WorldWideScience

Sample records for significantly increase ensemble

  1. Gas revenue increasingly significant

    International Nuclear Information System (INIS)

    Megill, R.E.

    1991-01-01

    This paper briefly describes the wellhead prices of natural gas compared to crude oil over the past 70 years. Although natural gas prices have never reached price parity with crude oil, the relative value of a gas BTU has been increasing. It is one of the reasons that the total amount of money coming from natural gas wells is becoming more significant. From 1920 to 1955 the revenue at the wellhead for natural gas was only about 10% of the money received by producers. Most of the money needed for exploration, development, and production came from crude oil. At present, however, over 40% of the money from the upstream portion of the petroleum industry is from natural gas. As a result, in a few short years natural gas may become 50% of the money revenues generated from wellhead production facilities

  2. Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task

    Science.gov (United States)

    Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.

    2000-06-01

    When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.

  3. Transient Atmospheric Circulation Changes in a Grand ensemble of Idealized CO2 Increase Experiments

    Science.gov (United States)

    Karpechko, A.; Manzini, E.; Kornblueh, L.

    2017-12-01

    The yearly evolution with increasing forcing of the large-scale atmospheric circulation is examined in a 68-member ensemble of 1pctCO2 scenario experiments performed with the MPI-ESM model. Each member of the experiment ensemble is integrated for 155 years, from initial conditions taken from a 2000-yr long pre-industrial control climate experiment. The 1pctCO2 scenario experiments are conducted following the protocol of including as external forcing only a CO2 concentration increase at 1%/year, till quadrupling of CO2 concentrations. MPI-ESM is the Max-Planck-Institute Earth System Model (including coupling between the atmosphere, ocean and seaice). By averaging over the 68 members (ensemble mean), atmospheric variability is greatly reduced. Thus, it is possible to investigate the sensitivity to the climate state of the atmospheric response to CO2 doubling. Indicators of global change show the expected monotonic evolution with increasing CO2 and a weak dependence of the thermodynamical response to CO2 doubling on the climate state. The surface climate response of the atmospheric circulation, diagnosed for instance by the pressure at sea level, and the eddy-driven jet response show instead a marked dependence to the climate state, for the Northern winter season. We find that as the CO2 concentration increases above doubling, Northern winter trends in some indicators of atmospheric circulation changes decrease or even reverse, posing the question on what are the causes of this nonlinear behavior. The investigation of the role of stationary waves, the meridional overturning circulation, the decrease in Arctic sea ice and the stratospheric vortex points to the latter as a plausible cause of such nonlinear response.

  4. Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections

    DEFF Research Database (Denmark)

    Seaby, Lauren Paige; Refsgaard, J.C.; Sonnenborg, T.O.

    2013-01-01

    An ensemble of 11 regional climate model (RCM) projections are analysed for Denmark from a hydrological modelling inputs perspective. Two bias correction approaches are applied: a relatively simple monthly delta change (DC) method and a more complex daily distribution-based scaling (DBS) method...

  5. Sixteen-Day Bedrest Significantly Increases Plasma Colloid Osmotic Pressure

    Science.gov (United States)

    Hargens, Alan R.; Hsieh, S. T.; Murthy, G.; Ballard, R. E.; Convertino, V. A.; Wade, Charles E. (Technical Monitor)

    1994-01-01

    Upon exposure to microgravity, astronauts lose up to 10% of their total plasma volume, which may contribute to orthostatic intolerance after space flight. Because plasma colloid osmotic pressure (COP) is a primary factor maintaining plasma volume, our objective was to measure time course changes in COP during microgravity simulated by 6 deg. head-down tilt (HDT). Seven healthy male subjects (30-55 years of age) were placed in HDT for 16 days. For the purpose of another study, three of the seven subjects were chosen to exercise on a cycle ergometer on day 16. Blood samples were drawn immediately before bedrest on day 14 of bedrest, 18-24 hours following exercise while all subjects were still in HDT and 1 hour following bedrest termination. Plasma COP was measured in all 20 microliter EDTA-treated samples using an osmometer fitted with a PM 30 membrane. Data were analyzed with paired and unpaired t-tests. Plasma COP on day 14 of bedrest (29.9 +/- 0.69 mmHg) was significantly higher (p less than 0.005) than the control, pre-bedrest value (23.1 +/- 0.76 mmHg). At one hour of upright recovery after HDT, plasma COP remained significantly elevated (exercise: 26.9 +/- 0.87 mmHg; no exercise: 26.3 +/- 0.85 mmHg). Additionally, exercise had no significant effect on plasma COP 18-24 hours following exercise (exercise: 27.8 +/- 1.09 mmHg; no exercise: 27.1 +/- 0.78 mmHg). Our results demonstrate that plasma COP increases significantly with microgravity simulated by HDT. However, preliminary results indicate exercise during HDT does not significantly affect plasma COP.

  6. Significance in the increase of women psychiatrists in Korea.

    Science.gov (United States)

    Kim, Ha Kyoung; Kim, Soo In

    2008-01-01

    The number of female doctors has increased in Korea; 18.9% (13,083) of the total medical doctors registered (69,097) were women in 2006, compared to 13.6% (2,216) in 1975. The proportion of female doctors will jump up by 2010 considering that nearly 40% of the medical students are women as of today. This trend has had strong influence on the field of psychiatry; the percentage of women psychiatrists rose from 1.6 (6)% to 18% (453), from 1975 to 2006 and now women residents comprise 39% (206) of all. This is not only a reflection of a social phenomenon of the increase in professional women but also attributed to some specific characteristics of the psychiatry. Psychiatric practice may come more natural to women. While clinical activities of women psychiatrists are expanding, there are few women leaders and much less women are involving in academic activities in this field as yet. Though there is less sexual discrimination in the field of psychiatry, women psychiatrists are still having a lot of difficulties in balancing work and family matters. Many women psychiatrists also report they've ever felt an implied discrimination in their careers. In this study, we are to identify the characteristics of women psychiatrists and to explore the significance of the increase in women psychiatrists in Korea and the situation in which they are.

  7. Can the combined use of an ensemble based modelling approach and the analysis of measured meteorological trends lead to increased confidence in climate change impact assessments?

    Science.gov (United States)

    Gädeke, Anne; Koch, Hagen; Pohle, Ina; Grünewald, Uwe

    2014-05-01

    simulate a strong decrease in future long term annual precipitation, the dynamical DAs simulate a tendency towards increasing precipitation. The trend analysis suggests that precipitation has not changed significantly during the period 1961-2006. Therefore, the decrease simulated by the statistical DAs should be interpreted as a rather dry future projection. Concerning air temperature, measured and simulated trends agree on a positive trend. Also the uncertainty related to the hydrological model within the climate change modelling chain is comparably low when long-term averages are considered but increases significantly during extreme events. This proposed framework of combining an ensemble based modelling approach with measured trend analysis is a promising approach for regional stakeholders to gain more confidence into the final results of climate change impact assessments. However, climate change impact assessments will remain highly uncertain. Thus, flexible adaptation strategies need to be developed which should not only consider climate but also other aspects of global change.

  8. Increasing the statistical significance of entanglement detection in experiments.

    Science.gov (United States)

    Jungnitsch, Bastian; Niekamp, Sönke; Kleinmann, Matthias; Gühne, Otfried; Lu, He; Gao, Wei-Bo; Chen, Yu-Ao; Chen, Zeng-Bing; Pan, Jian-Wei

    2010-05-28

    Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. Experimentally, we observe this phenomenon in a four-photon experiment, testing the Mermin and Ardehali inequality for different levels of noise. Furthermore, we provide a way to develop entanglement tests with high statistical significance.

  9. Increasing the statistical significance of entanglement detection in experiments

    Energy Technology Data Exchange (ETDEWEB)

    Jungnitsch, Bastian; Niekamp, Soenke; Kleinmann, Matthias; Guehne, Otfried [Institut fuer Quantenoptik und Quanteninformation, Innsbruck (Austria); Lu, He; Gao, Wei-Bo; Chen, Zeng-Bing [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Chen, Yu-Ao; Pan, Jian-Wei [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Physikalisches Institut, Universitaet Heidelberg (Germany)

    2010-07-01

    Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. We show this to be the case for an error model in which the variance of an observable is interpreted as its error and for the standard error model in photonic experiments. Specifically, we demonstrate that the Mermin inequality yields a Bell test which is statistically more significant than the Ardehali inequality in the case of a photonic four-qubit state that is close to a GHZ state. Experimentally, we observe this phenomenon in a four-photon experiment, testing the above inequalities for different levels of noise.

  10. Ensemble Methods

    Science.gov (United States)

    Re, Matteo; Valentini, Giorgio

    2012-03-01

    Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been

  11. Entropy of network ensembles

    Science.gov (United States)

    Bianconi, Ginestra

    2009-03-01

    In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

  12. NYYD Ensemble

    Index Scriptorium Estoniae

    2002-01-01

    NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx

  13. Significant increase of Echinococcus multilocularis prevalencein foxes, but no increased predicted risk for humans

    NARCIS (Netherlands)

    Maas, M.; Dam-Deisz, W.D.C.; Roon, van A.M.; Takumi, K.; Giessen, van der J.W.B.

    2014-01-01

    The emergence of the zoonotic tapeworm Echinococcus multilocularis, causative agent ofalveolar echinococcosis (AE), poses a public health risk. A previously designed risk mapmodel predicted a spread of E. multilocularis and increasing numbers of alveolar echinococ-cosis patients in the province of

  14. Increasing vaginal progesterone gel supplementation after frozen-thawed embryo transfer significantly increases the delivery rate

    DEFF Research Database (Denmark)

    Alsbjerg, Birgit; Polyzos, Nikolaos P; Elbaek, Helle Olesen

    2013-01-01

    The aim of this study was to evaluate the reproductive outcome in patients receiving frozen-thawed embryo transfer before and after doubling of the vaginal progesterone gel supplementation. The study was a retrospective study performed in The Fertility Clinic, Skive Regional Hospital, Denmark....... A total of 346 infertility patients with oligoamenorrhoea undergoing frozen-thawed embryo transfer after priming with oestradiol and vaginal progesterone gel were included. The vaginal progesterone dose was changed from 90mg (Crinone) once a day to twice a day and the reproductive outcome during the two...... rate (8.7% versus 20.5%, respectively; P=0.002). Doubling of the vaginal progesterone gel supplementation during frozen-thawed embryo transfer cycles decreased the early pregnancy loss rate, resulting in a significantly higher delivery rate. This study evaluated the reproductive outcome of 346 women...

  15. AUC-Maximizing Ensembles through Metalearning.

    Science.gov (United States)

    LeDell, Erin; van der Laan, Mark J; Petersen, Maya

    2016-05-01

    Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

  16. Ensembl 2004.

    Science.gov (United States)

    Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

    2004-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

  17. Can the confidence in long range atmospheric transport models be increased? The pan European experience of ensemble

    International Nuclear Information System (INIS)

    Galmarini, S.; Bianconi, R.; Mikkelsen, T.

    2003-01-01

    Full text: In the unfortunate event of an accidental release of radioactive material to the environment, the first concern for early-phase emergency response is atmospheric dispersion. For this purpose, several countries worldwide use operational Long Range Atmospheric Transport (LRAT) models to produce predictions of the event evolution over the continental scale to determine whether, when and how the radioactive cloud is going to hit their country. While presenting the multi-model ensemble dispersion forecast system (ENSEMBLE), the paper seeks to answer the following questions: is atmospheric dispersion forecasting an important asset of the early-phase emergency response management?; Is there a 'Perfect Atmospheric Dispersion Model'?; Is there a way to make the results of dispersion models more reliable and trustworthy? Several activities conducted during the 1990's, sought to estimate quantitatively the capability of LRAT models to forecast the atmospheric dispersion of radionuclides in the atmosphere. The results obtained clearly demonstrated that: the predictions of the various operational LRAT models used worldwide do not systematically agree (mainly due to conceptual differences in model structure and differences in the meteorological forecasts used to simulate the dispersion); none of the models used in the various countries is better than others under all circumstances and therefore there is no objective indication that shows one or few models to be the 'perfect model/s'. Given the realistic scenario that an accident can take place any time, any national authority is however faced with the practical need of managing the emergency and therefore with the dilemma: 'shall one rely an a LRAT model or only an the now cast provided by a monitoring network?' and 'to what extent are a model predictions going to be deceptive in the decision making process?' Since it goes without saying that even a vague idea an the future evolution of a dispersion process is better

  18. Ensembl 2017

    OpenAIRE

    Aken, Bronwen L.; Achuthan, Premanand; Akanni, Wasiu; Amode, M. Ridwan; Bernsdorff, Friederike; Bhai, Jyothish; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Gil, Laurent; Gir?n, Carlos Garc?a; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.

    2016-01-01

    Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access ...

  19. Ensemble Sampling

    OpenAIRE

    Lu, Xiuyuan; Van Roy, Benjamin

    2017-01-01

    Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applica...

  20. Ensembl variation resources

    Directory of Open Access Journals (Sweden)

    Marin-Garcia Pablo

    2010-05-01

    Full Text Available Abstract Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.

  1. Big data integration shows Australian bush-fire frequency is increasing significantly.

    Science.gov (United States)

    Dutta, Ritaban; Das, Aruneema; Aryal, Jagannath

    2016-02-01

    Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data. In a 336 week data trial, we demonstrate that the model provides highly accurate bush-fire incidence hot-spot estimation (91% global accuracy) from the weekly climatic surfaces. Our analysis also indicates that Australian weekly bush-fire frequencies increased by 40% over the last 5 years, particularly during summer months, implicating a serious climatic shift.

  2. Significantly Increased Extreme Precipitation Expected in Europe and North America from Extratropical Storms

    Science.gov (United States)

    Hawcroft, M.; Hodges, K.; Walsh, E.; Zappa, G.

    2017-12-01

    For the Northern Hemisphere extratropics, changes in circulation are key to determining the impacts of climate warming. The mechanisms governing these circulation changes are complex, leading to the well documented uncertainty in projections of the future location of the mid-latitude storm tracks simulated by climate models. These storms are the primary source of precipitation for North America and Europe and generate many of the large-scale precipitation extremes associated with flooding and severe economic loss. Here, we show that in spite of the uncertainty in circulation changes, by analysing the behaviour of the storms themselves, we find entirely consistent and robust projections across an ensemble of climate models. In particular, we find that projections of change in the most intensely precipitating storms (above the present day 99th percentile) in the Northern Hemisphere are substantial and consistent across models, with large increases in the frequency of both summer (June-August, +226±68%) and winter (December-February, +186±34%) extreme storms by the end of the century. Regionally, both North America (summer +202±129%, winter +232±135%) and Europe (summer +390±148%, winter +318±114%) are projected to experience large increases in the frequency of intensely precipitating storms. These changes are thermodynamic and driven by surface warming, rather than by changes in the dynamical behaviour of the storms. Such changes in storm behaviour have the potential to have major impacts on society given intensely precipitating storms are responsible for many large-scale flooding events.

  3. The semantic similarity ensemble

    Directory of Open Access Journals (Sweden)

    Andrea Ballatore

    2013-12-01

    Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

  4. Continuous background light significantly increases flashing-light enhancement of photosynthesis and growth of microalgae.

    Science.gov (United States)

    Abu-Ghosh, Said; Fixler, Dror; Dubinsky, Zvy; Iluz, David

    2015-01-01

    Under specific conditions, flashing light enhances the photosynthesis rate in comparison to continuous illumination. Here we show that a combination of flashing light and continuous background light with the same integrated photon dose as continuous or flashing light alone can be used to significantly enhance photosynthesis and increase microalgae growth. To test this hypothesis, the green microalga Dunaliella salina was exposed to three different light regimes: continuous light, flashing light, and concomitant application of both. Algal growth was compared under three different integrated light quantities; low, intermediate, and moderately high. Under the combined light regime, there was a substantial increase in all algal growth parameters, with an enhanced photosynthesis rate, within 3days. Our strategy demonstrates a hitherto undescribed significant increase in photosynthesis and algal growth rates, which is beyond the increase by flashing light alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. St. John's wort significantly increased the systemic exposure and toxicity of methotrexate in rats

    International Nuclear Information System (INIS)

    Yang, Shih-Ying; Juang, Shin-Hun; Tsai, Shang-Yuan; Chao, Pei-Dawn Lee; Hou, Yu-Chi

    2012-01-01

    St. John's wort (SJW, Hypericum perforatum) is one of the popular nutraceuticals for treating depression. Methotrexate (MTX) is an immunosuppressant with narrow therapeutic window. This study investigated the effect of SJW on MTX pharmacokinetics in rats. Rats were orally given MTX alone and coadministered with 300 and 150 mg/kg of SJW, and 25 mg/kg of diclofenac, respectively. Blood was withdrawn at specific time points and serum MTX concentrations were assayed by a specific monoclonal fluorescence polarization immunoassay method. The results showed that 300 mg/kg of SJW significantly increased the AUC 0−t and C max of MTX by 163% and 60%, respectively, and 150 mg/kg of SJW significantly increased the AUC 0−t of MTX by 55%. In addition, diclofenac enhanced the C max of MTX by 110%. The mortality of rats treated with SJW was higher than that of controls. In conclusion, coadministration of SJW significantly increased the systemic exposure and toxicity of MTX. The combined use of MTX with SJW would need to be with caution. -- Highlights: ► St. John's wort significantly increased the AUC 0−t and C max of methotrexate. ► Coadministration of St. John's wort increased the exposure and toxicity of methotrexate. ► The combined use of methotrexate with St. John's wort will need to be with caution.

  6. Increased frequency of retinopathy of prematurity over the last decade and significant regional differences.

    Science.gov (United States)

    Holmström, Gerd; Tornqvist, Kristina; Al-Hawasi, Abbas; Nilsson, Åsa; Wallin, Agneta; Hellström, Ann

    2018-03-01

    Retinopathy of prematurity (ROP) causes childhood blindness globally in prematurely born infants. Although increased levels of oxygen supply lead to increased survival and reduced frequency of cerebral palsy, increased incidence of ROP is reported. With the help of a Swedish register for ROP, SWEDROP, national and regional incidences of ROP and frequencies of treatment were evaluated from 2008 to 2015 (n = 5734), as well as before and after targets of provided oxygen changed from 85-89% to 91-95% in 2014. Retinopathy of prematurity (ROP) was found in 31.9% (1829/5734) of all infants with a gestational age (GA) of <31 weeks at birth and 5.7% of the infants (329/5734) had been treated for ROP. Analyses of the national data revealed an increased incidence of ROP during the 8-year study period (p = 0.003), but there was no significant increase in the frequency of treatment. There were significant differences between the seven health regions of Sweden, regarding both incidence of ROP and frequency of treatment (p < 0.001). Comparison of regional data before and after the new oxygen targets revealed a significant increase in treated ROP in one region [OR: 2.24 (CI: 1.11-4.49), p = 0.024] and a borderline increase in one other [OR: 3.08 (CI: 0.99-9.60), p = 0.052]. The Swedish national ROP register revealed an increased incidence of ROP during an 8-year period and significant regional differences regarding the incidence of ROP and frequency of treatment. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

  7. Forcings and feedbacks in the GeoMIP ensemble for a reduction in solar irradiance and increase in CO2

    Science.gov (United States)

    Huneeus, Nicolas; Boucher, Olivier; Alterskjær, Kari; Cole, Jason N. S.; Curry, Charles L.; Ji, Duoying; Jones, Andy; Kravitz, Ben; Kristjánsson, Jón Egill; Moore, John C.; Muri, Helene; Niemeier, Ulrike; Rasch, Phil; Robock, Alan; Singh, Balwinder; Schmidt, Hauke; Schulz, Michael; Tilmes, Simone; Watanabe, Shingo; Yoon, Jin-Ho

    2014-05-01

    The effective radiative forcings (including rapid adjustments) and feedbacks associated with an instantaneous quadrupling of the preindustrial CO2 concentration and a counterbalancing reduction of the solar constant are investigated in the context of the Geoengineering Model Intercomparison Project (GeoMIP). The forcing and feedback parameters of the net energy flux, as well as its different components at the top-of-atmosphere (TOA) and surface, were examined in 10 Earth System Models to better understand the impact of solar radiation management on the energy budget. In spite of their very different nature, the feedback parameter and its components at the TOA and surface are almost identical for the two forcing mechanisms, not only in the global mean but also in their geographical distributions. This conclusion holds for each of the individual models despite intermodel differences in how feedbacks affect the energy budget. This indicates that the climate sensitivity parameter is independent of the forcing (when measured as an effective radiative forcing). We also show the existence of a large contribution of the cloudy-sky component to the shortwave effective radiative forcing at the TOA suggesting rapid cloud adjustments to a change in solar irradiance. In addition, the models present significant diversity in the spatial distribution of the shortwave feedback parameter in cloudy regions, indicating persistent uncertainties in cloud feedback mechanisms.

  8. THE SMALL BUT SIGNIFICANT AND NONTRANSITORY INCREASE IN PRICES (SSNIP TEST

    Directory of Open Access Journals (Sweden)

    Liviana Niminet

    2008-12-01

    Full Text Available The Small but Significant Nontransitory Increase in Price Test was designed to define the relevant market by concepts of product, geographical area and time. This test, also called the ,,hypothetical monopolistic test” is the subject of many researches both economical and legal as it deals with economic concepts as well as with legally aspects.

  9. Evaluation of Significance of Diffusely Increased Bilateral Renal Uptake on Bone Scan

    Energy Technology Data Exchange (ETDEWEB)

    Sung, Mi Sook; Yang, Woo Jin; Byun, Jae Young; Park, Jung Mi; Shinn, Kyung Sub; Bahk, Yong Whee [Catholic University College of Medicine, Seoul (Korea, Republic of)

    1990-03-15

    Unexpected renal abnormality can be detected on bone scan using {sup 99m}Tc-MDP. The purpose of the study is to evaluate the diagnostic significance of diffusely increased bilateral renal uptake on bone scan. 1,500 bone scan were reviewed and 43 scans which showed diffusely increased bilateral renal uptake were selected for analysis. Laboratory findings for renal and liver function tests including routine urinalysis were reviewed in 43 patients. 26 of 43 case showed abnormality in urinalysis and renal function study. 20 of 43 cases showed abnormal liver function study and 3 of these cases were diagnosed as hepatorenal syndrome later. 13 of those 20 cases had liver cirrhosis with or without hepatoma. 12 of 43 cases showed abnormality both in renal and liver function studies. 2 of 43 cases showed diffusely increased bilateral renal uptake after chemotherapy for cancer but not on previous scans before chemotherapy. 2 of 43 cases showed hypercalcaemia and 8 of 43 cases had multifocal bone uptake due to metastasis or benign bone lesion. But the latter showed no hypercalcaemia at all. There was no significant correlation between increased renal uptake and MDP uptake in soft tissue other than kidneys. This study raised the possibility that the impaired liver and/or renal function may result in diffuse increase of bilateral renal uptake of MDP of unknown mechanism. It seems to need further study on this correlation.

  10. Evaluation of Significance of Diffusely Increased Bilateral Renal Uptake on Bone Scan

    International Nuclear Information System (INIS)

    Sung, Mi Sook; Yang, Woo Jin; Byun, Jae Young; Park, Jung Mi; Shinn, Kyung Sub; Bahk, Yong Whee

    1990-01-01

    Unexpected renal abnormality can be detected on bone scan using 99m Tc-MDP. The purpose of the study is to evaluate the diagnostic significance of diffusely increased bilateral renal uptake on bone scan. 1,500 bone scan were reviewed and 43 scans which showed diffusely increased bilateral renal uptake were selected for analysis. Laboratory findings for renal and liver function tests including routine urinalysis were reviewed in 43 patients. 26 of 43 case showed abnormality in urinalysis and renal function study. 20 of 43 cases showed abnormal liver function study and 3 of these cases were diagnosed as hepatorenal syndrome later. 13 of those 20 cases had liver cirrhosis with or without hepatoma. 12 of 43 cases showed abnormality both in renal and liver function studies. 2 of 43 cases showed diffusely increased bilateral renal uptake after chemotherapy for cancer but not on previous scans before chemotherapy. 2 of 43 cases showed hypercalcaemia and 8 of 43 cases had multifocal bone uptake due to metastasis or benign bone lesion. But the latter showed no hypercalcaemia at all. There was no significant correlation between increased renal uptake and MDP uptake in soft tissue other than kidneys. This study raised the possibility that the impaired liver and/or renal function may result in diffuse increase of bilateral renal uptake of MDP of unknown mechanism. It seems to need further study on this correlation.

  11. Ensemble methods for handwritten digit recognition

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Liisberg, Christian; Salamon, P.

    1992-01-01

    Neural network ensembles are applied to handwritten digit recognition. The individual networks of the ensemble are combinations of sparse look-up tables (LUTs) with random receptive fields. It is shown that the consensus of a group of networks outperforms the best individual of the ensemble....... It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...... by optimizing the receptive fields. It is concluded that it is possible to improve performance significantly by introducing moderate-size ensembles; in particular, a 20-25% improvement has been found. The ensemble random LUTs, when trained on a medium-size database, reach a performance (without rejects) of 94...

  12. Introducing extra NADPH consumption ability significantly increases the photosynthetic efficiency and biomass production of cyanobacteria.

    Science.gov (United States)

    Zhou, Jie; Zhang, Fuliang; Meng, Hengkai; Zhang, Yanping; Li, Yin

    2016-11-01

    Increasing photosynthetic efficiency is crucial to increasing biomass production to meet the growing demands for food and energy. Previous theoretical arithmetic analysis suggests that the light reactions and dark reactions are imperfectly coupled due to shortage of ATP supply, or accumulation of NADPH. Here we hypothesized that solely increasing NADPH consumption might improve the coupling of light reactions and dark reactions, thereby increasing the photosynthetic efficiency and biomass production. To test this hypothesis, an NADPH consumption pathway was constructed in cyanobacterium Synechocystis sp. PCC 6803. The resulting extra NADPH-consuming mutant grew much faster and achieved a higher biomass concentration. Analyses of photosynthesis characteristics showed the activities of photosystem II and photosystem I and the light saturation point of the NADPH-consuming mutant all significantly increased. Thus, we demonstrated that introducing extra NADPH consumption ability is a promising strategy to increase photosynthetic efficiency and to enable utilization of high-intensity lights. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  13. Hydrologic effects of large southwestern USA wildfires significantly increase regional water supply: fact or fiction?

    Science.gov (United States)

    Wine, M. L.; Cadol, D.

    2016-08-01

    In recent years climate change and historic fire suppression have increased the frequency of large wildfires in the southwestern USA, motivating study of the hydrological consequences of these wildfires at point and watershed scales, typically over short periods of time. These studies have revealed that reduced soil infiltration capacity and reduced transpiration due to tree canopy combustion increase streamflow at the watershed scale. However, the degree to which these local increases in runoff propagate to larger scales—relevant to urban and agricultural water supply—remains largely unknown, particularly in semi-arid mountainous watersheds co-dominated by winter snowmelt and the North American monsoon. To address this question, we selected three New Mexico watersheds—the Jemez (1223 km2), Mogollon (191 km2), and Gila (4807 km2)—that together have been affected by over 100 wildfires since 1982. We then applied climate-driven linear models to test for effects of fire on streamflow metrics after controlling for climatic variability. Here we show that, after controlling for climatic and snowpack variability, significantly more streamflow discharged from the Gila watershed for three to five years following wildfires, consistent with increased regional water yield due to enhanced infiltration-excess overland flow and groundwater recharge at the large watershed scale. In contrast, we observed no such increase in discharge from the Jemez watershed following wildfires. Fire regimes represent a key difference between the contrasting responses of the Jemez and Gila watersheds with the latter experiencing more frequent wildfires, many caused by lightning strikes. While hydrologic dynamics at the scale of large watersheds were previously thought to be climatically dominated, these results suggest that if one fifth or more of a large watershed has been burned in the previous three to five years, significant increases in water yield can be expected.

  14. Breast-cancer-associated metastasis is significantly increased in a model of autoimmune arthritis.

    Science.gov (United States)

    Das Roy, Lopamudra; Pathangey, Latha B; Tinder, Teresa L; Schettini, Jorge L; Gruber, Helen E; Mukherjee, Pinku

    2009-01-01

    Sites of chronic inflammation are often associated with the establishment and growth of various malignancies including breast cancer. A common inflammatory condition in humans is autoimmune arthritis (AA) that causes inflammation and deformity of the joints. Other systemic effects associated with arthritis include increased cellular infiltration and inflammation of the lungs. Several studies have reported statistically significant risk ratios between AA and breast cancer. Despite this knowledge, available for a decade, it has never been questioned if the site of chronic inflammation linked to AA creates a milieu that attracts tumor cells to home and grow in the inflamed bones and lungs which are frequent sites of breast cancer metastasis. To determine if chronic inflammation induced by autoimmune arthritis contributes to increased breast cancer-associated metastasis, we generated mammary gland tumors in SKG mice that were genetically prone to develop AA. Two breast cancer cell lines, one highly metastatic (4T1) and the other non-metastatic (TUBO) were used to generate the tumors in the mammary fat pad. Lung and bone metastasis and the associated inflammatory milieu were evaluated in the arthritic versus the non-arthritic mice. We report a three-fold increase in lung metastasis and a significant increase in the incidence of bone metastasis in the pro-arthritic and arthritic mice compared to non-arthritic control mice. We also report that the metastatic breast cancer cells augment the severity of arthritis resulting in a vicious cycle that increases both bone destruction and metastasis. Enhanced neutrophilic and granulocytic infiltration in lungs and bone of the pro-arthritic and arthritic mice and subsequent increase in circulating levels of proinflammatory cytokines, such as macrophage colony stimulating factor (M-CSF), interleukin-17 (IL-17), interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), and tumor necrosis factor-alpha (TNF-alpha) may contribute

  15. Breast cancer-associated metastasis is significantly increased in a model of autoimmune arthritis

    Science.gov (United States)

    Das Roy, Lopamudra; Pathangey, Latha B; Tinder, Teresa L; Schettini, Jorge L; Gruber, Helen E; Mukherjee, Pinku

    2009-01-01

    Introduction Sites of chronic inflammation are often associated with the establishment and growth of various malignancies including breast cancer. A common inflammatory condition in humans is autoimmune arthritis (AA) that causes inflammation and deformity of the joints. Other systemic effects associated with arthritis include increased cellular infiltration and inflammation of the lungs. Several studies have reported statistically significant risk ratios between AA and breast cancer. Despite this knowledge, available for a decade, it has never been questioned if the site of chronic inflammation linked to AA creates a milieu that attracts tumor cells to home and grow in the inflamed bones and lungs which are frequent sites of breast cancer metastasis. Methods To determine if chronic inflammation induced by autoimmune arthritis contributes to increased breast cancer-associated metastasis, we generated mammary gland tumors in SKG mice that were genetically prone to develop AA. Two breast cancer cell lines, one highly metastatic (4T1) and the other non-metastatic (TUBO) were used to generate the tumors in the mammary fat pad. Lung and bone metastasis and the associated inflammatory milieu were evaluated in the arthritic versus the non-arthritic mice. Results We report a three-fold increase in lung metastasis and a significant increase in the incidence of bone metastasis in the pro-arthritic and arthritic mice compared to non-arthritic control mice. We also report that the metastatic breast cancer cells augment the severity of arthritis resulting in a vicious cycle that increases both bone destruction and metastasis. Enhanced neutrophilic and granulocytic infiltration in lungs and bone of the pro-arthritic and arthritic mice and subsequent increase in circulating levels of proinflammatory cytokines, such as macrophage colony stimulating factor (M-CSF), interleukin-17 (IL-17), interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), and tumor necrosis factor

  16. A note on the multi model super ensemble technique for reducing forecast errors

    International Nuclear Information System (INIS)

    Kantha, L.; Carniel, S.; Sclavo, M.

    2008-01-01

    The multi model super ensemble (S E) technique has been used with considerable success to improve meteorological forecasts and is now being applied to ocean models. Although the technique has been shown to produce deterministic forecasts that can be superior to the individual models in the ensemble or a simple multi model ensemble forecast, there is a clear need to understand its strengths and limitations. This paper is an attempt to do so in simple, easily understood contexts. The results demonstrate that the S E forecast is almost always better than the simple ensemble forecast, the degree of improvement depending on the properties of the models in the ensemble. However, the skill of the S E forecast with respect to the true forecast depends on a number of factors, principal among which is the skill of the models in the ensemble. As can be expected, if the ensemble consists of models with poor skill, the S E forecast will also be poor, although better than the ensemble forecast. On the other hand, the inclusion of even a single skillful model in the ensemble increases the forecast skill significantly.

  17. 普通高校开设室内乐赏析课的教学实践探析%The Important Significance of the Chamber Music Appreciation Course and the Chamber Ensemble in the College

    Institute of Scientific and Technical Information of China (English)

    陶芳芝

    2015-01-01

    室内乐是16世纪末产生于意大利的器乐重奏曲形式。介绍了室内乐的起源、发展与各种演奏形式,结合普通高校的实际情况展开论述开设室内乐赏析课与组建室内乐团的一些概况与重要意义。同时,提出了创新室内乐赏析课的对策。%Chamber music is a form of classical music that is composed for a small group of instruments in sixteenth century in Italy.This paper introduces the history and different type performance forms of the chamber music.Moreover,the paper discusses the important significance of the chamber music appreciation course and the chamber ensemble in the college.

  18. Significant increase of surface ozone at a rural site, north of eastern China

    Directory of Open Access Journals (Sweden)

    Z. Ma

    2016-03-01

    Full Text Available Ozone pollution in eastern China has become one of the top environmental issues. Quantifying the temporal trend of surface ozone helps to assess the impacts of the anthropogenic precursor reductions and the likely effects of emission control strategies implemented. In this paper, ozone data collected at the Shangdianzi (SDZ regional atmospheric background station from 2003 to 2015 are presented and analyzed to obtain the variation in the trend of surface ozone in the most polluted region of China, north of eastern China or the North China Plain. A modified Kolmogorov–Zurbenko (KZ filter method was performed on the maximum daily average 8 h (MDA8 concentrations of ozone to separate the contributions of different factors from the variation of surface ozone and remove the influence of meteorological fluctuations on surface ozone. Results reveal that the short-term, seasonal and long-term components of ozone account for 36.4, 57.6 and 2.2 % of the total variance, respectively. The long-term trend indicates that the MDA8 has undergone a significant increase in the period of 2003–2015, with an average rate of 1.13 ± 0.01 ppb year−1 (R2 = 0.92. It is found that meteorological factors did not significantly influence the long-term variation of ozone and the increase may be completely attributed to changes in emissions. Furthermore, there is no significant correlation between the long-term O3 and NO2 trends. This study suggests that emission changes in VOCs might have played a more important role in the observed increase of surface ozone at SDZ.

  19. Application of Bioorganic Fertilizer Significantly Increased Apple Yields and Shaped Bacterial Community Structure in Orchard Soil.

    Science.gov (United States)

    Wang, Lei; Li, Jing; Yang, Fang; E, Yaoyao; Raza, Waseem; Huang, Qiwei; Shen, Qirong

    2017-02-01

    and Rhodospirillaceae, were found to be the significantly increased by the BOF addition and the genus Lysobacter may identify members of this group effective in biological control-based plant disease management and the members of family Rhodospirillaceae had an important role in fixing molecular nitrogen. These results strengthen the understanding of responses to the BOF and possible interactions within bacterial communities in soil that can be associated with disease suppression and the accumulation of carbon and nitrogen. The increase of apple yields after the application of BOF might be attributed to the fact that the application of BOF increased SOM, and soil total nitrogen, and changed the bacterial community by enriching Rhodospirillaceae, Alphaprotreobateria, and Proteobacteria.

  20. A multi-model ensemble approach to seabed mapping

    Science.gov (United States)

    Diesing, Markus; Stephens, David

    2015-06-01

    Seabed habitat mapping based on swath acoustic data and ground-truth samples is an emergent and active marine science discipline. Significant progress could be achieved by transferring techniques and approaches that have been successfully developed and employed in such fields as terrestrial land cover mapping. One such promising approach is the multiple classifier system, which aims at improving classification performance by combining the outputs of several classifiers. Here we present results of a multi-model ensemble applied to multibeam acoustic data covering more than 5000 km2 of seabed in the North Sea with the aim to derive accurate spatial predictions of seabed substrate. A suite of six machine learning classifiers (k-Nearest Neighbour, Support Vector Machine, Classification Tree, Random Forest, Neural Network and Naïve Bayes) was trained with ground-truth sample data classified into seabed substrate classes and their prediction accuracy was assessed with an independent set of samples. The three and five best performing models were combined to classifier ensembles. Both ensembles led to increased prediction accuracy as compared to the best performing single classifier. The improvements were however not statistically significant at the 5% level. Although the three-model ensemble did not perform significantly better than its individual component models, we noticed that the five-model ensemble did perform significantly better than three of the five component models. A classifier ensemble might therefore be an effective strategy to improve classification performance. Another advantage is the fact that the agreement in predicted substrate class between the individual models of the ensemble could be used as a measure of confidence. We propose a simple and spatially explicit measure of confidence that is based on model agreement and prediction accuracy.

  1. One stone, two birds: silica nanospheres significantly increase photocatalytic activity and colloidal stability of photocatalysts

    Science.gov (United States)

    Rasamani, Kowsalya D.; Foley, Jonathan J., IV; Sun, Yugang

    2018-03-01

    Silver-doped silver chloride [AgCl(Ag)] nanoparticles represent a unique class of visible-light-driven photocatalysts, in which the silver dopants introduce electron-abundant mid-gap energy levels to lower the bandgap of AgCl. However, free-standing AgCl(Ag) nanoparticles, particularly those with small sizes and large surface areas, exhibit low colloidal stability and low compositional stability upon exposure to light irradiation, leading to easy aggregation and conversion to metallic silver and thus a loss of photocatalytic activity. These problems could be eliminated by attaching the small AgCl(Ag) nanoparticles to the surfaces of spherical dielectric silica particles with submicrometer sizes. The high optical transparency in the visible spectral region (400-800 nm), colloidal stability, and chemical/electronic inertness displayed by the silica spheres make them ideal for supporting photocatalysts and significantly improving their stability. The spherical morphology of the dielectric silica particles can support light scattering resonances to generate significantly enhanced electric fields near the silica particle surfaces, on which the optical absorption cross-section of the AgCl(Ag) nanoparticles is dramatically increased to promote their photocatalytic activity. The hybrid silica/AgCl(Ag) structures exhibit superior photocatalytic activity and stability, suitable for supporting photocatalysis sustainably; for instance, their efficiency in the photocatalytic decomposition of methylene blue decreases by only ˜9% even after ten cycles of operation.

  2. Phytohormone supplementation significantly increases growth of Chlamydomonas reinhardtii cultivated for biodiesel production.

    Science.gov (United States)

    Park, Won-Kun; Yoo, Gursong; Moon, Myounghoon; Kim, Chul Woong; Choi, Yoon-E; Yang, Ji-Won

    2013-11-01

    Cultivation is the most expensive step in the production of biodiesel from microalgae, and substantial research has been devoted to developing more cost-effective cultivation methods. Plant hormones (phytohormones) are chemical messengers that regulate various aspects of growth and development and are typically active at very low concentrations. In this study, we investigated the effect of different phytohormones on microalgal growth and biodiesel production in Chlamydomonas reinhardtii and their potential to lower the overall cost of commercial biofuel production. The results indicated that all five of the tested phytohormones (indole-3-acetic acid, gibberellic acid, kinetin, 1-triacontanol, and abscisic acid) promoted microalgal growth. In particular, hormone treatment increased biomass production by 54 to 69 % relative to the control growth medium (Tris-acetate-phosphate, TAP). Phytohormone treatments also affected microalgal cell morphology but had no effect on the yields of fatty acid methyl esters (FAMEs) as a percent of biomass. We also tested the effect of these phytohormones on microalgal growth in nitrogen-limited media by supplementation in the early stationary phase. Maximum cell densities after addition of phytohormones were higher than in TAP medium, even when the nitrogen source was reduced to 40 % of that in TAP medium. Taken together, our results indicate that phytohormones significantly increased microalgal growth, particularly in nitrogen-limited media, and have potential for use in the development of efficient microalgal cultivation for biofuel production.

  3. [Significant increase in the colonisation of Staphylococcus aureus among medical students during their hospital practices].

    Science.gov (United States)

    Rodríguez-Avial, Carmen; Alvarez-Novoa, Andrea; Losa, Azucena; Picazo, Juan J

    2013-10-01

    Staphylococcus aureus is a pathogen of major concern. The emergence of methicillin-resistant S. aureus (MRSA) has increasingly complicated the therapeutic approach of hospital-acquired infections. Surveillance of MRSA and control measures must be implemented in different healthcare settings, including screening programs for carriers. Our first aim was to determine the prevalence of methicillin-susceptible S. aureus (MSSA) and MRSA nasal carriage in medical students from the Clínico San Carlos Hospital (Madrid). As the MRSA carrier rate in healthcare workers is higher than in the general population, we hypothesised that carrier rate could be increased during their clinical practice in their last three years. We performed an epidemiologic al study of the prevalence of S. aureus colonisation among a group of medical students, who were sampled in 2008 in their third-year, and in 2012 when this class was in its sixth year. We have found a significant increase in MSSA carriage, from 27% to 46%. There were no MRSA colonisations in the third-year, but one was found in the sixth-year group. The large majority of strains (89%) of strains were resistant to penicillin, and 27% to erythromycin and clindamycin. As 19 coagulase-negative Staphylococcus MR were also identified, a horizontal transfer of genes, such as mecA gene to S. aureus, could have occurred. Medical students are both, at risk for acquiring, and a potential source of nosocomial pathogens, mainly MSSA. Therefore, they should take special care for hygienic precautions, such as frequent and proper hand washing, while working in the hospital. Copyright © 2012 Elsevier España, S.L. All rights reserved.

  4. Skipping one or more dialysis sessions significantly increases mortality: measuring the impact of non-adherence

    Directory of Open Access Journals (Sweden)

    Eduardo Gottlieb

    2014-06-01

    Full Text Available Introduction: Non-adherence to the prescribed dialysis sessions frequency ranges from 2% to 50% of patients. The objective of this study was to evaluate the impact of detecting and measuring the non-adherence to the prescribed dialysis frequency and to determine the importance of a multidisciplinary approach with the aim of improving adherence. Methods: longitudinal cohort study including 8,164 prevalent hemodialysis patients in April 2010, with more than 90 days of treatment, in Fresenius Medical Care Argentina units that were monitored for 3 years. The survey evaluated: interruption of at least one dialysis session in a month or reduction at least 10 minutes of a dialysis session in a month, during 6 months prior to the survey. Relative mortality risks were evaluated among groups. Results: 648 patients (7.9% interrupted dialysis sessions: 320 (3.9% interrupted one session per month and 328 (4.01% interrupted more than one session per month. After 3 years monitoring, 349 patients (53.8 % remained active in hemodialysis and 299 were inactive due to different reasons: 206 deceased (31.8 %, 47 transfers or monitoring losses (7.25 %, 36 transplanted (5.55 %, 8 changes to PD modality (1.2% and 2 recovered their kidney function (0.3 %.Interrupting one session per month significantly increased the mortality risk comparing both groups (interrupters and non-interrupters: RR 2.65 (IC 95% 2.24 – 3.14. Interrupting more than one dialysis session also increased significantly mortality risk comparing to the non-interrupters: RR 2.8 (IC 95% 2.39 – 3.28. After 3 years monitoring, 41.6 % of interrupters at the beginning had improved their adherence through a multidisciplinary program of quality improvement. Conclusion: Global mortality was greater among patients who interrupted dialysis sessions. A considerable proportion of interrupter patients at the beginning modified their behavior through the implementation of a multidisciplinary program of quality

  5. Maternal undernutrition significantly impacts ovarian follicle number and increases ovarian oxidative stress in adult rat offspring.

    Directory of Open Access Journals (Sweden)

    Angelica B Bernal

    Full Text Available BACKGROUND: We have shown recently that maternal undernutrition (UN advanced female pubertal onset in a manner that is dependent upon the timing of UN. The long-term consequence of this accelerated puberty on ovarian function is unknown. Recent findings suggest that oxidative stress may be one mechanism whereby early life events impact on later physiological functioning. Therefore, using an established rodent model of maternal UN at critical windows of development, we examined maternal UN-induced changes in offspring ovarian function and determined whether these changes were underpinned by ovarian oxidative stress. METHODOLOGY/PRINCIPAL FINDINGS: Our study is the first to show that maternal UN significantly reduced primordial and secondary follicle number in offspring in a manner that was dependent upon the timing of maternal UN. Specifically, a reduction in these early stage follicles was observed in offspring born to mothers undernourished throughout both pregnancy and lactation. Additionally, antral follicle number was reduced in offspring born to all mothers that were UN regardless of whether the period of UN was restricted to pregnancy or lactation or both. These reductions were associated with decreased mRNA levels of genes critical for follicle maturation and ovulation. Increased ovarian protein carbonyls were observed in offspring born to mothers UN during pregnancy and/or lactation and this was associated with peroxiredoxin 3 hyperoxidation and reduced mRNA levels; suggesting compromised antioxidant defence. This was not observed in offspring of mothers UN during lactation alone. CONCLUSIONS: We propose that maternal UN, particularly at a time-point that includes pregnancy, results in reduced offspring ovarian follicle numbers and mRNA levels of regulatory genes and may be mediated by increased ovarian oxidative stress coupled with a decreased ability to repair the resultant oxidative damage. Together these data are suggestive of

  6. Free ammonia pre-treatment of secondary sludge significantly increases anaerobic methane production.

    Science.gov (United States)

    Wei, Wei; Zhou, Xu; Wang, Dongbo; Sun, Jing; Wang, Qilin

    2017-07-01

    Energy recovery in the form of methane from sludge/wastewater is restricted by the poor and slow biodegradability of secondary sludge. An innovative pre-treatment technology using free ammonia (FA, i.e. NH 3 ) was proposed in this study to increase anaerobic methane production. The solubilisation of secondary sludge was significantly increased after FA pre-treatment at up to 680 mg NH 3 -N/L for 1 day, under which the solubilisation (i.e. 0.4 mg SCOD/mg VS; SCOD: soluble chemical oxygen demand; VS: volatile solids) was >10 times higher than that without FA pre-treatment (i.e. 0.03 mg SCOD/mg VS). Biochemical methane potential assays showed that FA pre-treatment at above 250 mg NH 3 -N/L is effective in improving anaerobic methane production. The highest improvement in biochemical methane potential (B 0 ) and hydrolysis rate (k) was achieved at FA concentrations of 420-680 mg NH 3 -N/L, and was determined as approximately 22% (from 160 to 195 L CH 4 /kg VS added) and 140% (from 0.22 to 0.53 d -1 ) compared to the secondary sludge without pre-treatment. More analysis revealed that the FA induced improvement in B 0 and k could be attributed to the rapidly biodegradable substances rather than the slowly biodegradable substances. Economic and environmental analyses showed that the FA-based technology is economically favourable and environmentally friendly. Since this FA technology aims to use the wastewater treatment plants (WWTPs) waste (i.e. anaerobic digestion liquor) to enhance methane production from the WWTPs, it will set an example for the paradigm shift of the WWTPs from 'linear economy' to 'circular economy'. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Myriocin significantly increases the mortality of a non-mammalian model host during Candida pathogenesis.

    Directory of Open Access Journals (Sweden)

    Nadja Rodrigues de Melo

    Full Text Available Candida albicans is a major human pathogen whose treatment is challenging due to antifungal drug toxicity, drug resistance and paucity of antifungal agents available. Myrocin (MYR inhibits sphingosine synthesis, a precursor of sphingolipids, an important cell membrane and signaling molecule component. MYR also has dual immune suppressive and antifungal properties, potentially modulating mammalian immunity and simultaneously reducing fungal infection risk. Wax moth (Galleria mellonella larvae, alternatives to mice, were used to establish if MYR suppressed insect immunity and increased survival of C. albicans-infected insects. MYR effects were studied in vivo and in vitro, and compared alone and combined with those of approved antifungal drugs, fluconazole (FLC and amphotericin B (AMPH. Insect immune defenses failed to inhibit C. albicans with high mortalities. In insects pretreated with the drug followed by C. albicans inoculation, MYR+C. albicans significantly increased mortality to 93% from 67% with C. albicans alone 48 h post-infection whilst AMPH+C. albicans and FLC+C. albicans only showed 26% and 0% mortalities, respectively. MYR combinations with other antifungal drugs in vivo also enhanced larval mortalities, contrasting the synergistic antifungal effect of the MYR+AMPH combination in vitro. MYR treatment influenced immunity and stress management gene expression during C. albicans pathogenesis, modulating transcripts putatively associated with signal transduction/regulation of cytokines, I-kappaB kinase/NF-kappaB cascade, G-protein coupled receptor and inflammation. In contrast, all stress management gene expression was down-regulated in FLC and AMPH pretreated C. albicans-infected insects. Results are discussed with their implications for clinical use of MYR to treat sphingolipid-associated disorders.

  8. Significantly increased risk of carotid atherosclerosis with arsenic exposure and polymorphisms in arsenic metabolism genes

    International Nuclear Information System (INIS)

    Hsieh, Yi-Chen; Lien, Li-Ming; Chung, Wen-Ting; Hsieh, Fang-I; Hsieh, Pei-Fan; Wu, Meei-Maan; Tseng, Hung-Pin; Chiou, Hung-Yi; Chen, Chien-Jen

    2011-01-01

    Individual susceptibility to arsenic-induced carotid atherosclerosis might be associated with genetic variations in arsenic metabolism. The purpose of this study is to explore the interaction effect on risk of carotid atherosclerosis between arsenic exposure and risk genotypes of purine nucleoside phosphorylase (PNP), arsenic (+3) methyltransferase (As3MT), and glutathione S-transferase omega 1 (GSTO1) and omega 2 (GSTO2). A community-based case-control study was conducted in northeastern Taiwan to investigate the arsenic metabolic-related genetic susceptibility to carotid atherosclerosis. In total, 863 subjects, who had been genotyped and for whom the severity of carotid atherosclerosis had been determined, were included in the present study. Individual well water was collected and arsenic concentration determined using hydride generation combined with flame atomic absorption spectrometry. The result showed that a significant dose-response trend (P=0.04) of carotid atherosclerosis risk associated with increasing arsenic concentration. Non-significant association between genetic polymorphisms of PNP Gly51Ser, Pro57Pro, As3MT Met287Thr, GSTO1 Ala140Asp, and GSTO2 A-183G and the risk for development of carotid atherosclerosis were observed. However, the significant interaction effect on carotid atherosclerosis risk was found for arsenic exposure (>50 μg/l) and the haplotypes of PNP (p=0.0115). A marked elevated risk of carotid atherosclerosis was observed in subjects with arsenic exposure of >50 μg/l in drinking water and those who carried the PNP A-T haplotype and at least either of the As3MT risk polymorphism or GSTO risk haplotypes (OR, 6.43; 95% CI, 1.79-23.19). In conclusion, arsenic metabolic genes, PNP, As3MT, and GSTO, may exacerbate the formation of atherosclerosis in individuals with high levels of arsenic concentration in well water (>50 μg/l). - Highlights: →Arsenic metabolic genes might be associated with carotid atherosclerosis. → A case

  9. Significantly increased risk of carotid atherosclerosis with arsenic exposure and polymorphisms in arsenic metabolism genes

    Energy Technology Data Exchange (ETDEWEB)

    Hsieh, Yi-Chen [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Lien, Li-Ming [Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (China); School of Medicine, Taipei Medical University, Taipei, Taiwan (China); Department of Neurology, Shin Kong WHS Memorial Hospital, Taipei, Taiwan (China); Chung, Wen-Ting [Department of Neurology, Wanfang Hospital, Taipei Medical University, Taipei, Taiwan (China); Graduate Institute of Clinical Medicine, Taipei Medical University, Taipei, Taiwan (China); Hsieh, Fang-I; Hsieh, Pei-Fan [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Wu, Meei-Maan [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Graduate Institute of Basic Medicine, College of Medicine, Fu-Jen Catholic University, Taipei, Taiwan (China); Tseng, Hung-Pin [Department of Neurology, Lotung Poh-Ai Hospital, I-Lan, Taiwan (China); Chiou, Hung-Yi, E-mail: hychiou@tmu.edu.tw [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Chen, Chien-Jen [Genomics Research Center, Academia Sinica, Taipei, Taiwan (China)

    2011-08-15

    Individual susceptibility to arsenic-induced carotid atherosclerosis might be associated with genetic variations in arsenic metabolism. The purpose of this study is to explore the interaction effect on risk of carotid atherosclerosis between arsenic exposure and risk genotypes of purine nucleoside phosphorylase (PNP), arsenic (+3) methyltransferase (As3MT), and glutathione S-transferase omega 1 (GSTO1) and omega 2 (GSTO2). A community-based case-control study was conducted in northeastern Taiwan to investigate the arsenic metabolic-related genetic susceptibility to carotid atherosclerosis. In total, 863 subjects, who had been genotyped and for whom the severity of carotid atherosclerosis had been determined, were included in the present study. Individual well water was collected and arsenic concentration determined using hydride generation combined with flame atomic absorption spectrometry. The result showed that a significant dose-response trend (P=0.04) of carotid atherosclerosis risk associated with increasing arsenic concentration. Non-significant association between genetic polymorphisms of PNP Gly51Ser, Pro57Pro, As3MT Met287Thr, GSTO1 Ala140Asp, and GSTO2 A-183G and the risk for development of carotid atherosclerosis were observed. However, the significant interaction effect on carotid atherosclerosis risk was found for arsenic exposure (>50 {mu}g/l) and the haplotypes of PNP (p=0.0115). A marked elevated risk of carotid atherosclerosis was observed in subjects with arsenic exposure of >50 {mu}g/l in drinking water and those who carried the PNP A-T haplotype and at least either of the As3MT risk polymorphism or GSTO risk haplotypes (OR, 6.43; 95% CI, 1.79-23.19). In conclusion, arsenic metabolic genes, PNP, As3MT, and GSTO, may exacerbate the formation of atherosclerosis in individuals with high levels of arsenic concentration in well water (>50 {mu}g/l). - Highlights: {yields}Arsenic metabolic genes might be associated with carotid atherosclerosis. {yields

  10. Templated assembly of photoswitches significantly increases the energy-storage capacity of solar thermal fuels.

    Science.gov (United States)

    Kucharski, Timothy J; Ferralis, Nicola; Kolpak, Alexie M; Zheng, Jennie O; Nocera, Daniel G; Grossman, Jeffrey C

    2014-05-01

    Large-scale utilization of solar-energy resources will require considerable advances in energy-storage technologies to meet ever-increasing global energy demands. Other than liquid fuels, existing energy-storage materials do not provide the requisite combination of high energy density, high stability, easy handling, transportability and low cost. New hybrid solar thermal fuels, composed of photoswitchable molecules on rigid, low-mass nanostructures, transcend the physical limitations of molecular solar thermal fuels by introducing local sterically constrained environments in which interactions between chromophores can be tuned. We demonstrate this principle of a hybrid solar thermal fuel using azobenzene-functionalized carbon nanotubes. We show that, on composite bundling, the amount of energy stored per azobenzene more than doubles from 58 to 120 kJ mol(-1), and the material also maintains robust cyclability and stability. Our results demonstrate that solar thermal fuels composed of molecule-nanostructure hybrids can exhibit significantly enhanced energy-storage capabilities through the generation of template-enforced steric strain.

