WorldWideScience

Sample records for largest prediction information

  1. Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Yan Liu

    2016-01-01

    Full Text Available The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs, are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks.

  2. Approaching the largest ‘API’: extracting information from the Internet with Python

    Directory of Open Access Journals (Sweden)

    Jonathan E. Germann

    2018-02-01

    Full Text Available This article explores the need for libraries to algorithmically access and manipulate the world’s largest API: the Internet. The billions of pages on the ‘Internet API’ (HTTP, HTML, CSS, XPath, DOM, etc. are easily accessible and manipulable. Libraries can assist in creating meaning through the datafication of information on the world wide web. Because most information is created for human consumption, some programming is required for automated extraction. Python is an easy-to-learn programming language with extensive packages and community support for web page automation. Four packages (Urllib, Selenium, BeautifulSoup, Scrapy in Python can automate almost any web page for all sized projects. An example warrant data project is explained to illustrate how well Python packages can manipulate web pages to create meaning through assembling custom datasets.

  3. Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

    Science.gov (United States)

    Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

    1999-01-01

    Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

  4. Predictive medical information and underwriting.

    Science.gov (United States)

    Dodge, John H

    2007-01-01

    Medical underwriting involves the application of actuarial science by analyzing medical information to predict the future risk of a claim. The objective is that individuals with like risk are treated in a like manner so that the premium paid is proportional to the risk of future claim.

  5. Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo.

    Science.gov (United States)

    Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

    2016-01-28

    The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

  6. Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo

    Science.gov (United States)

    Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

    2016-01-01

    The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

  7. Diabetes prevention information in Japanese magazines with the largest print runs. Content analysis using clinical guidelines as a standard.

    Science.gov (United States)

    Noda, Emi; Mifune, Taka; Nakayama, Takeo

    2013-01-01

    To characterize information on diabetes prevention appearing in Japanese general health magazines and to examine the agreement of the content with that in clinical practice guidelines for the treatment of diabetes in Japan. We used the Japanese magazines' databases provided by the Media Research Center and selected magazines with large print runs published in 2006. Two medical professionals independently conducted content analysis based on items in the diabetes prevention guidelines. The number of pages for each item and agreement with the information in the guidelines were determined. We found 63 issues of magazines amounting to 8,982 pages; 484 pages included diabetes prevention related content. For 23 items included in the diabetes prevention guidelines, overall agreement of information printed in the magazines with that in the guidelines was 64.5% (471 out of 730). The number of times these items were referred to in the magazines varied widely, from 247 times for food items to 0 times for items on screening for pregnancy-induced diabetes, dyslipidemia, and hypertension. Among the 20 items that were referred to at least once, 18 items showed more than 90% agreement with the guidelines. However, there was poor agreement for information on vegetable oil (2/14, 14%) and for specific foods (5/247, 2%). For the fatty acids category, "fat" was not mentioned in the guidelines; however, the term frequently appeared in magazines. "Uncertainty" was never mentioned in magazines for specific food items. The diabetes prevention related content in the health magazines differed from that defined in clinical practice guidelines. Most information in the magazines agreed with the guidelines, however some items were referred to inappropriately. To disseminate correct information to the public on diabetes prevention, health professionals and the media must collaborate.

  8. Predictive Analytics in Information Systems Research

    OpenAIRE

    Shmueli, Galit; Koppius, Otto

    2011-01-01

    textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory bu...

  9. Predictive Analytics in Information Systems Research

    NARCIS (Netherlands)

    G. Shmueli (Galit); O.R. Koppius (Otto)

    2011-01-01

    textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as

  10. Predicting Information Flows in Network Traffic.

    Science.gov (United States)

    Hinich, Melvin J.; Molyneux, Robert E.

    2003-01-01

    Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

  11. Predicting incident size from limited information

    International Nuclear Information System (INIS)

    Englehardt, J.D.

    1995-01-01

    Predicting the size of low-probability, high-consequence natural disasters, industrial accidents, and pollutant releases is often difficult due to limitations in the availability of data on rare events and future circumstances. When incident data are available, they may be difficult to fit with a lognormal distribution. Two Bayesian probability distributions for inferring future incident-size probabilities from limited, indirect, and subjective information are proposed in this paper. The distributions are derived from Pareto distributions that are shown to fit data on different incident types and are justified theoretically. The derived distributions incorporate both inherent variability and uncertainty due to information limitations. Results were analyzed to determine the amount of data needed to predict incident-size probabilities in various situations. Information requirements for incident-size prediction using the methods were low, particularly when the population distribution had a thick tail. Use of the distributions to predict accumulated oil-spill consequences was demonstrated

  12. Speech Intelligibility Prediction Based on Mutual Information

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, Cees H.

    2014-01-01

    This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

  13. Largest College Endowments, 2011

    Science.gov (United States)

    Chronicle of Higher Education, 2012

    2012-01-01

    Of all endowments valued at more than $250-million, the UCLA Foundation had the highest rate of growth over the previous year, at 49 percent. This article presents a table of the largest college endowments in 2011. The table covers the "rank," "institution," "market value as of June 30, 2011," and "1-year change" of institutions participating in…

  14. Network information improves cancer outcome prediction.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

    2014-07-01

    Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  15. Predicting RNA Structure Using Mutual Information

    DEFF Research Database (Denmark)

    Freyhult, E.; Moulton, V.; Gardner, P. P.

    2005-01-01

    , to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. Results: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall...... package. Conclusion: MIfold provides a useful supplementary tool to programs such as RNA Structure Logo, RNAalifold and COVE, and should be useful for automatically generating structural predictions for databases such as Rfam. Availability: MIfold is freely available from http......Background: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure...

  16. Empirical Information Metrics for Prediction Power and Experiment Planning

    Directory of Open Access Journals (Sweden)

    Christopher Lee

    2011-01-01

    Full Text Available In principle, information theory could provide useful metrics for statistical inference. In practice this is impeded by divergent assumptions: Information theory assumes the joint distribution of variables of interest is known, whereas in statistical inference it is hidden and is the goal of inference. To integrate these approaches we note a common theme they share, namely the measurement of prediction power. We generalize this concept as an information metric, subject to several requirements: Calculation of the metric must be objective or model-free; unbiased; convergent; probabilistically bounded; and low in computational complexity. Unfortunately, widely used model selection metrics such as Maximum Likelihood, the Akaike Information Criterion and Bayesian Information Criterion do not necessarily meet all these requirements. We define four distinct empirical information metrics measured via sampling, with explicit Law of Large Numbers convergence guarantees, which meet these requirements: Ie, the empirical information, a measure of average prediction power; Ib, the overfitting bias information, which measures selection bias in the modeling procedure; Ip, the potential information, which measures the total remaining information in the observations not yet discovered by the model; and Im, the model information, which measures the model’s extrapolation prediction power. Finally, we show that Ip + Ie, Ip + Im, and Ie — Im are fixed constants for a given observed dataset (i.e. prediction target, independent of the model, and thus represent a fundamental subdivision of the total information contained in the observations. We discuss the application of these metrics to modeling and experiment planning.    

  17. Prediction information - GRIPDB | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us GRI...a.nbdc01665-004 Description of data contents Predicted GPCR interaction regions Data file File name: gripdb_...predicted_info.zip File URL: ftp://ftp.biosciencedbc.jp/archive/gripdb/LATEST/gripdb_predicted_info.zip File... size: 219 KB Simple search URL http://togodb.biosciencedbc.jp/togodb/view/gripdb...entries Data item Description ID Prediction information ID GRIP ID GRIP ID related wigh the prediction Predi

  18. Changes in Pilot Behavior with Predictive System Status Information

    Science.gov (United States)

    Trujillo, Anna C.

    1998-01-01

    Research has shown a strong pilot preference for predictive information of aircraft system status in the flight deck. However, changes in pilot behavior associated with using this predictive information have not been ascertained. The study described here quantified these changes using three types of predictive information (none, whether a parameter was changing abnormally, and the time for a parameter to reach an alert range) and three initial time intervals until a parameter alert range was reached (ITIs) (1 minute, 5 minutes, and 15 minutes). With predictive information, subjects accomplished most of their tasks before an alert occurred. Subjects organized the time they did their tasks by locus-of-control with no predictive information and for the 1-minute ITI, and by aviatenavigate-communicate for the time for a parameter to reach an alert range and the 15-minute conditions. Overall, predictive information and the longer ITIs moved subjects to performing tasks before the alert actually occurred and had them more mission oriented as indicated by their tasks grouping of aviate-navigate-communicate.

  19. Suboptimal choice, reward-predictive signals, and temporal information.

    Science.gov (United States)

    Cunningham, Paul J; Shahan, Timothy A

    2018-01-01

    Suboptimal choice refers to preference for an alternative offering a low probability of food (suboptimal alternative) over an alternative offering a higher probability of food (optimal alternative). Numerous studies have found that stimuli signaling probabilistic food play a critical role in the development and maintenance of suboptimal choice. However, there is still much debate about how to characterize how these stimuli influence suboptimal choice. There is substantial evidence that the temporal information conveyed by a food-predictive signal governs its function as both a Pavlovian conditioned stimulus and as an instrumental conditioned reinforcer. Thus, we explore the possibility that food-predictive signals influence suboptimal choice via the temporal information they convey. Application of this temporal information-theoretic approach to suboptimal choice provides a formal, quantitative framework that describes how food-predictive signals influence suboptimal choice in a manner consistent with related phenomena in Pavlovian conditioning and conditioned reinforcement. Our reanalysis of previous data on suboptimal choice suggests that, generally speaking, preference in the suboptimal choice procedure tracks relative temporal information conveyed by food-predictive signals for the suboptimal and optimal alternatives. The model suggests that suboptimal choice develops when the food-predictive signal for the suboptimal alternative conveys more temporal information than that for the optimal alternative. Finally, incorporating a role for competition between temporal information provided by food-predictive signals and relative primary reinforcement rate provides a reasonable account of existing data on suboptimal choice. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  20. Largest particle detector nearing completion

    CERN Multimedia

    2006-01-01

    "Construction of another part of the Large Hadron Collider (LHC), the worl's largest particle accelerator at CERN in Switzerland, is nearing completion. The Compact Muon Solenoid (CMS) is oner of the LHC project's four large particle detectors. (1/2 page)

  1. SPEEDI: system for prediction of environmental emergency dose information

    International Nuclear Information System (INIS)

    Chino, Masamichi; Ishikawa, Hirohiko; Kai, Michiaki

    1984-03-01

    In this report a computer code system for prediction of environmental emergency dose information , i.e., SPEEDI for short, is presented. In case of an accidental release of radioactive materials from a nuclear plant, it is very important for an emergency planning to predict the concentration and dose caused by the materials. The SPEEDI code system has been developed for this purpose and it has features to predict by calculation the released nuclides, wind fields, concentrations and dose based on release information, actual weather and topographical data. (author)

  2. Information assessment on predicting protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Gerstein Mark

    2004-10-01

    Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the

  3. Learning and Prediction of Slip from Visual Information

    Science.gov (United States)

    Angelova, Anelia; Matthies, Larry; Helmick, Daniel; Perona, Pietro

    2007-01-01

    This paper presents an approach for slip prediction from a distance for wheeled ground robots using visual information as input. Large amounts of slippage which can occur on certain surfaces, such as sandy slopes, will negatively affect rover mobility. Therefore, obtaining information about slip before entering such terrain can be very useful for better planning and avoiding these areas. To address this problem, terrain appearance and geometry information about map cells are correlated to the slip measured by the rover while traversing each cell. This relationship is learned from previous experience, so slip can be predicted remotely from visual information only. The proposed method consists of terrain type recognition and nonlinear regression modeling. The method has been implemented and tested offline on several off-road terrains including: soil, sand, gravel, and woodchips. The final slip prediction error is about 20%. The system is intended for improved navigation on steep slopes and rough terrain for Mars rovers.

  4. Prediction of Missing Streamflow Data using Principle of Information Entropy

    Directory of Open Access Journals (Sweden)

    Santosa, B.

    2014-01-01

    Full Text Available Incomplete (missing of streamflow data often occurs. This can be caused by a not continous data recording or poor storage. In this study, missing consecutive streamflow data are predicted using the principle of information entropy. Predictions are performed ​​using the complete monthly streamflow information from the nearby river. Data on average monthly streamflow used as a simulation sample are taken from observation stations Katulampa, Batubeulah, and Genteng, which are the Ciliwung Cisadane river areas upstream. The simulated prediction of missing streamflow data in 2002 and 2003 at Katulampa Station are based on information from Genteng Station, and Batubeulah Station. The mean absolute error (MAE average obtained was 0,20 and 0,21 in 2002 and the MAE average in 2003 was 0,12 and 0,16. Based on the value of the error and pattern of filled gaps, this method has the potential to be developed further.

  5. Tax Evasion, Information Reporting, and the Regressive Bias Prediction

    DEFF Research Database (Denmark)

    Boserup, Simon Halphen; Pinje, Jori Veng

    2013-01-01

    evasion and audit probabilities once we account for information reporting in the tax compliance game. When conditioning on information reporting, we find that both reduced-form evidence and simulations exhibit the predicted regressive bias. However, in the overall economy, this bias is negated by the tax......Models of rational tax evasion and optimal enforcement invariably predict a regressive bias in the effective tax system, which reduces redistribution in the economy. Using Danish administrative data, we show that a calibrated structural model of this type replicates moments and correlations of tax...

  6. Comparison of Predictive Contract Mechanisms from an Information Theory Perspective

    OpenAIRE

    Zhang, Xin; Ward, Tomas; McLoone, Seamus

    2012-01-01

    Inconsistency arises across a Distributed Virtual Environment due to network latency induced by state changes communications. Predictive Contract Mechanisms (PCMs) combat this problem through reducing the amount of messages transmitted in return for perceptually tolerable inconsistency. To date there are no methods to quantify the efficiency of PCMs in communicating this reduced state information. This article presents an approach derived from concepts in information theory for a dee...

  7. Estimating the decomposition of predictive information in multivariate systems

    Science.gov (United States)

    Faes, Luca; Kugiumtzis, Dimitris; Nollo, Giandomenico; Jurysta, Fabrice; Marinazzo, Daniele

    2015-03-01

    In the study of complex systems from observed multivariate time series, insight into the evolution of one system may be under investigation, which can be explained by the information storage of the system and the information transfer from other interacting systems. We present a framework for the model-free estimation of information storage and information transfer computed as the terms composing the predictive information about the target of a multivariate dynamical process. The approach tackles the curse of dimensionality employing a nonuniform embedding scheme that selects progressively, among the past components of the multivariate process, only those that contribute most, in terms of conditional mutual information, to the present target process. Moreover, it computes all information-theoretic quantities using a nearest-neighbor technique designed to compensate the bias due to the different dimensionality of individual entropy terms. The resulting estimators of prediction entropy, storage entropy, transfer entropy, and partial transfer entropy are tested on simulations of coupled linear stochastic and nonlinear deterministic dynamic processes, demonstrating the superiority of the proposed approach over the traditional estimators based on uniform embedding. The framework is then applied to multivariate physiologic time series, resulting in physiologically well-interpretable information decompositions of cardiovascular and cardiorespiratory interactions during head-up tilt and of joint brain-heart dynamics during sleep.

  8. Why hydrological predictions should be evaluated using information theory

    Directory of Open Access Journals (Sweden)

    S. V. Weijs

    2010-12-01

    Full Text Available Probabilistic predictions are becoming increasingly popular in hydrology. Equally important are methods to test such predictions, given the topical debate on uncertainty analysis in hydrology. Also in the special case of hydrological forecasting, there is still discussion about which scores to use for their evaluation. In this paper, we propose to use information theory as the central framework to evaluate predictions. From this perspective, we hope to shed some light on what verification scores measure and should measure. We start from the ''divergence score'', a relative entropy measure that was recently found to be an appropriate measure for forecast quality. An interpretation of a decomposition of this measure provides insight in additive relations between climatological uncertainty, correct information, wrong information and remaining uncertainty. When the score is applied to deterministic forecasts, it follows that these increase uncertainty to infinity. In practice, however, deterministic forecasts tend to be judged far more mildly and are widely used. We resolve this paradoxical result by proposing that deterministic forecasts either are implicitly probabilistic or are implicitly evaluated with an underlying decision problem or utility in mind. We further propose that calibration of models representing a hydrological system should be the based on information-theoretical scores, because this allows extracting all information from the observations and avoids learning from information that is not there. Calibration based on maximizing utility for society trains an implicit decision model rather than the forecasting system itself. This inevitably results in a loss or distortion of information in the data and more risk of overfitting, possibly leading to less valuable and informative forecasts. We also show this in an example. The final conclusion is that models should preferably be explicitly probabilistic and calibrated to maximize the

  9. Aggregation of Information and Beliefs in Prediction Markets

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    We analyze a binary prediction market in which traders have heterogeneous prior beliefs and private information. Realistically, we assume that traders are allowed to invest a limited amount of money (or have decreasing absolute risk aversion). We show that the rational expectations equilibrium...... price underreacts to information. When favorable information to an event is available and is revealed by the market, the price increases and this forces optimists to reduce the number of assets they can (or want to) buy. For the market to equilibrate, the price must increase less than a posterior belief...

  10. Social networks predict selective observation and information spread in ravens

    Science.gov (United States)

    Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

    2016-01-01

    Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

  11. Predicting Key Events in the Popularity Evolution of Online Information.

    Science.gov (United States)

    Hu, Ying; Hu, Changjun; Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

    2017-01-01

    The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

  12. Predicting Key Events in the Popularity Evolution of Online Information.

    Directory of Open Access Journals (Sweden)

    Ying Hu

    Full Text Available The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

  13. Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

    Science.gov (United States)

    Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

    2018-05-02

    The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

  14. Basic disturbances of information processing in psychosis prediction.

    Science.gov (United States)

    Bodatsch, Mitja; Klosterkötter, Joachim; Müller, Ralf; Ruhrmann, Stephan

    2013-01-01

    The basic symptoms (BS) approach provides a valid instrument in predicting psychosis onset and represents moreover a significant heuristic framework for research. The term "basic symptoms" denotes subtle changes of cognition and perception in the earliest and prodromal stages of psychosis development. BS are thought to correspond to disturbances of neural information processing. Following the heuristic implications of the BS approach, the present paper aims at exploring disturbances of information processing, revealed by functional magnetic resonance imaging (fMRI) and electro-encephalographic as characteristics of the at-risk state of psychosis. Furthermore, since high-risk studies employing ultra-high-risk criteria revealed non-conversion rates commonly exceeding 50%, thus warranting approaches that increase specificity, the potential contribution of neural information processing disturbances to psychosis prediction is reviewed. In summary, the at-risk state seems to be associated with information processing disturbances. Moreover, fMRI investigations suggested that disturbances of language processing domains might be a characteristic of the prodromal state. Neurophysiological studies revealed that disturbances of sensory processing may assist psychosis prediction in allowing for a quantification of risk in terms of magnitude and time. The latter finding represents a significant advancement since an estimation of the time to event has not yet been achieved by clinical approaches. Some evidence suggests a close relationship between self-experienced BS and neural information processing. With regard to future research, the relationship between neural information processing disturbances and different clinical risk concepts warrants further investigations. Thereby, a possible time sequence in the prodromal phase might be of particular interest.

  15. Predicting Genes Involved in Human Cancer Using Network Contextual Information

    Directory of Open Access Journals (Sweden)

    Rahmani Hossein

    2012-03-01

    Full Text Available Protein-Protein Interaction (PPI networks have been widely used for the task of predicting proteins involved in cancer. Previous research has shown that functional information about the protein for which a prediction is made, proximity to specific other proteins in the PPI network, as well as local network structure are informative features in this respect. In this work, we introduce two new types of input features, reflecting additional information: (1 Functional Context: the functions of proteins interacting with the target protein (rather than the protein itself; and (2 Structural Context: the relative position of the target protein with respect to specific other proteins selected according to a novel ANOVA (analysis of variance based measure. We also introduce a selection strategy to pinpoint the most informative features. Results show that the proposed feature types and feature selection strategy yield informative features. A standard machine learning method (Naive Bayes that uses the features proposed here outperforms the current state-of-the-art methods by more than 5% with respect to F-measure. In addition, manual inspection confirms the biological relevance of the top-ranked features.

  16. Curiosity and reward: Valence predicts choice and information prediction errors enhance learning.

    Science.gov (United States)

    Marvin, Caroline B; Shohamy, Daphna

    2016-03-01

    Curiosity drives many of our daily pursuits and interactions; yet, we know surprisingly little about how it works. Here, we harness an idea implied in many conceptualizations of curiosity: that information has value in and of itself. Reframing curiosity as the motivation to obtain reward-where the reward is information-allows one to leverage major advances in theoretical and computational mechanisms of reward-motivated learning. We provide new evidence supporting 2 predictions that emerge from this framework. First, we find an asymmetric effect of positive versus negative information, with positive information enhancing both curiosity and long-term memory for information. Second, we find that it is not the absolute value of information that drives learning but, rather, the gap between the reward expected and reward received, an "information prediction error." These results support the idea that information functions as a reward, much like money or food, guiding choices and driving learning in systematic ways. (c) 2016 APA, all rights reserved).

  17. Drug-target interaction prediction from PSSM based evolutionary information.

    Science.gov (United States)

    Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-01-01

    The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Reduced Predictable Information in Brain Signals in Autism Spectrum Disorder

    Directory of Open Access Journals (Sweden)

    Carlos eGomez

    2014-02-01

    Full Text Available Autism spectrum disorder (ASD is a common developmental disorder characterized by communication difficulties and impaired social interaction. Recent results suggest altered brain dynamics as a potential cause of symptoms in ASD. Here, we aim to describe potential information-processing consequences of these alterations by measuring active information storage (AIS – a key quantity in the theory of distributed computation in biological networks. AIS is defined as the mutual information between the semi-infinite past of a process and its next state. It measures the amount of stored information that is used for computation of the next time step of a process. AIS is high for rich but predictable dynamics. We recorded magnetoencephalography (MEG signals in 13 ASD patients and 14 matched control subjects in a visual task. After a beamformer source analysis, twelve task-relevant sources were obtained. For these sources, stationary baseline activity was analyzed using AIS. Our results showed a decrease of AIS values in the hippocampus of ASD patients in comparison with controls, meaning that brain signals in ASD were either less predictable, reduced in their dynamic richness or both. Our study suggests the usefulness of AIS to detect an abnormal type of dynamics in ASD. The observed changes in AIS are compatible with Bayesian theories of reduced use or precision of priors in ASD.

  19. System for prediction of environmental emergency dose information

    International Nuclear Information System (INIS)

    Moriuchi, Shigeru

    1989-01-01

    According to the national research program revised by the Japan Nuclear Safety Commission after the TMI-2 reactor accident JAERI started the development of a computer code system for the real-time prediction of environmental consequences following a nuclear reactor accident, and in 1985 the basic development of the System for Prediction of Environmental Emergency Dose Information SPEEDI was completed. The system consists of three-dimensional models of wind field calculation (WIND04), dispersion calculation (PRWDA) and internal and external dose calculation (CIDE), and is designed to speedily predict radioactive concentration in the air, the ground deposition and radiation doses of upto 100 km range by simulation calculation when the radioactive materials are accidentally released from a reactor. At Chernobyl accident the calculational domain of SPEEDI were extended tentatively upto 2000 km, and simulation calculations of the movement of radioactive cloud were executed, and the estimation of the amounts of released radioactivities were made using calculated results and observed data. The calculated distribution and the movement of plume well agreed with the distribution patterns evaluated from observation data, and the estimated source term agreed approximately with data reported from USSR and other countries. (author)

  20. System for prediction of environmental emergency dose information network system

    International Nuclear Information System (INIS)

    Misawa, Makoto; Nagamori, Fumio

    2009-01-01

    In cases when an accident happens to arise with some risk for emission of a large amount radioactivity from the nuclear facilities, the environmental emergency due to this accident should be predicted rapidly and be informed immediately. The SPEEDI network system for such purpose was completed and now operated by Nuclear Safety Technology Center (NUSTEC) commissioned to do by Ministry of Education, Culture, Sports, Science and Technology, Japan. Fujitsu has been contributing to this project by developing the principal parts of the network performance, by introducing necessary servers, and also by keeping the network in good condition, such as with construction of the system followed by continuous operation and maintenance of the system. Real-time prediction of atmospheric diffusion of radionuclides for nuclear accidents in the world is now available with experimental verification for the real-time emergency response system. Improvement of worldwide version of the SPEEDI network system, accidental discharge of radionuclides with the function of simultaneous prediction for multiple domains and its evaluation is possible. (S. Ohno)

  1. A comparison of SAR ATR performance with information theoretic predictions

    Science.gov (United States)

    Blacknell, David

    2003-09-01

    Performance assessment of automatic target detection and recognition algorithms for SAR systems (or indeed any other sensors) is essential if the military utility of the system / algorithm mix is to be quantified. This is a relatively straightforward task if extensive trials data from an existing system is used. However, a crucial requirement is to assess the potential performance of novel systems as a guide to procurement decisions. This task is no longer straightforward since a hypothetical system cannot provide experimental trials data. QinetiQ has previously developed a theoretical technique for classification algorithm performance assessment based on information theory. The purpose of the study presented here has been to validate this approach. To this end, experimental SAR imagery of targets has been collected using the QinetiQ Enhanced Surveillance Radar to allow algorithm performance assessments as a number of parameters are varied. In particular, performance comparisons can be made for (i) resolutions up to 0.1m, (ii) single channel versus polarimetric (iii) targets in the open versus targets in scrubland and (iv) use versus non-use of camouflage. The change in performance as these parameters are varied has been quantified from the experimental imagery whilst the information theoretic approach has been used to predict the expected variation of performance with parameter value. A comparison of these measured and predicted assessments has revealed the strengths and weaknesses of the theoretical technique as will be discussed in the paper.

  2. Information trimming: Sufficient statistics, mutual information, and predictability from effective channel states

    Science.gov (United States)

    James, Ryan G.; Mahoney, John R.; Crutchfield, James P.

    2017-06-01

    One of the most basic characterizations of the relationship between two random variables, X and Y , is the value of their mutual information. Unfortunately, calculating it analytically and estimating it empirically are often stymied by the extremely large dimension of the variables. One might hope to replace such a high-dimensional variable by a smaller one that preserves its relationship with the other. It is well known that either X (or Y ) can be replaced by its minimal sufficient statistic about Y (or X ) while preserving the mutual information. While intuitively reasonable, it is not obvious or straightforward that both variables can be replaced simultaneously. We demonstrate that this is in fact possible: the information X 's minimal sufficient statistic preserves about Y is exactly the information that Y 's minimal sufficient statistic preserves about X . We call this procedure information trimming. As an important corollary, we consider the case where one variable is a stochastic process' past and the other its future. In this case, the mutual information is the channel transmission rate between the channel's effective states. That is, the past-future mutual information (the excess entropy) is the amount of information about the future that can be predicted using the past. Translating our result about minimal sufficient statistics, this is equivalent to the mutual information between the forward- and reverse-time causal states of computational mechanics. We close by discussing multivariate extensions to this use of minimal sufficient statistics.

  3. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-05-25

    The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

  4. Learning Predictive Interactions Using Information Gain and Bayesian Network Scoring.

    Directory of Open Access Journals (Sweden)

    Xia Jiang

    Full Text Available The problems of correlation and classification are long-standing in the fields of statistics and machine learning, and techniques have been developed to address these problems. We are now in the era of high-dimensional data, which is data that can concern billions of variables. These data present new challenges. In particular, it is difficult to discover predictive variables, when each variable has little marginal effect. An example concerns Genome-wide Association Studies (GWAS datasets, which involve millions of single nucleotide polymorphism (SNPs, where some of the SNPs interact epistatically to affect disease status. Towards determining these interacting SNPs, researchers developed techniques that addressed this specific problem. However, the problem is more general, and so these techniques are applicable to other problems concerning interactions. A difficulty with many of these techniques is that they do not distinguish whether a learned interaction is actually an interaction or whether it involves several variables with strong marginal effects.We address this problem using information gain and Bayesian network scoring. First, we identify candidate interactions by determining whether together variables provide more information than they do separately. Then we use Bayesian network scoring to see if a candidate interaction really is a likely model. Our strategy is called MBS-IGain. Using 100 simulated datasets and a real GWAS Alzheimer's dataset, we investigated the performance of MBS-IGain.When analyzing the simulated datasets, MBS-IGain substantially out-performed nine previous methods at locating interacting predictors, and at identifying interactions exactly. When analyzing the real Alzheimer's dataset, we obtained new results and results that substantiated previous findings. We conclude that MBS-IGain is highly effective at finding interactions in high-dimensional datasets. This result is significant because we have increasingly

  5. Loy Yang A - Australia's largest privatisation

    International Nuclear Information System (INIS)

    Yenckin, C.

    1997-01-01

    The recent A$4,746 million privatisation of the 2000MW Loy Yang A power station and the Loy Yang coal mine by the Victorian Government is Australia's largest privatisation and one of 1997's largest project financing deals. (author)

  6. Synchrotron Emission on the Largest Scales: Radio Detection of the ...

    Indian Academy of Sciences (India)

    Abstract. Shocks and turbulence generated during large-scale structure formation are predicted to produce large-scale, low surface-brightness synchrotron emission. On the largest scales, this emission is globally correlated with the thermal baryon distribution, and constitutes the 'syn- chrotron cosmic-web'. I present the ...

  7. broken magnet highlights largest collider's engineering challenges

    CERN Multimedia

    Inman, Mason

    2007-01-01

    "Even at the world's soon-to-be largest particle accelerator - a device that promises to push the boundaries of physics - scientists need to be mindful of one of the most fundamental laws in the universe: Murphy's Law. (2 pages)

  8. Predictive information processing in music cognition. A critical review.

    Science.gov (United States)

    Rohrmeier, Martin A; Koelsch, Stefan

    2012-02-01

    Expectation and prediction constitute central mechanisms in the perception and cognition of music, which have been explored in theoretical and empirical accounts. We review the scope and limits of theoretical accounts of musical prediction with respect to feature-based and temporal prediction. While the concept of prediction is unproblematic for basic single-stream features such as melody, it is not straight-forward for polyphonic structures or higher-order features such as formal predictions. Behavioural results based on explicit and implicit (priming) paradigms provide evidence of priming in various domains that may reflect predictive behaviour. Computational learning models, including symbolic (fragment-based), probabilistic/graphical, or connectionist approaches, provide well-specified predictive models of specific features and feature combinations. While models match some experimental results, full-fledged music prediction cannot yet be modelled. Neuroscientific results regarding the early right-anterior negativity (ERAN) and mismatch negativity (MMN) reflect expectancy violations on different levels of processing complexity, and provide some neural evidence for different predictive mechanisms. At present, the combinations of neural and computational modelling methodologies are at early stages and require further research. Copyright © 2012 Elsevier B.V. All rights reserved.

