broeck; 19. Synthesis of chaos A. Vanecek and S. Celikovsky; 20. Computational complexity of continuous problems H. Wozniakowski; Part IV. Complex Systems As An Interface Between Natural Sciences and Environmental Social and Economic Sciences: 21. Stochastic differential geometry in finance studies V. G. Makhankov; Part V. Conference Banquet

Statistical physics of vaccination

NASA Astrophysics Data System (ADS)

Wang, Zhen; Bauch, Chris T.; Bhattacharyya, Samit; d'Onofrio, Alberto; Manfredi, Piero; Perc, Matjaž; Perra, Nicola; Salathé, Marcel; Zhao, Dawei

2016-12-01

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination-one of the most important preventive measures of modern times-is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research.

Capture approximations beyond a statistical quantum mechanical method for atom-diatom reactions

NASA Astrophysics Data System (ADS)

Barrios, Lizandra; Rubayo-Soneira, Jesús; González-Lezana, Tomás

2016-03-01

Statistical techniques constitute useful approaches to investigate atom-diatom reactions mediated by insertion dynamics which involves complex-forming mechanisms. Different capture schemes based on energy considerations regarding the specific diatom rovibrational states are suggested to evaluate the corresponding probabilities of formation of such collision species between reactants and products in an attempt to test reliable alternatives for computationally demanding processes. These approximations are tested in combination with a statistical quantum mechanical method for the S + H2(v = 0 ,j = 1) → SH + H and Si + O2(v = 0 ,j = 1) → SiO + O reactions, where this dynamical mechanism plays a significant role, in order to probe their validity.

Statistical methodologies for the control of dynamic remapping

NASA Technical Reports Server (NTRS)

Saltz, J. H.; Nicol, D. M.

1986-01-01

Following an initial mapping of a problem onto a multiprocessor machine or computer network, system performance often deteriorates with time. In order to maintain high performance, it may be necessary to remap the problem. The decision to remap must take into account measurements of performance deterioration, the cost of remapping, and the estimated benefits achieved by remapping. We examine the tradeoff between the costs and the benefits of remapping two qualitatively different kinds of problems. One problem assumes that performance deteriorates gradually, the other assumes that performance deteriorates suddenly. We consider a variety of policies for governing when to remap. In order to evaluate these policies, statistical models of problem behaviors are developed. Simulation results are presented which compare simple policies with computationally expensive optimal decision policies; these results demonstrate that for each problem type, the proposed simple policies are effective and robust.

The relationship between poor sleep and inhibitory functions indicated by event-related potentials.

PubMed

Breimhorst, Markus; Falkenstein, Michael; Marks, Anke; Griefahn, Barbara

2008-06-01

The present study focused on the relationship between normal variations of sleep and inhibitory functions as reflected in event-related potentials. For this reason one night of 21 healthy participants was analysed. After waking up all participants completed a visual Go/Nogo task. On the basis of a sleep disturbance index (SDI) the participants were separated into 8 SDI-good and 13 SDI-poor sleepers using a cluster analysis. The results showed that Nogo-N2 amplitude was smaller and Nogo-P3 latency longer in SDI-poor sleepers. Moreover, Go-P3 amplitude was smaller in SDI-poor sleepers. Performance parameters were not influenced by poor sleep. We concluded that poor sleep specifically affects the intensity of pre-motor inhibitory processes (Nogo-N2 amplitude), the speed to inhibit a motor response (Nogo-P3 latency) and the intensity of task-relevant information processing (Go-P3 amplitude). In further studies, it should be explored under which conditions such subliminal deficits also become relevant for overt behaviour.

Master-slave interferometry for parallel spectral domain interferometry sensing and versatile 3D optical coherence tomography.

PubMed

Podoleanu, Adrian Gh; Bradu, Adrian

2013-08-12

Conventional spectral domain interferometry (SDI) methods suffer from the need of data linearization. When applied to optical coherence tomography (OCT), conventional SDI methods are limited in their 3D capability, as they cannot deliver direct en-face cuts. Here we introduce a novel SDI method, which eliminates these disadvantages. We denote this method as Master - Slave Interferometry (MSI), because a signal is acquired by a slave interferometer for an optical path difference (OPD) value determined by a master interferometer. The MSI method radically changes the main building block of an SDI sensor and of a spectral domain OCT set-up. The serially provided signal in conventional technology is replaced by multiple signals, a signal for each OPD point in the object investigated. This opens novel avenues in parallel sensing and in parallelization of signal processing in 3D-OCT, with applications in high- resolution medical imaging and microscopy investigation of biosamples. Eliminating the need of linearization leads to lower cost OCT systems and opens potential avenues in increasing the speed of production of en-face OCT images in comparison with conventional SDI.

Statistical mechanics of self-driven Carnot cycles.

PubMed

Smith, E

1999-10-01

The spontaneous generation and finite-amplitude saturation of sound, in a traveling-wave thermoacoustic engine, are derived as properties of a second-order phase transition. It has previously been argued that this dynamical phase transition, called "onset," has an equivalent equilibrium representation, but the saturation mechanism and scaling were not computed. In this work, the sound modes implementing the engine cycle are coarse-grained and statistically averaged, in a partition function derived from microscopic dynamics on criteria of scale invariance. Self-amplification performed by the engine cycle is introduced through higher-order modal interactions. Stationary points and fluctuations of the resulting phenomenological Lagrangian are analyzed and related to background dynamical currents. The scaling of the stable sound amplitude near the critical point is derived and shown to arise universally from the interaction of finite-temperature disorder, with the order induced by self-amplification.

Response statistics of rotating shaft with non-linear elastic restoring forces by path integration

NASA Astrophysics Data System (ADS)

Gaidai, Oleg; Naess, Arvid; Dimentberg, Michael

2017-07-01

Extreme statistics of random vibrations is studied for a Jeffcott rotor under uniaxial white noise excitation. Restoring force is modelled as elastic non-linear; comparison is done with linearized restoring force to see the force non-linearity effect on the response statistics. While for the linear model analytical solutions and stability conditions are available, it is not generally the case for non-linear system except for some special cases. The statistics of non-linear case is studied by applying path integration (PI) method, which is based on the Markov property of the coupled dynamic system. The Jeffcott rotor response statistics can be obtained by solving the Fokker-Planck (FP) equation of the 4D dynamic system. An efficient implementation of PI algorithm is applied, namely fast Fourier transform (FFT) is used to simulate dynamic system additive noise. The latter allows significantly reduce computational time, compared to the classical PI. Excitation is modelled as Gaussian white noise, however any kind distributed white noise can be implemented with the same PI technique. Also multidirectional Markov noise can be modelled with PI in the same way as unidirectional. PI is accelerated by using Monte Carlo (MC) estimated joint probability density function (PDF) as initial input. Symmetry of dynamic system was utilized to afford higher mesh resolution. Both internal (rotating) and external damping are included in mechanical model of the rotor. The main advantage of using PI rather than MC is that PI offers high accuracy in the probability distribution tail. The latter is of critical importance for e.g. extreme value statistics, system reliability, and first passage probability.

The Shock and Vibration Bulletin. Part 2. Invited Papers, Structural Dynamics

DTIC Science & Technology

1974-08-01

VIKING LANDER DYNAMICS 41 Mr. Joseph C. Pohlen, Martin Marietta Aerospace, Denver, Colorado Structural Dynamics PERFORMANCE OF STATISTICAL ENERGY ANALYSIS 47...aerospace structures. Analytical prediction of these environments is beyond the current scope of classical modal techniques. Statistical energy analysis methods...have been developed that circumvent the difficulties of high-frequency nodal analysis. These statistical energy analysis methods are evaluated

Use of Data Visualisation in the Teaching of Statistics: A New Zealand Perspective

ERIC Educational Resources Information Center

Forbes, Sharleen; Chapman, Jeanette; Harraway, John; Stirling, Doug; Wild, Chris

2014-01-01

For many years, students have been taught to visualise data by drawing graphs. Recently, there has been a growing trend to teach statistics, particularly statistical concepts, using interactive and dynamic visualisation tools. Free down-loadable teaching and simulation software designed specifically for schools, and more general data visualisation…

Experimental Determination of Dynamical Lee-Yang Zeros

NASA Astrophysics Data System (ADS)

Brandner, Kay; Maisi, Ville F.; Pekola, Jukka P.; Garrahan, Juan P.; Flindt, Christian

2017-05-01

Statistical physics provides the concepts and methods to explain the phase behavior of interacting many-body systems. Investigations of Lee-Yang zeros—complex singularities of the free energy in systems of finite size—have led to a unified understanding of equilibrium phase transitions. The ideas of Lee and Yang, however, are not restricted to equilibrium phenomena. Recently, Lee-Yang zeros have been used to characterize nonequilibrium processes such as dynamical phase transitions in quantum systems after a quench or dynamic order-disorder transitions in glasses. Here, we experimentally realize a scheme for determining Lee-Yang zeros in such nonequilibrium settings. We extract the dynamical Lee-Yang zeros of a stochastic process involving Andreev tunneling between a normal-state island and two superconducting leads from measurements of the dynamical activity along a trajectory. From the short-time behavior of the Lee-Yang zeros, we predict the large-deviation statistics of the activity which is typically difficult to measure. Our method paves the way for further experiments on the statistical mechanics of many-body systems out of equilibrium.

Sex modulates approach systems and impulsivity in substance dependence.

PubMed

Perry, Robert I; Krmpotich, Theodore; Thompson, Laetitia L; Mikulich-Gilbertson, Susan K; Banich, Marie T; Tanabe, Jody

2013-11-01

Personality traits such as pathological engagement in approach behaviors, high levels of impulsivity and heightened negative affect are consistently observed in substance dependent individuals (SDI). The clinical course of addiction has been shown to differ between sexes. For example, women increase their rates of consumption of some drugs of abuse more quickly than men. Despite the potential influence of personality and sex on features of addiction, few studies have investigated the interaction of these factors in substance dependence. Fifty-one SDI (26 males, 25 females) and 66 controls (41 males, 25 females) completed the Behavioral Inhibition/Behavioral Activation System (BIS/BAS) Scales, the Barratt Impulsiveness Scale, and the Positive and Negative Affect Schedule (PANAS-X). Data were analyzed with 2×2 ANCOVAs testing for main effects of group, sex and group by sex interactions, adjusting for education level. Significant group by sex interactions were observed for BAS scores [F(1,116)=7.03, p<.01] and Barratt Motor Impulsiveness [F(1,116)=6.11, p<.02] with female SDI showing the highest approach tendencies and impulsivity followed by male SDI, male controls, and finally female controls. SDI scored higher on negative affect [F(1,116)=25.23, p<.001] than controls. Behavioral Inhibition System scores were higher in women than men [F(1,116)=14.03, p<.001]. Higher BAS and motor impulsivity in SDI women relative to SDI men and control women suggest that personality traits that have been previously associated with drug use may be modulated by sex. These factors may contribute to differences in the disease course observed in male compared to female drug users. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Development and Initial Validation of the Self-Assessed Lupus Damage Index Questionnaire (LDIQ)

PubMed Central

Costenbader, Karen H.; Khamashta, Munther; Ruiz-Garcia, Silvia; Perez-Rodriguez, Maria Teresa; Petri, Michelle; Elliott, Jennifer; Manzi, Susan; Karlson, Elizabeth W.; Turner-Stokes, Tabitha; Bermas, Bonnie; Coblyn, Jonathan; Massarotti, Elena; Schur, Peter; Fraser, Patricia; Navarro, Iris; Hanly, John G.; Shaver, Timothy S.; Katz, Robert S.; Chakravarty, Eliza; Fortin, Paul R.; Sanchez, Martha L.; Liu, Jigna; Michaud, Kaleb; Alarcón, Graciela S.; Wolfe, Frederick

2010-01-01

Purpose The SLICC Damage Index (SDI) is a validated instrument for assessing organ damage in systemic lupus erythematosus (SLE). Trained physicians must complete it, limiting utility where this is impossible. Methods We developed and pilot-tested a self-assessed organ damage instrument, the Lupus Damage Index Questionnaire (LDIQ), in 37 SLE subjects and 7 physicians. After refinement, 569 English-speaking SLE subjects and 14 rheumatologists from 11 international SLE clinics participated in validation. Subjects and physicians completed instruments separately. We calculated sensitivity, specificity, Spearman correlations and agreement, using the SDI as gold standard. 605 SLE participants in the community-based National Data Bank for Rheumatic Diseases (NDB) study completed the LDIQ and we assessed correlations with outcome and disability measures. Results Mean LDIQ score was 3.3 (0-16) and mean SDI score was 1.5 (0-9). LDIQ had a moderately high correlation with SDI (Spearman r=0.50, p<0.001). Specificities of individual LDIQ items were >80%, except for neuropathy. Sensitivities were variable and lowest for damage with <1% prevalence. Agreement between SDI and LDIQ was > 85% for all but neuropathy, reduced renal function, deforming arthritis and alopecia. In the NDB, LDIQ correlated well with comorbidity index (r=0.45), SF-36 physical component scale (0.43), Medical Research Council dyspnea scale (0.40), disability (0.37) and SLE Activity Questionnaire score (0.37). Conclusions The LDIQ’s metric properties are good compared to the SDI. It has construct validity and correlations with health assessments similar to the SDI. The LDIQ should allow expansion of SLE research. Its ultimate value will be determined in longitudinal studies. PMID:20391512

Many-Body Localization and Thermalization in Quantum Statistical Mechanics

NASA Astrophysics Data System (ADS)

Nandkishore, Rahul; Huse, David A.

2015-03-01

We review some recent developments in the statistical mechanics of isolated quantum systems. We provide a brief introduction to quantum thermalization, paying particular attention to the eigenstate thermalization hypothesis (ETH) and the resulting single-eigenstate statistical mechanics. We then focus on a class of systems that fail to quantum thermalize and whose eigenstates violate the ETH: These are the many-body Anderson-localized systems; their long-time properties are not captured by the conventional ensembles of quantum statistical mechanics. These systems can forever locally remember information about their local initial conditions and are thus of interest for possibilities of storing quantum information. We discuss key features of many-body localization (MBL) and review a phenomenology of the MBL phase. Single-eigenstate statistical mechanics within the MBL phase reveal dynamically stable ordered phases, and phase transitions among them, that are invisible to equilibrium statistical mechanics and can occur at high energy and low spatial dimensionality, where equilibrium ordering is forbidden.

Observing fermionic statistics with photons in arbitrary processes

PubMed Central

Matthews, Jonathan C. F.; Poulios, Konstantinos; Meinecke, Jasmin D. A.; Politi, Alberto; Peruzzo, Alberto; Ismail, Nur; Wörhoff, Kerstin; Thompson, Mark G.; O'Brien, Jeremy L.

2013-01-01

Quantum mechanics defines two classes of particles-bosons and fermions-whose exchange statistics fundamentally dictate quantum dynamics. Here we develop a scheme that uses entanglement to directly observe the correlated detection statistics of any number of fermions in any physical process. This approach relies on sending each of the entangled particles through identical copies of the process and by controlling a single phase parameter in the entangled state, the correlated detection statistics can be continuously tuned between bosonic and fermionic statistics. We implement this scheme via two entangled photons shared across the polarisation modes of a single photonic chip to directly mimic the fermion, boson and intermediate behaviour of two-particles undergoing a continuous time quantum walk. The ability to simulate fermions with photons is likely to have applications for verifying boson scattering and for observing particle correlations in analogue simulation using any physical platform that can prepare the entangled state prescribed here. PMID:23531788

Particle statistics and lossy dynamics of ultracold atoms in optical lattices

NASA Astrophysics Data System (ADS)

Yago Malo, J.; van Nieuwenburg, E. P. L.; Fischer, M. H.; Daley, A. J.

2018-05-01

Experimental control over ultracold quantum gases has made it possible to investigate low-dimensional systems of both bosonic and fermionic atoms. In closed one-dimensional systems there are many similarities in the dynamics of local quantities for spinless fermions and strongly interacting "hard-core" bosons, which on a lattice can be formalized via a Jordan-Wigner transformation. In this study, we analyze the similarities and differences for spinless fermions and hard-core bosons on a lattice in the presence of particle loss. The removal of a single fermion causes differences in local quantities compared with the bosonic case because of the different particle exchange symmetry in the two cases. We identify deterministic and probabilistic signatures of these dynamics in terms of local particle density, which could be measured in ongoing experiments with quantum gas microscopes.

Statistical context shapes stimulus-specific adaptation in human auditory cortex

PubMed Central

Henry, Molly J.; Fromboluti, Elisa Kim; McAuley, J. Devin

2015-01-01

Stimulus-specific adaptation is the phenomenon whereby neural response magnitude decreases with repeated stimulation. Inconsistencies between recent nonhuman animal recordings and computational modeling suggest dynamic influences on stimulus-specific adaptation. The present human electroencephalography (EEG) study investigates the potential role of statistical context in dynamically modulating stimulus-specific adaptation by examining the auditory cortex-generated N1 and P2 components. As in previous studies of stimulus-specific adaptation, listeners were presented with oddball sequences in which the presentation of a repeated tone was infrequently interrupted by rare spectral changes taking on three different magnitudes. Critically, the statistical context varied with respect to the probability of small versus large spectral changes within oddball sequences (half of the time a small change was most probable; in the other half a large change was most probable). We observed larger N1 and P2 amplitudes (i.e., release from adaptation) for all spectral changes in the small-change compared with the large-change statistical context. The increase in response magnitude also held for responses to tones presented with high probability, indicating that statistical adaptation can overrule stimulus probability per se in its influence on neural responses. Computational modeling showed that the degree of coadaptation in auditory cortex changed depending on the statistical context, which in turn affected stimulus-specific adaptation. Thus the present data demonstrate that stimulus-specific adaptation in human auditory cortex critically depends on statistical context. Finally, the present results challenge the implicit assumption of stationarity of neural response magnitudes that governs the practice of isolating established deviant-detection responses such as the mismatch negativity. PMID:25652920

Statistical context shapes stimulus-specific adaptation in human auditory cortex.

PubMed

Herrmann, Björn; Henry, Molly J; Fromboluti, Elisa Kim; McAuley, J Devin; Obleser, Jonas

2015-04-01

Stimulus-specific adaptation is the phenomenon whereby neural response magnitude decreases with repeated stimulation. Inconsistencies between recent nonhuman animal recordings and computational modeling suggest dynamic influences on stimulus-specific adaptation. The present human electroencephalography (EEG) study investigates the potential role of statistical context in dynamically modulating stimulus-specific adaptation by examining the auditory cortex-generated N1 and P2 components. As in previous studies of stimulus-specific adaptation, listeners were presented with oddball sequences in which the presentation of a repeated tone was infrequently interrupted by rare spectral changes taking on three different magnitudes. Critically, the statistical context varied with respect to the probability of small versus large spectral changes within oddball sequences (half of the time a small change was most probable; in the other half a large change was most probable). We observed larger N1 and P2 amplitudes (i.e., release from adaptation) for all spectral changes in the small-change compared with the large-change statistical context. The increase in response magnitude also held for responses to tones presented with high probability, indicating that statistical adaptation can overrule stimulus probability per se in its influence on neural responses. Computational modeling showed that the degree of coadaptation in auditory cortex changed depending on the statistical context, which in turn affected stimulus-specific adaptation. Thus the present data demonstrate that stimulus-specific adaptation in human auditory cortex critically depends on statistical context. Finally, the present results challenge the implicit assumption of stationarity of neural response magnitudes that governs the practice of isolating established deviant-detection responses such as the mismatch negativity. Copyright © 2015 the American Physiological Society.

Time Series Expression Analyses Using RNA-seq: A Statistical Approach

PubMed Central

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021

Time series expression analyses using RNA-seq: a statistical approach.

PubMed

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.

Statistical Mechanics of Turbulent Dynamos

NASA Technical Reports Server (NTRS)

Shebalin, John V.

2014-01-01

Incompressible magnetohydrodynamic (MHD) turbulence and magnetic dynamos, which occur in magnetofluids with large fluid and magnetic Reynolds numbers, will be discussed. When Reynolds numbers are large and energy decays slowly, the distribution of energy with respect to length scale becomes quasi-stationary and MHD turbulence can be described statistically. In the limit of infinite Reynolds numbers, viscosity and resistivity become zero and if these values are used in the MHD equations ab initio, a model system called ideal MHD turbulence results. This model system is typically confined in simple geometries with some form of homogeneous boundary conditions, allowing for velocity and magnetic field to be represented by orthogonal function expansions. One advantage to this is that the coefficients of the expansions form a set of nonlinearly interacting variables whose behavior can be described by equilibrium statistical mechanics, i.e., by a canonical ensemble theory based on the global invariants (energy, cross helicity and magnetic helicity) of ideal MHD turbulence. Another advantage is that truncated expansions provide a finite dynamical system whose time evolution can be numerically simulated to test the predictions of the associated statistical mechanics. If ensemble predictions are the same as time averages, then the system is said to be ergodic; if not, the system is nonergodic. Although it had been implicitly assumed in the early days of ideal MHD statistical theory development that these finite dynamical systems were ergodic, numerical simulations provided sufficient evidence that they were, in fact, nonergodic. Specifically, while canonical ensemble theory predicted that expansion coefficients would be (i) zero-mean random variables with (ii) energy that decreased with length scale, it was found that although (ii) was correct, (i) was not and the expected ergodicity was broken. The exact cause of this broken ergodicity was explained, after much

Multiscale Auroral Emission Statistics as Evidence of Turbulent Reconnection in Earth's Midtail Plasma Sheet

NASA Technical Reports Server (NTRS)

Klimas, Alex; Uritsky, Vadim; Donovan, Eric

2010-01-01

We provide indirect evidence for turbulent reconnection in Earth's midtail plasma sheet by reexamining the statistical properties of bright, nightside auroral emission events as observed by the UVI experiment on the Polar spacecraft and discussed previously by Uritsky et al. The events are divided into two groups: (1) those that map to absolute value of (X(sub GSM)) < 12 R(sub E) in the magnetotail and do not show scale-free statistics and (2) those that map to absolute value of (X(sub GSM)) > 12 R(sub E) and do show scale-free statistics. The absolute value of (X(sub GSM)) dependence is shown to most effectively organize the events into these two groups. Power law exponents obtained for group 2 are shown to validate the conclusions of Uritsky et al. concerning the existence of critical dynamics in the auroral emissions. It is suggested that the auroral dynamics is a reflection of a critical state in the magnetotail that is based on the dynamics of turbulent reconnection in the midtail plasma sheet.

Many Scientists Welcome the Reluctance of Congress to Back Large Increases for "Star Wars" Research.

ERIC Educational Resources Information Center

Cordes, Colleen

1987-01-01

Ronald Reagan's Strategic Defense Initiative (SDI) program has inspired heated debate on campuses, and many scientists have pledged not to accept federal money for SDI research, for a variety of political, economic, and scientific reasons. (MSE)

Langmuir waveforms at interplanetary shocks: STEREO statistical analysis

NASA Astrophysics Data System (ADS)

Briand, C.

2016-12-01

Wave-particle interactions and particle acceleration are the two main processes allowing energy dissipation at non collisional shocks. Ion acceleration has been deeply studied for many years, also for their central role in the shock front reformation. Electron dynamics is also important in the shock dynamics through the instabilities they can generate which may impact the ion dynamics.Particle measurements can be efficiently completed by wave measurements to determine the characteristics of the electron beams and study the turbulence of the medium. Electric waveforms obtained from the S/WAVES instrument of the STEREO mission between 2007 to 2014 are analyzed. Thus, clear signature of Langmuir waves are observed on 41 interplanetary shocks. These data enable a statistical analysis and to deduce some characteristics of the electron dynamics on different shocks sources (SIR or ICME) and types (quasi-perpendicular or quasi-parallel). The conversion process between electrostatic to electromagnetic waves has also been tested in several cases.

Arms control and The President's Strategic Defense Initiative

NASA Astrophysics Data System (ADS)

Bon, J. J.

1985-04-01

The President's Strategic Defense Initiative (SDI) provides the hope for eliminating the threat from ballistic missiles. This study evaluates the impact of SDI on existing and future arms control agreements. Because new or modified space-related treaties are a probable result of the SDI, this study concludes that the best single strategy for arms control negotiations is to preserve overall US interests and maintain open technological options vice severely limiting any space technology that might some day become part of a space-based defensive system.

The Impact of Varying Statutory Arrangements on Spatial Data Sharing and Access in Regional NRM Bodies

NASA Astrophysics Data System (ADS)

Paudyal, D. R.; McDougall, K.; Apan, A.