  11. Increased Mortality in Diabetic Foot Ulcer Patients: The Significance of Ulcer Type

    Science.gov (United States)

    Chammas, N. K.; Hill, R. L. R.; Edmonds, M. E.

    2016-01-01

    Diabetic foot ulcer (DFU) patients have a greater than twofold increase in mortality compared with nonulcerated diabetic patients. We investigated (a) cause of death in DFU patients, (b) age at death, and (c) relationship between cause of death and ulcer type. This was an eleven-year retrospective study on DFU patients who attended King's College Hospital Foot Clinic and subsequently died. A control group of nonulcerated diabetic patients was matched for age and type of diabetes mellitus. The cause of death was identified from death certificates (DC) and postmortem (PM) examinations. There were 243 DFU patient deaths during this period. Ischaemic heart disease (IHD) was the major cause of death in 62.5% on PM compared to 45.7% on DC. Mean age at death from IHD on PM was 5 years lower in DFU patients compared to controls (68.2 ± 8.7 years versus 73.1 ± 8.0 years, P = 0.015). IHD as a cause of death at PM was significantly linked to neuropathic foot ulcers (OR 3.064, 95% CI 1.003–9.366, and P = 0.049). Conclusions. IHD is the major cause of premature mortality in DFU patients with the neuropathic foot ulcer patients being at a greater risk. PMID:27213157

  12. Factors associated with an increased risk of vertebral fracture in monoclonal gammopathies of undetermined significance

    International Nuclear Information System (INIS)

    Piot, J M; Royer, M; Schmidt-Tanguy, A; Hoppé, E; Gardembas, M; Bourrée, T; Hunault, M; François, S; Boyer, F; Ifrah, N; Renier, G; Chevailler, A; Audran, M; Chappard, D; Libouban, H; Mabilleau, G; Legrand, E; Bouvard, B

    2015-01-01

    Monoclonal gammopathies of undetermined significance (MGUS) have been shown to be associated with an increased risk of fractures. This study describes prospectively the bone status of MGUS patients and determines the factors associated with vertebral fracture. We included prospectively 201 patients with MGUS, incidentally discovered, and with no known history of osteoporosis: mean age 66.6±12.5 years, 48.3% women, 51.7% immunoglobulin G (IgG), 33.3% IgM and 10.4% IgA. Light chain was kappa in 64.2% patients. All patients had spinal radiographs and bone mineral density measurement in addition to gammopathy assessment. At least one prevalent non-traumatic vertebral fracture was discovered in 18.4% patients and equally distributed between men and women. Fractured patients were older, had a lower bone density and had also more frequently a lambda light chain isotype. Compared with patients with κ light chain, the odds ratio of being fractured for patients with λ light chain was 4.32 (95% confidence interval 1.80–11.16; P=0.002). These results suggest a high prevalence of non-traumatic vertebral fractures in MGUS associated with lambda light chain isotype and not only explained by low bone density

  13. World Music Ensemble: Kulintang

    Science.gov (United States)

    Beegle, Amy C.

    2012-01-01

    As instrumental world music ensembles such as steel pan, mariachi, gamelan and West African drums are becoming more the norm than the exception in North American school music programs, there are other world music ensembles just starting to gain popularity in particular parts of the United States. The kulintang ensemble, a drum and gong ensemble…

  14. Measuring social interaction in music ensembles.

    Science.gov (United States)

    Volpe, Gualtiero; D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano

    2016-05-05

    Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances. © 2016 The Author(s).

  15. Constrained parameterisation of photosynthetic capacity causes significant increase of modelled tropical vegetation surface temperature

    Science.gov (United States)

    Kattge, J.; Knorr, W.; Raddatz, T.; Wirth, C.

    2009-04-01

    Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models whose representation in global scale simulations has been severely hampered by a lack of systematic analyses using a sufficiently broad database. Due to its coupling to stomatal conductance changes in the parameterisation of photosynthetic capacity may potentially influence transpiration rates and vegetation surface temperature. Here, we provide a constrained parameterisation of photosynthetic capacity for different plant functional types in the context of the photosynthesis model proposed by Farquhar et al. (1980), based on a comprehensive compilation of leaf photosynthesis rates and leaf nitrogen content. Mean values of photosynthetic capacity were implemented into the coupled climate-vegetation model ECHAM5/JSBACH and modelled gross primary production (GPP) is compared to a compilation of independent observations on stand scale. Compared to the current standard parameterisation the root-mean-squared difference between modelled and observed GPP is substantially reduced for almost all PFTs by the new parameterisation of photosynthetic capacity. We find a systematic depression of NUE (photosynthetic capacity divided by leaf nitrogen content) on certain tropical soils that are known to be deficient in phosphorus. Photosynthetic capacity of tropical trees derived by this study is substantially lower than standard estimates currently used in terrestrial biosphere models. This causes a decrease of modelled GPP while it significantly increases modelled tropical vegetation surface temperatures, up to 0.8°C. These results emphasise the importance of a constrained parameterisation of photosynthetic capacity not only for the carbon cycle, but also for the climate system.

  16. Significant yield increases from control of leaf diseases in maize - an overlooked problem?!

    DEFF Research Database (Denmark)

    Jørgensen, Lise Nistrup

    2012-01-01

    The area of maize has increased in several European countries in recent years. In Denmark, the area has increased from 10,000 ha in 1980 to 185,000 ha in 2011. Initially only silage maize was cultivated in Denmark, but in more recent years the area of grain maize has also increased. Farms growing...

  17. Quantum ensembles of quantum classifiers.

    Science.gov (United States)

    Schuld, Maria; Petruccione, Francesco

    2018-02-09

    Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

  18. Presence of gingivitis and periodontitis significantly increases hospital charges in patients undergoing heart valve surgery.

    Science.gov (United States)

    Allareddy, Veerasathpurush; Elangovan, Satheesh; Rampa, Sankeerth; Shin, Kyungsup; Nalliah, Romesh P; Allareddy, Veerajalandhar

    2015-01-01

    To examine the prevalence and impact of gingivitis and periodontitis in patients having heart valve surgical procedures. Nationwide Inpatient Sample for the years 2004-2010 was used. All patients who had heart valve surgical procedures were selected. Prevalence of gingivitis/periodontitis was examined in these patients. Impact of gingivitis/periodontitis on hospital charges, length of stay, and infectious complications was examined. 596,190 patients had heart valve surgical procedures. Gingivitis/periodontitis was present in 0.2 percent. Outcomes included: median hospital charges ($175,418 with gingivitis/ periodontitis versus $149,353 without gingivitis/periodontitis) and median length of stay (14 days with gingivitis/periodontitis versus 8 days without gingivitis/periodontitis). After adjusting for the effects of patient- and hospital-level confounding factors, hospital charges and length of stay were significantly higher (p gingivitis/periodontitis compared to their counterparts. Further, patients with gingivitis/periodontitis had significantly higher odds for having bacterial infections (OR = 3.41, 95% CI = 2.33-4.98, p gingivitis/periodontitis. Presence of gingivitis and periodontitis is associated with higher risk for bacterial infections and significant hospital resource utilization.

  19. Transabdominal cerclage: the significance of dual pathology and increased preterm delivery.

    Science.gov (United States)

    Farquharson, Roy G; Topping, Joanne; Quenby, Siobhan M

    2005-10-01

    Transabdominal cerclage is a recognised treatment for cervical weakness with a history of recurrent mid-trimester loss and a failed elective vaginal suture. The emergence of dual pathology, such as antiphospholipid syndrome and bacterial vaginosis, is associated with an increased risk of preterm delivery (RR 2.34, 95% CI 1.15-5.8). The first 40 cases are described where strict adherence to an investigation protocol and consistent treatment plan has been implemented.

  20. Clinical significance of increased lung/heart ratio in 210Tl stress myocardial image

    International Nuclear Information System (INIS)

    Liu Zaoli; Chang Fengqin; Zhang Fengge; Wang Xiaoyuan; Liu Liuhua

    1990-01-01

    230 cases were studied with 201 Tl stress image. The results showed that the lung/heart ratio closely correlated with the presence and severity of coronary heart disease (CHD). Among them, 18 cases (7.8%) showed significantly elevated lung/heart ratio (> 0.50). It was confirmed that all of the 18 cases have severe CHD with left ventricular insufficiency. The author emphasizes that measurement of the lung/heart ratio during 201 Tl stress myocardial image may be useful for the assessment of the severity, evalation of the left ventricular function and judgement of prognosis in CHD

  1. Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein.

    Directory of Open Access Journals (Sweden)

    Aditi Gupta

    2016-03-01

    Full Text Available Epistatic interactions between residues determine a protein's adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1 using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient condition that detects epistasis in most cases. We analyze the "fossils" of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing

  2. Corruption Significantly Increases the Capital Cost of Power Plants in Developing Contexts

    Directory of Open Access Journals (Sweden)

    Kumar Biswajit Debnath

    2018-03-01

    Full Text Available Emerging economies with rapidly growing population and energy demand, own some of the most expensive power plants in the world. We hypothesized that corruption has a relationship with the capital cost of power plants in developing countries such as Bangladesh. For this study, we analyzed the capital cost of 61 operational and planned power plants in Bangladesh. Initial comparison study revealed that the mean capital cost of a power plant in Bangladesh is twice than that of the global average. Then, the statistical analysis revealed a significant correlation between corruption and the cost of power plants, indicating that higher corruption leads to greater capital cost. The high up-front cost can be a significant burden on the economy, at present and in the future, as most are financed through international loans with extended repayment terms. There is, therefore, an urgent need for the review of the procurement and due diligence process of establishing power plants, and for the implementation of a more transparent system to mitigate adverse effects of corruption on megaprojects.

  3. Modern environmental health hazards: a public health issue of increasing significance in Africa.

    Science.gov (United States)

    Nweke, Onyemaechi C; Sanders, William H

    2009-06-01

    Traditional hazards such as poor sanitation currently account for most of Africa's environmentally related disease burden. However, with rapid development absent appropriate safeguards for environment and health, modern environmental health hazards (MEHHs) may emerge as critical contributors to the continent's disease burden. We review recent evidence of human exposure to and health effects from MEHHs, and their occurrence in environmental media and consumer products. Our purpose is to highlight the growing significance of these hazards as African countries experience urbanization, industrial growth, and development. We reviewed published epidemiologic, exposure, and environmental studies of chemical agents such as heavy metals and pesticides. The body of evidence demonstrates ongoing environmental releases of MEHHs and human exposures sometimes at toxicologically relevant levels. Several sources of MEHHs in environmental media have been identified, including natural resource mining and processing and automobile exhaust. Biomonitoring studies provided direct evidence of human exposure to metals such as mercury and lead and pesticides such as p,p'-dichlorodiphenyltrichloroethane (DDT) and organophosphates. Land and water resource pollution and industrial air toxics are areas of significant data gaps, notwithstanding the presence of several emitting sources. Unmitigated MEHH releases and human exposure have implications for Africa's disease burden. For Africans encumbered by conditions such as malnutrition that impair resilience to toxicologic challenges, the burden may be higher. A shift in public health policy toward accommodating the emerging diversity in Africa's environmental health issues is necessary to successfully alleviate the burden of avoidable ill health and premature death for all its communities now and in the future.

  4. Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

    Directory of Open Access Journals (Sweden)

    Sers Christine T

    2010-12-01

    Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.

  5. Increased Body Mass Index during Therapy for Childhood Acute Lymphoblastic Leukemia: A Significant and Underestimated Complication

    Directory of Open Access Journals (Sweden)

    Helen C. Atkinson

    2015-01-01

    Full Text Available Objective & Design. We undertook a retrospective review of children diagnosed with acute lymphoblastic leukemia (ALL and treated with modern COG protocols (n=80 to determine longitudinal changes in body mass index (BMI and the prevalence of obesity compared with a healthy reference population. Results. At diagnosis, the majority of patients (77.5% were in the healthy weight category. During treatment, increases in BMI z-scores were greater for females than males; the prevalence of obesity increased from 10.3% to 44.8% (P<0.004 for females but remained relatively unchanged for males (9.8% to 13.7%, P=0.7. Longitudinal analysis using linear mixed-effects identified associations between BMI z-scores and time-dependent interactions with sex (P=0.0005, disease risk (P<0.0001, age (P=0.0001, and BMI z-score (P<0.0001 at diagnosis and total dose of steroid during maintenance (P=0.01. Predicted mean BMI z-scores at the end of therapy were greater for females with standard risk ALL irrespective of age at diagnosis and for males younger than 4 years of age at diagnosis with standard risk ALL. Conclusion. Females treated on standard risk protocols and younger males may be at greatest risk of becoming obese during treatment for ALL. These subgroups may benefit from intervention strategies to manage BMI during treatment for ALL.

  6. Circulatory nucleosome levels are significantly increased in early and late-onset preeclampsia.

    Science.gov (United States)

    Zhong, Xiao Yan; Gebhardt, Stefan; Hillermann, Renate; Tofa, Kashefa Carelse; Holzgreve, Wolfgang; Hahn, Sinuhe

    2005-08-01

    Elevations in circulatory DNA, as measured by real-time PCR, have been observed in pregnancies with manifest preeclampsia. Recent reports have indicated that circulatory nucleosome levels are elevated in the periphery of cancer patients. We have now examined whether circulatory nucleosome levels are similarly elevated in cases with preeclampsia. Maternal plasma samples were prepared from 17 cases with early onset preeclampsia (34 weeks gestation) with 10 matched normotensive controls. Levels of circulatory nucleosomes were quantified by commercial ELISA (enzyme-linked immunosorbant assay). The level of circulatory nucleosomes was significantly elevated in both study preeclampsia groups, compared to the matched normotensive control group (p = 0.000 and p = 0.001, respectively). Our data suggests that preeclampsia is associated with the elevated presence of circulatory nucleosomes, and that this phenomenon occurs in both early- and late-onset forms of the disorder. Copyright 2005 John Wiley & Sons, Ltd.

  7. Bidirectional Modulation of Intrinsic Excitability in Rat Prelimbic Cortex Neuronal Ensembles and Non-Ensembles after Operant Learning.

    Science.gov (United States)

    Whitaker, Leslie R; Warren, Brandon L; Venniro, Marco; Harte, Tyler C; McPherson, Kylie B; Beidel, Jennifer; Bossert, Jennifer M; Shaham, Yavin; Bonci, Antonello; Hope, Bruce T

    2017-09-06

    Learned associations between environmental stimuli and rewards drive goal-directed learning and motivated behavior. These memories are thought to be encoded by alterations within specific patterns of sparsely distributed neurons called neuronal ensembles that are activated selectively by reward-predictive stimuli. Here, we use the Fos promoter to identify strongly activated neuronal ensembles in rat prelimbic cortex (PLC) and assess altered intrinsic excitability after 10 d of operant food self-administration training (1 h/d). First, we used the Daun02 inactivation procedure in male FosLacZ-transgenic rats to ablate selectively Fos-expressing PLC neurons that were active during operant food self-administration. Selective ablation of these neurons decreased food seeking. We then used male FosGFP-transgenic rats to assess selective alterations of intrinsic excitability in Fos-expressing neuronal ensembles (FosGFP + ) that were activated during food self-administration and compared these with alterations in less activated non-ensemble neurons (FosGFP - ). Using whole-cell recordings of layer V pyramidal neurons in an ex vivo brain slice preparation, we found that operant self-administration increased excitability of FosGFP + neurons and decreased excitability of FosGFP - neurons. Increased excitability of FosGFP + neurons was driven by increased steady-state input resistance. Decreased excitability of FosGFP - neurons was driven by increased contribution of small-conductance calcium-activated potassium (SK) channels. Injections of the specific SK channel antagonist apamin into PLC increased Fos expression but had no effect on food seeking. Overall, operant learning increased intrinsic excitability of PLC Fos-expressing neuronal ensembles that play a role in food seeking but decreased intrinsic excitability of Fos - non-ensembles. SIGNIFICANCE STATEMENT Prefrontal cortex activity plays a critical role in operant learning, but the underlying cellular mechanisms are

  8. TNFRSF14 aberrations in follicular lymphoma increase clinically significant allogeneic T-cell responses.

    Science.gov (United States)

    Kotsiou, Eleni; Okosun, Jessica; Besley, Caroline; Iqbal, Sameena; Matthews, Janet; Fitzgibbon, Jude; Gribben, John G; Davies, Jeffrey K

    2016-07-07

    Donor T-cell immune responses can eradicate lymphomas after allogeneic hematopoietic stem cell transplantation (AHSCT), but can also damage healthy tissues resulting in harmful graft-versus-host disease (GVHD). Next-generation sequencing has recently identified many new genetic lesions in follicular lymphoma (FL). One such gene, tumor necrosis factor receptor superfamily 14 (TNFRSF14), abnormal in 40% of FL patients, encodes the herpes virus entry mediator (HVEM) which limits T-cell activation via ligation of the B- and T-lymphocyte attenuator. As lymphoma B cells can act as antigen-presenting cells, we hypothesized that TNFRSF14 aberrations that reduce HVEM expression could alter the capacity of FL B cells to stimulate allogeneic T-cell responses and impact the outcome of AHSCT. In an in vitro model of alloreactivity, human lymphoma B cells with TNFRSF14 aberrations had reduced HVEM expression and greater alloantigen-presenting capacity than wild-type lymphoma B cells. The increased immune-stimulatory capacity of lymphoma B cells with TNFRSF14 aberrations had clinical relevance, associating with higher incidence of acute GVHD in patients undergoing AHSCT. FL patients with TNFRSF14 aberrations may benefit from more aggressive immunosuppression to reduce harmful GVHD after transplantation. Importantly, this study is the first to demonstrate the impact of an acquired genetic lesion on the capacity of tumor cells to stimulate allogeneic T-cell immune responses which may have wider consequences for adoptive immunotherapy strategies. © 2016 by The American Society of Hematology.

  9. Exposure to Tumescent Solution Significantly Increases Phosphorylation of Perilipin in Adipocytes.

    Science.gov (United States)

    Keskin, Ilknur; Sutcu, Mustafa; Eren, Hilal; Keskin, Mustafa

    2017-02-01

    Lidocaine and epinephrine could potentially decrease adipocyte viability, but these effects have not been substantiated. The phosphorylation status of perilipin in adipocytes may be predictive of cell viability. Perilipin coats lipid droplets and restricts access of lipases; phospho-perilipin lacks this protective function. The authors investigated the effects of tumescent solution containing lidocaine and epinephrine on the phosphorylation status of perilipin in adipocytes. In this in vitro study, lipoaspirates were collected before and after tumescence from 15 women who underwent abdominoplasty. Fat samples were fixed, sectioned, and stained for histologic and immunohistochemical analyses. Relative phosphorylation of perilipin was inferred from pixel intensities of immunostained adipocytes observed with confocal microscopy. For adipocytes collected before tumescent infiltration, 10.08% of total perilipin was phosphorylated. In contrast, 30.62% of total perilipin was phosphorylated for adipocytes collected from tumescent tissue (P < .01). The tumescent technique increases the relative phosphorylation of perilipin in adipocytes, making these cells more vulnerable to lipolysis. Tumescent solution applied for analgesia or hemostasis of the donor site should contain the lowest possible concentrations of lidocaine and epinephrine. LEVEL OF EVIDENCE 5. © 2016 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

  10. Significance of Increasing n-3 PUFA Content in Pork on Human Health.

    Science.gov (United States)

    Ma, Xianyong; Jiang, Zongyong; Lai, Chaoqiang

    2016-01-01

    Evidence for the health-promoting effects of food rich in n-3 polyunsaturated fatty acids (n-3 PUFA) is reviewed. Pork is an important meat source for humans. According to a report by the US Department of Agriculture ( http://www.ers.usda.gov/topics ), the pork consumption worldwide in 2011 was about 79.3 million tons, much higher than that of beef (48.2 million tons). Pork also contains high levels of unsaturated fatty acids relative to ruminant meats (Enser, M., Hallett, K., Hewett, B., Fursey, G. A. J. and Wood, J. D. (1996) . Fatty acid content and composition of English beef, lamb, and pork at retail. Meat Sci. 44:443-458). The available literature indicates that the levels of eicosatetraenoic and docosahexaenoic in pork may be increased by fish-derived or linseed products, the extent of which being dependent on the nature of the supplementation. Transgenic pigs and plants show promise with high content of n-3 PUFA and low ratio of n-6/n-3 fatty acids in their tissues. The approaches mentioned for decreasing n-6/n-3 ratios have both advantages and disadvantages. Selected articles are critically reviewed and summarized.

  11. Continues administration of Nano-PSO significantly increased survival of genetic CJD mice.

    Science.gov (United States)

    Binyamin, Orli; Keller, Guy; Frid, Kati; Larush, Liraz; Magdassi, Shlomo; Gabizon, Ruth

    2017-12-01

    We have shown previously that Nano-PSO, a nanodroplet formulation of pomegranate seed oil, delayed progression of neurodegeneration signs when administered for a designated period of time to TgMHu2ME199K mice, modeling for genetic prion disease. In the present work, we treated these mice with a self-emulsion formulation of Nano-PSO or a parallel Soybean oil formulation from their day of birth until a terminal disease stage. We found that long term Nano-PSO administration resulted in increased survival of TgMHu2ME199K lines by several months. Interestingly, initiation of treatment at day 1 had no clinical advantage over initiation at day 70, however cessation of treatment at 9months of age resulted in the rapid loss of the beneficial clinical effect. Pathological studies revealed that treatment with Nano-PSO resulted in the reduction of GAG accumulation and lipid oxidation, indicating a strong neuroprotective effect. Contrarily, the clinical effect of Nano-PSO did not correlate with reduction in the levels of disease related PrP, the main prion marker. We conclude that long term administration of Nano-PSO is safe and may be effective in the prevention/delay of onset of neurodegenerative conditions such as genetic CJD. Copyright © 2017. Published by Elsevier Inc.

  12. Elicitor Mixtures Significantly Increase Bioactive Compounds, Antioxidant Activity, and Quality Parameters in Sweet Bell Pepper

    Directory of Open Access Journals (Sweden)

    Lina Garcia-Mier

    2015-01-01

    Full Text Available Sweet bell peppers are greatly appreciated for their taste, color, pungency, and aroma. Additionally, they are good sources of bioactive compounds with antioxidant activity, which can be improved by the use of elicitors. Elicitors act as metabolite-inducing factors (MIF by mimic stress conditions. Since plants rarely experience a single stress condition one by one but are more likely to be exposed to simultaneous stresses, it is important to evaluate the effect of elicitors on plant secondary metabolism as mixtures. Jasmonic acid (JA, hydrogen peroxide (HP, and chitosan (CH were applied to fruits and plants of bell pepper as mixtures. Bioactive compounds, antioxidant activity, and quality parameters were evaluated. The assessed elicitor cocktail leads to an increase in the variables evaluated (P ≤ 0.05 when applied to mature fruits after harvest, whereas the lowest values were observed in the treatment applied to immature fruits. Therefore, the application of the elicitor cocktail to harvested mature fruits is recommended in order to improve bioactive compounds and the antioxidant activity of sweet bell peppers.

  13. Enhancing optical nonreciprocity by an atomic ensemble in two coupled cavities

    Science.gov (United States)

    Song, L. N.; Wang, Z. H.; Li, Yong

    2018-05-01

    We study the optical nonreciprocal propagation in an optical molecule of two coupled cavities with one of them interacting with a two-level atomic ensemble. The effect of increasing the number of atoms on the optical isolation ratio of the system is studied. We demonstrate that the significant nonlinearity supplied by the coupling of the atomic ensemble with the cavity leads to the realization of greatly-enhanced optical nonreciprocity compared with the case of single atom.

  14. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  15. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey

    2016-01-06

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  16. The Ensembl REST API: Ensembl Data for Any Language.

    Science.gov (United States)

    Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

    2015-01-01

    We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.

  17. A Simple Approach to Account for Climate Model Interdependence in Multi-Model Ensembles

    Science.gov (United States)

    Herger, N.; Abramowitz, G.; Angelil, O. M.; Knutti, R.; Sanderson, B.

    2016-12-01

    Multi-model ensembles are an indispensable tool for future climate projection and its uncertainty quantification. Ensembles containing multiple climate models generally have increased skill, consistency and reliability. Due to the lack of agreed-on alternatives, most scientists use the equally-weighted multi-model mean as they subscribe to model democracy ("one model, one vote").Different research groups are known to share sections of code, parameterizations in their model, literature, or even whole model components. Therefore, individual model runs do not represent truly independent estimates. Ignoring this dependence structure might lead to a false model consensus, wrong estimation of uncertainty and effective number of independent models.Here, we present a way to partially address this problem by selecting a subset of CMIP5 model runs so that its climatological mean minimizes the RMSE compared to a given observation product. Due to the cancelling out of errors, regional biases in the ensemble mean are reduced significantly.Using a model-as-truth experiment we demonstrate that those regional biases persist into the future and we are not fitting noise, thus providing improved observationally-constrained projections of the 21st century. The optimally selected ensemble shows significantly higher global mean surface temperature projections than the original ensemble, where all the model runs are considered. Moreover, the spread is decreased well beyond that expected from the decreased ensemble size.Several previous studies have recommended an ensemble selection approach based on performance ranking of the model runs. Here, we show that this approach can perform even worse than randomly selecting ensemble members and can thus be harmful. We suggest that accounting for interdependence in the ensemble selection process is a necessary step for robust projections for use in impact assessments, adaptation and mitigation of climate change.

  18. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

    Directory of Open Access Journals (Sweden)

    Jan D. Keller

    2008-12-01

    Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

  19. Musical ensembles in Ancient Mesapotamia

    NARCIS (Netherlands)

    Krispijn, T.J.H.; Dumbrill, R.; Finkel, I.

    2010-01-01

    Identification of musical instruments from ancient Mesopotamia by comparing musical ensembles attested in Sumerian and Akkadian texts with depicted ensembles. Lexicographical contributions to the Sumerian and Akkadian lexicon.

  20. Robustness of Ensemble Climate Projections Analyzed with Climate Signal Maps: Seasonal and Extreme Precipitation for Germany

    Directory of Open Access Journals (Sweden)

    Susanne Pfeifer

    2015-05-01

    Full Text Available Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP 4.5 vs. RCP8.5 vs. A1B, some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation.

  1. Ensemble Data Mining Methods

    Science.gov (United States)

    Oza, Nikunj C.

    2004-01-01

    Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

  2. Ensemble Data Mining Methods

    Data.gov (United States)

    National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...

  3. Demonstrating the value of larger ensembles in forecasting physical systems

    Directory of Open Access Journals (Sweden)

    Reason L. Machete

    2016-12-01

    Full Text Available Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying variations in the sensitivity of the model all the way to providing actionable probability forecasts of the future. Whatever the goal is, success depends on the properties of the ensemble, and there is a longstanding discussion in meteorology as to the size of initial condition ensemble most appropriate for Numerical Weather Prediction. In terms of resource allocation: how is one to divide finite computing resources between model complexity, ensemble size, data assimilation and other components of the forecast system. One wishes to avoid undersampling information available from the model's dynamics, yet one also wishes to use the highest fidelity model available. Arguably, a higher fidelity model can better exploit a larger ensemble; nevertheless it is often suggested that a relatively small ensemble, say ~16 members, is sufficient and that larger ensembles are not an effective investment of resources. This claim is shown to be dubious when the goal is probabilistic forecasting, even in settings where the forecast model is informative but imperfect. Probability forecasts for a ‘simple’ physical system are evaluated at different lead times; ensembles of up to 256 members are considered. The pure density estimation context (where ensemble members are drawn from the same underlying distribution as the target differs from the forecasting context, where one is given a high fidelity (but imperfect model. In the forecasting context, the information provided by additional members depends also on the fidelity of the model, the ensemble formation scheme (data assimilation, the ensemble interpretation and the nature of the observational noise. The effect of increasing the ensemble size is quantified by

  4. Statistical Analysis of Protein Ensembles

    Science.gov (United States)

    Máté, Gabriell; Heermann, Dieter

    2014-04-01

    As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

  5. Ensemble Machine Learning Methods and Applications

    CERN Document Server

    Ma, Yunqian

    2012-01-01

    It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

  6. Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

    Directory of Open Access Journals (Sweden)

    Nikola Simidjievski

    Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

  7. 'Lazy' quantum ensembles

    International Nuclear Information System (INIS)

    Parfionov, George; Zapatrin, Roman

    2006-01-01

    We compare different strategies aimed to prepare an ensemble with a given density matrix ρ. Preparing the ensemble of eigenstates of ρ with appropriate probabilities can be treated as 'generous' strategy: it provides maximal accessible information about the state. Another extremity is the so-called 'Scrooge' ensemble, which is mostly stingy in sharing the information. We introduce 'lazy' ensembles which require minimal effort to prepare the density matrix by selecting pure states with respect to completely random choice. We consider two parties, Alice and Bob, playing a kind of game. Bob wishes to guess which pure state is prepared by Alice. His null hypothesis, based on the lack of any information about Alice's intention, is that Alice prepares any pure state with equal probability. Then, the average quantum state measured by Bob turns out to be ρ, and he has to make a new hypothesis about Alice's intention solely based on the information that the observed density matrix is ρ. The arising 'lazy' ensemble is shown to be the alternative hypothesis which minimizes type I error

  8. Conductor gestures influence evaluations of ensemble performance.

    Science.gov (United States)

    Morrison, Steven J; Price, Harry E; Smedley, Eric M; Meals, Cory D

    2014-01-01

    Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor's gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the ensemble's articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble's performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

  9. Triglyceride content in remnant lipoproteins is significantly increased after food intake and is associated with plasma lipoprotein lipase.

    Science.gov (United States)

    Nakajima, Katsuyuki; Tokita, Yoshiharu; Sakamaki, Koji; Shimomura, Younosuke; Kobayashi, Junji; Kamachi, Keiko; Tanaka, Akira; Stanhope, Kimber L; Havel, Peter J; Wang, Tao; Machida, Tetsuo; Murakami, Masami

    2017-02-01

    Previous large population studies reported that non-fasting plasma triglyceride (TG) reflect a higher risk for cardiovascular disease than TG in the fasting plasma. This is suggestive of the presence of higher concentration of remnant lipoproteins (RLP) in postprandial plasma. TG and RLP-TG together with other lipids, lipoproteins and lipoprotein lipase (LPL) in both fasting and postprandial plasma were determined in generally healthy volunteers and in patients with coronary artery disease (CAD) after consuming a fat load or a more typical moderate meal. RLP-TG/TG ratio (concentration) and RLP-TG/RLP-C ratio (particle size) were significantly increased in the postprandial plasma of both healthy controls and CAD patients compared with those in fasting plasma. LPL/RLP-TG ratio demonstrated the interaction correlation between RLP concentration and LPL activity The increased RLP-TG after fat consumption contributed to approximately 90% of the increased plasma TG, while approximately 60% after a typical meal. Plasma LPL in postprandial plasma was not significantly altered after either type of meal. Concentrations of RLP-TG found in the TG along with its particle size are significantly increased in postprandial plasma compared with fasting plasma. Therefore, non-fasting TG determination better reflects the presence of higher RLP concentrations in plasma. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  10. St. John's wort significantly increased the systemic exposure and toxicity of methotrexate in rats

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Shih-Ying [Graduate Institute of Pharmaceutical Chemistry, China Medical University, Taichung, Taiwan (China); Juang, Shin-Hun [Graduate Institute of Pharmaceutical Chemistry, China Medical University, Taichung, Taiwan (China); Department of Medical Research, China Medical University Hospital, Taichung, Taiwan (China); Tsai, Shang-Yuan; Chao, Pei-Dawn Lee [School of Pharmacy, China Medical University, Taichung, Taiwan (China); Hou, Yu-Chi, E-mail: hou5133@gmail.com [School of Pharmacy, China Medical University, Taichung, Taiwan (China); Department of Medical Research, China Medical University Hospital, Taichung, Taiwan (China)

    2012-08-15

    St. John's wort (SJW, Hypericum perforatum) is one of the popular nutraceuticals for treating depression. Methotrexate (MTX) is an immunosuppressant with narrow therapeutic window. This study investigated the effect of SJW on MTX pharmacokinetics in rats. Rats were orally given MTX alone and coadministered with 300 and 150 mg/kg of SJW, and 25 mg/kg of diclofenac, respectively. Blood was withdrawn at specific time points and serum MTX concentrations were assayed by a specific monoclonal fluorescence polarization immunoassay method. The results showed that 300 mg/kg of SJW significantly increased the AUC{sub 0−t} and C{sub max} of MTX by 163% and 60%, respectively, and 150 mg/kg of SJW significantly increased the AUC{sub 0−t} of MTX by 55%. In addition, diclofenac enhanced the C{sub max} of MTX by 110%. The mortality of rats treated with SJW was higher than that of controls. In conclusion, coadministration of SJW significantly increased the systemic exposure and toxicity of MTX. The combined use of MTX with SJW would need to be with caution. -- Highlights: ► St. John's wort significantly increased the AUC{sub 0−t} and C{sub max} of methotrexate. ► Coadministration of St. John's wort increased the exposure and toxicity of methotrexate. ► The combined use of methotrexate with St. John's wort will need to be with caution.

  11. Significant social events and increasing use of life-sustaining treatment: trend analysis using extracorporeal membrane oxygenation as an example.

    Science.gov (United States)

    Chen, Yen-Yuan; Chen, Likwang; Huang, Tien-Shang; Ko, Wen-Je; Chu, Tzong-Shinn; Ni, Yen-Hsuan; Chang, Shan-Chwen

    2014-03-04

    Most studies have examined the outcomes of patients supported by extracorporeal membrane oxygenation as a life-sustaining treatment. It is unclear whether significant social events are associated with the use of life-sustaining treatment. This study aimed to compare the trend of extracorporeal membrane oxygenation use in Taiwan with that in the world, and to examine the influence of significant social events on the trend of extracorporeal membrane oxygenation use in Taiwan. Taiwan's extracorporeal membrane oxygenation uses from 2000 to 2009 were collected from National Health Insurance Research Dataset. The number of the worldwide extracorporeal membrane oxygenation cases was mainly estimated using Extracorporeal Life Support Registry Report International Summary July 2012. The trend of Taiwan's crude annual incidence rate of extracorporeal membrane oxygenation use was compared with that of the rest of the world. Each trend of extracorporeal membrane oxygenation use was examined using joinpoint regression. The measurement was the crude annual incidence rate of extracorporeal membrane oxygenation use. Each of the Taiwan's crude annual incidence rates was much higher than the worldwide one in the same year. Both the trends of Taiwan's and worldwide crude annual incidence rates have significantly increased since 2000. Joinpoint regression selected the model of the Taiwan's trend with one joinpoint in 2006 as the best-fitted model, implying that the significant social events in 2006 were significantly associated with the trend change of extracorporeal membrane oxygenation use following 2006. In addition, significantly social events highlighted by the media are more likely to be associated with the increase of extracorporeal membrane oxygenation use than being fully covered by National Health Insurance. Significant social events, such as a well-known person's successful extracorporeal membrane oxygenation use highlighted by the mass media, are associated with the use of

  12. Social marketing campaign significantly associated with increases in syphilis testing among gay and bisexual men in San Francisco.

    Science.gov (United States)

    Montoya, Jorge A; Kent, Charlotte K; Rotblatt, Harlan; McCright, Jacque; Kerndt, Peter R; Klausner, Jeffrey D

    2005-07-01

    Between 1999 and 2002, San Francisco experienced a sharp increase in early syphilis among gay and bisexual men. In response, the San Francisco Department of Public Health launched a social marketing campaign to increase testing for syphilis, and awareness and knowledge about syphilis among gay and bisexual men. A convenience sample of 244 gay and bisexual men (18-60 years of age) were surveyed to evaluate the effectiveness of the campaign. Respondents were interviewed to elicit unaided and aided awareness about the campaign, knowledge about syphilis, recent sexual behaviors, and syphilis testing behavior. After controlling for other potential confounders, unaided campaign awareness was a significant correlate of having a syphilis test in the last 6 months (odds ratio, 3.21; 95% confidence interval, 1.30-7.97) compared with no awareness of the campaign. A comparison of respondents aware of the campaign with those not aware also revealed significant increases in awareness and knowledge about syphilis. The Healthy Penis 2002 campaign achieved its primary objective of increasing syphilis testing, and awareness and knowledge about syphilis among gay and bisexual men in San Francisco.

  13. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon

    2016-01-08

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  14. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  15. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  16. On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

    Energy Technology Data Exchange (ETDEWEB)

    Webb, M.J.; Senior, C.A.; Sexton, D.M.H.; Ingram, W.J.; Williams, K.D.; Ringer, M.A. [Hadley Centre for Climate Prediction and Research, Met Office, Exeter (United Kingdom); McAvaney, B.J.; Colman, R. [Bureau of Meteorology Research Centre (BMRC), Melbourne (Australia); Soden, B.J. [University of Miami, Rosenstiel School for Marine and Atmospheric Science, Miami, FL (United States); Gudgel, R.; Knutson, T. [Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ (United States); Emori, S.; Ogura, T. [National Institute for Environmental Studies (NIES), Tsukuba (Japan); Tsushima, Y. [Japan Agency for Marine-Earth Science and Technology, Frontier Research Center for Global Change (FRCGC), Kanagawa (Japan); Andronova, N. [University of Michigan, Department of Atmospheric, Oceanic and Space Sciences, Ann Arbor, MI (United States); Li, B. [University of Illinois at Urbana-Champaign (UIUC), Department of Atmospheric Sciences, Urbana, IL (United States); Musat, I.; Bony, S. [Institut Pierre Simon Laplace (IPSL), Paris (France); Taylor, K.E. [Program for Climate Model Diagnosis and Intercomparison (PCMDI), Livermore, CA (United States)

    2006-07-15

    Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO{sub 2} doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level

  17. Significance and prognostic value of increased serum direct bilirubin level for lymph node metastasis in Chinese rectal cancer patients.

    Science.gov (United States)

    Gao, Chun; Fang, Long; Li, Jing-Tao; Zhao, Hong-Chuan

    2016-02-28

    To determine the significance of increased serum direct bilirubin level for lymph node metastasis (LNM) in Chinese rectal cancer patients, after those with known hepatobiliary and pancreatic diseases were excluded. A cohort of 469 patients, who were treated at the China-Japan Friendship Hospital, Ministry of Health (Beijing, China), in the period from January 2003 to June 2011, and with a pathological diagnosis of rectal adenocarcinoma, were recruited. They included 231 patients with LNM (49.3%) and 238 patients without LNM. Follow-up for these patients was taken through to December 31, 2012. The baseline serum direct bilirubin concentration was (median/inter-quartile range) 2.30/1.60-3.42 μmol/L. Univariate analysis showed that compared with patients without LNM, the patients with LNM had an increased level of direct bilirubin (2.50/1.70-3.42 vs 2.10/1.40-3.42, P = 0.025). Multivariate analysis showed that direct bilirubin was independently associated with LNM (OR = 1.602; 95%CI: 1.098-2.338, P = 0.015). Moreover, we found that: (1) serum direct bilirubin differs between male and female patients; a higher concentration was associated with poor tumor classification; (2) as the baseline serum direct bilirubin concentration increased, the percentage of patients with LNM increased; and (3) serum direct bilirubin was associated with the prognosis of rectal cancer patients and higher values indicated poor prognosis. Higher serum direct bilirubin concentration was associated with the increased risk of LNM and poor prognosis in our rectal cancers.

  18. Expression of a bacterial catalase in a strictly anaerobic methanogen significantly increases tolerance to hydrogen peroxide but not oxygen

    Science.gov (United States)

    Jennings, Matthew E.; Schaff, Cody W.; Horne, Alexandra J.; Lessner, Faith H.

    2014-01-01

    Haem-dependent catalase is an antioxidant enzyme that degrades H2O2, producing H2O and O2, and is common in aerobes. Catalase is present in some strictly anaerobic methane-producing archaea (methanogens), but the importance of catalase to the antioxidant system of methanogens is poorly understood. We report here that a survey of the sequenced genomes of methanogens revealed that the majority of species lack genes encoding catalase. Moreover, Methanosarcina acetivorans is a methanogen capable of synthesizing haem and encodes haem-dependent catalase in its genome; yet, Methanosarcina acetivorans cells lack detectable catalase activity. However, inducible expression of the haem-dependent catalase from Escherichia coli (EcKatG) in the chromosome of Methanosarcina acetivorans resulted in a 100-fold increase in the endogenous catalase activity compared with uninduced cells. The increased catalase activity conferred a 10-fold increase in the resistance of EcKatG-induced cells to H2O2 compared with uninduced cells. The EcKatG-induced cells were also able to grow when exposed to levels of H2O2 that inhibited or killed uninduced cells. However, despite the significant increase in catalase activity, growth studies revealed that EcKatG-induced cells did not exhibit increased tolerance to O2 compared with uninduced cells. These results support the lack of catalase in the majority of methanogens, since methanogens are more likely to encounter O2 rather than high concentrations of H2O2 in the natural environment. Catalase appears to be a minor component of the antioxidant system in methanogens, even those that are aerotolerant, including Methanosarcina acetivorans. Importantly, the experimental approach used here demonstrated the feasibility of engineering beneficial traits, such as H2O2 tolerance, in methanogens. PMID:24222618

  19. The adipokine leptin increases skeletal muscle mass and significantly alters skeletal muscle miRNA expression profile in aged mice

    International Nuclear Information System (INIS)

    Hamrick, Mark W.; Herberg, Samuel; Arounleut, Phonepasong; He, Hong-Zhi; Shiver, Austin; Qi, Rui-Qun; Zhou, Li; Isales, Carlos M.

    2010-01-01

    Research highlights: → Aging is associated with muscle atrophy and loss of muscle mass, known as the sarcopenia of aging. → We demonstrate that age-related muscle atrophy is associated with marked changes in miRNA expression in muscle. → Treating aged mice with the adipokine leptin significantly increased muscle mass and the expression of miRNAs involved in muscle repair. → Recombinant leptin therapy may therefore be a novel approach for treating age-related muscle atrophy. -- Abstract: Age-associated loss of muscle mass, or sarcopenia, contributes directly to frailty and an increased risk of falls and fractures among the elderly. Aged mice and elderly adults both show decreased muscle mass as well as relatively low levels of the fat-derived hormone leptin. Here we demonstrate that loss of muscle mass and myofiber size with aging in mice is associated with significant changes in the expression of specific miRNAs. Aging altered the expression of 57 miRNAs in mouse skeletal muscle, and many of these miRNAs are now reported to be associated specifically with age-related muscle atrophy. These include miR-221, previously identified in studies of myogenesis and muscle development as playing a role in the proliferation and terminal differentiation of myogenic precursors. We also treated aged mice with recombinant leptin, to determine whether leptin therapy could improve muscle mass and alter the miRNA expression profile of aging skeletal muscle. Leptin treatment significantly increased hindlimb muscle mass and extensor digitorum longus fiber size in aged mice. Furthermore, the expression of 37 miRNAs was altered in muscles of leptin-treated mice. In particular, leptin treatment increased the expression of miR-31 and miR-223, miRNAs known to be elevated during muscle regeneration and repair. These findings suggest that aging in skeletal muscle is associated with marked changes in the expression of specific miRNAs, and that nutrient-related hormones such as leptin

  20. The adipokine leptin increases skeletal muscle mass and significantly alters skeletal muscle miRNA expression profile in aged mice

    Energy Technology Data Exchange (ETDEWEB)

    Hamrick, Mark W., E-mail: mhamrick@mail.mcg.edu [Department of Cellular Biology and Anatomy, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); Department of Orthopaedic Surgery, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); Herberg, Samuel; Arounleut, Phonepasong [Department of Cellular Biology and Anatomy, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); Department of Orthopaedic Surgery, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); He, Hong-Zhi [Henry Ford Immunology Program, Henry Ford Health System, Detroit, MI (United States); Department of Dermatology, Henry Ford Health System, Detroit, MI (United States); Shiver, Austin [Department of Cellular Biology and Anatomy, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); Department of Orthopaedic Surgery, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); Qi, Rui-Qun [Henry Ford Immunology Program, Henry Ford Health System, Detroit, MI (United States); Department of Dermatology, Henry Ford Health System, Detroit, MI (United States); Zhou, Li [Henry Ford Immunology Program, Henry Ford Health System, Detroit, MI (United States); Department of Dermatology, Henry Ford Health System, Detroit, MI (United States); Department of Internal Medicine, Henry Ford Health System, Detroit, MI (United States); Isales, Carlos M. [Department of Cellular Biology and Anatomy, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); Department of Orthopaedic Surgery, Institute of Molecular Medicine and Genetics, Medical College of Georgia, Augusta, GA (United States); others, and

    2010-09-24

    Research highlights: {yields} Aging is associated with muscle atrophy and loss of muscle mass, known as the sarcopenia of aging. {yields} We demonstrate that age-related muscle atrophy is associated with marked changes in miRNA expression in muscle. {yields} Treating aged mice with the adipokine leptin significantly increased muscle mass and the expression of miRNAs involved in muscle repair. {yields} Recombinant leptin therapy may therefore be a novel approach for treating age-related muscle atrophy. -- Abstract: Age-associated loss of muscle mass, or sarcopenia, contributes directly to frailty and an increased risk of falls and fractures among the elderly. Aged mice and elderly adults both show decreased muscle mass as well as relatively low levels of the fat-derived hormone leptin. Here we demonstrate that loss of muscle mass and myofiber size with aging in mice is associated with significant changes in the expression of specific miRNAs. Aging altered the expression of 57 miRNAs in mouse skeletal muscle, and many of these miRNAs are now reported to be associated specifically with age-related muscle atrophy. These include miR-221, previously identified in studies of myogenesis and muscle development as playing a role in the proliferation and terminal differentiation of myogenic precursors. We also treated aged mice with recombinant leptin, to determine whether leptin therapy could improve muscle mass and alter the miRNA expression profile of aging skeletal muscle. Leptin treatment significantly increased hindlimb muscle mass and extensor digitorum longus fiber size in aged mice. Furthermore, the expression of 37 miRNAs was altered in muscles of leptin-treated mice. In particular, leptin treatment increased the expression of miR-31 and miR-223, miRNAs known to be elevated during muscle regeneration and repair. These findings suggest that aging in skeletal muscle is associated with marked changes in the expression of specific miRNAs, and that nutrient

  1. Prognostic significance of increased bone marrow microcirculation in newly diagnosed multiple myeloma: results of a prospective DCE-MRI study

    Energy Technology Data Exchange (ETDEWEB)

    Merz, Maximilian; Hillengass, Jens [Department of Radiology, German Cancer Research Center, Heidelberg (Germany); University of Heidelberg, Department of Hematology, Oncology and Rheumatology, Heidelberg (Germany); Moehler, Thomas M.; Ritsch, Judith; Delorme, Stefan [Department of Radiology, German Cancer Research Center, Heidelberg (Germany); Baeuerle, Tobias [University of Erlangen-Nuremberg, Department of Radiology, Erlangen (Germany); Zechmann, Christian M. [Rinecker Proton Therapy, Muenchen (Germany); Wagner, Barbara; Hose, Dirk [University of Heidelberg, Department of Hematology, Oncology and Rheumatology, Heidelberg (Germany); Jauch, Anna [University of Heidelberg, Institute of Human Genetics, Heidelberg (Germany); Kunz, Christina; Hielscher, Thomas [German Cancer Research Center, Department of Biostatistics, Heidelberg (Germany); Laue, Hendrik [Fraunhofer MEVIS, Bremen (Germany); Goldschmidt, Hartmut [University of Heidelberg, Department of Hematology, Oncology and Rheumatology, Heidelberg (Germany); National Center for Tumor Diseases, Heidelberg (Germany)

    2016-05-15

    Aim of this prospective study was to investigate prognostic significance of increased bone marrow microcirculation as detected by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for survival and local complications in patients with multiple myeloma (MM). We performed DCE-MRI of the lumbar spine in 131 patients with newly diagnosed MM and analysed data according to the Brix model to acquire amplitude A and exchange rate constant k{sub ep}. In 61 patients a second MRI performed after therapy was evaluated to assess changes in vertebral height and identify vertebral fractures. Correlation analysis revealed significant positive association between beta2-microglobulin as well as immunoparesis with DCE-MRI parameters A and k{sub ep}. Additionally, A was negatively correlated with haemoglobin levels and k{sub ep} was positively correlated with LDH levels. Higher baseline k{sub ep} values were associated with decreased vertebral height in a second MRI (P = 0.007) and A values were associated with new vertebral fractures in the lower lumbar spine (P = 0.03 for L4). Pre-existing lytic bone lesions or remission after therapy had no impact on the occurrence of vertebral fractures. Multivariate analysis revealed that amplitude A is an independent adverse risk factor for overall survival. DCE-MRI is a non-invasive tool with significance for systemic prognosis and vertebral complications. (orig.)

  2. Balance disorder and increased risk of falls in osteoporosis and kyphosis: significance of kyphotic posture and muscle strength.

    Science.gov (United States)

    Sinaki, Mehrsheed; Brey, Robert H; Hughes, Christine A; Larson, Dirk R; Kaufman, Kenton R

    2005-08-01

    This controlled trial was designed to investigate the influence of osteoporosis-related kyphosis (O-K) on falls. Twelve community-dwelling women with O-K (Cobb angle, 50-65 degrees measured from spine radiographs) and 13 healthy women serving as controls were enrolled. Mean age of the O-K group was 76 years (+/-5.1), height 158 cm (+/-5), and weight 61 kg (+/-7.9), and mean age of the control group was 71 years (+/-4.6), height 161 cm (+/-3.8), and weight 66 kg (+/-11.7). Quantitative isometric strength data were collected. Gait was monitored during unobstructed level walking and during stepping over an obstacle of four different heights randomly assigned (2.5%, 5%, 10%, and 15% of the subject's height). Balance was objectively assessed with computerized dynamic posturography consisting of the sensory organization test. Back extensor strength, grip strength, and all lower extremity muscle groups were significantly weaker in the O-K group than the control group (P controls for all conditions of unobstructed and obstructed level walking. Obstacle height had a significant effect on all center-of-mass variables. The O-K subjects had significantly greater balance abnormalities on computerized dynamic posturography than the control group (P =0.002). Data show that thoracic hyperkyphosis on a background of reduced muscle strength plays an important role in increasing body sway, gait unsteadiness, and risk of falls in osteoporosis.

  3. Neurite outgrowth is significantly increased by the simultaneous presentation of Schwann cells and moderate exogenous electric fields

    Science.gov (United States)

    Koppes, Abigail N.; Seggio, Angela M.; Thompson, Deanna M.

    2011-08-01

    Axonal extension is influenced by a variety of external guidance cues; therefore, the development and optimization of a multi-faceted approach is probably necessary to address the intricacy of functional regeneration following nerve injury. In this study, primary dissociated neonatal rat dorsal root ganglia neurons and Schwann cells were examined in response to an 8 h dc electrical stimulation (0-100 mV mm-1). Stimulated samples were then fixed immediately, immunostained, imaged and analyzed to determine Schwann cell orientation and characterize neurite outgrowth relative to electric field strength and direction. Results indicate that Schwann cells are viable following electrical stimulation with 10-100 mV mm-1, and retain a normal morphology relative to unstimulated cells; however, no directional bias is observed. Neurite outgrowth was significantly enhanced by twofold following exposure to either a 50 mV mm-1 electric field (EF) or co-culture with unstimulated Schwann cells by comparison to neurons cultured alone. Neurite outgrowth was further increased in the presence of simultaneously applied cues (Schwann cells + 50 mV mm-1 dc EF), exhibiting a 3.2-fold increase over unstimulated control neurons, and a 1.2-fold increase over either neurons cultured with unstimulated Schwann cells or the electrical stimulus alone. These results indicate that dc electric stimulation in combination with Schwann cells may provide synergistic guidance cues for improved axonal growth relevant to nerve injuries in the peripheral nervous system.

  4. The contribution of human agricultural activities to increasing evapotranspiration is significantly greater than climate change effect over Heihe agricultural region.

    Science.gov (United States)

    Zou, Minzhong; Niu, Jun; Kang, Shaozhong; Li, Xiaolin; Lu, Hongna

    2017-08-18

    Evapotranspiration (ET) is a major component linking the water, energy, and carbon cycles. Understanding changes in ET and the relative contribution rates of human activity and of climate change at the basin scale is important for sound water resources management. In this study, changes in ET in the Heihe agricultural region in northwest China during 1984-2014 were examined using remotely-sensed ET data with the Soil and Water Assessment Tool (SWAT). Correlation analysis identified the dominant factors that influence change in ET per unit area and those that influence change in total ET. Factor analysis identified the relative contribution rates of the dominant factors in each case. The results show that human activity, which includes factors for agronomy and irrigation, and climate change, including factors for precipitation and relative humidity, both contribute to increases in ET per unit area at rates of 60.93% and 28.01%, respectively. Human activity, including the same factors, and climate change, including factors for relative humidity and wind speed, contribute to increases in total ET at rates of 53.86% and 35.68%, respectively. Overall, in the Heihe agricultural region, the contribution of human agricultural activities to increased ET was significantly greater than that of climate change.

  5. Representing Color Ensembles.

    Science.gov (United States)

    Chetverikov, Andrey; Campana, Gianluca; Kristjánsson, Árni

    2017-10-01

    Colors are rarely uniform, yet little is known about how people represent color distributions. We introduce a new method for studying color ensembles based on intertrial learning in visual search. Participants looked for an oddly colored diamond among diamonds with colors taken from either uniform or Gaussian color distributions. On test trials, the targets had various distances in feature space from the mean of the preceding distractor color distribution. Targets on test trials therefore served as probes into probabilistic representations of distractor colors. Test-trial response times revealed a striking similarity between the physical distribution of colors and their internal representations. The results demonstrate that the visual system represents color ensembles in a more detailed way than previously thought, coding not only mean and variance but, most surprisingly, the actual shape (uniform or Gaussian) of the distribution of colors in the environment.

  6. Tailored Random Graph Ensembles

    International Nuclear Information System (INIS)

    Roberts, E S; Annibale, A; Coolen, A C C

    2013-01-01

    Tailored graph ensembles are a developing bridge between biological networks and statistical mechanics. The aim is to use this concept to generate a suite of rigorous tools that can be used to quantify and compare the topology of cellular signalling networks, such as protein-protein interaction networks and gene regulation networks. We calculate exact and explicit formulae for the leading orders in the system size of the Shannon entropies of random graph ensembles constrained with degree distribution and degree-degree correlation. We also construct an ergodic detailed balance Markov chain with non-trivial acceptance probabilities which converges to a strictly uniform measure and is based on edge swaps that conserve all degrees. The acceptance probabilities can be generalized to define Markov chains that target any alternative desired measure on the space of directed or undirected graphs, in order to generate graphs with more sophisticated topological features.