  9. Adult age differences in predicting memory performance: the effects of normative information and task experience.

    Science.gov (United States)

    McDonald-Miszczak, L; Hunter, M A; Hultsch, D F

    1994-03-01

    Two experiments addressed the effects of task information and experience on younger and older adults' ability to predict their memory for words. The first study examined the effects of normative task information on subjects' predictions for 30-word lists across three trials. The second study looked at the effects of making predictions and recalling either an easy (15) or a difficult (45) word list prior to making predictions and recalling a moderately difficult (30) word list. The results from both studies showed that task information and experience affected subjects' predictions and that elderly adults predicted their performance more accurately than younger adults.

  10. An Information Theory Account of Preference Prediction Accuracy

    NARCIS (Netherlands)

    Pollmann, Monique; Scheibehenne, Benjamin

    2015-01-01

    Knowledge about other people's preferences is essential for successful social interactions, but what exactly are the driving factors that determine how well we can predict the likes and dislikes of people around us? To investigate the accuracy of couples’ preference predictions we outline and

  11. THE CHALLENGE OF THE LARGEST STRUCTURES IN THE UNIVERSE TO COSMOLOGY

    International Nuclear Information System (INIS)

    Park, Changbom; Choi, Yun-Young; Kim, Sungsoo S.; Kim, Kap-Sung; Kim, Juhan; Gott III, J. Richard

    2012-01-01

    Large galaxy redshift surveys have long been used to constrain cosmological models and structure formation scenarios. In particular, the largest structures discovered observationally are thought to carry critical information on the amplitude of large-scale density fluctuations or homogeneity of the universe, and have often challenged the standard cosmological framework. The Sloan Great Wall (SGW) recently found in the Sloan Digital Sky Survey (SDSS) region casts doubt on the concordance cosmological model with a cosmological constant (i.e., the flat ΛCDM model). Here we show that the existence of the SGW is perfectly consistent with the ΛCDM model, a result that only our very large cosmological N-body simulation (the Horizon Run 2, HR2) could supply. In addition, we report on the discovery of a void complex in the SDSS much larger than the SGW, and show that such size of the largest void is also predicted in the ΛCDM paradigm. Our results demonstrate that an initially homogeneous isotropic universe with primordial Gaussian random phase density fluctuations growing in accordance with the general relativity can explain the richness and size of the observed large-scale structures in the SDSS. Using the HR2 simulation we predict that a future galaxy redshift survey about four times deeper or with 3 mag fainter limit than the SDSS should reveal a largest structure of bright galaxies about twice as big as the SGW.

  12. Using the information on cosmic rays to predict influenza epidemics

    International Nuclear Information System (INIS)

    Yu, Z.D.

    1985-01-01

    A correlation between the incidence of influenza pandemics and increased cosmic ray activity is made. A correlation is also made between the occurrence of these pandemics and the appearance of bright novae, e.g., Nova Eta Car. Four indices based on increased cosmic ray activity and novae are proposed to predict future influenza pandemics and viral antigenic shifts

  13. Predicting recoveries and the importance of using enough information

    NARCIS (Netherlands)

    Cai, X.; den Haan, W.

    2009-01-01

    Several papers that make forecasts about the long-term impact of the current financial crisis rely on models in which there is only one type of financial crisis. These models tend to predict that the current crisis will have long lasting negative effects on economic growth. This paper points out the

  14. CERN tests largest superconducting solenoid magnet

    CERN Multimedia

    2006-01-01

    "CERN's Compacts Muon Solenoid (CMS) - the world's largest superconducting solenoid magnet - has reached full field in testing. The instrument is part of the proton-proton Large Hadron Collider (LHC) project, located in a giant subterranean chamber at Cessy on the Franco-Swiss border." (1 page)

  15. Information Fusion for High Level Situation Assessment and Prediction

    National Research Council Canada - National Science Library

    Ji, Qiang

    2007-01-01

    .... In addition, we developed algorithms for performing active information fusion to improve both fusion accuracy and efficiency so that decision making and situation assessment can be made in a timely and efficient manner...

  16. Predicting Atomic Decay Rates Using an Informational-Entropic Approach

    Science.gov (United States)

    Gleiser, Marcelo; Jiang, Nan

    2018-06-01

    We show that a newly proposed Shannon-like entropic measure of shape complexity applicable to spatially-localized or periodic mathematical functions known as configurational entropy (CE) can be used as a predictor of spontaneous decay rates for one-electron atoms. The CE is constructed from the Fourier transform of the atomic probability density. For the hydrogen atom with degenerate states labeled with the principal quantum number n, we obtain a scaling law relating the n-averaged decay rates to the respective CE. The scaling law allows us to predict the n-averaged decay rate without relying on the traditional computation of dipole matrix elements. We tested the predictive power of our approach up to n = 20, obtaining an accuracy better than 3.7% within our numerical precision, as compared to spontaneous decay tables listed in the literature.

  17. The prediction of swimming performance in competition from behavioral information.

    Science.gov (United States)

    Rushall, B S; Leet, D

    1979-06-01

    The swimming performances of the Canadian Team at the 1976 Olympic Games were categorized as being improved or worse than previous best times in the events contested. The two groups had been previously assessed on the Psychological Inventories for Competitive Swimmers. A stepwise multiple-discriminant analysis of the inventory responses revealed that 13 test questions produced a perfect discrimination of group membership. The resultant discriminant functions for predicting performance classification were applied to the test responses of 157 swimmers at the 1977 Canadian Winter National Swimming Championships. Using the same performance classification criteria the accuracy of prediction was not better than chance in three of four sex by performance classifications. This yielded a failure to locate a set of behavioral factors which determine swimming performance improvements in elite competitive circumstances. The possibility of sets of factors which do not discriminate between performances in similar environments or between similar groups of swimmers was raised.

  18. Predicting Atomic Decay Rates Using an Informational-Entropic Approach

    Science.gov (United States)

    Gleiser, Marcelo; Jiang, Nan

    2018-02-01

    We show that a newly proposed Shannon-like entropic measure of shape complexity applicable to spatially-localized or periodic mathematical functions known as configurational entropy (CE) can be used as a predictor of spontaneous decay rates for one-electron atoms. The CE is constructed from the Fourier transform of the atomic probability density. For the hydrogen atom with degenerate states labeled with the principal quantum number n, we obtain a scaling law relating the n-averaged decay rates to the respective CE. The scaling law allows us to predict the n-averaged decay rate without relying on the traditional computation of dipole matrix elements. We tested the predictive power of our approach up to n = 20, obtaining an accuracy better than 3.7% within our numerical precision, as compared to spontaneous decay tables listed in the literature.

  19. Predictable information in neural signals during resting state is reduced in autism spectrum disorder.

    Science.gov (United States)

    Brodski-Guerniero, Alla; Naumer, Marcus J; Moliadze, Vera; Chan, Jason; Althen, Heike; Ferreira-Santos, Fernando; Lizier, Joseph T; Schlitt, Sabine; Kitzerow, Janina; Schütz, Magdalena; Langer, Anne; Kaiser, Jochen; Freitag, Christine M; Wibral, Michael

    2018-04-04

    The neurophysiological underpinnings of the nonsocial symptoms of autism spectrum disorder (ASD) which include sensory and perceptual atypicalities remain poorly understood. Well-known accounts of less dominant top-down influences and more dominant bottom-up processes compete to explain these characteristics. These accounts have been recently embedded in the popular framework of predictive coding theory. To differentiate between competing accounts, we studied altered information dynamics in ASD by quantifying predictable information in neural signals. Predictable information in neural signals measures the amount of stored information that is used for the next time step of a neural process. Thus, predictable information limits the (prior) information which might be available for other brain areas, for example, to build predictions for upcoming sensory information. We studied predictable information in neural signals based on resting-state magnetoencephalography (MEG) recordings of 19 ASD patients and 19 neurotypical controls aged between 14 and 27 years. Using whole-brain beamformer source analysis, we found reduced predictable information in ASD patients across the whole brain, but in particular in posterior regions of the default mode network. In these regions, epoch-by-epoch predictable information was positively correlated with source power in the alpha and beta frequency range as well as autocorrelation decay time. Predictable information in precuneus and cerebellum was negatively associated with nonsocial symptom severity, indicating a relevance of the analysis of predictable information for clinical research in ASD. Our findings are compatible with the assumption that use or precision of prior knowledge is reduced in ASD patients. © 2018 Wiley Periodicals, Inc.

  20. Evaluating and Predicting Patient Safety for Medical Devices With Integral Information Technology

    Science.gov (United States)

    2005-01-01

    323 Evaluating and Predicting Patient Safety for Medical Devices with Integral Information Technology Jiajie Zhang, Vimla L. Patel, Todd R...errors are due to inappropriate designs for user interactions, rather than mechanical failures. Evaluating and predicting patient safety in medical ...the users on the identified trouble spots in the devices. We developed two methods for evaluating and predicting patient safety in medical devices

  1. Early Prediction of Student Dropout and Performance in MOOCSs Using Higher Granularity Temporal Information

    Science.gov (United States)

    Ye, Cheng; Biswas, Gautam

    2014-01-01

    Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…

  2. Wireless digital information transfer : Modelling, prediction and assessment

    NARCIS (Netherlands)

    Lager, I.E.; De Hoop, A.T.; Kikkawa, T.

    2013-01-01

    The loop-to-loop pulsed electromagnetic field wireless signal transfer is investigated with a view on its application in wireless digital information transfer. Closed-form expressions are derived for the emitted magnetic field and for the open-circuit voltage of the receiving loop in dependence on

  3. Prediction from partial information and hindsight, an alternative proof

    Czech Academy of Sciences Publication Activity Database

    Smal, A.V.; Talebanfard, Navid

    2018-01-01

    Roč. 136, August (2018), s. 102-104 ISSN 0020-0190 EU Projects: European Commission(XE) 339691 - FEALORA Institutional support: RVO:67985840 Keywords : certificate complexity * circuit complexity * computational complexity Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.748, year: 2016 https://www.sciencedirect.com/science/article/pii/S0020019018300917?via%3Dihub

  4. Effects of historical and predictive information on ability of transport pilot to predict an alert

    Science.gov (United States)

    Trujillo, Anna C.

    1994-01-01

    In the aviation community, the early detection of the development of a possible subsystem problem during a flight is potentially useful for increasing the safety of the flight. Commercial airlines are currently using twin-engine aircraft for extended transport operations over water, and the early detection of a possible problem might increase the flight crew's options for safely landing the aircraft. One method for decreasing the severity of a developing problem is to predict the behavior of the problem so that appropriate corrective actions can be taken. To investigate the pilots' ability to predict long-term events, a computer workstation experiment was conducted in which 18 airline pilots predicted the alert time (the time to an alert) using 3 different dial displays and 3 different parameter behavior complexity levels. The three dial displays were as follows: standard (resembling current aircraft round dial presentations); history (indicating the current value plus the value of the parameter 5 sec in the past); and predictive (indicating the current value plus the value of the parameter 5 sec into the future). The time profiles describing the behavior of the parameter consisted of constant rate-of-change profiles, decelerating profiles, and accelerating-then-decelerating profiles. Although the pilots indicated that they preferred the near term predictive dial, the objective data did not support its use. The objective data did show that the time profiles had the most significant effect on performance in estimating the time to an alert.

  5. GIS learning tool for world's largest earthquakes and their causes

    Science.gov (United States)

    Chatterjee, Moumita

    The objective of this thesis is to increase awareness about earthquakes among people, especially young students by showing the five largest and two most predictable earthquake locations in the world and their plate tectonic settings. This is a geographic based interactive tool which could be used for learning about the cause of great earthquakes in the past and the safest places on the earth in order to avoid direct effect of earthquakes. This approach provides an effective way of learning for the students as it is very user friendly and more aligned to the interests of the younger generation. In this tool the user can click on the various points located on the world map which will open a picture and link to the webpage for that point, showing detailed information of the earthquake history of that place including magnitude of quake, year of past quakes and the plate tectonic settings that made this place earthquake prone. Apart from knowing the earthquake related information students will also be able to customize the tool to suit their needs or interests. Students will be able to add/remove layers, measure distance between any two points on the map, select any place on the map and know more information for that place, create a layer from this set to do a detail analysis, run a query, change display settings, etc. At the end of this tool the user has to go through the earthquake safely guidelines in order to be safe during an earthquake. This tool uses Java as programming language and uses Map Objects Java Edition (MOJO) provided by ESRI. This tool is developed for educational purpose and hence its interface has been kept simple and easy to use so that students can gain maximum knowledge through it instead of having a hard time to install it. There are lots of details to explore which can help more about what a GIS based tool is capable of. Only thing needed to run this tool is latest JAVA edition installed in their machine. This approach makes study more fun and

  6. Risk-informed prediction of feeder end of life

    International Nuclear Information System (INIS)

    Jyrkama, M.; Pandey, M.

    2011-01-01

    The operating life of feeder piping is negatively impacted by flow accelerated corrosion (FAC). In this study, an assessment of a large set of inspection data reveals that FAC in feeders is a relatively stationary process, with variability only at the local scale. Given the added uncertainty from inspection coverage, a new method for estimating the thinning rate and feeder EOL is developed using a probabilistic approach. The results of the study illustrate the benefits of the methodology in supporting risk-informed decision making at the station by quantifying the present and incremental risk in the feeder system over time. (author)

  7. Risk-informed prediction of feeder end of life

    Energy Technology Data Exchange (ETDEWEB)

    Jyrkama, M.; Pandey, M. [Univ. of Waterloo, Ontario (Canada)

    2011-07-01

    The operating life of feeder piping is negatively impacted by flow accelerated corrosion (FAC). In this study, an assessment of a large set of inspection data reveals that FAC in feeders is a relatively stationary process, with variability only at the local scale. Given the added uncertainty from inspection coverage, a new method for estimating the thinning rate and feeder EOL is developed using a probabilistic approach. The results of the study illustrate the benefits of the methodology in supporting risk-informed decision making at the station by quantifying the present and incremental risk in the feeder system over time. (author)

  8. Predicting Biological Information Flow in a Model Oxygen Minimum Zone

    Science.gov (United States)

    Louca, S.; Hawley, A. K.; Katsev, S.; Beltran, M. T.; Bhatia, M. P.; Michiels, C.; Capelle, D.; Lavik, G.; Doebeli, M.; Crowe, S.; Hallam, S. J.

    2016-02-01

    Microbial activity drives marine biochemical fluxes and nutrient cycling at global scales. Geochemical measurements as well as molecular techniques such as metagenomics, metatranscriptomics and metaproteomics provide great insight into microbial activity. However, an integration of molecular and geochemical data into mechanistic biogeochemical models is still lacking. Recent work suggests that microbial metabolic pathways are, at the ecosystem level, strongly shaped by stoichiometric and energetic constraints. Hence, models rooted in fluxes of matter and energy may yield a holistic understanding of biogeochemistry. Furthermore, such pathway-centric models would allow a direct consolidation with meta'omic data. Here we present a pathway-centric biogeochemical model for the seasonal oxygen minimum zone in Saanich Inlet, a fjord off the coast of Vancouver Island. The model considers key dissimilatory nitrogen and sulfur fluxes, as well as the population dynamics of the genes that mediate them. By assuming a direct translation of biocatalyzed energy fluxes to biosynthesis rates, we make predictions about the distribution and activity of the corresponding genes. A comparison of the model to molecular measurements indicates that the model explains observed DNA, RNA, protein and cell depth profiles. This suggests that microbial activity in marine ecosystems such as oxygen minimum zones is well described by DNA abundance, which, in conjunction with geochemical constraints, determines pathway expression and process rates. Our work further demonstrates how meta'omic data can be mechanistically linked to environmental redox conditions and biogeochemical processes.

  9. Predicting interactions from mechanistic information: Can omic data validate theories?

    International Nuclear Information System (INIS)

    Borgert, Christopher J.

    2007-01-01

    To address the most pressing and relevant issues for improving mixture risk assessment, researchers must first recognize that risk assessment is driven by both regulatory requirements and scientific research, and that regulatory concerns may expand beyond the purely scientific interests of researchers. Concepts of 'mode of action' and 'mechanism of action' are used in particular ways within the regulatory arena, depending on the specific assessment goals. The data requirements for delineating a mode of action and predicting interactive toxicity in mixtures are not well defined from a scientific standpoint due largely to inherent difficulties in testing certain underlying assumptions. Understanding the regulatory perspective on mechanistic concepts will be important for designing experiments that can be interpreted clearly and applied in risk assessments without undue reliance on extrapolation and assumption. In like fashion, regulators and risk assessors can be better equipped to apply mechanistic data if the concepts underlying mechanistic research and the limitations that must be placed on interpretation of mechanistic data are understood. This will be critically important for applying new technologies to risk assessment, such as functional genomics, proteomics, and metabolomics. It will be essential not only for risk assessors to become conversant with the language and concepts of mechanistic research, including new omic technologies, but also, for researchers to become more intimately familiar with the challenges and needs of risk assessment

  10. Mean Velocity Prediction Information Feedback Strategy in Two-Route Systems under ATIS

    Directory of Open Access Journals (Sweden)

    Jianqiang Wang

    2015-02-01

    Full Text Available Feedback contents of previous information feedback strategies in advanced traveler information systems are almost real-time traffic information. Compared with real-time information, prediction traffic information obtained by a reliable and effective prediction algorithm has many undisputable advantages. In prediction information environment, a traveler is prone to making a more rational route-choice. For these considerations, a mean velocity prediction information feedback strategy (MVPFS is presented. The approach adopts the autoregressive-integrated moving average model (ARIMA to forecast short-term traffic flow. Furthermore, prediction results of mean velocity are taken as feedback contents and displayed on a variable message sign to guide travelers' route-choice. Meanwhile, discrete choice model (Logit model is selected to imitate more appropriately travelers' route-choice behavior. In order to investigate the performance of MVPFS, a cellular automaton model with ARIMA is adopted to simulate a two-route scenario. The simulation shows that such innovative prediction feedback strategy is feasible and efficient. Even more importantly, this study demonstrates the excellence of prediction feedback ideology.

  11. Crash testing the largest experiment on Earth

    OpenAIRE

    Cauchi, Marija

    2015-01-01

    Under Europe lies a 27 km tunnel that is both the coldest and hottest place on Earth. The Large Hadron Collider (LHC) has already found out what gives mass to all the matter in the Universe. It is now trying to go even deeper into what makes up everything we see around us. Dr Marija Cauchi writes about her research that helped protect this atom smasher from itself. Photography by Jean Claude Vancell. http://www.um.edu.mt/think/crash-testing-the-largest-experiment-on-earth/

  12. Cognitive Factors in Predicting Continued Use of Information Systems with Technology Adoption Models

    Science.gov (United States)

    Huang, Chi-Cheng

    2017-01-01

    Introduction: The ultimate viability of an information system is dependent on individuals' continued use of the information system. In this study, we use the technology acceptance model and the theory of interpersonal behaviour to predict continued use of information systems. Method: We established a Web questionnaire on the mySurvey Website and…

  13. The world's largest LNG producer's next market

    International Nuclear Information System (INIS)

    Fuller, R.; Isworo Suharno; Simandjuntak, W.M.P.

    1996-01-01

    The development of the domestic gas market in Indonesia, the world's largest liquefied natural gas producing country, is described as part of the overall impact of the country's oil and gas production. The first large scale use of natural gas in Indonesia was established in 1968 when a fertiliser plant using gas as the feedstock was built. Ultimately, through increased yields, this has enabled Indonesia to be self-sufficient in rice and an exporter of fertiliser. Problems which stand in the way of further developments include: capital, though Pertamina and PGN are perceived as attractive for foreign investment; the lack of a regulatory framework for gas; geographical constraints, among them the fact that the gas deposits are remote from the largest population concentrations; lack of infrastructure. There are nevertheless plans for expansion and the provision of an integrated gas pipeline system. Pertamina, which has responsibility for all oil and gas developments, and PGN, whose primary role has been as a manufacturer and distributor of gas, are now working together in the coordination of all gas activities. (10 figures). (UK)

  14. Information system of rice planting calendar based on ten-day (Dasarian) rainfall prediction

    International Nuclear Information System (INIS)

    Susandi, Armi; Tamamadin, Mamad; Djamal, Erizal; Las, Irsal

    2015-01-01

    This paper describes information system of rice planting calendar to help farmers in determining the time for rice planting. The information includes rainfall prediction in ten days (dasarian) scale overlaid to map of rice field to produce map of rice planting in village level. The rainfall prediction was produced by stochastic modeling using Fast Fourier Transform (FFT) and Non-Linier Least Squares methods to fit the curve of function to the rainfall data. In this research, the Fourier series has been modified become non-linear function to follow the recent characteristics of rainfall that is non stationary. The results have been also validated in 4 steps, including R-Square, RMSE, R-Skill, and comparison with field data. The development of information system (cyber extension) provides information such as rainfall prediction, prediction of the planting time, and interactive space for farmers to respond to the information submitted. Interfaces for interactive response will be critical to the improvement of prediction accuracy of information, both rainfall and planting time. The method used to get this information system includes mapping on rice planting prediction, converting the format file, developing database system, developing website, and posting website. Because of this map was overlaid with the Google map, the map files must be converted to the .kml file format

  15. Adaptive plasticity in speech perception: Effects of external information and internal predictions.

    Science.gov (United States)

    Guediche, Sara; Fiez, Julie A; Holt, Lori L

    2016-07-01

    When listeners encounter speech under adverse listening conditions, adaptive adjustments in perception can improve comprehension over time. In some cases, these adaptive changes require the presence of external information that disambiguates the distorted speech signals, whereas in other cases mere exposure is sufficient. Both external (e.g., written feedback) and internal (e.g., prior word knowledge) sources of information can be used to generate predictions about the correct mapping of a distorted speech signal. We hypothesize that these predictions provide a basis for determining the discrepancy between the expected and actual speech signal that can be used to guide adaptive changes in perception. This study provides the first empirical investigation that manipulates external and internal factors through (a) the availability of explicit external disambiguating information via the presence or absence of postresponse orthographic information paired with a repetition of the degraded stimulus, and (b) the accuracy of internally generated predictions; an acoustic distortion is introduced either abruptly or incrementally. The results demonstrate that the impact of external information on adaptive plasticity is contingent upon whether the intelligibility of the stimuli permits accurate internally generated predictions during exposure. External information sources enhance adaptive plasticity only when input signals are severely degraded and cannot reliably access internal predictions. This is consistent with a computational framework for adaptive plasticity in which error-driven supervised learning relies on the ability to compute sensory prediction error signals from both internal and external sources of information. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  16. Information system of rice planting calendar based on ten-day (Dasarian) rainfall prediction

    Energy Technology Data Exchange (ETDEWEB)

    Susandi, Armi, E-mail: armi@meteo.itb.ac.id [Department of Meteorology, Institut Teknologi Bandung, Labtek XI Building floor 1, Jalan Ganesa 10 Bandung 40132 (Indonesia); Tamamadin, Mamad, E-mail: mamadtama@meteo.itb.ac.id [Laboratory of Applied Meteorology, Institut Teknologi Bandung Ged. Labtek XI lt. 1, Jalan Ganesa 10 Bandung 40132 (Indonesia); Djamal, Erizal, E-mail: erizal-jamal@yahoo.com [Center for Agricultural Technology Transfer Management, Ministry of Agriculture Jl. Salak No. 22 Bogor (Indonesia); Las, Irsal, E-mail: irsallas@yahoo.com [Indonesian Agroclimate and Hydrology Research Institute, Ministry of Agriculture Jl. Tentara Pelajar 1a Bogor 16111 (Indonesia)

    2015-09-30

    This paper describes information system of rice planting calendar to help farmers in determining the time for rice planting. The information includes rainfall prediction in ten days (dasarian) scale overlaid to map of rice field to produce map of rice planting in village level. The rainfall prediction was produced by stochastic modeling using Fast Fourier Transform (FFT) and Non-Linier Least Squares methods to fit the curve of function to the rainfall data. In this research, the Fourier series has been modified become non-linear function to follow the recent characteristics of rainfall that is non stationary. The results have been also validated in 4 steps, including R-Square, RMSE, R-Skill, and comparison with field data. The development of information system (cyber extension) provides information such as rainfall prediction, prediction of the planting time, and interactive space for farmers to respond to the information submitted. Interfaces for interactive response will be critical to the improvement of prediction accuracy of information, both rainfall and planting time. The method used to get this information system includes mapping on rice planting prediction, converting the format file, developing database system, developing website, and posting website. Because of this map was overlaid with the Google map, the map files must be converted to the .kml file format.

  17. Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

    Science.gov (United States)

    Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

    2013-01-27

    A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

  18. Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility

    NARCIS (Netherlands)

    C. Cakmakli (Cem); D.J.C. van Dijk (Dick)

    2010-01-01

    textabstractThis paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that

  19. Getting the most out of macroeconomic information for predicting stock returns and volatility

    NARCIS (Netherlands)

    Cakmakli, C.; van Dijk, D.

    2011-01-01

    This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only include

  20. A rule-based backchannel prediction model using pitch and pause information

    NARCIS (Netherlands)

    Truong, Khiet Phuong; Poppe, Ronald Walter; Heylen, Dirk K.J.

    We manually designed rules for a backchannel (BC) prediction model based on pitch and pause information. In short, the model predicts a BC when there is a pause of a certain length that is preceded by a falling or rising pitch. This model was validated against the Dutch IFADV Corpus in a

  1. Vertical structure of predictability and information transport over the Northern Hemisphere

    International Nuclear Information System (INIS)

    Feng Ai-Xia; Wang Qi-Gang; Gong Zhi-Qiang; Feng Guo-Lin

    2014-01-01

    Based on nonlinear prediction and information theory, vertical heterogeneity of predictability and information loss rate in geopotential height field are obtained over the Northern Hemisphere. On a seasonal-to-interannual time scale, the predictability is low in the lower troposphere and high in the mid-upper troposphere. However, within mid-upper troposphere over the subtropics ocean area, there is a relatively poor predictability. These conclusions also fit the seasonal time scale. Moving to the interannual time scale, the predictability becomes high in the lower troposphere and low in the mid-upper troposphere, contrary to the former case. On the whole the interannual trend is more predictable than the seasonal trend. The average information loss rate is low over the mid-east Pacific, west of North America, Atlantic and Eurasia, and the atmosphere over other places has a relatively high information loss rate on all-time scales. Two channels are found steadily over the Pacific Ocean and Atlantic Ocean in subtropics. There are also unstable channels. The four-season influence on predictability and information communication are studied. The predictability is low, no matter which season data are removed and each season plays an important role in the existence of the channels, except for the winter. The predictability and teleconnections are paramount issues in atmospheric science, and the teleconnections may be established by communication channels. So, this work is interesting since it reveals the vertical structure of predictability distribution, channel locations, and the contributions of different time scales to them and their variations under different seasons. (geophysics, astronomy, and astrophysics)

  2. Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

    Science.gov (United States)

    Aghakouchak, Amir; Tourian, Mohammad J.

    2015-04-01

    Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014

  3. Protein Sub-Nuclear Localization Prediction Using SVM and Pfam Domain Information

    Science.gov (United States)

    Kumar, Ravindra; Jain, Sohni; Kumari, Bandana; Kumar, Manish

    2014-01-01

    The nucleus is the largest and the highly organized organelle of eukaryotic cells. Within nucleus exist a number of pseudo-compartments, which are not separated by any membrane, yet each of them contains only a specific set of proteins. Understanding protein sub-nuclear localization can hence be an important step towards understanding biological functions of the nucleus. Here we have described a method, SubNucPred developed by us for predicting the sub-nuclear localization of proteins. This method predicts protein localization for 10 different sub-nuclear locations sequentially by combining presence or absence of unique Pfam domain and amino acid composition based SVM model. The prediction accuracy during leave-one-out cross-validation for centromeric proteins was 85.05%, for chromosomal proteins 76.85%, for nuclear speckle proteins 81.27%, for nucleolar proteins 81.79%, for nuclear envelope proteins 79.37%, for nuclear matrix proteins 77.78%, for nucleoplasm proteins 76.98%, for nuclear pore complex proteins 88.89%, for PML body proteins 75.40% and for telomeric proteins it was 83.33%. Comparison with other reported methods showed that SubNucPred performs better than existing methods. A web-server for predicting protein sub-nuclear localization named SubNucPred has been established at http://14.139.227.92/mkumar/subnucpred/. Standalone version of SubNucPred can also be downloaded from the web-server. PMID:24897370

  4. Making smart social judgments takes time: infants' recruitment of goal information when generating action predictions.

    Science.gov (United States)

    Krogh-Jespersen, Sheila; Woodward, Amanda L

    2014-01-01

    Previous research has shown that young infants perceive others' actions as structured by goals. One open question is whether the recruitment of this understanding when predicting others' actions imposes a cognitive challenge for young infants. The current study explored infants' ability to utilize their knowledge of others' goals to rapidly predict future behavior in complex social environments and distinguish goal-directed actions from other kinds of movements. Fifteen-month-olds (N = 40) viewed videos of an actor engaged in either a goal-directed (grasping) or an ambiguous (brushing the back of her hand) action on a Tobii eye-tracker. At test, critical elements of the scene were changed and infants' predictive fixations were examined to determine whether they relied on goal information to anticipate the actor's future behavior. Results revealed that infants reliably generated goal-based visual predictions for the grasping action, but not for the back-of-hand behavior. Moreover, response latencies were longer for goal-based predictions than for location-based predictions, suggesting that goal-based predictions are cognitively taxing. Analyses of areas of interest indicated that heightened attention to the overall scene, as opposed to specific patterns of attention, was the critical indicator of successful judgments regarding an actor's future goal-directed behavior. These findings shed light on the processes that support "smart" social behavior in infants, as it may be a challenge for young infants to use information about others' intentions to inform rapid predictions.