2014-12-01

Spatial information plays an important role in many social, environmental and economic decisions and increasingly acknowledged as a national resource essential for wider societal and environmental benefits. Natural Resource Management is one area where spatial information can be used for improved planning and decision making processes. In Australia, state government organisations are the custodians of spatial information necessary for natural resource management and regional NRM bodies are responsible to regional delivery of NRM activities. The access and sharing of spatial information between government agencies and regional NRM bodies is therefore as an important issue for improving natural resource management outcomes. The aim of this paper is to evaluate the current status of spatial information access, sharing and use with varying statutory arrangements and its impacts on spatial data infrastructure (SDI) development in catchment management sector in Australia. Further, it critically examined whether any trends and significant variations exist due to different institutional arrangements (statutory versus non-statutory) or not. A survey method was used to collect primary data from 56 regional natural resource management (NRM) bodies responsible for catchment management in Australia. Descriptive statistics method was used to show the similarities and differences between statutory and non-statutory arrangements. The key factors which influence sharing and access to spatial information are also explored. The results show the current statutory and administrative arrangements and regional focus for natural resource management is reasonable from a spatial information management perspective and provides an opportunity for building SDI at the catchment scale. However, effective institutional arrangements should align catchment SDI development activities with sub-national and national SDI development activities to address catchment management issues. We found minor

Addressing the statistical mechanics of planet orbits in the solar system

NASA Astrophysics Data System (ADS)

Mogavero, Federico

2017-10-01

The chaotic nature of planet dynamics in the solar system suggests the relevance of a statistical approach to planetary orbits. In such a statistical description, the time-dependent position and velocity of the planets are replaced by the probability density function (PDF) of their orbital elements. It is natural to set up this kind of approach in the framework of statistical mechanics. In the present paper, I focus on the collisionless excitation of eccentricities and inclinations via gravitational interactions in a planetary system. The future planet trajectories in the solar system constitute the prototype of this kind of dynamics. I thus address the statistical mechanics of the solar system planet orbits and try to reproduce the PDFs numerically constructed by Laskar (2008, Icarus, 196, 1). I show that the microcanonical ensemble of the Laplace-Lagrange theory accurately reproduces the statistics of the giant planet orbits. To model the inner planets I then investigate the ansatz of equiprobability in the phase space constrained by the secular integrals of motion. The eccentricity and inclination PDFs of Earth and Venus are reproduced with no free parameters. Within the limitations of a stationary model, the predictions also show a reasonable agreement with Mars PDFs and that of Mercury inclination. The eccentricity of Mercury demands in contrast a deeper analysis. I finally revisit the random walk approach of Laskar to the time dependence of the inner planet PDFs. Such a statistical theory could be combined with direct numerical simulations of planet trajectories in the context of planet formation, which is likely to be a chaotic process.

Étude statistique et dynamique de la propagation d'épidémies dans un réseau de petit mondeStatistical and dynamical study of the epidemics propagation in a small world network

NASA Astrophysics Data System (ADS)

Zekri, Nouredine; Clerc, Jean Pierre

We study numerically in this work the statistical and dynamical properties of the clusters in a one dimensional small world model. The parameters chosen correspond to a realistic network of children of school age where a disease like measles can propagate. Extensive results on the statistical behavior of the clusters around the percolation threshold, as well as the evoltion with time, are discussed. To cite this article: N. Zekri, J.P. Clerc, C. R. Physique 3 (2002) 741-747.

Development and initial validation of the Localized Scleroderma Skin Damage Index and Physician Global Assessment of disease Damage: a proof-of-concept study

PubMed Central

Vilaiyuk, Soamarat; Torok, Kathryn S.; Medsger, Thomas A.

2010-01-01

Objective. To develop and assess the psychometric properties of the Localized Scleroderma (LS) Skin Damage Index (LoSDI) and Physician Global Assessment of disease Damage (PGA-D). Methods. Damage was defined as irreversible/persistent changes (>6 months) due to previous active disease/complications of therapy. Eight rheumatologists assessed the importance of 17 variables in formulating the PGA-D/LoSDI. LS patients were evaluated by two rheumatologists using both tools to assess their psychometric properties. LoSDI was calculated by summing three scores for cutaneous features of damage [dermal atrophy (DAT), subcutaneous atrophy (SAT) and dyspigmentation (DP)] measured at 18 anatomic sites. Patient GA of disease severity (PtGA-S), Children's Dermatology Life Quality Index (CDLQI) and PGA-D were recorded at the time of each examination. Results. Thirty LS patients (112 lesions) and nine patient-visit pairs (18 lesions) were included for inter- and intra-rater reliability study. LoSDI and its domains DAT, SAT, DP and PGA-D demonstrated excellent inter- and intra-rater reliability (reliability coefficients 0.86–0.99 and 0.74–0.96, respectively). LoSDI correlated moderately with PGA-D and poorly with PtGA-S and CDLQI. PGA-D correlated moderately with PtGA-S, but poorly with CDLQI. Conclusions. To complete the LS Cutaneous Assessment Tool (LoSCAT), we developed and evaluated the psychometric properties of the LoSDI and PGA-D in addition to the LS Skin Severity Index (LoSSI). These instruments will facilitate evaluation of LS patients for individual patient management and clinical trials. LoSDI and PGA-D demonstrated excellent reliability and high validity. LoSCAT provides an improved understanding of LS natural history. Further study in a larger group of patients is needed to confirm these preliminary findings. PMID:20008472

Top-Down Network Effective Connectivity in Abstinent Substance Dependent Individuals

PubMed Central

Regner, Michael F.; Saenz, Naomi; Maharajh, Keeran; Yamamoto, Dorothy J.; Mohl, Brianne; Wylie, Korey; Tregellas, Jason; Tanabe, Jody

2016-01-01

Objective We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls. Methods 50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI. fMRI results were analyzed using group independent component analysis; 14 networks-of-interest (NOI) were selected using template matching to a canonical set of resting state networks. The number, direction, and strength of connections between NOI were analyzed with Granger Causality. Within-group thresholds were p<0.005 using a bootstrap permutation. Between group thresholds were p<0.05, FDR-corrected for multiple comparisons. NOI were correlated with behavioral measures, and group-level graph theory measures were compared. Results Compared to controls, SDI showed significantly greater Granger causal connectivity from right executive control network (RECN) to dorsal default mode network (dDMN) and from dDMN to basal ganglia network (BGN). RECN was negatively correlated with impulsivity, behavioral approach, and negative affect; dDMN was positively correlated with impulsivity. Among the 14 NOI, SDI showed greater bidirectional connectivity; controls showed more unidirectional connectivity. SDI demonstrated greater global efficiency and lower local efficiency. Conclusions Increased effective connectivity in long-term abstinent drug users may reflect improved cognitive control over habit and reward processes. Higher global and lower local efficiency across all networks in SDI compared to controls may reflect connectivity changes associated with drug dependence or remission and requires future, longitudinal

Advanced power sources for space missions

NASA Technical Reports Server (NTRS)

Gavin, Joseph G., Jr.; Burkes, Tommy R.; English, Robert E.; Grant, Nicholas J.; Kulcinski, Gerald L.; Mullin, Jerome P.; Peddicord, K. Lee; Purvis, Carolyn K.; Sarjeant, W. James; Vandevender, J. Pace

1989-01-01

Approaches to satisfying the power requirements of space-based Strategic Defense Initiative (SDI) missions are studied. The power requirements for non-SDI military space missions and for civil space missions of the National Aeronautics and Space Administration (NASA) are also considered. The more demanding SDI power requirements appear to encompass many, if not all, of the power requirements for those missions. Study results indicate that practical fulfillment of SDI requirements will necessitate substantial advances in the state of the art of power technology. SDI goals include the capability to operate space-based beam weapons, sometimes referred to as directed-energy weapons. Such weapons pose unprecedented power requirements, both during preparation for battle and during battle conditions. The power regimes for these two sets of applications are referred to as alert mode and burst mode, respectively. Alert-mode power requirements are presently stated to range from about 100 kW to a few megawatts for cumulative durations of about a year or more. Burst-mode power requirements are roughly estimated to range from tens to hundreds of megawatts for durations of a few hundred to a few thousand seconds. There are two likely energy sources, chemical and nuclear, for powering SDI directed-energy weapons during the alert and burst modes. The choice between chemical and nuclear space power systems depends in large part on the total duration during which power must be provided. Complete study findings, conclusions, and eight recommendations are reported.

HRV-derived data similarity and distribution index based on ensemble neural network for measuring depth of anaesthesia.

PubMed

Liu, Quan; Ma, Li; Chiu, Ren-Chun; Fan, Shou-Zen; Abbod, Maysam F; Shieh, Jiann-Shing

2017-01-01

Evaluation of depth of anaesthesia (DoA) is critical in clinical surgery. Indices derived from electroencephalogram (EEG) are currently widely used to quantify DoA. However, there are known to be inaccurate under certain conditions; therefore, experienced anaesthesiologists rely on the monitoring of vital signs such as body temperature, pulse rate, respiration rate, and blood pressure to control the procedure. Because of the lack of an ideal approach for quantifying level of consciousness, studies have been conducted to develop improved methods of measuring DoA. In this study, a short-term index known as the similarity and distribution index (SDI) is proposed. The SDI is generated using heart rate variability (HRV) in the time domain and is based on observations of data distribution differences between two consecutive 32 s HRV data segments. A comparison between SDI results and expert assessments of consciousness level revealed that the SDI has strong correlation with anaesthetic depth. To optimise the effect, artificial neural network (ANN) models were constructed to fit the SDI, and ANN blind cross-validation was conducted to overcome random errors and overfitting problems. An ensemble ANN was then employed and was discovered to provide favourable DoA assessment in comparison with commonly used Bispectral Index. This study demonstrated the effectiveness of this method of DoA assessment, and the results imply that it is feasible and meaningful to use the SDI to measure DoA with the additional use of other measurement methods, if appropriate.

Southern Indian Ocean SST as a modulator for the progression of Indian summer monsoon

NASA Astrophysics Data System (ADS)

Shahi, Namendra Kumar; Rai, Shailendra; Mishra, Nishant

2018-01-01

This study explores the possibility of southern Indian Ocean (SIO) sea surface temperature (SST) as a modulator for the early phase of Indian summer monsoon and its possible physical mechanism. A dipole-like structure is obtained from the empirical orthogonal function (EOF) analysis which is similar to an Indian Ocean subtropical dipole (IOSD) found earlier. A subtropical dipole index (SDI) is defined based on the SST anomaly over the positive and negative poles. The regression map of rainfall over India in the month of June corresponding to the SDI during 1983-2013 shows negative patterns along the Western Ghats and Central India. However, the regression pattern is insignificant during 1952-1982. The multiple linear regression models and partial correlation analysis also indicate that the SDI acts as a dominant factor to influence the rainfall over India in the month of June during 1983-2013. The similar result is also obtained with the help of composite rainfall over the land points of India in the month of June for positive (negative) SDI events. It is also observed that the positive (negative) SDI delays (early) the onset dates of Indian monsoon over Kerala during the time domain of our study. The study is further extended to identify the physical mechanism of this impact, and it is found that the heating (cooling) in the region covering SDI changes the circulation pattern in the SIO and hence impacts the progression of monsoon in India.

An optimization model to design and manage subsurface drip irrigation system for alfalfa

NASA Astrophysics Data System (ADS)

Kandelous, M.; Kamai, T.; Vrugt, J. A.; Simunek, J.; Hanson, B.; Hopmans, J. W.

2010-12-01

Subsurface drip irrigation (SDI) is one of the most efficient and cost-effective methods for watering alfalfa plants. Lateral installation depth and distance, emitter discharge, and irrigation time and frequency of SDI, in addition to soil and climatic conditions affect alfalfa’s root water uptake and yield. Here we use a multi-objective optimization approach to find optimal SDI strategies. Our approach uses the AMALGAM evolutionary search method, in combination with the HYDRUS-2D unsaturated flow model to maximize water uptake by alfalfa’s plant roots, and minimize loss of irrigation and drainage water to the atmosphere or groundwater. We use a variety of different objective functions to analyze SDI. These criteria include the lateral installation depth and distance, the lateral discharge, irrigation duration, and irrigation frequency. Our framework includes explicit recognition of the soil moisture status during the simulation period to make sure that the top soil is dry for harvesting during the growing season. Initial results show a wide spectrum of optimized SDI strategies for different root distributions, soil textures and climate conditions. The developed tool should be useful in helping farmers optimize their irrigation strategy and design.

Statistical Decoupling of a Lagrangian Fluid Parcel in Newtonian Cosmology

NASA Astrophysics Data System (ADS)

Wang, Xin; Szalay, Alex

2016-03-01

The Lagrangian dynamics of a single fluid element within a self-gravitational matter field is intrinsically non-local due to the presence of the tidal force. This complicates the theoretical investigation of the nonlinear evolution of various cosmic objects, e.g., dark matter halos, in the context of Lagrangian fluid dynamics, since fluid parcels with given initial density and shape may evolve differently depending on their environments. In this paper, we provide a statistical solution that could decouple this environmental dependence. After deriving the evolution equation for the probability distribution of the matter field, our method produces a set of closed ordinary differential equations whose solution is uniquely determined by the initial condition of the fluid element. Mathematically, it corresponds to the projected characteristic curve of the transport equation of the density-weighted probability density function (ρPDF). Consequently it is guaranteed that the one-point ρPDF would be preserved by evolving these local, yet nonlinear, curves with the same set of initial data as the real system. Physically, these trajectories describe the mean evolution averaged over all environments by substituting the tidal tensor with its conditional average. For Gaussian distributed dynamical variables, this mean tidal tensor is simply proportional to the velocity shear tensor, and the dynamical system would recover the prediction of the Zel’dovich approximation (ZA) with the further assumption of the linearized continuity equation. For a weakly non-Gaussian field, the averaged tidal tensor could be expanded perturbatively as a function of all relevant dynamical variables whose coefficients are determined by the statistics of the field.

The Effect on Prospective Teachers of the Learning Environment Supported by Dynamic Statistics Software

ERIC Educational Resources Information Center

Koparan, Timur

2016-01-01

In this study, the effect on the achievement and attitudes of prospective teachers is examined. With this aim ahead, achievement test, attitude scale for statistics and interviews were used as data collection tools. The achievement test comprises 8 problems based on statistical data, and the attitude scale comprises 13 Likert-type items. The study…

Radiation belt seed population and its association with the relativistic electron dynamics: A statistical study: Radiation Belt Seed Population

DOE PAGES

Tang, C. L.; Wang, Y. X.; Ni, B.; ...

2017-05-19

Using the Van Allen Probes data, we study the radiation belt seed population and it associated with the relativistic electron dynamics during 74 geomagnetic storm events. Based on the flux changes of 1 MeV electrons before and after the storm peak, these storm events are divided into two groups of “non-preconditioned” and “preconditioned”. The statistical study shows that the storm intensity is of significant importance for the distribution of the seed population (336 keV electrons) in the outer radiation belt. However, substorm intensity can also be important to the evolution of the seed population for some geomagnetic storm events. Formore » non-preconditioned storm events, the correlation between the peak fluxes and their L-shell locations of the seed population and relativistic electrons (592 keV, 1.0 MeV, 1.8 MeV, and 2.1 MeV) is consistent with the energy-dependent dynamic processes in the outer radiation belt. For preconditioned storm events, the correlation between the features of the seed population and relativistic electrons is not fully consistent with the energy-dependent processes. It is suggested that the good correlation between the radiation belt seed population and ≤1.0 MeV electrons contributes to the prediction of the evolution of ≤1.0 MeV electrons in the Earth’s outer radiation belt during periods of geomagnetic storms.« less

Radiation belt seed population and its association with the relativistic electron dynamics: A statistical study: Radiation Belt Seed Population

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

Tang, C. L.; Wang, Y. X.; Ni, B.

Using the Van Allen Probes data, we study the radiation belt seed population and it associated with the relativistic electron dynamics during 74 geomagnetic storm events. Based on the flux changes of 1 MeV electrons before and after the storm peak, these storm events are divided into two groups of “non-preconditioned” and “preconditioned”. The statistical study shows that the storm intensity is of significant importance for the distribution of the seed population (336 keV electrons) in the outer radiation belt. However, substorm intensity can also be important to the evolution of the seed population for some geomagnetic storm events. Formore » non-preconditioned storm events, the correlation between the peak fluxes and their L-shell locations of the seed population and relativistic electrons (592 keV, 1.0 MeV, 1.8 MeV, and 2.1 MeV) is consistent with the energy-dependent dynamic processes in the outer radiation belt. For preconditioned storm events, the correlation between the features of the seed population and relativistic electrons is not fully consistent with the energy-dependent processes. It is suggested that the good correlation between the radiation belt seed population and ≤1.0 MeV electrons contributes to the prediction of the evolution of ≤1.0 MeV electrons in the Earth’s outer radiation belt during periods of geomagnetic storms.« less

How electronic dynamics with Pauli exclusion produces Fermi-Dirac statistics.

PubMed

Nguyen, Triet S; Nanguneri, Ravindra; Parkhill, John

2015-04-07

It is important that any dynamics method approaches the correct population distribution at long times. In this paper, we derive a one-body reduced density matrix dynamics for electrons in energetic contact with a bath. We obtain a remarkable equation of motion which shows that in order to reach equilibrium properly, rates of electron transitions depend on the density matrix. Even though the bath drives the electrons towards a Boltzmann distribution, hole blocking factors in our equation of motion cause the electronic populations to relax to a Fermi-Dirac distribution. These factors are an old concept, but we show how they can be derived with a combination of time-dependent perturbation theory and the extended normal ordering of Mukherjee and Kutzelnigg for a general electronic state. The resulting non-equilibrium kinetic equations generalize the usual Redfield theory to many-electron systems, while ensuring that the orbital occupations remain between zero and one. In numerical applications of our equations, we show that relaxation rates of molecules are not constant because of the blocking effect. Other applications to model atomic chains are also presented which highlight the importance of treating both dephasing and relaxation. Finally, we show how the bath localizes the electron density matrix.

Statistical dynamics of regional populations and economies

NASA Astrophysics Data System (ADS)

Huo, Jie; Wang, Xu-Ming; Hao, Rui; Wang, Peng

Quantitative analysis of human behavior and social development is becoming a hot spot of some interdisciplinary studies. A statistical analysis on the population and GDP of 150 cities in China from 1990 to 2013 is conducted. The result indicates the cumulative probability distribution of the populations and that of the GDPs obeying the shifted power law, respectively. In order to understand these characteristics, a generalized Langevin equation describing variation of population is proposed, which is based on the correlations between population and GDP as well as the random fluctuations of the related factors. The equation is transformed into the Fokker-Plank equation to express the evolution of population distribution. The general solution demonstrates a transition of the distribution from the normal Gaussian distribution to a shifted power law, which suggests a critical point of time at which the transition takes place. The shifted power law distribution in the supercritical situation is qualitatively in accordance with the practical result. The distribution of the GDPs is derived from the well-known Cobb-Douglas production function. The result presents a change, in supercritical situation, from a shifted power law to the Gaussian distribution. This is a surprising result-the regional GDP distribution of our world will be the Gaussian distribution one day in the future. The discussions based on the changing trend of economic growth suggest it will be true. Therefore, these theoretical attempts may draw a historical picture of our society in the aspects of population and economy.

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

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

Wood, Andrew W; Leung, Lai R; Sridhar, V

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able

Comparison of statistical models for analyzing wheat yield time series.

PubMed

Michel, Lucie; Makowski, David

2013-01-01

The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha⁻¹ year⁻¹ in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale.

Comparison of Statistical Models for Analyzing Wheat Yield Time Series

PubMed Central

Michel, Lucie; Makowski, David

2013-01-01

The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha−1 year−1 in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale. PMID:24205280

Understanding Statistics - Cancer Statistics

Cancer.gov

Annual reports of U.S. cancer statistics including new cases, deaths, trends, survival, prevalence, lifetime risk, and progress toward Healthy People targets, plus statistical summaries for a number of common cancer types.

Social and economic sustainability of urban systems: comparative analysis of metropolitan statistical areas in Ohio, USA

EPA Science Inventory

This article presents a general and versatile methodology for assessing sustainability with Fisher Information as a function of dynamic changes in urban systems. Using robust statistical methods, six Metropolitan Statistical Areas (MSAs) in Ohio were evaluated to comparatively as...

A statistical mechanics approach to autopoietic immune networks

NASA Astrophysics Data System (ADS)

Barra, Adriano; Agliari, Elena

2010-07-01

In this work we aim to bridge theoretical immunology and disordered statistical mechanics. We introduce a model for the behavior of B-cells which naturally merges the clonal selection theory and the autopoietic network theory as a whole. From the analysis of its features we recover several basic phenomena such as low-dose tolerance, dynamical memory of antigens and self/non-self discrimination.

Geostatistics as a tool to improve sampling and statistical analysis in wetlands: a case study on dynamics of organic matter distribution in the Pantanal of Mato Grosso, Brazil.

PubMed

Nogueira, F; Couto, E G; Bernardi, C J

2002-11-01

The Pantanal of Mato Grosso presents distinct landscape units: permanently, occasionally and periodically flooded areas. In the last ones, sampling is especially difficult due to the high heterogeneity occurring inter and intrastratas. This paper presents a comparison of different methodological approaches showing that they can influence decisively the knowledge of distribution organic matter dynamics. In such an area in order to understand the role of the flood pulse in the distribution dynamics of organic matter in a wetland at the Pantanal, we considered that there is spatial dependence between points. This consideration contradicts the classical statistic principle that focuses on the aleatority, and allowed the obtainment of a larger volume of information from a minor sampling effort, which means better performance, with time and money economy.

Statistical deprojection of galaxy pairs

NASA Astrophysics Data System (ADS)

Nottale, Laurent; Chamaraux, Pierre

2018-06-01

Aims: The purpose of the present paper is to provide methods of statistical analysis of the physical properties of galaxy pairs. We perform this study to apply it later to catalogs of isolated pairs of galaxies, especially two new catalogs we recently constructed that contain ≈1000 and ≈13 000 pairs, respectively. We are particularly interested by the dynamics of those pairs, including the determination of their masses. Methods: We could not compute the dynamical parameters directly since the necessary data are incomplete. Indeed, we only have at our disposal one component of the intervelocity between the members, namely along the line of sight, and two components of their interdistance, i.e., the projection on the sky-plane. Moreover, we know only one point of each galaxy orbit. Hence we need statistical methods to find the probability distribution of 3D interdistances and 3D intervelocities from their projections; we designed those methods under the term deprojection. Results: We proceed in two steps to determine and use the deprojection methods. First we derive the probability distributions expected for the various relevant projected quantities, namely intervelocity vz, interdistance rp, their ratio, and the product rp v_z^2, which is involved in mass determination. In a second step, we propose various methods of deprojection of those parameters based on the previous analysis. We start from a histogram of the projected data and we apply inversion formulae to obtain the deprojected distributions; lastly, we test the methods by numerical simulations, which also allow us to determine the uncertainties involved.

Delayed fission and multifragmentation in sub-keV C60 - Au(0 0 1) collisions via molecular dynamics simulations: Mass distributions and activated statistical decay

NASA Astrophysics Data System (ADS)

Bernstein, V.; Kolodney, E.

2017-10-01

We have recently observed, both experimentally and computationally, the phenomenon of postcollision multifragmentation in sub-keV surface collisions of a C60 projectile. Namely, delayed multiparticle breakup of a strongly impact deformed and vibrationally excited large cluster collider into several large fragments, after leaving the surface. Molecular dynamics simulations with extensive statistics revealed a nearly simultaneous event, within a sub-psec time window. Here we study, computationally, additional essential aspects of this new delayed collisional fragmentation which were not addressed before. Specifically, we study here the delayed (binary) fission channel for different impact energies both by calculating mass distributions over all fission events and by calculating and analyzing lifetime distributions of the scattered projectile. We observe an asymmetric fission resulting in a most probable fission channel and we find an activated exponential (statistical) decay. Finally, we also calculate and discuss the fragment mass distribution in (triple) multifragmentation over different time windows, in terms of most abundant fragments.

A Survey of Probabilistic Methods for Dynamical Systems with Uncertain Parameters.

DTIC Science & Technology

1986-05-01

J., "An Approach to the Theoretical Background of Statistical Energy Analysis Applied to Structural Vibration," Journ. Acoust. Soc. Amer., Vol. 69...1973, Sect. 8.3. 80. Lyon, R.H., " Statistical Energy Analysis of Dynamical Systems," M.I.T. Press, 1975. e) Late References added in Proofreading !! 81...Dowell, E.H., and Kubota, Y., "Asymptotic Modal Analysis and ’~ y C-" -165- Statistical Energy Analysis of Dynamical Systems," Journ. Appi. - Mech

Dynamic Uncertain Causality Graph for Knowledge Representation and Reasoning: Utilization of Statistical Data and Domain Knowledge in Complex Cases.