  7. Plucking the Golden Goose: Higher Royalty Rates on the Oil Sands Generate Significant Increases in Government Revenue

    Directory of Open Access Journals (Sweden)

    Kenneth J. McKenzie

    2011-09-01

    Full Text Available The Alberta government’s 2009 New Royalty Framework elicited resistance on the part of the energy industry, leading to subsequent reductions in the royalties imposed on natural gas and conventional oil. However, the oil sands sector, subject to different terms, quickly accepted the new arrangement with little complaint, recognizing it as win-win situation for industry and the government. Under the framework, Alberta recoups much more money in royalties — about $1 billion over the two year period of 2009 and 2010 — without impinging significantly on investment in the oil sands. This brief paper demonstrates that by spreading the financial risks and benefits to everyone involved, the new framework proves it’s possible to generate increased revenue without frightening off future investment. The same model could conceivably be applied to the conventional oil and natural gas sectors.

  8. A Prolonged Time Interval Between Trauma and Prophylactic Radiation Therapy Significantly Increases the Risk of Heterotopic Ossification

    Energy Technology Data Exchange (ETDEWEB)

    Mourad, Waleed F., E-mail: Waleed246@gmail.com [Department of Radiation Oncology, University of Mississippi Medical Center, Jackson, MS (United States); Department of Radiation Oncology, Beth Israel Medical Center, New York, NY (Israel); Packianathan, Satyaseelan [Department of Radiation Oncology, University of Mississippi Medical Center, Jackson, MS (United States); Shourbaji, Rania A. [Department of Epidemiology and Biostatistics, Jackson State University, Jackson, MS (United States); Zhang Zhen; Graves, Mathew [Department of Orthopedic Surgery, University of Mississippi Medical Center, Jackson, MS (United States); Khan, Majid A. [Department of Radiology, University of Mississippi Medical Center, Jackson, MS (United States); Baird, Michael C. [Department of Radiation Oncology, University of Mississippi Medical Center, Jackson, MS (United States); Russell, George [Department of Orthopedic Surgery, University of Mississippi Medical Center, Jackson, MS (United States); Vijayakumar, Srinivasan [Department of Radiation Oncology, University of Mississippi Medical Center, Jackson, MS (United States)

    2012-03-01

    Purpose: To ascertain whether the time from injury to prophylactic radiation therapy (RT) influences the rate of heterotopic ossification (HO) after operative treatment of displaced acetabular fractures. Methods and Materials: This is a single-institution, retrospective analysis of patients referred for RT for the prevention of HO. Between January 2000 and January 2009, 585 patients with displaced acetabular fractures were treated surgically followed by RT for HO prevention. We analyzed the effect of time from injury on prevention of HO by RT. In all patients, 700 cGy was prescribed in a single fraction and delivered within 72 hours postsurgery. The patients were stratified into five groups according to time interval (in days) from the date of their accident to the date of RT: Groups A {<=}3, B {<=}7, C {<=}14, D {<=}21, and E >21days. Results: Of the 585 patients with displaced acetabular fractures treated with RT, (18%) 106 patients developed HO within the irradiated field. The risk of HO after RT increased from 10% for RT delivered {<=}3 days to 92% for treatment delivered >21 days after the initial injury. Wilcoxon test showed a significant correlation between the risk of HO and the length of time from injury to RT (p < 0.0001). Chi-square test and multiple logistic regression analysis showed no significant association between all other factors and the risk of HO (race, gender, cause and type of fracture, surgical approach, or the use of indomethacin). Conclusions: Our data suggest that there is higher incidence and risk of HO if prophylactic RT is significantly delayed after a displaced acetabular fracture. Thus, RT should be administered as early as clinically possible after the trauma. Patients undergoing RT >3 weeks from their displaced acetabular fracture should be informed of the higher risk (>90%) of developing HO despite prophylaxis.

  9. Significance of increased lung thallium-201 activity on serial cardiac images after dipyridamole treatment in coronary heart disease

    International Nuclear Information System (INIS)

    Okada, R.D.; Dai, Y.H.; Boucher, C.A.; Pohost, G.M.

    1984-01-01

    Increased lung thallium-201 (Tl-201) activity occurs in patients with severe coronary artery disease (CAD) on initial postexercise images. To determine the significance of assessing lung Tl-201 on serial imaging after dipyridamole therapy, initial and delayed (2 to 3 hours) Tl-201 imaging was performed in 40 patients with CAD and 26 normal control subjects. Lung Tl-201 activity was quantitated as a percentage of maximal myocardial activity for each imaging time (lung Tl-201 index). The mean initial lung Tl-201 activity was 42 +/- 2% (+/- standard error of the mean) in 26 control subjects, 56 +/- 2% in 25 patients with 2- or 3-vessel CAD (p less than 0.001) and 53 +/- 2% in 15 patients with 1-vessel CAD (p less than 0.005 compared with control subjects) (difference not significant between 1-vessel and multivessel CAD). Dipyridamole lung Tl-201 activity decreased relative to the myocardium from initial to delayed images (p less than 0.001) in patients with CAD but not in control subjects. When a dipyridamole lung Tl-201 index of 58% (mean +/- 2 standard deviations for control subjects) was chosen as the upper limit of normal, 14 of 40 of the CAD patients (35%) had abnormal values and all control patients had values within normal limits. These 14 patients with CAD and abnormal initial lung Tl-201 indexes had rest ejection fractions that were not significantly different from those in patients with CAD, and normal initial dipyridamole lung Tl-201 index (58 +/- 4% and 63 +/- 2%, respectively)

  10. Pressure sores significantly increase the risk of developing a Fournier's gangrene in patients with spinal cord injury.

    Science.gov (United States)

    Backhaus, M; Citak, M; Tilkorn, D-J; Meindl, R; Schildhauer, T A; Fehmer, T

    2011-11-01

    Retrospective chart review. The aim of our study was to evaluate the mortality rate and further specific risk factors for Fournier's gangrene in patients with spinal cord injury (SCI). Division of Spinal Cord Injury, BG-University Hospital Bergmannsheil Bochum, Ruhr-University Bochum, Germany. All patients with a SCI and a Fournier's gangrene treated in our hospital were enrolled in this study. Following parameters were taken form patients medical records: age, type of SCI, cause of Fournier's gangrene, number of surgical debridements, length of hospital and intensive care unit stay, co morbidity factors and mortality rate. In addition, laboratory parameter including the laboratory risk indicator for necrotizing fasciitis (LRINEC) score and microbiological findings were analyzed. Clinical diagnosis was made via histological examination. A total of 16 male patients (15 paraplegic and one tetraplegic) were included in the study. In 81% of all cases, the origin of Fournier's gangrene was a pressure sore. The median LRINEC score on admission was 6.5. In the vast majority of cases, a polybacterial infection was found. No patient died during the hospital stay. The mean number of surgical debridements before soft tissue closure was 1.9 and after a mean time interval of 39.1 days wound closure was performed in all patients. Pressure sores significantly increase the risk of developing Fournier's gangrene in patients with SCI. We reported the results of our patients to increase awareness among physicians and training staff working with patients with a SCI in order to expedite the diagnosis.

  11. Programming in the Zone: Repertoire Selection for the Large Ensemble

    Science.gov (United States)

    Hopkins, Michael

    2013-01-01

    One of the great challenges ensemble directors face is selecting high-quality repertoire that matches the musical and technical levels of their ensembles. Thoughtful repertoire selection can lead to increased student motivation as well as greater enthusiasm for the music program from parents, administrators, teachers, and community members. Common…

  12. Ensemble Network Architecture for Deep Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Xi-liang Chen

    2018-01-01

    Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.

  13. Unequivocal detection of ozone recovery in the Antarctic Ozone Hole through significant increases in atmospheric layers with minimum ozone

    Science.gov (United States)

    de Laat, Jos; van Weele, Michiel; van der A, Ronald

    2015-04-01

    An important new landmark in present day ozone research is presented through MLS satellite observations of significant ozone increases during the ozone hole season that are attributed unequivocally to declining ozone depleting substances. For many decades the Antarctic ozone hole has been the prime example of both the detrimental effects of human activities on our environment as well as how to construct effective and successful environmental policies. Nowadays atmospheric concentrations of ozone depleting substances are on the decline and first signs of recovery of stratospheric ozone and ozone in the Antarctic ozone hole have been observed. The claimed detection of significant recovery, however, is still subject of debate. In this talk we will discuss first current uncertainties in the assessment of ozone recovery in the Antarctic ozone hole by using multi-variate regression methods, and, secondly present an alternative approach to identify ozone hole recovery unequivocally. Even though multi-variate regression methods help to reduce uncertainties in estimates of ozone recovery, great care has to be taken in their application due to the existence of uncertainties and degrees of freedom in the choice of independent variables. We show that taking all uncertainties into account in the regressions the formal recovery of ozone in the Antarctic ozone hole cannot be established yet, though is likely before the end of the decade (before 2020). Rather than focusing on time and area averages of total ozone columns or ozone profiles, we argue that the time evolution of the probability distribution of vertically resolved ozone in the Antarctic ozone hole contains a better fingerprint for the detection of ozone recovery in the Antarctic ozone hole. The advantages of this method over more tradition methods of trend analyses based on spatio-temporal average ozone are discussed. The 10-year record of MLS satellite measurements of ozone in the Antarctic ozone hole shows a

  14. Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

    2018-01-01

    Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

  15. Embedded random matrix ensembles in quantum physics

    CERN Document Server

    Kota, V K B

    2014-01-01

    Although used with increasing frequency in many branches of physics, random matrix ensembles are not always sufficiently specific to account for important features of the physical system at hand. One refinement which retains the basic stochastic approach but allows for such features consists in the use of embedded ensembles.  The present text is an exhaustive introduction to and survey of this important field. Starting with an easy-to-read introduction to general random matrix theory, the text then develops the necessary concepts from the beginning, accompanying the reader to the frontiers of present-day research. With some notable exceptions, to date these ensembles have primarily been applied in nuclear spectroscopy. A characteristic example is the use of a random two-body interaction in the framework of the nuclear shell model. Yet, topics in atomic physics, mesoscopic physics, quantum information science and statistical mechanics of isolated finite quantum systems can also be addressed using these ensemb...

  16. Ensemble computing for the petroleum industry

    International Nuclear Information System (INIS)

    Annaratone, M.; Dossa, D.

    1995-01-01

    Computer downsizing is one of the most often used buzzwords in today's competitive business, and the petroleum industry is at the forefront of this revolution. Ensemble computing provides the key for computer downsizing with its first incarnation, i.e., workstation farms. This paper concerns the importance of increasing the productivity cycle and not just the execution time of a job. The authors introduce the concept of ensemble computing and workstation farms. The they discuss how different computing paradigms can be addressed by workstation farms

  17. Ensemble forecasting of potential habitat for three invasive fishes

    Science.gov (United States)

    Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David

    2012-01-01

    Aquatic invasive species pose major ecological and economic threats to aquatic ecosystems worldwide via displacement, predation, or hybridization with native species and the alteration of aquatic habitats and hydrologic cycles. Modeling the habitat suitability of alien aquatic species through spatially explicit mapping is an increasingly important risk assessment tool. Habitat modeling also facilitates identification of key environmental variables influencing invasive species distributions. We compared four modeling methods to predict the potential continental United States distributions of northern snakehead Channa argus (Cantor, 1842), round goby Neogobius melanostomus (Pallas, 1814), and silver carp Hypophthalmichthys molitrix (Valenciennes, 1844) using maximum entropy (Maxent), the genetic algorithm for rule set production (GARP), DOMAIN, and support vector machines (SVM). We used inventory records from the USGS Nonindigenous Aquatic Species Database and a geographic information system of 20 climatic and environmental variables to generate individual and ensemble distribution maps for each species. The ensemble maps from our study performed as well as or better than all of the individual models except Maxent. The ensemble and Maxent models produced significantly higher accuracy individual maps than GARP, one-class SVMs, or DOMAIN. The key environmental predictor variables in the individual models were consistent with the tolerances of each species. Results from this study provide insights into which locations and environmental conditions may promote the future spread of invasive fish in the US.

  18. Imprinting and recalling cortical ensembles.

    Science.gov (United States)

    Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S; Yuste, Rafael

    2016-08-12

    Neuronal ensembles are coactive groups of neurons that may represent building blocks of cortical circuits. These ensembles could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations from ensembles in the visual cortex of awake mice builds neuronal ensembles that recur spontaneously after being imprinted and do not disrupt preexisting ones. Moreover, imprinted ensembles can be recalled by single- cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. Copyright © 2016, American Association for the Advancement of Science.

  19. Marrying Step Feed with Secondary Clarifier Improvements to Significantly Increase Peak Wet Weather Treatment Capacity: An Integrated Methodology.

    Science.gov (United States)

    Daigger, Glen T; Siczka, John S; Smith, Thomas F; Frank, David A; McCorquodale, J A

    2017-08-01

      The need to increase the peak wet weather secondary treatment capacity of the City of Akron, Ohio, Water Reclamation Facility (WRF) provided the opportunity to test an integrated methodology for maximizing the peak wet weather secondary treatment capacity of activated sludge systems. An initial investigation, consisting of process modeling of the secondary treatment system and computational fluid dynamics (CFD) analysis of the existing relatively shallow secondary clarifiers (3.3 and 3.7 m sidewater depth in 30.5 m diameter units), indicated that a significant increase in capacity from 416 000 to 684 000 m3/d or more was possible by adding step feed capabilities to the existing bioreactors and upgrading the existing secondary clarifiers. One of the six treatment units at the WRF was modified, and an extensive 2-year testing program was conducted to determine the total peak wet weather secondary treatment capacity achievable. The results demonstrated that a peak wet weather secondary treatment capacity approaching 974 000 m3/d is possible as long as secondary clarifier solids and hydraulic loadings could be separately controlled using the step feed capability provided. Excellent sludge settling characteristics are routinely experienced at the City of Akron WRF, raising concerns that the identified peak wet weather secondary treatment capacity could not be maintained should sludge settling characteristics deteriorate for some reason. Computational fluid dynamics analysis indicated that the impact of the deterioration of sludge settling characteristics could be mitigated and the identified peak wet weather secondary treatment capacity maintained by further use of the step feed capability provided to further reduce secondary clarifier solids loading rates at the identified high surface overflow rates. The results also demonstrated that effluent limits not only for total suspended solids (TSS) and five-day carbonaceous biochemical oxygen demand (cBOD5) could be

  20. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon

    2016-06-14

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  1. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon; Law, Kody J. H.; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  2. The Effects of Classical Guitar Ensembles on Student Self-Perceptions and Acquisition of Music Skills

    Science.gov (United States)

    Kramer, John R.

    2012-01-01

    Classical guitar ensembles are increasing in the United States as popular alternatives to band, choir, and orchestra. Classical guitar ensembles are offered at many middle and high schools as fine arts electives as one of the only options for classical guitarists to participate in ensembles. The purpose of this study was to explore the development…

  3. Diversity in random subspacing ensembles

    NARCIS (Netherlands)

    Tsymbal, A.; Pechenizkiy, M.; Cunningham, P.; Kambayashi, Y.; Mohania, M.K.; Wöß, W.

    2004-01-01

    Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. It was shown experimentally and theoretically that in order for an ensemble to be effective, it should consist of classifiers having diversity in their predictions. A number of ways are

  4. PSO-Ensemble Demo Application

    DEFF Research Database (Denmark)

    2004-01-01

    Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output...

  5. New concept of statistical ensembles

    International Nuclear Information System (INIS)

    Gorenstein, M.I.

    2009-01-01

    An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution is introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.

  6. Clinical significance of increased gelatinolytic activity in the rectal mucosa during external beam radiation therapy of prostate cancer

    International Nuclear Information System (INIS)

    Hovdenak, Nils; Wang Junru; Sung, C.-C.; Kelly, Thomas; Fajardo, Luis F.; Hauer-Jensen, Martin

    2002-01-01

    Purpose: Rectal toxicity (proctitis) is a dose-limiting factor in pelvic radiation therapy. Mucosal atrophy, i.e., net extracellular matrix degradation, is a prominent feature of radiation proctitis, but the underlying mechanisms are not known. We prospectively examined changes in matrix metalloproteinase (MMP)-2 and MMP-9 (gelatinase A and B) in the rectal mucosa during radiation therapy of prostate cancer, as well as the relationships of these changes with symptomatic, structural, and cellular evidence of radiation proctitis. Methods and Materials: Seventeen patients scheduled for external beam radiation therapy for prostate cancer were prospectively enrolled. Symptoms of gastrointestinal toxicity were recorded, and endoscopy with biopsy of the rectal mucosa was performed before radiation therapy, as well as 2 and 6 weeks into the treatment course. Radiation proctitis was assessed by endoscopic scoring, quantitative histology, and quantitative immunohistochemistry. MMP-2 and MMP-9 were localized immunohistochemically, and activities were determined by gelatin zymography. Results: Symptoms, endoscopic scores, histologic injury, and mucosal macrophages and neutrophils increased from baseline to 2 weeks. Symptoms increased further from 2 weeks to 6 weeks, whereas endoscopic and cellular evidence of proctitis did not. Compared to pretreatment values, there was increased total gelatinolytic activity of MMP-2 and MMP-9 at 2 weeks (p=0.02 and p=0.004, respectively) and 6 weeks (p=0.006 and p=0.001, respectively). Active MMP-2 was increased at both time points (p=0.0001 and p=0.002). Increased MMP-9 and MMP-2 at 6 weeks was associated with radiation-induced diarrhea (p=0.007 and p=0.02, respectively) and with mucosal neutrophil infiltration (rho=0.62). Conclusions: Pelvic radiation therapy causes increased MMP-2 and MMP-9 activity in the rectal mucosa. These changes correlate with radiation-induced diarrhea and granulocyte infiltration and may contribute to abnormal

  7. Determination of relative CMRO2 from CBF and BOLD changes: significant increase of oxygen consumption rate during visual stimulation

    DEFF Research Database (Denmark)

    Kim, S.G.; Rostrup, Egill; Larsson, H.B.

    1999-01-01

    signal changes were measured simultaneously using the flow-sensitive alternating inversion recovery (FAIR) technique. During hypercapnia established by an end-tidal CO2 increase of 1.46 kPa, CBF in the visual cortex increased by 47.3 +/- 17.3% (mean +/- SD; n = 9), and deltaR2* was -0.478 +/- 0.147 sec......The blood oxygenation level-dependent (BOLD) effect in functional magnetic resonance imaging depends on at least partial uncoupling between cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) changes. By measuring CBF and BOLD simultaneously, the relative change in CMRO2 can...

  8. Ensembl 2002: accommodating comparative genomics.

    Science.gov (United States)

    Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

    2003-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

  9. Conductor gestures influence evaluations of ensemble performance

    Directory of Open Access Journals (Sweden)

    Steven eMorrison

    2014-07-01

    Full Text Available Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor’s gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance, articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and nonmajors (N = 285 viewed sixteen 30-second performances and evaluated the quality of the ensemble’s articulation, dynamics, technique and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble’s performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

  10. Ensembl Genomes 2016: more genomes, more complexity.

    Science.gov (United States)

    Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

    2016-01-04

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Increased Risk of Clinically Significant Gallstones following an Appendectomy: A Five-Year Follow-Up Study.

    Directory of Open Access Journals (Sweden)

    Shiu-Dong Chung

    Full Text Available Although the vermiform appendix is commonly considered a vestigial organ, adverse health consequences after an appendectomy have garnered increasing attention. In this study, we investigated the risks of gallstone occurrence during a 5-year follow-up period after an appendectomy, using a population-based dataset. We used data from the Taiwan Longitudinal Health Insurance Database 2005. The exposed cohort included 4916 patients who underwent an appendectomy. The unexposed cohort was retrieved by randomly selecting 4916 patients matched with the exposed cohort in terms of sex, age, and year. We individually tracked each patient for a 5-year period to identify those who received a diagnosis of gallstones during the follow-up period. Cox proportional hazard regressions were performed for the analysis. During the 5-year follow-up period, the incidence rate per 1000 person-years was 4.71 for patients who had undergone an appendectomy, compared to a rate of 2.59 for patients in the unexposed cohort (p<0.001. Patients who had undergone an appendectomy were independently associated with a 1.79 (95% CI = 1.29~2.48-fold increased risk of being diagnosed with gallstones during the 5-year follow-up period. We found that among female patients, the adjusted hazard ratio of gallstones was 2.25 (95% CI = 1.41~3.59 for patients who underwent an appendectomy compared to unexposed patients. However, for male patients, we failed to observe an increased hazard for gallstones among patients who underwent an appendectomy compared to unexposed patients. We found an increased risk of a subsequent gallstone diagnosis within 5 years after an appendectomy.

  12. Decadal climate predictions improved by ocean ensemble dispersion filtering

    Science.gov (United States)

    Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

    2017-06-01

    Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.Plain Language SummaryDecadal predictions aim to predict the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. The ocean memory due to its heat capacity holds big potential skill. In recent years, more precise initialization techniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions. Ensembles are another important aspect. Applying slightly perturbed predictions to trigger the famous butterfly effect results in an ensemble. Instead of evaluating one prediction, but the whole ensemble with its

  13. On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

    KAUST Repository

    Luo, Xiaodong

    2010-09-19

    The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

  14. Modifications resulting in significant increases in the beam usage time of a 60 keV electron beam welder

    International Nuclear Information System (INIS)

    Zielinski, R.E.; Harrison, J.L.

    1976-01-01

    Short beam usage times were encountered using a 60 keV electron beam welder. These short times were the direct result of a buildup of a reaction product (WO 2 . 90 ) that occurred on graphite washers which housed the tungsten emitter plate. While it was not possible to prevent the reaction product, its growth rate was sufficiently altered by changing graphite materials and minor design changes of the washers. With these modifications beam usage times increased from an original 40 min to approximately 675 min

  15. Was there significant tax evasion after the 1999 50 cent per pack cigarette tax increase in California?

    Science.gov (United States)

    Emery, S; White, M; Gilpin, E; Pierce, J

    2002-01-01

    Objectives: Several states, including California, have implemented large cigarette excise tax increases, which may encourage smokers to purchase their cigarettes in other lower taxed states, or from other lower or non-taxed sources. Such tax evasion thwarts tobacco control objectives and may cost the state substantial tax revenues. Thus, this study investigates the extent of tax evasion in the 6–12 months after the implementation of California's $0.50/pack excise tax increase. Design and setting: Retrospective data analysis from the 1999 California Tobacco Surveys (CTS), a random digit dialled telephone survey of California households. Main outcome measures: Sources of cigarettes, average daily cigarette consumption, and reported price paid. Results: Very few (5.1 (0.7)% (±95% confidence limits)) of California smokers avoided the excise tax by usually purchasing cigarettes from non- or lower taxed sources, such as out-of-state outlets, military commissaries, or the internet. The vast majority of smokers purchased their cigarettes from the most convenient and expensive sources: convenience stores/gas (petrol) stations (45.0 (1.9)%), liquor/drug stores (16.4 (1.6)%), and supermarkets (8.8 (1.2)%). Conclusions: Despite the potential savings, tax evasion by individual smokers does not appear to pose a serious threat to California's excise tax revenues or its tobacco control objectives. PMID:12035006

  16. Love is the triumph of the imagination: Daydreams about significant others are associated with increased happiness, love and connection.

    Science.gov (United States)

    Poerio, Giulia L; Totterdell, Peter; Emerson, Lisa-Marie; Miles, Eleanor

    2015-05-01

    Social relationships and interactions contribute to daily emotional well-being. The emotional benefits that come from engaging with others are known to arise from real events, but do they also come from the imagination during daydreaming activity? Using experience sampling methodology with 101 participants, we obtained 371 reports of naturally occurring daydreams with social and non-social content and self-reported feelings before and after daydreaming. Social, but not non-social, daydreams were associated with increased happiness, love and connection and this effect was not solely attributable to the emotional content of the daydreams. These effects were only present when participants were lacking in these feelings before daydreaming and when the daydream involved imagining others with whom the daydreamer had a high quality relationship. Findings are consistent with the idea that social daydreams may function to regulate emotion: imagining close others may serve the current emotional needs of daydreamers by increasing positive feelings towards themselves and others. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Electronic prompts significantly increase response rates to postal questionnaires: a randomized trial within a randomized trial and meta-analysis.

    Science.gov (United States)

    Clark, Laura; Ronaldson, Sarah; Dyson, Lisa; Hewitt, Catherine; Torgerson, David; Adamson, Joy

    2015-12-01

    To assess the effectiveness of sending electronic prompts to randomized controlled trial participants to return study questionnaires. A "trial within a trial" embedded within a study determining the effectiveness of chronic obstructive pulmonary disease (DOC) screening on smoking cessation. Those participants taking part in DOC who provided a mobile phone number and/or an electronic mail address were randomized to either receive an electronic prompt or no electronic prompt to return a study questionnaire. The results were combined with two previous studies in a meta-analysis. A total of 437 participants were randomized: 226 to the electronic prompt group and 211 to the control group. A total of 285 (65.2%) participants returned the follow-up questionnaire: 157 (69.5%) in the electronic prompt group and 128 (60.7%) in the control group [difference 8.8%; 95% confidence interval (CI): -0.11%, 17.7%; P = 0.05]. The mean time to response was 23 days in the electronic prompt group and 33 days in the control group (hazard ratio = 1.27; 95% CI: 1.105, 1.47). The meta-analysis of all three studies showed an increase in response rate of 7.1% (95% CI: 0.8%, 13.3%). The use of electronic prompts increased response rates and reduces the time to response. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. 'Knowledge for better health' revisited - the increasing significance of health research systems: a review by departing Editors-in-Chief.

    Science.gov (United States)

    Hanney, Stephen R; González-Block, Miguel A

    2017-10-02

    How can nations organise research investments to obtain the best bundle of knowledge and the maximum level of improved health, spread as equitably as possible? This question was the central focus of a major initiative from WHO led by Prof Tikki Pang, which resulted in a range of developments, including the publication of a conceptual framework for national health research systems - Knowledge for better health - in 2003, and in the founding of the journal Health Research Policy and Systems (HARPS). As Editors-in-Chief of the journal since 2006, we mark our retirement by tracking both the progress of the journal and the development of national health research systems. HARPS has maintained its focus on a range of central themes that are key components of a national health research system in any country. These include building capacity to conduct and use health research, identifying appropriate priorities, securing funds and allocating them accountably, producing scientifically valid research outputs, promoting the use of research in polices and practice in order to improve health, and monitoring and evaluating the health research system. Some of the themes covered in HARPS are now receiving increased attention and, for example, with the assessment of research impact and development of knowledge translation platforms, the journal has covered their progress throughout that expansion of interest. In addition, there is increasing recognition of new imperatives, including the importance of promoting gender equality in health research if benefits are to be maximised. In this Editorial, we outline some of the diverse and developing perspectives considered within each theme, as well as considering how they are held together by the growing desire to build effective health research systems in all countries.From 2003 until mid-June 2017, HARPS published 590 articles on the above and related themes, with authors being located in 76 countries. We present quantitative data tracing

  19. Using ensemble forecasting for wind power

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Landberg, L.; Badger, J. [Risoe National Lab., Roskilde (Denmark); Sattler, K.

    2003-07-01

    Short-term prediction of wind power has a long tradition in Denmark. It is an essential tool for the operators to keep the grid from becoming unstable in a region like Jutland, where more than 27% of the electricity consumption comes from wind power. This means that the minimum load is already lower than the maximum production from wind energy alone. Danish utilities have therefore used short-term prediction of wind energy since the mid-90ies. However, the accuracy is still far from being sufficient in the eyes of the utilities (used to have load forecasts accurate to within 5% on a one-week horizon). The Ensemble project tries to alleviate the dependency of the forecast quality on one model by using multiple models, and also will investigate the possibilities of using the model spread of multiple models or of dedicated ensemble runs for a prediction of the uncertainty of the forecast. Usually, short-term forecasting works (especially for the horizon beyond 6 hours) by gathering input from a Numerical Weather Prediction (NWP) model. This input data is used together with online data in statistical models (this is the case eg in Zephyr/WPPT) to yield the output of the wind farms or of a whole region for the next 48 hours (only limited by the NWP model horizon). For the accuracy of the final production forecast, the accuracy of the NWP prediction is paramount. While many efforts are underway to increase the accuracy of the NWP forecasts themselves (which ultimately are limited by the amount of computing power available, the lack of a tight observational network on the Atlantic and limited physics modelling), another approach is to use ensembles of different models or different model runs. This can be either an ensemble of different models output for the same area, using different data assimilation schemes and different model physics, or a dedicated ensemble run by a large institution, where the same model is run with slight variations in initial conditions and

  20. Irrigation Is Significantly Associated with an Increased Prevalence of Listeria monocytogenes in Produce Production Environments in New York State.

    Science.gov (United States)

    Weller, Daniel; Wiedmann, Martin; Strawn, Laura K

    2015-06-01

    Environmental (i.e., meteorological and landscape) factors and management practices can affect the prevalence of foodborne pathogens in produce production environments. This study was conducted to determine the prevalence of Listeria monocytogenes, Listeria species (including L. monocytogenes), Salmonella, and Shiga toxin-producing Escherichia coli (STEC) in produce production environments and to identify environmental factors and management practices associated with their isolation. Ten produce farms in New York State were sampled during a 6-week period in 2010, and 124 georeferenced samples (80 terrestrial, 33 water, and 11 fecal) were collected. L. monocytogenes, Listeria spp., Salmonella, and STEC were detected in 16, 44, 4, and 5% of terrestrial samples, 30, 58, 12, and 3% of water samples, and 45, 45, 27, and 9% of fecal samples, respectively. Environmental factors and management practices were evaluated for their association with terrestrial samples positive for L. monocytogenes or other Listeria species by univariate logistic regression; analysis was not conducted for Salmonella or STEC because the number of samples positive for these pathogens was low. Although univariate analysis identified associations between isolation of L. monocytogenes or Listeria spp. from terrestrial samples and various water-related factors (e.g., proximity to wetlands and precipitation), multivariate analysis revealed that only irrigation within 3 days of sample collection was significantly associated with isolation of L. monocytogenes (odds ratio = 39) and Listeria spp. (odds ratio = 5) from terrestrial samples. These findings suggest that intervention at the irrigation level may reduce the risk of produce contamination.

  1. Plant Explants Grown on Medium Supplemented with Fe3O4 Nanoparticles Have a Significant Increase in Embryogenesis

    Directory of Open Access Journals (Sweden)

    Inese Kokina

    2017-01-01

    Full Text Available Development of nanotechnology leads to the increasing release of nanoparticles in the environment that results in accumulation of different NPs in living organisms including plants. This can lead to serious changes in plant cultures which leads to genotoxicity. The aims of the present study were to detect if iron oxide NPs pass through the flax cell wall, to compare callus morphology, and to estimate the genotoxicity in Linum usitatissimum L. callus cultures induced by different concentrations of Fe3O4 nanoparticles. Two parallel experiments were performed: experiment A, where flax explants were grown on medium supplemented with 0.5 mg/l, 1 mg/l, and 1.5 mg/l Fe3O4 NPs for callus culture obtaining, and experiment B, where calluses obtained from basal MS medium were transported into medium supplemented with concentrations of NPs identical to experiment A. Obtained results demonstrate similarly in both experiments that 25 nm Fe3O4 NPs pass into callus cells and induce low toxicity level in the callus cultures. Nevertheless, calluses from experiment A showed 100% embryogenesis in comparison with experiment B where 100% rhizogenesis was noticed. It could be associated with different stress levels and adaptation time for explants and calluses that were transported into medium with Fe3O4 NPs supplementation.

  2. Clinical significance of stress-related increase in blood pressure: current evidence in office and out-of-office settings.

    Science.gov (United States)

    Munakata, Masanori

    2018-05-29

    High blood pressure is the most significant risk factor of cardiovascular and cerebrovascular diseases worldwide. Blood pressure and its variability are recognized as risk factors. Thus, hypertension control should focus not only on maintaining optimal levels but also on achieving less variability in blood pressure. Psychosocial stress is known to contribute to the development and worsening of hypertension. Stress is perceived by the brain and induces neuroendocrine responses in either a rapid or long-term manner. Moreover, endothelial dysfunction and inflammation might be further involved in the modulation of blood pressure elevation associated with stress. White-coat hypertension, defined as high clinic blood pressure but normal out-of-office blood pressure, is the most popular stress-related blood pressure response. Careful follow-up is necessary for this type of hypertensive patients because some show organ damage or a worse prognosis. On the other hand, masked hypertension, defined as high out-of-office blood pressure but normal office blood pressure, has received considerable interest as a poor prognostic condition. The cause of masked hypertension is complex, but evidence suggests that chronic stress at the workplace or home could be involved. Chronic psychological stress could be associated with distorted lifestyle and mental distress as well as long-lasting allostatic load, contributing to the maintenance of blood pressure elevation. Stress issues are common in patients in modern society. Considering psychosocial stress as the pathogenesis of blood pressure elevation is useful for achieving an individual-focused approach and 24-h blood pressure control.

  3. High Dose Atorvastatin Associated with Increased Risk of Significant Hepatotoxicity in Comparison to Simvastatin in UK GPRD Cohort.

    Directory of Open Access Journals (Sweden)

    Alan T Clarke

    Full Text Available Occasional risk of serious liver dysfunction and autoimmune hepatitis during atorvastatin therapy has been reported. We compared the risk of hepatotoxicity in atorvastatin relative to simvastatin treatment.The UK GPRD identified patients with a first prescription for simvastatin [164,407] or atorvastatin [76,411] between 1997 and 2006, but with no prior record of liver disease, alcohol-related diagnosis, or liver dysfunction. Incident liver dysfunction in the following six months was identified by biochemical value and compared between statin groups by Cox regression model adjusting for age, sex, year treatment started, dose, alcohol consumption, smoking, body mass index and comorbid conditions.Moderate to severe hepatotoxicity [bilirubin >60μmol/L, AST or ALT >200U/L or alkaline phosphatase >1200U/L] developed in 71 patients on atorvastatin versus 101 on simvastatin. Adjusted hazard ratio [AHR] for all atorvastatin relative to simvastatin was 1.9 [95% confidence interval 1.4-2.6]. High dose was classified as 40-80mg daily and low dose 10-20mg daily. Hepatotoxicity occurred in 0.44% of 4075 patients on high dose atorvastatin [HDA], 0.07% of 72,336 on low dose atorvastatin [LDA], 0.09% of 44,675 on high dose simvastatin [HDS] and 0.05% of 119,732 on low dose simvastatin [LDS]. AHRs compared to LDS were 7.3 [4.2-12.7] for HDA, 1.4 [0.9-2.0] for LDA and 1.5 [1.0-2.2] for HDS.The risk of hepatotoxicity was increased in the first six months of atorvastatin compared to simvastatin treatment, with the greatest difference between high dose atorvastatin and low dose simvastatin. The numbers of events in the analyses were small.

  4. High Dose Atorvastatin Associated with Increased Risk of Significant Hepatotoxicity in Comparison to Simvastatin in UK GPRD Cohort

    Science.gov (United States)

    Clarke, Alan T.; Johnson, Paul C. D.; Hall, Gillian C.; Ford, Ian; Mills, Peter R.

    2016-01-01

    Background & Aims Occasional risk of serious liver dysfunction and autoimmune hepatitis during atorvastatin therapy has been reported. We compared the risk of hepatotoxicity in atorvastatin relative to simvastatin treatment. Methods The UK GPRD identified patients with a first prescription for simvastatin [164,407] or atorvastatin [76,411] between 1997 and 2006, but with no prior record of liver disease, alcohol-related diagnosis, or liver dysfunction. Incident liver dysfunction in the following six months was identified by biochemical value and compared between statin groups by Cox regression model adjusting for age, sex, year treatment started, dose, alcohol consumption, smoking, body mass index and comorbid conditions. Results Moderate to severe hepatotoxicity [bilirubin >60μmol/L, AST or ALT >200U/L or alkaline phosphatase >1200U/L] developed in 71 patients on atorvastatin versus 101 on simvastatin. Adjusted hazard ratio [AHR] for all atorvastatin relative to simvastatin was 1.9 [95% confidence interval 1.4–2.6]. High dose was classified as 40–80mg daily and low dose 10–20mg daily. Hepatotoxicity occurred in 0.44% of 4075 patients on high dose atorvastatin [HDA], 0.07% of 72,336 on low dose atorvastatin [LDA], 0.09% of 44,675 on high dose simvastatin [HDS] and 0.05% of 119,732 on low dose simvastatin [LDS]. AHRs compared to LDS were 7.3 [4.2–12.7] for HDA, 1.4 [0.9–2.0] for LDA and 1.5 [1.0–2.2] for HDS. Conclusions The risk of hepatotoxicity was increased in the first six months of atorvastatin compared to simvastatin treatment, with the greatest difference between high dose atorvastatin and low dose simvastatin. The numbers of events in the analyses were small. PMID:26983033

  5. Contact planarization of ensemble nanowires

    Science.gov (United States)

    Chia, A. C. E.; LaPierre, R. R.

    2011-06-01

    The viability of four organic polymers (S1808, SC200, SU8 and Cyclotene) as filling materials to achieve planarization of ensemble nanowire arrays is reported. Analysis of the porosity, surface roughness and thermal stability of each filling material was performed. Sonication was used as an effective method to remove the tops of the nanowires (NWs) to achieve complete planarization. Ensemble nanowire devices were fully fabricated and I-V measurements confirmed that Cyclotene effectively planarizes the NWs while still serving the role as an insulating layer between the top and bottom contacts. These processes and analysis can be easily implemented into future characterization and fabrication of ensemble NWs for optoelectronic device applications.

  6. A significant increase in the pepsinogen I/II ratio is a reliable biomarker for successful Helicobacter pylori eradication.

    Directory of Open Access Journals (Sweden)

    Hiroki Osumi

    Full Text Available Helicobacter pylori (H. pylori eradication is usually assessed using the 13C-urea breath test (UBT, anti-H. pylori antibody and the H. pylori stool antigen test. However, a few reports have used pepsinogen (PG, in particular, the percentage change in the PG I/II ratio. Here, we evaluated the usefulness of the percentage changes in serum PG I/II ratios for determining the success of eradication therapy for H. pylori.In total, 650 patients received eradication therapy from October 2008 to March 2013 in our Cancer Institute Hospital. We evaluated the relationship between H. pylori eradication and percentage changes in serum PG I/II ratios before and 3 months after treatment with CLEIA® (FUJIREBIO Inc, Tokyo, Japan. The gold standard of H. pylori eradication was defined as negative by the UBT performed 3 months after completion of eradication treatment. Cut-off values for percentage changes in serum PG I/II ratios were set as +40, +25 and +10% when the serum PG I/II ratio before treatment was below 3.0, above 3.0 but below 5.0 and 5.0 or above, respectively.Serum PG I and PG II levels were measured in 562 patients with H. pylori infection before and after eradication therapy. Eradication of H. pylori was achieved in 433 patients studied (77.0%. The ratios of first, second, third-line and penicillin allergy eradication treatment were 73.8% (317/429, 88.3% (99/112, 75% (12/16 and 100% (5/5, respectively. An increasing percentage in the serum levels of the PG I/II ratios after treatment compared with the values before treatment clearly distinguished success from failure of eradication (108.2±57.2 vs. 6.8±30.7, p<0.05. Using the above cut-off values, the sensitivity, specificity and validity for determination of H. pylori were 93.1, 93.8 and 93.2%, respectively.In conclusion, the percentage changes in serum PG I/II ratios are useful as evaluation criteria for assessing the success of eradication therapy for H. pylori.

  7. On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

    KAUST Repository

    Luo, Xiaodong; Hoteit, Ibrahim; Moroz, Irene M.

    2010-01-01

    However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

  8. Online Learning of Commission Avoidant Portfolio Ensembles

    OpenAIRE

    Uziel, Guy; El-Yaniv, Ran

    2016-01-01

    We present a novel online ensemble learning strategy for portfolio selection. The new strategy controls and exploits any set of commission-oblivious portfolio selection algorithms. The strategy handles transaction costs using a novel commission avoidance mechanism. We prove a logarithmic regret bound for our strategy with respect to optimal mixtures of the base algorithms. Numerical examples validate the viability of our method and show significant improvement over the state-of-the-art.

  9. Ensemble manifold regularization.

    Science.gov (United States)

    Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng

    2012-06-01

    We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.

  10. An Efficient Ensemble Learning Method for Gene Microarray Classification

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  11. Modeling polydispersive ensembles of diamond nanoparticles

    International Nuclear Information System (INIS)

    Barnard, Amanda S

    2013-01-01

    While significant progress has been made toward production of monodispersed samples of a variety of nanoparticles, in cases such as diamond nanoparticles (nanodiamonds) a significant degree of polydispersivity persists, so scaling-up of laboratory applications to industrial levels has its challenges. In many cases, however, monodispersivity is not essential for reliable application, provided that the inevitable uncertainties are just as predictable as the functional properties. As computational methods of materials design are becoming more widespread, there is a growing need for robust methods for modeling ensembles of nanoparticles, that capture the structural complexity characteristic of real specimens. In this paper we present a simple statistical approach to modeling of ensembles of nanoparticles, and apply it to nanodiamond, based on sets of individual simulations that have been carefully selected to describe specific structural sources that are responsible for scattering of fundamental properties, and that are typically difficult to eliminate experimentally. For the purposes of demonstration we show how scattering in the Fermi energy and the electronic band gap are related to different structural variations (sources), and how these results can be combined strategically to yield statistically significant predictions of the properties of an entire ensemble of nanodiamonds, rather than merely one individual ‘model’ particle or a non-representative sub-set. (paper)

  12. The Ensembl genome database project.

    Science.gov (United States)

    Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

    2002-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

  13. Modeling task-specific neuronal ensembles improves decoding of grasp

    Science.gov (United States)

    Smith, Ryan J.; Soares, Alcimar B.; Rouse, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

    2018-06-01

    Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more

  14. Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

    Science.gov (United States)

    Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

    2015-12-01

    In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

  15. A Separation between Divergence and Holevo Information for Ensembles

    OpenAIRE

    Jain, Rahul; Nayak, Ashwin; Su, Yi

    2007-01-01

    The notion of divergence information of an ensemble of probability distributions was introduced by Jain, Radhakrishnan, and Sen in the context of the ``substate theorem''. Since then, divergence has been recognized as a more natural measure of information in several situations in quantum and classical communication. We construct ensembles of probability distributions for which divergence information may be significantly smaller than the more standard Holevo information. As a result, we establ...

  16. On the distribution of eigenvalues of certain matrix ensembles

    International Nuclear Information System (INIS)

    Bogomolny, E.; Bohigas, O.; Pato, M.P.

    1995-01-01

    Invariant random matrix ensembles with weak confinement potentials of the eigenvalues, corresponding to indeterminate moment problems, are investigated. These ensembles are characterized by the fact that the mean density of eigenvalues tends to a continuous function with increasing matrix dimension contrary to the usual cases where it grows indefinitely. It is demonstrated that the standard asymptotic formulae are not applicable in these cases and that the asymptotic distribution of eigenvalues can deviate from the classical ones. (author)

  17. Ensembles of a small number of conformations with relative populations

    Energy Technology Data Exchange (ETDEWEB)

    Vammi, Vijay, E-mail: vsvammi@iastate.edu; Song, Guang, E-mail: gsong@iastate.edu [Iowa State University, Bioinformatics and Computational Biology Program, Department of Computer Science (United States)

    2015-12-15

    In our previous work, we proposed a new way to represent protein native states, using ensembles of a small number of conformations with relative Populations, or ESP in short. Using Ubiquitin as an example, we showed that using a small number of conformations could greatly reduce the potential of overfitting and assigning relative populations to protein ensembles could significantly improve their quality. To demonstrate that ESP indeed is an excellent alternative to represent protein native states, in this work we compare the quality of two ESP ensembles of Ubiquitin with several well-known regular ensembles or average structure representations. Extensive amount of significant experimental data are employed to achieve a thorough assessment. Our results demonstrate that ESP ensembles, though much smaller in size comparing to regular ensembles, perform equally or even better sometimes in all four different types of experimental data used in the assessment, namely, the residual dipolar couplings, residual chemical shift anisotropy, hydrogen exchange rates, and solution scattering profiles. This work further underlines the significance of having relative populations in describing the native states.

  18. The canonical ensemble redefined - 1: Formalism

    International Nuclear Information System (INIS)

    Venkataraman, R.

    1984-12-01

    For studying the thermodynamic properties of systems we propose an ensemble that lies in between the familiar canonical and microcanonical ensembles. We point out the transition from the canonical to microcanonical ensemble and prove from a comparative study that all these ensembles do not yield the same results even in the thermodynamic limit. An investigation of the coupling between two or more systems with these ensembles suggests that the state of thermodynamical equilibrium is a special case of statistical equilibrium. (author)

  19. Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

    Science.gov (United States)

    Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

    2017-06-01

    Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

  20. Changes in rocket salad phytochemicals within the commercial supply chain: Glucosinolates, isothiocyanates, amino acids and bacterial load increase significantly after processing.

    Science.gov (United States)

    Bell, Luke; Yahya, Hanis Nadia; Oloyede, Omobolanle Oluwadamilola; Methven, Lisa; Wagstaff, Carol

    2017-04-15

    Five cultivars of Eruca sativa and a commercial variety of Diplotaxis tenuifolia were grown in the UK (summer) and subjected to commercial growth, harvesting and processing, with subsequent shelf life storage. Glucosinolates (GSL), isothiocyanates (ITC), amino acids (AA), free sugars, and bacterial loads were analysed throughout the supply chain to determine the effects on phytochemical compositions. Bacterial load of leaves increased significantly over time and peaked during shelf life storage. Significant correlations were observed with GSL and AA concentrations, suggesting a previously unknown relationship between plants and endemic leaf bacteria. GSLs, ITCs and AAs increased significantly after processing and during shelf life. The supply chain did not significantly affect glucoraphanin concentrations, and its ITC sulforaphane significantly increased during shelf life in E. sativa cultivars. We hypothesise that commercial processing may increase the nutritional value of the crop, and have added health benefits for the consumer. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. DroidEnsemble: Detecting Android Malicious Applications with Ensemble of String and Structural Static Features

    KAUST Repository

    Wang, Wei

    2018-05-11

    Android platform has dominated the Operating System of mobile devices. However, the dramatic increase of Android malicious applications (malapps) has caused serious software failures to Android system and posed a great threat to users. The effective detection of Android malapps has thus become an emerging yet crucial issue. Characterizing the behaviors of Android applications (apps) is essential to detecting malapps. Most existing work on detecting Android malapps was mainly based on string static features such as permissions and API usage extracted from apps. There also exists work on the detection of Android malapps with structural features, such as Control Flow Graph (CFG) and Data Flow Graph (DFG). As Android malapps have become increasingly polymorphic and sophisticated, using only one type of static features may result in false negatives. In this work, we propose DroidEnsemble that takes advantages of both string features and structural features to systematically and comprehensively characterize the static behaviors of Android apps and thus build a more accurate detection model for the detection of Android malapps. We extract each app’s string features, including permissions, hardware features, filter intents, restricted API calls, used permissions, code patterns, as well as structural features like function call graph. We then use three machine learning algorithms, namely, Support Vector Machine (SVM), k-Nearest Neighbor (kNN) and Random Forest (RF), to evaluate the performance of these two types of features and of their ensemble. In the experiments, We evaluate our methods and models with 1386 benign apps and 1296 malapps. Extensive experimental results demonstrate the effectiveness of DroidEnsemble. It achieves the detection accuracy as 95.8% with only string features and as 90.68% with only structural features. DroidEnsemble reaches the detection accuracy as 98.4% with the ensemble of both types of features, reducing 9 false positives and 12 false

  2. Ensemble forecasting of species distributions.

    Science.gov (United States)

    Araújo, Miguel B; New, Mark

    2007-01-01

    Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

  3. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  4. On the forecast skill of a convection-permitting ensemble

    Science.gov (United States)

    Schellander-Gorgas, Theresa; Wang, Yong; Meier, Florian; Weidle, Florian; Wittmann, Christoph; Kann, Alexander

    2017-01-01

    The 2.5 km convection-permitting (CP) ensemble AROME-EPS (Applications of Research to Operations at Mesoscale - Ensemble Prediction System) is evaluated by comparison with the regional 11 km ensemble ALADIN-LAEF (Aire Limitée Adaption dynamique Développement InterNational - Limited Area Ensemble Forecasting) to show whether a benefit is provided by a CP EPS. The evaluation focuses on the abilities of the ensembles to quantitatively predict precipitation during a 3-month convective summer period over areas consisting of mountains and lowlands. The statistical verification uses surface observations and 1 km × 1 km precipitation analyses, and the verification scores involve state-of-the-art statistical measures for deterministic and probabilistic forecasts as well as novel spatial verification methods. The results show that the convection-permitting ensemble with higher-resolution AROME-EPS outperforms its mesoscale counterpart ALADIN-LAEF for precipitation forecasts. The positive impact is larger for the mountainous areas than for the lowlands. In particular, the diurnal precipitation cycle is improved in AROME-EPS, which leads to a significant improvement of scores at the concerned times of day (up to approximately one-third of the scored verification measure). Moreover, there are advantages for higher precipitation thresholds at small spatial scales, which are due to the improved simulation of the spatial structure of precipitation.

  5. Ensemble method for dengue prediction.

    Science.gov (United States)

    Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

    2018-01-01

    In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

  6. Ensemble method for dengue prediction.

    Directory of Open Access Journals (Sweden)

    Anna L Buczak

    Full Text Available In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico during four dengue seasons: 1 peak height (i.e., maximum weekly number of cases during a transmission season; 2 peak week (i.e., week in which the maximum weekly number of cases occurred; and 3 total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date.Our approach used ensemble models created by combining three disparate types of component models: 1 two-dimensional Method of Analogues models incorporating both dengue and climate data; 2 additive seasonal Holt-Winters models with and without wavelet smoothing; and 3 simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations.Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week.The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

  7. Advanced Atmospheric Ensemble Modeling Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Chiswell, S. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Kurzeja, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Maze, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Viner, B. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Werth, D. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-09-29

    Ensemble modeling (EM), the creation of multiple atmospheric simulations for a given time period, has become an essential tool for characterizing uncertainties in model predictions. We explore two novel ensemble modeling techniques: (1) perturbation of model parameters (Adaptive Programming, AP), and (2) data assimilation (Ensemble Kalman Filter, EnKF). The current research is an extension to work from last year and examines transport on a small spatial scale (<100 km) in complex terrain, for more rigorous testing of the ensemble technique. Two different release cases were studied, a coastal release (SF6) and an inland release (Freon) which consisted of two release times. Observations of tracer concentration and meteorology are used to judge the ensemble results. In addition, adaptive grid techniques have been developed to reduce required computing resources for transport calculations. Using a 20- member ensemble, the standard approach generated downwind transport that was quantitatively good for both releases; however, the EnKF method produced additional improvement for the coastal release where the spatial and temporal differences due to interior valley heating lead to the inland movement of the plume. The AP technique showed improvements for both release cases, with more improvement shown in the inland release. This research demonstrated that transport accuracy can be improved when models are adapted to a particular location/time or when important local data is assimilated into the simulation and enhances SRNL’s capability in atmospheric transport modeling in support of its current customer base and local site missions, as well as our ability to attract new customers within the intelligence community.

  8. Medium Range Ensembles Flood Forecasts for Community Level Applications

    Science.gov (United States)

    Fakhruddin, S.; Kawasaki, A.; Babel, M. S.; AIT

    2013-05-01

    Early warning is a key element for disaster risk reduction. In recent decades, there has been a major advancement in medium range and seasonal forecasting. These could provide a great opportunity to improve early warning systems and advisories for early action for strategic and long term planning. This could result in increasing emphasis on proactive rather than reactive management of adverse consequences of flood events. This can be also very helpful for the agricultural sector by providing a diversity of options to farmers (e.g. changing cropping pattern, planting timing, etc.). An experimental medium range (1-10 days) flood forecasting model has been developed for Bangladesh which provides 51 set of discharge ensembles forecasts of one to ten days with significant persistence and high certainty. This could help communities (i.e. farmer) for gain/lost estimation as well as crop savings. This paper describe the application of ensembles probabilistic flood forecast at the community level for differential decision making focused on agriculture. The framework allows users to interactively specify the objectives and criteria that are germane to a particular situation, and obtain the management options that are possible, and the exogenous influences that should be taken into account before planning and decision making. risk and vulnerability assessment was conducted through community consultation. The forecast lead time requirement, users' needs, impact and management options for crops, livestock and fisheries sectors were identified through focus group discussions, informal interviews and questionnaire survey.

  9. Arctic sea ice area changes in CMIP3 and CMIP5 climate models’ ensembles

    Directory of Open Access Journals (Sweden)

    V. A. Semenov

    2017-01-01

    Full Text Available The shrinking Arctic sea ice cover observed during the last decades is probably the clearest manifestation of ongoing climate change. While climate models in general reproduce the sea ice retreat in the Arctic during the 20th century and simulate further sea ice area loss during the 21st century in response to anthropogenic forcing, the models suffer from large biases and the results exhibit considerable spread. Here, we compare results from the two last generations of climate models, CMIP3 and CMIP5, with respect to total and regional Arctic sea ice change. Different characteristics of sea ice area (SIA in March and September have been analysed for the Entire Arctic, Central Arctic and Barents Sea. Further, the sensitivity of SIA to changes in Northern Hemisphere (NH temperature is investigated and dynamical links between SIA and some atmospheric variability modes are assessed.CMIP3 (SRES A1B and CMIP5 (RCP8.5 models not only simulate a coherent decline of the Arctic SIA but also depict consistent changes in the SIA seasonal cycle. The spatial patterns of SIC variability improve in CMIP5 ensemble, most noticeably in summer when compared to HadISST1 data. A better simulation of summer SIA in the Entire Arctic by CMIP5 models is accompanied by a slightly increased bias for winter season in comparison to CMIP3 ensemble. SIA in the Barents Sea is strongly overestimated by the majority of CMIP3 and CMIP5 models, and projected SIA changes are characterized by a high uncertainty. Both CMIP ensembles depict a significant link between the SIA and NH temperature changes indicating that a part of inter-ensemble SIA spread comes from different temperature sensitivity to anthropogenic forcing. The results suggest that, in general, a sensitivity of SIA to external forcing is enhanced in CMIP5 models. Arctic SIA interannual variability in the end of the 20th century is on average well simulated by both ensembles. To the end of the 21st century, September

  10. Conservation of Mass and Preservation of Positivity with Ensemble-Type Kalman Filter Algorithms

    Science.gov (United States)

    Janjic, Tijana; Mclaughlin, Dennis; Cohn, Stephen E.; Verlaan, Martin

    2014-01-01

    This paper considers the incorporation of constraints to enforce physically based conservation laws in the ensemble Kalman filter. In particular, constraints are used to ensure that the ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. In certain situations filtering algorithms such as the ensemble Kalman filter (EnKF) and ensemble transform Kalman filter (ETKF) yield updated ensembles that conserve mass but are negative, even though the actual states must be nonnegative. In such situations if negative values are set to zero, or a log transform is introduced, the total mass will not be conserved. In this study, mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate non-negativity constraints. Simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. In two examples, an update that includes a non-negativity constraint is able to properly describe the transport of a sharp feature (e.g., a triangle or cone). A number of implementation questions still need to be addressed, particularly the need to develop a computationally efficient quadratic programming update for large ensemble.