  5. Evolution of the Largest Mammalian Genome.

    Science.gov (United States)

    Evans, Ben J; Upham, Nathan S; Golding, Goeffrey B; Ojeda, Ricardo A; Ojeda, Agustina A

    2017-06-01

    The genome of the red vizcacha rat (Rodentia, Octodontidae, Tympanoctomys barrerae) is the largest of all mammals, and about double the size of their close relative, the mountain vizcacha rat Octomys mimax, even though the lineages that gave rise to these species diverged from each other only about 5 Ma. The mechanism for this rapid genome expansion is controversial, and hypothesized to be a consequence of whole genome duplication or accumulation of repetitive elements. To test these alternative but nonexclusive hypotheses, we gathered and evaluated evidence from whole transcriptome and whole genome sequences of T. barrerae and O. mimax. We recovered support for genome expansion due to accumulation of a diverse assemblage of repetitive elements, which represent about one half and one fifth of the genomes of T. barrerae and O. mimax, respectively, but we found no strong signal of whole genome duplication. In both species, repetitive sequences were rare in transcribed regions as compared with the rest of the genome, and mostly had no close match to annotated repetitive sequences from other rodents. These findings raise new questions about the genomic dynamics of these repetitive elements, their connection to widespread chromosomal fissions that occurred in the T. barrerae ancestor, and their fitness effects-including during the evolution of hypersaline dietary tolerance in T. barrerae. ©The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  6. Largest US oil and gas fields, August 1993

    International Nuclear Information System (INIS)

    1993-01-01

    The Largest US Oil and Gas Fields is a technical report and part of an Energy Information Administration (EIA) series presenting distributions of US crude oil and natural gas resources, developed using field-level data collected by EIA's annual survey of oil and gas proved reserves. The series' objective is to provide useful information beyond that routinely presented in the EIA annual report on crude oil and natural gas reserves. These special reports also will provide oil and gas resource analysts with a fuller understanding of the nature of US crude oil and natural gas occurrence, both at the macro level and with respect to the specific subjects addressed. The series' approach is to integrate EIA's crude oil and natural gas survey data with related data obtained from other authoritative sources, and then to present illustrations and analyses of interest to a broad spectrum of energy information users ranging from the general public to oil and gas industry personnel

  7. Information-Theoretic Evidence for Predictive Coding in the Face-Processing System.

    Science.gov (United States)

    Brodski-Guerniero, Alla; Paasch, Georg-Friedrich; Wollstadt, Patricia; Özdemir, Ipek; Lizier, Joseph T; Wibral, Michael

    2017-08-23

    Predictive coding suggests that the brain infers the causes of its sensations by combining sensory evidence with internal predictions based on available prior knowledge. However, the neurophysiological correlates of (pre)activated prior knowledge serving these predictions are still unknown. Based on the idea that such preactivated prior knowledge must be maintained until needed, we measured the amount of maintained information in neural signals via the active information storage (AIS) measure. AIS was calculated on whole-brain beamformer-reconstructed source time courses from MEG recordings of 52 human subjects during the baseline of a Mooney face/house detection task. Preactivation of prior knowledge for faces showed as α-band-related and β-band-related AIS increases in content-specific areas; these AIS increases were behaviorally relevant in the brain's fusiform face area. Further, AIS allowed decoding of the cued category on a trial-by-trial basis. Our results support accounts indicating that activated prior knowledge and the corresponding predictions are signaled in low-frequency activity (information our eyes/retina and other sensory organs receive from the outside world, but strongly depends also on information already present in our brains, such as prior knowledge about specific situations or objects. A currently popular theory in neuroscience, predictive coding theory, suggests that this prior knowledge is used by the brain to form internal predictions about upcoming sensory information. However, neurophysiological evidence for this hypothesis is rare, mostly because this kind of evidence requires strong a priori assumptions about the specific predictions the brain makes and the brain areas involved. Using a novel, assumption-free approach, we find that face-related prior knowledge and the derived predictions are represented in low-frequency brain activity. Copyright © 2017 the authors 0270-6474/17/378273-11$15.00/0.

  8. Quantifying predictability through information theory: small sample estimation in a non-Gaussian framework

    International Nuclear Information System (INIS)

    Haven, Kyle; Majda, Andrew; Abramov, Rafail

    2005-01-01

    Many situations in complex systems require quantitative estimates of the lack of information in one probability distribution relative to another. In short term climate and weather prediction, examples of these issues might involve the lack of information in the historical climate record compared with an ensemble prediction, or the lack of information in a particular Gaussian ensemble prediction strategy involving the first and second moments compared with the non-Gaussian ensemble itself. The relative entropy is a natural way to quantify the predictive utility in this information, and recently a systematic computationally feasible hierarchical framework has been developed. In practical systems with many degrees of freedom, computational overhead limits ensemble predictions to relatively small sample sizes. Here the notion of predictive utility, in a relative entropy framework, is extended to small random samples by the definition of a sample utility, a measure of the unlikeliness that a random sample was produced by a given prediction strategy. The sample utility is the minimum predictability, with a statistical level of confidence, which is implied by the data. Two practical algorithms for measuring such a sample utility are developed here. The first technique is based on the statistical method of null-hypothesis testing, while the second is based upon a central limit theorem for the relative entropy of moment-based probability densities. These techniques are tested on known probability densities with parameterized bimodality and skewness, and then applied to the Lorenz '96 model, a recently developed 'toy' climate model with chaotic dynamics mimicking the atmosphere. The results show a detection of non-Gaussian tendencies of prediction densities at small ensemble sizes with between 50 and 100 members, with a 95% confidence level

  9. Canada's largest co-gen project

    International Nuclear Information System (INIS)

    Salaff, S.

    2000-01-01

    In November 2000, the TransAlta Energy Corp. began construction on its $400 million natural gas fuelled cogeneration project in Sarnia Ontario. The Sarnia Regional Cogeneration Project (SRCP) is designed to integrate a new 440 MW cogeneration facility to be built at the Sarnia Division of Dow Chemicals Canada Inc. with nearby existing generators totaling 210 MW at Dow and Bayer Inc. At 650 MW, the new facility will rank as Canada's largest cogeneration installation. Commercial operation is scheduled for October 2002. TransAlta owns three natural gas fuelled cogeneration facilities in Ontario (in Ottawa, Mississauga and Windsor) totaling 250 MW. The cost of electric power in Ontario is currently controlled by rising natural gas prices and the supply demand imbalance. This balance will be significantly affected by the possible return to service of 2000 MW of nuclear generating capacity. The SRCP project was announced just prior to the Ontario Energy Competition Act of October 1998 which committed the province to introduce competition to the electricity sector and which created major uncertainties in the electricity market. Some of the small, 25 MW projects which survived the market uncertainty included the Toronto-based Toromont Energy Ltd. project involving gas fuelled cogeneration and methane gas generation from landfill projects in Sudbury and Waterloo. It was emphasized that cogeneration and combined heat and power projects have significant environmental advantages over large combined cycle facilities. The Ontario Energy Board is currently considering an application from TransAlta to link the SRCP facility to Ontario's Hydro One Network Inc.'s transmission grid. 1 fig

  10. About Skin: Your Body's Largest Organ

    Science.gov (United States)

    ... Registration General information Housing & travel Education Exhibit hall Mobile app 2019 Annual Meeting Derm Exam Prep Course ... SkinPAC State societies Scope of practice Truth in advertising NP/PA laws Action center Public and patients ...

  11. The information value of early career productivity in mathematics: a ROC analysis of prediction errors in bibliometricly informed decision making.

    Science.gov (United States)

    Lindahl, Jonas; Danell, Rickard

    The aim of this study was to provide a framework to evaluate bibliometric indicators as decision support tools from a decision making perspective and to examine the information value of early career publication rate as a predictor of future productivity. We used ROC analysis to evaluate a bibliometric indicator as a tool for binary decision making. The dataset consisted of 451 early career researchers in the mathematical sub-field of number theory. We investigated the effect of three different definitions of top performance groups-top 10, top 25, and top 50 %; the consequences of using different thresholds in the prediction models; and the added prediction value of information on early career research collaboration and publications in prestige journals. We conclude that early career performance productivity has an information value in all tested decision scenarios, but future performance is more predictable if the definition of a high performance group is more exclusive. Estimated optimal decision thresholds using the Youden index indicated that the top 10 % decision scenario should use 7 articles, the top 25 % scenario should use 7 articles, and the top 50 % should use 5 articles to minimize prediction errors. A comparative analysis between the decision thresholds provided by the Youden index which take consequences into consideration and a method commonly used in evaluative bibliometrics which do not take consequences into consideration when determining decision thresholds, indicated that differences are trivial for the top 25 and the 50 % groups. However, a statistically significant difference between the methods was found for the top 10 % group. Information on early career collaboration and publication strategies did not add any prediction value to the bibliometric indicator publication rate in any of the models. The key contributions of this research is the focus on consequences in terms of prediction errors and the notion of transforming uncertainty

  12. Endogenous Information, Risk Characterization, and the Predictability of Average Stock Returns

    Directory of Open Access Journals (Sweden)

    Pradosh Simlai

    2012-09-01

    Full Text Available In this paper we provide a new type of risk characterization of the predictability of two widely known abnormal patterns in average stock returns: momentum and reversal. The purpose is to illustrate the relative importance of common risk factors and endogenous information. Our results demonstrates that in the presence of zero-investment factors, spreads in average momentum and reversal returns correspond to spreads in the slopes of the endogenous information. The empirical findings support the view that various classes of firms react differently to volatility risk, and endogenous information harbor important sources of potential risk loadings. Taken together, our results suggest that returns are influenced by random endogenous information flow, which is asymmetric in nature, and can be used as a performance attribution factor. If one fails to incorporate the existing asymmetric endogenous information hidden in the historical behavior, any attempt to explore average stock return predictability will be subject to an unquantified specification bias.

  13. Characterization of Initial Parameter Information for Lifetime Prediction of Electronic Devices.

    Science.gov (United States)

    Li, Zhigang; Liu, Boying; Yuan, Mengxiong; Zhang, Feifei; Guo, Jiaqiang

    2016-01-01

    Newly manufactured electronic devices are subject to different levels of potential defects existing among the initial parameter information of the devices. In this study, a characterization of electromagnetic relays that were operated at their optimal performance with appropriate and steady parameter values was performed to estimate the levels of their potential defects and to develop a lifetime prediction model. First, the initial parameter information value and stability were quantified to measure the performance of the electronics. In particular, the values of the initial parameter information were estimated using the probability-weighted average method, whereas the stability of the parameter information was determined by using the difference between the extrema and end points of the fitting curves for the initial parameter information. Second, a lifetime prediction model for small-sized samples was proposed on the basis of both measures. Finally, a model for the relationship of the initial contact resistance and stability over the lifetime of the sampled electromagnetic relays was proposed and verified. A comparison of the actual and predicted lifetimes of the relays revealed a 15.4% relative error, indicating that the lifetime of electronic devices can be predicted based on their initial parameter information.

  14. Characterization of Initial Parameter Information for Lifetime Prediction of Electronic Devices.

    Directory of Open Access Journals (Sweden)

    Zhigang Li

    Full Text Available Newly manufactured electronic devices are subject to different levels of potential defects existing among the initial parameter information of the devices. In this study, a characterization of electromagnetic relays that were operated at their optimal performance with appropriate and steady parameter values was performed to estimate the levels of their potential defects and to develop a lifetime prediction model. First, the initial parameter information value and stability were quantified to measure the performance of the electronics. In particular, the values of the initial parameter information were estimated using the probability-weighted average method, whereas the stability of the parameter information was determined by using the difference between the extrema and end points of the fitting curves for the initial parameter information. Second, a lifetime prediction model for small-sized samples was proposed on the basis of both measures. Finally, a model for the relationship of the initial contact resistance and stability over the lifetime of the sampled electromagnetic relays was proposed and verified. A comparison of the actual and predicted lifetimes of the relays revealed a 15.4% relative error, indicating that the lifetime of electronic devices can be predicted based on their initial parameter information.

  15. Predictive control strategies for energy saving of hybrid electric vehicles based on traffic light information

    Directory of Open Access Journals (Sweden)

    Kaijiang YU

    2015-10-01

    Full Text Available As the conventional control method for hybrid electric vehicle doesn’t consider the effect of known traffic light information on the vehicle energy management, this paper proposes a model predictive control intelligent optimization strategies based on traffic light information for hybrid electric vehicles. By building the simplified model of the hybrid electric vehicle and adopting the continuation/generalized minimum residual method, the model prediction problem is solved. The simulation is conducted by using MATLAB/Simulink platform. The simulation results show the effectiveness of the proposed model of the traffic light information, and that the proposed model predictive control method can improve fuel economy and the real-time control performance significantly. The research conclusions show that the proposed control strategy can achieve optimal control of the vehicle trajectory, significantly improving fuel economy of the vehicle, and meet the system requirements for the real-time optimal control.

  16. Identification of informative features for predicting proinflammatory potentials of engine exhausts.

    Science.gov (United States)

    Wang, Chia-Chi; Lin, Ying-Chi; Lin, Yuan-Chung; Jhang, Syu-Ruei; Tung, Chun-Wei

    2017-08-18

    The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment. To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm. A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively. The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.

  17. Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.

    Science.gov (United States)

    Zhang, Wen; Chen, Yanlin; Li, Dingfang

    2017-11-25

    Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.

  18. The Environmental Responsibility of the World’s Largest Banks

    Directory of Open Access Journals (Sweden)

    Ryszawska Bożena

    2018-03-01

    Full Text Available Sustainability transition is changing the role and function of banks, specially their products and services also in relation to stakeholders. Banks are one of the main actors supporting the transition to sustainable economy. The purpose of this study is to emphasise the role of world’s largest banks in that process. Banks are slowly responding to the new demand of sustainability and responsibility, and they try to align with it. The paper is based on an overview of the world’s five largest banks that employ corporate social responsibility (CSR reporting standards, together with detailed enumeration of pro-environmental activities included in the reports. The first section of this paper presents the most popular approaches to the problem at hand, as reported in professional literature. Section two presents the characteristics of the CSR actions in banks. The third section discusses the environmental actions of the biggest banks in Global Reporting Initiative (GRI reporting the most popular standard for reporting non-financial information. And the last part of the paper presents the conclusions resulting from the article. The research was conducted using a variety of sources, such as scientific articles, statistical data, CSR reports of the world’s largest banks, as well reporting principles and standard disclosures. The basic method used in the process of writing was a critical analysis of literature and reports concerning the CSR reporting standards, environmental responsibilities of different kinds of entities, as well as own observations based on special reports of banks. In the article, also the analysis of financial market data, induction method and comparison method have been used. The main conclusions of the analysis of the CSR reports disclosed by the world’s largest banks confirm all three of the theses presented in the article. The findings suggest that the banks under study can be regarded as environmentally responsible

  19. Prediction on sunspot activity based on fuzzy information granulation and support vector machine

    Science.gov (United States)

    Peng, Lingling; Yan, Haisheng; Yang, Zhigang

    2018-04-01

    In order to analyze the range of sunspots, a combined prediction method of forecasting the fluctuation range of sunspots based on fuzzy information granulation (FIG) and support vector machine (SVM) was put forward. Firstly, employing the FIG to granulate sample data and extract va)alid information of each window, namely the minimum value, the general average value and the maximum value of each window. Secondly, forecasting model is built respectively with SVM and then cross method is used to optimize these parameters. Finally, the fluctuation range of sunspots is forecasted with the optimized SVM model. Case study demonstrates that the model have high accuracy and can effectively predict the fluctuation of sunspots.

  20. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  1. The impact of real-time and predictive traffic information on travelers' behavior on the I-4 corridor. Final report.

    Science.gov (United States)

    2003-07-01

    Real time and predicted traffic information plays a key role in the successful implementation of advanced traveler information systems (ATIS) and advance traffic management systems (ATMS). Traffic information is essentially valuable to both transport...

  2. Middle Range Sea Ice Prediction System of Voyage Environmental Information System in Arctic Sea Route

    Science.gov (United States)

    Lim, H. S.

    2017-12-01

    Due to global warming, the sea ice in the Arctic Ocean is melting dramatically in summer, which is providing a new opportunity to exploit the Northern Sea Route (NSR) connecting Asia and Europe ship route. Recent increases in logistics transportation through NSR and resource development reveal the possible threats of marine pollution and marine transportation accidents without real-time navigation system. To develop a safe Voyage Environmental Information System (VEIS) for vessels operating, the Korea Institute of Ocean Science and Technology (KIOST) which is supported by the Ministry of Oceans and Fisheries, Korea has initiated the development of short-term and middle range prediction system for the sea ice concentration (SIC) and sea ice thickness (SIT) in NSR since 2014. The sea ice prediction system of VEIS consists of AMSR2 satellite composite images (a day), short-term (a week) prediction system, and middle range (a month) prediction system using a statistical method with re-analysis data (TOPAZ) and short-term predicted model data. In this study, the middle range prediction system for the SIC and SIT in NSR is calibrated with another middle range predicted atmospheric and oceanic data (NOAA CFSv2). The system predicts one month SIC and SIT on a daily basis, as validated with dynamic composite SIC data extracted from AMSR2 L2 satellite images.

  3. Informative sensor selection and learning for prediction of lower limb kinematics using generative stochastic neural networks.

    Science.gov (United States)

    Eunsuk Chong; Taejin Choi; Hyungmin Kim; Seung-Jong Kim; Yoha Hwang; Jong Min Lee

    2017-07-01

    We propose a novel approach of selecting useful input sensors as well as learning a mathematical model for predicting lower limb joint kinematics. We applied a feature selection method based on the mutual information called the variational information maximization, which has been reported as the state-of-the-art work among information based feature selection methods. The main difficulty in applying the method is estimating reliable probability density of input and output data, especially when the data are high dimensional and real-valued. We addressed this problem by applying a generative stochastic neural network called the restricted Boltzmann machine, through which we could perform sampling based probability estimation. The mutual informations between inputs and outputs are evaluated in each backward sensor elimination step, and the least informative sensor is removed with its network connections. The entire network is fine-tuned by maximizing conditional likelihood in each step. Experimental results are shown for 4 healthy subjects walking with various speeds, recording 64 sensor measurements including electromyogram, acceleration, and foot-pressure sensors attached on both lower limbs for predicting hip and knee joint angles. For test set of walking with arbitrary speed, our results show that our suggested method can select informative sensors while maintaining a good prediction accuracy.

  4. Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries

    NARCIS (Netherlands)

    Nistor, Nicolae; Dascalu, Mihai; Stavarache, Lucia Larise; Serafin, Yvonne; Trausan-Matu, Stefan

    2016-01-01

    Nistor, N., Dascalu, M., Stavarache, L.L., Serafin, Y., & Trausan-Matu, S. (2015). Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries. In G. Conole, T. Klobucar, C. Rensing, J. Konert & É. Lavoué (Eds.), 10th European Conf. on Technology Enhanced

  5. Informal Workplace Learning among Nurses: Organisational Learning Conditions and Personal Characteristics That Predict Learning Outcomes

    Science.gov (United States)

    Kyndt, Eva; Vermeire, Eva; Cabus, Shana

    2016-01-01

    Purpose: This paper aims to examine which organisational learning conditions and individual characteristics predict the learning outcomes nurses achieve through informal learning activities. There is specific relevance for the nursing profession because of the rapidly changing healthcare systems. Design/Methodology/Approach: In total, 203 nurses…

  6. Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs.

    Science.gov (United States)

    Várnai, Csilla; Burkoff, Nikolas S; Wild, David L

    2017-01-01

    Evolutionary information stored in multiple sequence alignments (MSAs) has been used to identify the interaction interface of protein complexes, by measuring either co-conservation or co-mutation of amino acid residues across the interface. Recently, maximum entropy related correlated mutation measures (CMMs) such as direct information, decoupling direct from indirect interactions, have been developed to identify residue pairs interacting across the protein complex interface. These studies have focussed on carefully selected protein complexes with large, good-quality MSAs. In this work, we study protein complexes with a more typical MSA consisting of fewer than 400 sequences, using a set of 79 intramolecular protein complexes. Using a maximum entropy based CMM at the residue level, we develop an interface level CMM score to be used in re-ranking docking decoys. We demonstrate that our interface level CMM score compares favourably to the complementarity trace score, an evolutionary information-based score measuring co-conservation, when combined with the number of interface residues, a knowledge-based potential and the variability score of individual amino acid sites. We also demonstrate, that, since co-mutation and co-complementarity in the MSA contain orthogonal information, the best prediction performance using evolutionary information can be achieved by combining the co-mutation information of the CMM with co-conservation information of a complementarity trace score, predicting a near-native structure as the top prediction for 41% of the dataset. The method presented is not restricted to small MSAs, and will likely improve interface prediction also for complexes with large and good-quality MSAs.

  7. Algorithm for predicting the evolution of series of dynamics of complex systems in solving information problems

    Science.gov (United States)

    Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.

    2018-03-01

    In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.

  8. Maladaptive social information processing in childhood predicts young men's atypical amygdala reactivity to threat.

    Science.gov (United States)

    Choe, Daniel Ewon; Shaw, Daniel S; Forbes, Erika E

    2015-05-01

    Maladaptive social information processing, such as hostile attributional bias and aggressive response generation, is associated with childhood maladjustment. Although social information processing problems are correlated with heightened physiological responses to social threat, few studies have examined their associations with neural threat circuitry, specifically amygdala activation to social threat. A cohort of 310 boys participated in an ongoing longitudinal study and completed questionnaires and laboratory tasks assessing their social and cognitive characteristics the boys were between 10 and 12 years of age. At age 20, 178 of these young men underwent functional magnetic resonance imaging and a social threat task. At age 22, adult criminal arrest records and self-reports of impulsiveness were obtained. Path models indicated that maladaptive social information-processing at ages 10 and 11 predicted increased left amygdala reactivity to fear faces, an ambiguous threat, at age 20 while accounting for childhood antisocial behavior, empathy, IQ, and socioeconomic status. Exploratory analyses indicated that aggressive response generation - the tendency to respond to threat with reactive aggression - predicted left amygdala reactivity to fear faces and was concurrently associated with empathy, antisocial behavior, and hostile attributional bias, whereas hostile attributional bias correlated with IQ. Although unrelated to social information-processing problems, bilateral amygdala reactivity to anger faces at age 20 was unexpectedly predicted by low IQ at age 11. Amygdala activation did not mediate associations between social information processing and number of criminal arrests, but both impulsiveness at age 22 and arrests were correlated with right amygdala reactivity to anger facial expressions at age 20. Childhood social information processing and IQ predicted young men's amygdala response to threat a decade later, which suggests that childhood social

  9. Prediction of N2O emission from local information with Random Forest

    International Nuclear Information System (INIS)

    Philibert, Aurore; Loyce, Chantal; Makowski, David

    2013-01-01

    Nitrous oxide is a potent greenhouse gas, with a global warming potential 298 times greater than that of CO 2 . In agricultural soils, N 2 O emissions are influenced by a large number of environmental characteristics and crop management techniques that are not systematically reported in experiments. Random Forest (RF) is a machine learning method that can handle missing data and ranks input variables on the basis of their importance. We aimed to predict N 2 O emission on the basis of local information, to rank environmental and crop management variables according to their influence on N 2 O emission, and to compare the performances of RF with several regression models. RF outperformed the regression models for predictive purposes, and this approach led to the identification of three important input variables: N fertilization, type of crop, and experiment duration. This method could be used in the future for prediction of N 2 O emissions from local information. -- Highlights: ► Random Forest gave more accurate N 2 O predictions than regression. ► Missing data were well handled by Random Forest. ► The most important factors were nitrogen rate, type of crop and experiment duration. -- Random Forest, a machine learning method, outperformed the regression models for predicting N 2 O emissions and led to the identification of three important input variables

  10. Efficient network disintegration under incomplete information: the comic effect of link prediction

    Science.gov (United States)

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-01-01

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized. PMID:26960247

  11. Efficient network disintegration under incomplete information: the comic effect of link prediction

    Science.gov (United States)

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-03-01

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

  12. [Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

    Science.gov (United States)

    Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

    2012-02-01

    In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

  13. Prediction of membrane transport proteins and their substrate specificities using primary sequence information.

    Directory of Open Access Journals (Sweden)

    Nitish K Mishra

    Full Text Available Membrane transport proteins (transporters move hydrophilic substrates across hydrophobic membranes and play vital roles in most cellular functions. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity as well as sequence similarity. Among the functional annotations of transporters, information about their transporting substrates is especially important. The experimental identification and characterization of transporters is currently costly and time-consuming. The development of robust bioinformatics-based methods for the prediction of membrane transport proteins and their substrate specificities is therefore an important and urgent task.Support vector machine (SVM-based computational models, which comprehensively utilize integrative protein sequence features such as amino acid composition, dipeptide composition, physico-chemical composition, biochemical composition, and position-specific scoring matrices (PSSM, were developed to predict the substrate specificity of seven transporter classes: amino acid, anion, cation, electron, protein/mRNA, sugar, and other transporters. An additional model to differentiate transporters from non-transporters was also developed. Among the developed models, the biochemical composition and PSSM hybrid model outperformed other models and achieved an overall average prediction accuracy of 76.69% with a Mathews correlation coefficient (MCC of 0.49 and a receiver operating characteristic area under the curve (AUC of 0.833 on our main dataset. This model also achieved an overall average prediction accuracy of 78.88% and MCC of 0.41 on an independent dataset.Our analyses suggest that evolutionary information (i.e., the PSSM and the AAIndex are key features for the substrate specificity prediction of transport proteins. In comparison, similarity-based methods such as BLAST, PSI-BLAST, and hidden Markov models do not provide accurate predictions

  14. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  15. Largest US oil and gas fields, August 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-08-06

    The Largest US Oil and Gas Fields is a technical report and part of an Energy Information Administration (EIA) series presenting distributions of US crude oil and natural gas resources, developed using field-level data collected by EIA`s annual survey of oil and gas proved reserves. The series` objective is to provide useful information beyond that routinely presented in the EIA annual report on crude oil and natural gas reserves. These special reports also will provide oil and gas resource analysts with a fuller understanding of the nature of US crude oil and natural gas occurrence, both at the macro level and with respect to the specific subjects addressed. The series` approach is to integrate EIA`s crude oil and natural gas survey data with related data obtained from other authoritative sources, and then to present illustrations and analyses of interest to a broad spectrum of energy information users ranging from the general public to oil and gas industry personnel.

  16. Best-fitting prediction equations for basal metabolic rate: informing obesity interventions in diverse populations.

    Science.gov (United States)

    Sabounchi, N S; Rahmandad, H; Ammerman, A

    2013-10-01

    Basal metabolic rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat-free mass, fat mass, height, waist-to-hip ratio, body mass index and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to 20 specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender and weight.

  17. Poor sleep quality predicts deficient emotion information processing over time in early adolescence.

    Science.gov (United States)

    Soffer-Dudek, Nirit; Sadeh, Avi; Dahl, Ronald E; Rosenblat-Stein, Shiran

    2011-11-01

    There is deepening understanding of the effects of sleep on emotional information processing. Emotion information processing is a key aspect of social competence, which undergoes important maturational and developmental changes in adolescence; however, most research in this area has focused on adults. Our aim was to test the links between sleep and emotion information processing during early adolescence. Sleep and facial information processing were assessed objectively during 3 assessment waves, separated by 1-year lags. Data were obtained in natural environments-sleep was assessed in home settings, and facial information processing was assessed at school. 94 healthy children (53 girls, 41 boys), aged 10 years at Time 1. N/A. Facial information processing was tested under neutral (gender identification) and emotional (emotional expression identification) conditions. Sleep was assessed in home settings using actigraphy for 7 nights at each assessment wave. Waking > 5 min was considered a night awakening. Using multilevel modeling, elevated night awakenings and decreased sleep efficiency significantly predicted poor performance only in the emotional information processing condition (e.g., b = -1.79, SD = 0.52, confidence interval: lower boundary = -2.82, upper boundary = -0.076, t(416.94) = -3.42, P = 0.001). Poor sleep quality is associated with compromised emotional information processing during early adolescence, a sensitive period in socio-emotional development.

  18. The prediction of engineering cost for green buildings based on information entropy

    Science.gov (United States)

    Liang, Guoqiang; Huang, Jinglian

    2018-03-01

    Green building is the developing trend in the world building industry. Additionally, construction costs are an essential consideration in building constructions. Therefore, it is necessary to investigate the problems of cost prediction in green building. On the basis of analyzing the cost of green building, this paper proposes the forecasting method of actual cost in green building based on information entropy and provides the forecasting working procedure. Using the probability density obtained from statistical data, such as labor costs, material costs, machinery costs, administration costs, profits, risk costs a unit project quotation and etc., situations can be predicted which lead to cost variations between budgeted cost and actual cost in constructions, through estimating the information entropy of budgeted cost and actual cost. The research results of this article have a practical significance in cost control of green building. Additionally, the method proposed in this article can be generalized and applied to a variety of other aspects in building management.

  19. Enhancing the prediction of protein pairings between interacting families using orthology information

    Directory of Open Access Journals (Sweden)

    Pazos Florencio

    2008-01-01

    Full Text Available Abstract Background It has repeatedly been shown that interacting protein families tend to have similar phylogenetic trees. These similarities can be used to predicting the mapping between two families of interacting proteins (i.e. which proteins from one family interact with which members of the other. The correct mapping will be that which maximizes the similarity between the trees. The two families may eventually comprise orthologs and paralogs, if members of the two families are present in more than one organism. This fact can be exploited to restrict the possible mappings, simply by impeding links between proteins of different organisms. We present here an algorithm to predict the mapping between families of interacting proteins which is able to incorporate information regarding orthologues, or any other assignment of proteins to "classes" that may restrict possible mappings. Results For the first time in methods for predicting mappings, we have tested this new approach on a large number of interacting protein domains in order to statistically assess its performance. The method accurately predicts around 80% in the most favourable cases. We also analysed in detail the results of the method for a well defined case of interacting families, the sensor and kinase components of the Ntr-type two-component system, for which up to 98% of the pairings predicted by the method were correct. Conclusion Based on the well established relationship between tree similarity and interactions we developed a method for predicting the mapping between two interacting families using genomic information alone. The program is available through a web interface.