PubMed

Zhang, Qin; Yao, Quanying

2018-05-01

The dynamic uncertain causality graph (DUCG) is a newly presented framework for uncertain causality representation and probabilistic reasoning. It has been successfully applied to online fault diagnoses of large, complex industrial systems, and decease diagnoses. This paper extends the DUCG to model more complex cases than what could be previously modeled, e.g., the case in which statistical data are in different groups with or without overlap, and some domain knowledge and actions (new variables with uncertain causalities) are introduced. In other words, this paper proposes to use -mode, -mode, and -mode of the DUCG to model such complex cases and then transform them into either the standard -mode or the standard -mode. In the former situation, if no directed cyclic graph is involved, the transformed result is simply a Bayesian network (BN), and existing inference methods for BNs can be applied. In the latter situation, an inference method based on the DUCG is proposed. Examples are provided to illustrate the methodology.

Statistical against dynamical PLF fission as seen by the IMF-IMF correlation functions and comparisons with CoMD model

NASA Astrophysics Data System (ADS)

Pagano, E. V.; Acosta, L.; Auditore, L.; Cap, T.; Cardella, G.; Colonna, M.; De Filippo, E.; Geraci, E.; Gnoffo, B.; Lanzalone, G.; Maiolino, C.; Martorana, N.; Pagano, A.; Papa, M.; Piasecki, E.; Pirrone, S.; Politi, G.; Porto, F.; Quattrocchi, L.; Rizzo, F.; Russotto, P.; Trifiro’, A.; Trimarchi, M.; Siwek-Wilczynska, K.

2018-05-01

In nuclear reactions at Fermi energies two and multi particles intensity interferometry correlation methods are powerful tools in order to pin down the characteristic time scale of the emission processes. In this paper we summarize an improved application of the fragment-fragment correlation function in the specific physics case of heavy projectile-like (PLF) binary massive splitting in two fragments of intermediate mass(IMF). Results are shown for the reverse kinematics reaction 124 Sn+64 Ni at 35 AMeV that has been investigated by using the forward part of CHIMERA multi-detector. The analysis was performed as a function of the charge asymmetry of the observed couples of IMF. We show a coexistence of dynamical and statistical components as a function of the charge asymmetry. Transport CoMD simulations are compared with the data in order to pin down the timescale of the fragments production and the relevant ingredients of the in medium effective interaction used in the transport calculations.

Quantum Quench Dynamics

NASA Astrophysics Data System (ADS)

Mitra, Aditi

2018-03-01

Quench dynamics is an active area of study encompassing condensed matter physics and quantum information, with applications to cold-atomic gases and pump-probe spectroscopy of materials. Recent theoretical progress in studying quantum quenches is reviewed. Quenches in interacting one-dimensional systems as well as systems in higher spatial dimensions are covered. The appearance of nontrivial steady states following a quench in exactly solvable models is discussed, and the stability of these states to perturbations is described. Proper conserving approximations needed to capture the onset of thermalization at long times are outlined. The appearance of universal scaling for quenches near critical points and the role of the renormalization group in capturing the transient regime are reviewed. Finally, the effect of quenches near critical points on the dynamics of entanglement entropy and entanglement statistics is discussed. The extraction of critical exponents from the entanglement statistics is outlined.

Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain.

PubMed

Chládek, J; Brázdil, M; Halámek, J; Plešinger, F; Jurák, P

2013-01-01

We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency bands following different oddball stimuli is presented. The method is used for off-line functional classification of different brain areas.

MPGD for breast cancer prevention: a high resolution and low dose radiation medical imaging

NASA Astrophysics Data System (ADS)

Gutierrez, R. M.; Cerquera, E. A.; Mañana, G.

2012-07-01

Early detection of small calcifications in mammograms is considered the best preventive tool of breast cancer. However, existing digital mammography with relatively low radiation skin exposure has limited accessibility and insufficient spatial resolution for small calcification detection. Micro Pattern Gaseous Detectors (MPGD) and associated technologies, increasingly provide new information useful to generate images of microscopic structures and make more accessible cutting edge technology for medical imaging and many other applications. In this work we foresee and develop an application for the new information provided by a MPGD camera in the form of highly controlled images with high dynamical resolution. We present a new Super Detail Image (S-DI) that efficiently profits of this new information provided by the MPGD camera to obtain very high spatial resolution images. Therefore, the method presented in this work shows that the MPGD camera with SD-I, can produce mammograms with the necessary spatial resolution to detect microcalcifications. It would substantially increase efficiency and accessibility of screening mammography to highly improve breast cancer prevention.

Quench dynamics in superconducting nanojunctions: Metastability and dynamical Yang-Lee zeros

NASA Astrophysics Data System (ADS)

Souto, R. Seoane; Martín-Rodero, A.; Yeyati, A. Levy

2017-10-01

We study the charge transfer dynamics following the formation of a phase or voltage biased superconducting nanojunction using a full counting statistics analysis. We demonstrate that the evolution of the zeros of the generating function allows one to identify the population of different many body states much in the same way as the accumulation of Yang-Lee zeros of the partition function in equilibrium statistical mechanics is connected to phase transitions. We give an exact expression connecting the dynamical zeros to the charge transfer cumulants and discuss when an approximation based on "dominant" zeros is valid. We show that, for generic values of the parameters, the system gets trapped into a metastable state characterized by a nonequilibrium population of the many body states which is dependent on the initial conditions. We study in particular the effect of the switching rates in the dynamics showing that, in contrast to intuition, the deviation from thermal equilibrium increases for the slower rates. In the voltage biased case the steady state is reached independent of the initial conditions. Our method allows us to obtain accurate results for the steady state current and noise in quantitative agreement with steady state methods developed to describe the multiple Andreev reflections regime. Finally, we discuss the system dynamics after a sudden voltage drop showing the possibility of tuning the many body states population by an appropriate choice of the initial voltage, providing a feasible experimental way to access the quench dynamics and control the state of the system.

Statistical behavior of time dynamics evolution of HIV infection

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; Santos, Iury A. X.; Nunes, Marcos G. P.; de Oliveira, Viviane M.; Barbosa, Anderson L. R.

2017-09-01

We use the tools of the random matrix theory (RMT) to investigate the statistical behavior of the evolution of human immunodeficiency virus (HIV) infection. By means of the nearest-neighbor spacing distribution we have identified four distinct regimes of the evolution of HIV infection. We verified that at the beginning of the so-called clinical latency phase the concentration of infected cells grows slowly and evolves in a correlated way. This regime is followed by another one in which the correlation is lost and that in turn leads the system to a regime in which the increase of infected cells is faster and correlated. In the final phase, the one in which acquired immunodeficiency syndrome (AIDS) is stablished, the system presents maximum correlation as demonstrated by GOE distribution.

Novel Kalman filter algorithm for statistical monitoring of extensive landscapes with synoptic sensor data

Treesearch

Raymond L. Czaplewski

2015-01-01

Wall-to-wall remotely sensed data are increasingly available to monitor landscape dynamics over large geographic areas. However, statistical monitoring programs that use post-stratification cannot fully utilize those sensor data. The Kalman filter (KF) is an alternative statistical estimator. I develop a new KF algorithm that is numerically robust with large numbers of...

Statistical quasi-particle theory for open quantum systems

NASA Astrophysics Data System (ADS)

Zhang, Hou-Dao; Xu, Rui-Xue; Zheng, Xiao; Yan, YiJing

2018-04-01

This paper presents a comprehensive account on the recently developed dissipaton-equation-of-motion (DEOM) theory. This is a statistical quasi-particle theory for quantum dissipative dynamics. It accurately describes the influence of bulk environments, with a few number of quasi-particles, the dissipatons. The novel dissipaton algebra is then followed, which readily bridges the Schrödinger equation to the DEOM theory. As a fundamental theory of quantum mechanics in open systems, DEOM characterizes both the stationary and dynamic properties of system-and-bath interferences. It treats not only the quantum dissipative systems of primary interest, but also the hybrid environment dynamics that could be experimentally measurable. Examples are the linear or nonlinear Fano interferences and the Herzberg-Teller vibronic couplings in optical spectroscopies. This review covers the DEOM construction, the underlying dissipaton algebra and theorems, the physical meanings of dynamical variables, the possible identifications of dissipatons, and some recent advancements in efficient DEOM evaluations on various problems. The relations of the present theory to other nonperturbative methods are also critically presented.

Dynamics and Statistical Mechanics of Rotating and non-Rotating Vortical Flows

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

Lim, Chjan

Three projects were analyzed with the overall aim of developing a computational/analytical model for estimating values of the energy, angular momentum, enstrophy and total variation of fluid height at phase transitions between disordered and self-organized flow states in planetary atmospheres. It is believed that these transitions in equilibrium statistical mechanics models play a role in the construction of large-scale, stable structures including super-rotation in the Venusian atmosphere and the formation of the Great Red Spot on Jupiter. Exact solutions of the spherical energy-enstrophy models for rotating planetary atmospheres by Kac's method of steepest descent predicted phase transitions to super-rotating solid-bodymore » flows at high energy to enstrophy ratio for all planetary spins and to sub-rotating modes if the planetary spin is large enough. These canonical statistical ensembles are well-defined for the long-range energy interactions that arise from 2D fluid flows on compact oriented manifolds such as the surface of the sphere and torus. This is because in Fourier space available through Hodge theory, the energy terms are exactly diagonalizable and hence has zero range, leading to well-defined heat baths.« less

An analysis of I/O efficient order-statistic-based techniques for noise power estimation in the HRMS sky survey's operational system

NASA Technical Reports Server (NTRS)

Zimmerman, G. A.; Olsen, E. T.

1992-01-01

Noise power estimation in the High-Resolution Microwave Survey (HRMS) sky survey element is considered as an example of a constant false alarm rate (CFAR) signal detection problem. Order-statistic-based noise power estimators for CFAR detection are considered in terms of required estimator accuracy and estimator dynamic range. By limiting the dynamic range of the value to be estimated, the performance of an order-statistic estimator can be achieved by simpler techniques requiring only a single pass of the data. Simple threshold-and-count techniques are examined, and it is shown how several parallel threshold-and-count estimation devices can be used to expand the dynamic range to meet HRMS system requirements with minimal hardware complexity. An input/output (I/O) efficient limited-precision order-statistic estimator with wide but limited dynamic range is also examined.

Novel Kalman Filter Algorithm for Statistical Monitoring of Extensive Landscapes with Synoptic Sensor Data

PubMed Central

Czaplewski, Raymond L.

2015-01-01

Wall-to-wall remotely sensed data are increasingly available to monitor landscape dynamics over large geographic areas. However, statistical monitoring programs that use post-stratification cannot fully utilize those sensor data. The Kalman filter (KF) is an alternative statistical estimator. I develop a new KF algorithm that is numerically robust with large numbers of study variables and auxiliary sensor variables. A National Forest Inventory (NFI) illustrates application within an official statistics program. Practical recommendations regarding remote sensing and statistical issues are offered. This algorithm has the potential to increase the value of synoptic sensor data for statistical monitoring of large geographic areas. PMID:26393588

STATISTICAL DECOUPLING OF A LAGRANGIAN FLUID PARCEL IN NEWTONIAN COSMOLOGY

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

Wang, Xin; Szalay, Alex, E-mail: xwang@cita.utoronto.ca

The Lagrangian dynamics of a single fluid element within a self-gravitational matter field is intrinsically non-local due to the presence of the tidal force. This complicates the theoretical investigation of the nonlinear evolution of various cosmic objects, e.g., dark matter halos, in the context of Lagrangian fluid dynamics, since fluid parcels with given initial density and shape may evolve differently depending on their environments. In this paper, we provide a statistical solution that could decouple this environmental dependence. After deriving the evolution equation for the probability distribution of the matter field, our method produces a set of closed ordinary differentialmore » equations whose solution is uniquely determined by the initial condition of the fluid element. Mathematically, it corresponds to the projected characteristic curve of the transport equation of the density-weighted probability density function (ρPDF). Consequently it is guaranteed that the one-point ρPDF would be preserved by evolving these local, yet nonlinear, curves with the same set of initial data as the real system. Physically, these trajectories describe the mean evolution averaged over all environments by substituting the tidal tensor with its conditional average. For Gaussian distributed dynamical variables, this mean tidal tensor is simply proportional to the velocity shear tensor, and the dynamical system would recover the prediction of the Zel’dovich approximation (ZA) with the further assumption of the linearized continuity equation. For a weakly non-Gaussian field, the averaged tidal tensor could be expanded perturbatively as a function of all relevant dynamical variables whose coefficients are determined by the statistics of the field.« less

p21Waf1/Cip1/Sdi1 Prevents Apoptosis as Well as Stimulates Growth in Cells Transformed or Immortalized by Human T-Cell Leukemia Virus Type 1-Encoded Tax

PubMed Central

Kawata, Sanae; Ariumi, Yasuo; Shimotohno, Kunitada

2003-01-01

Human T-cell leukemia virus type 1 (HTLV-1) Tax regulates the expression of virally encoded genes, as well as various endogenous host genes in trans. Tax-mediated regulation of gene expression is important for the immortalization of normal human T lymphocytes and the transformation of fibroblast cells, such as Rat-1 cells. Tax has the ability to transactivate p21Waf1/Cip1/Sdi1, resulting in high expression levels in HTLV-1-immortalized cells. Since p21 expression is suppressed due to methylation of the promoter region in Rat-l cell line, p21 may not be critical for the transformation of this cell line by Tax. To further understand the role of p21 for the proliferation of Tax-transformed Rat-1 cells, we examined the effect of ectopic expression of p21 in these cells. Here, we observed that p21 expression enhanced the transformation of this cell line via at least two mechanisms: (i) the enhancement of NF-κB activation and/or CREB signaling and (ii) the excitation of antiapoptotic machinery. To analyze the role of p21 that is overexpressed in HTLV-1-immortalized lymphocytes, p21 expression was suppressed by using an antisense oligonucleotide specific for p21 mRNA; these cells then became sensitive to apoptotic induction. These results suggest that p21 plays an important role in the proliferation of Tax-expressing cells through the regulation of at least two independent mechanisms. PMID:12805427

Statistical Tests of System Linearity Based on the Method of Surrogate Data

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

Hunter, N.; Paez, T.; Red-Horse, J.

When dealing with measured data from dynamic systems we often make the tacit assumption that the data are generated by linear dynamics. While some systematic tests for linearity and determinism are available - for example the coherence fimction, the probability density fimction, and the bispectrum - fi,u-ther tests that quanti$ the existence and the degree of nonlinearity are clearly needed. In this paper we demonstrate a statistical test for the nonlinearity exhibited by a dynamic system excited by Gaussian random noise. We perform the usual division of the input and response time series data into blocks as required by themore » Welch method of spectrum estimation and search for significant relationships between a given input fkequency and response at harmonics of the selected input frequency. We argue that systematic tests based on the recently developed statistical method of surrogate data readily detect significant nonlinear relationships. The paper elucidates the method of surrogate data. Typical results are illustrated for a linear single degree-of-freedom system and for a system with polynomial stiffness nonlinearity.« less

Dynamic scaling in natural swarms

NASA Astrophysics Data System (ADS)

Cavagna, Andrea; Conti, Daniele; Creato, Chiara; Del Castello, Lorenzo; Giardina, Irene; Grigera, Tomas S.; Melillo, Stefania; Parisi, Leonardo; Viale, Massimiliano

2017-09-01

Collective behaviour in biological systems presents theoretical challenges beyond the borders of classical statistical physics. The lack of concepts such as scaling and renormalization is particularly problematic, as it forces us to negotiate details whose relevance is often hard to assess. In an attempt to improve this situation, we present here experimental evidence of the emergence of dynamic scaling laws in natural swarms of midges. We find that spatio-temporal correlation functions in different swarms can be rescaled by using a single characteristic time, which grows with the correlation length with a dynamical critical exponent z ~ 1, a value not found in any other standard statistical model. To check whether out-of-equilibrium effects may be responsible for this anomalous exponent, we run simulations of the simplest model of self-propelled particles and find z ~ 2, suggesting that natural swarms belong to a novel dynamic universality class. This conclusion is strengthened by experimental evidence of the presence of non-dissipative modes in the relaxation, indicating that previously overlooked inertial effects are needed to describe swarm dynamics. The absence of a purely dissipative regime suggests that natural swarms undergo a near-critical censorship of hydrodynamics.

Visualizing and Understanding Probability and Statistics: Graphical Simulations Using Excel

ERIC Educational Resources Information Center

Gordon, Sheldon P.; Gordon, Florence S.

2009-01-01

The authors describe a collection of dynamic interactive simulations for teaching and learning most of the important ideas and techniques of introductory statistics and probability. The modules cover such topics as randomness, simulations of probability experiments such as coin flipping, dice rolling and general binomial experiments, a simulation…

Maxwell's color statistics: from reduction of visible errors to reduction to invisible molecules.

PubMed

Cat, Jordi

2014-12-01

This paper presents a cross-disciplinary and multi-disciplinary account of Maxwell's introduction of statistical models of molecules for the composition of gases. The account focuses on Maxwell's deployment of statistical models of data in his contemporaneous color researches as established in Cambridge mathematical physics, especially by Maxwell's seniors and mentors. The paper also argues that the cross-disciplinary, or cross-domain, transfer of resources from the natural and social sciences took place in both directions and relied on the complex intra-disciplinary, or intra-domain, dynamics of Maxwell's researches in natural sciences, in color theory, physical astronomy, electromagnetism and dynamical theory of gases, as well as involving a variety of types of communicating and mediating media, from material objects to concepts, techniques and institutions.

Retinal network adaptation to bright light requires tyrosinase.

PubMed

Page-McCaw, Patrick S; Chung, S Clare; Muto, Akira; Roeser, Tobias; Staub, Wendy; Finger-Baier, Karin C; Korenbrot, Juan I; Baier, Herwig

2004-12-01

The visual system adjusts its sensitivity to a wide range of light intensities. We report here that mutation of the zebrafish sdy gene, which encodes tyrosinase, slows down the onset of adaptation to bright light. When fish larvae were challenged with periods of darkness during the day, the sdy mutants required nearly an hour to recover optokinetic behavior after return to bright light, whereas wild types recovered within minutes. This behavioral deficit was phenocopied in fully pigmented fish by inhibiting tyrosinase and thus does not depend on the absence of melanin pigment in sdy. Electroretinograms showed that the dark-adapted retinal network recovers sensitivity to a pulse of light more slowly in sdy mutants than in wild types. This failure is localized in the retinal neural network, postsynaptic to photoreceptors. We propose that retinal pigment epithelium (which normally expresses tyrosinase) secretes a modulatory factor, possibly L-DOPA, which regulates light adaptation in the retinal circuitry.

Statistical learning of movement.

PubMed

Ongchoco, Joan Danielle Khonghun; Uddenberg, Stefan; Chun, Marvin M

2016-12-01

The environment is dynamic, but objects move in predictable and characteristic ways, whether they are a dancer in motion, or a bee buzzing around in flight. Sequences of movement are comprised of simpler motion trajectory elements chained together. But how do we know where one trajectory element ends and another begins, much like we parse words from continuous streams of speech? As a novel test of statistical learning, we explored the ability to parse continuous movement sequences into simpler element trajectories. Across four experiments, we showed that people can robustly parse such sequences from a continuous stream of trajectories under increasingly stringent tests of segmentation ability and statistical learning. Observers viewed a single dot as it moved along simple sequences of paths, and were later able to discriminate these sequences from novel and partial ones shown at test. Observers demonstrated this ability when there were potentially helpful trajectory-segmentation cues such as a common origin for all movements (Experiment 1); when the dot's motions were entirely continuous and unconstrained (Experiment 2); when sequences were tested against partial sequences as a more stringent test of statistical learning (Experiment 3); and finally, even when the element trajectories were in fact pairs of trajectories, so that abrupt directional changes in the dot's motion could no longer signal inter-trajectory boundaries (Experiment 4). These results suggest that observers can automatically extract regularities in movement - an ability that may underpin our capacity to learn more complex biological motions, as in sport or dance.

Advanced dynamic statistical parametric mapping with MEG in localizing epileptogenicity of the bottom of sulcus dysplasia.

PubMed

Nakajima, Midori; Wong, Simeon; Widjaja, Elysa; Baba, Shiro; Okanishi, Tohru; Takada, Lynne; Sato, Yosuke; Iwata, Hiroki; Sogabe, Maya; Morooka, Hikaru; Whitney, Robyn; Ueda, Yuki; Ito, Tomoshiro; Yagyu, Kazuyori; Ochi, Ayako; Carter Snead, O; Rutka, James T; Drake, James M; Doesburg, Sam; Takeuchi, Fumiya; Shiraishi, Hideaki; Otsubo, Hiroshi

2018-06-01

To investigate whether advanced dynamic statistical parametric mapping (AdSPM) using magnetoencephalography (MEG) can better localize focal cortical dysplasia at bottom of sulcus (FCDB). We analyzed 15 children with diagnosis of FCDB in surgical specimen and 3 T MRI by using MEG. Using AdSPM, we analyzed a ±50 ms epoch relative to each single moving dipole (SMD) and applied summation technique to estimate the source activity. The most active area in AdSPM was defined as the location of AdSPM spike source. We compared spatial congruence between MRI-visible FCDB and (1) dipole cluster in SMD method; and (2) AdSPM spike source. AdSPM localized FCDB in 12 (80%) of 15 children whereas dipole cluster localized six (40%). AdSPM spike source was concordant within seizure onset zone in nine (82%) of 11 children with intracranial video EEG. Eleven children with resective surgery achieved seizure freedom with follow-up period of 1.9 ± 1.5 years. Ten (91%) of them had an AdSPM spike source in the resection area. AdSPM can noninvasively and neurophysiologically localize epileptogenic FCDB, whether it overlaps with the dipole cluster or not. This is the first study to localize epileptogenic FCDB using MEG. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Management of complex dynamical systems

NASA Astrophysics Data System (ADS)

MacKay, R. S.

2018-02-01

Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

Spatial Data Infrastructures (SDIs): Improving the Scientific Environmental Data Management and Visualization with ArcGIS Platform

NASA Astrophysics Data System (ADS)

Shrestha, S. R.; Hogeweg, M.; Rose, B.; Turner, A.

2017-12-01

The requirement for quality, authoritatively sourced data can often be challenging when working with scientific data. In addition, the lack of standard mechanism to discover, access, and use such data can be cumbersome. This results in slow research, poor dissemination and missed opportunities for research to positively impact policy and knowledge. There is widespread recognition that authoritative datasets are maintained by multiple organizations following various standards, and addressing these challenges will involve multiple stakeholders as well. The bottom line is that organizations need a mechanism to efficiently create, share, catalog, and discover data, and the ability to apply these to create an authoritative information products and applications is powerful and provides value. In real-world applications, individual organizations develop, modify, finalize, and support foundational data for distributed users across the system and thus require an efficient method of data management. For this, the SDI (Spatial Data Infrastructure) framework can be applied for GIS users to facilitate efficient and powerful decision making based on strong visualization and analytics. Working with research institutions, governments, and organizations across the world, we have developed a Hub framework for data and analysis sharing that is driven by outcome-centric goals which apply common methodologies and standards. SDI are an operational capability that should be equitably accessible to policy-makers, analysts, departments and public communities. These SDI need to align with operational workflows and support social communications and collaboration. The Hub framework integrates data across agencies, projects and organizations to support interoperability and drive coordination. We will present and share how Esri has been supporting the development of local, state, and national SDIs for many years and show some use cases for applications of planetary SDI. We will also share what

Statistical mechanics explanation for the structure of ocean eddies and currents

NASA Astrophysics Data System (ADS)

Venaille, A.; Bouchet, F.