  11. Teaching Strategies for Specialized Ensembles.

    Science.gov (United States)

    Teaching Music, 1999

    1999-01-01

    Provides a strategy, from the book "Strategies for Teaching Specialized Ensembles," that addresses Standard 9A of the National Standards for Music Education. Explains that students will identify and describe the musical and historical characteristics of the classical era in music they perform and in audio examples. (CMK)

  12. Multimodel ensembles of wheat growth

    DEFF Research Database (Denmark)

    Martre, Pierre; Wallach, Daniel; Asseng, Senthold

    2015-01-01

    , but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24...

  13. Spectral Diagonal Ensemble Kalman Filters

    Czech Academy of Sciences Publication Activity Database

    Kasanický, Ivan; Mandel, Jan; Vejmelka, Martin

    2015-01-01

    Roč. 22, č. 4 (2015), s. 485-497 ISSN 1023-5809 R&D Projects: GA ČR GA13-34856S Grant - others:NSF(US) DMS-1216481 Institutional support: RVO:67985807 Keywords : data assimilation * ensemble Kalman filter * spectral representation Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.321, year: 2015

  14. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    Marquardt algorithm by varying conditions such as inputs, hidden neurons, initialization, training sets and random Gaussian noise injection to ... Several such ensembles formed the population which was evolved to generate the fittest ensemble.

  15. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  16. Localization of atomic ensembles via superfluorescence

    International Nuclear Information System (INIS)

    Macovei, Mihai; Evers, Joerg; Keitel, Christoph H.; Zubairy, M. Suhail

    2007-01-01

    The subwavelength localization of an ensemble of atoms concentrated to a small volume in space is investigated. The localization relies on the interaction of the ensemble with a standing wave laser field. The light scattered in the interaction of the standing wave field and the atom ensemble depends on the position of the ensemble relative to the standing wave nodes. This relation can be described by a fluorescence intensity profile, which depends on the standing wave field parameters and the ensemble properties and which is modified due to collective effects in the ensemble of nearby particles. We demonstrate that the intensity profile can be tailored to suit different localization setups. Finally, we apply these results to two localization schemes. First, we show how to localize an ensemble fixed at a certain position in the standing wave field. Second, we discuss localization of an ensemble passing through the standing wave field

  17. High resolution ensemble forecasting for the Gulf of Mexico eddies and fronts

    Science.gov (United States)

    Counillon, F.; Bertino, L.

    2007-05-01

    As oil production moves further into deeper waters, the costs related to strong current hazards are increasing accordingly, and accurate three-dimensional forecasts of currents are urgently needed. To be useful, models have to locate eddies and fronts to an accuracy of 30 km at a nowcast stage, which is almost impossible to accomplish with the use of satellite data of the same accuracy. The use of stochastic forecast allows us to give confidence of our prediction. We are using a nested configuration of the Hybrid coordinate ocean model (HYCOM), where the TOPAZ system, which covers the Atlantic and the Artic, gives lateral boundary condition to a high-resolution (5km) model of the Gulf of Mexico (GOM). TOPAZ is a real-time forecasting coupled ocean-ice model, which assimilates sea level anomaly (SLA), sea surface temperature, and sea ice concentration, with the ensemble Kalman filter. The high- resolution model assimilates SLA using the ensemble optimal interpolation, which updates accordingly the currents, salinity, temperature, and layer interface at all depths. Here, we evaluate the ensemble forecast capabilities of our high-resolution model, for eddy Extreme that has been observed from altimeters around the 15th of July. We run 6 successive ensemble runs composed of 10 members of equal likelihood. Members differ by perturbations of the initial state, of the lateral boundary conditions, and of the atmospheric boundary conditions. We have started the experiment 1 month prior to the shedding event, because it was the time necessary for perturbation of boundary conditions to spread uniformly and reach a significant level across the GOM. The ensemble reproduces well the dynamics of the eddy shedding and produces a significant spread at the boundary of the eddy, but underestimates the RMS error of the SLA. Prior to the shedding time, the error growth increase, induced by the highly non-linear growth of cyclonic eddies at the boundary of the Loop Current. Additionally

  18. Squeezing of Collective Excitations in Spin Ensembles

    DEFF Research Database (Denmark)

    Kraglund Andersen, Christian; Mølmer, Klaus

    2012-01-01

    We analyse the possibility to create two-mode spin squeezed states of two separate spin ensembles by inverting the spins in one ensemble and allowing spin exchange between the ensembles via a near resonant cavity field. We investigate the dynamics of the system using a combination of numerical an...

  19. Ensemble ANNs-PSO-GA Approach for Day-ahead Stock E-exchange Prices Forecasting

    Directory of Open Access Journals (Sweden)

    Yi Xiao

    2013-02-01

    Full Text Available Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural network (GRNN and wavelet neural network (WNN are constructed by three non-overlapping training sets and are further optimized by improved particle swarm optimization (IPSO. Finally, a neural-network-based nonlinear meta-model is generated by learning three neural-network based models through support vector machines (SVM neural network. The superiority of the proposed approach lies in its flexibility to account for potentially complex nonlinear relationships. Three daily stock indices time series are used for validating the forecasting model. Empirical results suggest the ensemble ANNs-PSO-GA approach can significantly improve the prediction performance over other individual models and linear combination models listed in this study.

  20. Eigenfunction statistics of Wishart Brownian ensembles

    International Nuclear Information System (INIS)

    Shukla, Pragya

    2017-01-01

    We theoretically analyze the eigenfunction fluctuation measures for a Hermitian ensemble which appears as an intermediate state of the perturbation of a stationary ensemble by another stationary ensemble of Wishart (Laguerre) type. Similar to the perturbation by a Gaussian stationary ensemble, the measures undergo a diffusive dynamics in terms of the perturbation parameter but the energy-dependence of the fluctuations is different in the two cases. This may have important consequences for the eigenfunction dynamics as well as phase transition studies in many areas of complexity where Brownian ensembles appear. (paper)

  1. Shallow cumuli ensemble statistics for development of a stochastic parameterization

    Science.gov (United States)

    Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

    2014-05-01

    According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a

  2. Nonequilibrium statistical mechanics ensemble method

    CERN Document Server

    Eu, Byung Chan

    1998-01-01

    In this monograph, nonequilibrium statistical mechanics is developed by means of ensemble methods on the basis of the Boltzmann equation, the generic Boltzmann equations for classical and quantum dilute gases, and a generalised Boltzmann equation for dense simple fluids The theories are developed in forms parallel with the equilibrium Gibbs ensemble theory in a way fully consistent with the laws of thermodynamics The generalised hydrodynamics equations are the integral part of the theory and describe the evolution of macroscopic processes in accordance with the laws of thermodynamics of systems far removed from equilibrium Audience This book will be of interest to researchers in the fields of statistical mechanics, condensed matter physics, gas dynamics, fluid dynamics, rheology, irreversible thermodynamics and nonequilibrium phenomena

  3. Advances in sequential data assimilation and numerical weather forecasting: An Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic ensemble square root filters, and a test of a new time stepping scheme in an atmospheric model

    Science.gov (United States)

    Amezcua, Javier

    in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

  4. Can single classifiers be as useful as model ensembles to produce benthic seabed substratum maps?

    Science.gov (United States)

    Turner, Joseph A.; Babcock, Russell C.; Hovey, Renae; Kendrick, Gary A.

    2018-05-01

    Numerous machine-learning classifiers are available for benthic habitat map production, which can lead to different results. This study highlights the performance of the Random Forest (RF) classifier, which was significantly better than Classification Trees (CT), Naïve Bayes (NB), and a multi-model ensemble in terms of overall accuracy, Balanced Error Rate (BER), Kappa, and area under the curve (AUC) values. RF accuracy was often higher than 90% for each substratum class, even at the most detailed level of the substratum classification and AUC values also indicated excellent performance (0.8-1). Total agreement between classifiers was high at the broadest level of classification (75-80%) when differentiating between hard and soft substratum. However, this sharply declined as the number of substratum categories increased (19-45%) including a mix of rock, gravel, pebbles, and sand. The model ensemble, produced from the results of all three classifiers by majority voting, did not show any increase in predictive performance when compared to the single RF classifier. This study shows how a single classifier may be sufficient to produce benthic seabed maps and model ensembles of multiple classifiers.

  5. Pauci ex tanto numero: reducing redundancy in multi-model ensembles

    Science.gov (United States)

    Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

    2013-02-01

    We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date no attempts in this direction are documented within the air quality (AQ) community, although the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared biases among models will determine a biased ensemble, making therefore essential the errors of the ensemble members to be independent so that bias can cancel out. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated) we discourage selecting the members of the ensemble simply on the basis of scores, that is, independence and skills need to be considered disjointly.

  6. Benchmarking Commercial Conformer Ensemble Generators.

    Science.gov (United States)

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

    2017-11-27

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

  7. Sub-Ensemble Coastal Flood Forecasting: A Case Study of Hurricane Sandy

    Directory of Open Access Journals (Sweden)

    Justin A. Schulte

    2017-12-01

    Full Text Available In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters. After clustering the ensemble members, the ability to predict the cluster into which the observation will fall can be measured using a cluster skill score. Additional sub-ensemble and composite skill scores are proposed for assessing the forecast skill of a clustered ensemble forecast. A recently proposed method for statistically increasing the number of ensemble members is used to improve sub-ensemble probabilistic estimates. Through the application of the proposed methodology to Sandy coastal flood reforecasts, it is demonstrated that statistics computed using only ensemble members belonging to a specific cluster are more representative than those computed using all ensemble members simultaneously. A cluster skill-cluster uncertainty index relationship is identified, which is the cluster analog of the documented spread-skill relationship. Two sub-ensemble skill scores are shown to be positively correlated with cluster forecast skill, suggesting that skillfully forecasting the cluster into which the observation will fall is important to overall forecast skill. The identified relationships also suggest that the number of ensemble members within in each cluster can be used as guidance for assessing the potential for forecast error. The inevitable existence of ensemble member clusters in tidally dominated total water level prediction systems suggests that clustering is a necessary post-processing step for producing representative and skillful total water level forecasts.

  8. An Adaptive Approach to Mitigate Background Covariance Limitations in the Ensemble Kalman Filter

    KAUST Repository

    Song, Hajoon

    2010-07-01

    A new approach is proposed to address the background covariance limitations arising from undersampled ensembles and unaccounted model errors in the ensemble Kalman filter (EnKF). The method enhances the representativeness of the EnKF ensemble by augmenting it with new members chosen adaptively to add missing information that prevents the EnKF from fully fitting the data to the ensemble. The vectors to be added are obtained by back projecting the residuals of the observation misfits from the EnKF analysis step onto the state space. The back projection is done using an optimal interpolation (OI) scheme based on an estimated covariance of the subspace missing from the ensemble. In the experiments reported here, the OI uses a preselected stationary background covariance matrix, as in the hybrid EnKF–three-dimensional variational data assimilation (3DVAR) approach, but the resulting correction is included as a new ensemble member instead of being added to all existing ensemble members. The adaptive approach is tested with the Lorenz-96 model. The hybrid EnKF–3DVAR is used as a benchmark to evaluate the performance of the adaptive approach. Assimilation experiments suggest that the new adaptive scheme significantly improves the EnKF behavior when it suffers from small size ensembles and neglected model errors. It was further found to be competitive with the hybrid EnKF–3DVAR approach, depending on ensemble size and data coverage.

  9. Reduced memory skills and increased hair cortisol levels in recent Ecstasy/MDMA users: significant but independent neurocognitive and neurohormonal deficits.

    Science.gov (United States)

    Downey, Luke A; Sands, Helen; Jones, Lewis; Clow, Angela; Evans, Phil; Stalder, Tobias; Parrott, Andrew C

    2015-05-01

    The goals of this study were to measure the neurocognitive performance of recent users of recreational Ecstasy and investigate whether it was associated with the stress hormone cortisol. The 101 participants included 27 recent light users of Ecstasy (one to four times in the last 3 months), 23 recent heavier Ecstasy users (five or more times) and 51 non-users. Rivermead paragraph recall provided an objective measure for immediate and delayed recall. The prospective and retrospective memory questionnaire provided a subjective index of memory deficits. Cortisol levels were taken from near-scalp 3-month hair samples. Cortisol was significantly raised in recent heavy Ecstasy users compared with controls, whereas hair cortisol in light Ecstasy users was not raised. Both Ecstasy groups were significantly impaired on the Rivermead delayed word recall, and both groups reported significantly more retrospective and prospective memory problems. Stepwise regression confirmed that lifetime Ecstasy predicted the extent of these memory deficits. Recreational Ecstasy is associated with increased levels of the bio-energetic stress hormone cortisol and significant memory impairments. No significant relationship between cortisol and the cognitive deficits was observed. Ecstasy users did display evidence of a metacognitive deficit, with the strength of the correlations between objective and subjective memory performances being significantly lower in the Ecstasy users. Copyright © 2015 John Wiley & Sons, Ltd.

  10. Breaking of ensembles of linear and nonlinear oscillators

    International Nuclear Information System (INIS)

    Buts, V.A.

    2016-01-01

    Some results concerning the study of the dynamics of ensembles of linear and nonlinear oscillators are stated. It is shown that, in general, a stable ensemble of linear oscillator has a limited number of oscillators. This number has been defined for some simple models. It is shown that the features of the dynamics of linear oscillators can be used for conversion of the low-frequency energy oscillations into high frequency oscillations. The dynamics of coupled nonlinear oscillators in most cases is chaotic. For such a case, it is shown that the statistical characteristics (moments) of chaotic motion can significantly reduce potential barriers that keep the particles in the capture region

  11. Evaluation of LDA Ensembles Classifiers for Brain Computer Interface

    International Nuclear Information System (INIS)

    Arjona, Cristian; Pentácolo, José; Gareis, Iván; Atum, Yanina; Gentiletti, Gerardo; Acevedo, Rubén; Rufiner, Leonardo

    2011-01-01

    The Brain Computer Interface (BCI) translates brain activity into computer commands. To increase the performance of the BCI, to decode the user intentions it is necessary to get better the feature extraction and classification techniques. In this article the performance of a three linear discriminant analysis (LDA) classifiers ensemble is studied. The system based on ensemble can theoretically achieved better classification results than the individual counterpart, regarding individual classifier generation algorithm and the procedures for combine their outputs. Classic algorithms based on ensembles such as bagging and boosting are discussed here. For the application on BCI, it was concluded that the generated results using ER and AUC as performance index do not give enough information to establish which configuration is better.

  12. Measures of trajectory ensemble disparity in nonequilibrium statistical dynamics

    International Nuclear Information System (INIS)

    Crooks, Gavin E; Sivak, David A

    2011-01-01

    Many interesting divergence measures between conjugate ensembles of nonequilibrium trajectories can be experimentally determined from the work distribution of the process. Herein, we review the statistical and physical significance of several of these measures, in particular the relative entropy (dissipation), Jeffreys divergence (hysteresis), Jensen–Shannon divergence (time-asymmetry), Chernoff divergence (work cumulant generating function), and Rényi divergence

  13. Chemical Structure, Ensemble and Single-Particle Spectroscopy of Thick-Shell InP-ZnSe Quantum Dots.

    Science.gov (United States)

    Reid, Kemar R; McBride, James R; Freymeyer, Nathaniel J; Thal, Lucas B; Rosenthal, Sandra J

    2018-02-14

    Thick-shell (>5 nm) InP-ZnSe colloidal quantum dots (QDs) grown by a continuous-injection shell growth process are reported. The growth of a thick crystalline shell is attributed to the high temperature of the growth process and the relatively low lattice mismatch between the InP core and ZnSe shell. In addition to a narrow ensemble photoluminescence (PL) line-width (∼40 nm), ensemble and single-particle emission dynamics measurements indicate that blinking and Auger recombination are reduced in these heterostructures. More specifically, high single-dot ON-times (>95%) were obtained for the core-shell QDs, and measured ensemble biexciton lifetimes, τ 2x ∼ 540 ps, represent a 7-fold increase compared to InP-ZnS QDs. Further, high-resolution energy dispersive X-ray (EDX) chemical maps directly show for the first time significant incorporation of indium into the shell of the InP-ZnSe QDs. Examination of the atomic structure of the thick-shell QDs by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) reveals structural defects in subpopulations of particles that may mitigate PL efficiencies (∼40% in ensemble), providing insight toward further synthetic refinement. These InP-ZnSe heterostructures represent progress toward fully cadmium-free QDs with superior photophysical properties important in biological labeling and other emission-based technologies.

  14. Final report of a randomized trial on altered-fractionated radiotherapy in nasopharyngeal carcinoma prematurely terminated by significant increase in neurologic complications

    International Nuclear Information System (INIS)

    Teo, Peter Man Lung; Leung, Sing Fai; Chan, Anthony Tak Cheung; Leung, Thomas Wai Tong; Choi, Peter Ho Keung; Kwan, Wing Hong; Lee, Wai Yee; Chau, Ricky Ming Chun; Yu, Peter Kau Wing; Johnson, Philip James

    2000-01-01

    Purpose: The aim of the present study was to compare the survival, local control and complications of conventional/accelerated-hyperfractionated radiotherapy and conventional radiotherapy in nonmetastatic nasopharyngeal carcinoma (NPC). Methods and Materials: From February 1993 to October 1995, 159 patients with newly diagnosed nonmetastatic (M0) NPC with N0 or 4 cm or less N1 disease (Ho's N-stage classification, 1978) were randomized to receive either conventional radiotherapy (Arm I, n = 82) or conventional/accelerated-hyperfractionated radiotherapy (Arm II, n = 77). Stratification was according to the T stage. The biologic effective dose (10 Grays) to the primary and the upper cervical lymphatics were 75.0 and 73.1 for Arm I and 84.4 and 77.2 for Arm II, respectively. Results: With comparable distribution among the T stages between the two arms, the free from local failure rate at 5 years after radiotherapy was not significantly different between the two arms (85.3%; 95% confidence interval, 77.2-93.4% for Arm I; and 88.9%; 95% confidence interval, 81.7-96.2% for Arm II). The two arms were also comparable in overall survival, relapse-free survival, and rates of distant metastasis and regional relapse. Conventional/accelerated-hyperfractionated radiotherapy was associated with significantly increased radiation-induced damage to the central nervous system (including temporal lobe, cranial nerves, optic nerve/chiasma, and brainstem/spinal cord) in Arm II. Although insignificant, radiation-induced cranial nerve(s) palsy (typically involving VIII-XII), trismus, neck soft tissue fibrosis, and hypopituiturism and hypothyroidism occurred more often in Arm II. In addition, the complications occurred at significantly shorter intervals after radiotherapy in Arm II. Conclusion: Accelerated hyperfractionation when used in conjunction with a two-dimensional radiotherapy planning technique, in this case the Ho's technique, resulted in increased radiation damage to the central

  15. Editorial Commentary: Big Data Suggest That Because of a Significant Increased Risk of Postoperative Infection, Steroid Injection Is Not Recommended After Ankle Arthroscopy.

    Science.gov (United States)

    Brand, Jefferson C

    2016-02-01

    A recent study addressing infection rate after intra-articular steroid injection during ankle arthroscopy gives pause to this practice, with an odds ratio of 2.2 in the entire population that was injected with a steroid simultaneously with ankle arthroscopy compared with patients who did not receive an ankle injection. Big data, used in the study upon which the Editor comments here, suggest that because of a significant increased risk of postoperative infection, steroid injection is not recommended after ankle arthroscopy. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

  16. Prenatal prochloraz treatment significantly increases pregnancy length and reduces offspring weight but does not affect social-olfactory memory in rats

    DEFF Research Database (Denmark)

    Dmytriyeva, Oksana; Klementiev, Boris; Berezin, Vladimir

    2013-01-01

    Metabolites of the commonly used imidazole fungicide prochloraz are androgen receptor antagonists. They have been shown to block androgen-driven development and compromise reproductive function. We tested the effect of prochloraz on cognitive behavior following exposure to this fungicide during...... the perinatal period. Pregnant Wistar rats were administered a 200mg/kg dose of prochloraz on gestational day (GD) 7, GD11, and GD15. The social recognition test (SRT) was performed on 7-week-old male rat offspring. We found an increase in pregnancy length and a significantly reduced pup weight on PND15 and PND...

  17. Influence of blocking on Northern European and Western Russian heatwaves in large climate model ensembles

    Science.gov (United States)

    Schaller, N.; Sillmann, J.; Anstey, J.; Fischer, E. M.; Grams, C. M.; Russo, S.

    2018-05-01

    Better preparedness for summer heatwaves could mitigate their adverse effects on society. This can potentially be attained through an increased understanding of the relationship between heatwaves and one of their main dynamical drivers, atmospheric blocking. In the 1979–2015 period, we find that there is a significant correlation between summer heatwave magnitudes and the number of days influenced by atmospheric blocking in Northern Europe and Western Russia. Using three large global climate model ensembles, we find similar correlations, indicating that these three models are able to represent the relationship between extreme temperature and atmospheric blocking, despite having biases in their simulation of individual climate variables such as temperature or geopotential height. Our results emphasize the need to use large ensembles of different global climate models as single realizations do not always capture this relationship. The three large ensembles further suggest that the relationship between summer heatwaves and atmospheric blocking will not change in the future. This could be used to statistically model heatwaves with atmospheric blocking as a covariate and aid decision-makers in planning disaster risk reduction and adaptation to climate change.

  18. A comparative study of breast cancer diagnosis based on neural network ensemble via improved training algorithms.

    Science.gov (United States)

    Azami, Hamed; Escudero, Javier

    2015-08-01

    Breast cancer is one of the most common types of cancer in women all over the world. Early diagnosis of this kind of cancer can significantly increase the chances of long-term survival. Since diagnosis of breast cancer is a complex problem, neural network (NN) approaches have been used as a promising solution. Considering the low speed of the back-propagation (BP) algorithm to train a feed-forward NN, we consider a number of improved NN trainings for the Wisconsin breast cancer dataset: BP with momentum, BP with adaptive learning rate, BP with adaptive learning rate and momentum, Polak-Ribikre conjugate gradient algorithm (CGA), Fletcher-Reeves CGA, Powell-Beale CGA, scaled CGA, resilient BP (RBP), one-step secant and quasi-Newton methods. An NN ensemble, which is a learning paradigm to combine a number of NN outputs, is used to improve the accuracy of the classification task. Results demonstrate that NN ensemble-based classification methods have better performance than NN-based algorithms. The highest overall average accuracy is 97.68% obtained by NN ensemble trained by RBP for 50%-50% training-test evaluation method.

  19. epiDMS: Data Management and Analytics for Decision-Making From Epidemic Spread Simulation Ensembles.

    Science.gov (United States)

    Liu, Sicong; Poccia, Silvestro; Candan, K Selçuk; Chowell, Gerardo; Sapino, Maria Luisa

    2016-12-01

    Carefully calibrated large-scale computational models of epidemic spread represent a powerful tool to support the decision-making process during epidemic emergencies. Epidemic models are being increasingly used for generating forecasts of the spatial-temporal progression of epidemics at different spatial scales and for assessing the likely impact of different intervention strategies. However, the management and analysis of simulation ensembles stemming from large-scale computational models pose challenges, particularly when dealing with multiple interdependent parameters, spanning multiple layers and geospatial frames, affected by complex dynamic processes operating at different resolutions. We describe and illustrate with examples a novel epidemic simulation data management system, epiDMS, that was developed to address the challenges that arise from the need to generate, search, visualize, and analyze, in a scalable manner, large volumes of epidemic simulation ensembles and observations during the progression of an epidemic. epiDMS is a publicly available system that facilitates management and analysis of large epidemic simulation ensembles. epiDMS aims to fill an important hole in decision-making during healthcare emergencies by enabling critical services with significant economic and health impact. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

  20. Prognostic significance of repeat biopsy in lupus nephritis: Histopathologic worsening and a short time between biopsies is associated with significantly increased risk for end stage renal disease and death.

    Science.gov (United States)

    Arriens, Cristina; Chen, Sixia; Karp, David R; Saxena, Ramesh; Sambandam, Kamalanathan; Chakravarty, Eliza; James, Judith A; Merrill, Joan T

    2017-12-01

    histopathology had died compared to 2 (3.2%) of non-worsening patients. Biopsy worsening was associated with a significantly greater 15-year risk of ESRD (Hazard Ratio 4.2, p=0.0001) and death (Hazard Ratio 4.3, p=0.022), adjusting for age, gender, race, biopsy class, and treatment. Time between first and second biopsies was 5years in 28. Over a 15-year period, those with <1year between first and second biopsies (presumably enriched for patients with early clinical signs of progression) had a significantly greater risk of ESRD (Hazard Ratio 13.7, p<0.0001) and death (Hazard Ratio 16.9, p=0.0022) after adjusting for age, gender, race, biopsy class, and treatment. A repeat renal biopsy demonstrating worsening pathology increases the risk of ESRD and death more than four-fold compared to non-worsening patients. Given known potential mismatch between biopsy and clinical data, repeat biopsies may add important information and justify changes in treatment not considered on clinical grounds. Earlier detection of poor prognostic signs in those without early clinical deterioration might improve outcomes in enough patients to reconsider cost effectiveness of routine repeat biopsy. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Statistical ensembles in quantum mechanics

    International Nuclear Information System (INIS)

    Blokhintsev, D.

    1976-01-01

    The interpretation of quantum mechanics presented in this paper is based on the concept of quantum ensembles. This concept differs essentially from the canonical one by that the interference of the observer into the state of a microscopic system is of no greater importance than in any other field of physics. Owing to this fact, the laws established by quantum mechanics are not of less objective character than the laws governing classical statistical mechanics. The paradoxical nature of some statements of quantum mechanics which result from the interpretation of the wave functions as the observer's notebook greatly stimulated the development of the idea presented. (Auth.)

  2. Wind Power Prediction using Ensembles

    DEFF Research Database (Denmark)

    Giebel, Gregor; Badger, Jake; Landberg, Lars

    2005-01-01

    offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

  3. Among Metabolic Factors, Significance of Fasting and Postprandial Increases in Acyl and Desacyl Ghrelin and the Acyl/Desacyl Ratio in Obstructive Sleep Apnea before and after Treatment.

    Science.gov (United States)

    Chihara, Yuichi; Akamizu, Takashi; Azuma, Masanori; Murase, Kimihiko; Harada, Yuka; Tanizawa, Kiminobu; Handa, Tomohiro; Oga, Toru; Mishima, Michiaki; Chin, Kazuo

    2015-08-15

    There are reports suggesting that obstructive sleep apnea (OSA) may itself cause weight gain. However, recent reports showed increases in body mass index (BMI) following continuous positive airway pressure (CPAP) treatments. When considering weight changes, changes in humoral factors that have significant effects on appetite such as acyl (AG) and desacyl ghrelin (DAG), leptin, insulin, and glucose and their interactions, examples of which are AG/DAG and AG/insulin, are important. The aim of this study was to test the hypothesis that some appetite-related factors had a specific profile before and after CPAP treatment. Metabolic parameters were measured cross-sectionally while fasting and 30, 60, 90, and 120 min following breakfast in no or mild OSA (apnea-hypopnea index fasting and postprandial glucose, insulin, and leptin levels did not differ between no or mild OSA and moderate-to-severe OSA participants, AG and DAG, including AG/DAG and AG/insulin, under fasting and postprandial conditions were significantly increased in the moderate-to-severe OSA patients (p continuous changes in ghrelin secretion in OSA patients existed at least within 3 months of CPAP treatment. Methods to prevent OSA as well as treatment in its early stage may be recommended. © 2015 American Academy of Sleep Medicine.

  4. Sunitinib significantly suppresses the proliferation, migration, apoptosis resistance, tumor angiogenesis and growth of triple-negative breast cancers but increases breast cancer stem cells.

    Science.gov (United States)

    Chinchar, Edmund; Makey, Kristina L; Gibson, John; Chen, Fang; Cole, Shelby A; Megason, Gail C; Vijayakumar, Srinivassan; Miele, Lucio; Gu, Jian-Wei

    2014-01-01

    The majority of triple-negative breast cancers (TNBCs) are basal-like breast cancers. However there is no reported study on anti-tumor effects of sunitinib in xenografts of basal-like TNBC (MDA-MB-468) cells. In the present study, MDA-MB-231, MDA-MB-468, MCF-7 cells were cultured using RPMI 1640 media with 10% FBS. Vascular endothelia growth factor (VEGF) protein levels were detected using ELISA (R & D Systams). MDA-MB-468 cells were exposed to sunitinib for 18 hours for measuring proliferation (3H-thymidine incorporation), migration (BD Invasion Chamber), and apoptosis (ApopTag and ApoScreen Anuexin V Kit). The effect of sunitinib on Notch-1 expression was determined by Western blot in cultured MDA-MB-468 cells. 10(6) MDA-MB-468 cells were inoculated into the left fourth mammary gland fat pad in athymic nude-foxn1 mice. When the tumor volume reached 100 mm(3), sunitinib was given by gavage at 80 mg/kg/2 days for 4 weeks. Tumor angiogenesis was determined by CD31 immunohistochemistry. Breast cancer stem cells (CSCs) isolated from the tumors were determined by flow cytometry analysis using CD44(+)/CD24(-) or low. ELISA indicated that VEGF was much more highly expressed in MDA-MB-468 cells than MDA-MB-231 and MCF-7 cells. Sunitinib significantly inhibited the proliferation, invasion, and apoptosis resistance in cultured basal like breast cancer cells. Sunitinib significantly increased the expression of Notch-1 protein in cultured MDA-MB-468 or MDA-MB-231 cells. The xenograft models showed that oral sunitinib significantly reduced the tumor volume of TNBCs in association with the inhibition of tumor angiogeneisis, but increased breast CSCs. These findings support the hypothesis that the possibility should be considered of sunitinib increasing breast CSCs though it inhibits TNBC tumor angiogenesis and growth/progression, and that effects of sunitinib on Notch expression and hypoxia may increase breast cancer stem cells. This work provides the groundwork for an

  5. Pauci ex tanto numero: reduce redundancy in multi-model ensembles

    Science.gov (United States)

    Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

    2013-08-01

    We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date, no attempts in this direction have been documented within the air quality (AQ) community despite the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared, dependant biases among models do not cancel out but will instead determine a biased ensemble. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated), we discourage selecting the members of the ensemble simply on the basis of scores; that is, independence and skills need to be considered disjointly.

  6. EnsembleGASVR: A novel ensemble method for classifying missense single nucleotide polymorphisms

    KAUST Repository

    Rapakoulia, Trisevgeni; Theofilatos, Konstantinos A.; Kleftogiannis, Dimitrios A.; Likothanasis, Spiridon D.; Tsakalidis, Athanasios K.; Mavroudi, Seferina P.

    2014-01-01

    do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel

  7. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  8. Urban runoff forecasting with ensemble weather predictions

    DEFF Research Database (Denmark)

    Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

    This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice.......This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice....

  9. MaquiBright™ standardized maqui berry extract significantly increases tear fluid production and ameliorates dry eye-related symptoms in a clinical pilot trial.

    Science.gov (United States)

    Hitoe, S; Tanaka, J; Shimoda, H

    2014-09-01

    Dry eye symptoms, resulting from insufficient tear fluid generation, represent a considerable burden for a largely underestimated number of people. We concluded from earlier pre-clinical investigations that the etiology of dry eyes encompasses oxidative stress burden to lachrymal glands and that antioxidant MaquiBright™ Aristotelia chilensis berry extract helps restore glandular activity. In this pilot trial we investigated 13 healthy volunteers with moderately dry eyes using Schirmer test, as well as a questionnaire which allows for estimating the impact of dry eyes on daily routines. Study participants were assigned to one of two groups, receiving MaquiBright™ at daily dosage of either 30 mg (N.=7) or 60 mg (N.=6) over a period of 60 days. Both groups presented with significantly (Peye dryness on daily routines was evaluated employing the "Dry Eye-related Quality of life Score" (DEQS), with values spanning from zero (impact) to a maximum score of 60. Participants had comparable baseline values of 41.0±7.7 (30 mg) and 40.2±6.3 (60 mg). With 30 mg treatment the score significantly decreased to 21.8±3.9 and 18.9±3.9, after 30 and 60 days, respectively. With 60 mg treatment the DEQS significantly decreased to 26.9±5.3 and 11.1±2.7, after 30 and 60 days, respectively. Blood was drawn for safety analyses (complete blood rheology and -chemistry) at all three investigative time points without negative findings. In conclusion, while daily supplementation with 30 mg MaquiBright™ is effective, the dosage of 60 significantly increased tear fluid volume at all investigative time points and decreased dry eye symptoms to almost a quarter from initial values after two months treatment.

  10. The In Vitro Mass-Produced Model Mycorrhizal Fungus, Rhizophagus irregularis, Significantly Increases Yields of the Globally Important Food Security Crop Cassava

    Science.gov (United States)

    Ceballos, Isabel; Ruiz, Michael; Fernández, Cristhian; Peña, Ricardo

    2013-01-01

    The arbuscular mycorrhizal symbiosis is formed between arbuscular mycorrhizal fungi (AMF) and plant roots. The fungi provide the plant with inorganic phosphate (P). The symbiosis can result in increased plant growth. Although most global food crops naturally form this symbiosis, very few studies have shown that their practical application can lead to large-scale increases in food production. Application of AMF to crops in the tropics is potentially effective for improving yields. However, a main problem of using AMF on a large-scale is producing cheap inoculum in a clean sterile carrier and sufficiently concentrated to cheaply transport. Recently, mass-produced in vitro inoculum of the model mycorrhizal fungus Rhizophagus irregularis became available, potentially making its use viable in tropical agriculture. One of the most globally important food plants in the tropics is cassava. We evaluated the effect of in vitro mass-produced R. irregularis inoculum on the yield of cassava crops at two locations in Colombia. A significant effect of R. irregularis inoculation on yield occurred at both sites. At one site, yield increases were observed irrespective of P fertilization. At the other site, inoculation with AMF and 50% of the normally applied P gave the highest yield. Despite that AMF inoculation resulted in greater food production, economic analyses revealed that AMF inoculation did not give greater return on investment than with conventional cultivation. However, the amount of AMF inoculum used was double the recommended dose and was calculated with European, not Colombian, inoculum prices. R. irregularis can also be manipulated genetically in vitro, leading to improved plant growth. We conclude that application of in vitro R. irregularis is currently a way of increasing cassava yields, that there is a strong potential for it to be economically profitable and that there is enormous potential to improve this efficiency further in the future. PMID:23950975

  11. Addition of sodium caseinate to skim milk increases nonsedimentable casein and causes significant changes in rennet-induced gelation, heat stability, and ethanol stability.

    Science.gov (United States)

    Lin, Yingchen; Kelly, Alan L; O'Mahony, James A; Guinee, Timothy P

    2017-02-01

    The protein content of skim milk was increased from 3.3 to 4.1% (wt/wt) by the addition of a blend of skim milk powder and sodium caseinate (NaCas), in which the weight ratio of skim milk powder to NaCas was varied from 0.8:0.0 to 0.0:0.8. Addition of NaCas increased the levels of nonsedimentable casein (from ∼6 to 18% of total casein) and calcium (from ∼36 to 43% of total calcium) and reduced the turbidity of the fortified milk, to a degree depending on level of NaCas added. Rennet gelation was adversely affected by the addition of NaCas at 0.2% (wt/wt) and completely inhibited at NaCas ≥0.4% (wt/wt). Rennet-induced hydrolysis was not affected by added NaCas. The proportion of total casein that was nonsedimentable on centrifugation (3,000 × g, 1 h, 25°C) of the rennet-treated milk after incubation for 1 h at 31°C increased significantly on addition of NaCas at ≥0.4% (wt/wt). Heat stability in the pH range 6.7 to 7.2 and ethanol stability at pH 6.4 were enhanced by the addition of NaCas. It is suggested that the negative effect of NaCas on rennet gelation is due to the increase in nonsedimentable casein, which upon hydrolysis by chymosin forms into small nonsedimentable particles that physically come between, and impede the aggregation of, rennet-altered para-casein micelles, and thereby inhibit the development of a gel network. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  12. The in vitro mass-produced model mycorrhizal fungus, Rhizophagus irregularis, significantly increases yields of the globally important food security crop cassava.

    Directory of Open Access Journals (Sweden)

    Isabel Ceballos

    Full Text Available The arbuscular mycorrhizal symbiosis is formed between arbuscular mycorrhizal fungi (AMF and plant roots. The fungi provide the plant with inorganic phosphate (P. The symbiosis can result in increased plant growth. Although most global food crops naturally form this symbiosis, very few studies have shown that their practical application can lead to large-scale increases in food production. Application of AMF to crops in the tropics is potentially effective for improving yields. However, a main problem of using AMF on a large-scale is producing cheap inoculum in a clean sterile carrier and sufficiently concentrated to cheaply transport. Recently, mass-produced in vitro inoculum of the model mycorrhizal fungus Rhizophagus irregularis became available, potentially making its use viable in tropical agriculture. One of the most globally important food plants in the tropics is cassava. We evaluated the effect of in vitro mass-produced R. irregularis inoculum on the yield of cassava crops at two locations in Colombia. A significant effect of R. irregularis inoculation on yield occurred at both sites. At one site, yield increases were observed irrespective of P fertilization. At the other site, inoculation with AMF and 50% of the normally applied P gave the highest yield. Despite that AMF inoculation resulted in greater food production, economic analyses revealed that AMF inoculation did not give greater return on investment than with conventional cultivation. However, the amount of AMF inoculum used was double the recommended dose and was calculated with European, not Colombian, inoculum prices. R. irregularis can also be manipulated genetically in vitro, leading to improved plant growth. We conclude that application of in vitro R. irregularis is currently a way of increasing cassava yields, that there is a strong potential for it to be economically profitable and that there is enormous potential to improve this efficiency further in the future.

  13. Prognostic Significance of Creatinine Increases During an Acute Heart Failure Admission in Patients With and Without Residual Congestion: A Post Hoc Analysis of the PROTECT Data.

    Science.gov (United States)

    Metra, Marco; Cotter, Gad; Senger, Stefanie; Edwards, Christopher; Cleland, John G; Ponikowski, Piotr; Cursack, Guillermo C; Milo, Olga; Teerlink, John R; Givertz, Michael M; O'Connor, Christopher M; Dittrich, Howard C; Bloomfield, Daniel M; Voors, Adriaan A; Davison, Beth A

    2018-05-01

    The importance of a serum creatinine increase, traditionally considered worsening renal function (WRF), during admission for acute heart failure has been recently debated, with data suggesting an interaction between congestion and creatinine changes. In post hoc analyses, we analyzed the association of WRF with length of hospital stay, 30-day death or cardiovascular/renal readmission and 90-day mortality in the PROTECT study (Placebo-Controlled Randomized Study of the Selective A1 Adenosine Receptor Antagonist Rolofylline for Patients Hospitalized With Acute Decompensated Heart Failure and Volume Overload to Assess Treatment Effect on Congestion and Renal Function). Daily creatinine changes from baseline were categorized as WRF (an increase of 0.3 mg/dL or more) or not. Daily congestion scores were computed by summing scores for orthopnea, edema, and jugular venous pressure. Of the 2033 total patients randomized, 1537 patients had both available at study day 14. Length of hospital stay was longer and 30-day cardiovascular/renal readmission or death more common in patients with WRF. However, these were driven by significant associations in patients with concomitant congestion at the time of assessment of renal function. The mean difference in length of hospital stay because of WRF was 3.51 (95% confidence interval, 1.29-5.73) more days ( P =0.0019), and the hazard ratio for WRF on 30-day death or heart failure hospitalization was 1.49 (95% confidence interval, 1.06-2.09) times higher ( P =0.0205), in significantly congested than nonsignificantly congested patients. A similar trend was observed with 90-day mortality although not statistically significant. In patients admitted for acute heart failure, WRF defined as a creatinine increase of ≥0.3 mg/dL was associated with longer length of hospital stay, and worse 30- and 90-day outcomes. However, effects were largely driven by patients who had residual congestion at the time of renal function assessment. URL: https

  14. In vivo topical application of acetyl aspartic acid increases fibrillin-1 and collagen IV deposition leading to a significant improvement of skin firmness.

    Science.gov (United States)

    Gillbro, J M; Merinville, E; Cattley, K; Al-Bader, T; Hagforsen, E; Nilsson, M; Mavon, A

    2015-10-01

    Acetyl aspartic acid (A-A-A) was discovered through gene array analysis with corresponding Cmap analysis. We found that A-A-A increased keratinocyte regeneration, inhibited dermal matrix metalloprotease (MMP) expression and relieved fibroblast stiffness through reduction of the fibroblast stiffness marker F-actin. Dermal absorption studies showed successful delivery to both the epidermal and dermal regions, and in-use trial demonstrated that 1% A-A-A was well tolerated. In this study, the aim was to investigate whether A-A-A could stimulate the synthesis of extracellular matrix supporting proteins in vivo and thereby improving the viscoelastic properties of human skin by conducting a dual histological and biophysical clinical study. Two separate double-blind vehicle-controlled in vivo studies were conducted using a 1% A-A-A containing oil-in-water (o/w) emulsion. In the histological study, 16 female volunteers (>55 years of age) exhibiting photodamaged skin on their forearm were included, investigating the effect of a 12-day treatment of A-A-A on collagen IV (COLIV) and fibrillin-1. In a subsequent pilot study, 0.1% retinol was used for comparison to A-A-A (1%). The biomechanical properties of the skin were assessed in a panel of 16 women (>45 years of age) using the standard Cutometer MPA580 after topical application of the test products for 28 days. The use of multiple suction enabled the assessment of F4, an area parameter specifically representing skin firmness. Twelve-day topical application of 1% A-A-A significantly increased COLIV and fibrillin with 13% and 6%, respectively, compared to vehicle. 1% A-A-A and 0.1% retinol were found to significantly reduce F4 after 28 days of treatment by 15.8% and 14.7%, respectively, in the pilot Cutometer study. No significant difference was found between retinol and A-A-A. However, only A-A-A exhibited a significant effect vs. vehicle on skin firmness which indicated the incremental benefit of A-A-A as a skin

  15. Joys of Community Ensemble Playing: The Case of the Happy Roll Elastic Ensemble in Taiwan

    Science.gov (United States)

    Hsieh, Yuan-Mei; Kao, Kai-Chi

    2012-01-01

    The Happy Roll Elastic Ensemble (HREE) is a community music ensemble supported by Tainan Culture Centre in Taiwan. With enjoyment and friendship as its primary goals, it aims to facilitate the joys of ensemble playing and the spirit of social networking. This article highlights the key aspects of HREE's development in its first two years…

  16. Ensemble of regional climate model projections for Ireland

    Science.gov (United States)

    Nolan, Paul; McGrath, Ray

    2016-04-01

    of over 35 days per year. Results show significant projected decreases in mean annual, spring and summer precipitation amounts by mid-century. The projected decreases are largest for summer, with "likely" reductions ranging from 0% to 20%. The frequencies of heavy precipitation events show notable increases (approximately 20%) during the winter and autumn months. The number of extended dry periods is projected to increase substantially during autumn and summer. Regional variations of projected precipitation change remain statistically elusive. The energy content of the wind is projected to significantly decrease for the future spring, summer and autumn months. Projected increases for winter were found to be statistically insignificant. The projected decreases were largest for summer, with "likely" values ranging from 3% to 15%. Results suggest that the tracks of intense storms are projected to extend further south over Ireland relative to those in the reference simulation. As extreme storm events are rare, the storm-tracking research needs to be extended. Future work will focus on analysing a larger ensemble, thus allowing a robust statistical analysis of extreme storm track projections.

  17. Prenatal prochloraz treatment significantly increases pregnancy length and reduces offspring weight but does not affect social-olfactory memory in rats.

    Science.gov (United States)

    Dmytriyeva, Oksana; Klementiev, Boris; Berezin, Vladimir; Bock, Elisabeth

    2013-07-01

    Metabolites of the commonly used imidazole fungicide prochloraz are androgen receptor antagonists. They have been shown to block androgen-driven development and compromise reproductive function. We tested the effect of prochloraz on cognitive behavior following exposure to this fungicide during the perinatal period. Pregnant Wistar rats were administered a 200 mg/kg dose of prochloraz on gestational day (GD) 7, GD11, and GD15. The social recognition test (SRT) was performed on 7-week-old male rat offspring. We found an increase in pregnancy length and a significantly reduced pup weight on PND15 and PND40 but no effect of prenatal prochloraz exposure on social investigation or acquisition of social-olfactory memory. Copyright © 2012 Elsevier GmbH. All rights reserved.

  18. On the structure and phase transitions of power-law Poissonian ensembles

    Science.gov (United States)

    Eliazar, Iddo; Oshanin, Gleb

    2012-10-01

    Power-law Poissonian ensembles are Poisson processes that are defined on the positive half-line, and that are governed by power-law intensities. Power-law Poissonian ensembles are stochastic objects of fundamental significance; they uniquely display an array of fractal features and they uniquely generate a span of important applications. In this paper we apply three different methods—oligarchic analysis, Lorenzian analysis and heterogeneity analysis—to explore power-law Poissonian ensembles. The amalgamation of these analyses, combined with the topology of power-law Poissonian ensembles, establishes a detailed and multi-faceted picture of the statistical structure and the statistical phase transitions of these elemental ensembles.

  19. Long-term use of amiodarone before heart transplantation significantly reduces early post-transplant atrial fibrillation and is not associated with increased mortality after heart transplantation

    Directory of Open Access Journals (Sweden)

    Rivinius R

    2016-02-01

    group (P=0.0123. There was no statistically significant difference between patients with and without long-term use of amiodarone prior to HTX in 1-year (P=0.8596, 2-year (P=0.8620, 5-year (P=0.2737, or overall follow-up mortality after HTX (P=0.1049. Moreover, Kaplan–Meier survival analysis showed no statistically significant difference in overall survival (P=0.1786.Conclusion: Long-term use of amiodarone in patients before HTX significantly reduces early post-transplant AF and is not associated with increased mortality after HTX. Keywords: amiodarone, atrial fibrillation, heart failure, heart transplantation, mortality

  20. Ensemble modeling for aromatic production in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Matthew L Rizk

    2009-09-01

    Full Text Available Ensemble Modeling (EM is a recently developed method for metabolic modeling, particularly for utilizing the effect of enzyme tuning data on the production of a specific compound to refine the model. This approach is used here to investigate the production of aromatic products in Escherichia coli. Instead of using dynamic metabolite data to fit a model, the EM approach uses phenotypic data (effects of enzyme overexpression or knockouts on the steady state production rate to screen possible models. These data are routinely generated during strain design. An ensemble of models is constructed that all reach the same steady state and are based on the same mechanistic framework at the elementary reaction level. The behavior of the models spans the kinetics allowable by thermodynamics. Then by using existing data from the literature for the overexpression of genes coding for transketolase (Tkt, transaldolase (Tal, and phosphoenolpyruvate synthase (Pps to screen the ensemble, we arrive at a set of models that properly describes the known enzyme overexpression phenotypes. This subset of models becomes more predictive as additional data are used to refine the models. The final ensemble of models demonstrates the characteristic of the cell that Tkt is the first rate controlling step, and correctly predicts that only after Tkt is overexpressed does an increase in Pps increase the production rate of aromatics. This work demonstrates that EM is able to capture the result of enzyme overexpression on aromatic producing bacteria by successfully utilizing routinely generated enzyme tuning data to guide model learning.

  1. A study of fuzzy logic ensemble system performance on face recognition problem

    Science.gov (United States)

    Polyakova, A.; Lipinskiy, L.

    2017-02-01

    Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

  2. Loading of the knee during 3.0 T MRI is associated with significantly increased medial meniscus extrusion in mild and moderate osteoarthritis

    Energy Technology Data Exchange (ETDEWEB)

    Stehling, Christoph, E-mail: christoph.stehling@radiology.ucsf.edu [Musculoskeletal and Quantitative Imaging Group (MQIR), Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA (United States); Department of Clinical Radiology, University of Muenster, Muenster (Germany); Souza, Richard B. [Musculoskeletal and Quantitative Imaging Group (MQIR), Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA (United States); Graverand, Marie-Pierre Hellio Le; Wyman, Bradley T. [Pfizer Inc. New London, CT (United States); Li, Xiaojuan; Majumdar, Sharmila; Link, Thomas M. [Musculoskeletal and Quantitative Imaging Group (MQIR), Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA (United States)

    2012-08-15

    Purpose: Standard knee MRI is performed under unloading (ULC) conditions and not much is known about changes of the meniscus, ligaments or cartilage under loading conditions (LC). The aim is to study the influence of loading of different knee structures at 3 Tesla (T) in subjects with osteoarthritis (OA) and normal controls. Materials and methods: 30 subjects, 10 healthy and 20 with radiographic evidence of OA (10 mild and 10 moderate) underwent 3 T MRI under ULC and LC at 50% body weight. All images were analyzed by two musculoskeletal radiologists identifying and grading cartilage, meniscal, ligamentous abnormalities. The changes between ULC and LC were assessed. For meniscus, cartilage and ligaments the changes of lesions, signal and shape were evaluated. In addition, for the meniscus changes in extrusion were examined. A multivariate regression model was used for correlations to correct the data for the impact of age, gender, BMI. A paired T-Test was performed to calculate the differences in meniscus extrusion. Results: Subjects with degenerative knee abnormalities demonstrated significantly increased meniscus extrusion under LC when compared to normal subjects (p = 0.0008-0.0027). Subjects with knee abnormalities and higher KL scores showed significantly more changes in lesion, signal and shape of the meniscus (80% (16/20) vs. 20% (2/10); p = 0.0025), ligaments and cartilage during LC. Conclusion: The study demonstrates that axial loading has an effect on articular cartilage, ligament, and meniscus morphology, which is more significant in subjects with degenerative disease and may serve as an additional diagnostic tool for disease diagnosis and assessing progression in subjects with knee OA.

  3. Loading of the knee during 3.0 T MRI is associated with significantly increased medial meniscus extrusion in mild and moderate osteoarthritis

    International Nuclear Information System (INIS)

    Stehling, Christoph; Souza, Richard B.; Graverand, Marie-Pierre Hellio Le; Wyman, Bradley T.; Li, Xiaojuan; Majumdar, Sharmila; Link, Thomas M.

    2012-01-01

    Purpose: Standard knee MRI is performed under unloading (ULC) conditions and not much is known about changes of the meniscus, ligaments or cartilage under loading conditions (LC). The aim is to study the influence of loading of different knee structures at 3 Tesla (T) in subjects with osteoarthritis (OA) and normal controls. Materials and methods: 30 subjects, 10 healthy and 20 with radiographic evidence of OA (10 mild and 10 moderate) underwent 3 T MRI under ULC and LC at 50% body weight. All images were analyzed by two musculoskeletal radiologists identifying and grading cartilage, meniscal, ligamentous abnormalities. The changes between ULC and LC were assessed. For meniscus, cartilage and ligaments the changes of lesions, signal and shape were evaluated. In addition, for the meniscus changes in extrusion were examined. A multivariate regression model was used for correlations to correct the data for the impact of age, gender, BMI. A paired T-Test was performed to calculate the differences in meniscus extrusion. Results: Subjects with degenerative knee abnormalities demonstrated significantly increased meniscus extrusion under LC when compared to normal subjects (p = 0.0008–0.0027). Subjects with knee abnormalities and higher KL scores showed significantly more changes in lesion, signal and shape of the meniscus (80% (16/20) vs. 20% (2/10); p = 0.0025), ligaments and cartilage during LC. Conclusion: The study demonstrates that axial loading has an effect on articular cartilage, ligament, and meniscus morphology, which is more significant in subjects with degenerative disease and may serve as an additional diagnostic tool for disease diagnosis and assessing progression in subjects with knee OA.

  4. Nonlocal inhomogeneous broadening in plasmonic nanoparticle ensembles

    DEFF Research Database (Denmark)

    Tserkezis, Christos; Maack, Johan Rosenkrantz; Liu, Z.

    Nonclassical effects are increasingly more relevant in plasmonics as modern nanofabrication techniques rapidly approach the extreme nanoscale limits, for which departing from classical electrodynamics becomes important. One of the largest-scale necessary corrections towards this direction...... is to abandon the local response approximation (LRA) and take the nonlocal response of the metal into account, typically through the simple hydrodynamic Drude model (HDM), which predicts a sizedependent deviation of plasmon modes from the quasistatic (QS) limit. While this behaviour has been explored for simple...... metallic nanoparticles (NPs) or NP dimers, the possibility of inhomogeneous resonance broadening due to size variation in a large NP collection and the resulting spectral overlap of modes (as depicted in Fig. 1), has been so far overlooked. Here we study theoretically the effect of nonlocality on ensemble...

  5. Global Optimization Ensemble Model for Classification Methods

    Science.gov (United States)

    Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab

    2014-01-01

    Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382

  6. Global Optimization Ensemble Model for Classification Methods

    Directory of Open Access Journals (Sweden)

    Hina Anwar

    2014-01-01

    Full Text Available Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity.

  7. An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting

    Directory of Open Access Journals (Sweden)

    F. Anctil

    2009-11-01

    Full Text Available Hydrological forecasting consists in the assessment of future streamflow. Current deterministic forecasts do not give any information concerning the uncertainty, which might be limiting in a decision-making process. Ensemble forecasts are expected to fill this gap.

    In July 2007, the Meteorological Service of Canada has improved its ensemble prediction system, which has been operational since 1998. It uses the GEM model to generate a 20-member ensemble on a 100 km grid, at mid-latitudes. This improved system is used for the first time for hydrological ensemble predictions. Five watersheds in Quebec (Canada are studied: Chaudière, Châteauguay, Du Nord, Kénogami and Du Lièvre. An interesting 17-day rainfall event has been selected in October 2007. Forecasts are produced in a 3 h time step for a 3-day forecast horizon. The deterministic forecast is also available and it is compared with the ensemble ones. In order to correct the bias of the ensemble, an updating procedure has been applied to the output data. Results showed that ensemble forecasts are more skilful than the deterministic ones, as measured by the Continuous Ranked Probability Score (CRPS, especially for 72 h forecasts. However, the hydrological ensemble forecasts are under dispersed: a situation that improves with the increasing length of the prediction horizons. We conjecture that this is due in part to the fact that uncertainty in the initial conditions of the hydrological model is not taken into account.

  8. Symmetric dimeric bisbenzimidazoles DBP(n reduce methylation of RARB and PTEN while significantly increase methylation of rRNA genes in MCF-7 cancer cells.