  20. Prediction Model of Collapse Risk Based on Information Entropy and Distance Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Hujun He

    2017-01-01

    Full Text Available The prediction and risk classification of collapse is an important issue in the process of highway construction in mountainous regions. Based on the principles of information entropy and Mahalanobis distance discriminant analysis, we have produced a collapse hazard prediction model. We used the entropy measure method to reduce the influence indexes of the collapse activity and extracted the nine main indexes affecting collapse activity as the discriminant factors of the distance discriminant analysis model (i.e., slope shape, aspect, gradient, and height, along with exposure of the structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate, and degree of rock weathering. We employ postearthquake collapse data in relation to construction of the Yingxiu-Wolong highway, Hanchuan County, China, as training samples for analysis. The results were analyzed using the back substitution estimation method, showing high accuracy and no errors, and were the same as the prediction result of uncertainty measure. Results show that the classification model based on information entropy and distance discriminant analysis achieves the purpose of index optimization and has excellent performance, high prediction accuracy, and a zero false-positive rate. The model can be used as a tool for future evaluation of collapse risk.

  1. Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

    Science.gov (United States)

    Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

    2017-11-01

    Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

    Science.gov (United States)

    Darmon, David

    2018-03-01

    In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

  3. Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels.

    Science.gov (United States)

    Baseer, Abdul; Weddell, Stephen J; Jones, Richard D

    2017-07-01

    Microsleeps are involuntary and brief instances of complete loss of responsiveness, typically of 0.5-15 s duration. They adversely affect performance in extended attention-driven jobs and can be fatal. Our aim was to predict microsleeps from 16 channel EEG signals. Two information theoretic concepts - pairwise joint entropy and mutual information - were independently used to continuously extract features from EEG signals. k-nearest neighbor (kNN) with k = 3 was used to calculate both joint entropy and mutual information. Highly correlated features were discarded and the rest were ranked using Fisher score followed by an average of 3-fold cross-validation area under the curve of the receiver operating characteristic (AUC ROC ). Leave-one-out method (LOOM) was performed to test the performance of microsleep prediction system on independent data. The best prediction for 0.25 s ahead was AUCROC, sensitivity, precision, geometric mean (GM), and φ of 0.93, 0.68, 0.33, 0.75, and 0.38 respectively with joint entropy using single linear discriminant analysis (LDA) classifier.

  4. Performance of local information-based link prediction: a sampling perspective

    Science.gov (United States)

    Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

    2012-08-01

    Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

  5. Hydrodynamic and Inundation Modeling of China’s Largest Freshwater Lake Aided by Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2015-04-01

    Full Text Available China’s largest freshwater lake, Poyang Lake, is characterized by rapid changes in its inundation area and hydrodynamics, so in this study, a hydrodynamic model of Poyang Lake was established to simulate these long-term changes. Inundation information was extracted from Moderate Resolution Imaging Spectroradiometer (MODIS remote sensing data and used to calibrate the wetting and drying parameter by assessing the accuracy of the simulated inundation area and its boundary. The bottom friction parameter was calibrated using current velocity measurements from Acoustic Doppler Current Profilers (ADCP. The results show the model is capable of predicting the inundation area dynamic through cross-validation with remotely sensed inundation data, and can reproduce the seasonal dynamics of the water level, and water discharge through a comparison with hydrological data. Based on the model results, the characteristics of the current velocities of the lake in the wet season and the dry season of the lake were explored, and the potential effect of the current dynamic on water quality patterns was discussed. The model is a promising basic tool for prediction and management of the water resource and water quality of Poyang Lake.

  6. EKORISK project - an information system for prediction and expert evaluation of environmental impact

    International Nuclear Information System (INIS)

    Zaimov, V.; Antonov, A.

    1993-01-01

    The aim of this project is to create an expert system for prediction, evaluation and decision making support in case of accidents. The system consists of the following modules: 1) A data base containing information about the situation - geographical and demographical data for the region of the accident as well as data about the contaminants. The data about geographic objects (boundaries, rivers, roads, towns, soils, etc.) is managed and visualized by a geographic information system (GIS), which produces multi-layer geographical maps, showing different viewpoints of the region of interest. Information about the pollutants, their use and storage, as well as data about the available resources for action in case of accidents, are stored in relational data bases which guarantee easy access, search, sorting and proper visualisation. 2) Predicting the propagation of contamination by using actual meteorological information and applying mathematical models for propagation of the spilled substances in the air, water and ground. They calculate the concentration of the substance as a function of time and distance from the initial spill location. The choice of the proper model is made by applying expert knowledge for evaluation of situation and comparing the model characteristics. 3) Suggesting actions for minimising the accident's impact. Expert knowledge is used for recommendations concerning deactivating of the region as well as actions for reducing the absorbed radiation doses of population. The modern technologies for knowledge processing and the object-oriented approach ensure flexibility and integration of all subsystems. (author)

  7. Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato.

    Science.gov (United States)

    Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig

    2018-05-01

    As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.

  8. Prediction of glutathionylation sites in proteins using minimal sequence information and their experimental validation.

    Science.gov (United States)

    Pal, Debojyoti; Sharma, Deepak; Kumar, Mukesh; Sandur, Santosh K

    2016-09-01

    S-glutathionylation of proteins plays an important role in various biological processes and is known to be protective modification during oxidative stress. Since, experimental detection of S-glutathionylation is labor intensive and time consuming, bioinformatics based approach is a viable alternative. Available methods require relatively longer sequence information, which may prevent prediction if sequence information is incomplete. Here, we present a model to predict glutathionylation sites from pentapeptide sequences. It is based upon differential association of amino acids with glutathionylated and non-glutathionylated cysteines from a database of experimentally verified sequences. This data was used to calculate position dependent F-scores, which measure how a particular amino acid at a particular position may affect the likelihood of glutathionylation event. Glutathionylation-score (G-score), indicating propensity of a sequence to undergo glutathionylation, was calculated using position-dependent F-scores for each amino-acid. Cut-off values were used for prediction. Our model returned an accuracy of 58% with Matthew's correlation-coefficient (MCC) value of 0.165. On an independent dataset, our model outperformed the currently available model, in spite of needing much less sequence information. Pentapeptide motifs having high abundance among glutathionylated proteins were identified. A list of potential glutathionylation hotspot sequences were obtained by assigning G-scores and subsequent Protein-BLAST analysis revealed a total of 254 putative glutathionable proteins, a number of which were already known to be glutathionylated. Our model predicted glutathionylation sites in 93.93% of experimentally verified glutathionylated proteins. Outcome of this study may assist in discovering novel glutathionylation sites and finding candidate proteins for glutathionylation.

  9. Differential contribution of visual and auditory information to accurately predict the direction and rotational motion of a visual stimulus.

    Science.gov (United States)

    Park, Seoung Hoon; Kim, Seonjin; Kwon, MinHyuk; Christou, Evangelos A

    2016-03-01

    Vision and auditory information are critical for perception and to enhance the ability of an individual to respond accurately to a stimulus. However, it is unknown whether visual and auditory information contribute differentially to identify the direction and rotational motion of the stimulus. The purpose of this study was to determine the ability of an individual to accurately predict the direction and rotational motion of the stimulus based on visual and auditory information. In this study, we recruited 9 expert table-tennis players and used table-tennis service as our experimental model. Participants watched recorded services with different levels of visual and auditory information. The goal was to anticipate the direction of the service (left or right) and the rotational motion of service (topspin, sidespin, or cut). We recorded their responses and quantified the following outcomes: (i) directional accuracy and (ii) rotational motion accuracy. The response accuracy was the accurate predictions relative to the total number of trials. The ability of the participants to predict the direction of the service accurately increased with additional visual information but not with auditory information. In contrast, the ability of the participants to predict the rotational motion of the service accurately increased with the addition of auditory information to visual information but not with additional visual information alone. In conclusion, this finding demonstrates that visual information enhances the ability of an individual to accurately predict the direction of the stimulus, whereas additional auditory information enhances the ability of an individual to accurately predict the rotational motion of stimulus.

  10. Prediction of internet addiction based on information literacy among students of Iran University of Medical Sciences.

    Science.gov (United States)

    Langarizadeh, Mostafa; Naghipour, Majid; Tabatabaei, Seyed Mohsen; Mirzaei, Abbas; Vaghar, Mohammad Eslami

    2018-02-01

    A considerable group of internet users consists of university users; however, despite internet benefits and capabilities, internet overuse is a threat to societies especially to young people and students. The objective of this study was to determine the predictive role of information literacy in internet addiction among students of Iran University of Medical Sciences during 2016. This analytical cross-sectional study was conducted in Iran University of Medical Sciences in 2016. Using stratified random sampling method, 365 students from different disciplines were selected. Measuring tools included the Information Literacy Questionnaire, the Yang Online Drug Addiction Scale and the General Health Questionnaire. The collected data were analyzed by Pearson product-moment correlation, independent samples t-test and multiple linear regression using SPSS version 22. According to this study, 31.2% of students had internet addiction (29.9% were mildly addicted and 1.3% had severe addiction). There was a significant and inverse relationship between higher information literacy and internet addiction (R= -0.45) and (pInformation literacy" explained 20% of the variation in the outcome variable "Internet addiction". Students play a substantial role in promoting the cultural and scientific level of knowledge in society; the higher their information literacy, the lower the level of Internet addiction, and consequently the general health of society will improve. It seems that wise planning by authorities of Iran's universities to prevent internet addiction and to increase information literacy among students is needed.

  11. Predicting the fidelity of JPEG2000 compressed CT images using DICOM header information

    International Nuclear Information System (INIS)

    Kim, Kil Joong; Kim, Bohyoung; Lee, Hyunna; Choi, Hosik; Jeon, Jong-June; Ahn, Jeong-Hwan; Lee, Kyoung Ho

    2011-01-01

    Purpose: To propose multiple logistic regression (MLR) and artificial neural network (ANN) models constructed using digital imaging and communications in medicine (DICOM) header information in predicting the fidelity of Joint Photographic Experts Group (JPEG) 2000 compressed abdomen computed tomography (CT) images. Methods: Our institutional review board approved this study and waived informed patient consent. Using a JPEG2000 algorithm, 360 abdomen CT images were compressed reversibly (n = 48, as negative control) or irreversibly (n = 312) to one of different compression ratios (CRs) ranging from 4:1 to 10:1. Five radiologists independently determined whether the original and compressed images were distinguishable or indistinguishable. The 312 irreversibly compressed images were divided randomly into training (n = 156) and testing (n = 156) sets. The MLR and ANN models were constructed regarding the DICOM header information as independent variables and the pooled radiologists' responses as dependent variable. As independent variables, we selected the CR (DICOM tag number: 0028, 2112), effective tube current-time product (0018, 9332), section thickness (0018, 0050), and field of view (0018, 0090) among the DICOM tags. Using the training set, an optimal subset of independent variables was determined by backward stepwise selection in a four-fold cross-validation scheme. The MLR and ANN models were constructed with the determined independent variables using the training set. The models were then evaluated on the testing set by using receiver-operating-characteristic (ROC) analysis regarding the radiologists' pooled responses as the reference standard and by measuring Spearman rank correlation between the model prediction and the number of radiologists who rated the two images as distinguishable. Results: The CR and section thickness were determined as the optimal independent variables. The areas under the ROC curve for the MLR and ANN predictions were 0.91 (95% CI; 0

  12. Historical maintenance relevant information road-map for a self-learning maintenance prediction procedural approach

    Science.gov (United States)

    Morales, Francisco J.; Reyes, Antonio; Cáceres, Noelia; Romero, Luis M.; Benitez, Francisco G.; Morgado, Joao; Duarte, Emanuel; Martins, Teresa

    2017-09-01

    A large percentage of transport infrastructures are composed of linear assets, such as roads and rail tracks. The large social and economic relevance of these constructions force the stakeholders to ensure a prolonged health/durability. Even though, inevitable malfunctioning, breaking down, and out-of-service periods arise randomly during the life cycle of the infrastructure. Predictive maintenance techniques tend to diminish the appearance of unpredicted failures and the execution of needed corrective interventions, envisaging the adequate interventions to be conducted before failures show up. This communication presents: i) A procedural approach, to be conducted, in order to collect the relevant information regarding the evolving state condition of the assets involved in all maintenance interventions; this reported and stored information constitutes a rich historical data base to train Machine Learning algorithms in order to generate reliable predictions of the interventions to be carried out in further time scenarios. ii) A schematic flow chart of the automatic learning procedure. iii) Self-learning rules from automatic learning from false positive/negatives. The description, testing, automatic learning approach and the outcomes of a pilot case are presented; finally some conclusions are outlined regarding the methodology proposed for improving the self-learning predictive capability.

  13. An improved method for predicting the evolution of the characteristic parameters of an information system

    Science.gov (United States)

    Dushkin, A. V.; Kasatkina, T. I.; Novoseltsev, V. I.; Ivanov, S. V.

    2018-03-01

    The article proposes a forecasting method that allows, based on the given values of entropy and error level of the first and second kind, to determine the allowable time for forecasting the development of the characteristic parameters of a complex information system. The main feature of the method under consideration is the determination of changes in the characteristic parameters of the development of the information system in the form of the magnitude of the increment in the ratios of its entropy. When a predetermined value of the prediction error ratio is reached, that is, the entropy of the system, the characteristic parameters of the system and the depth of the prediction in time are estimated. The resulting values of the characteristics and will be optimal, since at that moment the system possessed the best ratio of entropy as a measure of the degree of organization and orderliness of the structure of the system. To construct a method for estimating the depth of prediction, it is expedient to use the maximum principle of the value of entropy.

  14. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

  15. Automated information system for analysis and prediction of production situations in blast furnace plant

    Science.gov (United States)

    Lavrov, V. V.; Spirin, N. A.

    2016-09-01

    Advances in modern science and technology are inherently connected with the development, implementation, and widespread use of computer systems based on mathematical modeling. Algorithms and computer systems are gaining practical significance solving a range of process tasks in metallurgy of MES-level (Manufacturing Execution Systems - systems controlling industrial process) of modern automated information systems at the largest iron and steel enterprises in Russia. This fact determines the necessity to develop information-modeling systems based on mathematical models that will take into account the physics of the process, the basics of heat and mass exchange, the laws of energy conservation, and also the peculiarities of the impact of technological and standard characteristics of raw materials on the manufacturing process data. Special attention in this set of operations for metallurgic production is devoted to blast-furnace production, as it consumes the greatest amount of energy, up to 50% of the fuel used in ferrous metallurgy. The paper deals with the requirements, structure and architecture of BF Process Engineer's Automated Workstation (AWS), a computer decision support system of MES Level implemented in the ICS of the Blast Furnace Plant at Magnitogorsk Iron and Steel Works. It presents a brief description of main model subsystems as well as assumptions made in the process of mathematical modelling. Application of the developed system allows the engineering and process staff to analyze online production situations in the blast furnace plant, to solve a number of process tasks related to control of heat, gas dynamics and slag conditions of blast-furnace smelting as well as to calculate the optimal composition of blast-furnace slag, which eventually results in increasing technical and economic performance of blast-furnace production.

  16. PREDICTING THE EFFECTIVENESS OF WEB INFORMATION SYSTEMS USING NEURAL NETWORKS MODELING: FRAMEWORK & EMPIRICAL TESTING

    Directory of Open Access Journals (Sweden)

    Dr. Kamal Mohammed Alhendawi

    2018-02-01

    Full Text Available The information systems (IS assessment studies have still used the commonly traditional tools such as questionnaires in evaluating the dependent variables and specially effectiveness of systems. Artificial neural networks have been recently accepted as an effective alternative tool for modeling the complicated systems and widely used for forecasting. A very few is known about the employment of Artificial Neural Network (ANN in the prediction IS effectiveness. For this reason, this study is considered as one of the fewest studies to investigate the efficiency and capability of using ANN for forecasting the user perceptions towards IS effectiveness where MATLAB is utilized for building and training the neural network model. A dataset of 175 subjects collected from international organization are utilized for ANN learning where each subject consists of 6 features (5 quality factors as inputs and one Boolean output. A percentage of 75% o subjects are used in the training phase. The results indicate an evidence on the ANN models has a reasonable accuracy in forecasting the IS effectiveness. For prediction, ANN with PURELIN (ANNP and ANN with TANSIG (ANNTS transfer functions are used. It is found that both two models have a reasonable prediction, however, the accuracy of ANNTS model is better than ANNP model (88.6% and 70.4% respectively. As the study proposes a new model for predicting IS dependent variables, it could save the considerably high cost that might be spent in sample data collection in the quantitative studies in the fields science, management, education, arts and others.

  17. Predicting Hotspots of Human-Elephant Conflict to Inform Mitigation Strategies in Xishuangbanna, Southwest China.

    Directory of Open Access Journals (Sweden)

    Ying Chen

    Full Text Available Research on the spatial patterns of human-wildlife conflict is fundamental to understanding the mechanisms underlying it and to identifying opportunities for mitigation. In the state of Xishuangbanna, containing China's largest tropical forest, an imbalance between nature conservation and economic development has led to increasing conflicts between humans and Asian elephants (Elephas maximus, as both elephant numbers and conversion of habitable land to rubber plantations have increased over the last several decades. We analyzed government data on the compensation costs of elephant-caused damage in Xishuangbanna between 2008 and 2012 to understand the spatial and temporal patterns of conflict, in terms of their occurrence, frequency and distribution. More than 18,261 incidents were reported, including episodes involving damage to rubber trees (n = 10,999, damage to crops such as paddy, upland rice, corn, bananas and sugarcane (n = 11,020, property loss (n = 689 and attacks on humans (n = 19. The conflict data reconfirmed the presence of elephants in areas which have lacked records since the late 1990s. Zero Altered Negative Binomial models revealed that the risk of damage to crops and plantations increased with proximity to protected areas, increasing distance from roads, and lower settlement density. The patterns were constant across seasons and types of crop damaged. Damage to rubber trees was essentially incidental as elephants searched for crops to eat. A predictive map of risks revealed hotspots of conflict within and around protected areas, the last refuges for elephants in the region, and along habitat corridors connecting them. Additionally, we analyzed how mitigation efforts can best diminish the risk of conflict while minimizing financial costs and adverse biological impacts. Our analytical approach can be adopted, adjusted and expanded to other areas with historical records of human-wildlife conflict.

  18. Predicting Hotspots of Human-Elephant Conflict to Inform Mitigation Strategies in Xishuangbanna, Southwest China.

    Science.gov (United States)

    Chen, Ying; Marino, Jorgelina; Chen, Yong; Tao, Qing; Sullivan, Casey D; Shi, Kun; Macdonald, David W

    2016-01-01

    Research on the spatial patterns of human-wildlife conflict is fundamental to understanding the mechanisms underlying it and to identifying opportunities for mitigation. In the state of Xishuangbanna, containing China's largest tropical forest, an imbalance between nature conservation and economic development has led to increasing conflicts between humans and Asian elephants (Elephas maximus), as both elephant numbers and conversion of habitable land to rubber plantations have increased over the last several decades. We analyzed government data on the compensation costs of elephant-caused damage in Xishuangbanna between 2008 and 2012 to understand the spatial and temporal patterns of conflict, in terms of their occurrence, frequency and distribution. More than 18,261 incidents were reported, including episodes involving damage to rubber trees (n = 10,999), damage to crops such as paddy, upland rice, corn, bananas and sugarcane (n = 11,020), property loss (n = 689) and attacks on humans (n = 19). The conflict data reconfirmed the presence of elephants in areas which have lacked records since the late 1990s. Zero Altered Negative Binomial models revealed that the risk of damage to crops and plantations increased with proximity to protected areas, increasing distance from roads, and lower settlement density. The patterns were constant across seasons and types of crop damaged. Damage to rubber trees was essentially incidental as elephants searched for crops to eat. A predictive map of risks revealed hotspots of conflict within and around protected areas, the last refuges for elephants in the region, and along habitat corridors connecting them. Additionally, we analyzed how mitigation efforts can best diminish the risk of conflict while minimizing financial costs and adverse biological impacts. Our analytical approach can be adopted, adjusted and expanded to other areas with historical records of human-wildlife conflict.

  19. Prediction of Periodontitis Occurrence: Influence of Classification and Sociodemographic and General Health Information

    DEFF Research Database (Denmark)

    Manzolli Leite, Fabio Renato; Peres, Karen Glazer; Do, Loc Giang

    2017-01-01

    BACKGROUND: Prediction of periodontitis development is challenging. Use of oral health-related data alone, especially in a young population, might underestimate disease risk. This study investigates accuracy of oral, systemic, and socioeconomic data on estimating periodontitis development...... in a population-based prospective cohort. METHODS: General health history and sociodemographic information were collected throughout the life-course of individuals. Oral examinations were performed at ages 24 and 31 years in the Pelotas 1982 birth cohort. Periodontitis at age 31 years according to six...... classifications was used as the gold standard to compute area under the receiver operating characteristic curve (AUC). Multivariable binomial regression models were used to evaluate the effects of oral health, general health, and socioeconomic characteristics on accuracy of periodontitis development prediction...

  20. Position-specific prediction of methylation sites from sequence conservation based on information theory.

    Science.gov (United States)

    Shi, Yinan; Guo, Yanzhi; Hu, Yayun; Li, Menglong

    2015-07-23

    Protein methylation plays vital roles in many biological processes and has been implicated in various human diseases. To fully understand the mechanisms underlying methylation for use in drug design and work in methylation-related diseases, an initial but crucial step is to identify methylation sites. The use of high-throughput bioinformatics methods has become imperative to predict methylation sites. In this study, we developed a novel method that is based only on sequence conservation to predict protein methylation sites. Conservation difference profiles between methylated and non-methylated peptides were constructed by the information entropy (IE) in a wider neighbor interval around the methylation sites that fully incorporated all of the environmental information. Then, the distinctive neighbor residues were identified by the importance scores of information gain (IG). The most representative model was constructed by support vector machine (SVM) for Arginine and Lysine methylation, respectively. This model yielded a promising result on both the benchmark dataset and independent test set. The model was used to screen the entire human proteome, and many unknown substrates were identified. These results indicate that our method can serve as a useful supplement to elucidate the mechanism of protein methylation and facilitate hypothesis-driven experimental design and validation.

  1. Prediction of natural disasters basing of chrono-and-information field characters

    Science.gov (United States)

    Sapunov, Valentin

    2013-04-01

    Living organisms are able to predict some future events particular catastrophic incidents. This is adaptive characters producing by evolution. The more energy produces incident the more possibility to predict one. Wild animals escaped natural hazards including tsunami (e.g. extremal tsunami in Asia December 2004). Living animals are able to predict strong phenomena of obscure nature. For example majority of animals escaped Tungus catastrophe taking place in Siberia at 1908. Wild animals are able to predict nuclear weapon experiences. The obscure characters are not typical for human, but they are fixed under probability 15%. Such were summarized by L.Vasiliev (1961). Effective theory describing such a characters is absent till now. N.Kozyrev (1991) suggested existence of unknown physical field (but gravitation and electro magnetic). The field was named "time" or "chrono". Some characters of the field appeared to be object of physical experiment. Kozyrev suggested specific role of the field for function of living organisms. Transition of biological information throw space (telepathy) and time (proscopy) may be based on characters of such a field. Hence physical chrono-and-information field is under consideration. Animals are more familiar with such a field than human. Evolutionary process experienced with possibility of extremal development of contact with such a field using highest primates. This mode of evolution appeared to stay obscure producing probable species "Wildman" (Bigfoot). Specific adaptive fitches suggest impossibility to study of such a species by usual ecological approaches. The perspective way for study of mysterious phenomena of physic is researches of this field characters.

  2. Alpha Oscillations during Incidental Encoding Predict Subsequent Memory for New "Foil" Information.

    Science.gov (United States)

    Vogelsang, David A; Gruber, Matthias; Bergström, Zara M; Ranganath, Charan; Simons, Jon S

    2018-05-01

    People can employ adaptive strategies to increase the likelihood that previously encoded information will be successfully retrieved. One such strategy is to constrain retrieval toward relevant information by reimplementing the neurocognitive processes that were engaged during encoding. Using EEG, we examined the temporal dynamics with which constraining retrieval toward semantic versus nonsemantic information affects the processing of new "foil" information encountered during a memory test. Time-frequency analysis of EEG data acquired during an initial study phase revealed that semantic compared with nonsemantic processing was associated with alpha decreases in a left frontal electrode cluster from around 600 msec after stimulus onset. Successful encoding of semantic versus nonsemantic foils during a subsequent memory test was related to decreases in alpha oscillatory activity in the same left frontal electrode cluster, which emerged relatively late in the trial at around 1000-1600 msec after stimulus onset. Across participants, left frontal alpha power elicited by semantic processing during the study phase correlated significantly with left frontal alpha power associated with semantic foil encoding during the memory test. Furthermore, larger left frontal alpha power decreases elicited by semantic foil encoding during the memory test predicted better subsequent semantic foil recognition in an additional surprise foil memory test, although this effect did not reach significance. These findings indicate that constraining retrieval toward semantic information involves reimplementing semantic encoding operations that are mediated by alpha oscillations and that such reimplementation occurs at a late stage of memory retrieval, perhaps reflecting additional monitoring processes.

  3. Digital contract approach for consistent and predictable multimedia information delivery in electronic commerce

    Science.gov (United States)

    Konana, Prabhudev; Gupta, Alok; Whinston, Andrew B.

    1997-01-01

    A pure 'technological' solution to network quality problems is incomplete since any benefits from new technologies are offset by the demand from exponentially growing electronic commerce ad data-intensive applications. SInce an economic paradigm is implicit in electronic commerce, we propose a 'market-system' approach to improve quality of service. Quality of service for digital products takes on a different meaning since users view quality of service differently and value information differently. We propose a framework for electronic commerce that is based on an economic paradigm and mass-customization, and works as a wide-area distributed management system. In our framework, surrogate-servers act as intermediaries between information provides and end- users, and arrange for consistent and predictable information delivery through 'digital contracts.' These contracts are negotiated and priced based on economic principles. Surrogate servers pre-fetched, through replication, information from many different servers and consolidate based on demand expectations. In order to recognize users' requirements and process requests accordingly, real-time databases are central to our framework. We also propose that multimedia information be separated into slowly changing and rapidly changing data streams to improve response time requirements. Surrogate- servers perform the tasks of integration of these data streams that is transparent to end-users.

  4. New technical functions for WSPEEDI: Worldwide version of System for Prediction of Environmental Emergency Dose Information

    International Nuclear Information System (INIS)

    Chino, Masamichi; Nagai, Haruyasu; Furuno, Akiko; Kitabata, Hideyuki; Yamazawa, Hiromi

    2000-01-01

    The Worldwide version of System for Prediction of Environmental Emergency Dose Information (WSPEEDI) at Japan Atomic Energy Research Institute (JAERI) is a computer-based system for providing real-time, world-wide, assessment of radiological impact due to nuclear emergencies. Since JAERI started the developpement of the system in 1980, various components of the system, e.g., three-dimensional atmospheric models, databases, data acquisition network, graphics, etc., have been integrated. The objective area has been also extended from local area for domestic nuclear incidents to hemispheric area for foreign ones. Furthermore, through the validation, exercises and responses to real events during the last decade, the following three state-of-the-art functions are under construction. (1) Construction of prototype international data communications network: For quick exchange of atmospheric modeling products and environmental data during emergency among world-wide emergency response systems, JAERI and Lawrence Livermore National Laboratory started a prototype information exchange protocol between WSPEEDI and the Atmospheric Release Advisory Capability ARAC. The network consists of the Web site/browser portion and the video-teleconferencing tool. The network has been utilized for a fire accident at bituminization plant for radioactive wastes of the former Power Reactor and Nuclear Fuel Development Corporation in March, 1997 and Argeciras incident in Spain occurred in May, 1998. (2) Development of synoptic hydrodynamic model: At present, WSPEEDI simply parameterizes the turbulence diffusion and precipitation scavenging, because information on the boundary layer, cloud and precipitation is insufficient in available global forecasts. Thus, to provide WSPEEDI with such information, this study aims to introduce a hydrodynamic model into WSPEEDI, which can predict boundary layer processes and moist processes, e.g., cloud formation and precipitation processes. (3) Development of

  5. Fair value versus historical cost-based valuation for biological assets: predictability of financial information

    Directory of Open Access Journals (Sweden)

    Josep M. Argilés

    2011-08-01

    This paper performs an empirical study with a sample of Spanish farms valuing biological assets at HC and a sample applying FV, finding no significant differences between both valuation methods to assess future cash flows. However, most tests reveal more predictive power of future earnings under fair valuation of biological assets, which is not explained by differences in volatility of earnings and profitability. The study also evidences the existence of flawed HC accounting practices for biological assets in agriculture, which suggests scarce information content of this valuation method in the predominant small business units existing in the agricultural sector in advanced Western countries.

  6. Predicting protein folding rate change upon point mutation using residue-level coevolutionary information.

    Science.gov (United States)

    Mallik, Saurav; Das, Smita; Kundu, Sudip

    2016-01-01

    Change in folding kinetics of globular proteins upon point mutation is crucial to a wide spectrum of biological research, such as protein misfolding, toxicity, and aggregations. Here we seek to address whether residue-level coevolutionary information of globular proteins can be informative to folding rate changes upon point mutations. Generating residue-level coevolutionary networks of globular proteins, we analyze three parameters: relative coevolution order (rCEO), network density (ND), and characteristic path length (CPL). A point mutation is considered to be equivalent to a node deletion of this network and respective percentage changes in rCEO, ND, CPL are found linearly correlated (0.84, 0.73, and -0.61, respectively) with experimental folding rate changes. The three parameters predict the folding rate change upon a point mutation with 0.031, 0.045, and 0.059 standard errors, respectively. © 2015 Wiley Periodicals, Inc.

  7. Stock return predictability and market integration: The role of global and local information

    Directory of Open Access Journals (Sweden)

    David G. McMillan

    2016-12-01

    Full Text Available This paper examines the predictability of a range of international stock markets where we allow the presence of both local and global predictive factors. Recent research has argued that US returns have predictive power for international stock returns. We expand this line of research, following work on market integration, to include a more general definition of the global factor, based on principal components analysis. Results identify three global expected returns factors, one related to the major stock markets of the US, UK and Asia and one related to the other markets analysed. The third component is related to dividend growth. A single dominant realised returns factor is also noted. A forecasting exercise comparing the principal components based factors to a US return factor and local market only factors, as well as the historical mean benchmark finds supportive evidence for the former approach. It is hoped that the results from this paper will be informative on three counts. First, to academics interested in understanding the dynamics asset price movement. Second, to market participants who aim to time the market and engage in portfolio and risk management. Third, to those (policy makers and others who are interested in linkages across international markets and the nature and degree of integration.