2010-12-01

The equilibrium statistical mechanics of two dimensional and geostrophic flows predicts the outcome for the large scales of the flow, resulting from the turbulent mixing. This theory has been successfully applied to describe detailed properties of Jupiter's Great Red Spot. We discuss the range of applicability of this theory to ocean dynamics. It is able to reproduce mesoscale structures like ocean rings. It explains, from statistical mechanics, the westward drift of rings at the speed of non dispersive baroclinic waves, and the recently observed (Chelton and col.) slower northward drift of cyclonic eddies and southward drift of anticyclonic eddies. We also uncover relations between strong eastward mid-basin inertial jets, like the Kuroshio extension and the Gulf Stream, and statistical equilibria. We explain under which conditions such strong mid-basin jets can be understood as statistical equilibria. We claim that these results are complementary to the classical Sverdrup-Munk theory: they explain the inertial part basin dynamics, the jets structure and location, using very simple theoretical arguments. References: A. VENAILLE and F. BOUCHET, Ocean rings and jets as statistical equilibrium states, submitted to JPO F. BOUCHET and A. VENAILLE, Statistical mechanics of two-dimensional and geophysical flows, arxiv ...., submitted to Physics Reports P. BERLOFF, A. M. HOGG, W. DEWAR, The Turbulent Oscillator: A Mechanism of Low- Frequency Variability of the Wind-Driven Ocean Gyres, Journal of Physical Oceanography 37 (2007) 2363-+. D. B. CHELTON, M. G. SCHLAX, R. M. SAMELSON, R. A. de SZOEKE, Global observations of large oceanic eddies, Geo. Res. Lett.34 (2007) 15606-+ b) and c) are snapshots of streamfunction and potential vorticity (red: positive values; blue: negative values) in the upper layer of a three layer quasi-geostrophic model of a mid-latitude ocean basin (from Berloff and co.). a) Streamfunction predicted by statistical mechanics. Even in an out

Mutual interference between statistical summary perception and statistical learning.

PubMed

Zhao, Jiaying; Ngo, Nhi; McKendrick, Ryan; Turk-Browne, Nicholas B

2011-09-01

The visual system is an efficient statistician, extracting statistical summaries over sets of objects (statistical summary perception) and statistical regularities among individual objects (statistical learning). Although these two kinds of statistical processing have been studied extensively in isolation, their relationship is not yet understood. We first examined how statistical summary perception influences statistical learning by manipulating the task that participants performed over sets of objects containing statistical regularities (Experiment 1). Participants who performed a summary task showed no statistical learning of the regularities, whereas those who performed control tasks showed robust learning. We then examined how statistical learning influences statistical summary perception by manipulating whether the sets being summarized contained regularities (Experiment 2) and whether such regularities had already been learned (Experiment 3). The accuracy of summary judgments improved when regularities were removed and when learning had occurred in advance. In sum, calculating summary statistics impeded statistical learning, and extracting statistical regularities impeded statistical summary perception. This mutual interference suggests that statistical summary perception and statistical learning are fundamentally related.

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

Child and Adolescent Health From 1990 to 2015

PubMed Central

Kyu, Hmwe Hmwe; Zoeckler, Leo; Olsen, Helen Elizabeth; Thomas, Katie; Pinho, Christine; Bhutta, Zulfiqar A.; Dandona, Lalit; Ferrari, Alize; Ghiwot, Tsegaye Tewelde; Hay, Simon I.; Kinfu, Yohannes; Liang, Xiaofeng; Lopez, Alan; Malta, Deborah Carvalho; Mokdad, Ali H.; Naghavi, Mohsen; Patton, George C.; Salomon, Joshua; Sartorius, Benn; Topor-Madry, Roman; Vollset, Stein Emil; Werdecker, Andrea; Whiteford, Harvey A.; Abate, Kalkidan Hasen; Abbas, Kaja; Damtew, Solomon Abrha; Ahmed, Muktar Beshir; Akseer, Nadia; Al-Raddadi, Rajaa; Alemayohu, Mulubirhan Assefa; Altirkawi, Khalid; Abajobir, Amanuel Alemu; Amare, Azmeraw T.; Antonio, Carl A. T.; Arnlov, Johan; Artaman, Al; Asayesh, Hamid; Avokpaho, Euripide Frinel G. Arthur; Awasthi, Ashish; Ayala Quintanilla, Beatriz Paulina; Bacha, Umar; Betsu, Balem Demtsu; Barac, Aleksandra; Bärnighausen, Till Winfried; Baye, Estifanos; Bedi, Neeraj; Bensenor, Isabela M.; Berhane, Adugnaw; Bernabe, Eduardo; Bernal, Oscar Alberto; Beyene, Addisu Shunu; Biadgilign, Sibhatu; Bikbov, Boris; Boyce, Cheryl Anne; Brazinova, Alexandra; Hailu, Gessessew Bugssa; Carter, Austin; Castañeda-Orjuela, Carlos A.; Catalá-López, Ferrán; Charlson, Fiona J.; Chitheer, Abdulaal A.; Choi, Jee-Young Jasmine; Ciobanu, Liliana G.; Crump, John; Dandona, Rakhi; Dellavalle, Robert P.; Deribew, Amare; deVeber, Gabrielle; Dicker, Daniel; Ding, Eric L.; Dubey, Manisha; Endries, Amanuel Yesuf; Erskine, Holly E.; Faraon, Emerito Jose Aquino; Faro, Andre; Farzadfar, Farshad; Fernandes, Joao C.; Fijabi, Daniel Obadare; Fitzmaurice, Christina; Fleming, Thomas D.; Flor, Luisa Sorio; Foreman, Kyle J.; Franklin, Richard C.; Fraser, Maya S.; Frostad, Joseph J.; Fullman, Nancy; Gebregergs, Gebremedhin Berhe; Gebru, Alemseged Aregay; Geleijnse, Johanna M.; Gibney, Katherine B.; Gidey Yihdego, Mahari; Ginawi, Ibrahim Abdelmageem Mohamed; Gishu, Melkamu Dedefo; Gizachew, Tessema Assefa; Glaser, Elizabeth; Gold, Audra L.; Goldberg, Ellen; Gona, Philimon; Goto, Atsushi; Gugnani, Harish Chander; Jiang, Guohong; Gupta, Rajeev; Tesfay, Fisaha Haile; Hankey, Graeme J.; Havmoeller, Rasmus; Hijar, Martha; Horino, Masako; Hosgood, H. Dean; Hu, Guoqing; Jacobsen, Kathryn H.; Jakovljevic, Mihajlo B.; Jayaraman, Sudha P.; Jha, Vivekanand; Jibat, Tariku; Johnson, Catherine O.; Jonas, Jost; Kasaeian, Amir; Kawakami, Norito; Keiyoro, Peter N.; Khalil, Ibrahim; Khang, Young-Ho; Khubchandani, Jagdish; Ahmad Kiadaliri, Aliasghar A.; Kieling, Christian; Kim, Daniel; Kissoon, Niranjan; Knibbs, Luke D.; Koyanagi, Ai; Krohn, Kristopher J.; Kuate Defo, Barthelemy; Kucuk Bicer, Burcu; Kulikoff, Rachel; Kumar, G. Anil; Lal, Dharmesh Kumar; Lam, Hilton Y.; Larson, Heidi J.; Larsson, Anders; Laryea, Dennis Odai; Leung, Janni; Lim, Stephen S.; Lo, Loon-Tzian; Lo, Warren D.; Looker, Katharine J.; Lotufo, Paulo A.; Magdy Abd El Razek, Hassan; Malekzadeh, Reza; Markos Shifti, Desalegn; Mazidi, Mohsen; Meaney, Peter A.; Meles, Kidanu Gebremariam; Memiah, Peter; Mendoza, Walter; Abera Mengistie, Mubarek; Mengistu, Gebremichael Welday; Mensah, George A.; Miller, Ted R.; Mock, Charles; Mohammadi, Alireza; Mohammed, Shafiu; Monasta, Lorenzo; Mueller, Ulrich; Nagata, Chie; Naheed, Aliya; Nguyen, Grant; Nguyen, Quyen Le; Nsoesie, Elaine; Oh, In-Hwan; Okoro, Anselm; Olusanya, Jacob Olusegun; Olusanya, Bolajoko O.; Ortiz, Alberto; Paudel, Deepak; Pereira, David M.; Perico, Norberto; Petzold, Max; Phillips, Michael Robert; Polanczyk, Guilherme V.; Pourmalek, Farshad; Qorbani, Mostafa; Rafay, Anwar; Rahimi-Movaghar, Vafa; Rahman, Mahfuzar; Rai, Rajesh Kumar; Ram, Usha; Rankin, Zane; Remuzzi, Giuseppe; Renzaho, Andre M. N.; Roba, Hirbo Shore; Rojas-Rueda, David; Ronfani, Luca; Sagar, Rajesh; Sanabria, Juan Ramon; Kedir Mohammed, Muktar Sano; Santos, Itamar S.; Satpathy, Maheswar; Sawhney, Monika; Schöttker, Ben; Schwebel, David C.; Scott, James G.; Sepanlou, Sadaf G.; Shaheen, Amira; Shaikh, Masood Ali; She, June; Shiri, Rahman; Shiue, Ivy; Sigfusdottir, Inga Dora; Singh, Jasvinder; Silpakit, Naris; Smith, Alison; Sreeramareddy, Chandrashekhar; Stanaway, Jeffrey D.; Stein, Dan J.; Steiner, Caitlyn; Sufiyan, Muawiyyah Babale; Swaminathan, Soumya; Tabarés-Seisdedos, Rafael; Tabb, Karen M.; Tadese, Fentaw; Tavakkoli, Mohammad; Taye, Bineyam; Teeple, Stephanie; Tegegne, Teketo Kassaw; Temam Shifa, Girma; Terkawi, Abdullah Sulieman; Thomas, Bernadette; Thomson, Alan J.; Tobe-Gai, Ruoyan; Tonelli, Marcello; Tran, Bach Xuan; Troeger, Christopher; Ukwaja, Kingsley N.; Uthman, Olalekan; Vasankari, Tommi; Venketasubramanian, Narayanaswamy; Vlassov, Vasiliy Victorovich; Weiderpass, Elisabete; Weintraub, Robert; Gebrehiwot, Solomon Weldemariam; Westerman, Ronny; Williams, Hywel C.; Wolfe, Charles D. A.; Woodbrook, Rachel; Yano, Yuichiro; Yonemoto, Naohiro; Yoon, Seok-Jun; Younis, Mustafa Z.; Yu, Chuanhua; Zaki, Maysaa El Sayed; Zegeye, Elias Asfaw; Zuhlke, Liesl Joanna; Murray, Christopher J. L.; Vos, Theo

2017-01-01

Importance Comprehensive and timely monitoring of disease burden in all age groups, including children and adolescents, is essential for improving population health. Objective To quantify and describe levels and trends of mortality and nonfatal health outcomes among children and adolescents from 1990 to 2015 to provide a framework for policy discussion. Evidence Review Cause-specific mortality and nonfatal health outcomes were analyzed for 195 countries and territories by age group, sex, and year from 1990 to 2015 using standardized approaches for data processing and statistical modeling, with subsequent analysis of the findings to describe levels and trends across geography and time among children and adolescents 19 years or younger. A composite indicator of income, education, and fertility was developed (Socio-demographic Index [SDI]) for each geographic unit and year, which evaluates the historical association between SDI and health loss. Findings Global child and adolescent mortality decreased from 14.18 million (95% uncertainty interval [UI], 14.09 million to 14.28 million) deaths in 1990 to 7.26 million (95% UI, 7.14 million to 7.39 million) deaths in 2015, but progress has been unevenly distributed. Countries with a lower SDI had a larger proportion of mortality burden (75%) in 2015 than was the case in 1990 (61%). Most deaths in 2015 occurred in South Asia and sub-Saharan Africa. Global trends were driven by reductions in mortality owing to infectious, nutritional, and neonatal disorders, which in the aggregate led to a relative increase in the importance of noncommunicable diseases and injuries in explaining global disease burden. The absolute burden of disability in children and adolescents increased 4.3% (95% UI, 3.1%-5.6%) from 1990 to 2015, with much of the increase owing to population growth and improved survival for children and adolescents to older ages. Other than infectious conditions, many top causes of disability are associated with long

Child and Adolescent Health From 1990 to 2015: Findings From the Global Burden of Diseases, Injuries, and Risk Factors 2015 Study.

PubMed

Kassebaum, Nicholas; Kyu, Hmwe Hmwe; Zoeckler, Leo; Olsen, Helen Elizabeth; Thomas, Katie; Pinho, Christine; Bhutta, Zulfiqar A; Dandona, Lalit; Ferrari, Alize; Ghiwot, Tsegaye Tewelde; Hay, Simon I; Kinfu, Yohannes; Liang, Xiaofeng; Lopez, Alan; Malta, Deborah Carvalho; Mokdad, Ali H; Naghavi, Mohsen; Patton, George C; Salomon, Joshua; Sartorius, Benn; Topor-Madry, Roman; Vollset, Stein Emil; Werdecker, Andrea; Whiteford, Harvey A; Abate, Kalkidan Hasen; Abbas, Kaja; Damtew, Solomon Abrha; Ahmed, Muktar Beshir; Akseer, Nadia; Al-Raddadi, Rajaa; Alemayohu, Mulubirhan Assefa; Altirkawi, Khalid; Abajobir, Amanuel Alemu; Amare, Azmeraw T; Antonio, Carl A T; Arnlov, Johan; Artaman, Al; Asayesh, Hamid; Avokpaho, Euripide Frinel G Arthur; Awasthi, Ashish; Ayala Quintanilla, Beatriz Paulina; Bacha, Umar; Betsu, Balem Demtsu; Barac, Aleksandra; Bärnighausen, Till Winfried; Baye, Estifanos; Bedi, Neeraj; Bensenor, Isabela M; Berhane, Adugnaw; Bernabe, Eduardo; Bernal, Oscar Alberto; Beyene, Addisu Shunu; Biadgilign, Sibhatu; Bikbov, Boris; Boyce, Cheryl Anne; Brazinova, Alexandra; Hailu, Gessessew Bugssa; Carter, Austin; Castañeda-Orjuela, Carlos A; Catalá-López, Ferrán; Charlson, Fiona J; Chitheer, Abdulaal A; Choi, Jee-Young Jasmine; Ciobanu, Liliana G; Crump, John; Dandona, Rakhi; Dellavalle, Robert P; Deribew, Amare; deVeber, Gabrielle; Dicker, Daniel; Ding, Eric L; Dubey, Manisha; Endries, Amanuel Yesuf; Erskine, Holly E; Faraon, Emerito Jose Aquino; Faro, Andre; Farzadfar, Farshad; Fernandes, Joao C; Fijabi, Daniel Obadare; Fitzmaurice, Christina; Fleming, Thomas D; Flor, Luisa Sorio; Foreman, Kyle J; Franklin, Richard C; Fraser, Maya S; Frostad, Joseph J; Fullman, Nancy; Gebregergs, Gebremedhin Berhe; Gebru, Alemseged Aregay; Geleijnse, Johanna M; Gibney, Katherine B; Gidey Yihdego, Mahari; Ginawi, Ibrahim Abdelmageem Mohamed; Gishu, Melkamu Dedefo; Gizachew, Tessema Assefa; Glaser, Elizabeth; Gold, Audra L; Goldberg, Ellen; Gona, Philimon; Goto, Atsushi; Gugnani, Harish Chander; Jiang, Guohong; Gupta, Rajeev; Tesfay, Fisaha Haile; Hankey, Graeme J; Havmoeller, Rasmus; Hijar, Martha; Horino, Masako; Hosgood, H Dean; Hu, Guoqing; Jacobsen, Kathryn H; Jakovljevic, Mihajlo B; Jayaraman, Sudha P; Jha, Vivekanand; Jibat, Tariku; Johnson, Catherine O; Jonas, Jost; Kasaeian, Amir; Kawakami, Norito; Keiyoro, Peter N; Khalil, Ibrahim; Khang, Young-Ho; Khubchandani, Jagdish; Ahmad Kiadaliri, Aliasghar A; Kieling, Christian; Kim, Daniel; Kissoon, Niranjan; Knibbs, Luke D; Koyanagi, Ai; Krohn, Kristopher J; Kuate Defo, Barthelemy; Kucuk Bicer, Burcu; Kulikoff, Rachel; Kumar, G Anil; Lal, Dharmesh Kumar; Lam, Hilton Y; Larson, Heidi J; Larsson, Anders; Laryea, Dennis Odai; Leung, Janni; Lim, Stephen S; Lo, Loon-Tzian; Lo, Warren D; Looker, Katharine J; Lotufo, Paulo A; Magdy Abd El Razek, Hassan; Malekzadeh, Reza; Markos Shifti, Desalegn; Mazidi, Mohsen; Meaney, Peter A; Meles, Kidanu Gebremariam; Memiah, Peter; Mendoza, Walter; Abera Mengistie, Mubarek; Mengistu, Gebremichael Welday; Mensah, George A; Miller, Ted R; Mock, Charles; Mohammadi, Alireza; Mohammed, Shafiu; Monasta, Lorenzo; Mueller, Ulrich; Nagata, Chie; Naheed, Aliya; Nguyen, Grant; Nguyen, Quyen Le; Nsoesie, Elaine; Oh, In-Hwan; Okoro, Anselm; Olusanya, Jacob Olusegun; Olusanya, Bolajoko O; Ortiz, Alberto; Paudel, Deepak; Pereira, David M; Perico, Norberto; Petzold, Max; Phillips, Michael Robert; Polanczyk, Guilherme V; Pourmalek, Farshad; Qorbani, Mostafa; Rafay, Anwar; Rahimi-Movaghar, Vafa; Rahman, Mahfuzar; Rai, Rajesh Kumar; Ram, Usha; Rankin, Zane; Remuzzi, Giuseppe; Renzaho, Andre M N; Roba, Hirbo Shore; Rojas-Rueda, David; Ronfani, Luca; Sagar, Rajesh; Sanabria, Juan Ramon; Kedir Mohammed, Muktar Sano; Santos, Itamar S; Satpathy, Maheswar; Sawhney, Monika; Schöttker, Ben; Schwebel, David C; Scott, James G; Sepanlou, Sadaf G; Shaheen, Amira; Shaikh, Masood Ali; She, June; Shiri, Rahman; Shiue, Ivy; Sigfusdottir, Inga Dora; Singh, Jasvinder; Silpakit, Naris; Smith, Alison; Sreeramareddy, Chandrashekhar; Stanaway, Jeffrey D; Stein, Dan J; Steiner, Caitlyn; Sufiyan, Muawiyyah Babale; Swaminathan, Soumya; Tabarés-Seisdedos, Rafael; Tabb, Karen M; Tadese, Fentaw; Tavakkoli, Mohammad; Taye, Bineyam; Teeple, Stephanie; Tegegne, Teketo Kassaw; Temam Shifa, Girma; Terkawi, Abdullah Sulieman; Thomas, Bernadette; Thomson, Alan J; Tobe-Gai, Ruoyan; Tonelli, Marcello; Tran, Bach Xuan; Troeger, Christopher; Ukwaja, Kingsley N; Uthman, Olalekan; Vasankari, Tommi; Venketasubramanian, Narayanaswamy; Vlassov, Vasiliy Victorovich; Weiderpass, Elisabete; Weintraub, Robert; Gebrehiwot, Solomon Weldemariam; Westerman, Ronny; Williams, Hywel C; Wolfe, Charles D A; Woodbrook, Rachel; Yano, Yuichiro; Yonemoto, Naohiro; Yoon, Seok-Jun; Younis, Mustafa Z; Yu, Chuanhua; Zaki, Maysaa El Sayed; Zegeye, Elias Asfaw; Zuhlke, Liesl Joanna; Murray, Christopher J L; Vos, Theo

2017-06-01

Comprehensive and timely monitoring of disease burden in all age groups, including children and adolescents, is essential for improving population health. To quantify and describe levels and trends of mortality and nonfatal health outcomes among children and adolescents from 1990 to 2015 to provide a framework for policy discussion. Cause-specific mortality and nonfatal health outcomes were analyzed for 195 countries and territories by age group, sex, and year from 1990 to 2015 using standardized approaches for data processing and statistical modeling, with subsequent analysis of the findings to describe levels and trends across geography and time among children and adolescents 19 years or younger. A composite indicator of income, education, and fertility was developed (Socio-demographic Index [SDI]) for each geographic unit and year, which evaluates the historical association between SDI and health loss. Global child and adolescent mortality decreased from 14.18 million (95% uncertainty interval [UI], 14.09 million to 14.28 million) deaths in 1990 to 7.26 million (95% UI, 7.14 million to 7.39 million) deaths in 2015, but progress has been unevenly distributed. Countries with a lower SDI had a larger proportion of mortality burden (75%) in 2015 than was the case in 1990 (61%). Most deaths in 2015 occurred in South Asia and sub-Saharan Africa. Global trends were driven by reductions in mortality owing to infectious, nutritional, and neonatal disorders, which in the aggregate led to a relative increase in the importance of noncommunicable diseases and injuries in explaining global disease burden. The absolute burden of disability in children and adolescents increased 4.3% (95% UI, 3.1%-5.6%) from 1990 to 2015, with much of the increase owing to population growth and improved survival for children and adolescents to older ages. Other than infectious conditions, many top causes of disability are associated with long-term sequelae of conditions present at birth (eg

Statistical Properties of Online Auctions

NASA Astrophysics Data System (ADS)

Namazi, Alireza; Schadschneider, Andreas

We characterize the statistical properties of a large number of online auctions run on eBay. Both stationary and dynamic properties, like distributions of prices, number of bids etc., as well as relations between these quantities are studied. The analysis of the data reveals surprisingly simple distributions and relations, typically of power-law form. Based on these findings we introduce a simple method to identify suspicious auctions that could be influenced by a form of fraud known as shill bidding. Furthermore the influence of bidding strategies is discussed. The results indicate that the observed behavior is related to a mixture of agents using a variety of strategies.

Making Spatial Statistics Service Accessible On Cloud Platform

NASA Astrophysics Data System (ADS)

Mu, X.; Wu, J.; Li, T.; Zhong, Y.; Gao, X.

2014-04-01

Web service can bring together applications running on diverse platforms, users can access and share various data, information and models more effectively and conveniently from certain web service platform. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtualized resources are provided as services. With the rampant growth of massive data and restriction of net, traditional web services platforms have some prominent problems existing in development such as calculation efficiency, maintenance cost and data security. In this paper, we offer a spatial statistics service based on Microsoft cloud. An experiment was carried out to evaluate the availability and efficiency of this service. The results show that this spatial statistics service is accessible for the public conveniently with high processing efficiency.

BIG DATA AND STATISTICS

PubMed Central

Rossell, David

2016-01-01

Big Data brings unprecedented power to address scientific, economic and societal issues, but also amplifies the possibility of certain pitfalls. These include using purely data-driven approaches that disregard understanding the phenomenon under study, aiming at a dynamically moving target, ignoring critical data collection issues, summarizing or preprocessing the data inadequately and mistaking noise for signal. We review some success stories and illustrate how statistical principles can help obtain more reliable information from data. We also touch upon current challenges that require active methodological research, such as strategies for efficient computation, integration of heterogeneous data, extending the underlying theory to increasingly complex questions and, perhaps most importantly, training a new generation of scientists to develop and deploy these strategies. PMID:27722040

Emergent irreversibility and entanglement spectrum statistics

NASA Astrophysics Data System (ADS)

Mucciolo, Eduardo; Chamon, Claudio; Hamma, Alioscia

2014-03-01

We study the problem of irreversibility when the dynamical evolution of a many-body system is described by a stochastic quantum circuit. Such evolution is more general than Hamitonian, and since energy levels are not well defined, the well-established connection between the statistical fluctuations of the energy spectrum and irreversibility cannot be made. We show that the entanglement spectrum provides a more general connection. Irreversibility is marked by a failure of a disentangling algorithm and is preceded by the appearance of Wigner-Dyson statistical fluctuations in the entanglement spectrum. This analysis can be done at the wavefunction level and offers a new route to study quantum chaos and quantum integrability. We acknowledge financial support from the U.S. National Science Foundation through grants CCF 1116590 and CCF 1117241, from the National Basic Research Program of China through grants 2011CBA00300 and 2011CBA00301, and from the National Natural Science Fo.

Statistical properties of fluctuating enzymes with dynamic cooperativity using a first passage time distribution formalism.

PubMed

Singh, Divya; Chaudhury, Srabanti

2017-04-14

We study the temporal fluctuations in catalytic rates for single enzyme reactions undergoing slow transitions between two active states. We use a first passage time distribution formalism to obtain the closed-form analytical expressions of the mean reaction time and the randomness parameter for reaction schemes where conformational fluctuations are present between two free enzyme conformers. Our studies confirm that the sole presence of free enzyme fluctuations yields a non Michaelis-Menten equation and can lead to dynamic cooperativity. The randomness parameter, which is a measure of the dynamic disorder in the system, converges to unity at a high substrate concentration. If slow fluctuations are present between the enzyme-substrate conformers (off-pathway mechanism), dynamic disorder is present at a high substrate concentration. Our results confirm that the dynamic disorder at a high substrate concentration is determined only by the slow fluctuations between the enzyme-substrate conformers and the randomness parameter is greater than unity. Slow conformational fluctuations between free enzymes are responsible for the emergence of dynamic cooperativity in single enzymes. Our theoretical findings are well supported by comparison with experimental data on the single enzyme beta-galactosidase.