    Directory of Open Access Journals (Sweden)

    Svetlana V Kostyuk

    Full Text Available Hypermethylation is observed in the promoter regions of suppressor genes in the tumor cancer cells. Reactivation of these genes by demethylation of their promoters is a prospective strategy of the anticancer therapy. Previous experiments have shown that symmetric dimeric bisbenzimidazoles DBP(n are able to block DNA methyltransferase activities. It was also found that DBP(n produces a moderate effect on the activation of total gene expression in HeLa-TI population containing epigenetically repressed avian sarcoma genome.It is shown that DBP(n are able to penetrate the cellular membranes and accumulate in breast carcinoma cell MCF-7, mainly in the mitochondria and in the nucleus, excluding the nucleolus. The DBP(n are non-toxic to the cells and have a weak overall demethylation effect on genomic DNA. DBP(n demethylate the promoter regions of the tumor suppressor genes PTEN and RARB. DBP(n promotes expression of the genes RARB, PTEN, CDKN2A, RUNX3, Apaf-1 and APC "silent" in the MCF-7 because of the hypermethylation of their promoter regions. Simultaneously with the demethylation of the DNA in the nucleus a significant increase in the methylation level of rRNA genes in the nucleolus was detected. Increased rDNA methylation correlated with a reduction of the rRNA amount in the cells by 20-30%. It is assumed that during DNA methyltransferase activity inhibition by the DBP(n in the nucleus, the enzyme is sequestered in the nucleolus and provides additional methylation of the rDNA that are not shielded by DBP(n.It is concluded that DBP (n are able to accumulate in the nucleus (excluding the nucleolus area and in the mitochondria of cancer cells, reducing mitochondrial potential. The DBP (n induce the demethylation of a cancer cell's genome, including the demethylation of the promoters of tumor suppressor genes. DBP (n significantly increase the methylation of ribosomal RNA genes in the nucleoli. Therefore the further study of these compounds is needed

  9. Risk assessments of regional climate change over Europe: generation of probabilistic ensemble and uncertainty assessment for EURO-CODEX

    Science.gov (United States)

    Yuan, J.; Kopp, R. E.

    2017-12-01

    Quantitative risk analysis of regional climate change is crucial for risk management and impact assessment of climate change. Two major challenges to assessing the risks of climate change are: CMIP5 model runs, which drive EURO-CODEX downscaling runs, do not cover the full range of uncertainty of future projections; Climate models may underestimate the probability of tail risks (i.e. extreme events). To overcome the difficulties, this study offers a viable avenue, where a set of probabilistic climate ensemble is generated using the Surrogate/Model Mixed Ensemble (SMME) method. The probabilistic ensembles for temperature and precipitation are used to assess the range of uncertainty covered by five bias-corrected simulations from the high-resolution (0.11º) EURO-CODEX database, which are selected by the PESETA (The Projection of Economic impacts of climate change in Sectors of the European Union based on bottom-up Analysis) III project. Results show that the distribution of SMME ensemble is notably wider than both distribution of raw ensemble of GCMs and the spread of the five EURO-CORDEX in RCP8.5. Tail risks are well presented by the SMME ensemble. Both SMME ensemble and EURO-CORDEX projections are aggregated to administrative level, and are integrated into impact functions of PESETA III to assess climate risks in Europe. To further evaluate the uncertainties introduced by the downscaling process, we compare the 5 runs from EURO-CORDEX with runs from the corresponding GCMs. Time series of regional mean, spatial patterns, and climate indices are examined for the future climate (2080-2099) deviating from the present climate (1981-2010). The downscaling processes do not appear to be trend-preserving, e.g. the increase in regional mean temperature from EURO-CORDEX is slower than that from the corresponding GCM. The spatial pattern comparison reveals that the differences between each pair of GCM and EURO-CORDEX are small in winter. In summer, the temperatures of EURO

  10. Popular Music and the Instrumental Ensemble.

    Science.gov (United States)

    Boespflug, George

    1999-01-01

    Discusses popular music, the role of the musical performer as a creator, and the styles of jazz and popular music. Describes the pop ensemble at the college level, focusing on improvisation, rehearsals, recording, and performance. Argues that pop ensembles be used in junior and senior high school. (CMK)

  11. Layered Ensemble Architecture for Time Series Forecasting.

    Science.gov (United States)

    Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

    2016-01-01

    Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

  12. Ensemble methods for seasonal limited area forecasts

    DEFF Research Database (Denmark)

    Arritt, Raymond W.; Anderson, Christopher J.; Takle, Eugene S.

    2004-01-01

    The ensemble prediction methods used for seasonal limited area forecasts were examined by comparing methods for generating ensemble simulations of seasonal precipitation. The summer 1993 model over the north-central US was used as a test case. The four methods examined included the lagged-average...

  13. PARP-1 depletion in combination with carbon ion exposure significantly reduces MMPs activity and overall increases TIMPs expression in cultured HeLa cells

    International Nuclear Information System (INIS)

    Ghorai, Atanu; Sarma, Asitikantha; Chowdhury, Priyanka; Ghosh, Utpal

    2016-01-01

    Hadron therapy is an innovative technique where cancer cells are precisely killed leaving surrounding healthy cells least affected by high linear energy transfer (LET) radiation like carbon ion beam. Anti-metastatic effect of carbon ion exposure attracts investigators into the field of hadron biology, although details remain poor. Poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors are well-known radiosensitizer and several PARP-1 inhibitors are in clinical trial. Our previous studies showed that PARP-1 depletion makes the cells more radiosensitive towards carbon ion than gamma. The purpose of the present study was to investigate combining effects of PARP-1 inhibition with carbon ion exposure to control metastatic properties in HeLa cells. Activities of matrix metalloproteinases-2, 9 (MMP-2, MMP-9) were measured using the gelatin zymography after 85 MeV carbon ion exposure or gamma irradiation (0- 4 Gy) to compare metastatic potential between PARP-1 knock down (HsiI) and control cells (H-vector - HeLa transfected with vector without shRNA construct). Expression of MMP-2, MMP-9, tissue inhibitor of MMPs such as TIMP-1, TIMP-2 and TIMP-3 were checked by immunofluorescence and western blot. Cell death by trypan blue, apoptosis and autophagy induction were studied after carbon ion exposure in each cell-type. The data was analyzed using one way ANOVA and 2-tailed paired-samples T-test. PARP-1 silencing significantly reduced MMP-2 and MMP-9 activities and carbon ion exposure further diminished their activities to less than 3 % of control H-vector. On the contrary, gamma radiation enhanced both MMP-2 and MMP-9 activities in H-vector but not in HsiI cells. The expression of MMP-2 and MMP-9 in H-vector and HsiI showed different pattern after carbon ion exposure. All three TIMPs were increased in HsiI, whereas only TIMP-1 was up-regulated in H-vector after irradiation. Notably, the expressions of all TIMPs were significantly higher in HsiI than H-vector at 4 Gy. Apoptosis was

  14. Treatment of rheumatoid arthritis with tumor necrosis factor inhibitors may predispose to significant increase in tuberculosis risk: a multicenter active-surveillance report.

    Science.gov (United States)

    Gómez-Reino, Juan J; Carmona, Loreto; Valverde, Vicente Rodríguez; Mola, Emilio Martín; Montero, Maria Dolores

    2003-08-01

    The long-term safety of therapeutic agents that neutralize tumor necrosis factor (TNF) is uncertain. Recent evidence based on spontaneous reporting shows an association with active tuberculosis (TB). We undertook this study to determine and describe the long-term safety of 2 of these agents, infliximab and etanercept, in rheumatic diseases based on a national active-surveillance system following the commercialization of the drugs. We analyzed the safety data actively collected in the BIOBADASER (Base de Datos de Productos Biológicos de la Sociedad Española de Reumatología) database, which was launched in February 2000 by the Spanish Society of Rheumatology. For the estimation of TB risk, the annual incidence rate in patients treated with these agents was compared with the background rate and with the rate in a cohort of patients with rheumatoid arthritis (RA) assembled before the era of anti-TNF treatment. Seventy-one participating centers sent data on 1,578 treatments with infliximab (86%) or etanercept (14%) in 1,540 patients. Drug survival rates (reported as the cumulative percentage of patients still receiving medication) for infliximab and etanercept pooled together were 85% and 81% at 1 year and 2 years, respectively. Instances of discontinuation were essentially due to adverse events. Seventeen cases of TB were found in patients treated with infliximab. The estimated incidence of TB associated with infliximab in RA patients was 1,893 per 100,000 in the year 2000 and 1,113 per 100,000 in the year 2001. These findings represent a significant increased risk compared with background rates. In the first 5 months of 2002, after official guidelines were established for TB prevention in patients treated with biologics, only 1 new TB case was registered (in January). Therapy with infliximab is associated with an increased risk of active TB. Proper measures are needed to prevent and manage this adverse event.

  15. Dephytinisation with Intrinsic Wheat Phytase and Iron Fortification Significantly Increase Iron Absorption from Fonio (Digitaria exilis) Meals in West African Women

    Science.gov (United States)

    Moretti, Diego; Schuth, Stephan; Egli, Ines; Zimmermann, Michael B.; Brouwer, Inge D.

    2013-01-01

    Low iron and high phytic acid content make fonio based meals a poor source of bioavailable iron. Phytic acid degradation in fonio porridge using whole grain cereals as phytase source and effect on iron bioavailability when added to iron fortified fonio meals were investigated. Grains, nuts and seeds collected in Mali markets were screened for phytic acid and phytase activity. We performed an iron absorption study in Beninese women (n = 16), using non-dephytinised fonio porridge (FFP) and dephytinised fonio porridge (FWFP; 75% fonio-25% wheat), each fortified with 57Fe or 58Fe labeled FeSO4. Iron absorption was quantified by measuring the erythrocyte incorporation of stable iron isotopes. Phytic acid varied from 0.39 (bambara nut) to 4.26 g/100 g DM (pumpkin seed), with oilseeds values higher than grains and nuts. Phytase activity ranged from 0.17±1.61 (fonio) to 2.9±1.3 phytase unit (PU) per g (whole wheat). Phytic acid was almost completely degraded in FWFP after 60 min of incubation (pH≈5.0, 50°C). Phytate∶iron molar ratios decreased from 23.7∶1 in FFP to 2.7∶1 in FWFP. Iron fortification further reduced phytate∶iron molar ratio to 1.9∶1 in FFP and 0.3∶1 in FWFP, respectively. Geometric mean (95% CI) iron absorption significantly increased from 2.6% (0.8–7.8) in FFP to 8.3% (3.8–17.9) in FWFP (Pphytase increased fractional iron absorption 3.2 times, suggesting it could be a possible strategy to decrease PA in cereal-based porridges. PMID:24124445

  16. Exploiting ensemble learning for automatic cataract detection and grading.

    Science.gov (United States)

    Yang, Ji-Jiang; Li, Jianqiang; Shen, Ruifang; Zeng, Yang; He, Jian; Bi, Jing; Li, Yong; Zhang, Qinyan; Peng, Lihui; Wang, Qing

    2016-02-01

    Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a barrier to early intervention due to underlying costs. To date, studies reported in the literature utilize a single learning model for retinal image classification in grading cataract severity. We present an ensemble learning based approach as a means to improving diagnostic accuracy. Three independent feature sets, i.e., wavelet-, sketch-, and texture-based features, are extracted from each fundus image. For each feature set, two base learning models, i.e., Support Vector Machine and Back Propagation Neural Network, are built. Then, the ensemble methods, majority voting and stacking, are investigated to combine the multiple base learning models for final fundus image classification. Empirical experiments are conducted for cataract detection (two-class task, i.e., cataract or non-cataractous) and cataract grading (four-class task, i.e., non-cataractous, mild, moderate or severe) tasks. The best performance of the ensemble classifier is 93.2% and 84.5% in terms of the correct classification rates for cataract detection and grading tasks, respectively. The results demonstrate that the ensemble classifier outperforms the single learning model significantly, which also illustrates the effectiveness of the proposed approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  17. Topological quantization of ensemble averages

    International Nuclear Information System (INIS)

    Prodan, Emil

    2009-01-01

    We define the current of a quantum observable and, under well-defined conditions, we connect its ensemble average to the index of a Fredholm operator. The present work builds on a formalism developed by Kellendonk and Schulz-Baldes (2004 J. Funct. Anal. 209 388) to study the quantization of edge currents for continuous magnetic Schroedinger operators. The generalization given here may be a useful tool to scientists looking for novel manifestations of the topological quantization. As a new application, we show that the differential conductance of atomic wires is given by the index of a certain operator. We also comment on how the formalism can be used to probe the existence of edge states

  18. Characterizing Ensembles of Superconducting Qubits

    Science.gov (United States)

    Sears, Adam; Birenbaum, Jeff; Hover, David; Rosenberg, Danna; Weber, Steven; Yoder, Jonilyn L.; Kerman, Jamie; Gustavsson, Simon; Kamal, Archana; Yan, Fei; Oliver, William

    We investigate ensembles of up to 48 superconducting qubits embedded within a superconducting cavity. Such arrays of qubits have been proposed for the experimental study of Ising Hamiltonians, and efficient methods to characterize and calibrate these types of systems are still under development. Here we leverage high qubit coherence (> 70 μs) to characterize individual devices as well as qubit-qubit interactions, utilizing the common resonator mode for a joint readout. This research was funded by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) under Air Force Contract No. FA8721-05-C-0002. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of ODNI, IARPA, or the US Government.

  19. Preliminary Assessment of Tecplot Chorus for Analyzing Ensemble of CTH Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Agelastos, Anthony Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stevenson, Joel O. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Attaway, Stephen W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Peterson, David

    2015-04-01

    The exploration of large parameter spaces in search of problem solution and uncertainty quantifcation produces very large ensembles of data. Processing ensemble data will continue to require more resources as simulation complexity and HPC platform throughput increase. More tools are needed to help provide rapid insight into these data sets to decrease manual processing time by the analyst and to increase knowledge the data can provide. One such tool is Tecplot Chorus, whose strengths are visualizing ensemble metadata and linked images. This report contains the analysis and conclusions from evaluating Tecplot Chorus with an example problem that is relevant to Sandia National Laboratories.

  20. Enhancing COSMO-DE ensemble forecasts by inexpensive techniques

    Directory of Open Access Journals (Sweden)

    Zied Ben Bouallègue

    2013-02-01

    Full Text Available COSMO-DE-EPS, a convection-permitting ensemble prediction system based on the high-resolution numerical weather prediction model COSMO-DE, is pre-operational since December 2010, providing probabilistic forecasts which cover Germany. This ensemble system comprises 20 members based on variations of the lateral boundary conditions, the physics parameterizations and the initial conditions. In order to increase the sample size in a computationally inexpensive way, COSMO-DE-EPS is combined with alternative ensemble techniques: the neighborhood method and the time-lagged approach. Their impact on the quality of the resulting probabilistic forecasts is assessed. Objective verification is performed over a six months period, scores based on the Brier score and its decomposition are shown for June 2011. The combination of the ensemble system with the alternative approaches improves probabilistic forecasts of precipitation in particular for high precipitation thresholds. Moreover, combining COSMO-DE-EPS with only the time-lagged approach improves the skill of area probabilities for precipitation and does not deteriorate the skill of 2 m-temperature and wind gusts forecasts.

  1. Tweet-based Target Market Classification Using Ensemble Method

    Directory of Open Access Journals (Sweden)

    Muhammad Adi Khairul Anshary

    2016-09-01

    Full Text Available Target market classification is aimed at focusing marketing activities on the right targets. Classification of target markets can be done through data mining and by utilizing data from social media, e.g. Twitter. The end result of data mining are learning models that can classify new data. Ensemble methods can improve the accuracy of the models and therefore provide better results. In this study, classification of target markets was conducted on a dataset of 3000 tweets in order to extract features. Classification models were constructed to manipulate the training data using two ensemble methods (bagging and boosting. To investigate the effectiveness of the ensemble methods, this study used the CART (classification and regression tree algorithm for comparison. Three categories of consumer goods (computers, mobile phones and cameras and three categories of sentiments (positive, negative and neutral were classified towards three target-market categories. Machine learning was performed using Weka 3.6.9. The results of the test data showed that the bagging method improved the accuracy of CART with 1.9% (to 85.20%. On the other hand, for sentiment classification, the ensemble methods were not successful in increasing the accuracy of CART. The results of this study may be taken into consideration by companies who approach their customers through social media, especially Twitter.

  2. Multicomponent ensemble models to forecast induced seismicity

    Science.gov (United States)

    Király-Proag, E.; Gischig, V.; Zechar, J. D.; Wiemer, S.

    2018-01-01

    In recent years, human-induced seismicity has become a more and more relevant topic due to its economic and social implications. Several models and approaches have been developed to explain underlying physical processes or forecast induced seismicity. They range from simple statistical models to coupled numerical models incorporating complex physics. We advocate the need for forecast testing as currently the best method for ascertaining if models are capable to reasonably accounting for key physical governing processes—or not. Moreover, operational forecast models are of great interest to help on-site decision-making in projects entailing induced earthquakes. We previously introduced a standardized framework following the guidelines of the Collaboratory for the Study of Earthquake Predictability, the Induced Seismicity Test Bench, to test, validate, and rank induced seismicity models. In this study, we describe how to construct multicomponent ensemble models based on Bayesian weightings that deliver more accurate forecasts than individual models in the case of Basel 2006 and Soultz-sous-Forêts 2004 enhanced geothermal stimulation projects. For this, we examine five calibrated variants of two significantly different model groups: (1) Shapiro and Smoothed Seismicity based on the seismogenic index, simple modified Omori-law-type seismicity decay, and temporally weighted smoothed seismicity; (2) Hydraulics and Seismicity based on numerically modelled pore pressure evolution that triggers seismicity using the Mohr-Coulomb failure criterion. We also demonstrate how the individual and ensemble models would perform as part of an operational Adaptive Traffic Light System. Investigating seismicity forecasts based on a range of potential injection scenarios, we use forecast periods of different durations to compute the occurrence probabilities of seismic events M ≥ 3. We show that in the case of the Basel 2006 geothermal stimulation the models forecast hazardous levels

  3. Significantly increased detection rate of drugs of abuse in urine following the introduction of new German driving licence re-granting guidelines.

    Science.gov (United States)

    Agius, Ronald; Nadulski, Thomas; Kahl, Hans-Gerhard; Dufaux, Bertin

    2012-02-10

    In this paper we present the first assessment of the new German driving licence re-granting medical and psychological assessment (MPA) guidelines by comparing over 3500 urine samples tested under the old MPA cut-offs to over 5000 samples tested under the new MPA cut-offs. Since the enzyme multiplied immunoassay technique (EMIT) technology used previously was not sensitive enough to screen for drugs at such low concentrations, as suggested by the new MPA guidelines, enzyme-linked immunosorbent assay (ELISA) screening kits were used to screen for the drugs of abuse at the new MPA cut-offs. The above comparison revealed significantly increased detection rates of drug use or exposure during the rehabilitation period as follows: 1.61, 2.33, 3.33, and 7 times higher for 11-nor-delta-9-tetrahydrocannabinol-9-carboxylic acid (THC-COOH), morphine, benzoylecgonine and amphetamine respectively. The present MPA guidelines seem to be more effective to detect non-abstinence from drugs of abuse and hence to detecting drivers who do not yet fulfil the MPA requirements to regain their revoked driving licence. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  4. The Oral Bioavailability of Trans-Resveratrol from a Grapevine-Shoot Extract in Healthy Humans is Significantly Increased by Micellar Solubilization.

    Science.gov (United States)

    Calvo-Castro, Laura A; Schiborr, Christina; David, Franziska; Ehrt, Heidi; Voggel, Jenny; Sus, Nadine; Behnam, Dariush; Bosy-Westphal, Anja; Frank, Jan

    2018-05-01

    Grapevine-shoot extract Vineatrol30 contains abundant resveratrol monomers and oligomers with health-promoting potential. However, the oral bioavailability of these compounds in humans is low (˂1-2%). The aim of this study was to improve the oral bioavailability of resveratrol from vineatrol by micellar solubilization. Twelve healthy volunteers (six women, six men) randomly ingested a single dose of 500 mg vineatrol (30 mg trans-resveratrol, 75 mg trans-ε-viniferin) as native powder or liquid micelles. Plasma and urine were collected at baseline and over 24 h after intake. Resveratrol and viniferin were analyzed by HPLC. The area under the plasma concentration-time curve (AUC) and mean maximum plasma trans-resveratrol concentrations were 5.0-fold and 10.6-fold higher, respectively, after micellar supplementation relative to the native powder. However, no detectable amounts of trans-ε-viniferin were found in either plasma or urine. The transepithelial permeability of trans-resveratrol and trans-ε-viniferin across differentiated Caco-2 monolayers was consistent to the absorbed fractions in vivo. The oral bioavailability of trans-resveratrol from the grapevine-shoot extract Vineatrol30 was significantly increased using a liquid micellar formulation, without any treatment-related adverse effects, making it a suitable system for improved supplementation of trans-resveratrol. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Ensemble modeling of E. coli in the Charles River, Boston, Massachusetts, USA.

    Science.gov (United States)

    Hellweger, F L

    2007-01-01

    A case study of ensemble modeling of Escherichia coli (E. coli) densities in surface waters in the context of public health risk prediction is presented. The output of two different models, mechanistic and empirical, are combined and compared to data. The mechanistic model is a high-resolution, time-variable, three-dimensional coupled hydrodynamic and water quality model. It generally reproduces the mechanisms of E. coli fate and transport in the river, including the presence and absence of a plume in the study area under similar input, but different hydrodynamic conditions caused by the operation of a downstream dam and wind. At the time series station, the model has a root mean square error (RMSE) of 370 CFU/100mL, a total error rate (with respect to the EPA-recommended single sample criteria value of 235 CFU/100mL) (TER) of 15% and negative error rate (NER) of 30%. The empirical model is based on multiple linear regression using the forcing functions of the mechanistic model as independent variables. It has better overall performance (at the time series station), due to a strong correlation of E. coli density with upstream inflow for this time period (RMSE =200 CFU/100mL, TER =13%, NER =1.6%). However, the model is mechanistically incorrect in that it predicts decreasing densities with increasing Combined Sewer Overflow (CSO) input. The two models are fundamentally different and their errors are uncorrelated (R(2) =0.02), which motivates their combination in an ensemble. Two combination approaches, a geometric mean ensemble (GME) and an "either exceeds" ensemble (EEE), are explored. The GME model outperforms the mechanistic and empirical models in terms of RMSE (190 CFU/100mL) and TER (11%), but has a higher NER (23%). The EEE has relatively high TER (16%), but low NER (0.8%) and may be the best method for a conservative prediction. The study demonstrates the potential utility of ensemble modeling for pathogen indicators, but significant further research is

  6. DYNAMIC STABILITY OF THE SOLAR SYSTEM: STATISTICALLY INCONCLUSIVE RESULTS FROM ENSEMBLE INTEGRATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Zeebe, Richard E., E-mail: zeebe@soest.hawaii.edu [School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, 1000 Pope Road, MSB 629, Honolulu, HI 96822 (United States)

    2015-01-01

    Due to the chaotic nature of the solar system, the question of its long-term stability can only be answered in a statistical sense, for instance, based on numerical ensemble integrations of nearby orbits. Destabilization of the inner planets, leading to close encounters and/or collisions can be initiated through a large increase in Mercury's eccentricity, with a currently assumed likelihood of ∼1%. However, little is known at present about the robustness of this number. Here I report ensemble integrations of the full equations of motion of the eight planets and Pluto over 5 Gyr, including contributions from general relativity. The results show that different numerical algorithms lead to statistically different results for the evolution of Mercury's eccentricity (e{sub M}). For instance, starting at present initial conditions (e{sub M}≃0.21), Mercury's maximum eccentricity achieved over 5 Gyr is, on average, significantly higher in symplectic ensemble integrations using heliocentric rather than Jacobi coordinates and stricter error control. In contrast, starting at a possible future configuration (e{sub M}≃0.53), Mercury's maximum eccentricity achieved over the subsequent 500 Myr is, on average, significantly lower using heliocentric rather than Jacobi coordinates. For example, the probability for e{sub M} to increase beyond 0.53 over 500 Myr is >90% (Jacobi) versus only 40%-55% (heliocentric). This poses a dilemma because the physical evolution of the real system—and its probabilistic behavior—cannot depend on the coordinate system or the numerical algorithm chosen to describe it. Some tests of the numerical algorithms suggest that symplectic integrators using heliocentric coordinates underestimate the odds for destabilization of Mercury's orbit at high initial e{sub M}.

  7. Online probabilistic learning with an ensemble of forecasts

    Science.gov (United States)

    Thorey, Jean; Mallet, Vivien; Chaussin, Christophe

    2016-04-01

    Our objective is to produce a calibrated weighted ensemble to forecast a univariate time series. In addition to a meteorological ensemble of forecasts, we rely on observations or analyses of the target variable. The celebrated Continuous Ranked Probability Score (CRPS) is used to evaluate the probabilistic forecasts. However applying the CRPS on weighted empirical distribution functions (deriving from the weighted ensemble) may introduce a bias because of which minimizing the CRPS does not produce the optimal weights. Thus we propose an unbiased version of the CRPS which relies on clusters of members and is strictly proper. We adapt online learning methods for the minimization of the CRPS. These methods generate the weights associated to the members in the forecasted empirical distribution function. The weights are updated before each forecast step using only past observations and forecasts. Our learning algorithms provide the theoretical guarantee that, in the long run, the CRPS of the weighted forecasts is at least as good as the CRPS of any weighted ensemble with weights constant in time. In particular, the performance of our forecast is better than that of any subset ensemble with uniform weights. A noteworthy advantage of our algorithm is that it does not require any assumption on the distributions of the observations and forecasts, both for the application and for the theoretical guarantee to hold. As application example on meteorological forecasts for photovoltaic production integration, we show that our algorithm generates a calibrated probabilistic forecast, with significant performance improvements on probabilistic diagnostic tools (the CRPS, the reliability diagram and the rank histogram).

  8. Ensemble models of neutrophil trafficking in severe sepsis.

    Directory of Open Access Journals (Sweden)

    Sang Ok Song

    Full Text Available A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about 18% of the treated population that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental

  9. On evaluation of ensemble precipitation forecasts with observation-based ensembles

    Directory of Open Access Journals (Sweden)

    S. Jaun

    2007-04-01

    Full Text Available Spatial interpolation of precipitation data is uncertain. How important is this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation forecasts? These questions are discussed by experimental evaluation of the COSMO consortium's limited-area ensemble prediction system COSMO-LEPS. The applied performance measure is the often used Brier skill score (BSS. The observational references in the evaluation are (a analyzed rain gauge data by ordinary Kriging and (b ensembles of interpolated rain gauge data by stochastic simulation. This permits the consideration of either a deterministic reference (the event is observed or not with 100% certainty or a probabilistic reference that makes allowance for uncertainties in spatial averaging. The evaluation experiments show that the evaluation uncertainties are substantial even for the large area (41 300 km2 of Switzerland with a mean rain gauge distance as good as 7 km: the one- to three-day precipitation forecasts have skill decreasing with forecast lead time but the one- and two-day forecast performances differ not significantly.

  10. EnsembleGASVR: A novel ensemble method for classifying missense single nucleotide polymorphisms

    KAUST Repository

    Rapakoulia, Trisevgeni

    2014-04-26

    Motivation: Single nucleotide polymorphisms (SNPs) are considered the most frequently occurring DNA sequence variations. Several computational methods have been proposed for the classification of missense SNPs to neutral and disease associated. However, existing computational approaches fail to select relevant features by choosing them arbitrarily without sufficient documentation. Moreover, they are limited to the problem ofmissing values, imbalance between the learning datasets and most of them do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel evolutionary embedded algorithm to locate close to optimal Support Vector Regression models. In its second step, these models are combined to extract a universal predictor, which is less prone to overfitting issues, systematizes the rebalancing of the learning sets and uses an internal approach for solving the missing values problem without loss of information. Confidence scores support all the predictions and the model becomes tunable by modifying the classification thresholds. An extensive study was performed for collecting the most relevant features for the problem of classifying SNPs, and a superset of 88 features was constructed. Experimental results show that the proposed framework outperforms well-known algorithms in terms of classification performance in the examined datasets. Finally, the proposed algorithmic framework was able to uncover the significant role of certain features such as the solvent accessibility feature, and the top-scored predictions were further validated by linking them with disease phenotypes. © The Author 2014.

  11. MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

    Science.gov (United States)

    Chen, Lei; Kamel, Mohamed S.

    2016-01-01

    In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

  12. Ensemble models on palaeoclimate to predict India's groundwater challenge

    Directory of Open Access Journals (Sweden)

    Partha Sarathi Datta

    2013-09-01

    Full Text Available In many parts of the world, freshwater crisis is largely due to increasing water consumption and pollution by rapidly growing population and aspirations for economic development, but, ascribed usually to the climate. However, limited understanding and knowledge gaps in the factors controlling climate and uncertainties in the climate models are unable to assess the probable impacts on water availability in tropical regions. In this context, review of ensemble models on δ18O and δD in rainfall and groundwater, 3H- and 14C- ages of groundwater and 14C- age of lakes sediments helped to reconstruct palaeoclimate and long-term recharge in the North-west India; and predict future groundwater challenge. The annual mean temperature trend indicates both warming/cooling in different parts of India in the past and during 1901–2010. Neither the GCMs (Global Climate Models nor the observational record indicates any significant change/increase in temperature and rainfall over the last century, and climate change during the last 1200 yrs BP. In much of the North-West region, deep groundwater renewal occurred from past humid climate, and shallow groundwater renewal from limited modern recharge over the past decades. To make water management to be more responsive to climate change, the gaps in the science of climate change need to be bridged.

  13. Crossover between the Gaussian orthogonal ensemble, the Gaussian unitary ensemble, and Poissonian statistics.

    Science.gov (United States)

    Schweiner, Frank; Laturner, Jeanine; Main, Jörg; Wunner, Günter

    2017-11-01

    Until now only for specific crossovers between Poissonian statistics (P), the statistics of a Gaussian orthogonal ensemble (GOE), or the statistics of a Gaussian unitary ensemble (GUE) have analytical formulas for the level spacing distribution function been derived within random matrix theory. We investigate arbitrary crossovers in the triangle between all three statistics. To this aim we propose an according formula for the level spacing distribution function depending on two parameters. Comparing the behavior of our formula for the special cases of P→GUE, P→GOE, and GOE→GUE with the results from random matrix theory, we prove that these crossovers are described reasonably. Recent investigations by F. Schweiner et al. [Phys. Rev. E 95, 062205 (2017)2470-004510.1103/PhysRevE.95.062205] have shown that the Hamiltonian of magnetoexcitons in cubic semiconductors can exhibit all three statistics in dependence on the system parameters. Evaluating the numerical results for magnetoexcitons in dependence on the excitation energy and on a parameter connected with the cubic valence band structure and comparing the results with the formula proposed allows us to distinguish between regular and chaotic behavior as well as between existent or broken antiunitary symmetries. Increasing one of the two parameters, transitions between different crossovers, e.g., from the P→GOE to the P→GUE crossover, are observed and discussed.

  14. Optical properties of single semiconductor nanowires and nanowire ensembles. Probing surface physics by photoluminescence spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Pfueller, Carsten

    2011-06-27

    This thesis presents a detailed investigation of the optical properties of semiconductor nanowires (NWs) in general and single GaN NWs and GaN NW ensembles in particular by photoluminescence (PL) spectroscopy. NWs are often considered as potential building blocks for future nanometer-scaled devices. This vision is based on several attractive features that are generally ascribed to NWs. For instance, they are expected to grow virtually free of strain and defects even on substrates with a large structural mismatch. In the first part of the thesis, some of these expectations are examined using semiconductor NWs of different materials. On the basis of the temperature-dependent PL of Au- and selfassisted GaAs/(Al,Ga)As core-shell NWs, the influence of foreign catalyst particles on the optical properties of NWs is investigated. For the Au-assisted NWs, we find a thermally activated, nonradiative recombination channel, possibly related to Auatoms incorporated from the catalyst. These results indicate the limited suitability of catalyst-assisted NWs for optoelectronic applications. The effect of the substrate choice is studied by comparing the PL of ZnO NWs grown on Si, Al{sub 2}O{sub 3}, and ZnO substrates. Their virtually identical optical characteristics indicate that the synthesis of NWs may indeed overcome the constraints that limit the heteroepitaxial deposition of thin films. The major part of this thesis discusses the optical properties of GaN NWs grown on Si substrates. The investigation of the PL of single GaN NWs and GaN NW ensembles reveals the significance of their large surface-to-volume ratio. Differences in the recombination behavior of GaNNW ensembles and GaN layers are observed. First, the large surface-to-volume ratio is discussed to be responsible for the different recombination mechanisms apparent in NWs. Second, certain optical features are only found in the PL of GaN NWs, but not in that of GaN layers. An unexpected broadening of the donor

  15. Cold-knife conisation and large loop excision of transformation zone significantly increase the risk for spontaneous preterm birth: a population-based cohort study.

    Science.gov (United States)

    Jančar, Nina; Mihevc Ponikvar, Barbara; Tomšič, Sonja

    2016-08-01

    Our aim was to explore the association between cold-knife conisation and large loop excision of transformation zone (LLETZ) with spontaneous preterm birth in a large 10-year national sample. We wanted to explore further the association of these procedures with preterm birth according to gestation. We conducted a population based retrospective cohort study, using data from national Medical Birth Registry. The study population consisted of all women giving birth to singletons in the period 2003-2012 in Slovenia, excluding all induced labors and elective cesarean sections before 37 weeks of gestation (N=192730). We compared the prevalence of spontaneous preterm births (before 28 weeks, before 32 weeks, before 34 weeks and before 37 weeks of gestation) in women with cold-knife conisation or LLETZ compared to women without history of conisation, calculating odds ratios (OR), adjusted for potential confounders. Chi-square test was used for descriptive analysis. Logistic regression analyses were performed to estimate crude odds ratio (OR) and adjusted odds ratio (aOR) and their 95% confidence intervals (95% CI) with two-sided probability (p) values. A total of 8420 (4.4%) women had a preterm birth before 37 weeks of gestation, 2250 (1.2%) before 34 weeks of gestation, 1333 (0.7%) before 32 weeks of gestation and 603 (0.3%) before 28 weeks of gestation. A total of 4580 (2.4%) women had some type of conisation in their medical history: 2083 (1.1%) had cold-knife conisation and 2498 (1.3%) had LLETZ. In women with history of cold-knife conisation, the adjusted OR for preterm birth before 37 weeks of gestation was 3.13 (95% CI; 2.74-3.57) and for preterm birth before 28 weeks of gestation 5.96 (95% CI; 4.3-8.3). In women with history of LLETZ, the adjusted OR was 1.95 (95% CI; 1.68-2.25) and 2.88 (95% CI; 1.87-4.43), respectively. Women with cervical excision procedure of any kind have significantly increased odds for preterm birth, especially for preterm birth before 28

  16. Single-source dual-energy spectral multidetector CT of pancreatic adenocarcinoma: Optimization of energy level viewing significantly increases lesion contrast

    International Nuclear Information System (INIS)

    Patel, B.N.; Thomas, J.V.; Lockhart, M.E.; Berland, L.L.; Morgan, D.E.

    2013-01-01

    V was 31 ± 25 HU (p = 0.007). Conclusion: Significantly increased pancreatic lesion contrast was noted at lower viewing energies using spectral MDCT. Individual patient CNR-optimized energy level images have the potential to improve lesion conspicuity.

  17. Single-source dual-energy spectral multidetector CT of pancreatic adenocarcinoma: optimization of energy level viewing significantly increases lesion contrast.

    Science.gov (United States)

    Patel, B N; Thomas, J V; Lockhart, M E; Berland, L L; Morgan, D E

    2013-02-01

    .007). Significantly increased pancreatic lesion contrast was noted at lower viewing energies using spectral MDCT. Individual patient CNR-optimized energy level images have the potential to improve lesion conspicuity. Copyright © 2012 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  18. Creating ensembles of decision trees through sampling

    Science.gov (United States)

    Kamath, Chandrika; Cantu-Paz, Erick

    2005-08-30

    A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

  19. Derivation of Mayer Series from Canonical Ensemble

    International Nuclear Information System (INIS)

    Wang Xian-Zhi

    2016-01-01

    Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula. (paper)

  20. Derivation of Mayer Series from Canonical Ensemble

    Science.gov (United States)

    Wang, Xian-Zhi

    2016-02-01

    Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.

  1. Mass Conservation and Positivity Preservation with Ensemble-type Kalman Filter Algorithms

    Science.gov (United States)

    Janjic, Tijana; McLaughlin, Dennis B.; Cohn, Stephen E.; Verlaan, Martin

    2013-01-01

    Maintaining conservative physical laws numerically has long been recognized as being important in the development of numerical weather prediction (NWP) models. In the broader context of data assimilation, concerted efforts to maintain conservation laws numerically and to understand the significance of doing so have begun only recently. In order to enforce physically based conservation laws of total mass and positivity in the ensemble Kalman filter, we incorporate constraints to ensure that the filter ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. We show that the analysis steps of ensemble transform Kalman filter (ETKF) algorithm and ensemble Kalman filter algorithm (EnKF) can conserve the mass integral, but do not preserve positivity. Further, if localization is applied or if negative values are simply set to zero, then the total mass is not conserved either. In order to ensure mass conservation, a projection matrix that corrects for localization effects is constructed. In order to maintain both mass conservation and positivity preservation through the analysis step, we construct a data assimilation algorithms based on quadratic programming and ensemble Kalman filtering. Mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate constraints. Some simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. The results show clear improvements in both analyses and forecasts, particularly in the presence of localized features. Behavior of the algorithm is also tested in presence of model error.

  2. A Thermal Physiological Comparison of Two HazMat Protective Ensembles With and Without Active Convective Cooling

    Science.gov (United States)

    Williamson, Rebecca; Carbo, Jorge; Luna, Bernadette; Webbon, Bruce W.

    1998-01-01

    Wearing impermeable garments for hazardous materials clean up can often present a health and safety problem for the wearer. Even short duration clean up activities can produce heat stress injuries in hazardous materials workers. It was hypothesized that an internal cooling system might increase worker productivity and decrease likelihood of heat stress injuries in typical HazMat operations. Two HazMat protective ensembles were compared during treadmill exercise. The different ensembles were created using two different suits: a Trelleborg VPS suit representative of current HazMat suits and a prototype suit developed by NASA engineers. The two life support systems used were a current technology Interspiro Spirolite breathing apparatus and a liquid air breathing system that also provided convective cooling. Twelve local members of a HazMat team served as test subjects. They were fully instrumented to allow a complete physiological comparison of their thermal responses to the different ensembles. Results showed that cooling from the liquid air system significantly decreased thermal stress. The results of the subjective evaluations of new design features in the prototype suit were also highly favorable. Incorporation of these new design features could lead to significant operational advantages in the future.

  3. Ensemble-based prediction of RNA secondary structures.

    Science.gov (United States)

    Aghaeepour, Nima; Hoos, Holger H

    2013-04-24

    Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

  4. Ensemble Weight Enumerators for Protograph LDPC Codes

    Science.gov (United States)

    Divsalar, Dariush

    2006-01-01

    Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length ensemble weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining ensemble average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular ensembles, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on ensemble weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.

  5. Ensemble Kalman filtering with residual nudging

    KAUST Repository

    Luo, X.; Hoteit, Ibrahim

    2012-01-01

    Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work

  6. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

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

    2015-01-01

    the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function

  7. Polarized ensembles of random pure states

    International Nuclear Information System (INIS)

    Cunden, Fabio Deelan; Facchi, Paolo; Florio, Giuseppe

    2013-01-01

    A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise. (paper)

  8. Polarized ensembles of random pure states

    Science.gov (United States)

    Deelan Cunden, Fabio; Facchi, Paolo; Florio, Giuseppe

    2013-08-01

    A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise.

  9. Quark ensembles with infinite correlation length

    OpenAIRE

    Molodtsov, S. V.; Zinovjev, G. M.

    2014-01-01

    By studying quark ensembles with infinite correlation length we formulate the quantum field theory model that, as we show, is exactly integrable and develops an instability of its standard vacuum ensemble (the Dirac sea). We argue such an instability is rooted in high ground state degeneracy (for 'realistic' space-time dimensions) featuring a fairly specific form of energy distribution, and with the cutoff parameter going to infinity this inherent energy distribution becomes infinitely narrow...

  10. Orbital magnetism in ensembles of ballistic billiards

    International Nuclear Information System (INIS)

    Ullmo, D.; Richter, K.; Jalabert, R.A.

    1993-01-01

    The magnetic response of ensembles of small two-dimensional structures at finite temperatures is calculated. Using semiclassical methods and numerical calculation it is demonstrated that only short classical trajectories are relevant. The magnetic susceptibility is enhanced in regular systems, where these trajectories appear in families. For ensembles of squares large paramagnetic susceptibility is obtained, in good agreement with recent measurements in the ballistic regime. (authors). 20 refs., 2 figs

  11. Multivariate localization methods for ensemble Kalman filtering

    OpenAIRE

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

    2015-01-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of ...

  12. Impacts of calibration strategies and ensemble methods on ensemble flood forecasting over Lanjiang basin, Southeast China

    Science.gov (United States)

    Liu, Li; Xu, Yue-Ping

    2017-04-01

    Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.

  13. Wave Extremes in the Northeast Atlantic from Ensemble Forecasts

    Science.gov (United States)

    Breivik, Øyvind; Aarnes, Ole Johan; Bidlot, Jean-Raymond; Carrasco, Ana; Saetra, Øyvind

    2013-10-01

    A method for estimating return values from ensembles of forecasts at advanced lead times is presented. Return values of significant wave height in the North-East Atlantic, the Norwegian Sea and the North Sea are computed from archived +240-h forecasts of the ECMWF ensemble prediction system (EPS) from 1999 to 2009. We make three assumptions: First, each forecast is representative of a six-hour interval and collectively the data set is then comparable to a time period of 226 years. Second, the model climate matches the observed distribution, which we confirm by comparing with buoy data. Third, the ensemble members are sufficiently uncorrelated to be considered independent realizations of the model climate. We find anomaly correlations of 0.20, but peak events (>P97) are entirely uncorrelated. By comparing return values from individual members with return values of subsamples of the data set we also find that the estimates follow the same distribution and appear unaffected by correlations in the ensemble. The annual mean and variance over the 11-year archived period exhibit no significant departures from stationarity compared with a recent reforecast, i.e., there is no spurious trend due to model upgrades. EPS yields significantly higher return values than ERA-40 and ERA-Interim and is in good agreement with the high-resolution hindcast NORA10, except in the lee of unresolved islands where EPS overestimates and in enclosed seas where it is biased low. Confidence intervals are half the width of those found for ERA-Interim due to the magnitude of the data set.

  14. Plasticity of the Binding Site of Renin: Optimized Selection of Protein Structures for Ensemble Docking.

    Science.gov (United States)

    Strecker, Claas; Meyer, Bernd

    2018-05-02

    Protein flexibility poses a major challenge to docking of potential ligands in that the binding site can adopt different shapes. Docking algorithms usually keep the protein rigid and only allow the ligand to be treated as flexible. However, a wrong assessment of the shape of the binding pocket can prevent a ligand from adapting a correct pose. Ensemble docking is a simple yet promising method to solve this problem: Ligands are docked into multiple structures, and the results are subsequently merged. Selection of protein structures is a significant factor for this approach. In this work we perform a comprehensive and comparative study evaluating the impact of structure selection on ensemble docking. We perform ensemble docking with several crystal structures and with structures derived from molecular dynamics simulations of renin, an attractive target for antihypertensive drugs. Here, 500 ns of MD simulations revealed binding site shapes not found in any available crystal structure. We evaluate the importance of structure selection for ensemble docking by comparing binding pose prediction, ability to rank actives above nonactives (screening utility), and scoring accuracy. As a result, for ensemble definition k-means clustering appears to be better suited than hierarchical clustering with average linkage. The best performing ensemble consists of four crystal structures and is able to reproduce the native ligand poses better than any individual crystal structure. Moreover this ensemble outperforms 88% of all individual crystal structures in terms of screening utility as well as scoring accuracy. Similarly, ensembles of MD-derived structures perform on average better than 75% of any individual crystal structure in terms of scoring accuracy at all inspected ensembles sizes.

  15. Sequential Ensembles Tolerant to Synthetic Aperture Radar (SAR Soil Moisture Retrieval Errors

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2016-04-01

    Full Text Available Due to complicated and undefined systematic errors in satellite observation, data assimilation integrating model states with satellite observations is more complicated than field measurements-based data assimilation at a local scale. In the case of Synthetic Aperture Radar (SAR soil moisture, the systematic errors arising from uncertainties in roughness conditions are significant and unavoidable, but current satellite bias correction methods do not resolve the problems very well. Thus, apart from the bias correction process of satellite observation, it is important to assess the inherent capability of satellite data assimilation in such sub-optimal but more realistic observational error conditions. To this end, time-evolving sequential ensembles of the Ensemble Kalman Filter (EnKF is compared with stationary ensemble of the Ensemble Optimal Interpolation (EnOI scheme that does not evolve the ensembles over time. As the sensitivity analysis demonstrated that the surface roughness is more sensitive to the SAR retrievals than measurement errors, it is a scope of this study to monitor how data assimilation alters the effects of roughness on SAR soil moisture retrievals. In results, two data assimilation schemes all provided intermediate values between SAR overestimation, and model underestimation. However, under the same SAR observational error conditions, the sequential ensembles approached a calibrated model showing the lowest Root Mean Square Error (RMSE, while the stationary ensemble converged towards the SAR observations exhibiting the highest RMSE. As compared to stationary ensembles, sequential ensembles have a better tolerance to SAR retrieval errors. Such inherent nature of EnKF suggests an operational merit as a satellite data assimilation system, due to the limitation of bias correction methods currently available.

  16. Noodles: a tool for visualization of numerical weather model ensemble uncertainty.

    Science.gov (United States)

    Sanyal, Jibonananda; Zhang, Song; Dyer, Jamie; Mercer, Andrew; Amburn, Philip; Moorhead, Robert J

    2010-01-01

    Numerical weather prediction ensembles are routinely used for operational weather forecasting. The members of these ensembles are individual simulations with either slightly perturbed initial conditions or different model parameterizations, or occasionally both. Multi-member ensemble output is usually large, multivariate, and challenging to interpret interactively. Forecast meteorologists are interested in understanding the uncertainties associated with numerical weather prediction; specifically variability between the ensemble members. Currently, visualization of ensemble members is mostly accomplished through spaghetti plots of a single mid-troposphere pressure surface height contour. In order to explore new uncertainty visualization methods, the Weather Research and Forecasting (WRF) model was used to create a 48-hour, 18 member parameterization ensemble of the 13 March 1993 "Superstorm". A tool was designed to interactively explore the ensemble uncertainty of three important weather variables: water-vapor mixing ratio, perturbation potential temperature, and perturbation pressure. Uncertainty was quantified using individual ensemble member standard deviation, inter-quartile range, and the width of the 95% confidence interval. Bootstrapping was employed to overcome the dependence on normality in the uncertainty metrics. A coordinated view of ribbon and glyph-based uncertainty visualization, spaghetti plots, iso-pressure colormaps, and data transect plots was provided to two meteorologists for expert evaluation. They found it useful in assessing uncertainty in the data, especially in finding outliers in the ensemble run and therefore avoiding the WRF parameterizations that lead to these outliers. Additionally, the meteorologists could identify spatial regions where the uncertainty was significantly high, allowing for identification of poorly simulated storm environments and physical interpretation of these model issues.

  17. Experimentally-induced immune activation in natural hosts of SIV induces significant increases in viral replication and CD4+ T cell depletion

    Energy Technology Data Exchange (ETDEWEB)

    Ribeiro, Ruy M [Los Alamos National Laboratory

    2008-01-01

    Chronically SIVagm-infected African green monkeys (AGMs) have a remarkably stable non-pathogenic disease course, with levels of immune activation in chronic SIVagm infection similar to those observed in uninfected monkeys and stable viral loads (VLs) for long periods of time. In vivo administration of lipopolysaccharide (LPS) or an IL-2/diphtheria toxin fusion protein (Ontak) to chronically SIVagm-infected AGMs triggered increases in immune activation and subsequently of viral replication and depletion of intestinal CD4{sup +} T cells. Our study indicates that circulating microbial products can increase viral replication by inducing immune activation and increasing the number of viral target cells, thus demonstrating that immune activation and T cell prolifeation are key factors in AIDS pathogenesis.

  18. Increased superior frontal gyrus activation during working memory processing in psychosis: Significant relation to cumulative antipsychotic medication and to negative symptoms.

    Science.gov (United States)

    Vogel, Tobias; Smieskova, Renata; Schmidt, André; Walter, Anna; Harrisberger, Fabienne; Eckert, Anne; Lang, Undine E; Riecher-Rössler, Anita; Graf, Marc; Borgwardt, Stefan

    2016-08-01

    Impairment in working memory (WM) is a core symptom in schizophrenia. However, little is known about how clinical features influence functional brain activity specific to WM processing during the development of first-episode psychosis (FEP) to schizophrenia (SZ). We compared functional WM-specific brain activity in FEP and SZ patients, including the effects of the duration of illness, psychopathological factors and antipsychotic medication. Cross-sectional study of male FEP (n=22) and SZ (n=20) patients performing an n-back task when undergoing functional magnetic resonance imaging (fMRI). Clinical features were collected by semi-structured interviews and medical records. The SZ group performed significantly worse than the FEP group in the 2-back condition. The SZ group also showed significantly higher activation in the left superior frontal gyrus in the 2-back versus 0-back condition (2-back>0-back). This frontal activation correlated positively with negative symptoms and with cumulative antipsychotic medication during the year before the fMRI examination. There were no significant correlations between activation and duration of illness. There was greater frontal neural activation in SZ than in FEP. This indicated differences in WM processing, and was significantly related to cumulative antipsychotic exposure and negative symptoms, but not to the duration of illness. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Improving the accuracy of flood forecasting with transpositions of ensemble NWP rainfall fields considering orographic effects

    Science.gov (United States)

    Yu, Wansik; Nakakita, Eiichi; Kim, Sunmin; Yamaguchi, Kosei

    2016-08-01

    The use of meteorological ensembles to produce sets of hydrological predictions increased the capability to issue flood warnings. However, space scale of the hydrological domain is still much finer than meteorological model, and NWP models have challenges with displacement. The main objective of this study to enhance the transposition method proposed in Yu et al. (2014) and to suggest the post-processing ensemble flood forecasting method for the real-time updating and the accuracy improvement of flood forecasts that considers the separation of the orographic rainfall and the correction of misplaced rain distributions using additional ensemble information through the transposition of rain distributions. In the first step of the proposed method, ensemble forecast rainfalls from a numerical weather prediction (NWP) model are separated into orographic and non-orographic rainfall fields using atmospheric variables and the extraction of topographic effect. Then the non-orographic rainfall fields are examined by the transposition scheme to produce additional ensemble information and new ensemble NWP rainfall fields are calculated by recombining the transposition results of non-orographic rain fields with separated orographic rainfall fields for a generation of place-corrected ensemble information. Then, the additional ensemble information is applied into a hydrologic model for post-flood forecasting with a 6-h interval. The newly proposed method has a clear advantage to improve the accuracy of mean value of ensemble flood forecasting. Our study is carried out and verified using the largest flood event by typhoon 'Talas' of 2011 over the two catchments, which are Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments of Shingu river basin (2360 km2), which is located in the Kii peninsula, Japan.

  20. Ensemble prediction of floods – catchment non-linearity and forecast probabilities

    Directory of Open Access Journals (Sweden)

    C. Reszler

    2007-07-01

    Full Text Available Quantifying the uncertainty of flood forecasts by ensemble methods is becoming increasingly important for operational purposes. The aim of this paper is to examine how the ensemble distribution of precipitation forecasts propagates in the catchment system, and to interpret the flood forecast probabilities relative to the forecast errors. We use the 622 km2 Kamp catchment in Austria as an example where a comprehensive data set, including a 500 yr and a 1000 yr flood, is available. A spatially-distributed continuous rainfall-runoff model is used along with ensemble and deterministic precipitation forecasts that combine rain gauge data, radar data and the forecast fields of the ALADIN and ECMWF numerical weather prediction models. The analyses indicate that, for long lead times, the variability of the precipitation ensemble is amplified as it propagates through the catchment system as a result of non-linear catchment response. In contrast, for lead times shorter than the catchment lag time (e.g. 12 h and less, the variability of the precipitation ensemble is decreased as the forecasts are mainly controlled by observed upstream runoff and observed precipitation. Assuming that all ensemble members are equally likely, the statistical analyses for five flood events at the Kamp showed that the ensemble spread of the flood forecasts is always narrower than the distribution of the forecast errors. This is because the ensemble forecasts focus on the uncertainty in forecast precipitation as the dominant source of uncertainty, and other sources of uncertainty are not accounted for. However, a number of analyses, including Relative Operating Characteristic diagrams, indicate that the ensemble spread is a useful indicator to assess potential forecast errors for lead times larger than 12 h.

  1. Co-downregulation of the hydroxycinnamoyl-CoA:shikimate hydroxycinnamoyl transferase and coumarate 3-hydroxylase significantly increases cellulose content in transgenic alfalfa (Medicago sativa L.).

    Science.gov (United States)

    Tong, Zongyong; Li, Heng; Zhang, Rongxue; Ma, Lei; Dong, Jiangli; Wang, Tao

    2015-10-01

    Lignin is a component of the cell wall that is essential for growth, development, structure and pathogen resistance in plants, but high lignin is an obstacle to the conversion of cellulose to ethanol for biofuel. Genetically modifying lignin and cellulose contents can be a good approach to overcoming that obstacle. Alfalfa (Medicago sativa L.) is rich in lignocellulose biomass and used as a model plant for the genetic modification of lignin in this study. Two key enzymes in the lignin biosynthesis pathway-hydroxycinnamoyl -CoA:shikimate hydroxycinnamoyl transferase (HCT) and coumarate 3-hydroxylase (C3H)-were co-downregulated. Compared to wild-type plants, the lignin content in the modified strain was reduced by 38%, cellulose was increased by 86.1%, enzyme saccharification efficiency was increased by 10.9%, and cell wall digestibility was increased by 13.0%. The modified alfalfa exhibited a dwarf phenotype, but normal above ground biomass. This approach provides a new strategy for reducing lignin and increasing cellulose contents and creates a new genetically modified crop with enhanced value for biofuel. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  2. The significance of the European beaver (Castor fibre activity for the process of renaturalization of river valleys in the era of increasing

    Directory of Open Access Journals (Sweden)

    Kusztal Piotr

    2017-03-01

    Full Text Available Changes in the environment that are caused by the activity of beavers bring numerous advantages. They affect the increase in biodiversity, contribute to improving the condition of cleanliness of watercourses, improve local water relations and restore the natural landscape of river valleys.