  8. Information Mining from Heterogeneous Data Sources: A Case Study on Drought Predictions

    Directory of Open Access Journals (Sweden)

    Getachew B. Demisse

    2017-07-01

    Full Text Available The objective of this study was to develop information mining methodology for drought modeling and predictions using historical records of climate, satellite, environmental, and oceanic data. The classification and regression tree (CART approach was used for extracting drought episodes at different time-lag prediction intervals. Using the CART approach, a number of successful model trees were constructed, which can easily be interpreted and used by decision makers in their drought management decisions. The regression rules produced by CART were found to have correlation coefficients from 0.71–0.95 in rules-alone modeling. The accuracies of the models were found to be higher in the instance and rules model (0.77–0.96 compared to the rules-alone model. From the experimental analysis, it was concluded that different combinations of the nearest neighbor and committee models significantly increase the performances of CART drought models. For more robust results from the developed methodology, it is recommended that future research focus on selecting relevant attributes for slow-onset drought episode identification and prediction.

  9. Prediction of Groundwater Arsenic Contamination using Geographic Information System and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Md. Moqbul Hossain

    2013-01-01

    Full Text Available Ground water arsenic contamination is a well known health and environmental problem in Bangladesh. Sources of this heavy metal are known to be geogenic, however, the processes of its release into groundwater are poorly understood phenomena. In quest of mitigation of the problem it is necessary to predict probable contamination before it causes any damage to human health. Hence our research has been carried out to find the factor relations of arsenic contamination and develop an arsenic contamination prediction model. Researchers have generally agreed that the elevated concentration of arsenic is affected by several factors such as soil reaction (pH, organic matter content, geology, iron content, etc. However, the variability of concentration within short lateral and vertical intervals, and the inter-relationships of variables among themselves, make the statistical analyses highly non-linear and difficult to converge with a meaningful relationship. Artificial Neural Networks (ANN comes in handy for such a black box type problem. This research uses Back propagation Neural Networks (BPNN to train and validate the data derived from Geographic Information System (GIS spatial distribution grids. The neural network architecture with (6-20-1 pattern was able to predict the arsenic concentration with reasonable accuracy.

  10. Multiple genetic interaction experiments provide complementary information useful for gene function prediction.

    Directory of Open Access Journals (Sweden)

    Magali Michaut

    Full Text Available Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.

  11. Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information

    Science.gov (United States)

    Dolloff, John; Hottel, Bryant; Edwards, David; Theiss, Henry; Braun, Aaron

    2017-05-01

    This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.

  12. Guaranteeing uptime at worl's largest particle physics lab

    CERN Multimedia

    Brodkin, Jon

    2007-01-01

    "As the European agency CERN was gearing up to build the world's largest particle accelerator, officials there knew they could not afford to have problems in their technical infrastructure cause any downtime." (1 page)

  13. Soliciting scientific information and beliefs in predictive modeling and adaptive management

    Science.gov (United States)

    Glynn, P. D.; Voinov, A. A.; Shapiro, C. D.

    2015-12-01

    Post-normal science requires public engagement and adaptive corrections in addressing issues with high complexity and uncertainty. An adaptive management framework is presented for the improved management of natural resources and environments through a public participation process. The framework solicits the gathering and transformation and/or modeling of scientific information but also explicitly solicits the expression of participant beliefs. Beliefs and information are compared, explicitly discussed for alignments or misalignments, and ultimately melded back together as a "knowledge" basis for making decisions. An effort is made to recognize the human or participant biases that may affect the information base and the potential decisions. In a separate step, an attempt is made to recognize and predict the potential "winners" and "losers" (perceived or real) of any decision or action. These "winners" and "losers" include present human communities with different spatial, demographic or socio-economic characteristics as well as more dispersed or more diffusely characterized regional or global communities. "Winners" and "losers" may also include future human communities as well as communities of other biotic species. As in any adaptive management framework, assessment of predictions, iterative follow-through and adaptation of policies or actions is essential, and commonly very difficult or impossible to achieve. Recognizing beforehand the limits of adaptive management is essential. More generally, knowledge of the behavioral and economic sciences and of ethics and sociology will be key to a successful implementation of this adaptive management framework. Knowledge of biogeophysical processes will also be essential, but by definition of the issues being addressed, will always be incomplete and highly uncertain. The human dimensions of the issues addressed and the participatory processes used carry their own complexities and uncertainties. Some ideas and principles are

  14. Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

    Science.gov (United States)

    Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

    2009-06-27

    A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient

  15. Triangle network motifs predict complexes by complementing high-error interactomes with structural information

    Directory of Open Access Journals (Sweden)

    Labudde Dirk

    2009-06-01

    Full Text Available Abstract Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS. PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that

  16. Informant-reported cognitive symptoms that predict amnestic mild cognitive impairment

    Directory of Open Access Journals (Sweden)

    Malek-Ahmadi Michael

    2012-02-01

    Full Text Available Abstract Background Differentiating amnestic mild cognitive impairment (aMCI from normal cognition is difficult in clinical settings. Self-reported and informant-reported memory complaints occur often in both clinical groups, which then necessitates the use of a comprehensive neuropsychological examination to make a differential diagnosis. However, the ability to identify cognitive symptoms that are predictive of aMCI through informant-based information may provide some clinical utility in accurately identifying individuals who are at risk for developing Alzheimer's disease (AD. Methods The current study utilized a case-control design using data from an ongoing validation study of the Alzheimer's Questionnaire (AQ, an informant-based dementia assessment. Data from 51 cognitively normal (CN individuals participating in a brain donation program and 47 aMCI individuals seen in a neurology practice at the same institute were analyzed to determine which AQ items differentiated aMCI from CN individuals. Results Forward stepwise multiple logistic regression analysis which controlled for age and education showed that 4 AQ items were strong indicators of aMCI which included: repetition of statements and/or questions [OR 13.20 (3.02, 57.66]; trouble knowing the day, date, month, year, and time [OR 17.97 (2.63, 122.77]; difficulty managing finances [OR 11.60 (2.10, 63.99]; and decreased sense of direction [OR 5.84 (1.09, 31.30]. Conclusions Overall, these data indicate that certain informant-reported cognitive symptoms may help clinicians differentiate individuals with aMCI from those with normal cognition. Items pertaining to repetition of statements, orientation, ability to manage finances, and visuospatial disorientation had high discriminatory power.

  17. An Information Retrieval Approach for Robust Prediction of Road Surface States.

    Science.gov (United States)

    Park, Jae-Hyung; Kim, Kwanho

    2017-01-28

    Recently, due to the increasing importance of reducing severe vehicle accidents on roads (especially on highways), the automatic identification of road surface conditions, and the provisioning of such information to drivers in advance, have recently been gaining significant momentum as a proactive solution to decrease the number of vehicle accidents. In this paper, we firstly propose an information retrieval approach that aims to identify road surface states by combining conventional machine-learning techniques and moving average methods. Specifically, when signal information is received from a radar system, our approach attempts to estimate the current state of the road surface based on the similar instances observed previously based on utilizing a given similarity function. Next, the estimated state is then calibrated by using the recently estimated states to yield both effective and robust prediction results. To validate the performances of the proposed approach, we established a real-world experimental setting on a section of actual highway in South Korea and conducted a comparison with the conventional approaches in terms of accuracy. The experimental results show that the proposed approach successfully outperforms the previously developed methods.

  18. Numerical approximation abilities correlate with and predict informal but not formal mathematics abilities.

    Science.gov (United States)

    Libertus, Melissa E; Feigenson, Lisa; Halberda, Justin

    2013-12-01

    Previous research has found a relationship between individual differences in children's precision when nonverbally approximating quantities and their school mathematics performance. School mathematics performance emerges from both informal (e.g., counting) and formal (e.g., knowledge of mathematics facts) abilities. It remains unknown whether approximation precision relates to both of these types of mathematics abilities. In the current study, we assessed the precision of numerical approximation in 85 3- to 7-year-old children four times over a span of 2years. In addition, at the final time point, we tested children's informal and formal mathematics abilities using the Test of Early Mathematics Ability (TEMA-3). We found that children's numerical approximation precision correlated with and predicted their informal, but not formal, mathematics abilities when controlling for age and IQ. These results add to our growing understanding of the relationship between an unlearned nonsymbolic system of quantity representation and the system of mathematics reasoning that children come to master through instruction. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information.

    Science.gov (United States)

    Panwar, Bharat; Gupta, Sudheer; Raghava, Gajendra P S

    2013-02-07

    The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of 0.53, 0.48, 0.61, 0

  20. Genome-Wide Prediction of SH2 Domain Targets Using Structural Information and the FoldX Algorithm

    DEFF Research Database (Denmark)

    Sanchez, Ignacio E.; Beltrao, Pedro; Stricher, Francois

    2008-01-01

    validated the predictions using literature-derived SH2 interactions and a probabilistic score obtained from a naive Bayes integration of information on coexpression, conservation of the interaction in other species, shared interaction partners, and functions. We show how our predictions lead to a new...

  1. Information-Based Maintenance Optimization with Focus on Predictive Maintenance (Informatiegebaseerde onderhoudsoptimalisatie met focus op predictief onderhoud)

    OpenAIRE

    Van Horenbeek, Adriaan

    2013-01-01

    This dissertation presents an information-based maintenance optimization methodology for physical assets; with focus on, but not limited to, predictive maintenance (PdM). The overall concept of information-based maintenance is that of updating maintenance decisions based on evolving knowledge of operation history and anticipated usage of the machinery, as well as the physics and dynamics of material degradation in critical machinery components. Within this concept, predictive maintenance is a...

  2. Transforming Atmospheric and Remotely-Sensed Information to Hydrologic Predictability in South Asia

    Science.gov (United States)

    Hopson, T. M.; Riddle, E. E.; Broman, D.; Brakenridge, G. R.; Birkett, C. M.; Kettner, A.; Sampson, K. M.; Boehnert, J.; Priya, S.; Collins, D. C.; Rostkier-Edelstein, D.; Young, W.; Singh, D.; Islam, A. S.

    2017-12-01

    South Asia is a flashpoint for natural disasters with profound societal impacts for the region and globally. Although close to 40% of the world's population depends on the Greater Himalaya's great rivers, $20 Billion of GDP is affected by river floods each year. The frequent occurrence of floods, combined with large and rapidly growing populations with high levels of poverty, make South Asia highly susceptible to humanitarian disasters. The challenges of mitigating such devastating disasters are exacerbated by the limited availability of real-time rain and stream gauge measuring stations and transboundary data sharing, and by constrained institutional commitments to overcome these challenges. To overcome such limitations, India and the World Bank have committed resources to the National Hydrology Project III, with the development objective to improve the extent, quality, and accessibility of water resources information and to strengthen the capacity of targeted water resources management institutions in India. The availability and application of remote sensing products and weather forecasts from ensemble prediction systems (EPS) have transformed river forecasting capability over the last decade, and is of interest to India. In this talk, we review the potential predictability of river flow contributed by some of the freely-available remotely-sensed and weather forecasting products within the framework of the physics of water migration through a watershed. Our specific geographical context is the Ganges, Brahmaputra, and Meghna river basin and a newly-available set of stream gauge measurements located over the region. We focus on satellite rainfall estimation, river height and width estimation, and EPS weather forecasts. For the later, we utilize the THORPEX-TIGGE dataset of global forecasts, and discuss how atmospheric predictability, as measured by an EPS, is transformed into hydrometeorological predictability. We provide an overview of the strengths and

  3. Geographical information system and predictive risk maps of urinary schistosomiasis in Ogun State, Nigeria

    Directory of Open Access Journals (Sweden)

    Solarin Adewale RT

    2008-05-01

    Full Text Available Abstract Background The control of urinary schistosomiasis in Ogun State, Nigeria remains inert due to lack of reliable data on the geographical distribution of the disease and the population at risk. To help in developing a control programme, delineating areas of risk, geographical information system and remotely sensed environmental images were used to developed predictive risk maps of the probability of occurrence of the disease and quantify the risk for infection in Ogun State, Nigeria. Methods Infection data used were derived from carefully validated morbidity questionnaires among primary school children in 2001–2002, in which school children were asked among other questions if they have experienced "blood in urine" or urinary schistosomiasis. The infection data from 1,092 schools together with remotely sensed environmental data such as rainfall, vegetation, temperature, soil-types, altitude and land cover were analysis using binary logistic regression models to identify environmental features that influence the spatial distribution of the disease. The final regression equations were then used in Arc View 3.2a GIS software to generate predictive risk maps of the distribution of the disease and population at risk in the state. Results Logistic regression analysis shows that the only significant environmental variable in predicting the presence and absence of urinary schistosomiasis in any area of the State was Land Surface Temperature (LST (B = 0.308, p = 0.013. While LST (B = -0.478, p = 0.035, rainfall (B = -0.006, p = 0.0005, ferric luvisols (B = 0.539, p = 0.274, dystric nitosols (B = 0.133, p = 0.769 and pellic vertisols (B = 1.386, p = 0.008 soils types were the final variables in the model for predicting the probability of an area having an infection prevalence equivalent to or more than 50%. The two predictive risk maps suggest that urinary schistosomiasis is widely distributed and occurring in all the Local Government Areas (LGAs

  4. Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions.

    Directory of Open Access Journals (Sweden)

    Torre J Hovick

    Full Text Available The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003-2011 of Greater Prairie-Chicken (Tympanuchus cupido lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (0.81, indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures. Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern.

  5. Predicting summer residential electricity demand across the U.S.A using climate information

    Science.gov (United States)

    Sun, X.; Wang, S.; Lall, U.

    2017-12-01

    We developed a Bayesian Hierarchical model to predict monthly residential per capita electricity consumption at the state level across the USA using climate information. The summer period was selected since cooling requirements may be directly associated with electricity use, while for winter a mix of energy sources may be used to meet heating needs. Historical monthly electricity consumption data from 1990 to 2013 were used to build a predictive model with a set of corresponding climate and non-climate covariates. A clustering analysis was performed first to identify groups of states that had similar temporal patterns for the cooling degree days of each state. Then, a partial pooling model was applied to each cluster to assess the sensitivity of monthly per capita residential electricity demand to each predictor (including cooling-degree-days, gross domestic product (GDP) per capita, per capita electricity demand of previous month and previous year, and the residential electricity price). The sensitivity of residential electricity to cooling-degree-days has an identifiable geographic distribution with higher values in northeastern United States.

  6. A predictive model to inform adaptive management of double-crested cormorants and fisheries in Michigan

    Science.gov (United States)

    Tsehaye, Iyob; Jones, Michael L.; Irwin, Brian J.; Fielder, David G.; Breck, James E.; Luukkonen, David R.

    2015-01-01

    The proliferation of double-crested cormorants (DCCOs; Phalacrocorax auritus) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a deterministic predictive model representing bird–fish interactions to inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately reconstruct past DCCO population dynamics. These comparisons helped discriminate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future research and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in Michigan and that DCCO control may be necessary to achieve management goals for some DCCO-impacted fisheries in the state. Finally, our model can be extended by accounting for parametric or ecological uncertainty and including more complex assumptions on DCCO–fish interactions as part of the adaptive management process.

  7. Unrequested information from routine diagnostic chest CT predicts future cardiovascular events

    International Nuclear Information System (INIS)

    Jacobs, Peter C.; Gondrie, Martijn J.; Grobbee, Diederick E.; Graaf, Yolanda van der; Mali, Willem P.; Oen, Ayke L.; Prokop, Mathias

    2011-01-01

    An increase in the number of CT investigations will likely result in a an increase in unrequested information. Clinical relevance of these findings is unknown. This is the first follow-up study to investigate the prognostic relevance of subclinical coronary (CAC) and aortic calcification (TAC) as contained in routine diagnostic chest CT in a clinical care population. The follow-up of 10,410 subjects (>40 years) from a multicentre, clinical care-based cohort of patients included 240 fatal to 275 non-fatal cardiovascular disease (CVD) events (mean follow-up 17.8 months). Patients with a history of CVD were excluded. Coronary (0-12) and aortic calcification (0-8) were semi-quantitatively scored. We used Cox proportional-hazard models to compute hazard ratios to predict CVD events. CAC and TAC were significantly and independently predictive of CVD events. Compared with subjects with no calcium, the adjusted risk of a CVD event was 3.7 times higher (95% CI, 2.7-5.2) among patients with severe coronary calcification (CAC score ≥6) and 2.7 times higher (95% CI, 2.0-3.7) among patients with severe aortic calcification (TAC score ≥5). Subclinical vascular calcification on CT is a strong predictor of incident CVD events in a routine clinical care population. (orig.)

  8. Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows.

    Directory of Open Access Journals (Sweden)

    Nina Melzer

    Full Text Available In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach. To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317 SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype.

  9. Prediction of the human response time with the similarity and quantity of information

    International Nuclear Information System (INIS)

    Lee, Sungjin; Heo, Gyunyoung; Chang, Soon Heung

    2006-01-01

    Memory is one of brain processes that are important when trying to understand how people process information. Although a large number of studies have been made on the human performance, little is known about the similarity effect in human performance. The purpose of this paper is to propose and validate the quantitative and predictive model on the human response time in the user interface with the concept of similarity. However, it is not easy to explain the human performance with only similarity or information amount. We are confronted by two difficulties: making the quantitative model on the human response time with the similarity and validating the proposed model by experimental work. We made the quantitative model based on the Hick's law and the law of practice. In addition, we validated the model with various experimental conditions by measuring participants' response time in the environment of computer-based display. Experimental results reveal that the human performance is improved by the user interface's similarity. We think that the proposed model is useful for the user interface design and evaluation phases

  10. The predictive model on the user reaction time using the information similarity

    International Nuclear Information System (INIS)

    Lee, Sung Jin; Heo, Gyun Young; Chang, Soon Heung

    2005-01-01

    Human performance is frequently degraded because people forget. Memory is one of brain processes that are important when trying to understand how people process information. Although a large number of studies have been made on the human performance, little is known about the similarity effect in human performance. The purpose of this paper is to propose and validate the quantitative and predictive model on the human response time in the user interface with the concept of similarity. However, it is not easy to explain the human performance with only similarity or information amount. We are confronted by two difficulties: making the quantitative model on the human response time with the similarity and validating the proposed model by experimental work. We made the quantitative model based on the Hick's law and the law of practice. In addition, we validated the model with various experimental conditions by measuring participants' response time in the environment of computer-based display. Experimental results reveal that the human performance is improved by the user interface's similarity. We think that the proposed model is useful for the user interface design and evaluation phases

  11. Geographical information system (GIS) application for flood prediction at Sungai Sembrong

    Science.gov (United States)

    Kamin, Masiri; Ahmad, Nor Farah Atiqah; Razali, Siti Nooraiin Mohd; Hilaham, Mashuda Mohamad; Rahman, Mohamad Abdul; Ngadiman, Norhayati; Sahat, Suhaila

    2017-10-01

    The occurrence of flood is one of natural disaster that often beset Malaysia. The latest incident that happened in 2007 was the worst occurrence of floods ever be set in Johor. Reporting floods mainly focused on rising water rising levels, so about once a focus on the area of flood delineation. A study focused on the effectiveness of using Geographic Information System (GIS) to predict the flood by taking Sg. Sembrong, Batu Pahat, Johor as study area. This study combined hydrological model and water balance model in the display to show the expected flood area for future reference. The minimum, maximum and average rainfall data for January 2007 at Sg Sembrong were used in this study. The data shows that flood does not occurs at the minimum and average rainfall of 17.2mm and 2mm respectively. At maximum rainfall, 203mm, shows the flood area was 9983 hectares with the highest level of the water depth was 2m. The result showed that the combination of hydrological models and water balance model in GIS is very suitable to be used as a tool to obtain preliminary information on flood immediately. Besides that, GIS system is a very powerful tool used in hydrology engineering to help the engineer and planner to imagine the real situation of flood events, doing flood analysis, problem solving and provide a rational, accurate and efficient decision making.

  12. Joint Asymptotic Distributions of Smallest and Largest Insurance Claims

    Directory of Open Access Journals (Sweden)

    Hansjörg Albrecher

    2014-07-01

    Full Text Available Assume that claims in a portfolio of insurance contracts are described by independent and identically distributed random variables with regularly varying tails and occur according to a near mixed Poisson process. We provide a collection of results pertaining to the joint asymptotic Laplace transforms of the normalised sums of the smallest and largest claims, when the length of the considered time interval tends to infinity. The results crucially depend on the value of the tail index of the claim distribution, as well as on the number of largest claims under consideration.

  13. Challenges with the largest commercial hydrogen station in the world

    Energy Technology Data Exchange (ETDEWEB)

    Charbonneau, Thomas; Gauthier, Pierre [Air Liquide Canada (Canada)

    2010-07-01

    This abstract's objective is to share with the participants the story of the largest hydrogen fueling station made to this date and to kick-start the story, we will cover the challenges; first the technical ones; the operational ones; the distribution ones and; the financial ones. We will then move on to review the logistic (geographic) issues raised by the project and conclude our presentation by sharing the output values of the largest fueling station built so far in the world. (orig.)

  14. What Predicts Online Health Information-Seeking Behavior Among Egyptian Adults? A Cross-Sectional Study.

    Science.gov (United States)

    Ghweeba, Mayada; Lindenmeyer, Antje; Shishi, Sobhi; Abbas, Mostafa; Waheed, Amani; Amer, Shaymaa

    2017-06-22

    Over the last decade, the Internet has become an important source of health-related information for a wide range of users worldwide. Yet, little is known about the personal characteristics of Egyptian Internet users who search for online health information (OHI). The aim of the study was to identify the personal characteristics of Egyptian OHI seekers and to determine any associations between their personal characteristics and their health information-seeking behavior.  This cross-sectional questionnaire study was conducted from June to October 2015. A Web-based questionnaire was sent to Egyptian users aged 18 years and older (N=1400) of a popular Arabic-language health information website. The questionnaire included (1) demographic characteristics; (2) self-reported general health status; and (3) OHI-seeking behavior that included frequency of use, different topics sought, and self-reported impact of obtained OHI on health behaviors. Data were analyzed using descriptive statistics and multiple regression analysis. A total of 490 participants completed the electronic questionnaire with a response rate equivalent to 35.0% (490/1400). Regarding personal characteristics, 57.1% (280/490) of participants were females, 63.4% (311/490) had a university level qualification, and 37.1% (182/490) had a chronic health problem. The most commonly sought OHI by the participants was nutrition-related. Results of the multiple regression analysis showed that 31.0% of the variance in frequency of seeking OHI among Egyptian adults can be predicted by personal characteristics. Participants who sought OHI more frequently were likely to be female, of younger age, had higher education levels, and good self-reported general health. Our results provide insights into personal characteristics and OHI-seeking behaviors of Egyptian OHI users. This will contribute to better recognize their needs, highlight ways to increase the availability of appropriate OHI, and may lead to the

  15. What kinds of fish stock predictions do we need and what kinds of information will help us to make better predictions?

    Directory of Open Access Journals (Sweden)

    Keith Brander

    2003-04-01

    Full Text Available Fish stock predictions are used to guide fisheries management, but stocks continue to be over-exploited. Traditional single-species age-structured stock assessment models, which became an operational component of fisheries management in the 1950s, ignore biological and environmental effects. As our knowledge of the marine environment improves and our concern about the state of the marine ecosystem and about global change increases, the scope of our models needs to be widened. We need different kinds of predictions as well as better predictions. Population characteristics (rates of mortality, growth, recruitment of 61 stocks of 17 species of NE Atlantic fish are reviewed in order to consider the implications for the time-scale and quality of stock predictions. Short life expectancy limits the time horizon for predictability based on the current fishable stock and predictions are therefore more dependent on estimates or assumptions about future rates. Evidence is presented that rates of growth and recruitment are influenced by environmental factors and possibilities for including new information are explored in order to improve predictions.

  16. Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information

    Directory of Open Access Journals (Sweden)

    Panwar Bharat

    2013-02-01

    Full Text Available Abstract Background The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. Results In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL. It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i vitamin interacting residues (VIRs, (ii vitamin-A interacting residues (VAIRs, (iii vitamin-B interacting residues (VBIRs and (iv pyridoxal-5-phosphate (vitamin B6 interacting residues (PLPIRs have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM features of protein sequences. Finally, we selected best performing SVM modules and

  17. NAFTA: The World's Largest Trading Zone Turns 20

    Science.gov (United States)

    Ferrarini, Tawni Hunt; Day, Stephen

    2014-01-01

    Everyone under the age of 20 who has grown up in North America has lived in the common market created by NAFTA--the North American Free Trade Agreement. In a zone linking the United States, Canada, and Mexico, most goods and investments flow freely across borders to users, consumers, and investors. In 1994, NAFTA created the largest relatively…

  18. Building Earth's Largest Library: Driving into the Future.

    Science.gov (United States)

    Coffman, Steve

    1999-01-01

    Examines the Amazon.com online bookstore as a blueprint for designing the world's largest library. Topics include selection; accessibility and convenience; quality of Web sites and search tools; personalized service; library collection development, including interlibrary loan; library catalogs and catalog records; a circulation system; costs;…

  19. Analysis of Human Standing Balance by Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Kun Liu

    2015-01-01

    Full Text Available The purpose of this research is to analyse the relationship between nonlinear dynamic character and individuals’ standing balance by the largest Lyapunov exponent, which is regarded as a metric for assessing standing balance. According to previous study, the largest Lyapunov exponent from centre of pressure time series could not well quantify the human balance ability. In this research, two improvements were made. Firstly, an external stimulus was applied to feet in the form of continuous horizontal sinusoidal motion by a moving platform. Secondly, a multiaccelerometer subsystem was adopted. Twenty healthy volunteers participated in this experiment. A new metric, coordinated largest Lyapunov exponent was proposed, which reflected the relationship of body segments by integrating multidimensional largest Lyapunov exponent values. By using this metric in actual standing performance under sinusoidal stimulus, an obvious relationship between the new metric and the actual balance ability was found in the majority of the subjects. These results show that the sinusoidal stimulus can make human balance characteristics more obvious, which is beneficial to assess balance, and balance is determined by the ability of coordinating all body segments.

  20. Worlds largest particle physics laboratory selects Proxim Wireless Mesh

    CERN Multimedia

    2007-01-01

    "Proxim Wireless has announced that the European Organization for Nuclear Research (CERN), the world's largest particle physics laboratory and the birthplace of the World Wide Web, is using it's ORiNOCO AP-4000 mesh access points to extend the range of the laboratory's Wi-Fi network and to provide continuous monitoring of the lab's calorimeters" (1/2 page)

  1. PNNL supercomputer to become largest computing resource on the Grid

    CERN Multimedia

    2002-01-01

    Hewlett Packard announced that the US DOE Pacific Northwest National Laboratory will connect a 9.3-teraflop HP supercomputer to the DOE Science Grid. This will be the largest supercomputer attached to a computer grid anywhere in the world (1 page).

  2. Toward sustainable harvesting of Africa's largest medicinal plant ...

    African Journals Online (AJOL)

    Global demand for treating prostate disorders with Prunus africana bark extract has made P. africana Africa's largest medicinal plant export. Unsustainable harvesting practices can lead to local extirpations of this multipurpose tree. Survey research targeting P. africana harvesters in a Tanzania forest reserve revealed that ...

  3. Human Factors Predicting Failure and Success in Hospital Information System Implementations in Sub-Saharan Africa.

    Science.gov (United States)

    Verbeke, Frank; Karara, Gustave; Nyssen, Marc

    2015-01-01

    From 2007 through 2014, the authors participated in the implementation of open source hospital information systems (HIS) in 19 hospitals in Rwanda, Burundi, DR Congo, Congo-Brazzaville, Gabon, and Mali. Most of these implementations were successful, but some failed. At the end of a seven-year implementation effort, a number of risk factors, facilitators, and pragmatic approaches related to the deployment of HIS in Sub-Saharan health facilities have been identified. Many of the problems encountered during the HIS implementation process were not related to technical issues but human, cultural, and environmental factors. This study retrospectively evaluates the predictive value of 14 project failure factors and 15 success factors in HIS implementation in the Sub-Saharan region. Nine of the failure factors were strongly correlated with project failure, three were moderately correlated, and one weakly correlated. Regression analysis also confirms that eight factors were strongly correlated with project success, four moderately correlated, and two weakly correlated. The study results may help estimate the expedience of future HIS projects.

  4. NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.

    Directory of Open Access Journals (Sweden)

    Bent Petersen

    Full Text Available UNLABELLED: β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. CONCLUSION: The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.

  5. NetTurnP – Neural Network Prediction of Beta-turns by Use of Evolutionary Information and Predicted Protein Sequence Features

    Science.gov (United States)

    Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl

    2010-01-01

    β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC  = 0.50, Qtotal = 82.1%, sensitivity  = 75.6%, PPV  = 68.8% and AUC  = 0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17 – 0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. Conclusion The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences. PMID:21152409

  6. NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.

    Science.gov (United States)

    Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl

    2010-11-30

    β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.

  7. Temporal properties of seismicity and largest earthquakes in SE Carpathians

    Directory of Open Access Journals (Sweden)

    S. Byrdina

    2006-01-01

    Full Text Available In order to estimate the hazard rate distribution of the largest seismic events in Vrancea, South-Eastern Carpathians, we study temporal properties of historical and instrumental catalogues of seismicity. First, on the basis of Generalized Extreme Value theory we estimate the average return period of the largest events. Then, following Bak et al. (2002 and Corral (2005a, we study scaling properties of recurrence times between earthquakes in appropriate spatial volumes. We come to the conclusion that the seismicity is temporally clustered, and that the distribution of recurrence times is significantly different from a Poisson process even for times largely exceeding corresponding periods of foreshock and aftershock activity. Modeling the recurrence times by a gamma distributed variable, we finally estimate hazard rates with respect to the time elapsed from the last large earthquake.