Arms Control and the Strategic Defense Initiative: Three Perspectives. Occasional Paper 36.

ERIC Educational Resources Information Center

Hough, Jerry F.; And Others

Three perspectives on President Ronald Reagan's Strategic Defense Initiative (SDI), which is intended to defend U.S. targets from a Soviet nuclear attack, are presented in separate sections. In the first section, "Soviet Interpretation and Response," Jerry F. Hough examines possible reasons for Soviet preoccupation with SDI. He discusses…

Reagan and the Nuclear Freeze: "Stars Wars" as a Rhetorical Strategy.

ERIC Educational Resources Information Center

Bjork, Rebecca S.

1988-01-01

Analyzes the interaction between nuclear freeze activists and proponents of a Strategic Defense Initiative (SDI). Argues that SDI strengthens Reagan's rhetorical position concerning nuclear weapons policy because it reduces the argumentative ground of the freeze movement by envisioning a defensive weapons system that would nullify nuclear weapons.…

Selecting summary statistics in approximate Bayesian computation for calibrating stochastic models.

PubMed

Burr, Tom; Skurikhin, Alexei

2013-01-01

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the "go-to" option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics rather than the full data and is therefore computationally feasible. One technical challenge with ABC is that the quality of the approximation to the posterior distribution of model parameters depends on the user-chosen summary statistics. In this paper, the user requirement to choose effective summary statistics in order to accurately estimate the posterior distribution of model parameters is investigated and illustrated by example, using a model and corresponding real data of mitochondrial DNA population dynamics. We show that for some choices of summary statistics, the posterior distribution of model parameters is closely approximated and for other choices of summary statistics, the posterior distribution is not closely approximated. A strategy to choose effective summary statistics is suggested in cases where the stochastic computer model can be run at many trial parameter settings, as in the example.

Studies in the use of cloud type statistics in mission simulation

NASA Technical Reports Server (NTRS)

Fowler, M. G.; Willand, J. H.; Chang, D. T.; Cogan, J. L.

1974-01-01

A study to further improve NASA's global cloud statistics for mission simulation is reported. Regional homogeneity in cloud types was examined; most of the original region boundaries defined for cloud cover amount in previous studies were supported by the statistics on cloud types and the number of cloud layers. Conditionality in cloud statistics was also examined with special emphasis on temporal and spatial dependencies, and cloud type interdependence. Temporal conditionality was found up to 12 hours, and spatial conditionality up to 200 miles; the diurnal cycle in convective cloudiness was clearly evident. As expected, the joint occurrence of different cloud types reflected the dynamic processes which form the clouds. Other phases of the study improved the cloud type statistics for several region and proposed a mission simulation scheme combining the 4-dimensional atmospheric model, sponsored by MSFC, with the global cloud model.

Dynamic principle for ensemble control tools.

PubMed

Samoletov, A; Vasiev, B

2017-11-28

Dynamical equations describing physical systems in contact with a thermal bath are commonly extended by mathematical tools called "thermostats." These tools are designed for sampling ensembles in statistical mechanics. Here we propose a dynamic principle underlying a range of thermostats which is derived using fundamental laws of statistical physics and ensures invariance of the canonical measure. The principle covers both stochastic and deterministic thermostat schemes. Our method has a clear advantage over a range of proposed and widely used thermostat schemes that are based on formal mathematical reasoning. Following the derivation of the proposed principle, we show its generality and illustrate its applications including design of temperature control tools that differ from the Nosé-Hoover-Langevin scheme.

From Weakly Chaotic Dynamics to Deterministic Subdiffusion via Copula Modeling

NASA Astrophysics Data System (ADS)

Nazé, Pierre

2018-03-01

Copula modeling consists in finding a probabilistic distribution, called copula, whereby its coupling with the marginal distributions of a set of random variables produces their joint distribution. The present work aims to use this technique to connect the statistical distributions of weakly chaotic dynamics and deterministic subdiffusion. More precisely, we decompose the jumps distribution of Geisel-Thomae map into a bivariate one and determine the marginal and copula distributions respectively by infinite ergodic theory and statistical inference techniques. We verify therefore that the characteristic tail distribution of subdiffusion is an extreme value copula coupling Mittag-Leffler distributions. We also present a method to calculate the exact copula and joint distributions in the case where weakly chaotic dynamics and deterministic subdiffusion statistical distributions are already known. Numerical simulations and consistency with the dynamical aspects of the map support our results.

The major origin of seedless grapes is associated with a missense mutation in the MADS-box gene VviAGL11.

PubMed

Royo, Carolina; Torres-Pérez, Rafael; Mauri, Nuria; Diestro, Nieves; Cabezas, José Antonio; Marchal, Cécile; Lacombe, Thierry; Ibáñez, Javier; Tornel, Manuel; Carreño, Juan; Martínez-Zapater, José M; Carbonell-Bejerano, Pablo

2018-05-31

Seedlessness is greatly prized by consumers of fresh grapes. While stenospermocarpic seed abortion determined by the SEED DEVELOPMENT INHIBITOR (SDI) locus is the usual source of seedlessness in commercial grapevine (Vitis vinifera) cultivars, the underlying sdi mutation remains unknown. Here, we undertook an integrative approach to identify the causal mutation. Quantitative genetics and fine mapping in two 'Crimson Seedless' (CS)-derived F1 mapping populations confirmed the major effect of the SDI locus and delimited the sdi mutation to a 323-kb region on chromosome 18. RNA-seq comparing seed traces of seedless and seeds of seeded F1 individuals identified processes triggered during sdi-determined seed abortion, including activation of salicylic acid-dependent defenses. The RNA-seq dataset was investigated for candidate genes and, while no evidence for causal cis-acting regulatory mutations was detected, deleterious nucleotide changes in coding sequences of the seedless haplotype were predicted in two genes within the sdi fine mapping interval. Targeted re-sequencing of the two genes in a collection of 124 grapevine cultivars showed that only the point variation causing the Arg197Leu substitution in the seed morphogenesis regulator gene AGAMOUS-LIKE 11 (VviAGL11) was fully linked with stenospermocarpy. The concurrent post-zygotic variation identified for this missense polymorphism and seedlessness phenotype in seeded somatic variants of the original stenospermocarpic cultivar supports a causal effect. We postulate that seed abortion caused by this amino acid substitution in VviAGL11 is the major cause of seedlessness in cultivated grapevine. This information can be exploited to boost seedless grape breeding. {copyright, serif} 2018 American Society of Plant Biologists. All rights reserved.

Finding Statistically Significant Communities in Networks

PubMed Central

Lancichinetti, Andrea; Radicchi, Filippo; Ramasco, José J.; Fortunato, Santo

2011-01-01

Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure. In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics. It is based on the local optimization of a fitness function expressing the statistical significance of clusters with respect to random fluctuations, which is estimated with tools of Extreme and Order Statistics. OSLOM can be used alone or as a refinement procedure of partitions/covers delivered by other techniques. We have also implemented sequential algorithms combining OSLOM with other fast techniques, so that the community structure of very large networks can be uncovered. Our method has a comparable performance as the best existing algorithms on artificial benchmark graphs. Several applications on real networks are shown as well. OSLOM is implemented in a freely available software (http://www.oslom.org), and we believe it will be a valuable tool in the analysis of networks. PMID:21559480

Radiation from quantum weakly dynamical horizons in loop quantum gravity.

PubMed

Pranzetti, Daniele

2012-07-06

We provide a statistical mechanical analysis of quantum horizons near equilibrium in the grand canonical ensemble. By matching the description of the nonequilibrium phase in terms of weakly dynamical horizons with a local statistical framework, we implement loop quantum gravity dynamics near the boundary. The resulting radiation process provides a quantum gravity description of the horizon evaporation. For large black holes, the spectrum we derive presents a discrete structure which could be potentially observable.

Assessment of Change in Dynamic Psychotherapy

PubMed Central

Høglend, Per; Bøgwald, Kjell-Petter; Amlo, Svein; Heyerdahl, Oscar; Sørbye, Øystein; Marble, Alice; Sjaastad, Mary Cosgrove; Bentsen, Håvard

2000-01-01

Five scales have been developed to assess changes that are consistent with the therapeutic rationales and procedures of dynamic psychotherapy. Seven raters evaluated 50 patients before and 36 patients again after brief dynamic psychotherapy. A factor analysis indicated that the scales represent a dimension that is discriminable from general symptoms. A summary measure, Dynamic Capacity, was rated with acceptable reliability by a single rater. However, average scores of three raters were needed for good reliability of change ratings. The scales seem to be sufficiently fine-grained to capture statistically and clinically significant changes during brief dynamic psychotherapy. PMID:11069131

Assessment of change in dynamic psychotherapy.

PubMed

Høglend, P; Bøgwald, K P; Amlo, S; Heyerdahl, O; Sørbye, O; Marble, A; Sjaastad, M C; Bentsen, H

2000-01-01

Five scales have been developed to assess changes that are consistent with the therapeutic rationales and procedures of dynamic psychotherapy. Seven raters evaluated 50 patients before and 36 patients again after brief dynamic psychotherapy. A factor analysis indicated that the scales represent a dimension that is discriminable from general symptoms. A summary measure, Dynamic Capacity, was rated with acceptable reliability by a single rater. However, average scores of three raters were needed for good reliability of change ratings. The scales seem to be sufficiently fine-grained to capture statistically and clinically significant changes during brief dynamic psychotherapy.

Tracking Climate Change through the Spatiotemporal Dynamics of the Teletherms, the Statistically Hottest and Coldest Days of the Year

DOE PAGES

Dodds, Peter Sheridan; Mitchell, Lewis; Reagan, Andrew J.; ...

2016-05-11

Instabilities and long term shifts in seasons, whether induced by natural drivers or human activities, pose great disruptive threats to ecological, agricultural, and social systems. Here, we propose, measure, and explore two fundamental markers of location-sensitive seasonal variations: the Summer and Winter Teletherms—the on-average annual dates of the hottest and coldest days of the year. We analyze daily temperature extremes recorded at 1218 stations across the contiguous United States from 1853–2012, and observe large regional variation with the Summer Teletherm falling up to 90 days after the Summer Solstice, and 50 days for the Winter Teletherm after the Winter Solstice.more » We show that Teletherm temporal dynamics are substantive with clear and in some cases dramatic shifts reflective of system bifurcations. We also compare recorded daily temperature extremes with output from two regional climate models finding considerable though relatively unbiased error. In conclusion, our work demonstrates that Teletherms are an intuitive, powerful, and statistically sound measure of local climate change, and that they pose detailed, stringent challenges for future theoretical and computational models.« less

Dynamic re-weighted total variation technique and statistic Iterative reconstruction method for x-ray CT metal artifact reduction

NASA Astrophysics Data System (ADS)

Peng, Chengtao; Qiu, Bensheng; Zhang, Cheng; Ma, Changyu; Yuan, Gang; Li, Ming

2017-07-01

Over the years, the X-ray computed tomography (CT) has been successfully used in clinical diagnosis. However, when the body of the patient to be examined contains metal objects, the image reconstructed would be polluted by severe metal artifacts, which affect the doctor's diagnosis of disease. In this work, we proposed a dynamic re-weighted total variation (DRWTV) technique combined with the statistic iterative reconstruction (SIR) method to reduce the artifacts. The DRWTV method is based on the total variation (TV) and re-weighted total variation (RWTV) techniques, but it provides a sparser representation than TV and protects the tissue details better than RWTV. Besides, the DRWTV can suppress the artifacts and noise, and the SIR convergence speed is also accelerated. The performance of the algorithm is tested on both simulated phantom dataset and clinical dataset, which are the teeth phantom with two metal implants and the skull with three metal implants, respectively. The proposed algorithm (SIR-DRWTV) is compared with two traditional iterative algorithms, which are SIR and SIR constrained by RWTV regulation (SIR-RWTV). The results show that the proposed algorithm has the best performance in reducing metal artifacts and protecting tissue details.

Avalanche Statistics Identify Intrinsic Stellar Processes near Criticality in KIC 8462852

NASA Astrophysics Data System (ADS)

Sheikh, Mohammed A.; Weaver, Richard L.; Dahmen, Karin A.

2016-12-01

The star KIC8462852 (Tabby's star) has shown anomalous drops in light flux. We perform a statistical analysis of the more numerous smaller dimming events by using methods found useful for avalanches in ferromagnetism and plastic flow. Scaling exponents for avalanche statistics and temporal profiles of the flux during the dimming events are close to mean field predictions. Scaling collapses suggest that this star may be near a nonequilibrium critical point. The large events are interpreted as avalanches marked by modified dynamics, limited by the system size, and not within the scaling regime.

A Spatial Data Infrastructure to Share Earth and Space Science Data

NASA Astrophysics Data System (ADS)

Nativi, S.; Mazzetti, P.; Bigagli, L.; Cuomo, V.

2006-05-01

Spatial Data Infrastructure:SDI (also known as Geospatial Data Infrastructure) is fundamentally a mechanism to facilitate the sharing and exchange of geospatial data. SDI is a scheme necessary for the effective collection, management, access, delivery and utilization of geospatial data; it is important for: objective decision making and sound land based policy, support economic development and encourage socially and environmentally sustainable development. As far as data model and semantics are concerned, a valuable and effective SDI should be able to cross the boundaries between the Geographic Information System/Science (GIS) and Earth and Space Science (ESS) communities. Hence, SDI should be able to discover, access and share information and data produced and managed by both GIS and ESS communities, in an integrated way. In other terms, SDI must be built on a conceptual and technological framework which abstracts the nature and structure of shared dataset: feature-based data or Imagery, Gridded and Coverage Data (IGCD). ISO TC211 and the Open Geospatial Consortium provided important artifacts to build up this framework. In particular, the OGC Web Services (OWS) initiatives and several Interoperability Experiment (e.g. the GALEON IE) are extremely useful for this purpose. We present a SDI solution which is able to manage both GIS and ESS datasets. It is based on OWS and other well-accepted or promising technologies, such as: UNIDATA netCDF and CDM, ncML and ncML-GML. Moreover, it uses a specific technology to implement a distributed and federated system of catalogues: the GI-Cat. This technology performs data model mediation and protocol adaptation tasks. It is used to work out a metadata clearinghouse service, implementing a common (federal) catalogue model which is based on the ISO 19115 core metadata for geo-dataset. Nevertheless, other well- accepted or standard catalogue data models can be easily implemented as common view (e.g. OGC CS-W, the next coming

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

NASA Technical Reports Server (NTRS)

Zhang, Taiping

1994-01-01

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations.

Statistical properties and pre-hit dynamics of price limit hits in the Chinese stock markets.

PubMed

Wan, Yu-Lei; Xie, Wen-Jie; Gu, Gao-Feng; Jiang, Zhi-Qiang; Chen, Wei; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

2015-01-01

Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners.

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach.

PubMed

Chertkov, Michael; Chernyak, Vladimir

2017-08-17

Thermostatically controlled loads, e.g., air conditioners and heaters, are by far the most widespread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control - changing from on to off, and vice versa, depending on temperature. We considered aggregation of a large group of similar devices into a statistical ensemble, where the devices operate following the same dynamics, subject to stochastic perturbations and randomized, Poisson on/off switching policy. Using theoretical and computational tools of statistical physics, we analyzed how the ensemble relaxes to a stationary distribution and established a relationship between the relaxation and the statistics of the probability flux associated with devices' cycling in the mixed (discrete, switch on/off, and continuous temperature) phase space. This allowed us to derive the spectrum of the non-equilibrium (detailed balance broken) statistical system and uncover how switching policy affects oscillatory trends and the speed of the relaxation. Relaxation of the ensemble is of practical interest because it describes how the ensemble recovers from significant perturbations, e.g., forced temporary switching off aimed at utilizing the flexibility of the ensemble to provide "demand response" services to change consumption temporarily to balance a larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach

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

Chertkov, Michael; Chernyak, Vladimir

Thermostatically Controlled Loads (TCL), e.g. air-conditioners and heaters, are by far the most wide-spread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control of temperature - changing from on to off , and vice versa, depending on temperature. Aggregation of a large group of similar devices into a statistical ensemble is considered, where the devices operate following the same dynamics subject to stochastic perturbations and randomized, Poisson on/off switching policy. We analyze, using theoretical and computational tools of statistical physics, how the ensemble relaxes to a stationary distribution and establish relation between the re- laxationmore » and statistics of the probability flux, associated with devices' cycling in the mixed (discrete, switch on/off , and continuous, temperature) phase space. This allowed us to derive and analyze spec- trum of the non-equilibrium (detailed balance broken) statistical system. and uncover how switching policy affects oscillatory trend and speed of the relaxation. Relaxation of the ensemble is of a practical interest because it describes how the ensemble recovers from significant perturbations, e.g. forceful temporary switching o aimed at utilizing flexibility of the ensemble in providing "demand response" services relieving consumption temporarily to balance larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.« less

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach

DOE PAGES

Chertkov, Michael; Chernyak, Vladimir

2017-01-17

Thermostatically Controlled Loads (TCL), e.g. air-conditioners and heaters, are by far the most wide-spread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control of temperature - changing from on to off , and vice versa, depending on temperature. Aggregation of a large group of similar devices into a statistical ensemble is considered, where the devices operate following the same dynamics subject to stochastic perturbations and randomized, Poisson on/off switching policy. We analyze, using theoretical and computational tools of statistical physics, how the ensemble relaxes to a stationary distribution and establish relation between the re- laxationmore » and statistics of the probability flux, associated with devices' cycling in the mixed (discrete, switch on/off , and continuous, temperature) phase space. This allowed us to derive and analyze spec- trum of the non-equilibrium (detailed balance broken) statistical system. and uncover how switching policy affects oscillatory trend and speed of the relaxation. Relaxation of the ensemble is of a practical interest because it describes how the ensemble recovers from significant perturbations, e.g. forceful temporary switching o aimed at utilizing flexibility of the ensemble in providing "demand response" services relieving consumption temporarily to balance larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.« less

Use of statistically and dynamically downscaled atmospheric model output for hydrologic simulations in three mountainous basins in the western United States

USGS Publications Warehouse

Hay, L.E.; Clark, M.P.

2003-01-01

This paper examines the hydrologic model performance in three snowmelt-dominated basins in the western United States to dynamically- and statistically downscaled output from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP). Runoff produced using a distributed hydrologic model is compared using daily precipitation and maximum and minimum temperature timeseries derived from the following sources: (1) NCEP output (horizontal grid spacing of approximately 210 km); (2) dynamically downscaled (DDS) NCEP output using a Regional Climate Model (RegCM2, horizontal grid spacing of approximately 52 km); (3) statistically downscaled (SDS) NCEP output; (4) spatially averaged measured data used to calibrate the hydrologic model (Best-Sta) and (5) spatially averaged measured data derived from stations located within the area of the RegCM2 model output used for each basin, but excluding Best-Sta set (All-Sta). In all three basins the SDS-based simulations of daily runoff were as good as runoff produced using the Best-Sta timeseries. The NCEP, DDS, and All-Sta timeseries were able to capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all three basins, the NCEP-, DDS-, and All-Sta-based simulations of runoff showed little skill on a daily basis. When the precipitation and temperature biases were corrected in the NCEP, DDS, and All-Sta timeseries, the accuracy of the daily runoff simulations improved dramatically, but, with the exception of the bias-corrected All-Sta data set, these simulations were never as accurate as the SDS-based simulations. This need for a bias correction may be somewhat troubling, but in the case of the large station-timeseries (All-Sta), the bias correction did indeed 'correct' for the change in scale. It is unknown if bias corrections to model output will be valid in a future climate. Future work is warranted to identify the causes for (and removal of

Proceedings, Annual Meeting, Western Canada Chapter, American Society for Information Science (Third, Banff School of Fine Arts, October 3,4,5, 1971).

ERIC Educational Resources Information Center

Calgary Univ. (Alberta).

The proceedings contain papers given by the members of the chapter who come from both the University and Business environments. Some operational indexing, bibliographic, SDI and Retrospective Search Systems which include CAN/SDI, Compendex, TEXT-PAC, SIS II & III, KWOC and FAMULUS are discussed. Also included are papers on two projects…

Worldwide Report, Arms Control

DTIC Science & Technology

1986-02-28

NACHRICHTEN , 18 Oct 85) 39 Presummit Polish Reporting on SDI Issues (Warsaw RZECZPOSPOLITA, 19-20 Oct 85; Warsaw ZYCIE WARSZAWY, 15 Oct 85) 42...28 February 1986 SDI AND SPACE ARMS MEETING REVEALS SOME SUPPORT FOR EUREKA LINK TO MILITARY Puesseldbrf VDI NACHRICHTEN in German 18 Oct 85 p 10

Irrigation strategies using subsurface drip irrigation

USDA-ARS?s Scientific Manuscript database

Subsurface drip irrigation (SDI) is practiced on approximately 60,000 ha in the Texas High Plains region of the USA. Adoption of SDI continues to increase in the region. This has been attributed to record drought in Texas and the US Southwest in recent years, declining irrigation well yields, and ev...

[Statistics for statistics?--Thoughts about psychological tools].

PubMed

Berger, Uwe; Stöbel-Richter, Yve

2007-12-01

Statistical methods take a prominent place among psychologists' educational programs. Being known as difficult to understand and heavy to learn, students fear of these contents. Those, who do not aspire after a research carrier at the university, will forget the drilled contents fast. Furthermore, because it does not apply for the work with patients and other target groups at a first glance, the methodological education as a whole was often questioned. For many psychological practitioners the statistical education makes only sense by enforcing respect against other professions, namely physicians. For the own business, statistics is rarely taken seriously as a professional tool. The reason seems to be clear: Statistics treats numbers, while psychotherapy treats subjects. So, does statistics ends in itself? With this article, we try to answer the question, if and how statistical methods were represented within the psychotherapeutical and psychological research. Therefore, we analyzed 46 Originals of a complete volume of the journal Psychotherapy, Psychosomatics, Psychological Medicine (PPmP). Within the volume, 28 different analyse methods were applied, from which 89 per cent were directly based upon statistics. To be able to write and critically read Originals as a backbone of research, presumes a high degree of statistical education. To ignore statistics means to ignore research and at least to reveal the own professional work to arbitrariness.

Development of hi-resolution regional climate scenarios in Japan by statistical downscaling

NASA Astrophysics Data System (ADS)

Dairaku, K.

2016-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. To meet with the needs of stakeholders such as local governments, a Japan national project, Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), launched in December 2015. It develops reliable technologies for near-term climate change predictions. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 GCMs and a statistical downscaling method to support various municipal adaptation measures appropriate for possible regional climate changes. A statistical downscaling method, Bias Correction Spatial Disaggregation (BCSD), is employed to develop regional climate scenarios based on CMIP5 RCP8.5 five GCMs (MIROC5, MRI-CGCM3, GFDL-CM3, CSIRO-Mk3-6-0, HadGEM2-ES) for the periods of historical climate (1970-2005) and near future climate (2020-2055). Downscaled variables are monthly/daily precipitation and temperature. File format is NetCDF4 (conforming to CF1.6, HDF5 compression). Developed regional climate scenarios will be expanded to meet with needs of stakeholders and interface applications to access and download the data are under developing. Statistical downscaling method is not necessary to well represent locally forced nonlinear phenomena, extreme events such as heavy rain, heavy snow, etc. To complement the statistical method, dynamical downscaling approach is also combined and applied to some specific regions which have needs of stakeholders. The added values of statistical/dynamical downscaling methods compared with parent GCMs are investigated.

Synthetic Earthquake Statistics From Physical Fault Models for the Lower Rhine Embayment

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zöller, G.

2012-04-01

As of today, seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates they fail to provide a link between the observed seismicity and the underlying physical processes. Solving a state-of-the-art fully dynamic description set of all relevant physical processes related to earthquake fault systems is likely not useful since it comes with a large number of degrees of freedom, poor constraints on its model parameters and a huge computational effort. Here, quasi-static and quasi-dynamic physical fault simulators provide a compromise between physical completeness and computational affordability and aim at providing a link between basic physical concepts and statistics of seismicity. Within the framework of quasi-static and quasi-dynamic earthquake simulators we investigate a model of the Lower Rhine Embayment (LRE) that is based upon seismological and geological data. We present and discuss statistics of the spatio-temporal behavior of generated synthetic earthquake catalogs with respect to simplification (e.g. simple two-fault cases) as well as to complication (e.g. hidden faults, geometric complexity, heterogeneities of constitutive parameters).