  3. Rotationally invariant family of Levy-like random matrix ensembles

    International Nuclear Information System (INIS)

    Choi, Jinmyung; Muttalib, K A

    2009-01-01

    We introduce a family of rotationally invariant random matrix ensembles characterized by a parameter λ. While λ = 1 corresponds to well-known critical ensembles, we show that λ ≠ 1 describes 'Levy-like' ensembles, characterized by power-law eigenvalue densities. For λ > 1 the density is bounded, as in Gaussian ensembles, but λ < 1 describes ensembles characterized by densities with long tails. In particular, the model allows us to evaluate, in terms of a novel family of orthogonal polynomials, the eigenvalue correlations for Levy-like ensembles. These correlations differ qualitatively from those in either the Gaussian or the critical ensembles. (fast track communication)

  4. An Ensemble of Neural Networks for Stock Trading Decision Making

    Science.gov (United States)

    Chang, Pei-Chann; Liu, Chen-Hao; Fan, Chin-Yuan; Lin, Jun-Lin; Lai, Chih-Ming

    Stock turning signals detection are very interesting subject arising in numerous financial and economic planning problems. In this paper, Ensemble Neural Network system with Intelligent Piecewise Linear Representation for stock turning points detection is presented. The Intelligent piecewise linear representation method is able to generate numerous stocks turning signals from the historic data base, then Ensemble Neural Network system will be applied to train the pattern and retrieve similar stock price patterns from historic data for training. These turning signals represent short-term and long-term trading signals for selling or buying stocks from the market which are applied to forecast the future turning points from the set of test data. Experimental results demonstrate that the hybrid system can make a significant and constant amount of profit when compared with other approaches using stock data available in the market.

  5. Human resource recommendation algorithm based on ensemble learning and Spark

    Science.gov (United States)

    Cong, Zihan; Zhang, Xingming; Wang, Haoxiang; Xu, Hongjie

    2017-08-01

    Aiming at the problem of “information overload” in the human resources industry, this paper proposes a human resource recommendation algorithm based on Ensemble Learning. The algorithm considers the characteristics and behaviours of both job seeker and job features in the real business circumstance. Firstly, the algorithm uses two ensemble learning methods-Bagging and Boosting. The outputs from both learning methods are then merged to form user interest model. Based on user interest model, job recommendation can be extracted for users. The algorithm is implemented as a parallelized recommendation system on Spark. A set of experiments have been done and analysed. The proposed algorithm achieves significant improvement in accuracy, recall rate and coverage, compared with recommendation algorithms such as UserCF and ItemCF.

  6. Significant increase in cultivation of Gardnerella vaginalis, Alloscardovia omnicolens, Actinotignum schaalii, and Actinomyces spp. in urine samples with total laboratory automation.

    Science.gov (United States)

    Klein, Sabrina; Nurjadi, Dennis; Horner, Susanne; Heeg, Klaus; Zimmermann, Stefan; Burckhardt, Irene

    2018-04-13

    While total laboratory automation (TLA) is well established in laboratory medicine, only a few microbiological laboratories are using TLA systems. Especially in terms of speed and accuracy, working with TLA is expected to be superior to conventional microbiology. We compared in total 35,564 microbiological urine cultures with and without incubation and processing with BD Kiestra TLA for a 6-month period each retrospectively. Sixteen thousand three hundred thirty-eight urine samples were analyzed in the pre-TLA period and 19,226 with TLA. Sixty-two percent (n = 10,101/16338) of the cultures processed without TLA and 68% (n = 13,102/19226) of the cultures processed with TLA showed growth. There were significantly more samples with two or more species per sample and with low numbers of colony forming units (CFU) after incubation with TLA. Regarding the type of bacteria, there were comparable amounts of Enterobacteriaceae in the samples, slightly less non-fermenting Gram-negative bacteria, but significantly more Gram-positive cocci, and Gram-positive rods. Especially Alloscardivia omnicolens, Gardnerella vaginalis, Actinomyces spp., and Actinotignum schaalii were significantly more abundant in the samples incubated and processed with TLA. The time to report was significantly lower in the TLA processed samples by 1.5 h. We provide the first report in Europe of a large number of urine samples processed with TLA. TLA showed enhanced growth of non-classical and rarely cultured bacteria from urine samples. Our findings suggest that previously underestimated bacteria may be relevant pathogens for urinary tract infections. Further studies are needed to confirm our findings.

  7. Increased levels of IL-6 in the cerebrospinal fluid of patients with chronic schizophrenia — significance for activation of the kynurenine pathway

    Science.gov (United States)

    Schwieler, Lilly; Larsson, Markus K.; Skogh, Elisabeth; Kegel, Magdalena E.; Orhan, Funda; Abdelmoaty, Sally; Finn, Anja; Bhat, Maria; Samuelsson, Martin; Lundberg, Kristina; Dahl, Marja-Liisa; Sellgren, Carl; Schuppe-Koistinen, Ina; Svensson, Camilla I.; Erhardt, Sophie; Engberg, Göran

    2015-01-01

    Background Accumulating evidence indicates that schizophrenia is associated with brain immune activation. While a number of reports suggest increased cytokine levels in patients with schizophrenia, many of these studies have been limited by their focus on peripheral cytokines or confounded by various antipsychotic treatments. Here, well-characterized patients with schizophrenia, all receiving olanzapine treatment, and healthy volunteers were analyzed with regard to cerebrospinal fluid (CSF) levels of cytokines. We correlated the CSF cytokine levels to previously analyzed metabolites of the kynurenine (KYN) pathway. Methods We analyzed the CSF from patients and controls using electrochemiluminescence detection with regard to cytokines. Cell culture media from human cortical astrocytes were analyzed for KYN and kynurenic acid (KYNA) using high-pressure liquid chromatography or liquid chromatography/mass spectrometry. Results We included 23 patients and 37 controls in our study. Patients with schizophrenia had increased CSF levels of interleukin (IL)-6 compared with healthy volunteers. In patients, we also observed a positive correlation between IL-6 and the tryptophan:KYNA ratio, indicating that IL-6 activates the KYN pathway. In line with this, application of IL-6 to cultured human astrocytes increased cell medium concentration of KYNA. Limitations The CSF samples had been frozen and thawed twice before analysis of cytokines. Median age differed between patients and controls. When appropriate, all present analyses were adjusted for age. Conclusion We have shown that IL-6, KYN and KYNA are elevated in patients with chronic schizophrenia, strengthening the idea of brain immune activation in patients with this disease. Our concurrent cell culture and clinical findings suggest that IL-6 induces the KYN pathway, leading to increased production of the N-methyl-d-aspartate receptor antagonist KYNA in patients with schizophrenia. PMID:25455350

  8. Security Enrichment in Intrusion Detection System Using Classifier Ensemble

    Directory of Open Access Journals (Sweden)

    Uma R. Salunkhe

    2017-01-01

    Full Text Available In the era of Internet and with increasing number of people as its end users, a large number of attack categories are introduced daily. Hence, effective detection of various attacks with the help of Intrusion Detection Systems is an emerging trend in research these days. Existing studies show effectiveness of machine learning approaches in handling Intrusion Detection Systems. In this work, we aim to enhance detection rate of Intrusion Detection System by using machine learning technique. We propose a novel classifier ensemble based IDS that is constructed using hybrid approach which combines data level and feature level approach. Classifier ensembles combine the opinions of different experts and improve the intrusion detection rate. Experimental results show the improved detection rates of our system compared to reference technique.

  9. Human circulating plasma DNA significantly decreases while lymphocyte DNA damage increases under chronic occupational exposure to low-dose gamma-neutron and tritium β-radiation

    Energy Technology Data Exchange (ETDEWEB)

    Korzeneva, Inna B., E-mail: inna.korzeneva@molgen.vniief.ru [Russian Federal Nuclear Center – All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) 607190, Sarov, 37 Mira ave., Nizhniy Novgorod Region (Russian Federation); Kostuyk, Svetlana V.; Ershova, Liza S. [Research Centre for Medical Genetics, Russian Academy of Medical Sciences, 115478 Moscow, 1 Moskvorechye str. (Russian Federation); Osipov, Andrian N. [Federal Medial and Biological Center named after Burnazyan of the Federal Medical and Biological Agency (FMBTz named after Burnazyan of FMBA), Moscow (Russian Federation); State Research Center - Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, Zhivopisnaya, 46, Moscow, 123098 (Russian Federation); Zhuravleva, Veronika F.; Pankratova, Galina V. [Russian Federal Nuclear Center – All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) 607190, Sarov, 37 Mira ave., Nizhniy Novgorod Region (Russian Federation); Porokhovnik, Lev N.; Veiko, Natalia N. [Research Centre for Medical Genetics, Russian Academy of Medical Sciences, 115478 Moscow, 1 Moskvorechye str. (Russian Federation)

    2015-09-15

    Highlights: • The chronic exposure to low-dose IR induces DSBs in human lymphocytes (TM index). • Exposure to IR decreases the level of human circulating DNA (cfDNA index). • IR induces an increase of DNase1 activity (DNase1 index) in plasma. • IR induces an increase of the level of antibodies to DNA (Ab DNA index) in plasma. • The ratio cfDNA/(DNase 1 × Ab DNA × TM) is a potential marker of human exposure to IR. - Abstract: The blood plasma of healthy people contains cell-fee (circulating) DNA (cfDNA). Apoptotic cells are the main source of the cfDNA. The cfDNA concentration increases in case of the organism’s cell death rate increase, for example in case of exposure to high-dose ionizing radiation (IR). The objects of the present research are the blood plasma and blood lymphocytes of people, who contacted occupationally with the sources of external gamma/neutron radiation or internal β-radiation of tritium N = 176). As the controls (references), blood samples of people, who had never been occupationally subjected to the IR sources, were used (N = 109). With respect to the plasma samples of each donor there were defined: the cfDNA concentration (the cfDNA index), DNase1 activity (the DNase1 index) and titre of antibodies to DNA (the Ab DNA index). The general DNA damage in the cells was defined (using the Comet assay, the tail moment (TM) index). A chronic effect of the low-dose ionizing radiation on a human being is accompanied by the enhancement of the DNA damage in lymphocytes along with a considerable cfDNA content reduction, while the DNase1 content and concentration of antibodies to DNA (Ab DNA) increase. All the aforementioned changes were also observed in people, who had not worked with the IR sources for more than a year. The ratio cfDNA/(DNase1 × Ab DNA × TM) is proposed to be used as a marker of the chronic exposure of a person to the external low-dose IR. It was formulated the assumption that the joint analysis of the cfDNA, DNase1, Ab

  10. Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

    Science.gov (United States)

    Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

    2013-12-01

    Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

  11. Ibuprofen therapy resulted in significantly decreased tissue bacillary loads and increased survival in a new murine experimental model of active tuberculosis.

    Science.gov (United States)

    Vilaplana, Cristina; Marzo, Elena; Tapia, Gustavo; Diaz, Jorge; Garcia, Vanesa; Cardona, Pere-Joan

    2013-07-15

    C3HeB/FeJ mice infected with Mycobacterium tuberculosis were used in an experimental animal model mimicking active tuberculosis in humans to evaluate the effect of antiinflammatory agents. No other treatment but ibuprofen was given, and it was administered when the animals' health started to deteriorate. Animals treated with ibuprofen had statistically significant decreases in the size and number of lung lesions, decreases in the bacillary load, and improvements in survival, compared with findings for untreated animals. Because antiinflammatory agents are already on the market, further clinical trials should be done to evaluate this effect in humans as soon as possible, to determine their suitability as coadjuvant tuberculosis treatment.

  12. With or without a conductor: Comparative analysis of leadership models in the musical ensemble

    Directory of Open Access Journals (Sweden)

    Kovačević Mia

    2016-01-01

    Full Text Available In search of innovative models of work organization and therefore the artistic process of one musical ensemble, in the last ten years musical ensembles have developed examples of non-traditional artistic-performing decisions and organizational practice. The paper is conceived as a research and analysis of the dominant models of leadership (i.e. organizing, conducting business applicable on the music ensembles and experiences of the musicians. The aim is to recognize and define leadership styles that encourage the increase of motivation and productivity of musicians within the musical ensemble. The paper will specifically investigate the relationship and differences between the two dominant models of leadership, leadership of conductor and collaborative leadership. At the same time, the paper describes and analyses an experiment that was conducted by the Ensemble Metamorphosis, which applied into their work two dominant models of leadership. In an effort to increase the motivation and productivity of musicians, Ensemble Metamorphosis also searched for a new management model of work organization and a new model of leadership. The aim of this paper was therefore to investigate the effects of leadership models that improve the artistic quality, motivation of the musicians, psychological climate and overall increase productivity of musical organization.

  13. The stage-classified matrix models project a significant increase in biomass carbon stocks in China's forests between 2005 and 2050.

    Science.gov (United States)

    Hu, Huifeng; Wang, Shaopeng; Guo, Zhaodi; Xu, Bing; Fang, Jingyun

    2015-06-25

    China's forests are characterized by young age, low carbon (C) density and a large plantation area, implying a high potential for increasing C sinks in the future. Using data of provincial forest area and biomass C density from China's forest inventories between 1994 and 2008 and the planned forest coverage of the country by 2050, we developed a stage-classified matrix model to predict biomass C stocks of China's forests from 2005 to 2050. The results showed that total forest biomass C stock would increase from 6.43 Pg C (1 Pg = 10(15) g) in 2005 to 9.97 Pg C (95% confidence interval: 8.98 ~ 11.07 Pg C) in 2050, with an overall net C gain of 78.8 Tg C yr(-1) (56.7 ~ 103.3 Tg C yr(-1); 1 Tg = 10(12) g). Our findings suggest that China's forests will be a large and persistent biomass C sink through 2050.

  14. The stage-classified matrix models project a significant increase in biomass carbon stocks in China’s forests between 2005 and 2050

    Science.gov (United States)

    Hu, Huifeng; Wang, Shaopeng; Guo, Zhaodi; Xu, Bing; Fang, Jingyun

    2015-01-01

    China’s forests are characterized by young age, low carbon (C) density and a large plantation area, implying a high potential for increasing C sinks in the future. Using data of provincial forest area and biomass C density from China’s forest inventories between 1994 and 2008 and the planned forest coverage of the country by 2050, we developed a stage-classified matrix model to predict biomass C stocks of China’s forests from 2005 to 2050. The results showed that total forest biomass C stock would increase from 6.43 Pg C (1 Pg = 1015 g) in 2005 to 9.97 Pg C (95% confidence interval: 8.98 ~ 11.07 Pg C) in 2050, with an overall net C gain of 78.8 Tg C yr−1 (56.7 ~ 103.3 Tg C yr−1; 1 Tg = 1012 g). Our findings suggest that China’s forests will be a large and persistent biomass C sink through 2050. PMID:26110831

  15. Human circulating plasma DNA significantly decreases while lymphocyte DNA damage increases under chronic occupational exposure to low-dose gamma-neutron and tritium β-radiation.

    Science.gov (United States)

    Korzeneva, Inna B; Kostuyk, Svetlana V; Ershova, Liza S; Osipov, Andrian N; Zhuravleva, Veronika F; Pankratova, Galina V; Porokhovnik, Lev N; Veiko, Natalia N

    2015-09-01

    The blood plasma of healthy people contains cell-fee (circulating) DNA (cfDNA). Apoptotic cells are the main source of the cfDNA. The cfDNA concentration increases in case of the organism's cell death rate increase, for example in case of exposure to high-dose ionizing radiation (IR). The objects of the present research are the blood plasma and blood lymphocytes of people, who contacted occupationally with the sources of external gamma/neutron radiation or internal β-radiation of tritium N = 176). As the controls (references), blood samples of people, who had never been occupationally subjected to the IR sources, were used (N = 109). With respect to the plasma samples of each donor there were defined: the cfDNA concentration (the cfDNA index), DNase1 activity (the DNase1 index) and titre of antibodies to DNA (the Ab DNA index). The general DNA damage in the cells was defined (using the Comet assay, the tail moment (TM) index). A chronic effect of the low-dose ionizing radiation on a human being is accompanied by the enhancement of the DNA damage in lymphocytes along with a considerable cfDNA content reduction, while the DNase1 content and concentration of antibodies to DNA (Ab DNA) increase. All the aforementioned changes were also observed in people, who had not worked with the IR sources for more than a year. The ratio cfDNA/(DNase1×Ab DNA × TM) is proposed to be used as a marker of the chronic exposure of a person to the external low-dose IR. It was formulated the assumption that the joint analysis of the cfDNA, DNase1, Ab DNA and TM values may provide the information about the human organism's cell resistivity to chronic exposure to the low-dose IR and about the development of the adaptive response in the organism that is aimed, firstly, at the effective cfDNA elimination from the blood circulation, and, secondly - at survival of the cells, including the cells with the damaged DNA. Copyright © 2015. Published by Elsevier B.V.

  16. Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre- and Post-Processing in Sequential Data Assimilation

    Science.gov (United States)

    Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.

    2018-03-01

    Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.

  17. Assessing probabilistic predictions of ENSO phase and intensity from the North American Multimodel Ensemble

    Science.gov (United States)

    Tippett, Michael K.; Ranganathan, Meghana; L'Heureux, Michelle; Barnston, Anthony G.; DelSole, Timothy

    2017-05-01

    Here we examine the skill of three, five, and seven-category monthly ENSO probability forecasts (1982-2015) from single and multi-model ensemble integrations of the North American Multimodel Ensemble (NMME) project. Three-category forecasts are typical and provide probabilities for the ENSO phase (El Niño, La Niña or neutral). Additional forecast categories indicate the likelihood of ENSO conditions being weak, moderate or strong. The level of skill observed for differing numbers of forecast categories can help to determine the appropriate degree of forecast precision. However, the dependence of the skill score itself on the number of forecast categories must be taken into account. For reliable forecasts with same quality, the ranked probability skill score (RPSS) is fairly insensitive to the number of categories, while the logarithmic skill score (LSS) is an information measure and increases as categories are added. The ignorance skill score decreases to zero as forecast categories are added, regardless of skill level. For all models, forecast formats and skill scores, the northern spring predictability barrier explains much of the dependence of skill on target month and forecast lead. RPSS values for monthly ENSO forecasts show little dependence on the number of categories. However, the LSS of multimodel ensemble forecasts with five and seven categories show statistically significant advantages over the three-category forecasts for the targets and leads that are least affected by the spring predictability barrier. These findings indicate that current prediction systems are capable of providing more detailed probabilistic forecasts of ENSO phase and amplitude than are typically provided.

  18. Adaptive Encoding of Outcome Prediction by Prefrontal Cortex Ensembles Supports Behavioral Flexibility.

    Science.gov (United States)

    Del Arco, Alberto; Park, Junchol; Wood, Jesse; Kim, Yunbok; Moghaddam, Bita

    2017-08-30

    The prefrontal cortex (PFC) is thought to play a critical role in behavioral flexibility by monitoring action-outcome contingencies. How PFC ensembles represent shifts in behavior in response to changes in these contingencies remains unclear. We recorded single-unit activity and local field potentials in the dorsomedial PFC (dmPFC) of male rats during a set-shifting task that required them to update their behavior, among competing options, in response to changes in action-outcome contingencies. As behavior was updated, a subset of PFC ensembles encoded the current trial outcome before the outcome was presented. This novel outcome-prediction encoding was absent in a control task, in which actions were rewarded pseudorandomly, indicating that PFC neurons are not merely providing an expectancy signal. In both control and set-shifting tasks, dmPFC neurons displayed postoutcome discrimination activity, indicating that these neurons also monitor whether a behavior is successful in generating rewards. Gamma-power oscillatory activity increased before the outcome in both tasks but did not differentiate between expected outcomes, suggesting that this measure is not related to set-shifting behavior but reflects expectation of an outcome after action execution. These results demonstrate that PFC neurons support flexible rule-based action selection by predicting outcomes that follow a particular action. SIGNIFICANCE STATEMENT Tracking action-outcome contingencies and modifying behavior when those contingencies change is critical to behavioral flexibility. We find that ensembles of dorsomedial prefrontal cortex neurons differentiate between expected outcomes when action-outcome contingencies change. This predictive mode of signaling may be used to promote a new response strategy at the service of behavioral flexibility. Copyright © 2017 the authors 0270-6474/17/378363-11$15.00/0.

  19. Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.

    Science.gov (United States)

    Notaro, Marco; Schubach, Max; Robinson, Peter N; Valentini, Giorgio

    2017-10-12

    The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene-disease associations has been widely investigated, the related problem of gene-phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a "flat" learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of-the-art algorithms and with a significant reduction of the computational complexity. Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository.

  20. Evaluation of the NMC regional ensemble prediction system during the Beijing 2008 Olympic Games

    Science.gov (United States)

    Li, Xiaoli; Tian, Hua; Deng, Guo

    2011-10-01

    Based on the B08RDP (Beijing 2008 Olympic Games Mesoscale Ensemble Prediction Research and Development Project) that was launched by the World Weather Research Programme (WWRP) in 2004, a regional ensemble prediction system (REPS) at a 15-km horizontal resolution was developed at the National Meteorological Center (NMC) of the China Meteorological Administration (CMA). Supplementing to the forecasters' subjective affirmation on the promising performance of the REPS during the 2008 Beijing Olympic Games (BOG), this paper focuses on the objective verification of the REPS for precipitation forecasts during the BOG period. By use of a set of advanced probabilistic verification scores, the value of the REPS compared to the quasi-operational global ensemble prediction system (GEPS) is assessed for a 36-day period (21 July-24 August 2008). The evaluation here involves different aspects of the REPS and GEPS, including their general forecast skills, specific attributes (reliability and resolution), and related economic values. The results indicate that the REPS generally performs significantly better for the short-range precipitation forecasts than the GEPS, and for light to heavy rainfall events, the REPS provides more skillful forecasts for accumulated 6- and 24-h precipitation. By further identifying the performance of the REPS through the attribute-focused measures, it is found that the advantages of the REPS over the GEPS come from better reliability (smaller biases and better dispersion) and increased resolution. Also, evaluation of a decision-making score reveals that a much larger group of users benefits from using the REPS forecasts than using the single model (the control run) forecasts, especially for the heavy rainfall events.

  1. Ensemble encoding of nociceptive stimulus intensity in the rat medial and lateral pain systems

    Directory of Open Access Journals (Sweden)

    Woodward Donald J

    2011-08-01

    Full Text Available Abstract Background The ability to encode noxious stimulus intensity is essential for the neural processing of pain perception. It is well accepted that the intensity information is transmitted within both sensory and affective pathways. However, it remains unclear what the encoding patterns are in the thalamocortical brain regions, and whether the dual pain systems share similar responsibility in intensity coding. Results Multichannel single-unit recordings were used to investigate the activity of individual neurons and neuronal ensembles in the rat brain following the application of noxious laser stimuli of increasing intensity to the hindpaw. Four brain regions were monitored, including two within the lateral sensory pain pathway, namely, the ventral posterior lateral thalamic nuclei and the primary somatosensory cortex, and two in the medial pathway, namely, the medial dorsal thalamic nuclei and the anterior cingulate cortex. Neuron number, firing rate, and ensemble spike count codings were examined in this study. Our results showed that the noxious laser stimulation evoked double-peak responses in all recorded brain regions. Significant correlations were found between the laser intensity and the number of responsive neurons, the firing rates, as well as the mass spike counts (MSCs. MSC coding was generally more efficient than the other two methods. Moreover, the coding capacities of neurons in the two pathways were comparable. Conclusion This study demonstrated the collective contribution of medial and lateral pathway neurons to the noxious intensity coding. Additionally, we provide evidence that ensemble spike count may be the most reliable method for coding pain intensity in the brain.

  2. Ensemble based system for whole-slide prostate cancer probability mapping using color texture features.

    LENUS (Irish Health Repository)

    DiFranco, Matthew D

    2011-01-01

    We present a tile-based approach for producing clinically relevant probability maps of prostatic carcinoma in histological sections from radical prostatectomy. Our methodology incorporates ensemble learning for feature selection and classification on expert-annotated images. Random forest feature selection performed over varying training sets provides a subset of generalized CIEL*a*b* co-occurrence texture features, while sample selection strategies with minimal constraints reduce training data requirements to achieve reliable results. Ensembles of classifiers are built using expert-annotated tiles from training images, and scores for the probability of cancer presence are calculated from the responses of each classifier in the ensemble. Spatial filtering of tile-based texture features prior to classification results in increased heat-map coherence as well as AUC values of 95% using ensembles of either random forests or support vector machines. Our approach is designed for adaptation to different imaging modalities, image features, and histological decision domains.

  3. Sieve-based device for MALDI sample preparation. I. Influence of sample deposition conditions in oligonucleotide analysis to achieve significant increases in both sensitivity and resolution.

    Science.gov (United States)

    Molin, Laura; Cristoni, Simone; Crotti, Sara; Bernardi, Luigi Rossi; Seraglia, Roberta; Traldi, Pietro

    2008-11-01

    Spraying of oligonucleotide-matrix solutions through a stainless steel (ss) sieve (38 microm, 450 mesh) leads to the formation, on the matrix-assisted laser desorption/ionization (MALDI) sample holder, of uniformly distributed microcrystals, well separated from each other. When the resulting sample holder surface is irradiated by laser, abundant molecular species form, with a clear increase in both intensity and resolution with respect to values obtained by 'Dried Droplet', 'Double Layer', and 'Sandwich' deposition methods. In addition, unlike the usual situation, the sample is perfectly homogeneous, and identical spectra are obtained by irradiating different areas. On one hand, the data indicate that this method is highly effective for oligonucleotide MALDI analysis, and on the other, that it can be validly employed for fully automated MALDI procedures.

  4. Reinnervation of Vastus lateralis is increased significantly in seniors (70-years old with a lifelong history of high-level exercise

    Directory of Open Access Journals (Sweden)

    Simone Mosole

    2013-12-01

    Full Text Available It has long been recognized that histological changes observed in aging muscle suggest that denervation contributes to muscle deterioration and that disuse accelerates the process while running activity, sustained for decades, protects against age-related loss of motor units. Here we show at the histological level that lifelong increased physical activity promotes reinnervation of muscle fibers. In muscle biopsies from 70-year old men with a lifelong history of high-level physical activity, we observed a considerable increase in fiber-type groupings (almost exclusively of the slow type in comparison to sedentary seniors, revealing a large population of reinnervated muscle fibers in the sportsmen. Slow-type transformation by reinnervation in senior sportsmen seems to be a clinically relevant mechanism: the muscle biopsies fluctuate from those with scarce fiber-type transformation and groupings to almost fully transformed muscle, going through a process in which isolated fibers co-expressing fast and slow MHCs seems to fill the gaps. Taken together, our results suggest that, beyond the direct effects of aging on the muscle fibers, changes occurring in skeletal muscle tissue appear to be largely, although not solely, a result of sparse denervation. Our data suggest that lifelong exercise allows the body to adapt to the consequences of the age-related denervation and to preserve muscle structure and function by saving otherwise lost muscle fibers through recruitment to different, mainly slow, motor units. These beneficial effects on motoneurons and, subsequently on muscle fibers, serve to maintain size, structure and function of muscle fibers, delaying the functional decline and loss of independence that are commonly seen in late aging.

  5. Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

    KAUST Repository

    Toye, Habib

    2017-05-26

    We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

  6. Conjugation of the CRM197-inulin conjugate significantly increases the immunogenicity of Mycobacterium tuberculosis CFP10-TB10.4 fusion protein.

    Science.gov (United States)

    Hu, Shun; Yu, Weili; Hu, Chunyang; Wei, Dong; Shen, Lijuan; Hu, Tao; Yi, Youjin

    2017-11-01

    Mycobacterium tuberculosis (Mtb) is a serious fatal pathogen that causes tuberculosis (TB). Effective vaccination is urgently needed to deal with the serious threat from TB. Mtb-secreted protein antigens are important virulence determinants of Mtb with poor immunogenicity. Adjuvants and antigen delivery systems are thus highly desired to improve the immunogenicity of protein antigens. Inulin is a biocompatible polysaccharide (PS) adjuvant that can stimulate a strong cellular and humoral immunity. Bacterial capsular PS and haptens have been conjugated with cross-reacting material 197 (CRM 197 ) to improve their immunogenicity. CFP10 and TB10.4 were two Mtb-secreted immunodominant protein antigens. A CFP10-TB10.4 fusion protein (CT) was used as the antigen for covalent conjugation with the CRM 197 -inulin conjugate (CRM-inu). The resultant conjugate (CT-CRM-inu) elicited high CT-specific IgG titers, stimulated splenocyte proliferation and provoked the secretion of Th1-type and Th2-type cytokines. Conjugation with CRM-inu significantly prolonged the systemic circulation of CT and exposure to the immune system. Moreover, CT-CRM-inu showed no apparent toxicity to cardiac, hepatic and renal functions. Thus, conjugation of CT with CRM-inu provided an effective strategy for development of protein-based vaccines against Mtb infection. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Repeated oral administration of a cathepsin K inhibitor significantly suppresses bone resorption in exercising horses with evidence of increased bone formation and maintained bone turnover.

    Science.gov (United States)

    Hussein, H; Dulin, J; Smanik, L; Drost, W T; Russell, D; Wellman, M; Bertone, A

    2017-08-01

    Our investigations evaluated the effect of VEL-0230, a highly specific irreversible inhibitor of cathepsin K (CatK). The objectives of our study were to determine whether repeated dosing of a CatK inhibitor (CatKI) produced a desired inhibition of the bone resorption biomarker (CTX-1), and document the effect of repeated dosing on bone homeostasis, structure, and dynamics of bone resorption and formation in horses. Twelve young exercising horses were randomized in a prospective, controlled clinical trial and received 4 weekly doses of a CatKI or vehicle. Baseline and poststudy nuclear scintigraphy, blood sampling and analysis of plasma bone biomarkers (CTX-1 and osteocalcin), poststudy bone fluorescent labeling, and bone biopsy were performed. Bone specimens were further processed for microcomputed tomography and bone histomorphometry. Each dose of this CatKI transiently inhibited plasma CTX-1 (reflecting inhibition of bone collagen resorption) and increased bone plasma osteocalcin concentrations, with no detectable adverse effect on normal bone turnover in the face of exercise. Bone morphology, density, and formation rate were not different between control and treated group. Further investigation of CatK inhibition in abnormal bone turnover is required in animals with bone diseases. © 2016 John Wiley & Sons Ltd.

  8. Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles

    Directory of Open Access Journals (Sweden)

    Gengjie Jia

    2012-11-01

    Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.

  9. Village Building Identification Based on Ensemble Convolutional Neural Networks

    Science.gov (United States)

    Guo, Zhiling; Chen, Qi; Xu, Yongwei; Shibasaki, Ryosuke; Shao, Xiaowei

    2017-01-01

    In this study, we present the Ensemble Convolutional Neural Network (ECNN), an elaborate CNN frame formulated based on ensembling state-of-the-art CNN models, to identify village buildings from open high-resolution remote sensing (HRRS) images. First, to optimize and mine the capability of CNN for village mapping and to ensure compatibility with our classification targets, a few state-of-the-art models were carefully optimized and enhanced based on a series of rigorous analyses and evaluations. Second, rather than directly implementing building identification by using these models, we exploited most of their advantages by ensembling their feature extractor parts into a stronger model called ECNN based on the multiscale feature learning method. Finally, the generated ECNN was applied to a pixel-level classification frame to implement object identification. The proposed method can serve as a viable tool for village building identification with high accuracy and efficiency. The experimental results obtained from the test area in Savannakhet province, Laos, prove that the proposed ECNN model significantly outperforms existing methods, improving overall accuracy from 96.64% to 99.26%, and kappa from 0.57 to 0.86. PMID:29084154

  10. Comprehensive Study on Lexicon-based Ensemble Classification Sentiment Analysis

    Directory of Open Access Journals (Sweden)

    Łukasz Augustyniak

    2015-12-01

    Full Text Available We propose a novel method for counting sentiment orientation that outperforms supervised learning approaches in time and memory complexity and is not statistically significantly different from them in accuracy. Our method consists of a novel approach to generating unigram, bigram and trigram lexicons. The proposed method, called frequentiment, is based on calculating the frequency of features (words in the document and averaging their impact on the sentiment score as opposed to documents that do not contain these features. Afterwards, we use ensemble classification to improve the overall accuracy of the method. What is important is that the frequentiment-based lexicons with sentiment threshold selection outperform other popular lexicons and some supervised learners, while being 3–5 times faster than the supervised approach. We compare 37 methods (lexicons, ensembles with lexicon’s predictions as input and supervised learners applied to 10 Amazon review data sets and provide the first statistical comparison of the sentiment annotation methods that include ensemble approaches. It is one of the most comprehensive comparisons of domain sentiment analysis in the literature.

  11. Disease-associated mutations that alter the RNA structural ensemble.

    Directory of Open Access Journals (Sweden)

    Matthew Halvorsen

    2010-08-01

    Full Text Available Genome-wide association studies (GWAS often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs from the Human Gene Mutation Database (HGMD that map to the untranslated regions (UTRs of a gene. Rather than using minimum free energy approaches (e.g. mFold, we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, beta-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD, and Hypertension, we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5' UTRs of FTL and RB1 SNP-induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a "RiboSNitch," that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble.

  12. Hybrid vs Adaptive Ensemble Kalman Filtering for Storm Surge Forecasting

    Science.gov (United States)

    Altaf, M. U.; Raboudi, N.; Gharamti, M. E.; Dawson, C.; McCabe, M. F.; Hoteit, I.

    2014-12-01

    Recent storm surge events due to Hurricanes in the Gulf of Mexico have motivated the efforts to accurately forecast water levels. Toward this goal, a parallel architecture has been implemented based on a high resolution storm surge model, ADCIRC. However the accuracy of the model notably depends on the quality and the recentness of the input data (mainly winds and bathymetry), model parameters (e.g. wind and bottom drag coefficients), and the resolution of the model grid. Given all these uncertainties in the system, the challenge is to build an efficient prediction system capable of providing accurate forecasts enough ahead of time for the authorities to evacuate the areas at risk. We have developed an ensemble-based data assimilation system to frequently assimilate available data into the ADCIRC model in order to improve the accuracy of the model. In this contribution we study and analyze the performances of different ensemble Kalman filter methodologies for efficient short-range storm surge forecasting, the aim being to produce the most accurate forecasts at the lowest possible computing time. Using Hurricane Ike meteorological data to force the ADCIRC model over a domain including the Gulf of Mexico coastline, we implement and compare the forecasts of the standard EnKF, the hybrid EnKF and an adaptive EnKF. The last two schemes have been introduced as efficient tools for enhancing the behavior of the EnKF when implemented with small ensembles by exploiting information from a static background covariance matrix. Covariance inflation and localization are implemented in all these filters. Our results suggest that both the hybrid and the adaptive approach provide significantly better forecasts than those resulting from the standard EnKF, even when implemented with much smaller ensembles.

  13. Deficiencies in both starch synthase IIIa and branching enzyme IIb lead to a significant increase in amylose in SSIIa-inactive japonica rice seeds.

    Science.gov (United States)

    Asai, Hiroki; Abe, Natsuko; Matsushima, Ryo; Crofts, Naoko; Oitome, Naoko F; Nakamura, Yasunori; Fujita, Naoko

    2014-10-01

    Starch synthase (SS) IIIa has the second highest activity of the total soluble SS activity in developing rice endosperm. Branching enzyme (BE) IIb is the major BE isozyme, and is strongly expressed in developing rice endosperm. A mutant (ss3a/be2b) was generated from wild-type japonica rice which lacks SSIIa activity. The seed weight of ss3a/be2b was 74-94% of that of the wild type, whereas the be2b seed weight was 59-73% of that of the wild type. There were significantly fewer amylopectin short chains [degree of polymerization (DP) ≤13] in ss3a/be2b compared with the wild type. In contrast, the amount of long chains (DP ≥25) connecting clusters of amylopectin in ss3a/be2b was higher than in the wild type and lower than in be2b. The apparent amylose content of ss3a/be2b was 45%, which was >1.5 times greater than that of either ss3a or be2b. Both SSIIIa and BEIIb deficiencies led to higher activity of ADP-glucose pyrophosphorylase (AGPase) and granule-bound starch synthase I (GBSSI), which partly explains the high amylose content in the ss3a/be2b endosperm. The percentage apparent amylose content of ss3a and ss3a/be2b at 10 days after flowering (DAF) was higher than that of the wild type and be2b. At 20 DAF, amylopectin biosynthesis in be2b and ss3a/be2b was not observed, whereas amylose biosynthesis in these lines was accelerated at 30 DAF. These data suggest that the high amylose content in the ss3a/be2b mutant results from higher amylose biosynthesis at two stages, up to 20 DAF and from 30 DAF to maturity. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  14. Ensemble stacking mitigates biases in inference of synaptic connectivity.

    Science.gov (United States)

    Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N

    2018-01-01

    A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.

  15. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    Science.gov (United States)

    Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.

    2012-12-01

    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological ensemble prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  16. High fasting blood glucose and obesity significantly and independently increase risk of breast cancer death in hormone receptor-positive disease.

    Science.gov (United States)

    Minicozzi, Pamela; Berrino, Franco; Sebastiani, Federica; Falcini, Fabio; Vattiato, Rosa; Cioccoloni, Francesca; Calagreti, Gioia; Fusco, Mario; Vitale, Maria Francesca; Tumino, Rosario; Sigona, Aurora; Budroni, Mario; Cesaraccio, Rosaria; Candela, Giuseppa; Scuderi, Tiziana; Zarcone, Maurizio; Campisi, Ildegarda; Sant, Milena

    2013-12-01

    We investigated the effect of fasting blood glucose and body mass index (BMI) at diagnosis on risk of breast cancer death for cases diagnosed in five Italian cancer registries in 2003-2005 and followed up to the end of 2008. For 1607 Italian women (≥15 years) with information on BMI or blood glucose or diabetes, we analysed the risk of breast cancer death in relation to glucose tertiles (≤84.0, 84.1-94.0, >94.0 mg/dl) plus diabetic and unspecified categories; BMI tertiles (≤23.4, 23.5-27.3, >27.3 kg/m(2), unspecified), stage (T1-3N0M0, T1-3N+M0 plus T4anyNM0, M1, unspecified), oestrogen (ER) and progesterone (PR) status (ER+PR+, ER-PR-, ER and PR unspecified, other), age, chemotherapy and endocrine therapy, using multiple regression models. Separate models for ER+PR+ and ER-PR- cases were also run. Patients often had T1-3N0M0, ER+PR+ cancers and received chemotherapy or endocrine therapy; only 6% were M1 and 17% ER-PR-. Diabetic patients were older and had more often high BMI (>27 kg/m(2)), ER-PR-, M1 cancers than other patients. For ER+PR+ cases, with adjustment for other variables, breast cancer mortality was higher in women with high BMI than those with BMI 23.5-27.3 kg/m(2) (hazard ratio (HR)=2.9, 95% confidence interval (CI) 1.2-6.9). Breast cancer mortality was also higher in women with high (>94 mg/dl) blood glucose compared to those with glucose 84.1-94.0mg/dl (HR=2.6, 95% CI 1.2-5.7). Our results provide evidence that in ER+PR+ patients, high blood glucose and high BMI are independently associated with increased risk of breast cancer death. Detection and correction of these factors in such patients may improve prognosis. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Site-directed immobilization of a genetically engineered anti-methotrexate antibody via an enzymatically introduced biotin label significantly increases the binding capacity of immunoaffinity columns.

    Science.gov (United States)

    Davenport, Kaitlynn R; Smith, Christopher A; Hofstetter, Heike; Horn, James R; Hofstetter, Oliver

    2016-05-15

    In this study, the effect of random vs. site-directed immobilization techniques on the performance of antibody-based HPLC columns was investigated using a single-domain camelid antibody (VHH) directed against methotrexate (MTX) as a model system. First, the high flow-through support material POROS-OH was activated with disuccinimidyl carbonate (DSC), and the VHH was bound in a random manner via amines located on the protein's surface. The resulting column was characterized by Frontal Affinity Chromatography (FAC). Then, two site-directed techniques were explored to increase column efficiency by immobilizing the antibody via its C-terminus, i.e., away from the antigen-binding site. In one approach, a tetra-lysine tail was added, and the antibody was immobilized onto DSC-activated POROS. In the second site-directed approach, the VHH was modified with the AviTag peptide, and a biotin-residue was enzymatically incorporated at the C-terminus using the biotin ligase BirA. The biotinylated antibody was subsequently immobilized onto NeutrAvidin-derivatized POROS. A comparison of the FAC analyses, which for all three columns showed excellent linearity (R(2)>0.999), revealed that both site-directed approaches yield better results than the random immobilization; the by far highest efficiency, however, was determined for the immunoaffinity column based on AviTag-biotinylated antibody. As proof of concept, all three columns were evaluated for quantification of MTX dissolved in phosphate buffered saline (PBS). Validation using UV-detection showed excellent linearity in the range of 0.04-12μM (R(2)>0.993). The lower limit of detection (LOD) and lower limit of quantification (LLOQ) were found to be independent of the immobilization strategy and were 40nM and 132nM, respectively. The intra- and inter-day precision was below 11.6%, and accuracy was between 90.7% and 112%. To the best of our knowledge, this is the first report of the AviTag-system in chromatography, and the first

  18. Understanding ensemble protein folding at atomic detail

    International Nuclear Information System (INIS)

    Wallin, Stefan; Shakhnovich, Eugene I

    2008-01-01

    Although far from routine, simulating the folding of specific short protein chains on the computer, at a detailed atomic level, is starting to become a reality. This remarkable progress, which has been made over the last decade or so, allows a fundamental aspect of the protein folding process to be addressed, namely its statistical nature. In order to make quantitative comparisons with experimental kinetic data a complete ensemble view of folding must be achieved, with key observables averaged over the large number of microscopically different folding trajectories available to a protein chain. Here we review recent advances in atomic-level protein folding simulations and the new insight provided by them into the protein folding process. An important element in understanding ensemble folding kinetics are methods for analyzing many separate folding trajectories, and we discuss techniques developed to condense the large amount of information contained in an ensemble of trajectories into a manageable picture of the folding process. (topical review)

  19. Lattice gauge theory in the microcanonical ensemble

    International Nuclear Information System (INIS)

    Callaway, D.J.E.; Rahman, A.

    1983-01-01

    The microcanonical-ensemble formulation of lattice gauge theory proposed recently is examined in detail. Expectation values in this new ensemble are determined by solving a large set of coupled ordinary differential equations, after the fashion of a molecular dynamics simulation. Following a brief review of the microcanonical ensemble, calculations are performed for the gauge groups U(1), SU(2), and SU(3). The results are compared and contrasted with standard methods of computation. Several advantages of the new formalism are noted. For example, no random numbers are required to update the system. Also, this update is performed in a simultaneous fashion. Thus the microcanonical method presumably adapts well to parallel processing techniques, especially when the p action is highly nonlocal (such as when fermions are included)

  20. A Fault-Tolerant HPC Scheduler Extension for Large and Operational Ensemble Data Assimilation:Application to the Red Sea

    KAUST Repository

    Toye, Habib

    2018-04-26

    A fully parallel ensemble data assimilation and forecasting system has been developed for the Red Sea based on the MIT general circulation model (MITgcm) to simulate the Red Sea circulation and the Data Assimilation Research Testbed (DART) ensemble assimilation software. An important limitation of operational ensemble assimilation systems is the risk of ensemble members’ collapse. This could happen in those situations when the filter update step imposes large corrections on one, or more, of the forecasted ensemble members that are not fully consistent with the model physics. Increasing the ensemble size is expected to improve the assimilation system performances, but obviously increases the risk of members’ collapse. Hardware failure or slow numerical convergence encountered for some members should also occur more frequently. In this context, the manual steering of the whole process appears as a real challenge and makes the implementation of the ensemble assimilation procedure uneasy and extremely time consuming.This paper presents our efforts to build an efficient and fault-tolerant MITgcm-DART ensemble assimilation system capable of operationally running thousands of members. Built on top of Decimate, a scheduler extension developed to ease the submission, monitoring and dynamic steering of workflow of dependent jobs in a fault-tolerant environment, we describe the assimilation system implementation and discuss in detail its coupling strategies. Within Decimate, only a few additional lines of Python is needed to define flexible convergence criteria and to implement any necessary actions to the forecast ensemble members, as for instance (i) restarting faulty job in case of job failure, (ii) changing the random seed in case of poor convergence or numerical instability, (iii) adjusting (reducing or increasing) the number of parallel forecasts on the fly, (iv) replacing members on the fly to enrich the ensemble with new members, etc.We demonstrate the efficiency

  1. Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP.

    Directory of Open Access Journals (Sweden)

    Yoonsik Shim

    2016-10-01

    Full Text Available We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP. The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture.

  2. Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP.

    Science.gov (United States)

    Shim, Yoonsik; Philippides, Andrew; Staras, Kevin; Husbands, Phil

    2016-10-01

    We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP). The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM) networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture.

  3. Ensemble Kalman methods for inverse problems

    International Nuclear Information System (INIS)

    Iglesias, Marco A; Law, Kody J H; Stuart, Andrew M

    2013-01-01

    The ensemble Kalman filter (EnKF) was introduced by Evensen in 1994 (Evensen 1994 J. Geophys. Res. 99 10143–62) as a novel method for data assimilation: state estimation for noisily observed time-dependent problems. Since that time it has had enormous impact in many application domains because of its robustness and ease of implementation, and numerical evidence of its accuracy. In this paper we propose the application of an iterative ensemble Kalman method for the solution of a wide class of inverse problems. In this context we show that the estimate of the unknown function that we obtain with the ensemble Kalman method lies in a subspace A spanned by the initial ensemble. Hence the resulting error may be bounded above by the error found from the best approximation in this subspace. We provide numerical experiments which compare the error incurred by the ensemble Kalman method for inverse problems with the error of the best approximation in A, and with variants on traditional least-squares approaches, restricted to the subspace A. In so doing we demonstrate that the ensemble Kalman method for inverse problems provides a derivative-free optimization method with comparable accuracy to that achieved by traditional least-squares approaches. Furthermore, we also demonstrate that the accuracy is of the same order of magnitude as that achieved by the best approximation. Three examples are used to demonstrate these assertions: inversion of a compact linear operator; inversion of piezometric head to determine hydraulic conductivity in a Darcy model of groundwater flow; and inversion of Eulerian velocity measurements at positive times to determine the initial condition in an incompressible fluid. (paper)

  4. Stochastic resonance of ensemble neurons for transient spike trains: Wavelet analysis

    International Nuclear Information System (INIS)

    Hasegawa, Hideo

    2002-01-01

    By using the wavelet transformation (WT), I have analyzed the response of an ensemble of N (=1, 10, 100, and 500) Hodgkin-Huxley neurons to transient M-pulse spike trains (M=1 to 3) with independent Gaussian noises. The cross correlation between the input and output signals is expressed in terms of the WT expansion coefficients. The signal-to-noise ratio (SNR) is evaluated by using the denoising method within the WT, by which the noise contribution is extracted from the output signals. Although the response of a single (N=1) neuron to subthreshold transient signals with noises is quite unreliable, the transmission fidelity assessed by the cross correlation and SNR is shown to be much improved by increasing the value of N: a population of neurons plays an indispensable role in the stochastic resonance (SR) for transient spike inputs. It is also shown that in a large-scale ensemble, the transmission fidelity for suprathreshold transient spikes is not significantly degraded by a weak noise which is responsible to SR for subthreshold inputs

  5. A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS Soil Moisture: Retrieval Ensembles

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2015-12-01

    Full Text Available Bias correction is a very important pre-processing step in satellite data assimilation analysis, as data assimilation itself cannot circumvent satellite biases. We introduce a retrieval algorithm-specific and spatially heterogeneous Instantaneous Field of View (IFOV bias correction method for Soil Moisture and Ocean Salinity (SMOS soil moisture. To the best of our knowledge, this is the first paper to present the probabilistic presentation of SMOS soil moisture using retrieval ensembles. We illustrate that retrieval ensembles effectively mitigated the overestimation problem of SMOS soil moisture arising from brightness temperature errors over West Africa in a computationally efficient way (ensemble size: 12, no time-integration. In contrast, the existing method of Cumulative Distribution Function (CDF matching considerably increased the SMOS biases, due to the limitations of relying on the imperfect reference data. From the validation at two semi-arid sites, Benin (moderately wet and vegetated area and Niger (dry and sandy bare soils, it was shown that the SMOS errors arising from rain and vegetation attenuation were appropriately corrected by ensemble approaches. In Benin, the Root Mean Square Errors (RMSEs decreased from 0.1248 m3/m3 for CDF matching to 0.0678 m3/m3 for the proposed ensemble approach. In Niger, the RMSEs decreased from 0.14 m3/m3 for CDF matching to 0.045 m3/m3 for the ensemble approach.

  6. An Effective and Novel Neural Network Ensemble for Shift Pattern Detection in Control Charts

    Directory of Open Access Journals (Sweden)

    Mahmoud Barghash

    2015-01-01

    Full Text Available Pattern recognition in control charts is critical to make a balance between discovering faults as early as possible and reducing the number of false alarms. This work is devoted to designing a multistage neural network ensemble that achieves this balance which reduces rework and scrape without reducing productivity. The ensemble under focus is composed of a series of neural network stages and a series of decision points. Initially, this work compared using multidecision points and single-decision point on the performance of the ANN which showed that multidecision points are highly preferable to single-decision points. This work also tested the effect of population percentages on the ANN and used this to optimize the ANN’s performance. Also this work used optimized and nonoptimized ANNs in an ensemble and proved that using nonoptimized ANN may reduce the performance of the ensemble. The ensemble that used only optimized ANNs has improved performance over individual ANNs and three-sigma level rule. In that respect using the designed ensemble can help in reducing the number of false stops and increasing productivity. It also can be used to discover even small shifts in the mean as early as possible.

  7. Cluster ensembles, quantization and the dilogarithm

    DEFF Research Database (Denmark)

    Fock, Vladimir; Goncharov, Alexander B.

    2009-01-01

    A cluster ensemble is a pair of positive spaces (i.e. varieties equipped with positive atlases), coming with an action of a symmetry group . The space is closely related to the spectrum of a cluster algebra [ 12 ]. The two spaces are related by a morphism . The space is equipped with a closed -form......, possibly degenerate, and the space has a Poisson structure. The map is compatible with these structures. The dilogarithm together with its motivic and quantum avatars plays a central role in the cluster ensemble structure. We define a non-commutative -deformation of the -space. When is a root of unity...

  8. Assessing an ensemble Kalman filter inference of Manning’s n coefficient of an idealized tidal inlet against a polynomial chaos-based MCMC

    KAUST Repository

    Siripatana, Adil

    2017-06-08

    Bayesian estimation/inversion is commonly used to quantify and reduce modeling uncertainties in coastal ocean model, especially in the framework of parameter estimation. Based on Bayes rule, the posterior probability distribution function (pdf) of the estimated quantities is obtained conditioned on available data. It can be computed either directly, using a Markov chain Monte Carlo (MCMC) approach, or by sequentially processing the data following a data assimilation approach, which is heavily exploited in large dimensional state estimation problems. The advantage of data assimilation schemes over MCMC-type methods arises from the ability to algorithmically accommodate a large number of uncertain quantities without significant increase in the computational requirements. However, only approximate estimates are generally obtained by this approach due to the restricted Gaussian prior and noise assumptions that are generally imposed in these methods. This contribution aims at evaluating the effectiveness of utilizing an ensemble Kalman-based data assimilation method for parameter estimation of a coastal ocean model against an MCMC polynomial chaos (PC)-based scheme. We focus on quantifying the uncertainties of a coastal ocean ADvanced CIRCulation (ADCIRC) model with respect to the Manning’s n coefficients. Based on a realistic framework of observation system simulation experiments (OSSEs), we apply an ensemble Kalman filter and the MCMC method employing a surrogate of ADCIRC constructed by a non-intrusive PC expansion for evaluating the likelihood, and test both approaches under identical scenarios. We study the sensitivity of the estimated posteriors with respect to the parameters of the inference methods, including ensemble size, inflation factor, and PC order. A full analysis of both methods, in the context of coastal ocean model, suggests that an ensemble Kalman filter with appropriate ensemble size and well-tuned inflation provides reliable mean estimates and

  9. Assessing an ensemble Kalman filter inference of Manning's n coefficient of an idealized tidal inlet against a polynomial chaos-based MCMC

    Science.gov (United States)

    Siripatana, Adil; Mayo, Talea; Sraj, Ihab; Knio, Omar; Dawson, Clint; Le Maitre, Olivier; Hoteit, Ibrahim

    2017-08-01

    Bayesian estimation/inversion is commonly used to quantify and reduce modeling uncertainties in coastal ocean model, especially in the framework of parameter estimation. Based on Bayes rule, the posterior probability distribution function (pdf) of the estimated quantities is obtained conditioned on available data. It can be computed either directly, using a Markov chain Monte Carlo (MCMC) approach, or by sequentially processing the data following a data assimilation approach, which is heavily exploited in large dimensional state estimation problems. The advantage of data assimilation schemes over MCMC-type methods arises from the ability to algorithmically accommodate a large number of uncertain quantities without significant increase in the computational requirements. However, only approximate estimates are generally obtained by this approach due to the restricted Gaussian prior and noise assumptions that are generally imposed in these methods. This contribution aims at evaluating the effectiveness of utilizing an ensemble Kalman-based data assimilation method for parameter estimation of a coastal ocean model against an MCMC polynomial chaos (PC)-based scheme. We focus on quantifying the uncertainties of a coastal ocean ADvanced CIRCulation (ADCIRC) model with respect to the Manning's n coefficients. Based on a realistic framework of observation system simulation experiments (OSSEs), we apply an ensemble Kalman filter and the MCMC method employing a surrogate of ADCIRC constructed by a non-intrusive PC expansion for evaluating the likelihood, and test both approaches under identical scenarios. We study the sensitivity of the estimated posteriors with respect to the parameters of the inference methods, including ensemble size, inflation factor, and PC order. A full analysis of both methods, in the context of coastal ocean model, suggests that an ensemble Kalman filter with appropriate ensemble size and well-tuned inflation provides reliable mean estimates and

  10. A class of energy-based ensembles in Tsallis statistics

    International Nuclear Information System (INIS)

    Chandrashekar, R; Naina Mohammed, S S

    2011-01-01

    A comprehensive investigation is carried out on the class of energy-based ensembles. The eight ensembles are divided into two main classes. In the isothermal class of ensembles the individual members are at the same temperature. A unified framework is evolved to describe the four isothermal ensembles using the currently accepted third constraint formalism. The isothermal–isobaric, grand canonical and generalized ensembles are illustrated through a study of the classical nonrelativistic and extreme relativistic ideal gas models. An exact calculation is possible only in the case of the isothermal–isobaric ensemble. The study of the ideal gas models in the grand canonical and the generalized ensembles has been carried out using a perturbative procedure with the nonextensivity parameter (1 − q) as the expansion parameter. Though all the thermodynamic quantities have been computed up to a particular order in (1 − q) the procedure can be extended up to any arbitrary order in the expansion parameter. In the adiabatic class of ensembles the individual members of the ensemble have the same value of the heat function and a unified formulation to described all four ensembles is given. The nonrelativistic and the extreme relativistic ideal gases are studied in the isoenthalpic–isobaric ensemble, the adiabatic ensemble with number fluctuations and the adiabatic ensemble with number and particle fluctuations

  11. How will precipitation change in extratropical cyclones as the planet warms? Insights from a large initial condition climate model ensemble

    Science.gov (United States)

    Yettella, Vineel; Kay, Jennifer E.