  8. Worlds Largest Wave Energy Project 2007 in Wales

    DEFF Research Database (Denmark)

    Christensen, Lars; Friis-Madsen, Erik; Kofoed, Jens Peter

    2006-01-01

    This paper introduces world largest wave energy project being developed in Wales and based on one of the leading wave energy technologies. The background for the development of wave energy, the total resource ands its distribution around the world is described. In contrast to wind energy turbines...... Dragon has to be scaled in accordance with the wave climate at the deployment site, which makes the Welch demonstrator device the worlds largest WEC so far with a total width of 300 meters. The project budget, the construction methods and the deployment site are also given....... a large number of fundamentally different technologies are utilised to harvest wave energy. The Wave Dragon belongs to the wave overtopping class of converters and the paper describes the fundamentals and the technical solutions used in this wave energy converter. An offshore floating WEC like the Wave...

  9. Upgrade and modernization of the six largest HPPs in Macedonia

    International Nuclear Information System (INIS)

    Hadzievska, M.

    2002-01-01

    In 1998, Electric Power Company of Macedonia and the International Bank for Development and Reconstruction, started the Power System Improvement Project a part of which is the Project for rehabilitation of the six largest Hydro Power Plants (HPPs) in the Republic of Macedonia. The six largest Hydro Power Plants (HPP Vrutok, HPP Raven, HPP Globocica, HPP Tikves and HPP Spilje and HPP Vrben) represent 91% of the country's hydropower capacity. The rehabilitation program is divided in five parts (contracts) and covers the refurbishment of: turbine runners, turbine and generator bearings, governors, inlet valves; butterfly valves, including accessories and control systems; generators, excitation system and voltage regulation; control system, protection and LV auxiliaries; switch gears and control gears in 220 kV, 110 kV and 35 kV substations. At the moment, only the implementation of switch gears has started, the first phase is already finished, and 50 % of the rehabilitation works for HPP Vrutok, the largest HPP, has been finished. With the realization of this project, greater hydropower production is expected. It also expected that HPPs will become a more vital part of the Macedonian power system

  10. Kabob report. Pt. 3. Chevron plant largest in Canada

    Energy Technology Data Exchange (ETDEWEB)

    1971-01-18

    Canada's largest fully integrated primary natural- gas processing and sulfur recovery plant is heading for physical completion by mid-summer of 1971. The Ralph M. Parsons Construction Co. of Canada Ltd., contractor for the S. Kaybob Beaverhill Lake Unit No. 3 gas-processing plant, to be operated by Chevron Standard Ltd., estimates completion by June 30. After that the $80 million complex will have tests and running in time. With any reasonable luck, it should be fully on stream by late summer. Preliminary construction on the 200-acre site started in Jan. 1969 with clearing and contouring of the main plant and sulfur storage sites. Initial rough grading started in the early summer, after spring breakup was over. Delivery of most of the big items was made by rail because the local secondary roads were inadequate for them. Concrete has been a large item. The contractor has its own batch plant on the site for the estimated 28,000 cu yd which will be needed for the whole job. Dominating the construction site from the start has been the high sulfur plant stack, first of the major items to be finished. It will serve to dispose of effluent from the largest sulfur recovery unit in Canada. It is 465 ft high, one of the largest in Alberta, and a significant contribution to pollution control and environmental protection.

  11. NetTurnP – Neural Network Prediction of Beta-turns by Use of Evolutionary Information and Predicted Protein Sequence Features

    DEFF Research Database (Denmark)

    Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl

    2010-01-01

    is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino......β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method...... NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which...

  12. Information processing biases concurrently and prospectively predict depressive symptoms in adolescents: Evidence from a self-referent encoding task.

    Science.gov (United States)

    Connolly, Samantha L; Abramson, Lyn Y; Alloy, Lauren B

    2016-01-01

    Negative information processing biases have been hypothesised to serve as precursors for the development of depression. The current study examined negative self-referent information processing and depressive symptoms in a community sample of adolescents (N = 291, Mage at baseline = 12.34 ± 0.61, 53% female, 47.4% African-American, 49.5% Caucasian and 3.1% Biracial). Participants completed a computerised self-referent encoding task (SRET) and a measure of depressive symptoms at baseline and completed an additional measure of depressive symptoms nine months later. Several negative information processing biases on the SRET were associated with concurrent depressive symptoms and predicted increases in depressive symptoms at follow-up. Findings partially support the hypothesis that negative information processing biases are associated with depressive symptoms in a nonclinical sample of adolescents, and provide preliminary evidence that these biases prospectively predict increases in depressive symptoms.

  13. Using information from historical high-throughput screens to predict active compounds.

    Science.gov (United States)

    Riniker, Sereina; Wang, Yuan; Jenkins, Jeremy L; Landrum, Gregory A

    2014-07-28

    Modern high-throughput screening (HTS) is a well-established approach for hit finding in drug discovery that is routinely employed in the pharmaceutical industry to screen more than a million compounds within a few weeks. However, as the industry shifts to more disease-relevant but more complex phenotypic screens, the focus has moved to piloting smaller but smarter chemically/biologically diverse subsets followed by an expansion around hit compounds. One standard method for doing this is to train a machine-learning (ML) model with the chemical fingerprints of the tested subset of molecules and then select the next compounds based on the predictions of this model. An alternative approach would be to take advantage of the wealth of bioactivity information contained in older (full-deck) screens using so-called HTS fingerprints, where each element of the fingerprint corresponds to the outcome of a particular assay, as input to machine-learning algorithms. We constructed HTS fingerprints using two collections of data: 93 in-house assays and 95 publicly available assays from PubChem. For each source, an additional set of 51 and 46 assays, respectively, was collected for testing. Three different ML methods, random forest (RF), logistic regression (LR), and naïve Bayes (NB), were investigated for both the HTS fingerprint and a chemical fingerprint, Morgan2. RF was found to be best suited for learning from HTS fingerprints yielding area under the receiver operating characteristic curve (AUC) values >0.8 for 78% of the internal assays and enrichment factors at 5% (EF(5%)) >10 for 55% of the assays. The RF(HTS-fp) generally outperformed the LR trained with Morgan2, which was the best ML method for the chemical fingerprint, for the majority of assays. In addition, HTS fingerprints were found to retrieve more diverse chemotypes. Combining the two models through heterogeneous classifier fusion led to a similar or better performance than the best individual model for all assays

  14. Final Status Survey for the Largest Decommissioning Project on Earth

    International Nuclear Information System (INIS)

    Dubiel, R.W.; Miller, J.; Quayle, D.

    2006-01-01

    To assist the United States Department of Energy's (US DOE's) re-industrialization efforts at its gaseous diffusion site in Oak Ridge, Tennessee, known as the East Tennessee Technology Park (ETTP), the US DOE awarded a 6-year Decontamination and Decommissioning (D and D) contract to BNG America (formerly BNFL Inc.) in 1997. The ETTP 3-Building D and D Project included the removal and disposition of the materials and equipment from the K-33, K-31, and K-29 Gaseous Diffusion Plant buildings. The three buildings comprise more than 4.8 million square feet (446,000 square meters) of floor surface area and more than 350 million pounds (148 million kilograms) of hazardous and radioactively contaminated material, making it the largest nuclear D and D project in progress anywhere in the world. The logistical hurdles involved in a project of this scope and magnitude required an extensive amount of Engineering and Health Physics professionals. In order to accomplish the Final Status Survey (FSS) for a project of this scope, the speed and efficiency of automated survey equipment was essential. Surveys of floors, structural steel and ceilings up to 60 feet (18 meters) were required. The FSS had to be expanded to include additional remediation and surveys due to characterization surveys and assumptions regarding the nature and extent of contamination provided by the US DOE. Survey design and technical bases had to consider highly variable constituents; including uranium from depleted to low enrichment, variable levels of Technetium-99 and transuranic nuclides, which were introduced into the cascade during the 1960's when recycled uranium (RU) from Savannah River was re-enriched at the facility. The RU was transported to unexpected locations from leaks in the cascade by complex building ventilation patterns. The primary survey tool used for the post remediation and FSS was the Surface Contamination Monitor (SCM) and the associated Survey Information Management System (SIMS

  15. Towards flash flood prediction in the dry Dead Sea region utilizing radar rainfall information

    Science.gov (United States)

    Morin, E.; Jacoby, Y.; Navon, S.; Bet-Halachmi, E.

    2009-04-01

    Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model utilizing radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on five years of data for one of the catchments. Validation was performed for a subsequent five-year period for the same catchment and then for an entire ten year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood-warning model is feasible for catchments in the area studied.

  16. Towards flash-flood prediction in the dry Dead Sea region utilizing radar rainfall information

    Science.gov (United States)

    Morin, Efrat; Jacoby, Yael; Navon, Shilo; Bet-Halachmi, Erez

    2009-07-01

    Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model which utilizes radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on the 5 years of data for one of the catchments. Validation was performed for a subsequent 5-year period for the same catchment and then for an entire 10-year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood warning model is feasible for catchments in the area studied.

  17. fRMSDPred: Predicting Local RMSD Between Structural Fragments Using Sequence Information

    National Research Council Canada - National Science Library

    Rangwala, Huzefa; Karypis, George

    2007-01-01

    .... We present algorithms to solve this fragment-level RMSD prediction problem using a supervised learning framework based on support vector regression and classification that incorporates protein...

  18. Predicting Cancer Information Seeking Behaviors of Smokers, Former Smokers and Nonsmokers Using the 2012 Health Information National Trends Survey

    Science.gov (United States)

    Lee, Suekyung

    2013-01-01

    Cancer can be one of the most serious diseases that can result in a costly reduction in the quality of life. Among a number of cancer risk factors, tobacco use has been identified as the leading preventable cause of deaths. Prior research has suggested that cancer information seeking may be a pre-step to adopt health protective behaviors that can…

  19. Constraining the magnitude of the largest event in a foreshock-main shock-aftershock sequence

    Science.gov (United States)

    Shcherbakov, Robert; Zhuang, Jiancang; Ogata, Yosihiko

    2018-01-01

    Extreme value statistics and Bayesian methods are used to constrain the magnitudes of the largest expected earthquakes in a sequence governed by the parametric time-dependent occurrence rate and frequency-magnitude statistics. The Bayesian predictive distribution for the magnitude of the largest event in a sequence is derived. Two types of sequences are considered, that is, the classical aftershock sequences generated by large main shocks and the aftershocks generated by large foreshocks preceding a main shock. For the former sequences, the early aftershocks during a training time interval are used to constrain the magnitude of the future extreme event during the forecasting time interval. For the latter sequences, the earthquakes preceding the main shock are used to constrain the magnitudes of the subsequent extreme events including the main shock. The analysis is applied retrospectively to past prominent earthquake sequences.

  20. Cognitive factors predicting intentions to search for health information: an application of the theory of planned behaviour.

    Science.gov (United States)

    Austvoll-Dahlgren, Astrid; Falk, Ragnhild S; Helseth, Sølvi

    2012-12-01

    Peoples' ability to obtain health information is a precondition for their effective participation in decision making about health. However, there is limited evidence describing which cognitive factors can predict the intention of people to search for health information. To test the utility of a questionnaire in predicting intentions to search for health information, and to identify important predictors associated with this intention such that these could be targeted in an Intervention. A questionnaire was developed based on the Theory of Planned Behaviour and tested on both a mixed population sample (n=30) and a sample of parents (n = 45). The questionnaire was explored by testing for internal consistency, calculating inter-correlations between theoretically-related constructs, and by using multiple regression analysis. The reliability and validity of the questionnaire were found to be satisfactory and consistent across the two samples. The questionnaires' direct measures prediction of intention was high and accounted for 47% and 55% of the variance in behavioural intentions. Attitudes and perceived behavioural control were identified as important predictors to intention for search for health information. The questionnaire may be a useful tool for understanding and evaluating behavioural intentions and beliefs related to searches for health information. © 2012 The authors. Health Information and Libraries Journal © 2012 Health Libraries Group.

  1. Information needs, acceptability of risk, trust, and reliance: The case of National Predictive Services customers

    Science.gov (United States)

    Patricia L. Winter; Heidi. Bigler-Cole

    2010-01-01

    Making complex risk-related decisions involves a degree of uncertainty. How that uncertainty is addressed or presented in reports or data tables can be tailored to meet information users’ needs and preferences. Involving the recipients of risk-related information in the design of information to be delivered (including the types of information delivered, format, and...

  2. Information needs, acceptability of risk, trust, and reliance: the case of national predictive services customers

    Science.gov (United States)

    Patricia L. Winter; Heidi Bigler-Cole

    2010-01-01

    Making complex risk-related decisions involves a degree of uncertainty. How that uncertainty is addressed or presented in reports or data tables can be tailored to meet information users’ needs and preferences. Involving the recipients of risk-related information in the design of information to be delivered (including the types of information delivered, format, and...

  3. A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information.

    Science.gov (United States)

    Luo, Yunan; Zhao, Xinbin; Zhou, Jingtian; Yang, Jinglin; Zhang, Yanqing; Kuang, Wenhua; Peng, Jian; Chen, Ligong; Zeng, Jianyang

    2017-09-18

    The emergence of large-scale genomic, chemical and pharmacological data provides new opportunities for drug discovery and repositioning. In this work, we develop a computational pipeline, called DTINet, to predict novel drug-target interactions from a constructed heterogeneous network, which integrates diverse drug-related information. DTINet focuses on learning a low-dimensional vector representation of features, which accurately explains the topological properties of individual nodes in the heterogeneous network, and then makes prediction based on these representations via a vector space projection scheme. DTINet achieves substantial performance improvement over other state-of-the-art methods for drug-target interaction prediction. Moreover, we experimentally validate the novel interactions between three drugs and the cyclooxygenase proteins predicted by DTINet, and demonstrate the new potential applications of these identified cyclooxygenase inhibitors in preventing inflammatory diseases. These results indicate that DTINet can provide a practically useful tool for integrating heterogeneous information to predict new drug-target interactions and repurpose existing drugs.Network-based data integration for drug-target prediction is a promising avenue for drug repositioning, but performance is wanting. Here, the authors introduce DTINet, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations.

  4. Specifications, Pre-Experimental Predictions, and Test Plate Characterization Information for the Prometheus Critical Experiments

    International Nuclear Information System (INIS)

    ML Zerkle; ME Meyers; SM Tarves; JJ Powers

    2006-01-01

    This report provides specifications, pre-experimental predictions, and test plate characterization information for a series of molybdenum (Mo), niobium (Nb), rhenium (Re), tantalum (Ta), and baseline critical experiments that were developed by the Naval Reactors Prime Contractor Team (NRPCT) for the Prometheus space reactor development project. In March 2004, the Naval Reactors program was assigned the responsibility to develop, design, deliver, and operationally support civilian space nuclear reactors for NASA's Project Prometheus. The NRPCT was formed to perform this work and consisted of engineers and scientists from the Naval Reactors (NR) Program prime contractors: Bettis Atomic Power Laboratory, Knolls Atomic Power Laboratory (KAPL), and Bechtel Plant Machinery Inc (BPMI). The NRPCT developed a series of clean benchmark critical experiments to address fundamental uncertainties in the neutron cross section data for Mo, Nb, Re, and Ta in fast, intermediate, and mixed neutron energy spectra. These experiments were to be performed by Los Alamos National Laboratory (LANL) using the Planet vertical lift critical assembly machine and were designed with a simple, geometrically clean, cylindrical configuration consisting of alternating layers of test, moderator/reflector, and fuel materials. Based on reprioritization of missions and funding within NASA, Naval Reactors and NASA discontinued their collaboration on Project Prometheus in September 2005. One critical experiment and eighteen subcritical handstacking experiments were completed prior to the termination of work in September 2005. Information on the Prometheus critical experiments and the test plates produced for these experiments are expected to be of value to future space reactor development programs and to integral experiments designed to address the fundamental neutron cross section uncertainties for these refractory metals. This information is being provided as an orderly closeout of NRPCT work on Project

  5. Improving runoff prediction using agronomical information in a cropped, loess covered catchment

    NARCIS (Netherlands)

    Lefrancq, Marie; Van Dijk, Paul; Jetten, Victor; Schwob, Matthieu; Payraudeau, Sylvain

    2017-01-01

    Predicting runoff hot spots and hot-moments within a headwater crop-catchment is of the utmost importance to reduce adverse effects on aquatic ecosystems by adapting land use management to control runoff. Reliable predictions of runoff patterns during a crop growing season remain challenging. This

  6. Identifying and predicting subgroups of information needs among cancer patients: an initial study using latent class analysis.

    Science.gov (United States)

    Neumann, Melanie; Wirtz, Markus; Ernstmann, Nicole; Ommen, Oliver; Längler, Alfred; Edelhäuser, Friedrich; Scheffer, Christian; Tauschel, Diethard; Pfaff, Holger

    2011-08-01

    Understanding how the information needs of cancer patients (CaPts) vary is important because met information needs affect health outcomes and CaPts' satisfaction. The goals of the study were to identify subgroups of CaPts based on self-reported cancer- and treatment-related information needs and to determine whether subgroups could be predicted on the basis of selected sociodemographic, clinical and clinician-patient relationship variables. Three hundred twenty-three CaPts participated in a survey using the "Cancer Patients Information Needs" scale, which is a new tool for measuring cancer-related information needs. The number of information need subgroups and need profiles within each subgroup was identified using latent class analysis (LCA). Multinomial logistic regression was applied to predict class membership. LCA identified a model of five subgroups exhibiting differences in type and extent of CaPts' unmet information needs: a subgroup with "no unmet needs" (31.4% of the sample), two subgroups with "high level of psychosocial unmet information needs" (27.0% and 12.0%), a subgroup with "high level of purely medical unmet information needs" (16.0%) and a subgroup with "high level of medical and psychosocial unmet information needs" (13.6%). An assessment of sociodemographic and clinical characteristics revealed that younger CaPts and CaPts' requiring psychological support seem to belong to subgroups with a higher level of unmet information needs. However, the most significant predictor for the subgroups with unmet information needs is a good clinician-patient relationship, i.e. subjective perception of high level of trust in and caring attention from nurses together with high degree of physician empathy seems to be predictive for inclusion in the subgroup with no unmet information needs. The results of our study can be used by oncology nurses and physicians to increase their awareness of the complexity and heterogeneity of information needs among CaPts and of

  7. Longevity in Calumma parsonii, the World's largest chameleon.

    Science.gov (United States)

    Tessa, Giulia; Glaw, Frank; Andreone, Franco

    2017-03-01

    Large body size of ectothermic species can be correlated with high life expectancy. We assessed the longevity of the World's largest chameleon, the Parson's chameleon Calumma parsonii from Madagascar by using skeletochronology of phalanges taken from preserved specimens held in European natural history museums. Due to the high bone resorption we can provide only the minimum age of each specimen. The highest minimum age detected was nine years for a male and eight years for a female, confirming that this species is considerably long living among chameleons. Our data also show a strong correlation between snout-vent length and estimated age. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Environmental isotope signatures of the largest freshwater lake in Kerala

    International Nuclear Information System (INIS)

    Unnikrishnan Warrier, C.

    2007-01-01

    Sasthamkotta lake, the largest freshwater lake in Kerala, serves as a source for drinking water for more than half a million people. Environmental 137 Cs analysis done on undisturbed sediment core samples reveals that the recent rate of sedimentation is not uniform in the lake. The useful life of lake is estimated as about 800 years. The δD and δ 18 O values of the lake waters indicate that the lake is well mixed with a slight variation horizontally. The stable isotope studies on well waters from the catchment indicate hydraulic communication with the lake and lake groundwater system is flow-through type. Analytical model also supports this view. (author)

  9. Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses.

    Science.gov (United States)

    Serbus, Laura R; Rodriguez, Brian Garcia; Sharmin, Zinat; Momtaz, A J M Zehadee; Christensen, Steen

    2017-06-07

    The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale. Copyright © 2017 Serbus et al.

  10. Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses

    Directory of Open Access Journals (Sweden)

    Laura R. Serbus

    2017-06-01

    Full Text Available The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale.

  11. The value of nodal information in predicting lung cancer relapse using 4DPET/4DCT

    Energy Technology Data Exchange (ETDEWEB)

    Li, Heyse, E-mail: heyse.li@mail.utoronto.ca [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Becker, Nathan; Raman, Srinivas [Radiation Oncology, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Bissonnette, Jean-Pierre [Radiation Oncology, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)

    2015-08-15

    Purpose: There is evidence that computed tomography (CT) and positron emission tomography (PET) imaging metrics are prognostic and predictive in nonsmall cell lung cancer (NSCLC) treatment outcomes. However, few studies have explored the use of standardized uptake value (SUV)-based image features of nodal regions as predictive features. The authors investigated and compared the use of tumor and node image features extracted from the radiotherapy target volumes to predict relapse in a cohort of NSCLC patients undergoing chemoradiation treatment. Methods: A prospective cohort of 25 patients with locally advanced NSCLC underwent 4DPET/4DCT imaging for radiation planning. Thirty-seven image features were derived from the CT-defined volumes and SUVs of the PET image from both the tumor and nodal target regions. The machine learning methods of logistic regression and repeated stratified five-fold cross-validation (CV) were used to predict local and overall relapses in 2 yr. The authors used well-known feature selection methods (Spearman’s rank correlation, recursive feature elimination) within each fold of CV. Classifiers were ranked on their Matthew’s correlation coefficient (MCC) after CV. Area under the curve, sensitivity, and specificity values are also presented. Results: For predicting local relapse, the best classifier found had a mean MCC of 0.07 and was composed of eight tumor features. For predicting overall relapse, the best classifier found had a mean MCC of 0.29 and was composed of a single feature: the volume greater than 0.5 times the maximum SUV (N). Conclusions: The best classifier for predicting local relapse had only tumor features. In contrast, the best classifier for predicting overall relapse included a node feature. Overall, the methods showed that nodes add value in predicting overall relapse but not local relapse.

  12. Fair Value Versus Historical Cost-Based Valuation for Biological Assets: Predictability of Financial Information

    Directory of Open Access Journals (Sweden)

    Josep M. Argilés

    2011-12-01

    Full Text Available There is an intense debate on the convenience of moving from historical cost (HC toward the fair value (FV principle. The debate and academic research is usually concerned with financial instruments, but the IAS 41 requirement of fair valuation for biological assets brings it into the agricultural domain.This paper performs an empirical study with a sample of Spanish farms valuing biological assets at HC and a sample applying FV, finding no significant differences between both valuation methods to assess future cash flows. However, most tests reveal more predictive power of future earnings under fair valuation of biological assets, which is not explained by differences in volatility of earnings and profitability. The study also evidences the existence of flawed HC accounting practices for biological assets in agriculture, which suggests scarce information content of this valuation method in the predominant small business units existing in the agricultural sector in advanced Western countries.La evolución de la contabilidad desde el coste histórico (CH hacia el valor razonable (VR ha suscitado debates y controversias, tanto en el ámbito profesional, como en el académico. Si bien el debate y los estudios se han referido principalmente a los instrumentos financieros, el requerimiento de la NIC41 de valorar los activos biológicos al VR ha ampliado el debate a la contabilidad agrícola.Este trabajo realiza un estudio empírico mediante una muestra de explotaciones agrícolas españolas que valoran sus activos biológicos al CH y otra que valoran al VR, para comparar el poder predictivo de ambos criterios de valoración. No se encuentran diferencias significativas entre ambos criterios para la predicción de los futuros flujos de tesorería. No obstante, la mayor parte de los tests realizados revelan un mayor poder predictivo de los futuros resultados contables bajo el valor razonable, que no se explica en función de diferencias en la

  13. Learning Strategies and Motivational Factors Predicting Information Literacy Self-Efficacy of E-Learners

    Science.gov (United States)

    Kilic-Cakmak, Ebru

    2010-01-01

    Rapid increase in information sources in different formats, developments in technology and need for lifelong learning have drawn increased attention to needs for information literacy. Although information literacy is significant for students of all educational levels, it has become even more significant for e-learners. Therefore, this study…

  14. Predicting Personal Healthcare Management: Impact of Individual Characteristics on Patient Use of Health Information Technology

    Science.gov (United States)

    Sandefer, Ryan Heath

    2017-01-01

    The use of health information and health information technology by consumers is a major factor in the current healthcare systems' effort to address issues related to quality, cost, and access. Patient engagement in the healthcare process through access to information related to diagnoses, procedures, and treatment has the potential to improve…

  15. Decisions on foot-and-mouth disease control informed by model prediction

    DEFF Research Database (Denmark)

    Hisham Beshara Halasa, Tariq; Willeberg, Preben; Christiansen, Lasse Engbo

    2013-01-01

    of affected herds, epidemic duration, geographical size, and costs. The first fourteen days spatial spread (FFS) was also included to support the prediction. The epidemic data were obtained from a Danish version (DTU-DADS) of the Davis Animal Disease Spread simulation model. The FFI and FFS showed good......The predictive capability of the first fortnight incidence (FFI), which is the number of detected herds within the first 14 days following detection of the disease, of the course of a foot-and-mouth disease (FMD) epidemic and its outcomes were investigated. Epidemic outcomes included the number...... correlations with the epidemic outcomes. The predictive capability of the FFI was high. This indicates that the FFI may take a part in the decision of whether or not to boost FMD control, which might prevent occurrence of a large epidemic in the face of an FMD incursion. The prediction power was improved...

  16. Fishing down the largest coral reef fish species.

    Science.gov (United States)

    Fenner, Douglas

    2014-07-15

    Studies on remote, uninhabited, near-pristine reefs have revealed surprisingly large populations of large reef fish. Locations such as the northwestern Hawaiian Islands, northern Marianas Islands, Line Islands, U.S. remote Pacific Islands, Cocos-Keeling Atoll and Chagos archipelago have much higher reef fish biomass than islands and reefs near people. Much of the high biomass of most remote reef fish communities lies in the largest species, such as sharks, bumphead parrots, giant trevally, and humphead wrasse. Some, such as sharks and giant trevally, are apex predators, but others such as bumphead parrots and humphead wrasse, are not. At many locations, decreases in large reef fish species have been attributed to fishing. Fishing is well known to remove the largest fish first, and a quantitative measure of vulnerability to fishing indicates that large reef fish species are much more vulnerable to fishing than small fish. The removal of large reef fish by fishing parallels the extinction of terrestrial megafauna by early humans. However large reef fish have great value for various ecological roles and for reef tourism. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. PINGU: PredIction of eNzyme catalytic residues usinG seqUence information.

    Directory of Open Access Journals (Sweden)

    Priyadarshini P Pai

    Full Text Available Identification of catalytic residues can help unveil interesting attributes of enzyme function for various therapeutic and industrial applications. Based on their biochemical roles, the number of catalytic residues and sequence lengths of enzymes vary. This article describes a prediction approach (PINGU for such a scenario. It uses models trained using physicochemical properties and evolutionary information of 650 non-redundant enzymes (2136 catalytic residues in a support vector machines architecture. Independent testing on 200 non-redundant enzymes (683 catalytic residues in predefined prediction settings, i.e., with non-catalytic per catalytic residue ranging from 1 to 30, suggested that the prediction approach was highly sensitive and specific, i.e., 80% or above, over the incremental challenges. To learn more about the discriminatory power of PINGU in real scenarios, where the prediction challenge is variable and susceptible to high false positives, the best model from independent testing was used on 60 diverse enzymes. Results suggested that PINGU was able to identify most catalytic residues and non-catalytic residues properly with 80% or above accuracy, sensitivity and specificity. The effect of false positives on precision was addressed in this study by application of predicted ligand-binding residue information as a post-processing filter. An overall improvement of 20% in F-measure and 0.138 in Correlation Coefficient with 16% enhanced precision could be achieved. On account of its encouraging performance, PINGU is hoped to have eventual applications in boosting enzyme engineering and novel drug discovery.

  18. Predictive information speeds up visual awareness in an individuation task by modulating threshold setting, not processing efficiency.

    Science.gov (United States)

    De Loof, Esther; Van Opstal, Filip; Verguts, Tom

    2016-04-01

    Theories on visual awareness claim that predicted stimuli reach awareness faster than unpredicted ones. In the current study, we disentangle whether prior information about the upcoming stimulus affects visual awareness of stimulus location (i.e., individuation) by modulating processing efficiency or threshold setting. Analogous research on stimulus identification revealed that prior information modulates threshold setting. However, as identification and individuation are two functionally and neurally distinct processes, the mechanisms underlying identification cannot simply be extrapolated directly to individuation. The goal of this study was therefore to investigate how individuation is influenced by prior information about the upcoming stimulus. To do so, a drift diffusion model was fitted to estimate the processing efficiency and threshold setting for predicted versus unpredicted stimuli in a cued individuation paradigm. Participants were asked to locate a picture, following a cue that was congruent, incongruent or neutral with respect to the picture's identity. Pictures were individuated faster in the congruent and neutral condition compared to the incongruent condition. In the diffusion model analysis, the processing efficiency was not significantly different across conditions. However, the threshold setting was significantly higher following an incongruent cue compared to both congruent and neutral cues. Our results indicate that predictive information about the upcoming stimulus influences visual awareness by shifting the threshold for individuation rather than by enhancing processing efficiency. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Multimethod prediction of physical parent-child aggression risk in expectant mothers and fathers with Social Information Processing theory.

    Science.gov (United States)

    Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J

    2016-01-01

    The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Predicting currency fluctuations and crises - do resident firms have an informational advantage?

    OpenAIRE

    Kaufmann, Daniel; Mehrez, Gil; Schmukler, Sergio

    1999-01-01

    The authors investigate whether resident enterprise managers have an informational advantage about the countries in which they work. They propose a method for extracting information available to resident managers but unknown to investors and forecasters. They rest their hypothesis of informational advantage using a unique data set, the Global Competitiveness Survey. The survey asks local managers about their outlook for the country in which they reside. They find that local managers do have u...

  1. Using Noble Gas Measurements to Derive Air-Sea Process Information and Predict Physical Gas Saturations

    Science.gov (United States)

    Hamme, Roberta C.; Emerson, Steven R.; Severinghaus, Jeffrey P.; Long, Matthew C.; Yashayaev, Igor

    2017-10-01

    Dissolved gas distributions are important because they influence oceanic habitats and Earth's climate, yet competing controls by biology and physics make gas distributions challenging to predict. Bubble-mediated gas exchange, temperature change, and varying atmospheric pressure all push gases away from equilibrium. Here we use new noble gas measurements from the Labrador Sea to demonstrate a technique to quantify physical processes. Our analysis shows that water-mass formation can be represented by a quasi steady state in which bubble fluxes and cooling push gases away from equilibrium balanced by diffusive gas exchange forcing gases toward equilibrium. We quantify the rates of these physical processes from our measurements, allowing direct comparison to gas exchange parameterizations, and predict the physically driven saturation of other gases. This technique produces predictions that reasonably match N2/Ar observations and demonstrates that physical processes should force SF6 to be ˜6% more supersaturated than CFC-11 and CFC-12, impacting ventilation age calculations.