Irradiation defect dispersions and effective dislocation mobility in strained ferritic grains: A statistical analysis based on 3D dislocation dynamics simulations

NASA Astrophysics Data System (ADS)

Li, Y.; Robertson, C.

2018-06-01

The influence of irradiation defect dispersions on plastic strain spreading is investigated by means of three-dimensional dislocation dynamics (DD) simulations, accounting for thermally activated slip and cross-slip mechanisms in Fe-2.5%Cr grains. The defect-induced evolutions of the effective screw dislocation mobility are evaluated by means of statistical comparisons, for various defect number density and defect size cases. Each comparison is systematically associated with a quantitative Defect-Induced Apparent Straining Temperature shift (or «ΔDIAT»), calculated without any adjustable parameters. In the investigated cases, the ΔDIAT level associated with a given defect dispersion closely replicates the measured ductile to brittle transition temperature shift (ΔDBTT) due to the same, actual defect dispersion. The results are further analyzed in terms of dislocation-based plasticity mechanisms and their possible relations with the dose-dependent changes of the ductile to brittle transition temperature.

An EAL domain protein and cyclic AMP contribute to the interaction between the two quorum sensing systems in Escherichia coli.

PubMed

Zhou, Xianxuan; Meng, Xiaoming; Sun, Baolin

2008-09-01

Quorum sensing (QS) is a bacterial cell-cell communication process by which bacteria communicate using extracellular signals called autoinducers. Two QS systems have been identified in Escherichia coli K-12, including an intact QS system 2 that is stimulated by the cyclic AMP (cAMP)-cAMP receptor protein (CRP) complex and a partial QS system 1 that consists of SdiA (suppressor of cell division inhibitor) responding to signals generated by other microbial species. The relationship between QS system 1 and system 2 in E. coli, however, remains obscure. Here, we show that an EAL domain protein, encoded by ydiV, and cAMP are involved in the interaction between the two QS systems in E. coli. Expression of sdiA and ydiV is inhibited by glucose. SdiA binds to the ydiV promoter region in a dose-dependent, but nonspecific, manner; extracellular autoinducer 1 from other species stimulates ydiV expression in an sdiA-dependent manner. Furthermore, we discovered that the double sdiA-ydiV mutation, but not the single mutation, causes a 2-fold decrease in intracellular cAMP concentration that leads to the inhibition of QS system 2. These results indicate that signaling pathways that respond to important environmental cues, such as autoinducers and glucose, are linked together for their control in E. coli.

Rigorous Statistical Bounds in Uncertainty Quantification for One-Layer Turbulent Geophysical Flows

NASA Astrophysics Data System (ADS)

Qi, Di; Majda, Andrew J.

2018-04-01

Statistical bounds controlling the total fluctuations in mean and variance about a basic steady-state solution are developed for the truncated barotropic flow over topography. Statistical ensemble prediction is an important topic in weather and climate research. Here, the evolution of an ensemble of trajectories is considered using statistical instability analysis and is compared and contrasted with the classical deterministic instability for the growth of perturbations in one pointwise trajectory. The maximum growth of the total statistics in fluctuations is derived relying on the statistical conservation principle of the pseudo-energy. The saturation bound of the statistical mean fluctuation and variance in the unstable regimes with non-positive-definite pseudo-energy is achieved by linking with a class of stable reference states and minimizing the stable statistical energy. Two cases with dependence on initial statistical uncertainty and on external forcing and dissipation are compared and unified under a consistent statistical stability framework. The flow structures and statistical stability bounds are illustrated and verified by numerical simulations among a wide range of dynamical regimes, where subtle transient statistical instability exists in general with positive short-time exponential growth in the covariance even when the pseudo-energy is positive-definite. Among the various scenarios in this paper, there exist strong forward and backward energy exchanges between different scales which are estimated by the rigorous statistical bounds.

The Use of ERIC Tapes in Scandinavia, Searching With Thesaurus Terms in Natural Language.

ERIC Educational Resources Information Center

Tell, Bjorn V.; And Others

Since February 1971 the Royal Institute of Technology, Stockholm, has been running the ERIC data base mainly for SDI purposes. The implementation of the data base into the generalized search system, ABACUS, is described. One hundred and fifty-eight users received SDI service at present, 99 from governmental and educational institutions, 23 from…

Non-Markovian full counting statistics in quantum dot molecules

PubMed Central

Xue, Hai-Bin; Jiao, Hu-Jun; Liang, Jiu-Qing; Liu, Wu-Ming

2015-01-01

Full counting statistics of electron transport is a powerful diagnostic tool for probing the nature of quantum transport beyond what is obtainable from the average current or conductance measurement alone. In particular, the non-Markovian dynamics of quantum dot molecule plays an important role in the nonequilibrium electron tunneling processes. It is thus necessary to understand the non-Markovian full counting statistics in a quantum dot molecule. Here we study the non-Markovian full counting statistics in two typical quantum dot molecules, namely, serially coupled and side-coupled double quantum dots with high quantum coherence in a certain parameter regime. We demonstrate that the non-Markovian effect manifests itself through the quantum coherence of the quantum dot molecule system, and has a significant impact on the full counting statistics in the high quantum-coherent quantum dot molecule system, which depends on the coupling of the quantum dot molecule system with the source and drain electrodes. The results indicated that the influence of the non-Markovian effect on the full counting statistics of electron transport, which should be considered in a high quantum-coherent quantum dot molecule system, can provide a better understanding of electron transport through quantum dot molecules. PMID:25752245

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

Statistical physics, seismogenesis, and seismic hazard

NASA Astrophysics Data System (ADS)

Main, Ian

1996-11-01

The scaling properties of earthquake populations show remarkable similarities to those observed at or near the critical point of other composite systems in statistical physics. This has led to the development of a variety of different physical models of seismogenesis as a critical phenomenon, involving locally nonlinear dynamics, with simplified rheologies exhibiting instability or avalanche-type behavior, in a material composed of a large number of discrete elements. In particular, it has been suggested that earthquakes are an example of a "self-organized critical phenomenon" analogous to a sandpile that spontaneously evolves to a critical angle of repose in response to the steady supply of new grains at the summit. In this stationary state of marginal stability the distribution of avalanche energies is a power law, equivalent to the Gutenberg-Richter frequency-magnitude law, and the behavior is relatively insensitive to the details of the dynamics. Here we review the results of some of the composite physical models that have been developed to simulate seismogenesis on different scales during (1) dynamic slip on a preexisting fault, (2) fault growth, and (3) fault nucleation. The individual physical models share some generic features, such as a dynamic energy flux applied by tectonic loading at a constant strain rate, strong local interactions, and fluctuations generated either dynamically or by fixed material heterogeneity, but they differ significantly in the details of the assumed dynamics and in the methods of numerical solution. However, all exhibit critical or near-critical behavior, with behavior quantitatively consistent with many of the observed fractal or multifractal scaling laws of brittle faulting and earthquakes, including the Gutenberg-Richter law. Some of the results are sensitive to the details of the dynamics and hence are not strict examples of self-organized criticality. Nevertheless, the results of these different physical models share some

Lagrangian acceleration statistics in a turbulent channel flow

NASA Astrophysics Data System (ADS)

Stelzenmuller, Nickolas; Polanco, Juan Ignacio; Vignal, Laure; Vinkovic, Ivana; Mordant, Nicolas

2017-05-01

Lagrangian acceleration statistics in a fully developed turbulent channel flow at Reτ=1440 are investigated, based on tracer particle tracking in experiments and direct numerical simulations. The evolution with wall distance of the Lagrangian velocity and acceleration time scales is analyzed. Dependency between acceleration components in the near-wall region is described using cross-correlations and joint probability density functions. The strong streamwise coherent vortices typical of wall-bounded turbulent flows are shown to have a significant impact on the dynamics. This results in a strong anisotropy at small scales in the near-wall region that remains present in most of the channel. Such statistical properties may be used as constraints in building advanced Lagrangian stochastic models to predict the dispersion and mixing of chemical components for combustion or environmental studies.

An application of statistics to comparative metagenomics

PubMed Central

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-01-01

Background Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Results Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. Conclusion The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems. PMID:16549025

An application of statistics to comparative metagenomics.

PubMed

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-03-20

Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems.

Intelligent Method for Diagnosing Structural Faults of Rotating Machinery Using Ant Colony Optimization

PubMed Central

Li, Ke; Chen, Peng

2011-01-01

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called “relative ratio symptom parameters” are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks. PMID:22163833

Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

PubMed

Li, Ke; Chen, Peng

2011-01-01

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks.

Statistical significance test for transition matrices of atmospheric Markov chains

NASA Technical Reports Server (NTRS)

Vautard, Robert; Mo, Kingtse C.; Ghil, Michael

1990-01-01

Low-frequency variability of large-scale atmospheric dynamics can be represented schematically by a Markov chain of multiple flow regimes. This Markov chain contains useful information for the long-range forecaster, provided that the statistical significance of the associated transition matrix can be reliably tested. Monte Carlo simulation yields a very reliable significance test for the elements of this matrix. The results of this test agree with previously used empirical formulae when each cluster of maps identified as a distinct flow regime is sufficiently large and when they all contain a comparable number of maps. Monte Carlo simulation provides a more reliable way to test the statistical significance of transitions to and from small clusters. It can determine the most likely transitions, as well as the most unlikely ones, with a prescribed level of statistical significance.

Molecular dynamics simulations and statistical coupling analysis reveal functional coevolution network of oncogenic mutations in the CDKN2A-CDK6 complex.

PubMed

Wang, Jingwen; Zhao, Yuqi; Wang, Yanjie; Huang, Jingfei

2013-01-16

Coevolution between proteins is crucial for understanding protein-protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural-functional integrity. In this study, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on the CDK6-CDKN2A protein complex to evaluate coevolution between proteins. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37 interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in the CDK6-CDKN2A complex can be helpful for designing protein engineering experiments. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Testing for significance of phase synchronisation dynamics in the EEG.

PubMed

Daly, Ian; Sweeney-Reed, Catherine M; Nasuto, Slawomir J

2013-06-01

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

Calculation of precise firing statistics in a neural network model

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2017-08-01

A precise prediction of neural firing dynamics is requisite to understand the function of and the learning process in a biological neural network which works depending on exact spike timings. Basically, the prediction of firing statistics is a delicate manybody problem because the firing probability of a neuron at a time is determined by the summation over all effects from past firing states. A neural network model with the Feynman path integral formulation is recently introduced. In this paper, we present several methods to calculate firing statistics in the model. We apply the methods to some cases and compare the theoretical predictions with simulation results.

Human turnover dynamics during sleep: Statistical behavior and its modeling

NASA Astrophysics Data System (ADS)

Yoneyama, Mitsuru; Okuma, Yasuyuki; Utsumi, Hiroya; Terashi, Hiroo; Mitoma, Hiroshi

2014-03-01

Turnover is a typical intermittent body movement while asleep. Exploring its behavior may provide insights into the mechanisms and management of sleep. However, little is understood about the dynamic nature of turnover in healthy humans and how it can be modified in disease. Here we present a detailed analysis of turnover signals that are collected by accelerometry from healthy elderly subjects and age-matched patients with neurodegenerative disorders such as Parkinson's disease. In healthy subjects, the time intervals between consecutive turnover events exhibit a well-separated bimodal distribution with one mode at ⩽10 s and the other at ⩾100 s, whereas such bimodality tends to disappear in neurodegenerative patients. The discovery of bimodality and fine temporal structures (⩽10 s) is a contribution that is not revealed by conventional sleep recordings with less time resolution (≈30 s). Moreover, we estimate the scaling exponent of the interval fluctuations, which also shows a clear difference between healthy subjects and patients. We incorporate these experimental results into a computational model of human decision making. A decision is to be made at each simulation step between two choices: to keep on sleeping or to make a turnover, the selection of which is determined dynamically by comparing a pair of random numbers assigned to each choice. This decision is weighted by a single parameter that reflects the depth of sleep. The resulting simulated behavior accurately replicates many aspects of observed turnover patterns, including the appearance or disappearance of bimodality and leads to several predictions, suggesting that the depth parameter may be useful as a quantitative measure for differentiating between normal and pathological sleep. These findings have significant clinical implications and may pave the way for the development of practical sleep assessment technologies.

Human turnover dynamics during sleep: statistical behavior and its modeling.

PubMed

Yoneyama, Mitsuru; Okuma, Yasuyuki; Utsumi, Hiroya; Terashi, Hiroo; Mitoma, Hiroshi

2014-03-01

Turnover is a typical intermittent body movement while asleep. Exploring its behavior may provide insights into the mechanisms and management of sleep. However, little is understood about the dynamic nature of turnover in healthy humans and how it can be modified in disease. Here we present a detailed analysis of turnover signals that are collected by accelerometry from healthy elderly subjects and age-matched patients with neurodegenerative disorders such as Parkinson's disease. In healthy subjects, the time intervals between consecutive turnover events exhibit a well-separated bimodal distribution with one mode at ⩽10 s and the other at ⩾100 s, whereas such bimodality tends to disappear in neurodegenerative patients. The discovery of bimodality and fine temporal structures (⩽10 s) is a contribution that is not revealed by conventional sleep recordings with less time resolution (≈30 s). Moreover, we estimate the scaling exponent of the interval fluctuations, which also shows a clear difference between healthy subjects and patients. We incorporate these experimental results into a computational model of human decision making. A decision is to be made at each simulation step between two choices: to keep on sleeping or to make a turnover, the selection of which is determined dynamically by comparing a pair of random numbers assigned to each choice. This decision is weighted by a single parameter that reflects the depth of sleep. The resulting simulated behavior accurately replicates many aspects of observed turnover patterns, including the appearance or disappearance of bimodality and leads to several predictions, suggesting that the depth parameter may be useful as a quantitative measure for differentiating between normal and pathological sleep. These findings have significant clinical implications and may pave the way for the development of practical sleep assessment technologies.

Non-Extensive Statistical Analysis of Solar Wind Electric, Magnetic Fields and Solar Energetic Particle time series.

NASA Astrophysics Data System (ADS)

Pavlos, G. P.; Malandraki, O.; Khabarova, O.; Livadiotis, G.; Pavlos, E.; Karakatsanis, L. P.; Iliopoulos, A. C.; Parisis, K.

2017-12-01

In this work we study the non-extensivity of Solar Wind space plasma by using electric-magnetic field data obtained by in situ spacecraft observations at different dynamical states of solar wind system especially in interplanetary coronal mass ejections (ICMEs), Interplanetary shocks, magnetic islands, or near the Earth Bow shock. Especially, we study the energetic particle non extensive fractional acceleration mechanism producing kappa distributions as well as the intermittent turbulence mechanism producing multifractal structures related with the Tsallis q-entropy principle. We present some new and significant results concerning the dynamics of ICMEs observed in the near Earth at L1 solar wind environment, as well as its effect in Earth's magnetosphere as well as magnetic islands. In-situ measurements of energetic particles at L1 are analyzed, in response to major solar eruptive events at the Sun (intense flares, fast CMEs). The statistical characteristics are obtained and compared for the Solar Energetic Particles (SEPs) originating at the Sun, the energetic particle enhancements associated with local acceleration during the CME-driven shock passage over the spacecraft (Energetic Particle Enhancements, ESPs) as well as the energetic particle signatures observed during the passage of the ICME. The results are referred to Tsallis non-extensive statistics and in particular to the estimation of Tsallis q-triplet, (qstat, qsen, qrel) of electric-magnetic field and the kappa distributions of solar energetic particles time series of the ICME, magnetic islands, resulting from the solar eruptive activity or the internal Solar Wind dynamics. Our results reveal significant differences in statistical and dynamical features, indicating important variations of the magnetic field dynamics both in time and space domains during the shock event, in terms of rate of entropy production, relaxation dynamics and non-equilibrium meta-stable stationary states.

Role of Three-Dimensional Speckle Tracking Echocardiography in the Quantification of Myocardial Iron Overload in Patients with Beta-Thalassemia Major.

PubMed

Li, Shu-Juan; Hwang, Yu-Yan; Ha, Shau-Yin; Chan, Godfrey C F; Mok, Amanda S P; Wong, Sophia J; Cheung, Yiu-Fai

2016-09-01

The new three-dimensional speckle tracking echocardiography (3DSTE) may enable comprehensive quantification of global left ventricular (LV) myocardial mechanics. Twenty-four patients aged 29.3 ± 5.2 years and 22 controls were studied. 3DSTE was performed to assess LV 3D global strain, twist and torsion, ejection fraction, and systolic dyssynchrony index (SDI). The LV SDI was calculated as % of SD of times-to-peak strain of 16 segments/RR interval. The global performance index (GPI) was calculated as (global 3D strain·torsion)/SDI. Area under the receiver operating characteristic curve (AUC) was calculated to determine the capability of 3DSTE parameters to discriminate between patients with (cardiac magnetic resonance T2* <20 ms) and those without myocardial iron overload. Compared with controls, patients had significantly lower LV global 3D strain (P < 0.001), twist (P = 0.01), torsion (P = 0.04), and ejection fraction (P < 0.001) and greater SDI (P < 0.001). The GPI was lower in patients than controls (P < 0.001). T2* value correlated positively with global 3D strain (r = 0.74, P < 0.001) and GPI (r = 0.63, P = 0.001), and negatively with SDI (r = -0.44, P = 0.03). The AUCs of GPI, global 3D strain, ejection fraction, torsion, and 1/SDI were 0.94, 0.90, 0.87, 0.82, and 0.70, respectively. The GPI cutoff of 2.7°/cm had a sensitivity of 94.9% and a specificity of 88.9% of differentiating patients with from those without myocardial iron overload. The LV composite index of strain, torsion, and dyssynchrony derived from 3DSTE enables sensitive detection of myocardial iron overload in patients with thalassemia. © 2016, Wiley Periodicals, Inc.

Decision-making and addiction (part II): myopia for the future or hypersensitivity to reward?

PubMed

Bechara, Antoine; Dolan, Sara; Hindes, Andrea

2002-01-01

On a decision-making instrument known as the "gambling task" (GT), a subgroup of substance dependent individuals (SDI) opted for choices that yield high immediate gains in spite of higher future losses. This resembles the behavior of patients with ventromedial (VM) prefrontal cortex lesions. In this study, we addressed the possibility that hypersensitivity to reward may account for the "myopia" for the future in this subgroup of SDI. We used a variant version of the GT, in which the good decks yielded high immediate punishment but higher delayed reward. The bad decks yielded low immediate punishment and lower delayed reward. We measured the skin conductance response (SCR) of subjects after receiving reward (reward SCR) and during their pondering from which deck to choose (anticipatory SCR). A subgroup of SDI who was not impaired on the original GT performed normally on the variant GT. The subgroup of SDI who was impaired on the original GT showed two levels of performance on the variant GT. One subgroup (36% of the sample) performed poorly on the variant GT, and showed similar behavioral and physiological impairments to VM patients. The other subgroup of SDI (64% of the sample) performed normally on the variant task, but had abnormally large physiological responses to reward, i.e. large SCR after receiving reward (reward SCR) and large SCR in anticipation of outcomes that yield large reward. Thus, the combined cognitive and physiological approach of assessing decision-making characterizes three sub-populations of SDI. One sub-population is without impairments that can be detected by any measure of the GT paradigm. Another sub-population is similar to VM patients in that they are insensitive to the future, both positive and negative. A third sub-population is hypersensitive to reward, so that the presence or the prospect of receiving, reward dominates their behavior.

Student Papers on Strategic Defense Initiative.

DTIC Science & Technology

1985-01-01

Initiative" NATO’s Sixteen Nations, November 1984, p. 18. 6. Europe, p. 45. 7. Macha Levinson, "Why Europe Fears SDI," International Defense Review...34Europe is Reluctant to Reach for the Stars." The Economist, 16 February 1985, pp. 45-46. Levinson, Macha . "Why Europe Fears SDI." International

Selecting Summary Statistics in Approximate Bayesian Computation for Calibrating Stochastic Models

PubMed Central

Burr, Tom

2013-01-01

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the “go-to” option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics rather than the full data and is therefore computationally feasible. One technical challenge with ABC is that the quality of the approximation to the posterior distribution of model parameters depends on the user-chosen summary statistics. In this paper, the user requirement to choose effective summary statistics in order to accurately estimate the posterior distribution of model parameters is investigated and illustrated by example, using a model and corresponding real data of mitochondrial DNA population dynamics. We show that for some choices of summary statistics, the posterior distribution of model parameters is closely approximated and for other choices of summary statistics, the posterior distribution is not closely approximated. A strategy to choose effective summary statistics is suggested in cases where the stochastic computer model can be run at many trial parameter settings, as in the example. PMID:24288668

A concurrent multiscale micromorphic molecular dynamics

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

Li, Shaofan, E-mail: shaofan@berkeley.edu; Tong, Qi

2015-04-21

In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from firstmore » principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation.« less

Quality changes of pomegranate arils throughout shelf life affected by deficit irrigation and pre-processing storage.

PubMed

Peña-Estévez, María E; Artés-Hernández, Francisco; Artés, Francisco; Aguayo, Encarna; Martínez-Hernández, Ginés Benito; Galindo, Alejandro; Gómez, Perla A

2016-10-15

This study investigated the influence of sustained deficit irrigation (SDI, 78% less water supply than the reference evapotranspiration, ET0) compared to a control (100% ET0) on the physicochemical and sensory qualities and health-promoting compounds of pomegranate arils stored for 14days at 5°C. Prior to processing, the fruits were stored for 0, 30, 60 or 90days at 5°C. The effect of the pre-processing storage duration was also examined. Physicochemical and sensory qualities were kept during the storage period. Arils from SDI fruit had lower punicalagin-α and ellagic acid losses than the control (13% vs 50%). However, the anthocyanin content decreased during the shelf-life (72%) regardless of the treatment. The ascorbic acid slight decreased. Arils from SDI experienced glucose/fructose ratio loss (19%) lower than that of the control (35%). In general, arils from SDI showed better quality and health attributes during the shelf-life than did the control samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Universality classes of fluctuation dynamics in hierarchical complex systems

NASA Astrophysics Data System (ADS)

Macêdo, A. M. S.; González, Iván R. Roa; Salazar, D. S. P.; Vasconcelos, G. L.

2017-03-01

A unified approach is proposed to describe the statistics of the short-time dynamics of multiscale complex systems. The probability density function of the relevant time series (signal) is represented as a statistical superposition of a large time-scale distribution weighted by the distribution of certain internal variables that characterize the slowly changing background. The dynamics of the background is formulated as a hierarchical stochastic model whose form is derived from simple physical constraints, which in turn restrict the dynamics to only two possible classes. The probability distributions of both the signal and the background have simple representations in terms of Meijer G functions. The two universality classes for the background dynamics manifest themselves in the signal distribution as two types of tails: power law and stretched exponential, respectively. A detailed analysis of empirical data from classical turbulence and financial markets shows excellent agreement with the theory.

Graphene Statistical Mechanics

NASA Astrophysics Data System (ADS)

Bowick, Mark; Kosmrlj, Andrej; Nelson, David; Sknepnek, Rastko

2015-03-01

Graphene provides an ideal system to test the statistical mechanics of thermally fluctuating elastic membranes. The high Young's modulus of graphene means that thermal fluctuations over even small length scales significantly stiffen the renormalized bending rigidity. We study the effect of thermal fluctuations on graphene ribbons of width W and length L, pinned at one end, via coarse-grained Molecular Dynamics simulations and compare with analytic predictions of the scaling of width-averaged root-mean-squared height fluctuations as a function of distance along the ribbon. Scaling collapse as a function of W and L also allows us to extract the scaling exponent eta governing the long-wavelength stiffening of the bending rigidity. A full understanding of the geometry-dependent mechanical properties of graphene, including arrays of cuts, may allow the design of a variety of modular elements with desired mechanical properties starting from pure graphene alone. Supported by NSF grant DMR-1435794

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

Mark, H.

A development history and development status evaluation is presented for weapons technologies capable of serving as defenses against nuclear-tipped ballistic missiles. The decisive turning-point in this history was the March 23, 1983 announcement by President Reagan of the Strategic Defense Initiative (SDI). Due to President Reagan's emphasis on population protection, 'global' defense systems have tended to dominate SDI design efforts. The most important SDI technical achievements to date encompass (1) miniature homig devices, (2) the upgrade of the Patriot SAM for missile-interception capabilities, (3) light exoatmospheric projectiles, such as 'Brilliant Pebbles', (4) successful laser-communications experiments, and (5) the warhead/decoy-discriminating Firepondmore » lidar system. 7 refs.« less

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

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

Zhang, T.