    2017-09-01

    The extratropical precipitation response to global warming is investigated within a 30-member initial condition climate model ensemble. As in observations, modeled cyclonic precipitation contributes a large fraction of extratropical precipitation, especially over the ocean and in the winter hemisphere. When compared to present day, the ensemble projects increased cyclone-associated precipitation under twenty-first century business-as-usual greenhouse gas forcing. While the cyclone-associated precipitation response is weaker in the near-future (2016-2035) than in the far-future (2081-2100), both future periods have similar patterns of response. Though cyclone frequency changes are important regionally, most of the increased cyclone-associated precipitation results from increased within-cyclone precipitation. Consistent with this result, cyclone-centric composites show statistically significant precipitation increases in all cyclone sectors. Decomposition into thermodynamic (mean cyclone water vapor path) and dynamic (mean cyclone wind speed) contributions shows that thermodynamics explains 92 and 95% of the near-future and far-future within-cyclone precipitation increases respectively. Surprisingly, the influence of dynamics on future cyclonic precipitation changes is negligible. In addition, the forced response exceeds internal variability in both future time periods. Overall, this work suggests that future cyclonic precipitation changes will result primarily from increased moisture availability in a warmer world, with secondary contributions from changes in cyclone frequency and cyclone dynamics.

  12. Ensemble stacking mitigates biases in inference of synaptic connectivity

    Directory of Open Access Journals (Sweden)

    Brendan Chambers

    2018-03-01

    Full Text Available A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches. Mapping the routing of spikes through local circuitry is crucial for understanding neocortical computation. Under appropriate experimental conditions, these maps can be used to infer likely patterns of synaptic recruitment, linking activity to underlying anatomical connections. Such inferences help to reveal the synaptic implementation of population dynamics and computation. We compare a number of standard functional measures to infer underlying connectivity. We find that regularization impacts measures

  13. Kinetics of particle ensembles with variable charges

    International Nuclear Information System (INIS)

    Ivlev, A. V.; Zhdanov, S.; Klumov, B.; Morfill, G.; Tsytovich, V. N.; Angelis, U. de

    2005-01-01

    One of the remarkable features distinguishing complex (dusty) plasmas from usual plasmas is that charges on the grains are not constant, but fluctuate in time around some equilibrium value which, in then, is some function of spatial coordinates. Generally, ensembles of particles with variable charges are non-Hamiltonian systems where the mutual collisions do not conserve energy. Therefore, the use of thermodynamic potentials to describe such systems is not really valid. An appropriate way to investigate their evolution is to employ the kinetic approach. We studied (both analytical and numerically) two cases: (a) inhomogeneous charge-it depends on the particle coordinate but does not change in time, and (b)fluctuating charge-it changes in time around the equilibrium value, which is constant in space. For both cases we used the Fokker-Planck approach to derive the collision integral which describes the momentum and energy transfer in mutual particle collisions as well as in the collisions with neutrals. We obtained that the mean particle energy grows in time when the neutral friction is below a certain threshold (as shown in Fig. 1). In case (a) the energy changes as ∞(t c r-t)''2, in case (b) it scales as ∞(t c r-t)''-1, exhibiting the explosion-like growth with t c r a critical time scale. The obtained solutions can be of significant importance for laboratory dusty plasmas as well as for space plasma environments, where inhomogeneous charge distributions are often present. For instance, the instability can cause dust heating in low-pressure complex plasma experiments, it can be responsible for the melting of plasma crystals, it might operate in protoplanetary disks and effect the kinetics of the planet formation, etc. (Author)

  14. Ensemble composition and activity levels of insectivorous bats in response to management intensification in coffee agroforestry systems.

    Science.gov (United States)

    Williams-Guillén, Kimberly; Perfecto, Ivette

    2011-01-26

    Shade coffee plantations have received attention for their role in biodiversity conservation. Bats are among the most diverse mammalian taxa in these systems; however, previous studies of bats in coffee plantations have focused on the largely herbivorous leaf-nosed bats (Phyllostomidae). In contrast, we have virtually no information on how ensembles of aerial insectivorous bats--nearly half the Neotropical bat species--change in response to habitat modification. To evaluate the effects of agroecosystem management on insectivorous bats, we studied their diversity and activity in southern Chiapas, Mexico, a landscape dominated by coffee agroforestry. We used acoustic monitoring and live captures to characterize the insectivorous bat ensemble in forest fragments and coffee plantations differing in the structural and taxonomic complexity of shade trees. We captured bats of 12 non-phyllostomid species; acoustic monitoring revealed the presence of at least 12 more species of aerial insectivores. Richness of forest bats was the same across all land-use types; in contrast, species richness of open-space bats increased in low shade, intensively managed coffee plantations. Conversely, only forest bats demonstrated significant differences in ensemble structure (as measured by similarity indices) across land-use types. Both overall activity and feeding activity of forest bats declined significantly with increasing management intensity, while the overall activity, but not feeding activity, of open-space bats increased. We conclude that diverse shade coffee plantations in our study area serve as valuable foraging and commuting habitat for aerial insectivorous bats, and several species also commute through or forage in low shade coffee monocultures.

  15. Ensemble composition and activity levels of insectivorous bats in response to management intensification in coffee agroforestry systems.

    Directory of Open Access Journals (Sweden)

    Kimberly Williams-Guillén

    Full Text Available Shade coffee plantations have received attention for their role in biodiversity conservation. Bats are among the most diverse mammalian taxa in these systems; however, previous studies of bats in coffee plantations have focused on the largely herbivorous leaf-nosed bats (Phyllostomidae. In contrast, we have virtually no information on how ensembles of aerial insectivorous bats--nearly half the Neotropical bat species--change in response to habitat modification. To evaluate the effects of agroecosystem management on insectivorous bats, we studied their diversity and activity in southern Chiapas, Mexico, a landscape dominated by coffee agroforestry. We used acoustic monitoring and live captures to characterize the insectivorous bat ensemble in forest fragments and coffee plantations differing in the structural and taxonomic complexity of shade trees. We captured bats of 12 non-phyllostomid species; acoustic monitoring revealed the presence of at least 12 more species of aerial insectivores. Richness of forest bats was the same across all land-use types; in contrast, species richness of open-space bats increased in low shade, intensively managed coffee plantations. Conversely, only forest bats demonstrated significant differences in ensemble structure (as measured by similarity indices across land-use types. Both overall activity and feeding activity of forest bats declined significantly with increasing management intensity, while the overall activity, but not feeding activity, of open-space bats increased. We conclude that diverse shade coffee plantations in our study area serve as valuable foraging and commuting habitat for aerial insectivorous bats, and several species also commute through or forage in low shade coffee monocultures.

  16. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    Science.gov (United States)

    Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena

    2015-04-01

    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (www.hepex.org), HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  17. A method for ensemble wildland fire simulation

    Science.gov (United States)

    Mark A. Finney; Isaac C. Grenfell; Charles W. McHugh; Robert C. Seli; Diane Trethewey; Richard D. Stratton; Stuart Brittain

    2011-01-01

    An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis...

  18. The Phantasmagoria of Competition in School Ensembles

    Science.gov (United States)

    Abramo, Joseph Michael

    2017-01-01

    Participation in competition festivals--where students and ensembles compete against each other for high scores and accolades--is a widespread practice in North American formal music education. In this article, I use Marx's theories of labor, value, and phantasmagoria to suggest a capitalist logic that structures these competitions. Marx's…

  19. NYYD Ensemble ja Riho Sibul / Anneli Remme

    Index Scriptorium Estoniae

    Remme, Anneli, 1968-

    2001-01-01

    Gavin Bryarsi teos "Jesus' Blood Never Failed Me Yet" NYYD Ensemble'i ja Riho Sibula esituses 27. detsembril Pauluse kirikus Tartus ja 28. detsembril Rootsi- Mihkli kirikus Tallinnas. Kaastegevad Tartu Ülikooli Kammerkoor (Tartus) ja kammerkoor Voces Musicales (Tallinnas). Kunstiline juht Olari Elts

  20. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    NJD

    Improvements in neural network calibration models by a novel approach using neural network ensemble (NNE) for the simultaneous ... process by training a number of neural networks. .... Matlab® version 6.1 was employed for building principal component ... provide a fair simulation of calibration data set with some degree.

  1. A Theoretical Analysis of Why Hybrid Ensembles Work

    Directory of Open Access Journals (Sweden)

    Kuo-Wei Hsu

    2017-01-01

    Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

  2. Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

    Institute of Scientific and Technical Information of China (English)

    Zhaoxia PU; Joshua HACKER

    2009-01-01

    This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

  3. Ensemble of classifiers based network intrusion detection system performance bound

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-11-01

    Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

  4. Global Ensemble Forecast System (GEFS) [2.5 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  5. Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

    KAUST Repository

    Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim

    2017-01-01

    We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation

  6. Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

    KAUST Repository

    Luo, Xiaodong; Hoteit, Ibrahim

    2011-01-01

    A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used

  7. Limited-area short-range ensemble predictions targeted for heavy rain in Europe

    Directory of Open Access Journals (Sweden)

    K. Sattler

    2005-01-01

    Full Text Available Inherent uncertainties in short-range quantitative precipitation forecasts (QPF from the high-resolution, limited-area numerical weather prediction model DMI-HIRLAM (LAM are addressed using two different approaches to creating a small ensemble of LAM simulations, with focus on prediction of extreme rainfall events over European river basins. The first ensemble type is designed to represent uncertainty in the atmospheric state of the initial condition and at the lateral LAM boundaries. The global ensemble prediction system (EPS from ECMWF serves as host model to the LAM and provides the state perturbations, from which a small set of significant members is selected. The significance is estimated on the basis of accumulated precipitation over a target area of interest, which contains the river basin(s under consideration. The selected members provide the initial and boundary data for the ensemble integration in the LAM. A second ensemble approach tries to address a portion of the model-inherent uncertainty responsible for errors in the forecasted precipitation field by utilising different parameterisation schemes for condensation and convection in the LAM. Three periods around historical heavy rain events that caused or contributed to disastrous river flooding in Europe are used to study the performance of the LAM ensemble designs. The three cases exhibit different dynamic and synoptic characteristics and provide an indication of the ensemble qualities in different weather situations. Precipitation analyses from the Deutsche Wetterdienst (DWD are used as the verifying reference and a comparison of daily rainfall amounts is referred to the respective river basins of the historical cases.

  8. Quantum canonical ensemble: A projection operator approach

    Science.gov (United States)

    Magnus, Wim; Lemmens, Lucien; Brosens, Fons

    2017-09-01

    Knowing the exact number of particles N, and taking this knowledge into account, the quantum canonical ensemble imposes a constraint on the occupation number operators. The constraint particularly hampers the systematic calculation of the partition function and any relevant thermodynamic expectation value for arbitrary but fixed N. On the other hand, fixing only the average number of particles, one may remove the above constraint and simply factorize the traces in Fock space into traces over single-particle states. As is well known, that would be the strategy of the grand-canonical ensemble which, however, comes with an additional Lagrange multiplier to impose the average number of particles. The appearance of this multiplier can be avoided by invoking a projection operator that enables a constraint-free computation of the partition function and its derived quantities in the canonical ensemble, at the price of an angular or contour integration. Introduced in the recent past to handle various issues related to particle-number projected statistics, the projection operator approach proves beneficial to a wide variety of problems in condensed matter physics for which the canonical ensemble offers a natural and appropriate environment. In this light, we present a systematic treatment of the canonical ensemble that embeds the projection operator into the formalism of second quantization while explicitly fixing N, the very number of particles rather than the average. Being applicable to both bosonic and fermionic systems in arbitrary dimensions, transparent integral representations are provided for the partition function ZN and the Helmholtz free energy FN as well as for two- and four-point correlation functions. The chemical potential is not a Lagrange multiplier regulating the average particle number but can be extracted from FN+1 -FN, as illustrated for a two-dimensional fermion gas.

  9. Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

    Directory of Open Access Journals (Sweden)

    Matthew B Biggs

    2017-03-01

    Full Text Available Genome-scale metabolic network reconstructions (GENREs are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA. We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

  10. The classicality and quantumness of a quantum ensemble

    International Nuclear Information System (INIS)

    Zhu Xuanmin; Pang Shengshi; Wu Shengjun; Liu Quanhui

    2011-01-01

    In this Letter, we investigate the classicality and quantumness of a quantum ensemble. We define a quantity called ensemble classicality based on classical cloning strategy (ECCC) to characterize how classical a quantum ensemble is. An ensemble of commuting states has a unit ECCC, while a general ensemble can have a ECCC less than 1. We also study how quantum an ensemble is by defining a related quantity called quantumness. We find that the classicality of an ensemble is closely related to how perfectly the ensemble can be cloned, and that the quantumness of the ensemble used in a quantum key distribution (QKD) protocol is exactly the attainable lower bound of the error rate in the sifted key. - Highlights: → A quantity is defined to characterize how classical a quantum ensemble is. → The classicality of an ensemble is closely related to the cloning performance. → Another quantity is also defined to investigate how quantum an ensemble is. → This quantity gives the lower bound of the error rate in a QKD protocol.

  11. Exploring and Listening to Chinese Classical Ensembles in General Music

    Science.gov (United States)

    Zhang, Wenzhuo

    2017-01-01

    Music diversity is valued in theory, but the extent to which it is efficiently presented in music class remains limited. Within this article, I aim to bridge this gap by introducing four genres of Chinese classical ensembles--Qin and Xiao duets, Jiang Nan bamboo and silk ensembles, Cantonese ensembles, and contemporary Chinese orchestras--into the…

  12. Critical Listening in the Ensemble Rehearsal: A Community of Learners

    Science.gov (United States)

    Bell, Cindy L.

    2018-01-01

    This article explores a strategy for engaging ensemble members in critical listening analysis of performances and presents opportunities for improving ensemble sound through rigorous dialogue, reflection, and attentive rehearsing. Critical listening asks ensemble members to draw on individual playing experience and knowledge to describe what they…

  13. Changes in Appetitive Associative Strength Modulates Nucleus Accumbens, But Not Orbitofrontal Cortex Neuronal Ensemble Excitability.

    Science.gov (United States)

    Ziminski, Joseph J; Hessler, Sabine; Margetts-Smith, Gabriella; Sieburg, Meike C; Crombag, Hans S; Koya, Eisuke

    2017-03-22

    Cues that predict the availability of food rewards influence motivational states and elicit food-seeking behaviors. If a cue no longer predicts food availability, then animals may adapt accordingly by inhibiting food-seeking responses. Sparsely activated sets of neurons, coined "neuronal ensembles," have been shown to encode the strength of reward-cue associations. Although alterations in intrinsic excitability have been shown to underlie many learning and memory processes, little is known about these properties specifically on cue-activated neuronal ensembles. We examined the activation patterns of cue-activated orbitofrontal cortex (OFC) and nucleus accumbens (NAc) shell ensembles using wild-type and Fos-GFP mice, which express green fluorescent protein (GFP) in activated neurons, after appetitive conditioning with sucrose and extinction learning. We also investigated the neuronal excitability of recently activated, GFP+ neurons in these brain areas using whole-cell electrophysiology in brain slices. Exposure to a sucrose cue elicited activation of neurons in both the NAc shell and OFC. In the NAc shell, but not the OFC, these activated GFP+ neurons were more excitable than surrounding GFP- neurons. After extinction, the number of neurons activated in both areas was reduced and activated ensembles in neither area exhibited altered excitability. These data suggest that learning-induced alterations in the intrinsic excitability of neuronal ensembles is regulated dynamically across different brain areas. Furthermore, we show that changes in associative strength modulate the excitability profile of activated ensembles in the NAc shell. SIGNIFICANCE STATEMENT Sparsely distributed sets of neurons called "neuronal ensembles" encode learned associations about food and cues predictive of its availability. Widespread changes in neuronal excitability have been observed in limbic brain areas after associative learning, but little is known about the excitability changes that

  14. A J-modulated protonless NMR experiment characterizes the conformational ensemble of the intrinsically disordered protein WIP

    Energy Technology Data Exchange (ETDEWEB)

    Rozentur-Shkop, Eva; Goobes, Gil; Chill, Jordan H., E-mail: Jordan.Chill@biu.ac.il [Bar Ilan University, Department of Chemistry (Israel)

    2016-12-15

    Intrinsically disordered proteins (IDPs) are multi-conformational polypeptides that lack a single stable three-dimensional structure. It has become increasingly clear that the versatile IDPs play key roles in a multitude of biological processes, and, given their flexible nature, NMR is a leading method to investigate IDP behavior on the molecular level. Here we present an IDP-tailored J-modulated experiment designed to monitor changes in the conformational ensemble characteristic of IDPs by accurately measuring backbone one- and two-bond J({sup 15}N,{sup 13}Cα) couplings. This concept was realized using a unidirectional (H)NCO {sup 13}C-detected experiment suitable for poor spectral dispersion and optimized for maximum coverage of amino acid types. To demonstrate the utility of this approach we applied it to the disordered actin-binding N-terminal domain of WASp interacting protein (WIP), a ubiquitous key modulator of cytoskeletal changes in a range of biological systems. One- and two-bond J({sup 15}N,{sup 13}Cα) couplings were acquired for WIP residues 2–65 at various temperatures, and in denaturing and crowding environments. Under native conditions fitted J-couplings identified in the WIP conformational ensemble a propensity for extended conformation at residues 16–23 and 45–60, and a helical tendency at residues 28–42. These findings are consistent with a previous study of the based upon chemical shift and RDC data and confirm that the WIP{sup 2–65} conformational ensemble is biased towards the structure assumed by this fragment in its actin-bound form. The effects of environmental changes upon this ensemble were readily apparent in the J-coupling data, which reflected a significant decrease in structural propensity at higher temperatures, in the presence of 8 M urea, and under the influence of a bacterial cell lysate. The latter suggests that crowding can cause protein unfolding through protein–protein interactions that stabilize the unfolded

  15. Atom lasers, coherent states, and coherence II. Maximally robust ensembles of pure states

    International Nuclear Information System (INIS)

    Wiseman, H.M.; Vaccaro, John A.

    2002-01-01

    As discussed in the preceding paper [Wiseman and Vaccaro, preceding paper, Phys. Rev. A 65, 043605 (2002)], the stationary state of an optical or atom laser far above threshold is a mixture of coherent field states with random phase, or, equivalently, a Poissonian mixture of number states. We are interested in which, if either, of these descriptions of ρ ss as a stationary ensemble of pure states, is more natural. In the preceding paper we concentrated upon the question of whether descriptions such as these are physically realizable (PR). In this paper we investigate another relevant aspect of these ensembles, their robustness. A robust ensemble is one for which the pure states that comprise it survive relatively unchanged for a long time under the system evolution. We determine numerically the most robust ensembles as a function of the parameters in the laser model: the self-energy χ of the bosons in the laser mode, and the excess phase noise ν. We find that these most robust ensembles are PR ensembles, or similar to PR ensembles, for all values of these parameters. In the ideal laser limit (ν=χ=0), the most robust states are coherent states. As the phase noise or phase dispersion is increased through ν or the self-interaction of the bosons χ, respectively, the most robust states become more and more amplitude squeezed. We find scaling laws for these states, and give analytical derivations for them. As the phase diffusion or dispersion becomes so large that the laser output is no longer quantum coherent, the most robust states become so squeezed that they cease to have a well-defined coherent amplitude. That is, the quantum coherence of the laser output is manifest in the most robust PR ensemble being an ensemble of states with a well-defined coherent amplitude. This lends support to our approach of regarding robust PR ensembles as the most natural description of the state of the laser mode. It also has interesting implications for atom lasers in particular

  16. Internal Spin Control, Squeezing and Decoherence in Ensembles of Alkali Atomic Spins

    Science.gov (United States)

    Norris, Leigh Morgan

    Large atomic ensembles interacting with light are one of the most promising platforms for quantum information processing. In the past decade, novel applications for these systems have emerged in quantum communication, quantum computing, and metrology. Essential to all of these applications is the controllability of the atomic ensemble, which is facilitated by a strong coupling between the atoms and light. Non-classical spin squeezed states are a crucial step in attaining greater ensemble control. The degree of entanglement present in these states, furthermore, serves as a benchmark for the strength of the atom-light interaction. Outside the broader context of quantum information processing with atomic ensembles, spin squeezed states have applications in metrology, where their quantum correlations can be harnessed to improve the precision of magnetometers and atomic clocks. This dissertation focuses upon the production of spin squeezed states in large ensembles of cold trapped alkali atoms interacting with optical fields. While most treatments of spin squeezing consider only the case in which the ensemble is composed of two level systems or qubits, we utilize the entire ground manifold of an alkali atom with hyperfine spin f greater than or equal to 1/2, a qudit. Spin squeezing requires non-classical correlations between the constituent atomic spins, which are generated through the atoms' collective coupling to the light. Either through measurement or multiple interactions with the atoms, the light mediates an entangling interaction that produces quantum correlations. Because the spin squeezing treated in this dissertation ultimately originates from the coupling between the light and atoms, conventional approaches of improving this squeezing have focused on increasing the optical density of the ensemble. The greater number of internal degrees of freedom and the controllability of the spin-f ground hyperfine manifold enable novel methods of enhancing squeezing. In

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

    Science.gov (United States)

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

    2017-11-01

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

  18. River Flow Prediction Using the Nearest Neighbor Probabilistic Ensemble Method

    Directory of Open Access Journals (Sweden)

    H. Sanikhani

    2016-02-01

    . Different combinations of recorded data were used as the input pattern to streamflow forecasting. Results and Discussion: Application of the used approaches in ensemble form (in order to choice the optimized parameters improved the model accuracy and robustness in prediction. Different statistical criteria including correlation coefficient (R, root mean squared error (RMSE and Nash–Sutcliffe efficiency coefficient (E were used for evaluating the performance of models. The ranges of parameter values to be covered in the ensemble prediction have been identified by some preliminary tests on the calibration set. Since very small values of k have been found to produce unacceptable results due to the presence of noise, the minimum value is fixed at 100 and trial values are taken up to 10000 (k = 100, 200, 300,500, 1000, 2000, 5000, 10000. The values of mare chosen between 1 and 20 and delay time values γ are tested in the range [1,5]. With increasing the discharge values, the width of confidence band increased and the maximum confidence band is related to maximum river flows. In Dizaj station, for ensemble numbers in the range of 50-100, the variation of RMSE is linear. The variation of RMSE in Mashin station is linear for ensemble members in the range of 100-150. It seems the numbers of ensemble members equals to 100 is suitable for pattern construction. The performance of NNPE model was acceptable for two stations. The number of points excluded 95% confidence interval were equal to 108 and 96 for Dizaj and Mashin stations, respectively. The results showed that the performance of model was better in prediction of minimum and median discharge in comparing maximum values. Conclusion: The results confirmed the performance and reliability of applied methods. The results indicated the better performance and lower uncertainty of ensemble method based on nearest neighbor in comparison with probabilistic nonlinear ensemble method. Nash–Sutcliffe model efficiency coefficient (E for

  19. Rainfall downscaling of weekly ensemble forecasts using self-organising maps

    Directory of Open Access Journals (Sweden)

    Masamichi Ohba

    2016-03-01

    Full Text Available This study presents an application of self-organising maps (SOMs to downscaling medium-range ensemble forecasts and probabilistic prediction of local precipitation in Japan. SOM was applied to analyse and connect the relationship between atmospheric patterns over Japan and local high-resolution precipitation data. Multiple SOM was simultaneously employed on four variables derived from the JRA-55 reanalysis over the area of study (south-western Japan, and a two-dimensional lattice of weather patterns (WPs was obtained. Weekly ensemble forecasts can be downscaled to local precipitation using the obtained multiple SOM. The downscaled precipitation is derived by the five SOM lattices based on the WPs of the global model ensemble forecasts for a particular day in 2009–2011. Because this method effectively handles the stochastic uncertainties from the large number of ensemble members, a probabilistic local precipitation is easily and quickly obtained from the ensemble forecasts. This downscaling of ensemble forecasts provides results better than those from a 20-km global spectral model (i.e. capturing the relatively detailed precipitation distribution over the region. To capture the effect of the detailed pattern differences in each SOM node, a statistical model is additionally concreted for each SOM node. The predictability skill of the ensemble forecasts is significantly improved under the neural network-statistics hybrid-downscaling technique, which then brings a much better skill score than the traditional method. It is expected that the results of this study will provide better guidance to the user community and contribute to the future development of dam-management models.

  20. Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system

    Science.gov (United States)

    Sharma, Sanjib; Siddique, Ridwan; Reed, Seann; Ahnert, Peter; Mendoza, Pablo; Mejia, Alfonso

    2018-03-01

    The relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1-7) are investigated. For this purpose, a regional hydrologic ensemble prediction system (RHEPS) is developed and implemented. The RHEPS is comprised of the following components: (i) hydrometeorological observations (multisensor precipitation estimates, gridded surface temperature, and gauged streamflow); (ii) weather ensemble forecasts (precipitation and near-surface temperature) from the National Centers for Environmental Prediction 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2); (iii) NOAA's Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM); (iv) heteroscedastic censored logistic regression (HCLR) as the statistical preprocessor; (v) two statistical postprocessors, an autoregressive model with a single exogenous variable (ARX(1,1)) and quantile regression (QR); and (vi) a comprehensive verification strategy. To implement the RHEPS, 1 to 7 days weather forecasts from the GEFSRv2 are used to force HL-RDHM and generate raw ensemble streamflow forecasts. Forecasting experiments are conducted in four nested basins in the US Middle Atlantic region, ranging in size from 381 to 12 362 km2. Results show that the HCLR preprocessed ensemble precipitation forecasts have greater skill than the raw forecasts. These improvements are more noticeable in the warm season at the longer lead times (> 3 days). Both postprocessors, ARX(1,1) and QR, show gains in skill relative to the raw ensemble streamflow forecasts, particularly in the cool season, but QR outperforms ARX(1,1). The scenarios that implement preprocessing and postprocessing separately tend to perform similarly, although the postprocessing-alone scenario is often more effective. The scenario involving both preprocessing and postprocessing consistently outperforms the other scenarios. In some cases

  1. Wind and wave extremes over the world oceans from very large ensembles

    Science.gov (United States)

    Breivik, Øyvind; Aarnes, Ole Johan; Abdalla, Saleh; Bidlot, Jean-Raymond; Janssen, Peter A. E. M.

    2014-07-01

    Global return values of marine wind speed and significant wave height are estimated from very large aggregates of archived ensemble forecasts at +240 h lead time. Long lead time ensures that the forecasts represent independent draws from the model climate. Compared with ERA-Interim, a reanalysis, the ensemble yields higher return estimates for both wind speed and significant wave height. Confidence intervals are much tighter due to the large size of the data set. The period (9 years) is short enough to be considered stationary even with climate change. Furthermore, the ensemble is large enough for nonparametric 100 year return estimates to be made from order statistics. These direct return estimates compare well with extreme value estimates outside areas with tropical cyclones. Like any method employing modeled fields, it is sensitive to tail biases in the numerical model, but we find that the biases are moderate outside areas with tropical cyclones.

  2. Improving Climate Projections Using "Intelligent" Ensembles

    Science.gov (United States)

    Baker, Noel C.; Taylor, Patrick C.

    2015-01-01

    Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and

  3. Potentialities of ensemble strategies for flood forecasting over the Milano urban area

    Science.gov (United States)

    Ravazzani, Giovanni; Amengual, Arnau; Ceppi, Alessandro; Homar, Víctor; Romero, Romu; Lombardi, Gabriele; Mancini, Marco

    2016-08-01

    Analysis of ensemble forecasting strategies, which can provide a tangible backing for flood early warning procedures and mitigation measures over the Mediterranean region, is one of the fundamental motivations of the international HyMeX programme. Here, we examine two severe hydrometeorological episodes that affected the Milano urban area and for which the complex flood protection system of the city did not completely succeed. Indeed, flood damage have exponentially increased during the last 60 years, due to industrial and urban developments. Thus, the improvement of the Milano flood control system needs a synergism between structural and non-structural approaches. First, we examine how land-use changes due to urban development have altered the hydrological response to intense rainfalls. Second, we test a flood forecasting system which comprises the Flash-flood Event-based Spatially distributed rainfall-runoff Transformation, including Water Balance (FEST-WB) and the Weather Research and Forecasting (WRF) models. Accurate forecasts of deep moist convection and extreme precipitation are difficult to be predicted due to uncertainties arising from the numeric weather prediction (NWP) physical parameterizations and high sensitivity to misrepresentation of the atmospheric state; however, two hydrological ensemble prediction systems (HEPS) have been designed to explicitly cope with uncertainties in the initial and lateral boundary conditions (IC/LBCs) and physical parameterizations of the NWP model. No substantial differences in skill have been found between both ensemble strategies when considering an enhanced diversity of IC/LBCs for the perturbed initial conditions ensemble. Furthermore, no additional benefits have been found by considering more frequent LBCs in a mixed physics ensemble, as ensemble spread seems to be reduced. These findings could help to design the most appropriate ensemble strategies before these hydrometeorological extremes, given the computational

  4. Can decadal climate predictions be improved by ocean ensemble dispersion filtering?

    Science.gov (United States)

    Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

    2017-12-01

    Decadal predictions by Earth system models aim to capture the state and phase of the climate several years inadvance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-termweather forecasts represent an initial value problem and long-term climate projections represent a boundarycondition problem, the decadal climate prediction falls in-between these two time scales. The ocean memorydue to its heat capacity holds big potential skill on the decadal scale. In recent years, more precise initializationtechniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions.Ensembles are another important aspect. Applying slightly perturbed predictions results in an ensemble. Insteadof using and evaluating one prediction, but the whole ensemble or its ensemble average, improves a predictionsystem. However, climate models in general start losing the initialized signal and its predictive skill from oneforecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improvedby a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. Wefound that this procedure, called ensemble dispersion filter, results in more accurate results than the standarddecadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions showan increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with largerensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from oceanensemble dispersion filtering toward the ensemble mean. This study is part of MiKlip (fona-miklip.de) - a major project on decadal climate prediction in Germany.We focus on the Max-Planck-Institute Earth System Model using the low-resolution version (MPI-ESM-LR) andMiKlip's basic initialization strategy as in 2017 published decadal climate forecast: http

  5. Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

    DEFF Research Database (Denmark)

    Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh

    2015-01-01

    Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

  6. Quasi-static ensemble variational data assimilation: a theoretical and numerical study with the iterative ensemble Kalman smoother

    Science.gov (United States)

    Fillion, Anthony; Bocquet, Marc; Gratton, Serge

    2018-04-01

    The analysis in nonlinear variational data assimilation is the solution of a non-quadratic minimization. Thus, the analysis efficiency relies on its ability to locate a global minimum of the cost function. If this minimization uses a Gauss-Newton (GN) method, it is critical for the starting point to be in the attraction basin of a global minimum. Otherwise the method may converge to a local extremum, which degrades the analysis. With chaotic models, the number of local extrema often increases with the temporal extent of the data assimilation window, making the former condition harder to satisfy. This is unfortunate because the assimilation performance also increases with this temporal extent. However, a quasi-static (QS) minimization may overcome these local extrema. It accomplishes this by gradually injecting the observations in the cost function. This method was introduced by Pires et al. (1996) in a 4D-Var context. We generalize this approach to four-dimensional strong-constraint nonlinear ensemble variational (EnVar) methods, which are based on both a nonlinear variational analysis and the propagation of dynamical error statistics via an ensemble. This forces one to consider the cost function minimizations in the broader context of cycled data assimilation algorithms. We adapt this QS approach to the iterative ensemble Kalman smoother (IEnKS), an exemplar of nonlinear deterministic four-dimensional EnVar methods. Using low-order models, we quantify the positive impact of the QS approach on the IEnKS, especially for long data assimilation windows. We also examine the computational cost of QS implementations and suggest cheaper algorithms.

  7. Statistical ensembles for money and debt

    Science.gov (United States)

    Viaggiu, Stefano; Lionetto, Andrea; Bargigli, Leonardo; Longo, Michele

    2012-10-01

    We build a statistical ensemble representation of two economic models describing respectively, in simplified terms, a payment system and a credit market. To this purpose we adopt the Boltzmann-Gibbs distribution where the role of the Hamiltonian is taken by the total money supply (i.e. including money created from debt) of a set of interacting economic agents. As a result, we can read the main thermodynamic quantities in terms of monetary ones. In particular, we define for the credit market model a work term which is related to the impact of monetary policy on credit creation. Furthermore, with our formalism we recover and extend some results concerning the temperature of an economic system, previously presented in the literature by considering only the monetary base as a conserved quantity. Finally, we study the statistical ensemble for the Pareto distribution.

  8. ABCD of Beta Ensembles and Topological Strings

    CERN Document Server

    Krefl, Daniel

    2012-01-01

    We study beta-ensembles with Bn, Cn, and Dn eigenvalue measure and their relation with refined topological strings. Our results generalize the familiar connections between local topological strings and matrix models leading to An measure, and illustrate that all those classical eigenvalue ensembles, and their topological string counterparts, are related one to another via various deformations and specializations, quantum shifts and discrete quotients. We review the solution of the Gaussian models via Macdonald identities, and interpret them as conifold theories. The interpolation between the various models is plainly apparent in this case. For general polynomial potential, we calculate the partition function in the multi-cut phase in a perturbative fashion, beyond tree-level in the large-N limit. The relation to refined topological string orientifolds on the corresponding local geometry is discussed along the way.

  9. Quark ensembles with the infinite correlation length

    Science.gov (United States)

    Zinov'ev, G. M.; Molodtsov, S. V.

    2015-01-01

    A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble.

  10. Quark ensembles with the infinite correlation length

    International Nuclear Information System (INIS)

    Zinov’ev, G. M.; Molodtsov, S. V.

    2015-01-01

    A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble

  11. Quark ensembles with the infinite correlation length

    Energy Technology Data Exchange (ETDEWEB)

    Zinov’ev, G. M. [National Academy of Sciences of Ukraine, Bogoliubov Institute for Theoretical Physics (Ukraine); Molodtsov, S. V., E-mail: molodtsov@itep.ru [Joint Institute for Nuclear Research (Russian Federation)

    2015-01-15

    A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble.

  12. Various multistage ensembles for prediction of heating energy consumption

    Directory of Open Access Journals (Sweden)

    Radisa Jovanovic

    2015-04-01

    Full Text Available Feedforward neural network models are created for prediction of daily heating energy consumption of a NTNU university campus Gloshaugen using actual measured data for training and testing. Improvement of prediction accuracy is proposed by using neural network ensemble. Previously trained feed-forward neural networks are first separated into clusters, using k-means algorithm, and then the best network of each cluster is chosen as member of an ensemble. Two conventional averaging methods for obtaining ensemble output are applied; simple and weighted. In order to achieve better prediction results, multistage ensemble is investigated. As second level, adaptive neuro-fuzzy inference system with various clustering and membership functions are used to aggregate the selected ensemble members. Feedforward neural network in second stage is also analyzed. It is shown that using ensemble of neural networks can predict heating energy consumption with better accuracy than the best trained single neural network, while the best results are achieved with multistage ensemble.

  13. Modeling Coordination Problems in a Music Ensemble

    DEFF Research Database (Denmark)

    Frimodt-Møller, Søren R.

    2008-01-01

    This paper considers in general terms, how musicians are able to coordinate through rational choices in a situation of (temporary) doubt in an ensemble performance. A fictitious example involving a 5-bar development in an unknown piece of music is analyzed in terms of epistemic logic, more...... to coordinate. Such coordination can be described in terms of Michael Bacharach's theory of variable frames as an aid to solve game theoretic coordination problems....

  14. Microcanonical ensemble formulation of lattice gauge theory

    International Nuclear Information System (INIS)

    Callaway, D.J.E.; Rahman, A.

    1982-01-01

    A new formulation of lattice gauge theory without explicit path integrals or sums is obtained by using the microcanonical ensemble of statistical mechanics. Expectation values in the new formalism are calculated by solving a large set of coupled, nonlinear, ordinary differential equations. The average plaquette for compact electrodynamics calculated in this fashion agrees with standard Monte Carlo results. Possible advantages of the microcanonical method in applications to fermionic systems are discussed

  15. Ensemble forecasts of road surface temperatures

    Czech Academy of Sciences Publication Activity Database

    Sokol, Zbyněk; Bližňák, Vojtěch; Sedlák, Pavel; Zacharov, Petr, jr.; Pešice, Petr; Škuthan, M.

    2017-01-01

    Roč. 187, 1 May (2017), s. 33-41 ISSN 0169-8095 R&D Projects: GA ČR GA13-34856S; GA TA ČR(CZ) TA01031509 Institutional support: RVO:68378289 Keywords : ensemble prediction * road surface temperature * road weather forecast Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 3.778, year: 2016 http://www.sciencedirect.com/science/article/pii/S0169809516307311

  16. Rainfall estimation with TFR model using Ensemble Kalman filter

    Science.gov (United States)

    Asyiqotur Rohmah, Nabila; Apriliani, Erna

    2018-03-01

    Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

  17. Microcanonical ensemble extensive thermodynamics of Tsallis statistics

    International Nuclear Information System (INIS)

    Parvan, A.S.

    2005-01-01

    The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics.The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ = 1/q - 1 in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z bar = 1/(q - 1)N = const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

  18. Ensemble Clustering using Semidefinite Programming with Applications.

    Science.gov (United States)

    Singh, Vikas; Mukherjee, Lopamudra; Peng, Jiming; Xu, Jinhui

    2010-05-01

    In this paper, we study the ensemble clustering problem, where the input is in the form of multiple clustering solutions. The goal of ensemble clustering algorithms is to aggregate the solutions into one solution that maximizes the agreement in the input ensemble. We obtain several new results for this problem. Specifically, we show that the notion of agreement under such circumstances can be better captured using a 2D string encoding rather than a voting strategy, which is common among existing approaches. Our optimization proceeds by first constructing a non-linear objective function which is then transformed into a 0-1 Semidefinite program (SDP) using novel convexification techniques. This model can be subsequently relaxed to a polynomial time solvable SDP. In addition to the theoretical contributions, our experimental results on standard machine learning and synthetic datasets show that this approach leads to improvements not only in terms of the proposed agreement measure but also the existing agreement measures based on voting strategies. In addition, we identify several new application scenarios for this problem. These include combining multiple image segmentations and generating tissue maps from multiple-channel Diffusion Tensor brain images to identify the underlying structure of the brain.

  19. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-12-03

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

  20. Decimated Input Ensembles for Improved Generalization

    Science.gov (United States)

    Tumer, Kagan; Oza, Nikunj C.; Norvig, Peter (Technical Monitor)

    1999-01-01

    Recently, many researchers have demonstrated that using classifier ensembles (e.g., averaging the outputs of multiple classifiers before reaching a classification decision) leads to improved performance for many difficult generalization problems. However, in many domains there are serious impediments to such "turnkey" classification accuracy improvements. Most notable among these is the deleterious effect of highly correlated classifiers on the ensemble performance. One particular solution to this problem is generating "new" training sets by sampling the original one. However, with finite number of patterns, this causes a reduction in the training patterns each classifier sees, often resulting in considerably worsened generalization performance (particularly for high dimensional data domains) for each individual classifier. Generally, this drop in the accuracy of the individual classifier performance more than offsets any potential gains due to combining, unless diversity among classifiers is actively promoted. In this work, we introduce a method that: (1) reduces the correlation among the classifiers; (2) reduces the dimensionality of the data, thus lessening the impact of the 'curse of dimensionality'; and (3) improves the classification performance of the ensemble.

  1. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-05-08

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

  2. Multivariate localization methods for ensemble Kalman filtering

    Science.gov (United States)

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

    2015-12-01

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

  3. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

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

    2015-01-01

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

  4. Microcanonical ensemble extensive thermodynamics of Tsallis statistics

    International Nuclear Information System (INIS)

    Parvan, A.S.

    2006-01-01

    The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics. The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ=1/(q-1) in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z-bar =1/(q-1)N=const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

  5. Establishment of a New National Reference Ensemble of Water Triple Point Cells

    Science.gov (United States)

    Senn, Remo

    2017-10-01

    The results of the Bilateral Comparison EURAMET.T-K3.5 (w/VSL, The Netherlands) with the goal to link Switzerland's ITS-90 realization (Ar to Al) to the latest key comparisons gave strong indications for a discrepancy in the realization of the triple point of water. Due to the age of the cells of about twenty years, it was decided to replace the complete reference ensemble with new "state-of-the-art" cells. Three new water triple point cells from three different suppliers were purchased, as well as a new maintenance bath for an additional improvement of the realization. In several loops measurements were taken, each cell of both ensembles intercompared, and the deviations and characteristics determined. The measurements show a significant lower average value of the old ensemble of 0.59 ± 0.25 mK (k=2) in comparison with the new one. Likewise, the behavior of the old cells is very unstable with a drift downward during the realization of the triple point. Based on these results the impact of the new ensemble on the ITS-90 realization from Ar to Al was calculated and set in the context to performed calibrations and their related uncertainties in the past. This paper presents the instrumentation, cells, measurement procedure, results, uncertainties and impact of the new national reference ensemble of water triple point cells on the current ITS-90 realization in Switzerland.

  6. A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment

    Science.gov (United States)

    Wang, S.; Huang, G. H.; Baetz, B. W.; Huang, W.

    2015-11-01

    This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS) for an efficient and robust uncertainty assessment of model parameters and predictions, in which possibilistic reasoning is infused into probabilistic parameter inference with simultaneous consideration of randomness and fuzziness. The PCEHPS is developed through a two-stage factorial polynomial chaos expansion (PCE) framework, which consists of an ensemble of PCEs to approximate the behavior of the hydrologic model, significantly speeding up the exhaustive sampling of the parameter space. Multiple hypothesis testing is then conducted to construct an ensemble of reduced-dimensionality PCEs with only the most influential terms, which is meaningful for achieving uncertainty reduction and further acceleration of parameter inference. The PCEHPS is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability. A detailed comparison between the HYMOD hydrologic model, the ensemble of PCEs, and the ensemble of reduced PCEs is performed in terms of accuracy and efficiency. Results reveal temporal and spatial variations in parameter sensitivities due to the dynamic behavior of hydrologic systems, and the effects (magnitude and direction) of parametric interactions depending on different hydrological metrics. The case study demonstrates that the PCEHPS is capable not only of capturing both expert knowledge and probabilistic information in the calibration process, but also of implementing an acceleration of more than 10 times faster than the hydrologic model without compromising the predictive accuracy.

  7. Model dependence and its effect on ensemble projections in CMIP5

    Science.gov (United States)

    Abramowitz, G.; Bishop, C.

    2013-12-01

    Conceptually, the notion of model dependence within climate model ensembles is relatively simple - modelling groups share a literature base, parametrisations, data sets and even model code - the potential for dependence in sampling different climate futures is clear. How though can this conceptual problem inform a practical solution that demonstrably improves the ensemble mean and ensemble variance as an estimate of system uncertainty? While some research has already focused on error correlation or error covariance as a candidate to improve ensemble mean estimates, a complete definition of independence must at least implicitly subscribe to an ensemble interpretation paradigm, such as the 'truth-plus-error', 'indistinguishable', or more recently 'replicate Earth' paradigm. Using a definition of model dependence based on error covariance within the replicate Earth paradigm, this presentation will show that accounting for dependence in surface air temperature gives cooler projections in CMIP5 - by as much as 20% globally in some RCPs - although results differ significantly for each RCP, especially regionally. The fact that the change afforded by accounting for dependence across different RCPs is different is not an inconsistent result. Different numbers of submissions to each RCP by different modelling groups mean that differences in projections from different RCPs are not entirely about RCP forcing conditions - they also reflect different sampling strategies.

  8. The role of model dynamics in ensemble Kalman filter performance for chaotic systems

    Science.gov (United States)

    Ng, G.-H.C.; McLaughlin, D.; Entekhabi, D.; Ahanin, A.

    2011-01-01

    The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or 'diverging', when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter's update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as non-linearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics. ?? 2011 The Authors Tellus A ?? 2011 John Wiley & Sons A/S.

  9. Performance of a multi-RCM ensemble for South Eastern South America

    Energy Technology Data Exchange (ETDEWEB)

    Carril, A.F.; Menendez, C.G.; Salio, P. [Ciudad Universitaria, Ciudad Autonoma de Buenos Aires, Centro de Investigaciones del Mar y la Atmosfera (CIMA), CONICET-UBA, Buenos Aires (Argentina); Universidad de Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos (DCAO), FCEN, Buenos Aires (Argentina); UMI IFAECI/CNRS, Buenos Aires (Argentina); Remedio, A.R.C.; Jacob, D.; Pfeifer, S. [Max Planck Institute for Meteorology (MPI-M), Hamburg (Germany); Robledo, F.; Tencer, B. [Universidad de Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos (DCAO), FCEN, Buenos Aires (Argentina); Soerensson, A.; Zaninelli, P. [Ciudad Universitaria, Ciudad Autonoma de Buenos Aires, Centro de Investigaciones del Mar y la Atmosfera (CIMA), CONICET-UBA, Buenos Aires (Argentina); UMI IFAECI/CNRS, Buenos Aires (Argentina); Boulanger, J.P. [LOCEAN, UMR CNRS/IRD/UPMC, Paris (France); Castro, M. de; Sanchez, E. [Universidad de Castilla-La Mancha (UCLM), Toledo (Spain); Le Treut, H.; Li, L.Z.X. [Sciences de l' Environnement en Ile de France, Laboratoire de Meteorologie Dynamique (LMD), Institut-Pierre-Simon-Laplace et Ecole Doctorale, Paris (France); Penalba, O.; Rusticucci, M. [Universidad de Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos (DCAO), FCEN, Buenos Aires (Argentina); UMI IFAECI/CNRS, Buenos Aires (Argentina); Samuelsson, P. [Swedish Meteorological and Hydrological Institute (SMHI), Norrkoeping (Sweden)

    2012-12-15

    The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991-2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons. (orig.)

  10. Simultaneous calibration of ensemble river flow predictions over an entire range of lead times

    Science.gov (United States)

    Hemri, S.; Fundel, F.; Zappa, M.

    2013-10-01

    Probabilistic estimates of future water levels and river discharge are usually simulated with hydrologic models using ensemble weather forecasts as main inputs. As hydrologic models are imperfect and the meteorological ensembles tend to be biased and underdispersed, the ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, in order to achieve both reliable and sharp predictions statistical postprocessing is required. In this work Bayesian model averaging (BMA) is applied to statistically postprocess ensemble runoff raw forecasts for a catchment in Switzerland, at lead times ranging from 1 to 240 h. The raw forecasts have been obtained using deterministic and ensemble forcing meteorological models with different forecast lead time ranges. First, BMA is applied based on mixtures of univariate normal distributions, subject to the assumption of independence between distinct lead times. Then, the independence assumption is relaxed in order to estimate multivariate runoff forecasts over the entire range of lead times simultaneously, based on a BMA version that uses multivariate normal distributions. Since river runoff is a highly skewed variable, Box-Cox transformations are applied in order to achieve approximate normality. Both univariate and multivariate BMA approaches are able to generate well calibrated probabilistic forecasts that are considerably sharper than climatological forecasts. Additionally, multivariate BMA provides a promising approach for incorporating temporal dependencies into the postprocessed forecasts. Its major advantage against univariate BMA is an increase in reliability when the forecast system is changing due to model availability.

  11. A model ensemble for projecting multi‐decadal coastal cliff retreat during the 21st century

    Science.gov (United States)

    Limber, Patrick; Barnard, Patrick; Vitousek, Sean; Erikson, Li

    2018-01-01

    Sea cliff retreat rates are expected to accelerate with rising sea levels during the 21st century. Here we develop an approach for a multi‐model ensemble that efficiently projects time‐averaged sea cliff retreat over multi‐decadal time scales and large (>50 km) spatial scales. The ensemble consists of five simple 1‐D models adapted from the literature that relate sea cliff retreat to wave impacts, sea level rise (SLR), historical cliff behavior, and cross‐shore profile geometry. Ensemble predictions are based on Monte Carlo simulations of each individual model, which account for the uncertainty of model parameters. The consensus of the individual models also weights uncertainty, such that uncertainty is greater when predictions from different models do not agree. A calibrated, but unvalidated, ensemble was applied to the 475 km‐long coastline of Southern California (USA), with 4 SLR scenarios of 0.5, 0.93, 1.5, and 2 m by 2100. Results suggest that future retreat rates could increase relative to mean historical rates by more than two‐fold for the higher SLR scenarios, causing an average total land loss of 19 – 41 m by 2100. However, model uncertainty ranges from +/‐ 5 – 15 m, reflecting the inherent difficulties of projecting cliff retreat over multiple decades. To enhance ensemble performance, future work could include weighting each model by its skill in matching observations in different morphological settings

  12. EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Shu, Qingya; Guo, Hanqi; Che, Limei; Yuan, Xiaoru; Liu, Junfeng; Liang, Jie

    2016-04-19

    We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based on ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.

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

    Science.gov (United States)

    Mel, Riccardo; Lionello, Piero

    2014-12-01

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

  14. An Ensemble Approach to Understanding the ENSO Response to Climate Change

    Science.gov (United States)

    Stevenson, S.; Capotondi, A.; Fasullo, J.; Otto-Bliesner, B. L.

    2017-12-01

    The dynamics of the El Nino/Southern Oscillation (ENSO) are known to be sensitive to changes in background climate conditions, as well as atmosphere/ocean feedbacks. However, the degree to which shifts in ENSO characteristics can be robustly attributed to external climate forcings remains unknown. Efforts to assess these changes in a multi-model framework are subject to uncertainties due to both differing model physics and internal ENSO variability. New community ensembles created at the National Center for Atmospheric Research and the NOAA Geophysical Fluid Dynamics Laboratory are ideally suited to addressing this problem, providing many realizations of the climate of the 850-2100 period with a combination of both natural and anthropogenic climate forcing factors. Here we analyze the impacts of external forcing on El Nino and La Nina evolution using four sets of simulations: the CESM Last Millennium Ensemble (CESM-LME), which covers the 850-2005 period and provides long-term context for forced responses; the Large Ensemble (CESM-LE), which includes 20th century and 21st century (RCP8.5) projections; the Medium Ensemble (CESM-ME), which is composed of 21st century RCP4.5 projections; and a large ensemble with the GFDL ESM2M, which includes 20th century and RCP8.5 projections. In the CESM, ENSO variance increases slightly over the 20th century in all ensembles, with the effects becoming much larger during the 21st. The slower increase in variance over the 20th century is shown to arise from compensating influences from greenhouse gas (GHG) and anthropogenic aerosol emissions, which give way to GHG-dominated effects by 2100. However, the 21st century variance increase is not robust: CESM and the ESM2M differ drastically in their ENSO projections. The mechanisms for these inter-model differences are discussed, as are the implications for the design of future multi-model ENSO projection experiments.

  15. HRensembleHR. High resolution ensemble for Horns Rev. Final project report. Executive summary; Offshore wind power

    Energy Technology Data Exchange (ETDEWEB)

    2010-03-15

    The development of offshore wind power results in more energy production per area unit and new requirements to the generation forecasts. Measurements from Horns Rev and ensemble forecasts were used to upgrade forecasting tools for the relevant periods and time scales. The most significant development is a new algorithm for short-term forecasts that combines any relevant online measurements by means of ensemble forecasts. (ln)

  16. Performance analysis of a Principal Component Analysis ensemble classifier for Emotiv headset P300 spellers.

    Science.gov (United States)

    Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

    2014-01-01

    The current trend to use Brain-Computer Interfaces (BCIs) with mobile devices mandates the development of efficient EEG data processing methods. In this paper, we demonstrate the performance of a Principal Component Analysis (PCA) ensemble classifier for P300-based spellers. We recorded EEG data from multiple subjects using the Emotiv neuroheadset in the context of a classical oddball P300 speller paradigm. We compare the performance of the proposed ensemble classifier to the performance of traditional feature extraction and classifier methods. Our results demonstrate the capability of the PCA ensemble classifier to classify P300 data recorded using the Emotiv neuroheadset with an average accuracy of 86.29% on cross-validation data. In addition, offline testing of the recorded data reveals an average classification accuracy of 73.3% that is significantly higher than that achieved using traditional methods. Finally, we demonstrate the effect of the parameters of the P300 speller paradigm on the performance of the method.

  17. Wang-Landau Reaction Ensemble Method: Simulation of Weak Polyelectrolytes and General Acid-Base Reactions.

    Science.gov (United States)

    Landsgesell, Jonas; Holm, Christian; Smiatek, Jens

    2017-02-14

    We present a novel method for the study of weak polyelectrolytes and general acid-base reactions in molecular dynamics and Monte Carlo simulations. The approach combines the advantages of the reaction ensemble and the Wang-Landau sampling method. Deprotonation and protonation reactions are simulated explicitly with the help of the reaction ensemble method, while the accurate sampling of the corresponding phase space is achieved by the Wang-Landau approach. The combination of both techniques provides a sufficient statistical accuracy such that meaningful estimates for the density of states and the partition sum can be obtained. With regard to these estimates, several thermodynamic observables like the heat capacity or reaction free energies can be calculated. We demonstrate that the computation times for the calculation of titration curves with a high statistical accuracy can be significantly decreased when compared to the original reaction ensemble method. The applicability of our approach is validated by the study of weak polyelectrolytes and their thermodynamic properties.

  18. Multi-complexity ensemble measures for gait time series analysis: application to diagnostics, monitoring and biometrics.

    Science.gov (United States)

    Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina

    2015-01-01

    Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.

  19. Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degree global warming

    Science.gov (United States)

    Thober, S.; Kumar, R.; Wanders, N.; Marx, A.; Pan, M.; Rakovec, O.; Samaniego, L. E.; Sheffield, J.; Wood, E. F.; Zink, M.

    2017-12-01

    Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 General Circulation Models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over entire Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow water equivalent decreases flood events in this region. The contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share of the overall uncertainty and exceed GCM uncertainty in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but has to account for significantly higher changes under 3 K global warming.

  20. Analyzing the impact of changing size and composition of a crop model ensemble

    Science.gov (United States)

    Rodríguez, Alfredo

    2017-04-01

    The use of an ensemble of crop growth simulation models is a practice recently adopted in order to quantify aspects of uncertainties in model simulations. Yet, while the climate modelling community has extensively investigated the properties of model ensembles and their implications, this has hardly been investigated for crop model ensembles (Wallach et al., 2016). In their ensemble of 27 wheat models, Martre et al. (2015) found that the accuracy of the multi-model ensemble-average only increases up to an ensemble size of ca. 10, but does not improve when including more models in the analysis. However, even when this number of members is reached, questions about the impact of the addition or removal of a member to/from the ensemble arise. When selecting ensemble members, identifying members with poor performance or giving implausible results can make a large difference on the outcome. The objective of this study is to set up a methodology that defines indicators to show the effects of changing the ensemble composition and size on simulation results, when a selection procedure of ensemble members is applied. Ensemble mean or median, and variance are measures used to depict ensemble results among other indicators. We are utilizing simulations from an ensemble of wheat models that have been used to construct impact response surfaces (Pirttioja et al., 2015) (IRSs). These show the response of an impact variable (e.g., crop yield) to systematic changes in two explanatory variables (e.g., precipitation and temperature). Using these, we compare different sub-ensembles in terms of the mean, median and spread, and also by comparing IRSs. The methodology developed here allows comparing an ensemble before and after applying any procedure that changes the ensemble composition and size by measuring the impact of this decision on the ensemble central tendency measures. The methodology could also be further developed to compare the effect of changing ensemble composition and size

  1. Stabilizing canonical-ensemble calculations in the auxiliary-field Monte Carlo method

    Science.gov (United States)

    Gilbreth, C. N.; Alhassid, Y.