  2. Predicting Defects Using Information Intelligence Process Models in the Software Technology Project.

    Science.gov (United States)

    Selvaraj, Manjula Gandhi; Jayabal, Devi Shree; Srinivasan, Thenmozhi; Balasubramanie, Palanisamy

    2015-01-01

    A key differentiator in a competitive market place is customer satisfaction. As per Gartner 2012 report, only 75%-80% of IT projects are successful. Customer satisfaction should be considered as a part of business strategy. The associated project parameters should be proactively managed and the project outcome needs to be predicted by a technical manager. There is lot of focus on the end state and on minimizing defect leakage as much as possible. Focus should be on proactively managing and shifting left in the software life cycle engineering model. Identify the problem upfront in the project cycle and do not wait for lessons to be learnt and take reactive steps. This paper gives the practical applicability of using predictive models and illustrates use of these models in a project to predict system testing defects thus helping to reduce residual defects.

  3. Carbon and energy fluxes from China's largest freshwater lake

    Science.gov (United States)

    Gan, G.; LIU, Y.

    2017-12-01

    Carbon and energy fluxes between lakes and the atmosphere are important aspects of hydrology, limnology, and ecology studies. China's largest freshwater lake, the Poyang lake experiences tremendous water-land transitions periodically throughout the year, which provides natural experimental settings for the study of carbon and energy fluxes. In this study, we use the eddy covariance technique to explore the seasonal and diurnal variation patterns of sensible and latent heat fluxes of Poyang lake during its high-water and low-water periods, when the lake is covered by water and mudflat, respectively. We also determine the annual NEE of Poyang lake and the variations of NEE's components: Gross Primary Productivity (GPP) and Ecosystem Respiration (Re). Controlling factors of seasonal and diurnal variations of carbon and energy fluxes are analyzed, and land cover impacts on the variation patterns are also studied. Finally, the coupling between the carbon and energy fluxes are analyzed under different atmospheric, boundary stability and land cover conditions.

  4. SSC RIAR is the largest centre of research reactors

    International Nuclear Information System (INIS)

    Kalygin, V.V.

    1997-01-01

    The State Scientific Centre (SSC) ''Research Institute of Atomic Reactors'' (RIAR) is situated 100 km to the south-east from Moscow, in Dimitrovgrad, the Volga Region of the Russian Federation. SSC RIAR is the largest centre of research reactors in Russia. At present there are 5 types of reactor facilities in operation, including two NPP. One of the main tasks the Centre is the investigations on safety increase for power reactors. Broad international connections are available at the Institute. On the basis of the SSC RIAR during 3 years work has been done on the development of the branch training centre (TC) for the training of operation personnel of research and pilot reactors in Russia. (author). 3 tabs

  5. BALU: Largest autoclave research facility in the world

    Directory of Open Access Journals (Sweden)

    Hakan Ucan

    2016-03-01

    Full Text Available Among the large-scale facilities operated at the Center for Lightweight-Production-Technology of the German Aerospace Center in Stade BALU is the world's largest research autoclave. With a loading length of 20m and a loading diameter of 5.8 m the main objective of the facility is the optimization of the curing process operated by components made of carbon fiber on an industrial scale. For this reason, a novel dynamic autoclaving control has been developed that is characterized by peripheral devices to expend the performance of the facility for differential applications, by sensing systems to detect the component state throughout the curing process and by a feedback system, which is capable to intervene into the running autoclave process.

  6. Switzerland's largest wood-pellet factory in Balsthal

    International Nuclear Information System (INIS)

    Stohler, F.

    2004-01-01

    This article describes how a small Swiss electricity utility has broken out of its traditional role in power generation and the distribution of electricity and gone into the production of wood pellets. The pellets, which are made from waste wood (sawdust) available from wood processing companies, are produced on a large scale in one of Europe's largest pellets production facilities. The boom in the use of wood pellets for heating purposes is discussed. The article discusses this unusual approach for a Swiss power utility, which also operates a wood-fired power station and is even involved in an incineration plant for household wastes. The markets being aimed for in Switzerland and in Europe are described, including modern low-energy-consumption housing projects. A further project is described that is to use waste wood available from a large wood processing facility planned in the utility's own region

  7. Opportunities for biodiversity gains under the world's largest reforestation programme

    Science.gov (United States)

    Hua, Fangyuan; Wang, Xiaoyang; Zheng, Xinlei; Fisher, Brendan; Wang, Lin; Zhu, Jianguo; Tang, Ya; Yu, Douglas W.; Wilcove, David S.

    2016-01-01

    Reforestation is a critical means of addressing the environmental and social problems of deforestation. China's Grain-for-Green Program (GFGP) is the world's largest reforestation scheme. Here we provide the first nationwide assessment of the tree composition of GFGP forests and the first combined ecological and economic study aimed at understanding GFGP's biodiversity implications. Across China, GFGP forests are overwhelmingly monocultures or compositionally simple mixed forests. Focusing on birds and bees in Sichuan Province, we find that GFGP reforestation results in modest gains (via mixed forest) and losses (via monocultures) of bird diversity, along with major losses of bee diversity. Moreover, all current modes of GFGP reforestation fall short of restoring biodiversity to levels approximating native forests. However, even within existing modes of reforestation, GFGP can achieve greater biodiversity gains by promoting mixed forests over monocultures; doing so is unlikely to entail major opportunity costs or pose unforeseen economic risks to households. PMID:27598524

  8. SSC RIAR is the largest centre of research reactors

    Energy Technology Data Exchange (ETDEWEB)

    Kalygin, V V [State Scientific Centre, Research Inst. of Atomic Reactors (Russian Federation)

    1997-10-01

    The State Scientific Centre (SSC) ``Research Institute of Atomic Reactors`` (RIAR) is situated 100 km to the south-east from Moscow, in Dimitrovgrad, the Volga Region of the Russian Federation. SSC RIAR is the largest centre of research reactors in Russia. At present there are 5 types of reactor facilities in operation, including two NPP. One of the main tasks the Centre is the investigations on safety increase for power reactors. Broad international connections are available at the Institute. On the basis of the SSC RIAR during 3 years work has been done on the development of the branch training centre (TC) for the training of operation personnel of research and pilot reactors in Russia. (author). 3 tabs.

  9. The largest Silurian vertebrate and its palaeoecological implications

    Science.gov (United States)

    Choo, Brian; Zhu, Min; Zhao, Wenjin; Jia, Liaotao; Zhu, You'an

    2014-01-01

    An apparent absence of Silurian fishes more than half-a-metre in length has been viewed as evidence that gnathostomes were restricted in size and diversity prior to the Devonian. Here we describe the largest pre-Devonian vertebrate (Megamastax amblyodus gen. et sp. nov.), a predatory marine osteichthyan from the Silurian Kuanti Formation (late Ludlow, ~423 million years ago) of Yunnan, China, with an estimated length of about 1 meter. The unusual dentition of the new form suggests a durophagous diet which, combined with its large size, indicates a considerable degree of trophic specialisation among early osteichthyans. The lack of large Silurian vertebrates has recently been used as constraint in palaeoatmospheric modelling, with purported lower oxygen levels imposing a physiological size limit. Regardless of the exact causal relationship between oxygen availability and evolutionary success, this finding refutes the assumption that pre-Emsian vertebrates were restricted to small body sizes. PMID:24921626

  10. Predictive information processing is a fundamental learning mechanism present in early development: evidence from infants.

    Science.gov (United States)

    Trainor, Laurel J

    2012-02-01

    Evidence is presented that predictive coding is fundamental to brain function and present in early infancy. Indeed, mismatch responses to unexpected auditory stimuli are among the earliest robust cortical event-related potential responses, and have been measured in young infants in response to many types of deviation, including in pitch, timing, and melodic pattern. Furthermore, mismatch responses change quickly with specific experience, suggesting that predictive coding reflects a powerful, early-developing learning mechanism. Copyright © 2011 Elsevier B.V. All rights reserved.

  11. An HMM posterior decoder for sequence feature prediction that includes homology information

    DEFF Research Database (Denmark)

    Käll, Lukas; Krogh, Anders Stærmose; Sonnhammer, Erik L. L.

    2005-01-01

    Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines probabil......Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines......://phobius.cgb.ki.se/poly.html . An implementation of the algorithm is available on request from the authors....

  12. The largest glitch observed in the Crab pulsar

    Science.gov (United States)

    Shaw, B.; Lyne, A. G.; Stappers, B. W.; Weltevrede, P.; Bassa, C. G.; Lien, A. Y.; Mickaliger, M. B.; Breton, R. P.; Jordan, C. A.; Keith, M. J.; Krimm, H. A.

    2018-05-01

    We have observed a large glitch in the Crab pulsar (PSR B0531+21). The glitch occurred around MJD 58064 (2017 November 8) when the pulsar underwent an increase in the rotation rate of Δν = 1.530 × 10-5 Hz, corresponding to a fractional increase of Δν/ν = 0.516 × 10-6 making this event the largest glitch ever observed in this source. Due to our high-cadence and long-dwell time observations of the Crab pulsar we are able to partially resolve a fraction of the total spin-up of the star. This delayed spin-up occurred over a timescale of ˜1.7 days and is similar to the behaviour seen in the 1989 and 1996 large Crab pulsar glitches. The spin-down rate also increased at the glitch epoch by Δ \\dot{ν } / \\dot{ν } = 7 × 10^{-3}. In addition to being the largest such event observed in the Crab, the glitch occurred after the longest period of glitch inactivity since at least 1984 and we discuss a possible relationship between glitch size and waiting time. No changes to the shape of the pulse profile were observed near the glitch epoch at 610 MHz or 1520 MHz, nor did we identify any changes in the X-ray flux from the pulsar. The long-term recovery from the glitch continues to progress as \\dot{ν } slowly rises towards pre-glitch values. In line with other large Crab glitches, we expect there to be a persistent change to \\dot{ν }. We continue to monitor the long-term recovery with frequent, high quality observations.

  13. Towards prediction of soil erodibility using hyperspectral information: a case study in a semi-arid region of Iran

    DEFF Research Database (Denmark)

    Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali

    2018-01-01

    and develop Spectrotransfer Function (STF) using spectral reflectance information and Pedotransfer Function (PTF) to predict the K-factor, respectively. The derived STF was compared with developed PTF using measurable soil properties by Ostovari et al. (2016) and the Universal Soil Loss Equation (USLE......Soil Visible–Near-Infrared (Vis-NIR) spectroscopy has become an applicable and interesting technique to evaluate a number of soil properties because it is a fast, cost-effective, and non-invasive measurement technique. The main objective of the study to predict soil erodibility (K-factor), soil...... organic matter (SOM), and calcium carbonate equivalent (CaCO3) in calcareous soils of semi-arid regions located in south of Iran using spectral reflectance information in the Vis-NIR range. The K-factor was measured in 40 erosion plots under natural rainfall and the spectral reflectance of soil samples...

  14. Translating visual information into action predictions: Statistical learning in action and nonaction contexts.

    Science.gov (United States)

    Monroy, Claire D; Gerson, Sarah A; Hunnius, Sabine

    2018-05-01

    Humans are sensitive to the statistical regularities in action sequences carried out by others. In the present eyetracking study, we investigated whether this sensitivity can support the prediction of upcoming actions when observing unfamiliar action sequences. In two between-subjects conditions, we examined whether observers would be more sensitive to statistical regularities in sequences performed by a human agent versus self-propelled 'ghost' events. Secondly, we investigated whether regularities are learned better when they are associated with contingent effects. Both implicit and explicit measures of learning were compared between agent and ghost conditions. Implicit learning was measured via predictive eye movements to upcoming actions or events, and explicit learning was measured via both uninstructed reproduction of the action sequences and verbal reports of the regularities. The findings revealed that participants, regardless of condition, readily learned the regularities and made correct predictive eye movements to upcoming events during online observation. However, different patterns of explicit-learning outcomes emerged following observation: Participants were most likely to re-create the sequence regularities and to verbally report them when they had observed an actor create a contingent effect. These results suggest that the shift from implicit predictions to explicit knowledge of what has been learned is facilitated when observers perceive another agent's actions and when these actions cause effects. These findings are discussed with respect to the potential role of the motor system in modulating how statistical regularities are learned and used to modify behavior.

  15. Integrating predictive information into an agro-economic model to guide agricultural management

    Science.gov (United States)

    Zhang, Y.; Block, P.

    2016-12-01

    Skillful season-ahead climate predictions linked with responsive agricultural planning and management have the potential to reduce losses, if adopted by farmers, particularly for rainfed-dominated agriculture such as in Ethiopia. Precipitation predictions during the growing season in major agricultural regions of Ethiopia are used to generate predicted climate yield factors, which reflect the influence of precipitation amounts on crop yields and serve as inputs into an agro-economic model. The adapted model, originally developed by the International Food Policy Research Institute, produces outputs of economic indices (GDP, poverty rates, etc.) at zonal and national levels. Forecast-based approaches, in which farmers' actions are in response to forecasted conditions, are compared with no-forecast approaches in which farmers follow business as usual practices, expecting "average" climate conditions. The effects of farmer adoption rates, including the potential for reduced uptake due to poor predictions, and increasing forecast lead-time on economic outputs are also explored. Preliminary results indicate superior gains under forecast-based approaches.

  16. Predicting Heat Stress to Inform Reef Management: NOAA Coral Reef Watch's 4-Month Coral Bleaching Outlook

    Directory of Open Access Journals (Sweden)

    Gang Liu

    2018-03-01

    Full Text Available The U.S. National Oceanic and Atmospheric Administration's (NOAA Coral Reef Watch (CRW operates a global 4-Month Coral Bleaching Outlook system for shallow-water coral reefs in collaboration with NOAA's National Centers for Environmental Prediction (NCEP. The Outlooks are generated by applying the algorithm used in CRW's operational satellite coral bleaching heat stress monitoring, with slight modifications, to the sea surface temperature (SST predictions from NCEP's operational Climate Forecast System Version 2 (CFSv2. Once a week, the probability of heat stress capable of causing mass coral bleaching is predicted for 4-months in advance. Each day, CFSv2 generates an ensemble of 16 forecasts, with nine runs out to 45-days, three runs out to 3-months, and four runs out to 9-months. This results in 28–112 ensemble members produced each week. A composite for each predicted week is derived from daily predictions within each ensemble member. The probability of each of four heat stress ranges (Watch and higher, Warning and higher, Alert Level 1 and higher, and Alert Level 2 is determined from all the available ensemble members for the week to form the weekly probabilistic Outlook. The probabilistic 4-Month Outlook is the highest weekly probability predicted among all the weekly Outlooks during a 4-month period for each of the stress ranges. An initial qualitative skill analysis of the Outlooks for 2011–2015, compared with CRW's satellite-based coral bleaching heat stress products, indicated the Outlook has performed well with high hit rates and low miss rates for most coral reef areas. Regions identified with high false alarm rates will guide future improvements. This Outlook system, as the first and only freely available global coral bleaching prediction system, has been providing critical early warning to marine resource managers, scientists, and decision makers around the world to guide management, protection, and monitoring of coral reefs

  17. Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information.

    Science.gov (United States)

    Tang, Zaixiang; Shen, Yueping; Li, Yan; Zhang, Xinyan; Wen, Jia; Qian, Chen'ao; Zhuang, Wenzhuo; Shi, Xinghua; Yi, Nengjun

    2018-03-15

    Large-scale molecular data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, standard approaches for omics data analysis ignore the group structure among genes encoded in functional relationships or pathway information. We propose new Bayesian hierarchical generalized linear models, called group spike-and-slab lasso GLMs, for predicting disease outcomes and detecting associated genes by incorporating large-scale molecular data and group structures. The proposed model employs a mixture double-exponential prior for coefficients that induces self-adaptive shrinkage amount on different coefficients. The group information is incorporated into the model by setting group-specific parameters. We have developed a fast and stable deterministic algorithm to fit the proposed hierarchal GLMs, which can perform variable selection within groups. We assess the performance of the proposed method on several simulated scenarios, by varying the overlap among groups, group size, number of non-null groups, and the correlation within group. Compared with existing methods, the proposed method provides not only more accurate estimates of the parameters but also better prediction. We further demonstrate the application of the proposed procedure on three cancer datasets by utilizing pathway structures of genes. Our results show that the proposed method generates powerful models for predicting disease outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). nyi@uab.edu. Supplementary data are available at Bioinformatics online.

  18. The global diversion of pharmaceutical drugs. India: the third largest illicit opium producer?

    Science.gov (United States)

    Paoli, Letizia; Greenfield, Victoria A; Charles, Molly; Reuter, Peter

    2009-03-01

    This paper explores India's role in the world illicit opiate market, particularly its role as a producer. India, a major illicit opiate consumer, is also the sole licensed exporter of raw opium: this unique status may be enabling substantial diversion to the illicit market. Participant observation and interviews were carried out at eight different sites. Information was also drawn from all standard secondary sources and the analysis of about 180 drug-related criminal proceedings reviewed by Indian High Courts and the Supreme Court from 1985 to 2001. Diversion from licit opium production takes place on such a large scale that India may be the third largest illicit opium producer after Afghanistan and Burma. With the possible exceptions of 2005 and 2006, 200-300 tons of India's opium may be diverted yearly. After estimating India's opiate consumption on the basis of UN-reported prevalence estimates, we find that diversion from licit production might have satisfied a quarter to more than a third of India's illicit opiate demand to 2004. India is not only among the world's largest consumer of illicit opiates but also one of the largest illicit opium producers. In contrast to all other illicit producers, India owes the latter distinction not to blatantly illicit cultivation but to diversion from licit cultivation. India's experience suggests the difficulty of preventing substantial leakage, even in a relatively well-governed nation.

  19. Predicting compliance with an information-based residential outdoor water conservation program

    Science.gov (United States)

    Landon, Adam C.; Kyle, Gerard T.; Kaiser, Ronald A.

    2016-05-01

    Residential water conservation initiatives often involve some form of education or persuasion intended to change the attitudes and behaviors of residential consumers. However, the ability of these instruments to change attitudes toward conservation and their efficacy in affecting water use remains poorly understood. In this investigation the authors examine consumer attitudes toward complying with a persuasive water conservation program, the extent to which those attitudes predict compliance, and the influence of environmental contextual factors on outdoor water use. Results indicate that the persuasive program was successful in developing positive attitudes toward compliance, and that those attitudes predict water use. However, attitudinal variables explain a relatively small proportion of the variance in objectively measured water use behavior. Recommendations for policy are made stressing the importance of understanding both the effects of attitudes and environmental contextual factors in behavior change initiatives in the municipal water sector.

  20. Decisions on control of foot-and-mouth disease informed using model predictions

    DEFF Research Database (Denmark)

    Hisham Beshara Halasa, Tariq; Willeberg, P.; Christiansen, Lasse Engbo

    2013-01-01

    , epidemic duration, geographical size and costs. The first 14 days spatial spread (FFS) was also included to further support the prediction. The epidemic data was obtained from a Danish version (DTU-DADS) of a pre-existing FMD simulation model (Davis Animal Disease Spread – DADS) adapted to model the spread......The decision on whether or not to change the control strategy, such as introducing emergency vaccination, is perhaps one of the most difficult decisions faced by the veterinary authorities during a foot-and-mouth disease (FMD) epidemic. A simple tool that may predict the epidemic outcome...... and consequences would be useful to assist the veterinary authorities in the decision-making process. A previously proposed simple quantitative tool based on the first 14 days outbreaks (FFO) of FMD was used with results from an FMD simulation exercise. Epidemic outcomes included the number of affected herds...

  1. Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach

    Science.gov (United States)

    Xie, Weihong; Yu, Yang

    2017-01-01

    Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG) in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM) estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly. PMID:29124062

  2. Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach

    Directory of Open Access Journals (Sweden)

    Fan Liang

    2017-01-01

    Full Text Available Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly.

  3. Statistics of the largest sunspot and facular areas per solar cycle

    International Nuclear Information System (INIS)

    Willis, D.M.; Kabasakal Tulunay, Y.

    1979-01-01

    The statistics of extreme values is used to investigate the statistical properties of the largest areas sunspots and photospheric faculae per solar cycle. The largest values of the synodic-solar-rotation mean areas of umbrae, whole spots and faculae, which have been recorded for nine solar cycles, are each shown to comply with the general form of the extreme value probability function. Empirical expressions are derived for the three extreme value populations from which the characteristic statistical parameters, namely the mode, median, mean and standard deviation, can be calculated for each population. These three extreme value populations are also used to find the expected ranges of the extreme areas in a group of solar cycles as a function of the number of cycles in the group. The extreme areas of umbrae and whole spots have a dispersion comparable to that found by Siscoe for the extreme values of sunspot number, whereas the extreme areas of faculae have a smaller dispersion which is comparable to that found by Siscoe for the largest geomagnetic storm per solar cycle. The expected range of the largest sunspot area per solar cycle for a group of one hundred cycles appears to be inconsistent with the existence of the prolonged periods of sunspot minima that have been inferred from the historical information on solar variability. This inconsistency supports the contention that there are temporal changes of solar-cycle statistics during protracted periods of sunspot minima (or maxima). Indeed, without such temporal changes, photospheric faculae should have been continually observable throughout the lifetime of the Sun. (orig.)

  4. Oceans of Opportunity. Harnessing Europe's largest domestic energy resource

    International Nuclear Information System (INIS)

    Fichaux, N.; Wilkes, J.

    2009-09-01

    Europe's offshore wind potential is enormous and able to power Europe seven times over. Over 100 GW of offshore wind projects are already in various stages of planning. If realised, these projects would produce 10% of the EU's electricity whilst avoiding 200 million tonnes of CO2 emissions each year. EWEA has a target of 40 GW of offshore wind in the EU by 2020, implying an average annual market growth of 28% over the coming 12 years. The EU market for onshore wind grew by an average 32% per year in the 12-year period from 1992-2004 - what the wind energy industry has achieved on land can be repeated at sea. EWEA's proposed offshore grid builds on the 11 offshore grids currently operating and 21 offshore grids currently being considered by the grid operators in the Baltic and North Seas to give Europe a truly pan-European electricity super highway. Strong political support and action from Europe's policy-makers will allow a new, multi-billion euro industry to be built. This new industry will deliver thousands of green collar jobs and a new renewable energy economy and establish Europe as world leader in offshore wind power technology. A single European electricity market with large amounts of wind power will bring affordable electricity to consumers, reduce import dependence, cut CO2 emissions and allow Europe to access its largest domestic energy source.

  5. Characterization of the largest effector gene cluster of Ustilago maydis.

    Directory of Open Access Journals (Sweden)

    Thomas Brefort

    2014-07-01

    Full Text Available In the genome of the biotrophic plant pathogen Ustilago maydis, many of the genes coding for secreted protein effectors modulating virulence are arranged in gene clusters. The vast majority of these genes encode novel proteins whose expression is coupled to plant colonization. The largest of these gene clusters, cluster 19A, encodes 24 secreted effectors. Deletion of the entire cluster results in severe attenuation of virulence. Here we present the functional analysis of this genomic region. We show that a 19A deletion mutant behaves like an endophyte, i.e. is still able to colonize plants and complete the infection cycle. However, tumors, the most conspicuous symptoms of maize smut disease, are only rarely formed and fungal biomass in infected tissue is significantly reduced. The generation and analysis of strains carrying sub-deletions identified several genes significantly contributing to tumor formation after seedling infection. Another of the effectors could be linked specifically to anthocyanin induction in the infected tissue. As the individual contributions of these genes to tumor formation were small, we studied the response of maize plants to the whole cluster mutant as well as to several individual mutants by array analysis. This revealed distinct plant responses, demonstrating that the respective effectors have discrete plant targets. We propose that the analysis of plant responses to effector mutant strains that lack a strong virulence phenotype may be a general way to visualize differences in effector function.

  6. El Paso natural gas nearing completion of system's largest expansion

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    El Paso Natural Gas Co.'s largest expansion program in its 64-year history will be completed along its northern system this spring or early summer. According to the company, the three-tiered, $241.5 million expansion program will increase El Paso's gas-transport capacity by 835 MMcfd to 2.5 bcfd of conventional and coal-seam gas from the San Juan basin in northwestern New Mexico. That's enough natural gas, says the company, to supply the needs of a city of more than 800,000 residents. This paper reports that the expansion involves the San Juan Triangle system, the company's northern main line, and the Permian-San Juan crossover line. The company also filed with the Federal Energy Regulatory Commission (FERC) in October 1991 to construct a new $15.2 million compressor station, Rio Vista, south of Bloomfield, N.M. The station would be used to move additional gas to the main line

  7. Benchmark Testing of the Largest Titanium Aluminide Sheet Subelement Conducted

    Science.gov (United States)

    Bartolotta, Paul A.; Krause, David L.

    2000-01-01

    To evaluate wrought titanium aluminide (gamma TiAl) as a viable candidate material for the High-Speed Civil Transport (HSCT) exhaust nozzle, an international team led by the NASA Glenn Research Center at Lewis Field successfully fabricated and tested the largest gamma TiAl sheet structure ever manufactured. The gamma TiAl sheet structure, a 56-percent subscale divergent flap subelement, was fabricated for benchmark testing in three-point bending. Overall, the subelement was 84-cm (33-in.) long by 13-cm (5-in.) wide by 8-cm (3-in.) deep. Incorporated into the subelement were features that might be used in the fabrication of a full-scale divergent flap. These features include the use of: (1) gamma TiAl shear clips to join together sections of corrugations, (2) multiple gamma TiAl face sheets, (3) double hot-formed gamma TiAl corrugations, and (4) brazed joints. The structural integrity of the gamma TiAl sheet subelement was evaluated by conducting a room-temperature three-point static bend test.

  8. Phosphorus Loadings to the World's Largest Lakes: Sources and Trends

    Science.gov (United States)

    Fink, Gabriel; Alcamo, Joseph; Flörke, Martina; Reder, Klara

    2018-04-01

    Eutrophication is a major water quality issue in lakes worldwide and is principally caused by the loadings of phosphorus from catchment areas. It follows that to develop strategies to mitigate eutrophication, we must have a good understanding of the amount, sources, and trends of phosphorus pollution. This paper provides the first consistent and harmonious estimates of current phosphorus loadings to the world's largest 100 lakes, along with the sources of these loadings and their trends. These estimates provide a perspective on the extent of lake eutrophication worldwide, as well as potential input to the evaluation and management of eutrophication in these lakes. We take a modeling approach and apply the WorldQual model for these estimates. The advantage of this approach is that it allows us to fill in large gaps in observational data. From the analysis, we find that about 66 of the 100 lakes are located in developing countries and their catchments have a much larger average phosphorus yield than the lake catchments in developed countries (11.1 versus 0.7 kg TP km-2 year-1). Second, the main source of phosphorus to the examined lakes is inorganic fertilizer (47% of total). Third, between 2005-2010 and 1990-1994, phosphorus pollution increased at 50 out of 100 lakes. Sixty percent of lakes with increasing pollution are in developing countries. P pollution changed primarily due to changing P fertilizer use. In conclusion, we show that the risk of P-stimulated eutrophication is higher in developing countries.

  9. LHC : The World's Largest Vacuum Systems being commissioned at CERN

    CERN Document Server

    Jiménez, J M

    2008-01-01

    When it switches on in 2008, the 26.7 km Large Hadron Collider (LHC) at CERN, will have the world's largest vacuum system operating over a wide range of pressures and employing an impressive array of vacuum technologies. This system is composed by 54 km of UHV vacuum for the circulating beams and 50 km of insulation vacuum around the cryogenic magnets and the liquid helium transfer lines. Over the 54 km of UHV beam vacuum, 48 km of this are at cryogenic temperature (1.9 K). The remaining 6 km of beam vacuum containing the insertions for "cleaning" the proton beams, radiofrequency cavities for accelerating the protons as well as beam-monitoring equipment is at ambient temperature and uses non-evaporable getter (NEG) coatings - a vacuum technology that was born and industrialized at CERN. The pumping scheme is completed using 780 ion pumps to remove noble gases and to provide pressure interlocks to the 303 vacuum safety valves. Pressure readings are provided by 170 Bayard-Alpert gauges and 1084 gauges (Pirani a...

  10. When clusters collide: constraints on antimatter on the largest scales

    International Nuclear Information System (INIS)

    Steigman, Gary

    2008-01-01

    Observations have ruled out the presence of significant amounts of antimatter in the Universe on scales ranging from the solar system, to the Galaxy, to groups and clusters of galaxies, and even to distances comparable to the scale of the present horizon. Except for the model-dependent constraints on the largest scales, the most significant upper limits to diffuse antimatter in the Universe are those on the ∼Mpc scale of clusters of galaxies provided by the EGRET upper bounds to annihilation gamma rays from galaxy clusters whose intracluster gas is revealed through its x-ray emission. On the scale of individual clusters of galaxies the upper bounds to the fraction of mixed matter and antimatter for the 55 clusters from a flux-limited x-ray survey range from 5 × 10 −9 to −6 , strongly suggesting that individual clusters of galaxies are made entirely of matter or of antimatter. X-ray and gamma-ray observations of colliding clusters of galaxies, such as the Bullet Cluster, permit these constraints to be extended to even larger scales. If the observations of the Bullet Cluster, where the upper bound to the antimatter fraction is found to be −6 , can be generalized to other colliding clusters of galaxies, cosmologically significant amounts of antimatter will be excluded on scales of order ∼20 Mpc (M∼5×10 15 M sun )

  11. Predicting visual attention to nutrition information on food products: the influence of motivation and ability.

    Science.gov (United States)

    Turner, Monique Mitchell; Skubisz, Christine; Pandya, Sejal Patel; Silverman, Meryl; Austin, Lucinda L

    2014-09-01

    Obesity is linked to numerous diseases including heart disease, diabetes, and cancer. To address this issue, food and beverage manufacturers as well as health organizations have developed nutrition symbols and logos to be placed on the front of food packages to guide consumers to more healthful food choices. In 2010, the U.S. Food and Drug Administration requested information on the extent to which consumers notice, use, and understand front-of-package nutrition symbols. In response, this study used eye-tracking technology to explore the degree to which people pay visual attention to the information contained in food nutrition labels and front-of-package nutrition symbols. Results indicate that people with motivation to shop for healthful foods spent significantly more time looking at all available nutrition information compared to people with motivation to shop for products on the basis of taste. Implications of these results for message design, food labeling, and public policy are discussed.