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover,more » soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations. 46 refs., 10 figs., 6 tabs.« less

Statistical Properties and Pre-Hit Dynamics of Price Limit Hits in the Chinese Stock Markets

PubMed Central

Wan, Yu-Lei; Xie, Wen-Jie; Gu, Gao-Feng; Jiang, Zhi-Qiang; Chen, Wei; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

2015-01-01

Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders’ short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners. PMID:25874716

Financial price dynamics and pedestrian counterflows: A comparison of statistical stylized facts

NASA Astrophysics Data System (ADS)

Parisi, Daniel R.; Sornette, Didier; Helbing, Dirk

2013-01-01

We propose and document the evidence for an analogy between the dynamics of granular counterflows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counterflows of simulated pedestrians through a door display eight stylized facts observed in financial markets when the density around the door is compared with the logarithm of the price. Finding so many stylized facts is very rare indeed among all agent-based models of financial markets. The stylized properties are present when the agents in the pedestrian model are assumed to display a zero-intelligent behavior. If agents are given decision-making capacity and adapt to partially follow the majority, periods of herding behavior may additionally occur. This generates the very slow decay of the autocorrelation of absolute return due to an intermittent dynamics. Our findings suggest that the stylized facts in the fluctuations of the financial prices result from a competition of two groups with opposite interests in the presence of a constraint funneling the flow of transactions to a narrow band of prices with limited liquidity.

Financial price dynamics and pedestrian counterflows: a comparison of statistical stylized facts.

PubMed

Parisi, Daniel R; Sornette, Didier; Helbing, Dirk

2013-01-01

We propose and document the evidence for an analogy between the dynamics of granular counterflows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counterflows of simulated pedestrians through a door display eight stylized facts observed in financial markets when the density around the door is compared with the logarithm of the price. Finding so many stylized facts is very rare indeed among all agent-based models of financial markets. The stylized properties are present when the agents in the pedestrian model are assumed to display a zero-intelligent behavior. If agents are given decision-making capacity and adapt to partially follow the majority, periods of herding behavior may additionally occur. This generates the very slow decay of the autocorrelation of absolute return due to an intermittent dynamics. Our findings suggest that the stylized facts in the fluctuations of the financial prices result from a competition of two groups with opposite interests in the presence of a constraint funneling the flow of transactions to a narrow band of prices with limited liquidity.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

Statistical Neurodynamics.

NASA Astrophysics Data System (ADS)

Paine, Gregory Harold

1982-03-01

The primary objective of the thesis is to explore the dynamical properties of small nerve networks by means of the methods of statistical mechanics. To this end, a general formalism is developed and applied to elementary groupings of model neurons which are driven by either constant (steady state) or nonconstant (nonsteady state) forces. Neuronal models described by a system of coupled, nonlinear, first-order, ordinary differential equations are considered. A linearized form of the neuronal equations is studied in detail. A Lagrange function corresponding to the linear neural network is constructed which, through a Legendre transformation, provides a constant of motion. By invoking the Maximum-Entropy Principle with the single integral of motion as a constraint, a probability distribution function for the network in a steady state can be obtained. The formalism is implemented for some simple networks driven by a constant force; accordingly, the analysis focuses on a study of fluctuations about the steady state. In particular, a network composed of N noninteracting neurons, termed Free Thinkers, is considered in detail, with a view to interpretation and numerical estimation of the Lagrange multiplier corresponding to the constant of motion. As an archetypical example of a net of interacting neurons, the classical neural oscillator, consisting of two mutually inhibitory neurons, is investigated. It is further shown that in the case of a network driven by a nonconstant force, the Maximum-Entropy Principle can be applied to determine a probability distribution functional describing the network in a nonsteady state. The above examples are reconsidered with nonconstant driving forces which produce small deviations from the steady state. Numerical studies are performed on simplified models of two physical systems: the starfish central nervous system and the mammalian olfactory bulb. Discussions are given as to how statistical neurodynamics can be used to gain a better

Establishing Consensus Turbulence Statistics for Hot Subsonic Jets

NASA Technical Reports Server (NTRS)

Bridges, James; Werner, Mark P.

2010-01-01

Many tasks in fluids engineering require knowledge of the turbulence in jets. There is a strong, although fragmented, literature base for low order statistics, such as jet spread and other meanvelocity field characteristics. Some sources, particularly for low speed cold jets, also provide turbulence intensities that are required for validating Reynolds-averaged Navier-Stokes (RANS) Computational Fluid Dynamics (CFD) codes. There are far fewer sources for jet spectra and for space-time correlations of turbulent velocity required for aeroacoustics applications, although there have been many singular publications with various unique statistics, such as Proper Orthogonal Decomposition, designed to uncover an underlying low-order dynamical description of turbulent jet flow. As the complexity of the statistic increases, the number of flows for which the data has been categorized and assembled decreases, making it difficult to systematically validate prediction codes that require high-level statistics over a broad range of jet flow conditions. For several years, researchers at NASA have worked on developing and validating jet noise prediction codes. One such class of codes, loosely called CFD-based or statistical methods, uses RANS CFD to predict jet mean and turbulent intensities in velocity and temperature. These flow quantities serve as the input to the acoustic source models and flow-sound interaction calculations that yield predictions of far-field jet noise. To develop this capability, a catalog of turbulent jet flows has been created with statistics ranging from mean velocity to space-time correlations of Reynolds stresses. The present document aims to document this catalog and to assess the accuracies of the data, e.g. establish uncertainties for the data. This paper covers the following five tasks: Document acquisition and processing procedures used to create the particle image velocimetry (PIV) datasets. Compare PIV data with hotwire and laser Doppler

New Method for Determining the Relative Stand Density of Forest Inventory Plots

Treesearch

Christopher W. Woodall; Patrick D. Miles

2006-01-01

Determining the relative density of Forest Inventory and Analysis plots is complicated by the various species and tree size combinations in the Nation?s forested ecosystems. Stand density index (SDI), although developed for use in even-aged monocultures, has been used for stand density assessment in largescale forest inventories. To improve application of SDI in uneven...

A statistical analogy between collapse of solids and death of living organisms: proposal for a 'law of life'.

PubMed

Pugno, Nicola M

2007-01-01

In this paper we present a statistical analogy between the collapse of solids and living organisms; in particular we deduce a statistical law governing their probability of death. We have derived such a law coupling the widely used Weibull Statistics, developed for describing the distribution of the strength of solids, with a general model for ontogenetic growth recently proposed in literature. The main idea presented in this paper is that cracks can propagate in solids and cause their failure as sick cells in living organisms can cause their death. Making a rough analogy, living organisms are found to behave as "growing" mechanical components under cyclic, i.e., fatigue, loadings and composed by a dynamic evolutionary material that, as an ineluctable fate, deteriorates. The implications on biological scaling laws are discussed. As an example, we apply such a Dynamic Weibull Statistics to large data collections on human deaths due to cancer of various types recorded in Italy: a significant agreement is observed.

The Relationship between Statistics Self-Efficacy, Statistics Anxiety, and Performance in an Introductory Graduate Statistics Course

ERIC Educational Resources Information Center

Schneider, William R.

2011-01-01

The purpose of this study was to determine the relationship between statistics self-efficacy, statistics anxiety, and performance in introductory graduate statistics courses. The study design compared two statistics self-efficacy measures developed by Finney and Schraw (2003), a statistics anxiety measure developed by Cruise and Wilkins (1980),…

Photon statistics and speckle visibility spectroscopy with partially coherent X-rays.

PubMed

Li, Luxi; Kwaśniewski, Paweł; Orsi, Davide; Wiegart, Lutz; Cristofolini, Luigi; Caronna, Chiara; Fluerasu, Andrei

2014-11-01

A new approach is proposed for measuring structural dynamics in materials from multi-speckle scattering patterns obtained with partially coherent X-rays. Coherent X-ray scattering is already widely used at high-brightness synchrotron lightsources to measure dynamics using X-ray photon correlation spectroscopy, but in many situations this experimental approach based on recording long series of images (i.e. movies) is either not adequate or not practical. Following the development of visible-light speckle visibility spectroscopy, the dynamic information is obtained instead by analyzing the photon statistics and calculating the speckle contrast in single scattering patterns. This quantity, also referred to as the speckle visibility, is determined by the properties of the partially coherent beam and other experimental parameters, as well as the internal motions in the sample (dynamics). As a case study, Brownian dynamics in a low-density colloidal suspension is measured and an excellent agreement is found between correlation functions measured by X-ray photon correlation spectroscopy and the decay in speckle visibility with integration time obtained from the analysis presented here.

Realistic finite temperature simulations of magnetic systems using quantum statistics

NASA Astrophysics Data System (ADS)

Bergqvist, Lars; Bergman, Anders

2018-01-01

We have performed realistic atomistic simulations at finite temperatures using Monte Carlo and atomistic spin dynamics simulations incorporating quantum (Bose-Einstein) statistics. The description is much improved at low temperatures compared to classical (Boltzmann) statistics normally used in these kind of simulations, while at higher temperatures the classical statistics are recovered. This corrected low-temperature description is reflected in both magnetization and the magnetic specific heat, the latter allowing for improved modeling of the magnetic contribution to free energies. A central property in the method is the magnon density of states at finite temperatures, and we have compared several different implementations for obtaining it. The method has no restrictions regarding chemical and magnetic order of the considered materials. This is demonstrated by applying the method to elemental ferromagnetic systems, including Fe and Ni, as well as Fe-Co random alloys and the ferrimagnetic system GdFe3.

Environmental statistics and optimal regulation.

PubMed

Sivak, David A; Thomson, Matt

2014-09-01

Any organism is embedded in an environment that changes over time. The timescale for and statistics of environmental change, the precision with which the organism can detect its environment, and the costs and benefits of particular protein expression levels all will affect the suitability of different strategies--such as constitutive expression or graded response--for regulating protein levels in response to environmental inputs. We propose a general framework-here specifically applied to the enzymatic regulation of metabolism in response to changing concentrations of a basic nutrient-to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, respectively, and the costs associated with enzyme production. We use this framework to address three fundamental questions: (i) when a cell should prefer thresholding to a graded response; (ii) when there is a fitness advantage to implementing a Bayesian decision rule; and (iii) when retaining memory of the past provides a selective advantage. We specifically find that: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones.

Environmental Statistics and Optimal Regulation

PubMed Central

2014-01-01

Any organism is embedded in an environment that changes over time. The timescale for and statistics of environmental change, the precision with which the organism can detect its environment, and the costs and benefits of particular protein expression levels all will affect the suitability of different strategies–such as constitutive expression or graded response–for regulating protein levels in response to environmental inputs. We propose a general framework–here specifically applied to the enzymatic regulation of metabolism in response to changing concentrations of a basic nutrient–to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, respectively, and the costs associated with enzyme production. We use this framework to address three fundamental questions: (i) when a cell should prefer thresholding to a graded response; (ii) when there is a fitness advantage to implementing a Bayesian decision rule; and (iii) when retaining memory of the past provides a selective advantage. We specifically find that: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones. PMID:25254493

Relationship between Graduate Students' Statistics Self-Efficacy, Statistics Anxiety, Attitude toward Statistics, and Social Support

ERIC Educational Resources Information Center

Perepiczka, Michelle; Chandler, Nichelle; Becerra, Michael

2011-01-01

Statistics plays an integral role in graduate programs. However, numerous intra- and interpersonal factors may lead to successful completion of needed coursework in this area. The authors examined the extent of the relationship between self-efficacy to learn statistics and statistics anxiety, attitude towards statistics, and social support of 166…

Statistical and sampling issues when using multiple particle tracking

NASA Astrophysics Data System (ADS)

Savin, Thierry; Doyle, Patrick S.

2007-08-01

Video microscopy can be used to simultaneously track several microparticles embedded in a complex material. The trajectories are used to extract a sample of displacements at random locations in the material. From this sample, averaged quantities characterizing the dynamics of the probes are calculated to evaluate structural and/or mechanical properties of the assessed material. However, the sampling of measured displacements in heterogeneous systems is singular because the volume of observation with video microscopy is finite. By carefully characterizing the sampling design in the experimental output of the multiple particle tracking technique, we derive estimators for the mean and variance of the probes’ dynamics that are independent of the peculiar statistical characteristics. We expose stringent tests of these estimators using simulated and experimental complex systems with a known heterogeneous structure. Up to a certain fundamental limitation, which we characterize through a material degree of sampling by the embedded probe tracking, these estimators can be applied to quantify the heterogeneity of a material, providing an original and intelligible kind of information on complex fluid properties. More generally, we show that the precise assessment of the statistics in the multiple particle tracking output sample of observations is essential in order to provide accurate unbiased measurements.

Negative reinforcement learning is affected in substance dependence.

PubMed

Thompson, Laetitia L; Claus, Eric D; Mikulich-Gilbertson, Susan K; Banich, Marie T; Crowley, Thomas; Krmpotich, Theodore; Miller, David; Tanabe, Jody

2012-06-01

Negative reinforcement results in behavior to escape or avoid an aversive outcome. Withdrawal symptoms are purported to be negative reinforcers in perpetuating substance dependence, but little is known about negative reinforcement learning in this population. The purpose of this study was to examine reinforcement learning in substance dependent individuals (SDI), with an emphasis on assessing negative reinforcement learning. We modified the Iowa Gambling Task to separately assess positive and negative reinforcement. We hypothesized that SDI would show differences in negative reinforcement learning compared to controls and we investigated whether learning differed as a function of the relative magnitude or frequency of the reinforcer. Thirty subjects dependent on psychostimulants were compared with 28 community controls on a decision making task that manipulated outcome frequencies and magnitudes and required an action to avoid a negative outcome. SDI did not learn to avoid negative outcomes to the same degree as controls. This difference was driven by the magnitude, not the frequency, of negative feedback. In contrast, approach behaviors in response to positive reinforcement were similar in both groups. Our findings are consistent with a specific deficit in negative reinforcement learning in SDI. SDI were relatively insensitive to the magnitude, not frequency, of loss. If this generalizes to drug-related stimuli, it suggests that repeated episodes of withdrawal may drive relapse more than the severity of a single episode. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

a Bottom-Up Geosptial Data Update Mechanism for Spatial Data Infrastructure Updating

NASA Astrophysics Data System (ADS)

Tian, W.; Zhu, X.; Liu, Y.

2012-08-01

Currently, the top-down spatial data update mechanism has made a big progress and it is wildly applied in many SDI (spatial data infrastructure). However, this mechanism still has some issues. For example, the update schedule is limited by the professional department's project, usually which is too long for the end-user; the data form collection to public cost too much time and energy for professional department; the details of geospatial information does not provide sufficient attribute, etc. Thus, how to deal with the problems has become the effective shortcut. Emerging Internet technology, 3S technique and geographic information knowledge which is popular in the public promote the booming development of geoscience in volunteered geospatial information. Volunteered geospatial information is the current "hotspot", which attracts many researchers to study its data quality and credibility, accuracy, sustainability, social benefit, application and so on. In addition to this, a few scholars also pay attention to the value of VGI to support the SDI updating. And on that basis, this paper presents a bottom-up update mechanism form VGI to SDI, which includes the processes of match homonymous elements between VGI and SDI vector data , change data detection, SDI spatial database update and new data product publication to end-users. Then, the proposed updating cycle is deeply discussed about the feasibility of which can detect the changed elements in time and shorten the update period, provide more accurate geometry and attribute data for spatial data infrastructure and support update propagation.

Multi-scale study of condensation in water jets using ellipsoidal-statistical Bhatnagar-Gross-Krook and molecular dynamics modeling

NASA Astrophysics Data System (ADS)

Li, Zheng; Borner, Arnaud; Levin, Deborah A.

2014-06-01

Homogeneous water condensation and ice formation in supersonic expansions to vacuum for stagnation pressures from 12 to 1000 mbar are studied using the particle-based Ellipsoidal-Statistical Bhatnagar-Gross-Krook (ES-BGK) method. We find that when condensation starts to occur, at a stagnation pressure of 96 mbar, the increase in the degree of condensation causes an increase in the rotational temperature due to the latent heat of vaporization. The simulated rotational temperature profiles along the plume expansion agree well with measurements confirming the kinetic homogeneous condensation models and the method of simulation. Comparisons of the simulated gas and cluster number densities, cluster size for different stagnation pressures along the plume centerline were made and it is found that the cluster size increase linearly with respect to stagnation pressure, consistent with classical nucleation theory. The sensitivity of our results to cluster nucleation model and latent heat values based on bulk water, specific cluster size, or bulk ice are examined. In particular, the ES-BGK simulations are found to be too coarse-grained to provide information on the phase or structure of the clusters formed. For this reason, molecular dynamics simulations of water condensation in a one-dimensional free expansion to simulate the conditions in the core of a plume are performed. We find that the internal structure of the clusters formed depends on the stagnation temperature. A larger cluster of average size 21 was tracked down the expansion, and a calculation of its average internal temperature as well as a comparison of its radial distribution functions (RDFs) with values measured for solid amorphous ice clusters lead us to conclude that this cluster is in a solid-like rather than liquid form. In another molecular-dynamics simulation at a much lower stagnation temperature, a larger cluster of size 324 and internal temperature 200 K was extracted from an expansion plume and

82 Key Statistics on Work and Family Issues. The National Report on Work & Family. Special Report #9.

ERIC Educational Resources Information Center

Bureau of National Affairs, Inc., Washington, DC.

This report was prepared because of the growing national interest in the questions of work and family dynamics. It puts together 82 key statistics on work and family issues in four major areas: child care, parental leave, alternative work schedules, and elder care. In addition, a chapter of miscellaneous statistics covers areas such as the…

The differences in temperament-character traits, suicide attempts, impulsivity, and functionality levels of patients with bipolar disorder I and II.

PubMed

Izci, Filiz; Fındıklı, Ebru Kanmaz; Zincir, Serkan; Zincir, Selma Bozkurt; Koc, Merve Iris

2016-01-01

The primary aim of this study was to compare the differences in temperament-character traits, suicide attempts, impulsivity, and functionality levels of patients with bipolar disorder I (BD-I) and bipolar disorder II (BD-II). Fifty-two BD-I patients and 49 BD-II patients admitted to Erenköy Mental and Neurological Disease Training and Research Hospital psychiatry clinic and fifty age- and sex-matched healthy control subjects were enrolled in this study. A structured clinical interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition Axis I Disorders, Temperament and Character Inventory, Barrett Impulsiveness Scale-11 (BIS-11), Hamilton Depression Inventory Scale, Young Mania Rating Scale, and Bipolar Disorder Functioning Questionnaire (BDFQ) were administered to patients and to control group. No statistically significant difference in sociodemographic features existed between the patient and control groups (P>0.05). Thirty-eight subjects (37.62%) in the patient group had a suicide attempt. Twenty-three of these subjects (60.52%) had BD-I, and 15 of these subjects (39.47%) had BD-II. Suicide attempt rates in BD-I and II patients were 60.52% and 39.47%, respectively (P<0.05). Comparison of BD-I and II patients with healthy control subjects revealed that cooperativeness (C), self-directedness (Sdi), and self-transcendence (ST) scores were lower and novelty seeking (NS1 and NS2), harm avoidance (HA4), and reward dependence (RD2) subscale scores were higher in patients with BD-I. When BD-I patients were compared with BD-II patients, BIS-11 (attention) scores were higher in patients with BD-II and BIS-11 (motor and nonplanning impulsivity) scores were higher in patients with BD-I. According to BDFQ, relations with friends, participation in social activities, daily activities and hobbies, and occupation subscale scores were lower and taking initiative subscale scores were higher in patients with BD-I. Social withdrawal subscale scores were higher in

Statistical analyses support power law distributions found in neuronal avalanches.

PubMed

Klaus, Andreas; Yu, Shan; Plenz, Dietmar

2011-01-01

The size distribution of neuronal avalanches in cortical networks has been reported to follow a power law distribution with exponent close to -1.5, which is a reflection of long-range spatial correlations in spontaneous neuronal activity. However, identifying power law scaling in empirical data can be difficult and sometimes controversial. In the present study, we tested the power law hypothesis for neuronal avalanches by using more stringent statistical analyses. In particular, we performed the following steps: (i) analysis of finite-size scaling to identify scale-free dynamics in neuronal avalanches, (ii) model parameter estimation to determine the specific exponent of the power law, and (iii) comparison of the power law to alternative model distributions. Consistent with critical state dynamics, avalanche size distributions exhibited robust scaling behavior in which the maximum avalanche size was limited only by the spatial extent of sampling ("finite size" effect). This scale-free dynamics suggests the power law as a model for the distribution of avalanche sizes. Using both the Kolmogorov-Smirnov statistic and a maximum likelihood approach, we found the slope to be close to -1.5, which is in line with previous reports. Finally, the power law model for neuronal avalanches was compared to the exponential and to various heavy-tail distributions based on the Kolmogorov-Smirnov distance and by using a log-likelihood ratio test. Both the power law distribution without and with exponential cut-off provided significantly better fits to the cluster size distributions in neuronal avalanches than the exponential, the lognormal and the gamma distribution. In summary, our findings strongly support the power law scaling in neuronal avalanches, providing further evidence for critical state dynamics in superficial layers of cortex.

Assessing the performance of surface and subsurface drip systems on irrigation water use efficiency of citrus orchards in Spain

NASA Astrophysics Data System (ADS)

Amparo Martinez-Gimeno, Maria; Provenzano, Giuseppe; Bonet, Luis; Intrigliolo, Diego S.; Badal, Eduardo; Ballestrer, Carlos

2017-04-01

.2 MPa in the remaining period of the year. In each sub-plot, soil water contents at different depths were monitored with a Frequency Domain Reflectometry probe (EnviroScan, Sentek, Stepney, Australia.), whereas ψstem values were acquired approximately weekly, with a Scholander chamber (Model 600 Pressure Chamber Instrument), on leaves wrapped in bags at least one hour before measurements. At the end of each season, the number of fruit per plant, the average fruit weight, the total yield and their corresponding variability were determined for each treatment. The results showed that within both DI and SDI, treatments with the double number of emitters per plant had the highest yield, number of fruit, fruit weight and IWUE, although with no statistically significant differences. IWUE associated to DI and SDI was, on average for the two years, 6.5 and 7.4 kg/m3, respectively. The best management option was achieved with the SDI14, to which corresponded the minimum seasonal irrigation volumes, with water savings compared to DI7 of about 23% and 28% in 2014 and 2015, respectively.

Dynamics of Granular Materials

NASA Technical Reports Server (NTRS)

Behringer, Robert P.

1996-01-01

Granular materials exhibit a rich variety of dynamical behavior, much of which is poorly understood. Fractal-like stress chains, convection, a variety of wave dynamics, including waves which resemble capillary waves, l/f noise, and fractional Brownian motion provide examples. Work beginning at Duke will focus on gravity driven convection, mixing and gravitational collapse. Although granular materials consist of collections of interacting particles, there are important differences between the dynamics of a collections of grains and the dynamics of a collections of molecules. In particular, the ergodic hypothesis is generally invalid for granular materials, so that ordinary statistical physics does not apply. In the absence of a steady energy input, granular materials undergo a rapid collapse which is strongly influenced by the presence of gravity. Fluctuations on laboratory scales in such quantities as the stress can be very large-as much as an order of magnitude greater than the mean.

High dynamic range subjective testing

NASA Astrophysics Data System (ADS)

Allan, Brahim; Nilsson, Mike

2016-09-01

This paper describes of a set of subjective tests that the authors have carried out to assess the end user perception of video encoded with High Dynamic Range technology when viewed in a typical home environment. Viewers scored individual single clips of content, presented in High Definition (HD) and Ultra High Definition (UHD), in Standard Dynamic Range (SDR), and in High Dynamic Range (HDR) using both the Perceptual Quantizer (PQ) and Hybrid Log Gamma (HLG) transfer characteristics, and presented in SDR as the backwards compatible rendering of the HLG representation. The quality of SDR HD was improved by approximately equal amounts by either increasing the dynamic range or increasing the resolution to UHD. A further smaller increase in quality was observed in the Mean Opinion Scores of the viewers by increasing both the dynamic range and the resolution, but this was not quite statistically significant.