    2015-03-01

    Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the auxiliary-field Monte Carlo (AFMC) method, low-temperature or large-model-space calculations require numerically stabilized matrix multiplication. When adapting methods used in the grand-canonical ensemble to the canonical ensemble of fixed particle number, the numerical stabilization increases the number of required floating-point operations for computing observables by a factor of the size of the single-particle model space, and thus can greatly limit the systems that can be studied. We describe an improved method for stabilizing canonical-ensemble calculations in AFMC that exhibits better scaling, and present numerical tests that demonstrate the accuracy and improved performance of the method.

  2. Using simulation to interpret experimental data in terms of protein conformational ensembles.

    Science.gov (United States)

    Allison, Jane R

    2017-04-01

    In their biological environment, proteins are dynamic molecules, necessitating an ensemble structural description. Molecular dynamics simulations and solution-state experiments provide complimentary information in the form of atomically detailed coordinates and averaged or distributions of structural properties or related quantities. Recently, increases in the temporal and spatial scale of conformational sampling and comparison of the more diverse conformational ensembles thus generated have revealed the importance of sampling rare events. Excitingly, new methods based on maximum entropy and Bayesian inference are promising to provide a statistically sound mechanism for combining experimental data with molecular dynamics simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Reducing storage of global wind ensembles with stochastic generators

    KAUST Repository

    Jeong, Jaehong

    2018-03-09

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth’s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  4. Reducing storage of global wind ensembles with stochastic generators

    KAUST Repository

    Jeong, Jaehong; Castruccio, Stefano; Crippa, Paola; Genton, Marc G.

    2018-01-01

    Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth’s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.

  5. Preserving the Boltzmann ensemble in replica-exchange molecular dynamics.

    Science.gov (United States)

    Cooke, Ben; Schmidler, Scott C

    2008-10-28

    We consider the convergence behavior of replica-exchange molecular dynamics (REMD) [Sugita and Okamoto, Chem. Phys. Lett. 314, 141 (1999)] based on properties of the numerical integrators in the underlying isothermal molecular dynamics (MD) simulations. We show that a variety of deterministic algorithms favored by molecular dynamics practitioners for constant-temperature simulation of biomolecules fail either to be measure invariant or irreducible, and are therefore not ergodic. We then show that REMD using these algorithms also fails to be ergodic. As a result, the entire configuration space may not be explored even in an infinitely long simulation, and the simulation may not converge to the desired equilibrium Boltzmann ensemble. Moreover, our analysis shows that for initial configurations with unfavorable energy, it may be impossible for the system to reach a region surrounding the minimum energy configuration. We demonstrate these failures of REMD algorithms for three small systems: a Gaussian distribution (simple harmonic oscillator dynamics), a bimodal mixture of Gaussians distribution, and the alanine dipeptide. Examination of the resulting phase plots and equilibrium configuration densities indicates significant errors in the ensemble generated by REMD simulation. We describe a simple modification to address these failures based on a stochastic hybrid Monte Carlo correction, and prove that this is ergodic.

  6. Monthly ENSO Forecast Skill and Lagged Ensemble Size

    Science.gov (United States)

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

    2018-04-01

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

  7. Class-specific Error Bounds for Ensemble Classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Prenger, R; Lemmond, T; Varshney, K; Chen, B; Hanley, W

    2009-10-06

    The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missed detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.

  8. Characterization of the critical submanifolds in quantum ensemble control landscapes

    International Nuclear Information System (INIS)

    Wu Rebing; Rabitz, Herschel; Hsieh, Michael

    2008-01-01

    The quantum control landscape is defined as the functional that maps the control variables to the expectation values of an observable over the ensemble of quantum systems. Analyzing the topology of such landscapes is important for understanding the origins of the increasing number of laboratory successes in the optimal control of quantum processes. This paper proposes a simple scheme to compute the characteristics of the critical topology of the quantum ensemble control landscapes showing that the set of disjoint critical submanifolds one-to-one corresponds to a finite number of contingency tables that solely depend on the degeneracy structure of the eigenvalues of the initial system density matrix and the observable whose expectation value is to be maximized. The landscape characteristics can be calculated as functions of the table entries, including the dimensions and the numbers of positive and negative eigenvalues of the Hessian quadratic form of each of the connected components of the critical submanifolds. Typical examples are given to illustrate the effectiveness of this method

  9. IASI Radiance Data Assimilation in Local Ensemble Transform Kalman Filter

    Science.gov (United States)

    Cho, K.; Hyoung-Wook, C.; Jo, Y.

    2016-12-01

    Korea institute of Atmospheric Prediction Systems (KIAPS) is developing NWP model with data assimilation systems. Local Ensemble Transform Kalman Filter (LETKF) system, one of the data assimilation systems, has been developed for KIAPS Integrated Model (KIM) based on cubed-sphere grid and has successfully assimilated real data. LETKF data assimilation system has been extended to 4D- LETKF which considers time-evolving error covariance within assimilation window and IASI radiance data assimilation using KPOP (KIAPS package for observation processing) with RTTOV (Radiative Transfer for TOVS). The LETKF system is implementing semi operational prediction including conventional (sonde, aircraft) observation and AMSU-A (Advanced Microwave Sounding Unit-A) radiance data from April. Recently, the semi operational prediction system updated radiance observations including GPS-RO, AMV, IASI (Infrared Atmospheric Sounding Interferometer) data at July. A set of simulation of KIM with ne30np4 and 50 vertical levels (of top 0.3hPa) were carried out for short range forecast (10days) within semi operation prediction LETKF system with ensemble forecast 50 members. In order to only IASI impact, our experiments used only conventional and IAIS radiance data to same semi operational prediction set. We carried out sensitivity test for IAIS thinning method (3D and 4D). IASI observation number was increased by temporal (4D) thinning and the improvement of IASI radiance data impact on the forecast skill of model will expect.

  10. Generation of scenarios from calibrated ensemble forecasts with a dual ensemble copula coupling approach

    DEFF Research Database (Denmark)

    Ben Bouallègue, Zied; Heppelmann, Tobias; Theis, Susanne E.

    2016-01-01

    the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error. The new...... approach, called d-ECC, is applied to wind forecasts from the high resolution ensemble system COSMO-DE-EPS run operationally at the German weather service. Scenarios generated by ECC and d-ECC are compared and assessed in the form of time series by means of multivariate verification tools and in a product...

  11. Combining large model ensembles with extreme value statistics to improve attribution statements of rare events

    Directory of Open Access Journals (Sweden)

    Sebastian Sippel

    2015-09-01

    In conclusion, our study shows that EVT and empirical estimates based on numerical simulations can indeed be used to productively inform each other, for instance to derive appropriate EVT parameters for short observational time series. Further, the combination of ensemble simulations with EVT allows us to significantly reduce the number of simulations needed for statements about the tails.

  12. Structure D'Ensemble, Multiple Classification, Multiple Seriation and Amount of Irrelevant Information

    Science.gov (United States)

    Hamel, B. Remmo; Van Der Veer, M. A. A.

    1972-01-01

    A significant positive correlation between multiple classification was found, in testing 65 children aged 6 to 8 years, at the stage of concrete operations. This is interpreted as support for the existence of a structure d'ensemble of operational schemes in the period of concrete operations. (Authors)

  13. Constraining the ensemble Kalman filter for improved streamflow forecasting

    Science.gov (United States)

    Maxwell, Deborah H.; Jackson, Bethanna M.; McGregor, James

    2018-05-01

    Data assimilation techniques such as the Ensemble Kalman Filter (EnKF) are often applied to hydrological models with minimal state volume/capacity constraints enforced during ensemble generation. Flux constraints are rarely, if ever, applied. Consequently, model states can be adjusted beyond physically reasonable limits, compromising the integrity of model output. In this paper, we investigate the effect of constraining the EnKF on forecast performance. A "free run" in which no assimilation is applied is compared to a completely unconstrained EnKF implementation, a 'typical' hydrological implementation (in which mass constraints are enforced to ensure non-negativity and capacity thresholds of model states are not exceeded), and then to a more tightly constrained implementation where flux as well as mass constraints are imposed to force the rate of water movement to/from ensemble states to be within physically consistent boundaries. A three year period (2008-2010) was selected from the available data record (1976-2010). This was specifically chosen as it had no significant data gaps and represented well the range of flows observed in the longer dataset. Over this period, the standard implementation of the EnKF (no constraints) contained eight hydrological events where (multiple) physically inconsistent state adjustments were made. All were selected for analysis. Mass constraints alone did little to improve forecast performance; in fact, several were significantly degraded compared to the free run. In contrast, the combined use of mass and flux constraints significantly improved forecast performance in six events relative to all other implementations, while the remaining two events showed no significant difference in performance. Placing flux as well as mass constraints on the data assimilation framework encourages physically consistent state estimation and results in more accurate and reliable forward predictions of streamflow for robust decision-making. We also

  14. Dynamics and Synchronization of Noise Perturbed Ensembles of Periodically Activated neuron Cells

    DEFF Research Database (Denmark)

    Belykh, V. N.; Pankratova, Evgeniya; Mosekilde, Erik

    2008-01-01

    The role of noise for a single neuron and for an ensemble of mutually coupled neurons is investigated. For a single element we show that an increase in noise intensity in the regime of irregular. ring enhances the coherence of the neuronal response. For this regime of spiking a study...... based on the connection graph stability method and through numerical simulation....

  15. Future changes in tropical cyclone activity projected by multi-physics and multi-SST ensemble experiments using the 60-km-mesh MRI-AGCM

    Energy Technology Data Exchange (ETDEWEB)

    Murakami, Hiroyuki [Japan Agency for Marine-Earth Science and Technology (JAMSTEC)/Meteorological Research Institute (MRI), Tsukuba, Ibaraki (Japan); University of Hawaii at Manoa, International Pacific Research Center, School of Ocean and Earth Science and Technology, Honolulu, Hawaii (United States); Mizuta, Ryo; Shindo, Eiki [Meteorological Research Institute (MRI), Climate Research Department, Tsukuba, Ibaraki (Japan)

    2012-11-15

    Uncertainties in projected future changes in tropical cyclone (TC) activity are investigated using future (2075-2099) ensemble projections of global warming under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. Twelve ensemble experiments are performed using three different cumulus convection schemes and four different assumptions for prescribed future sea surface temperatures (SSTs). All ensemble experiments consistently project significant reductions in global and hemispheric TC genesis numbers as well as reductions in TC frequency of occurrence (TCF) and TC genesis frequency (TGF) in the western North Pacific, South Indian Ocean, and South Pacific Ocean. TCF and TGF are projected to increase over the central Pacific which is consistent with the findings of Li et al. (2010). Inter-experimental variations of projected future changes in TGF and TC genesis number are caused mainly by differences in large-scale dynamical parameters and SST anomalies. Thermodynamic parameters are of secondary importance for variations in TGF and TC genesis number. These results imply that differences in SST spatial patterns can cause substantial variations and uncertainties in projected future changes of TGF and TC numbers at ocean-basin scales. (orig.)

  16. Ensemble-Based Data Assimilation in Reservoir Characterization: A Review

    Directory of Open Access Journals (Sweden)

    Seungpil Jung

    2018-02-01

    Full Text Available This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF and ensemble smoother (ES as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization.

  17. Supersymmetry applied to the spectrum edge of random matrix ensembles

    International Nuclear Information System (INIS)

    Andreev, A.V.; Simons, B.D.; Taniguchi, N.

    1994-01-01

    A new matrix ensemble has recently been proposed to describe the transport properties in mesoscopic quantum wires. Both analytical and numerical studies have shown that the ensemble of Laguerre or of chiral random matrices provides a good description of scattering properties in this class of systems. Until now only conventional methods of random matrix theory have been used to study statistical properties within this ensemble. We demonstrate that the supersymmetry method, already employed in the study Dyson ensembles, can be extended to treat this class of random matrix ensembles. In developing this approach we investigate both new, as well as verify known statistical measures. Although we focus on ensembles in which T-invariance is violated our approach lays the foundation for future studies of T-invariant systems. ((orig.))

  18. Bioactive focus in conformational ensembles: a pluralistic approach

    Science.gov (United States)

    Habgood, Matthew

    2017-12-01

    Computational generation of conformational ensembles is key to contemporary drug design. Selecting the members of the ensemble that will approximate the conformation most likely to bind to a desired target (the bioactive conformation) is difficult, given that the potential energy usually used to generate and rank the ensemble is a notoriously poor discriminator between bioactive and non-bioactive conformations. In this study an approach to generating a focused ensemble is proposed in which each conformation is assigned multiple rankings based not just on potential energy but also on solvation energy, hydrophobic or hydrophilic interaction energy, radius of gyration, and on a statistical potential derived from Cambridge Structural Database data. The best ranked structures derived from each system are then assembled into a new ensemble that is shown to be better focused on bioactive conformations. This pluralistic approach is tested on ensembles generated by the Molecular Operating Environment's Low Mode Molecular Dynamics module, and by the Cambridge Crystallographic Data Centre's conformation generator software.

  19. Grand Canonical Ensembles in General Relativity

    International Nuclear Information System (INIS)

    Klein, David; Yang, Wei-Shih

    2012-01-01

    We develop a formalism for general relativistic, grand canonical ensembles in space-times with timelike Killing fields. Using that, we derive ideal gas laws, and show how they depend on the geometry of the particular space-times. A systematic method for calculating Newtonian limits is given for a class of these space-times, which is illustrated for Kerr space-time. In addition, we prove uniqueness of the infinite volume Gibbs measure, and absence of phase transitions for a class of interaction potentials in anti-de Sitter space.

  20. A Lagrangian formalism for nonequilibrium ensembles

    International Nuclear Information System (INIS)

    Sobouti, Y.

    1989-08-01

    It is suggested to formulate a nonequilibrium ensemble theory by maximizing a time-integrated entropy constrained by Liouville's equation. This leads to distribution functions of the form f = Z -1 exp(-g/kT), where g(p,q,t) is a solution of Liouville's equation. A further requirement that the entropy should be an additivie functional of the integrals of Liouville's equation, limits the choice of g to linear superpositions of the nonlinearly independent integrals of motion. Time-dependent and time-independent integrals may participate in this superposition. (author). 14 refs

  1. Machines vs. ensembles: effective MAPK signaling through heterogeneous sets of protein complexes.

    Directory of Open Access Journals (Sweden)

    Ryan Suderman

    Full Text Available Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively

  2. A short-term ensemble wind speed forecasting system for wind power applications

    Science.gov (United States)

    Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

    2011-12-01

    This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

  3. Extension of the GHJW theorem for operator ensembles

    International Nuclear Information System (INIS)

    Choi, Jeong Woon; Hong, Dowon; Chang, Ku-Young; Chi, Dong Pyo; Lee, Soojoon

    2011-01-01

    The Gisin-Hughston-Jozsa-Wootters theorem plays an important role in analyzing various theories about quantum information, quantum communication, and quantum cryptography. It means that any purifications on the extended system which yield indistinguishable state ensembles on their subsystem should have a specific local unitary relation. In this Letter, we show that the local relation is also established even when the indistinguishability of state ensembles is extended to that of operator ensembles.

  4. Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine

    Science.gov (United States)

    Verkade, J. S.; Brown, J. D.; Davids, F.; Reggiani, P.; Weerts, A. H.

    2017-12-01

    Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) 'dressing' of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) 'dressing' of an ensemble streamflow forecast by adding an estimate of hydrological uncertainty to each individual streamflow ensemble member. Both approaches aim to produce an estimate of the 'total uncertainty' that captures both the meteorological and hydrological uncertainties. They differ in the degree to which they make use of statistical post-processing techniques. In the 'lumped' approach, both sources of uncertainty are lumped by post-processing deterministic forecasts using their verifying observations. In the 'source-specific' approach, the meteorological uncertainties are estimated by an ensemble of weather forecasts. These ensemble members are routed through a hydrological model and a realization of the probability distribution of hydrological uncertainties (only) is then added to each ensemble member to arrive at an estimate of the total uncertainty. The techniques are applied to one location in the Meuse basin and three locations in the Rhine basin. Resulting forecasts are assessed for their reliability and sharpness, as well as compared in terms of multiple verification scores including the relative mean error, Brier Skill Score, Mean Continuous Ranked Probability Skill Score, Relative Operating Characteristic Score and Relative Economic Value. The dressed deterministic forecasts are generally more reliable than the dressed ensemble forecasts, but the latter are sharper. On balance, however, they show similar quality across a range of verification metrics, with the dressed ensembles coming out slightly better. Some additional analyses are suggested. Notably, these include statistical post-processing of the meteorological forecasts in order to increase their reliability, thus increasing the reliability

  5. Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

    Science.gov (United States)

    Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

    2009-10-01

    One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

  6. Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

    Energy Technology Data Exchange (ETDEWEB)

    Somot, S.; Deque, M. [Meteo-France CNRM/GMGEC CNRS/GAME, Toulouse (France); Sanchez-Gomez, Emilia

    2009-10-15

    One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation. (orig.)

  7. Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination.

    Science.gov (United States)

    Sørensen, Lauge; Nielsen, Mads

    2018-05-15

    The International Challenge for Automated Prediction of MCI from MRI data offered independent, standardized comparison of machine learning algorithms for multi-class classification of normal control (NC), mild cognitive impairment (MCI), converting MCI (cMCI), and Alzheimer's disease (AD) using brain imaging and general cognition. We proposed to use an ensemble of support vector machines (SVMs) that combined bagging without replacement and feature selection. SVM is the most commonly used algorithm in multivariate classification of dementia, and it was therefore valuable to evaluate the potential benefit of ensembling this type of classifier. The ensemble SVM, using either a linear or a radial basis function (RBF) kernel, achieved multi-class classification accuracies of 55.6% and 55.0% in the challenge test set (60 NC, 60 MCI, 60 cMCI, 60 AD), resulting in a third place in the challenge. Similar feature subset sizes were obtained for both kernels, and the most frequently selected MRI features were the volumes of the two hippocampal subregions left presubiculum and right subiculum. Post-challenge analysis revealed that enforcing a minimum number of selected features and increasing the number of ensemble classifiers improved classification accuracy up to 59.1%. The ensemble SVM outperformed single SVM classifications consistently in the challenge test set. Ensemble methods using bagging and feature selection can improve the performance of the commonly applied SVM classifier in dementia classification. This resulted in competitive classification accuracies in the International Challenge for Automated Prediction of MCI from MRI data. Copyright © 2018 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Giuliani, Alessandro; Tomita, Masaru

    2010-01-01

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

  9. Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

    Science.gov (United States)

    Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

    2017-12-01

    A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

  10. Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

    2016-10-01

    The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

  11. Convergence of the Square Root Ensemble Kalman Filter in the Large Ensemble Limit

    Czech Academy of Sciences Publication Activity Database

    Kwiatkowski, E.; Mandel, Jan

    2015-01-01

    Roč. 3, č. 1 (2015), s. 1-17 ISSN 2166-2525 R&D Projects: GA ČR GA13-34856S Institutional support: RVO:67985807 Keywords : data assimilation * Lp laws of large numbers * Hilbert space * ensemble Kalman filter Subject RIV: IN - Informatics, Computer Science

  12. New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

    Science.gov (United States)

    Cane, D.; Milelli, M.

    2009-09-01

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

  13. Ensemble-based forecasting at Horns Rev: Ensemble conversion and kernel dressing

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    . The obtained ensemble forecasts of wind power are then converted into predictive distributions with an original adaptive kernel dressing method. The shape of the kernels is driven by a mean-variance model, the parameters of which are recursively estimated in order to maximize the overall skill of obtained...

  14. Wind power application research on the fusion of the determination and ensemble prediction

    Science.gov (United States)

    Lan, Shi; Lina, Xu; Yuzhu, Hao

    2017-07-01

    The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

  15. Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles

    Science.gov (United States)

    Treue, Stefan

    2018-01-01

    Abstract Single neurons in the primate lateral prefrontal cortex (LPFC) encode information about the allocation of visual attention and the features of visual stimuli. However, how this compares to the performance of neuronal ensembles at encoding the same information is poorly understood. Here, we recorded the responses of neuronal ensembles in the LPFC of two macaque monkeys while they performed a task that required attending to one of two moving random dot patterns positioned in different hemifields and ignoring the other pattern. We found single units selective for the location of the attended stimulus as well as for its motion direction. To determine the coding of both variables in the population of recorded units, we used a linear classifier and progressively built neuronal ensembles by iteratively adding units according to their individual performance (best single units), or by iteratively adding units based on their contribution to the ensemble performance (best ensemble). For both methods, ensembles of relatively small sizes (n decoding performance relative to individual single units. However, the decoder reached similar performance using fewer neurons with the best ensemble building method compared with the best single units method. Our results indicate that neuronal ensembles within the LPFC encode more information about the attended spatial and nonspatial features of visual stimuli than individual neurons. They further suggest that efficient coding of attention can be achieved by relatively small neuronal ensembles characterized by a certain relationship between signal and noise correlation structures. PMID:29568798

  16. Bayesian ensemble refinement by replica simulations and reweighting

    Science.gov (United States)

    Hummer, Gerhard; Köfinger, Jürgen

    2015-12-01

    We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

  17. Design ensemble machine learning model for breast cancer diagnosis.

    Science.gov (United States)

    Hsieh, Sheau-Ling; Hsieh, Sung-Huai; Cheng, Po-Hsun; Chen, Chi-Huang; Hsu, Kai-Ping; Lee, I-Shun; Wang, Zhenyu; Lai, Feipei

    2012-10-01

    In this paper, we classify the breast cancer of medical diagnostic data. Information gain has been adapted for feature selections. Neural fuzzy (NF), k-nearest neighbor (KNN), quadratic classifier (QC), each single model scheme as well as their associated, ensemble ones have been developed for classifications. In addition, a combined ensemble model with these three schemes has been constructed for further validations. The experimental results indicate that the ensemble learning performs better than individual single ones. Moreover, the combined ensemble model illustrates the highest accuracy of classifications for the breast cancer among all models.

  18. Ensemble atmospheric dispersion calculations for decision support systems

    International Nuclear Information System (INIS)

    Borysiewicz, M.; Potempski, S.; Galkowski, A.; Zelazny, R.

    2003-01-01

    This document describes two approaches to long-range atmospheric dispersion of pollutants based on the ensemble concept. In the first part of the report some experiences related to the exercises undertaken under the ENSEMBLE project of the European Union are presented. The second part is devoted to the implementation of mesoscale numerical prediction models RAMS and atmospheric dispersion model HYPACT on Beowulf cluster and theirs usage for ensemble forecasting and long range atmospheric ensemble dispersion calculations based on available meteorological data from NCEO, NOAA (USA). (author)

  19. Characterizing Drought Events from a Hydrological Model Ensemble

    Science.gov (United States)

    Smith, Katie; Parry, Simon; Prudhomme, Christel; Hannaford, Jamie; Tanguy, Maliko; Barker, Lucy; Svensson, Cecilia

    2017-04-01

    Hydrological droughts are a slow onset natural hazard that can affect large areas. Within the United Kingdom there have been eight major drought events over the last 50 years, with several events acting at the continental scale, and covering the entire nation. Many of these events have lasted several years and had significant impacts on agriculture, the environment and the economy. Generally in the UK, due to a northwest-southeast gradient in rainfall and relief, as well as varying underlying geology, droughts tend to be most severe in the southeast, which can threaten water supplies to the capital in London. With the impacts of climate change likely to increase the severity and duration of drought events worldwide, it is crucial that we gain an understanding of the characteristics of some of the longer and more extreme droughts of the 19th and 20th centuries, so we may utilize this information in planning for the future. Hydrological models are essential both for reconstructing such events that predate streamflow records, and for use in drought forecasting. However, whilst the uncertainties involved in modelling hydrological extremes on the flooding end of the flow regime have been studied in depth over the past few decades, the uncertainties in simulating droughts and low flow events have not yet received such rigorous academic attention. The "Cascade of Uncertainty" approach has been applied to explore uncertainty and coherence across simulations of notable drought events from the past 50 years using the airGR family of daily lumped catchment models. Parameter uncertainty has been addressed using a Latin Hypercube sampled experiment of 500,000 parameter sets per model (GR4J, GR5J and GR6J), over more than 200 catchments across the UK. The best performing model parameterisations, determined using a multi-objective function approach, have then been taken forward for use in the assessment of the impact of model parameters and model structure on drought event

  20. Infections and mixed infections with the selected species of Borrelia burgdorferi sensu lato complex in Ixodes ricinus ticks collected in eastern Poland: a significant increase in the course of 5 years.

    Science.gov (United States)

    Wójcik-Fatla, Angelina; Zając, Violetta; Sawczyn, Anna; Sroka, Jacek; Cisak, Ewa; Dutkiewicz, Jacek

    2016-02-01

    In the years 2008-2009 and 2013-2014, 1620 and 1500 questing Ixodes ricinus ticks, respectively, were examined on the territory of the Lublin province (eastern Poland). The presence of three pathogenic species causing Lyme disease was investigated: Borrelia burgdorferi sensu stricto, B. afzelii and B. garinii. The proportion of I. ricinus ticks infected with B. burgdorferi sensu lato showed a highly significant increase between 2008-2009 and 2013-2014, from 6.0 to 15.3%. A significant increase was noted with regard to all types of infections with individual species: single (4.7-7.8%), dual (1.2-6.6%), and triple (0.1-0.9%). When expressed as the percent of all infections, the frequency of mixed infections increased from 21.4 to 49.2%. Statistical analysis performed with two methods (by calculating of odds ratios and by Fisher's exact test) showed that the frequencies of mixed infections in most cases proved to be significantly greater than expected. The strongest associations were found between B. burgdorferi s. s. and B. afzelii, and between B. burgdorferi s. s. and B. garinii. They appeared to be highly significant (P eastern Poland, and dramatic enhancement of mixed infections with individual species, which may result in mixed infections of humans and exacerbation of the clinical course of Lyme disease cases on the studied area.

  1. Cluster Ensemble-Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  2. Nanobiosensing with Arrays and Ensembles of Nanoelectrodes

    Directory of Open Access Journals (Sweden)

    Najmeh Karimian

    2016-12-01

    Full Text Available Since the first reports dating back to the mid-1990s, ensembles and arrays of nanoelectrodes (NEEs and NEAs, respectively have gained an important role as advanced electroanalytical tools thank to their unique characteristics which include, among others, dramatically improved signal/noise ratios, enhanced mass transport and suitability for extreme miniaturization. From the year 2000 onward, these properties have been exploited to develop electrochemical biosensors in which the surfaces of NEEs/NEAs have been functionalized with biorecognition layers using immobilization modes able to take the maximum advantage from the special morphology and composite nature of their surface. This paper presents an updated overview of this field. It consists of two parts. In the first, we discuss nanofabrication methods and the principles of functioning of NEEs/NEAs, focusing, in particular, on those features which are important for the development of highly sensitive and miniaturized biosensors. In the second part, we review literature references dealing the bioanalytical and biosensing applications of sensors based on biofunctionalized arrays/ensembles of nanoelectrodes, focusing our attention on the most recent advances, published in the last five years. The goal of this review is both to furnish fundamental knowledge to researchers starting their activity in this field and provide critical information on recent achievements which can stimulate new ideas for future developments to experienced scientists.

  3. Ensemble Kalman filtering with residual nudging

    KAUST Repository

    Luo, X.

    2012-10-03

    Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.

  4. Deterministic Mean-Field Ensemble Kalman Filtering

    KAUST Repository

    Law, Kody

    2016-05-03

    The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.

  5. Online cross-validation-based ensemble learning.

    Science.gov (United States)

    Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

    2018-01-30

    Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  6. Performance Analysis of Local Ensemble Kalman Filter

    Science.gov (United States)

    Tong, Xin T.

    2018-03-01

    Ensemble Kalman filter (EnKF) is an important data assimilation method for high-dimensional geophysical systems. Efficient implementation of EnKF in practice often involves the localization technique, which updates each component using only information within a local radius. This paper rigorously analyzes the local EnKF (LEnKF) for linear systems and shows that the filter error can be dominated by the ensemble covariance, as long as (1) the sample size exceeds the logarithmic of state dimension and a constant that depends only on the local radius; (2) the forecast covariance matrix admits a stable localized structure. In particular, this indicates that with small system and observation noises, the filter error will be accurate in long time even if the initialization is not. The analysis also reveals an intrinsic inconsistency caused by the localization technique, and a stable localized structure is necessary to control this inconsistency. While this structure is usually taken for granted for the operation of LEnKF, it can also be rigorously proved for linear systems with sparse local observations and weak local interactions. These theoretical results are also validated by numerical implementation of LEnKF on a simple stochastic turbulence in two dynamical regimes.

  7. Ensemble Kalman filtering with residual nudging

    Directory of Open Access Journals (Sweden)

    Xiaodong Luo

    2012-10-01

    Full Text Available Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF by (in effect adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.

  8. Deterministic Mean-Field Ensemble Kalman Filtering

    KAUST Repository

    Law, Kody; Tembine, Hamidou; Tempone, Raul

    2016-01-01

    The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.

  9. Acute leukemia classification by ensemble particle swarm model selection.

    Science.gov (United States)

    Escalante, Hugo Jair; Montes-y-Gómez, Manuel; González, Jesús A; Gómez-Gil, Pilar; Altamirano, Leopoldo; Reyes, Carlos A; Reta, Carolina; Rosales, Alejandro

    2012-07-01

    Acute leukemia is a malignant disease that affects a large proportion of the world population. Different types and subtypes of acute leukemia require different treatments. In order to assign the correct treatment, a physician must identify the leukemia type or subtype. Advanced and precise methods are available for identifying leukemia types, but they are very expensive and not available in most hospitals in developing countries. Thus, alternative methods have been proposed. An option explored in this paper is based on the morphological properties of bone marrow images, where features are extracted from medical images and standard machine learning techniques are used to build leukemia type classifiers. This paper studies the use of ensemble particle swarm model selection (EPSMS), which is an automated tool for the selection of classification models, in the context of acute leukemia classification. EPSMS is the application of particle swarm optimization to the exploration of the search space of ensembles that can be formed by heterogeneous classification models in a machine learning toolbox. EPSMS does not require prior domain knowledge and it is able to select highly accurate classification models without user intervention. Furthermore, specific models can be used for different classification tasks. We report experimental results for acute leukemia classification with real data and show that EPSMS outperformed the best results obtained using manually designed classifiers with the same data. The highest performance using EPSMS was of 97.68% for two-type classification problems and of 94.21% for more than two types problems. To the best of our knowledge, these are the best results reported for this data set. Compared with previous studies, these improvements were consistent among different type/subtype classification tasks, different features extracted from images, and different feature extraction regions. The performance improvements were statistically significant

  10. Post-processing of multi-model ensemble river discharge forecasts using censored EMOS

    Science.gov (United States)

    Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

    2014-05-01

    When forecasting water levels and river discharge, ensemble weather forecasts are used as meteorological input to hydrologic process models. As hydrologic models are imperfect and the input ensembles tend to be biased and underdispersed, the output ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, statistical post-processing is required in order to achieve calibrated and sharp predictions. Standard post-processing methods such as Ensemble Model Output Statistics (EMOS) that have their origins in meteorological forecasting are now increasingly being used in hydrologic applications. Here we consider two sub-catchments of River Rhine, for which the forecasting system of the Federal Institute of Hydrology (BfG) uses runoff data that are censored below predefined thresholds. To address this methodological challenge, we develop a censored EMOS method that is tailored to such data. The censored EMOS forecast distribution can be understood as a mixture of a point mass at the censoring threshold and a continuous part based on a truncated normal distribution. Parameter estimates of the censored EMOS model are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over the training dataset. Model fitting on Box-Cox transformed data allows us to take account of the positive skewness of river discharge distributions. In order to achieve realistic forecast scenarios over an entire range of lead-times, there is a need for multivariate extensions. To this end, we smooth the marginal parameter estimates over lead-times. In order to obtain realistic scenarios of discharge evolution over time, the marginal distributions have to be linked with each other. To this end, the multivariate dependence structure can either be adopted from the raw ensemble like in Ensemble Copula Coupling (ECC), or be estimated from observations in a training period. The censored EMOS model has been applied to multi-model ensemble forecasts issued on a

  11. Impact of distributions on the archetypes and prototypes in heterogeneous nanoparticle ensembles.

    Science.gov (United States)

    Fernandez, Michael; Wilson, Hugh F; Barnard, Amanda S

    2017-01-05

    The magnitude and complexity of the structural and functional data available on nanomaterials requires data analytics, statistical analysis and information technology to drive discovery. We demonstrate that multivariate statistical analysis can recognise the sets of truly significant nanostructures and their most relevant properties in heterogeneous ensembles with different probability distributions. The prototypical and archetypal nanostructures of five virtual ensembles of Si quantum dots (SiQDs) with Boltzmann, frequency, normal, Poisson and random distributions are identified using clustering and archetypal analysis, where we find that their diversity is defined by size and shape, regardless of the type of distribution. At the complex hull of the SiQD ensembles, simple configuration archetypes can efficiently describe a large number of SiQDs, whereas more complex shapes are needed to represent the average ordering of the ensembles. This approach provides a route towards the characterisation of computationally intractable virtual nanomaterial spaces, which can convert big data into smart data, and significantly reduce the workload to simulate experimentally relevant virtual samples.

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

    Science.gov (United States)

    Oh, Seok-Geun; Suh, Myoung-Seok

    2017-07-01

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

  13. Music regulators in two string quartet ensembles: a comparison of communicative behaviours between low- and high-stress performance conditions

    Directory of Open Access Journals (Sweden)

    Michele Biasutti

    2016-08-01

    Full Text Available In ensemble performances, group members use particular bodily behaviours as a sort of language to supplement the lack of verbal communication. This research study focuses on music regulators, which are defined as signs to other group members for coordinating performance. The following two music regulators are considered: body gestures for articulating attacks (a set of movements externally directed that are used to signal entrances in performance and eye contacts. These regulators are recurring observable behaviors that play an important role in nonverbal communication among ensemble members. To understand how these regulators are used by chamber musicians, video recordings of members of two string quartet ensemble performances (Quartet Ensemble A performing Bartók and Quartet Ensemble B performing Haydn were analysed under two conditions: a low stress performance (LSP, undertaken in a rehearsal setting, and a high stress performance (HSP during a live concert. The results provide evidence for more emphasis in gestures for articulating attacks (i.e. the perceived strength of a performed attack-type body gestures during HSP than LSP. . Conversely, no significant differences were found for the frequency of eye contact between HSP and LSP. Moreover, there was variability in eye contacts during HSP and LSP, showing that these behaviours are less standardised and may change according to idiosyncratic performing conditions. Educational implications are discussed for improving interpersonal communication skills during ensemble performance.

  14. Real­-Time Ensemble Forecasting of Coronal Mass Ejections Using the Wsa-Enlil+Cone Model

    Science.gov (United States)

    Mays, M. L.; Taktakishvili, A.; Pulkkinen, A. A.; Odstrcil, D.; MacNeice, P. J.; Rastaetter, L.; LaSota, J. A.

    2014-12-01

    Ensemble forecasting of coronal mass ejections (CMEs) provides significant information in that it provides an estimation of the spread or uncertainty in CME arrival time predictions. Real-time ensemble modeling of CME propagation is performed by forecasters at the Space Weather Research Center (SWRC) using the WSA-ENLIL+cone model available at the Community Coordinated Modeling Center (CCMC). To estimate the effect of uncertainties in determining CME input parameters on arrival time predictions, a distribution of n (routinely n=48) CME input parameter sets are generated using the CCMC Stereo CME Analysis Tool (StereoCAT) which employs geometrical triangulation techniques. These input parameters are used to perform n different simulations yielding an ensemble of solar wind parameters at various locations of interest, including a probability distribution of CME arrival times (for hits), and geomagnetic storm strength (for Earth-directed hits). We present the results of ensemble simulations for a total of 38 CME events in 2013-2014. For 28 of the ensemble runs containing hits, the observed CME arrival was within the range of ensemble arrival time predictions for 14 runs (half). The average arrival time prediction was computed for each of the 28 ensembles predicting hits and using the actual arrival time, an average absolute error of 10.0 hours (RMSE=11.4 hours) was found for all 28 ensembles, which is comparable to current forecasting errors. Some considerations for the accuracy of ensemble CME arrival time predictions include the importance of the initial distribution of CME input parameters, particularly the mean and spread. When the observed arrivals are not within the predicted range, this still allows the ruling out of prediction errors caused by tested CME input parameters. Prediction errors can also arise from ambient model parameters such as the accuracy of the solar wind background, and other limitations. Additionally the ensemble modeling sysem was used to

  15. A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning.

    Science.gov (United States)

    Lu, Wei; Li, Zhe; Chu, Jinghui

    2017-04-01

    Breast cancer is a common cancer among women. With the development of modern medical science and information technology, medical imaging techniques have an increasingly important role in the early detection and diagnosis of breast cancer. In this paper, we propose an automated computer-aided diagnosis (CADx) framework for magnetic resonance imaging (MRI). The scheme consists of an ensemble of several machine learning-based techniques, including ensemble under-sampling (EUS) for imbalanced data processing, the Relief algorithm for feature selection, the subspace method for providing data diversity, and Adaboost for improving the performance of base classifiers. We extracted morphological, various texture, and Gabor features. To clarify the feature subsets' physical meaning, subspaces are built by combining morphological features with each kind of texture or Gabor feature. We tested our proposal using a manually segmented Region of Interest (ROI) data set, which contains 438 images of malignant tumors and 1898 images of normal tissues or benign tumors. Our proposal achieves an area under the ROC curve (AUC) value of 0.9617, which outperforms most other state-of-the-art breast MRI CADx systems. Compared with other methods, our proposal significantly reduces the false-positive classification rate. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

    Science.gov (United States)

    Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

    2017-12-01

    This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

  17. A deep learning-based multi-model ensemble method for cancer prediction.

    Science.gov (United States)

    Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

    2018-01-01

    Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Phase Locking a Clock Oscillator to a Coherent Atomic Ensemble

    Directory of Open Access Journals (Sweden)

    R. Kohlhaas

    2015-04-01

    Full Text Available The sensitivity of an atomic interferometer increases when the phase evolution of its quantum superposition state is measured over a longer interrogation interval. In practice, a limit is set by the measurement process, which returns not the phase but its projection in terms of population difference on two energetic levels. The phase interval over which the relation can be inverted is thus limited to the interval [-π/2,π/2]; going beyond it introduces an ambiguity in the readout, hence a sensitivity loss. Here, we extend the unambiguous interval to probe the phase evolution of an atomic ensemble using coherence-preserving measurements and phase corrections, and demonstrate the phase lock of the clock oscillator to an atomic superposition state. We propose a protocol based on the phase lock to improve atomic clocks limited by local oscillator noise, and foresee the application to other atomic interferometers such as inertial sensors.

  19. Ensemble Learning or Deep Learning? Application to Default Risk Analysis

    Directory of Open Access Journals (Sweden)

    Shigeyuki Hamori

    2018-03-01

    Full Text Available Proper credit-risk management is essential for lending institutions, as substantial losses can be incurred when borrowers default. Consequently, statistical methods that can measure and analyze credit risk objectively are becoming increasingly important. This study analyzes default payment data and compares the prediction accuracy and classification ability of three ensemble-learning methods—specifically, bagging, random forest, and boosting—with those of various neural-network methods, each of which has a different activation function. The results obtained indicate that the classification ability of boosting is superior to other machine-learning methods including neural networks. It is also found that the performance of neural-network models depends on the choice of activation function, the number of middle layers, and the inclusion of dropout.

  20. Gadolinium-enhanced cardiac MR exams of human subjects are associated with significant increases in the DNA repair marker 53BP1, but not the damage marker γH2AX.

    Directory of Open Access Journals (Sweden)

    Jennifer S McDonald

    Full Text Available Magnetic resonance imaging is considered low risk, yet recent studies have raised a concern of potential damage to DNA in peripheral blood leukocytes. This prospective Institutional Review Board-approved study examined potential double-strand DNA damage by analyzing changes in the DNA damage and repair markers γH2AX and 53BP1 in patients who underwent a 1.5 T gadolinium-enhanced cardiac magnetic resonance (MR exam. Sixty patients were enrolled (median age 55 years, 39 males. Patients with history of malignancy or who were receiving chemotherapy, radiation therapy, or steroids were excluded. MR sequence data were recorded and blood samples obtained immediately before and after MR exposure. An automated immunofluorescence assay quantified γH2AX or 53BP1 foci number in isolated peripheral blood mononuclear cells. Changes in foci number were analyzed using the Wilcoxon signed-rank test. Clinical and MR procedural characteristics were compared between patients who had a >10% increase in γH2AX or 53BP1 foci numbers and patients who did not. The number of γH2AX foci did not significantly change following cardiac MR (median foci per cell pre-MR = 0.11, post-MR = 0.11, p = .90, but the number of 53BP1 foci significantly increased following MR (median foci per cell pre-MR = 0.46, post-MR = 0.54, p = .0140. Clinical and MR characteristics did not differ significantly between patients who had at least a 10% increase in foci per cell and those who did not. We conclude that MR exposure leads to a small (median 25% increase in 53BP1 foci, however the clinical relevance of this increase is unknown and may be attributable to normal variation instead of MR exposure.

  1. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    Directory of Open Access Journals (Sweden)

    Shah Imran

    2011-07-01

    Full Text Available Abstract Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our

  2. Cluster-based analysis of multi-model climate ensembles

    Science.gov (United States)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

  3. Crossover ensembles of random matrices and skew-orthogonal polynomials

    International Nuclear Information System (INIS)

    Kumar, Santosh; Pandey, Akhilesh

    2011-01-01

    Highlights: → We study crossover ensembles of Jacobi family of random matrices. → We consider correlations for orthogonal-unitary and symplectic-unitary crossovers. → We use the method of skew-orthogonal polynomials and quaternion determinants. → We prove universality of spectral correlations in crossover ensembles. → We discuss applications to quantum conductance and communication theory problems. - Abstract: In a recent paper (S. Kumar, A. Pandey, Phys. Rev. E, 79, 2009, p. 026211) we considered Jacobi family (including Laguerre and Gaussian cases) of random matrix ensembles and reported exact solutions of crossover problems involving time-reversal symmetry breaking. In the present paper we give details of the work. We start with Dyson's Brownian motion description of random matrix ensembles and obtain universal hierarchic relations among the unfolded correlation functions. For arbitrary dimensions we derive the joint probability density (jpd) of eigenvalues for all transitions leading to unitary ensembles as equilibrium ensembles. We focus on the orthogonal-unitary and symplectic-unitary crossovers and give generic expressions for jpd of eigenvalues, two-point kernels and n-level correlation functions. This involves generalization of the theory of skew-orthogonal polynomials to crossover ensembles. We also consider crossovers in the circular ensembles to show the generality of our method. In the large dimensionality limit, correlations in spectra with arbitrary initial density are shown to be universal when expressed in terms of a rescaled symmetry breaking parameter. Applications of our crossover results to communication theory and quantum conductance problems are also briefly discussed.

  4. A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

    KAUST Repository

    Altaf, Muhammad

    2014-08-01

    This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

  5. Conductor and Ensemble Performance Expressivity and State Festival Ratings

    Science.gov (United States)

    Price, Harry E.; Chang, E. Christina

    2005-01-01

    This study is the second in a series examining the relationship between conducting and ensemble performance. The purpose was to further examine the associations among conductor, ensemble performance expressivity, and festival ratings. Participants were asked to rate the expressivity of video-only conducting and parallel audio-only excerpts from a…

  6. An iterative ensemble Kalman filter for reservoir engineering applications

    NARCIS (Netherlands)

    Krymskaya, M.V.; Hanea, R.G.; Verlaan, M.

    2009-01-01

    The study has been focused on examining the usage and the applicability of ensemble Kalman filtering techniques to the history matching procedures. The ensemble Kalman filter (EnKF) is often applied nowadays to solving such a problem. Meanwhile, traditional EnKF requires assumption of the

  7. Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

    Science.gov (United States)

    Ye, Qiang

    2010-01-01

    Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

  8. A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

    KAUST Repository

    Altaf, Muhammad; Butler, T.; Mayo, T.; Luo, X.; Dawson, C.; Heemink, A. W.; Hoteit, Ibrahim

    2014-01-01

    This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

  9. Ensemble dispersion forecasting - Part 2. Application and evaluation

    DEFF Research Database (Denmark)

    Galmarini, S.; Bianconi, R.; Addis, R.

    2004-01-01

    of the dispersion of ETEX release 1 and the model ensemble is compared with the monitoring data. The scope of the comparison is to estimate to what extent the ensemble analysis is an improvement with respect to the single model results and represents a superior analysis of the process evolution. (C) 2004 Elsevier...

  10. Adaptive calibration of (u,v)‐wind ensemble forecasts

    DEFF Research Database (Denmark)

    Pinson, Pierre

    2012-01-01

    of sufficient reliability. The original framework introduced here allows for an adaptive bivariate calibration of these ensemble forecasts. The originality of this methodology lies in the fact that calibrated ensembles still consist of a set of (space–time) trajectories, after translation and dilation...... of translation and dilation factors are discussed. Copyright © 2012 Royal Meteorological Society...

  11. Ensemble-based Probabilistic Forecasting at Horns Rev

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    2009-01-01

    forecasting methodology. In a first stage, ensemble forecasts of meteorological variables are converted to power through a suitable power curve model. This modelemploys local polynomial regression, and is adoptively estimated with an orthogonal fitting method. The obtained ensemble forecasts of wind power...

  12. Probabilistic Determination of Native State Ensembles of Proteins

    DEFF Research Database (Denmark)

    Olsson, Simon; Vögeli, Beat Rolf; Cavalli, Andrea

    2014-01-01

    ensembles of proteins by the combination of physical force fields and experimental data through modern statistical methodology. As an example, we use NMR residual dipolar couplings to determine a native state ensemble of the extensively studied third immunoglobulin binding domain of protein G (GB3...

  13. Preferences of and Attitudes toward Treble Choral Ensembles

    Science.gov (United States)

    Wilson, Jill M.

    2012-01-01

    In choral ensembles, a pursuit where females far outnumber males, concern exists that females are being devalued. Attitudes of female choral singers may be negatively affected by the gender imbalance that exists in mixed choirs and by the placement of the mixed choir as the most select ensemble in a program. The purpose of this research was to…

  14. Modality-Driven Classification and Visualization of Ensemble Variance

    Energy Technology Data Exchange (ETDEWEB)

    Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

    2016-10-01

    Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

  15. An educational model for ensemble streamflow simulation and uncertainty analysis

    Directory of Open Access Journals (Sweden)

    A. AghaKouchak

    2013-02-01

    Full Text Available This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.

  16. Ensemble inequivalence: Landau theory and the ABC model

    International Nuclear Information System (INIS)

    Cohen, O; Mukamel, D

    2012-01-01

    It is well known that systems with long-range interactions may exhibit different phase diagrams when studied within two different ensembles. In many of the previously studied examples of ensemble inequivalence, the phase diagrams differ only when the transition in one of the ensembles is first order. By contrast, in a recent study of a generalized ABC model, the canonical and grand-canonical ensembles of the model were shown to differ even when they both exhibit a continuous transition. Here we show that the order of the transition where ensemble inequivalence may occur is related to the symmetry properties of the order parameter associated with the transition. This is done by analyzing the Landau expansion of a generic model with long-range interactions. The conclusions drawn from the generic analysis are demonstrated for the ABC model by explicit calculation of its Landau expansion. (paper)

  17. Evaluation of bias-correction methods for ensemble streamflow volume forecasts

    Directory of Open Access Journals (Sweden)

    T. Hashino

    2007-01-01

    Full Text Available Ensemble prediction systems are used operationally to make probabilistic streamflow forecasts for seasonal time scales. However, hydrological models used for ensemble streamflow prediction often have simulation biases that degrade forecast quality and limit the operational usefulness of the forecasts. This study evaluates three bias-correction methods for ensemble streamflow volume forecasts. All three adjust the ensemble traces using a transformation derived with simulated and observed flows from a historical simulation. The quality of probabilistic forecasts issued when using the three bias-correction methods is evaluated using a distributions-oriented verification approach. Comparisons are made of retrospective forecasts of monthly flow volumes for a north-central United States basin (Des Moines River, Iowa, issued sequentially for each month over a 48-year record. The results show that all three bias-correction methods significantly improve forecast quality by eliminating unconditional biases and enhancing the potential skill. Still, subtle differences in the attributes of the bias-corrected forecasts have important implications for their use in operational decision-making. Diagnostic verification distinguishes these attributes in a context meaningful for decision-making, providing criteria to choose among bias-correction methods with comparable skill.

  18. "Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

    Science.gov (United States)

    Taylor, Patrick C.; Baker, Noel C.

    2015-01-01

    Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

  19. An adaptive Gaussian process-based iterative ensemble smoother for data assimilation

    Science.gov (United States)

    Ju, Lei; Zhang, Jiangjiang; Meng, Long; Wu, Laosheng; Zeng, Lingzao

    2018-05-01

    Accurate characterization of subsurface hydraulic conductivity is vital for modeling of subsurface flow and transport. The iterative ensemble smoother (IES) has been proposed to estimate the heterogeneous parameter field. As a Monte Carlo-based method, IES requires a relatively large ensemble size to guarantee its performance. To improve the computational efficiency, we propose an adaptive Gaussian process (GP)-based iterative ensemble smoother (GPIES) in this study. At each iteration, the GP surrogate is adaptively refined by adding a few new base points chosen from the updated parameter realizations. Then the sensitivity information between model parameters and measurements is calculated from a large number of realizations generated by the GP surrogate with virtually no computational cost. Since the original model evaluations are only required for base points, whose number is much smaller than the ensemble size, the computational cost is significantly reduced. The applicability of GPIES in estimating heterogeneous conductivity is evaluated by the saturated and unsaturated flow problems, respectively. Without sacrificing estimation accuracy, GPIES achieves about an order of magnitude of speed-up compared with the standard IES. Although subsurface flow problems are considered in this study, the proposed method can be equally applied to other hydrological models.

  20. Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

    Science.gov (United States)

    Hwang, Kyu-Baek; Lee, In-Hee; Park, Jin-Ho; Hambuch, Tina; Choe, Yongjoon; Kim, MinHyeok; Lee, Kyungjoon; Song, Taemin; Neu, Matthew B; Gupta, Neha; Kohane, Isaac S; Green, Robert C; Kong, Sek Won

    2014-08-01

    As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false-positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here, we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false-negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozygous and 4.5% for homozygous single nucleotide variants (SNVs); 30.0% for heterozygous and 18.7% for homozygous insertions; 25.2% for heterozygous and 16.6% for homozygous deletions) compared to the filtering based on genotype quality scores. Moreover, ensemble genotyping excluded > 98% (105,080 of 107,167) of false positives while retaining > 95% (897 of 937) of true positives in de novo mutation (DNM) discovery in NA12878, and performed better than a consensus method using two sequencing platforms. Our proposed methods were effective in prioritizing phenotype-associated variants, and an ensemble genotyping would be essential to minimize false-positive DNM candidates. © 2014 WILEY PERIODICALS, INC.

  1. Three-dimensional theory for interaction between atomic ensembles and free-space light

    International Nuclear Information System (INIS)

    Duan, L.-M.; Cirac, J.I.; Zoller, P.

    2002-01-01

    Atomic ensembles have shown to be a promising candidate for implementations of quantum information processing by many recently discovered schemes. All these schemes are based on the interaction between optical beams and atomic ensembles. For description of these interactions, one assumed either a cavity-QED model or a one-dimensional light propagation model, which is still inadequate for a full prediction and understanding of most of the current experimental efforts that are actually taken in the three-dimensional free space. Here, we propose a perturbative theory to describe the three-dimensional effects in interaction between atomic ensembles and free-space light with a level configuration important for several applications. The calculations reveal some significant effects that were not known before from the other approaches, such as the inherent mode-mismatching noise and the optimal mode-matching conditions. The three-dimensional theory confirms the collective enhancement of the signal-to-noise ratio which is believed to be one of the main advantages of the ensemble-based quantum information processing schemes, however, it also shows that this enhancement needs to be understood in a more subtle way with an appropriate mode-matching method

  2. Taylor-expansion Monte Carlo simulations of classical fluids in the canonical and grand canonical ensemble

    International Nuclear Information System (INIS)

    Schoen, M.

    1995-01-01

    In this article the Taylor-expansion method is introduced by which Monte Carlo (MC) simulations in the canonical ensemble can be speeded up significantly, Substantial gains in computational speed of 20-40% over conventional implementations of the MC technique are obtained over a wide range of densities in homogeneous bulk phases. The basic philosophy behind the Taylor-expansion method is a division of the neighborhood of each atom (or molecule) into three different spatial zones. Interactions between atoms belonging to each zone are treated at different levels of computational sophistication. For example, only interactions between atoms belonging to the primary zone immediately surrounding an atom are treated explicitly before and after displacement. The change in the configurational energy contribution from secondary-zone interactions is obtained from the first-order term of a Taylor expansion of the configurational energy in terms of the displacement vector d. Interactions with atoms in the tertiary zone adjacent to the secondary zone are neglected throughout. The Taylor-expansion method is not restricted to the canonical ensemble but may be employed to enhance computational efficiency of MC simulations in other ensembles as well. This is demonstrated for grand canonical ensemble MC simulations of an inhomogeneous fluid which can be performed essentially on a modern personal computer

  3. Dynamical Engineering of Interactions in Qudit Ensembles

    Science.gov (United States)

    Choi, Soonwon; Yao, Norman Y.; Lukin, Mikhail D.

    2017-11-01

    We propose and analyze a method to engineer effective interactions in an ensemble of d -level systems (qudits) driven by global control fields. In particular, we present (i) a necessary and sufficient condition under which a given interaction can be decoupled, (ii) the existence of a universal sequence that decouples any (cancelable) interaction, and (iii) an efficient algorithm to engineer a target Hamiltonian from an initial Hamiltonian (if possible). We illustrate the potential of this method with two examples. Specifically, we present a 6-pulse sequence that decouples effective spin-1 dipolar interactions and demonstrate that a spin-1 Ising chain can be engineered to study transitions among three distinct symmetry protected topological phases. Our work enables new approaches for the realization of both many-body quantum memories and programmable analog quantum simulators using existing experimental platforms.

  4. La crise du vivre-ensemble

    DEFF Research Database (Denmark)

    Schultz, Nils Voisin

    2014-01-01

    Cet article examine les caractères idéologique et affectif de deux essais écrits respectivement par Alain Finkielkraut et Richard Millet sur la crise actuelle du vivre-ensemble en France. Les deux penseurs critiquent la société multiculturelle, mais alors que pour Finkielkraut cette société est une...... chance pour la France à condition que le dialogue interculturel soit renforcé et que l’idée d’une culture française y garde sa place, elle reste pour Millet une imposs