Real-time dynamic range and signal to noise enhancement in beam-scanning microscopy by integration of sensor characteristics, data acquisition hardware, and statistical methods

NASA Astrophysics Data System (ADS)

Kissick, David J.; Muir, Ryan D.; Sullivan, Shane Z.; Oglesbee, Robert A.; Simpson, Garth J.

2013-02-01

Despite the ubiquitous use of multi-photon and confocal microscopy measurements in biology, the core techniques typically suffer from fundamental compromises between signal to noise (S/N) and linear dynamic range (LDR). In this study, direct synchronous digitization of voltage transients coupled with statistical analysis is shown to allow S/N approaching the theoretical maximum throughout an LDR spanning more than 8 decades, limited only by the dark counts of the detector on the low end and by the intrinsic nonlinearities of the photomultiplier tube (PMT) detector on the high end. Synchronous digitization of each voltage transient represents a fundamental departure from established methods in confocal/multi-photon imaging, which are currently based on either photon counting or signal averaging. High information-density data acquisition (up to 3.2 GB/s of raw data) enables the smooth transition between the two modalities on a pixel-by-pixel basis and the ultimate writing of much smaller files (few kB/s). Modeling of the PMT response allows extraction of key sensor parameters from the histogram of voltage peak-heights. Applications in second harmonic generation (SHG) microscopy are described demonstrating S/N approaching the shot-noise limit of the detector over large dynamic ranges.

Lindeberg theorem for Gibbs-Markov dynamics

NASA Astrophysics Data System (ADS)

Denker, Manfred; Senti, Samuel; Zhang, Xuan

2017-12-01

A dynamical array consists of a family of functions \\{ fn, i: 1≤slant i≤slant k_n, n≥slant 1\\} and a family of initial times \\{τn, i: 1≤slant i≤slant k_n, n≥slant 1\\} . For a dynamical system (X, T) we identify distributional limits for sums of the form for suitable (non-random) constants s_n>0 and an, i\\in { R} . We derive a Lindeberg-type central limit theorem for dynamical arrays. Applications include new central limit theorems for functions which are not locally Lipschitz continuous and central limit theorems for statistical functions of time series obtained from Gibbs-Markov systems. Our results, which hold for more general dynamics, are stated in the context of Gibbs-Markov dynamical systems for convenience.

A statistical mechanical model of economics

NASA Astrophysics Data System (ADS)

Lubbers, Nicholas Edward Williams

Statistical mechanics pursues low-dimensional descriptions of systems with a very large number of degrees of freedom. I explore this theme in two contexts. The main body of this dissertation explores and extends the Yard Sale Model (YSM) of economic transactions using a combination of simulations and theory. The YSM is a simple interacting model for wealth distributions which has the potential to explain the empirical observation of Pareto distributions of wealth. I develop the link between wealth condensation and the breakdown of ergodicity due to nonlinear diffusion effects which are analogous to the geometric random walk. Using this, I develop a deterministic effective theory of wealth transfer in the YSM that is useful for explaining many quantitative results. I introduce various forms of growth to the model, paying attention to the effect of growth on wealth condensation, inequality, and ergodicity. Arithmetic growth is found to partially break condensation, and geometric growth is found to completely break condensation. Further generalizations of geometric growth with growth in- equality show that the system is divided into two phases by a tipping point in the inequality parameter. The tipping point marks the line between systems which are ergodic and systems which exhibit wealth condensation. I explore generalizations of the YSM transaction scheme to arbitrary betting functions to develop notions of universality in YSM-like models. I find that wealth vi condensation is universal to a large class of models which can be divided into two phases. The first exhibits slow, power-law condensation dynamics, and the second exhibits fast, finite-time condensation dynamics. I find that the YSM, which exhibits exponential dynamics, is the critical, self-similar model which marks the dividing line between the two phases. The final chapter develops a low-dimensional approach to materials microstructure quantification. Modern materials design harnesses complex

Dynamic Displays of Data

ERIC Educational Resources Information Center

Angotti, Robin

2017-01-01

This article describes Gapminder, a dynamic time-series graph that can be found at http://www.gapminder.org. Gapminder was created by a team of developers (Rosling, Ronnlund, and Rosling 2005) to create beautiful, interactive graphs of otherwise lifeless numbers. Their goal is increased use and understanding of statistics and data that…

Harmonic statistics

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-05-01

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their 'public relations' for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford's law, and 1/f noise.

Statistical genetics and evolution of quantitative traits

NASA Astrophysics Data System (ADS)

Neher, Richard A.; Shraiman, Boris I.

2011-10-01

The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach quasilinkage equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parametrized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. Key results of quantitative genetics such as the generalized Fisher’s “fundamental theorem,” along with Wright’s adaptive landscape, are shown to emerge within QLE from the dynamics of the genotype distribution. This is followed by a discussion under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest.

Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

NASA Astrophysics Data System (ADS)

Abe, Sumiyoshi

2014-11-01

The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

A Categorization of Dynamic Analyzers

NASA Technical Reports Server (NTRS)

Lujan, Michelle R.

1997-01-01

Program analysis techniques and tools are essential to the development process because of the support they provide in detecting errors and deficiencies at different phases of development. The types of information rendered through analysis includes the following: statistical measurements of code, type checks, dataflow analysis, consistency checks, test data,verification of code, and debugging information. Analyzers can be broken into two major categories: dynamic and static. Static analyzers examine programs with respect to syntax errors and structural properties., This includes gathering statistical information on program content, such as the number of lines of executable code, source lines. and cyclomatic complexity. In addition, static analyzers provide the ability to check for the consistency of programs with respect to variables. Dynamic analyzers in contrast are dependent on input and the execution of a program providing the ability to find errors that cannot be detected through the use of static analysis alone. Dynamic analysis provides information on the behavior of a program rather than on the syntax. Both types of analysis detect errors in a program, but dynamic analyzers accomplish this through run-time behavior. This paper focuses on the following broad classification of dynamic analyzers: 1) Metrics; 2) Models; and 3) Monitors. Metrics are those analyzers that provide measurement. The next category, models, captures those analyzers that present the state of the program to the user at specified points in time. The last category, monitors, checks specified code based on some criteria. The paper discusses each classification and the techniques that are included under them. In addition, the role of each technique in the software life cycle is discussed. Familiarization with the tools that measure, model and monitor programs provides a framework for understanding the program's dynamic behavior from different, perspectives through analysis of the input

Predictors of post-partum damage accrual in systemic lupus erythematosus: data from LUMINA, a multiethnic US cohort (XXXVIII).

PubMed

Andrade, R M; McGwin, G; Alarcón, G S; Sanchez, M L; Bertoli, A M; Fernández, M; Fessler, B J; Apte, M; Arango, A M; Bastian, H M; Vilá, L M; Reveille, J D

2006-11-01

To determine the impact of pregnancy on systemic lupus erythematosus (SLE) outcome. SLE patients, age >or=16 yrs, disease duration SDI]. Differences in these variables between the visit immediately prior to, and the first visit after, pregnancy and their relationship with pregnancy outcome were examined. Damage accrual due to pregnancy exposure was examined by a case-crossover design. Sixty-three SLE women from all ethnic groups were included. The mean (S.D.) age and disease duration at pregnancy outcome were 27.6 (6.5) yrs and 18.3 (22.5) months, respectively. Adverse pregnancy outcomes occurred in 76.2% women. The SLAM-R and SDI scores were statistically different after pregnancy (P = 0.050 and P < 0.001, respectively); the SDI score was independent of pregnancy outcome but strongly associated with pregnancy duration (P = 0.006), disease activity (P = 0.001), damage prior to pregnancy (P < 0.001) and total disease duration (P = 0.039) by multivariable analyses. Exposure to pregnancy itself did not impact on damage accrual in the case-crossover analyses of 142 patients (17 pregnancy exposures) (OR = 1.25; 95% CI 0.336-4.655; P = 0.480). Pregnancy duration, total disease duration, disease activity and damage immediately prior to pregnancy decisively impact on damage accrual after pregnancy in patients with SLE.

Evolution of disease burden over five years in a multicenter inception systemic lupus erythematosus cohort.

PubMed

Urowitz, M B; Gladman, D D; Ibañez, D; Fortin, P R; Bae, S C; Gordon, C; Clarke, A; Bernatsky, S; Hanly, J G; Isenberg, D; Rahman, A; Sanchez-Guerrero, J; Wallace, D J; Ginzler, E; Alarcón, G S; Merrill, J T; Bruce, I N; Sturfelt, G; Nived, O; Steinsson, K; Khamashta, M; Petri, M; Manzi, S; Ramsey-Goldman, R; Dooley, M A; van Vollenhoven, R F; Ramos, M; Stoll, T; Zoma, A; Kalunian, K; Aranow, C

2012-01-01

We describe disease activity, damage, and the accrual of key autoantibodies in an inception systemic lupus erythematosus (SLE) cohort. The Systemic Lupus International Collaborating Clinics (SLICC) International Research Network, comprising 27 centers from 11 countries, has followed an inception cohort of SLE patients yearly according to a standardized protocol. Of these patients, 298 were followed for a minimum of 5 years and constitute the study population. Disease activity was assessed using the SLE Disease Activity Index 2000 (SLEDAI-2K) and damage was assessed using the SLICC/American College of Rheumatology Damage Index (SDI). Antinuclear antibody (ANA), anti-DNA, and anticardiolipin antibody (aCL) levels and lupus anticoagulant were assessed yearly. Descriptive statistics were generated and repeated-measures general linear models were used to evaluate SLEDAI-2K and SDI over time between whites and nonwhites. Of the 298 patients, 87% were women, 55% were white, 12% were African American, 14% were Asian, 16% were Hispanic, and 2% were categorized as "other." At enrollment, the mean age was 35.3 years, the mean SLEDAI-2K score was 5.9, and the mean disease duration was 5.5 months. Mean SLEDAI-2K scores decreased in the first year and then remained low. SLEDAI-2K scores were significantly lower at each year in whites compared to nonwhites. Mean SDI scores increased progressively over 5 years; there was no significant difference between whites and nonwhites. As expected, ANA positivity was high and anti-DNA positivity was relatively low at enrollment, and both increased over 5 years. Although lupus anticoagulant increased slightly over 5 years, aCL positivity did not. Disease activity in newly diagnosed patients decreases over their first 5 years, while damage increases. Antibody positivity ran variable courses over this period. Copyright © 2012 by the American College of Rheumatology.

Measurements of Transatmospheric Attenuation Statistics at the Microwave Frequencies : 15, 19, and 34 GHz

DOT National Transportation Integrated Search

1971-06-01

Attenuation statistics resulting from a twelve month observation program are presented. The sun is used as a source of microwave radiation. The dynamic range of atmospheric attenuation measurement capability is in excess of 30 dB. Solar radiation cha...

Statistics Anxiety and Business Statistics: The International Student

ERIC Educational Resources Information Center

Bell, James A.

2008-01-01

Does the international student suffer from statistics anxiety? To investigate this, the Statistics Anxiety Rating Scale (STARS) was administered to sixty-six beginning statistics students, including twelve international students and fifty-four domestic students. Due to the small number of international students, nonparametric methods were used to…

A smoothed residual based goodness-of-fit statistic for nest-survival models

Treesearch

Rodney X. Sturdivant; Jay J. Rotella; Robin E. Russell

2008-01-01

Estimating nest success and identifying important factors related to nest-survival rates is an essential goal for many wildlife researchers interested in understanding avian population dynamics. Advances in statistical methods have led to a number of estimation methods and approaches to modeling this problem. Recently developed models allow researchers to include a...

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Statistical quantifiers of memory for an analysis of human brain and neuro-system diseases

NASA Astrophysics Data System (ADS)

Demin, S. A.; Yulmetyev, R. M.; Panischev, O. Yu.; Hänggi, Peter

2008-03-01

On the basis of a memory function formalism for correlation functions of time series we investigate statistical memory effects by the use of appropriate spectral and relaxation parameters of measured stochastic data for neuro-system diseases. In particular, we study the dynamics of the walk of a patient who suffers from Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and compare against the data of healthy people (CO - control group). We employ an analytical method which is able to characterize the stochastic properties of stride-to-stride variations of gait cycle timing. Our results allow us to estimate quantitatively a few human locomotion function abnormalities occurring in the human brain and in the central nervous system (CNS). Particularly, the patient's gait dynamics are characterized by an increased memory behavior together with sizable fluctuations as compared with the locomotion dynamics of healthy patients. Moreover, we complement our findings with peculiar features as detected in phase-space portraits and spectral characteristics for the different data sets (PD, HD, ALS and healthy people). The evaluation of statistical quantifiers of the memory function is shown to provide a useful toolkit which can be put to work to identify various abnormalities of locomotion dynamics. Moreover, it allows one to diagnose qualitatively and quantitatively serious brain and central nervous system diseases.

From Data to Semantic Information

NASA Astrophysics Data System (ADS)

Floridi, Luciano

2003-06-01

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information.

Prediction of surface distress using neural networks

NASA Astrophysics Data System (ADS)

Hamdi, Hadiwardoyo, Sigit P.; Correia, A. Gomes; Pereira, Paulo; Cortez, Paulo

2017-06-01

Road infrastructures contribute to a healthy economy throughout a sustainable distribution of goods and services. A road network requires appropriately programmed maintenance treatments in order to keep roads assets in good condition, providing maximum safety for road users under a cost-effective approach. Surface Distress is the key element to identify road condition and may be generated by many different factors. In this paper, a new approach is aimed to predict Surface Distress Index (SDI) values following a data-driven approach. Later this model will be accordingly applied by using data obtained from the Integrated Road Management System (IRMS) database. Artificial Neural Networks (ANNs) are used to predict SDI index using input variables related to the surface of distress, i.e., crack area and width, pothole, rutting, patching and depression. The achieved results show that ANN is able to predict SDI with high correlation factor (R2 = 0.996%). Moreover, a sensitivity analysis was applied to the ANN model, revealing the influence of the most relevant input parameters for SDI prediction, namely rutting (59.8%), crack width (29.9%) and crack area (5.0%), patching (3.0%), pothole (1.7%) and depression (0.3%).

Universal statistics of vortex tangles in three-dimensional random waves

NASA Astrophysics Data System (ADS)

Taylor, Alexander J.

2018-02-01

The tangled nodal lines (wave vortices) in random, three-dimensional wavefields are studied as an exemplar of a fractal loop soup. Their statistics are a three-dimensional counterpart to the characteristic random behaviour of nodal domains in quantum chaos, but in three dimensions the filaments can wind around one another to give distinctly different large scale behaviours. By tracing numerically the structure of the vortices, their conformations are shown to follow recent analytical predictions for random vortex tangles with periodic boundaries, where the local disorder of the model ‘averages out’ to produce large scale power law scaling relations whose universality classes do not depend on the local physics. These results explain previous numerical measurements in terms of an explicit effect of the periodic boundaries, where the statistics of the vortices are strongly affected by the large scale connectedness of the system even at arbitrarily high energies. The statistics are investigated primarily for static (monochromatic) wavefields, but the analytical results are further shown to directly describe the reconnection statistics of vortices evolving in certain dynamic systems, or occurring during random perturbations of the static configuration.

Common pitfalls in statistical analysis: Clinical versus statistical significance

PubMed Central

Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc

2015-01-01

In clinical research, study results, which are statistically significant are often interpreted as being clinically important. While statistical significance indicates the reliability of the study results, clinical significance reflects its impact on clinical practice. The third article in this series exploring pitfalls in statistical analysis clarifies the importance of differentiating between statistical significance and clinical significance. PMID:26229754

ONR Ocean Wave Dynamics Workshop

NASA Astrophysics Data System (ADS)

In anticipation of the start (in Fiscal Year 1988) of a new Office of Naval Research (ONR) Accelerated Research Initiative (ARI) on Ocean Surface Wave Dynamics, a workshop was held August 5-7, 1986, at Woods Hole, Mass., to discuss new ideas and directions of research. This new ARI on Ocean Surface Wave Dynamics is a 5-year effort that is organized by the ONR Physical Oceanography Program in cooperation with the ONR Fluid Mechanics Program and the Physical Oceanography Branch at the Naval Ocean Research and Development Activity (NORDA). The central theme is improvement of our understanding of the basic physics and dynamics of surface wave phenomena, with emphasis on the following areas: precise air-sea coupling mechanisms,dynamics of nonlinear wave-wave interaction under realistic environmental conditions,wave breaking and dissipation of energy,interaction between surface waves and upper ocean boundary layer dynamics, andsurface statistical and boundary layer coherent structures.

IUTAM Symposium on Statistical Energy Analysis, 8-11 July 1997, Programme

DTIC Science & Technology

1997-01-01

distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (Maximum200 words) This was the first international scientific gathering devoted...energy flow, continuum dynamics, vibrational energy, statistical energy analysis (SEA) 15. NUMBER OF PAGES 16. PRICE CODE INSECURITY... correlation v=V(ɘ ’• • determination of the correlation n^, =11^, (<?). When harmonic motion and time-average are considered, the following I

Linguistic Analysis of the Human Heartbeat Using Frequency and Rank Order Statistics

NASA Astrophysics Data System (ADS)

Yang, Albert C.-C.; Hseu, Shu-Shya; Yien, Huey-Wen; Goldberger, Ary L.; Peng, C.-K.

2003-03-01

Complex physiologic signals may carry unique dynamical signatures that are related to their underlying mechanisms. We present a method based on rank order statistics of symbolic sequences to investigate the profile of different types of physiologic dynamics. We apply this method to heart rate fluctuations, the output of a central physiologic control system. The method robustly discriminates patterns generated from healthy and pathologic states, as well as aging. Furthermore, we observe increased randomness in the heartbeat time series with physiologic aging and pathologic states and also uncover nonrandom patterns in the ventricular response to atrial fibrillation.

Dynamical interpretation of conditional patterns

NASA Technical Reports Server (NTRS)

Adrian, R. J.; Moser, R. D.; Moin, P.

1988-01-01

While great progress is being made in characterizing the 3-D structure of organized turbulent motions using conditional averaging analysis, there is a lack of theoretical guidance regarding the interpretation and utilization of such information. Questions concerning the significance of the structures, their contributions to various transport properties, and their dynamics cannot be answered without recourse to appropriate dynamical governing equations. One approach which addresses some of these questions uses the conditional fields as initial conditions and calculates their evolution from the Navier-Stokes equations, yielding valuable information about stability, growth, and longevity of the mean structure. To interpret statistical aspects of the structures, a different type of theory which deals with the structures in the context of their contributions to the statistics of the flow is needed. As a first step toward this end, an effort was made to integrate the structural information from the study of organized structures with a suitable statistical theory. This is done by stochastically estimating the two-point conditional averages that appear in the equation for the one-point probability density function, and relating the structures to the conditional stresses. Salient features of the estimates are identified, and the structure of the one-point estimates in channel flow is defined.

Image dynamic range test and evaluation of Gaofen-2 dual cameras

NASA Astrophysics Data System (ADS)

Zhang, Zhenhua; Gan, Fuping; Wei, Dandan

2015-12-01

In order to fully understand the dynamic range of Gaofen-2 satellite data and support the data processing, application and next satellites development, in this article, we evaluated the dynamic range by calculating some statistics such as maximum ,minimum, average and stand deviation of four images obtained at the same time by Gaofen-2 dual cameras in Beijing area; then the maximum ,minimum, average and stand deviation of each longitudinal overlap of PMS1,PMS2 were calculated respectively for the evaluation of each camera's dynamic range consistency; and these four statistics of each latitudinal overlap of PMS1,PMS2 were calculated respectively for the evaluation of the dynamic range consistency between PMS1 and PMS2 at last. The results suggest that there is a wide dynamic range of DN value in the image obtained by PMS1 and PMS2 which contains rich information of ground objects; in general, the consistency of dynamic range between the single camera images is in close agreement, but also a little difference, so do the dual cameras. The consistency of dynamic range between the single camera images is better than the dual cameras'.

Characterizing complex networks through statistics of Möbius transformations

NASA Astrophysics Data System (ADS)

Jaćimović, Vladimir; Crnkić, Aladin

2017-04-01

It is well-known now that dynamics of large populations of globally (all-to-all) coupled oscillators can be reduced to low-dimensional submanifolds (WS transformation and OA ansatz). Marvel et al. (2009) described an intriguing algebraic structure standing behind this reduction: oscillators evolve by the action of the group of Möbius transformations. Of course, dynamics in complex networks of coupled oscillators is highly complex and not reducible. Still, closer look unveils that even in complex networks some (possibly overlapping) groups of oscillators evolve by Möbius transformations. In this paper, we study properties of the network by identifying Möbius transformations in the dynamics of oscillators. This enables us to introduce some new (statistical) concepts that characterize the network. In particular, the notion of coherence of the network (or subnetwork) is proposed. This conceptual approach is meaningful for the broad class of networks, including those with time-delayed, noisy or mixed interactions. In this paper, several simple (random) graphs are studied illustrating the meaning of the concepts introduced in the paper.

Distinct polymer physics principles govern chromatin dynamics in mouse and Drosophila topological domains.

PubMed

Ea, Vuthy; Sexton, Tom; Gostan, Thierry; Herviou, Laurie; Baudement, Marie-Odile; Zhang, Yunzhe; Berlivet, Soizik; Le Lay-Taha, Marie-Noëlle; Cathala, Guy; Lesne, Annick; Victor, Jean-Marc; Fan, Yuhong; Cavalli, Giacomo; Forné, Thierry

2015-08-15

In higher eukaryotes, the genome is partitioned into large "Topologically Associating Domains" (TADs) in which the chromatin displays favoured long-range contacts. While a crumpled/fractal globule organization has received experimental supports at higher-order levels, the organization principles that govern chromatin dynamics within these TADs remain unclear. Using simple polymer models, we previously showed that, in mouse liver cells, gene-rich domains tend to adopt a statistical helix shape when no significant locus-specific interaction takes place. Here, we use data from diverse 3C-derived methods to explore chromatin dynamics within mouse and Drosophila TADs. In mouse Embryonic Stem Cells (mESC), that possess large TADs (median size of 840 kb), we show that the statistical helix model, but not globule models, is relevant not only in gene-rich TADs, but also in gene-poor and gene-desert TADs. Interestingly, this statistical helix organization is considerably relaxed in mESC compared to liver cells, indicating that the impact of the constraints responsible for this organization is weaker in pluripotent cells. Finally, depletion of histone H1 in mESC alters local chromatin flexibility but not the statistical helix organization. In Drosophila, which possesses TADs of smaller sizes (median size of 70 kb), we show that, while chromatin compaction and flexibility are finely tuned according to the epigenetic landscape, chromatin dynamics within TADs is generally compatible with an unconstrained polymer configuration. Models issued from polymer physics can accurately describe the organization principles governing chromatin dynamics in both mouse and Drosophila TADs. However, constraints applied on this dynamics within mammalian TADs have a peculiar impact resulting in a statistical helix organization.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics.

PubMed

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-10-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

PubMed Central

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-01-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation. PMID:27699416

A general science-based framework for dynamical spatio-temporal models

USGS Publications Warehouse

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

Assessment of contribution of Australia's energy production to CO2 emissions and environmental degradation using statistical dynamic approach.

PubMed

Sarkodie, Samuel Asumadu; Strezov, Vladimir

2018-10-15

Energy production remains the major emitter of atmospheric emissions, thus, in accordance with Australia's Emissions Projections by 2030, this study analyzed the impact of Australia's energy portfolio on environmental degradation and CO 2 emissions using locally compiled data on disaggregate energy production, energy imports and exports spanning from 1974 to 2013. This study employed the fully modified ordinary least squares, dynamic ordinary least squares, and canonical cointegrating regression estimators; statistically inspired modification of partial least squares regression analysis with a subsequent sustainability sensitivity analysis. The validity of the environmental Kuznets curve hypothesis proposes a paradigm shift from energy-intensive and carbon-intensive industries to less-energy-intensive and green energy industries and its related services, leading to a structural change in the economy. Thus, decoupling energy services provide better interpretation of the role of the energy sector portfolio in environmental degradation and CO 2 emissions assessment. The sensitivity analysis revealed that nonrenewable energy production above 10% and energy imports above 5% will dampen the goals for the 2030 emission reduction target. Increasing the share of renewable energy penetration in the energy portfolio decreases the level of CO 2 emissions, while increasing the share of non-renewable energy sources in the energy mix increases the level of atmospheric emissions, thus increasing climate change and their impacts. Copyright © 2018 Elsevier B.V. All rights reserved.

Statistical inference approach to structural reconstruction of complex networks from binary time series

NASA Astrophysics Data System (ADS)

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.

Statistical inference approach to structural reconstruction of complex networks from binary time series.

PubMed

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.