  12. The Interaction of Temporal and Spectral Acoustic Information with Word Predictability on Speech Intelligibility

    Science.gov (United States)

    Shahsavarani, Somayeh Bahar

    High-level, top-down information such as linguistic knowledge is a salient cortical resource that influences speech perception under most listening conditions. But, are all listeners able to exploit these resources for speech facilitation to the same extent? It was found that children with cochlear implants showed different patterns of benefit from contextual information in speech perception compared with their normal-haring peers. Previous studies have discussed the role of non-acoustic factors such as linguistic and cognitive capabilities to account for this discrepancy. Given the fact that the amount of acoustic information encoded and processed by auditory nerves of listeners with cochlear implants differs from normal-hearing listeners and even varies across individuals with cochlear implants, it is important to study the interaction of specific acoustic properties of the speech signal with contextual cues. This relationship has been mostly neglected in previous research. In this dissertation, we aimed to explore how different acoustic dimensions interact to affect listeners' abilities to combine top-down information with bottom-up information in speech perception beyond the known effects of linguistic and cognitive capacities shown previously. Specifically, the present study investigated whether there were any distinct context effects based on the resolution of spectral versus slowly-varying temporal information in perception of spectrally impoverished speech. To that end, two experiments were conducted. In both experiments, a noise-vocoded technique was adopted to generate spectrally-degraded speech to approximate acoustic cues delivered to listeners with cochlear implants. The frequency resolution was manipulated by varying the number of frequency channels. The temporal resolution was manipulated by low-pass filtering of amplitude envelope with varying low-pass cutoff frequencies. The stimuli were presented to normal-hearing native speakers of American

  13. Prediction of meningococcal meningitis epidemics in western Africa by using climate information

    Science.gov (United States)

    YAKA, D. P.; Sultan, B.; Tarbangdo, F.; Thiaw, W. M.

    2013-12-01

    The variations of certain climatic parameters and the degradation of ecosystems, can affect human's health by influencing the transmission, the spatiotemporal repartition and the intensity of infectious diseases. It is mainly the case of meningococcal meningitis (MCM) whose epidemics occur particularly in Sahelo-Soudanian climatic area of Western Africa under quite particular climatic conditions. Meningococcal Meningitis (MCM) is a contagious infection disease due to the bacteria Neisseria meningitis. MCM epidemics occur worldwide but the highest incidence is observed in the "meningitis belt" of sub-Saharan Africa, stretching from Senegal to Ethiopia. In spite of standards, strategies of prevention and control of MCS epidemic from World Health Organization (WHO) and States, African Sahelo-Soudanian countries remain frequently afflicted by disastrous epidemics. In fact, each year, during the dry season (February-April), 25 to 250 thousands of cases are observed. Children under 15 are particularly affected. Among favourable conditions for the resurgence and dispersion of the disease, climatic conditions may be important inducing seasonal fluctuations in disease incidence and contributing to explain the spatial pattern of the disease roughly circumscribed to the ecological Sahelo-Sudanian band. In this study, we tried to analyse the relationships between climatic factors, ecosystems degradation and MCM for a better understanding of MCM epidemic dynamic and their prediction. We have shown that MCM epidemics, whether at the regional, national or local level, occur in a specific period of the year, mainly from January to May characterised by a dry, hot and sandy weather. We have identified both in situ (meteorological synoptic stations) and satellitales climatic variables (NCEP reanalysis dataset) whose seasonal variability is dominating in MCM seasonal transmission. Statistical analysis have measured the links between seasonal variation of certain climatic parameters

  14. Gender discrimination and prediction on the basis of facial metric information.

    Science.gov (United States)

    Fellous, J M

    1997-07-01

    Horizontal and vertical facial measurements are statistically independent. Discriminant analysis shows that five of such normalized distances explain over 95% of the gender differences of "training" samples and predict the gender of 90% novel test faces exhibiting various facial expressions. The robustness of the method and its results are assessed. It is argued that these distances (termed fiducial) are compatible with those found experimentally by psychophysical and neurophysiological studies. In consequence, partial explanations for the effects observed in these experiments can be found in the intrinsic statistical nature of the facial stimuli used.

  15. Seeing Central African forests through their largest trees

    NARCIS (Netherlands)

    Bastin, J.F.; Barbier, N.; Réjou-Méchain, M.; Fayolle, A.; Gourlet-Fleury, S.; Maniatis, D.; Haulleville, De T.; Baya, F.; Beeckman, H.; Beina, D.; Couteron, P.; Chuyong, G.; Dauby, G.; Doucet, J.L.; Droissart, V.; Dufrêne, M.; Ewango, C.E.N.; Gillet, F.; Gonmadje, C.H.; Hart, T.; Kavali, T.; Kenfack, D.; Libalah, M.; Malhi, Y.; Makana, J.R.; Pélissier, R.; Ploton, P.; Serckx, S.; Sonké, B.; Stevart, T.; Thomas, D.W.; Cannière, De C.; Bogaert, J.

    2015-01-01

    Large tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large,

  16. Economic Regime identification and prediction in TAC SCM using sales and procurement information

    NARCIS (Netherlands)

    Hogenboom, F.P.; Ketter, W.; Dalen, van Jan; Kaymak, U.; Collins, J.; Gupta, Alok

    2009-01-01

    Our research is focused on the effects of the additionof procurement information (offer prices) to a sales-based economic regime model. This model is used for strategic, tactical, and operational decision making in dynamic supply chains. We evaluate the performance of the regime model through

  17. Noise, Information and the Favorite-Longshot Bias in Parimutuel Predictions

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2010-01-01

    According to the favorite-longshot bias, the expected return on an outcome tends to increase in the fraction of bets laid on that outcome. We derive testable implications for the direction and extent of the bias depending on the ratio of private information to noise present in the market. We link...

  18. Identifying and predicting economic regimes in supply chains using sales and procurement information

    NARCIS (Netherlands)

    Hogenboom, F.P.; Ketter, W.; Dalen, van Jan; Kaymak, U.; Collins, J.; Gupta, Alok

    2009-01-01

    We investigate the effects of adding procurement information (component offer prices) to a sales-based economic regime model, which is used for strategic, tactical, and operational decision making in dynamic supply chains. The performance of the regime model is evaluated through experiments with the

  19. Information rates and post-FEC BER prediction in optical fiber communications

    NARCIS (Netherlands)

    Alvarado, Alex

    2017-01-01

    Information-theoretic metrics to analyze optical fiber communications systems with binary and nonbinary soft-decision FEC are reviewed. The numerical evaluation of these metrics in both simulations and experiments is also discussed. Ready-to-use closed-form approximations are presented.

  20. Prediction Model for Demands of the Health Meteorological Information Using a Decision Tree Method

    Directory of Open Access Journals (Sweden)

    Jina Oh, RN, PhD

    2010-09-01

    Conclusions: It can be effectively used as a reference model for future studies and is a suggested direction in health meteorological information service and policy development. We suggest health forecasting as a nursing service and a primary health care network for healthier and more comfortable life.

  1. Predicting Digital Informal Learning: An Empirical Study among Chinese University Students

    Science.gov (United States)

    He, Tao; Zhu, Chang; Questier, Frederik

    2018-01-01

    Although the adoption of digital technology has gained considerable attention in higher education, currently research mainly focuses on implementation in formal learning contexts. Investigating what factors influence students' digital informal learning is still unclear and limited. To understand better university students' digital informal…

  2. Sensory processing patterns predict the integration of information held in visual working memory.

    Science.gov (United States)

    Lowe, Matthew X; Stevenson, Ryan A; Wilson, Kristin E; Ouslis, Natasha E; Barense, Morgan D; Cant, Jonathan S; Ferber, Susanne

    2016-02-01

    Given the limited resources of visual working memory, multiple items may be remembered as an averaged group or ensemble. As a result, local information may be ill-defined, but these ensemble representations provide accurate diagnostics of the natural world by combining gist information with item-level information held in visual working memory. Some neurodevelopmental disorders are characterized by sensory processing profiles that predispose individuals to avoid or seek-out sensory stimulation, fundamentally altering their perceptual experience. Here, we report such processing styles will affect the computation of ensemble statistics in the general population. We identified stable adult sensory processing patterns to demonstrate that individuals with low sensory thresholds who show a greater proclivity to engage in active response strategies to prevent sensory overstimulation are less likely to integrate mean size information across a set of similar items and are therefore more likely to be biased away from the mean size representation of an ensemble display. We therefore propose the study of ensemble processing should extend beyond the statistics of the display, and should also consider the statistics of the observer. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  3. Electric vehicle energy consumption modelling and prediction based on road information

    NARCIS (Netherlands)

    Wang, J.; Besselink, I.J.M.; Nijmeijer, H.

    The limited driving range is considered as a significant barrier to the spread of electric vehicles. One effective method to reduce “range anxiety” is to offer accurate information to the driver on the remaining driving range. However, the energy consumption during driving is largely determined by

  4. Improving biological understanding and complex trait prediction by integrating prior information in genomic feature models

    DEFF Research Database (Denmark)

    Edwards, Stefan McKinnon

    externally founded information, such as KEGG pathways, Gene Ontology gene sets, or genomic features, and estimate the joint contribution of the genetic variants within these sets to complex trait phenotypes. The analysis of complex trait phenotypes is hampered by the myriad of genes that control the trait...

  5. Reach and messages of the world's largest ivory burn.

    Science.gov (United States)

    Braczkowski, Alexander; Holden, Matthew H; O'Bryan, Christopher; Choi, Chi-Yeung; Gan, Xiaojing; Beesley, Nicholas; Gao, Yufang; Allan, James; Tyrrell, Peter; Stiles, Daniel; Brehony, Peadar; Meney, Revocatus; Brink, Henry; Takashina, Nao; Lin, Ming-Ching; Lin, Hsien-Yung; Rust, Niki; Salmo, Severino G; Watson, James Em; Kahumbu, Paula; Maron, Martine; Possingham, Hugh P; Biggs, Duan

    2018-03-01

    Recent increases in ivory poaching have depressed African elephant populations. Successful enforcement has led to ivory being stockpiled. Stockpile destruction is becoming increasingly popular, and most destruction has occurred in the last five years. Ivory destruction is intended to send a strong message against ivory consumption, both in promoting a taboo on ivory use and catalyzing policy change. However, there has been no effort to establish the distribution and extent of media reporting on ivory destruction events globally. We analyze media coverage across eleven important nation states of the largest ivory destruction event in history (Kenya, 30 April 2016). We used a well-accepted online media crawling tool and key language translations to search online and print newspapers. We found most online news on the ivory burn came from the US (81% of articles), while print news was dominated by Kenya (61% of articles). We subjected online articles from five key countries and territories to content analysis and found 86-97% of all online articles reported the burn as a positive conservation action, while between 4-50% discussed ivory burning as having a negative impact on elephant conservation. Most articles discussed law enforcement and trade bans as effective for elephant conservation. There was more relative search interest globally on the 2016 Kenyan ivory burn than any other in five years. Our study is the first attempt to track the spread of media around an ivory burn and is a case study in tracking the effects of a conservation-marketing event. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  6. Genome size analyses of Pucciniales reveal the largest fungal genomes.

    Science.gov (United States)

    Tavares, Sílvia; Ramos, Ana Paula; Pires, Ana Sofia; Azinheira, Helena G; Caldeirinha, Patrícia; Link, Tobias; Abranches, Rita; Silva, Maria do Céu; Voegele, Ralf T; Loureiro, João; Talhinhas, Pedro

    2014-01-01

    Rust fungi (Basidiomycota, Pucciniales) are biotrophic plant pathogens which exhibit diverse complexities in their life cycles and host ranges. The completion of genome sequencing of a few rust fungi has revealed the occurrence of large genomes. Sequencing efforts for other rust fungi have been hampered by uncertainty concerning their genome sizes. Flow cytometry was recently applied to estimate the genome size of a few rust fungi, and confirmed the occurrence of large genomes in this order (averaging 225.3 Mbp, while the average for Basidiomycota was 49.9 Mbp and was 37.7 Mbp for all fungi). In this work, we have used an innovative and simple approach to simultaneously isolate nuclei from the rust and its host plant in order to estimate the genome size of 30 rust species by flow cytometry. Genome sizes varied over 10-fold, from 70 to 893 Mbp, with an average genome size value of 380.2 Mbp. Compared to the genome sizes of over 1800 fungi, Gymnosporangium confusum possesses the largest fungal genome ever reported (893.2 Mbp). Moreover, even the smallest rust genome determined in this study is larger than the vast majority of fungal genomes (94%). The average genome size of the Pucciniales is now of 305.5 Mbp, while the average Basidiomycota genome size has shifted to 70.4 Mbp and the average for all fungi reached 44.2 Mbp. Despite the fact that no correlation could be drawn between the genome sizes, the phylogenomics or the life cycle of rust fungi, it is interesting to note that rusts with Fabaceae hosts present genomes clearly larger than those with Poaceae hosts. Although this study comprises only a small fraction of the more than 7000 rust species described, it seems already evident that the Pucciniales represent a group where genome size expansion could be a common characteristic. This is in sharp contrast to sister taxa, placing this order in a relevant position in fungal genomics research.

  7. The role of atmospheric diagnosis and Big Data science in improving hydroclimatic extreme prediction and the merits of climate informed prediction for future water resources management

    Science.gov (United States)

    Lu, Mengqian; Lall, Upmanu

    2017-04-01

    The threats that hydroclimatic extremes pose to sustainable development, safety and operation of infrastructure are both severe and growing. Recent heavy precipitation triggered flood events in many regions and increasing frequency and intensity of extreme precipitation suggested by various climate projections highlight the importance of understanding the associated hydrometeorological patterns and space-time variability of such extreme events, and developing a new approach to improve predictability with a better estimation of uncertainty. This clear objective requires the optimal utility of Big Data analytics on multi-source datasets to extract informative predictors from the complex ocean-atmosphere coupled system and develop a statistical and physical based framework. The proposed presentation includes the essence of our selected works in the past two years, as part of our Global Floods Initiatives. Our approach for an improved extreme prediction begins with a better understanding of the associated atmospheric circulation patterns, under the influence and regulation of slowly changing oceanic boundary conditions [Lu et al., 2013, 2016a; Lu and Lall, 2016]. The study of the associated atmospheric circulation pattern and the regulation of teleconnected climate signals adopted data science techniques and statistical modeling recognizing the nonstationarity and nonlinearity of the system, as the underlying statistical assumptions of the classical extreme value frequency analysis are challenged in hydroclimatic studies. There are two main factors that are considered important for understanding how future flood risk will change. One is the consideration of moisture holding capacity as a function of temperature, as suggested by Clausius-Clapeyron equation. The other is the strength of the convergence or convection associated with extreme precipitation. As convergence or convection gets stronger, rain rates can be expected to increase if the moisture is available. For

  8. Prediction of Driver's Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques.

    Science.gov (United States)

    Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

    2017-06-10

    Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver's intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver's intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver's intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver's intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics.

  9. New welding information system on the internet (Prediction of the properties of weld heat-affected zones

    Directory of Open Access Journals (Sweden)

    M Fujita

    2003-08-01

    Full Text Available To promote continuous transfer and development of welding technology, a new system for predicting the microstructures and mechanical properties of welded joins has been built on the Internet. It combines a database system containing continuous cooling transformation diagrams (CCT diagrams for welding and an expert system for computing weld thermal histories. In addition, this system employs a technique which was invented during the development of another distributed database system called "Data-Free-Way" , which was designed to contain information advanced nuclear materials and materials obtained from other programs of welding research at NIMS in the past. This paper describes the current state of our new system for computing weld thermal histories to predict the properties of welded joints using the CCT diagrams database, which is now available on the Internet. Some problems encountered with the database used in such a system are also referred to.

  10. Correlating Structural Order with Structural Rearrangement in Dusty Plasma Liquids: Can Structural Rearrangement be Predicted by Static Structural Information?

    Science.gov (United States)

    Su, Yen-Shuo; Liu, Yu-Hsuan; I, Lin

    2012-11-01

    Whether the static microstructural order information is strongly correlated with the subsequent structural rearrangement (SR) and their predicting power for SR are investigated experimentally in the quenched dusty plasma liquid with microheterogeneities. The poor local structural order is found to be a good alarm to identify the soft spot and predict the short term SR. For the site with good structural order, the persistent time for sustaining the structural memory until SR has a large mean value but a broad distribution. The deviation of the local structural order from that averaged over nearest neighbors serves as a good second alarm to further sort out the short time SR sites. It has the similar sorting power to that using the temporal fluctuation of the local structural order over a small time interval.

  11. Predicting adolescents' disclosure of personal information in exchange for commercial incentives: an application of an extended theory of planned behavior.

    Science.gov (United States)

    Heirman, Wannes; Walrave, Michel; Ponnet, Koen

    2013-02-01

    This study adopts a global theoretical framework to predict adolescents' disclosure of personal information in exchange for incentives offered by commercial Websites. The study postulates and tests the validity of a model based on the theory of planned behavior (TPB), including antecedent factors of attitude and perceived behavioral control (PBC). A survey was conducted among 1,042 respondents. Results from SEM analyses show that the hypothesized model fits the empirical data well. The model accounts for 61.9 percent of the variance in adolescents' intention to disclose and 43.7 percent of the variance in self-reported disclosure. Perceived social pressure exerted by significant others (subjective norm) is the most important TPB factor in predicting intention to disclose personal information in exchange for incentives. This finding suggests that in discussions of adolescents' information privacy, the importance of social factors outweighs the individually oriented TPB factors of attitude and PBC. Moreover, privacy concern and trust propensity are significant predictors of respondents' attitudes toward online disclosure in exchange for commercial incentives, whereas the frequency of Internet use significantly affects their level of PBC.

  12. A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancer.

    Directory of Open Access Journals (Sweden)

    Sijia Huang

    2014-09-01

    Full Text Available Breast cancer is the most common malignancy in women worldwide. With the increasing awareness of heterogeneity in breast cancers, better prediction of breast cancer prognosis is much needed for more personalized treatment and disease management. Towards this goal, we have developed a novel computational model for breast cancer prognosis by combining the Pathway Deregulation Score (PDS based pathifier algorithm, Cox regression and L1-LASSO penalization method. We trained the model on a set of 236 patients with gene expression data and clinical information, and validated the performance on three diversified testing data sets of 606 patients. To evaluate the performance of the model, we conducted survival analysis of the dichotomized groups, and compared the areas under the curve based on the binary classification. The resulting prognosis genomic model is composed of fifteen pathways (e.g., P53 pathway that had previously reported cancer relevance, and it successfully differentiated relapse in the training set (log rank p-value = 6.25e-12 and three testing data sets (log rank p-value < 0.0005. Moreover, the pathway-based genomic models consistently performed better than gene-based models on all four data sets. We also find strong evidence that combining genomic information with clinical information improved the p-values of prognosis prediction by at least three orders of magnitude in comparison to using either genomic or clinical information alone. In summary, we propose a novel prognosis model that harnesses the pathway-based dysregulation as well as valuable clinical information. The selected pathways in our prognosis model are promising targets for therapeutic intervention.

  13. Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary information.

    Science.gov (United States)

    An, Ji-Yong; Zhang, Lei; Zhou, Yong; Zhao, Yu-Jun; Wang, Da-Fu

    2017-08-18

    Self-interactions Proteins (SIPs) is important for their biological activity owing to the inherent interaction amongst their secondary structures or domains. However, due to the limitations of experimental Self-interactions detection, one major challenge in the study of prediction SIPs is how to exploit computational approaches for SIPs detection based on evolutionary information contained protein sequence. In the work, we presented a novel computational approach named WELM-LAG, which combined the Weighed-Extreme Learning Machine (WELM) classifier with Local Average Group (LAG) to predict SIPs based on protein sequence. The major improvement of our method lies in presenting an effective feature extraction method used to represent candidate Self-interactions proteins by exploring the evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix (PSSM); and then employing a reliable and robust WELM classifier to carry out classification. In addition, the Principal Component Analysis (PCA) approach is used to reduce the impact of noise. The WELM-LAG method gave very high average accuracies of 92.94 and 96.74% on yeast and human datasets, respectively. Meanwhile, we compared it with the state-of-the-art support vector machine (SVM) classifier and other existing methods on human and yeast datasets, respectively. Comparative results indicated that our approach is very promising and may provide a cost-effective alternative for predicting SIPs. In addition, we developed a freely available web server called WELM-LAG-SIPs to predict SIPs. The web server is available at http://219.219.62.123:8888/WELMLAG/ .

  14. CorVue algorithm efficacy to predict heart failure in real life: Unnecessary and potentially misleading information?

    Science.gov (United States)

    Palfy, Julia Anna; Benezet-Mazuecos, Juan; Milla, Juan Martinez; Iglesias, Jose Antonio; de la Vieja, Juan Jose; Sanchez-Borque, Pepa; Miracle, Angel; Rubio, Jose Manuel

    2018-06-01

    Heart failure (HF) hospitalizations have a negative impact on quality of life and imply important costs. Intrathoracic impedance (ITI) variations detected by cardiac devices have been hypothesized to predict HF hospitalizations. Although Optivol™ algorithm (Medtronic) has been widely studied, CorVue™ algorithm (St. Jude Medical) long term efficacy has not been systematically evaluated in a "real life" cohort. CorVue™ was activated in ICD/CRT-D patients to store information about ITI measures. Clinical events (new episodes of HF requiring treatment and hospitalizations) and CorVue™ data were recorded every three months. Appropriate CorVue™ detection for HF was considered if it occurred in the four prior weeks to the clinical event. 53 ICD/CRT-D (26 ICD and 27 CRT-D) patients (67±1 years-old, 79% male) were included. Device position was subcutaneous in 28 patients. At inclusion, mean LVEF was 25±7% and 27 patients (51%) were in NYHA class I, 18 (34%) class II and 8 (15%) class III. After a mean follow-up of 17±9 months, 105 ITI drops alarms were detected in 32 patients (60%). Only six alarms were appropriate (true positive) and required hospitalization. Eighteen patients (34%) presented 25 clinical episodes (12 hospitalizations and 13 ER/ambulatory treatment modifications). Nineteen of these clinical episodes (76%) remained undetected by the CorVue™ (false negative). Sensitivity of CorVue™ resulted in 24%, specificity was 70%, positive predictive value of 6% and negative predictive value of 93%. CorVue™ showed a low sensitivity to predict HF events. Therefore, routinely activation of this algorithm could generate misleading information. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  15. HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

    Directory of Open Access Journals (Sweden)

    Hu Jianjun

    2011-05-01

    Full Text Available Abstract Background Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues. Results Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM. The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone

  16. GENECODIS-Grid: An online grid-based tool to predict functional information in gene lists

    International Nuclear Information System (INIS)

    Nogales, R.; Mejia, E.; Vicente, C.; Montes, E.; Delgado, A.; Perez Griffo, F. J.; Tirado, F.; Pascual-Montano, A.

    2007-01-01

    In this work we introduce GeneCodis-Grid, a grid-based alternative to a bioinformatics tool named Genecodis that integrates different sources of biological information to search for biological features (annotations) that frequently co-occur in a set of genes and rank them by statistical significance. GeneCodis-Grid is a web-based application that takes advantage of two independent grid networks and a computer cluster managed by a meta-scheduler and a web server that host the application. The mining of concurrent biological annotations provides significant information for the functional analysis of gene list obtained by high throughput experiments in biology. Due to the large popularity of this tool, that has registered more than 13000 visits since its publication in January 2007, there is a strong need to facilitate users from different sites to access the system simultaneously. In addition, the complexity of some of the statistical tests used in this approach has made this technique a good candidate for its implementation in a Grid opportunistic environment. (Author)

  17. Predicting protein complexes using a supervised learning method combined with local structural information.

    Science.gov (United States)

    Dong, Yadong; Sun, Yongqi; Qin, Chao

    2018-01-01

    The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

  18. Introducing spatial information into predictive NF-kappaB modelling--an agent-based approach.

    Directory of Open Access Journals (Sweden)

    Mark Pogson

    2008-06-01

    Full Text Available Nature is governed by local interactions among lower-level sub-units, whether at the cell, organ, organism, or colony level. Adaptive system behaviour emerges via these interactions, which integrate the activity of the sub-units. To understand the system level it is necessary to understand the underlying local interactions. Successful models of local interactions at different levels of biological organisation, including epithelial tissue and ant colonies, have demonstrated the benefits of such 'agent-based' modelling. Here we present an agent-based approach to modelling a crucial biological system--the intracellular NF-kappaB signalling pathway. The pathway is vital to immune response regulation, and is fundamental to basic survival in a range of species. Alterations in pathway regulation underlie a variety of diseases, including atherosclerosis and arthritis. Our modelling of individual molecules, receptors and genes provides a more comprehensive outline of regulatory network mechanisms than previously possible with equation-based approaches. The method also permits consideration of structural parameters in pathway regulation; here we predict that inhibition of NF-kappaB is directly affected by actin filaments of the cytoskeleton sequestering excess inhibitors, therefore regulating steady-state and feedback behaviour.

  19. On the improvement of neural cryptography using erroneous transmitted information with error prediction.

    Science.gov (United States)

    Allam, Ahmed M; Abbas, Hazem M

    2010-12-01

    Neural cryptography deals with the problem of "key exchange" between two neural networks using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between the two communicating parties is eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process. Therefore, diminishing the probability of such a threat improves the reliability of exchanging the output bits through a public channel. The synchronization with feedback algorithm is one of the existing algorithms that enhances the security of neural cryptography. This paper proposes three new algorithms to enhance the mutual learning process. They mainly depend on disrupting the attacker confidence in the exchanged outputs and input patterns during training. The first algorithm is called "Do not Trust My Partner" (DTMP), which relies on one party sending erroneous output bits, with the other party being capable of predicting and correcting this error. The second algorithm is called "Synchronization with Common Secret Feedback" (SCSFB), where inputs are kept partially secret and the attacker has to train its network on input patterns that are different from the training sets used by the communicating parties. The third algorithm is a hybrid technique combining the features of the DTMP and SCSFB. The proposed approaches are shown to outperform the synchronization with feedback algorithm in the time needed for the parties to synchronize.

  20. On the Use of Time-Limited Information for Maintenance Decision Support: A Predictive Approach under Maintenance Constraints

    Directory of Open Access Journals (Sweden)

    E. Khoury

    2013-01-01

    Full Text Available This paper deals with a gradually deteriorating system operating under an uncertain environment whose state is only known on a finite rolling horizon. As such, the system is subject to constraints. Maintenance actions can only be planned at imposed times called maintenance opportunities that are available on a limited visibility horizon. This system can, for example, be a commercial vehicle with a monitored critical component that can be maintained only in some specific workshops. Based on the considered system, we aim to use the monitoring data and the time-limited information for maintenance decision support in order to reduce its costs. We propose two predictive maintenance policies based, respectively, on cost and reliability criteria. Classical age-based and condition-based policies are considered as benchmarks. The performance assessment shows the value of the different types of information and the best way to use them in maintenance decision making.

  1. A Modified Spatiotemporal Fusion Algorithm Using Phenological Information for Predicting Reflectance of Paddy Rice in Southern China

    Directory of Open Access Journals (Sweden)

    Mengxue Liu

    2018-05-01

    Full Text Available Satellite data for studying surface dynamics in heterogeneous landscapes are missing due to frequent cloud contamination, low temporal resolution, and technological difficulties in developing satellites. A modified spatiotemporal fusion algorithm for predicting the reflectance of paddy rice is presented in this paper. The algorithm uses phenological information extracted from a moderate-resolution imaging spectroradiometer enhanced vegetation index time series to improve the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM. The algorithm is tested with satellite data on Yueyang City, China. The main contribution of the modified algorithm is the selection of similar neighborhood pixels by using phenological information to improve accuracy. Results show that the modified algorithm performs better than ESTARFM in visual inspection and quantitative metrics, especially for paddy rice. This modified algorithm provides not only new ideas for the improvement of spatiotemporal data fusion method, but also technical support for the generation of remote sensing data with high spatial and temporal resolution.

  2. Mediated interruptions of anaesthesia providers using predictions of workload from anaesthesia information management system data.

    Science.gov (United States)

    Epstein, R H; Dexter, F

    2012-09-01

    Perioperative interruptions generated electronically from anaesthesia information management systems (AIMS) can provide useful feedback, but may adversely affect task performance if distractions occur at inopportune moments. Ideally such interruptions would occur only at times when their impact would be minimal. In this study of AIMS data, we evaluated the times of comments, drugs, fluids and periodic assessments (e.g. electrocardiogram diagnosis and train-of-four) to develop recommendations for the timing of interruptions during the intraoperative period. The 39,707 cases studied were divided into intervals between: 1) enter operating room; 2) induction; 3) intubation; 4) surgical incision; and 5) end surgery. Five-minute intervals of no documentation were determined for each case. The offsets from the start of each interval when >50% of ongoing cases had completed initial documentation were calculated (MIN50). The primary endpoint for each interval was the percentage of all cases still ongoing at MIN50. Results were that the intervals from entering the operating room to induction and from induction to intubation were unsuitable for interruptions confirming prior observational studies of anaesthesia workload. At least 13 minutes after surgical incision was the most suitable time for interruptions with 92% of cases still ongoing. Timing was minimally affected by the type of anaesthesia, surgical facility, surgical service, prone positioning or scheduled case duration. The implication of our results is that for mediated interruptions, waiting at least 13 minutes after the start of surgery is appropriate. Although we used AIMS data, operating room information system data is also suitable.

  3. Goal-directed mechanisms that constrain retrieval predict subsequent memory for new "foil" information.

    Science.gov (United States)

    Vogelsang, David A; Bonnici, Heidi M; Bergström, Zara M; Ranganath, Charan; Simons, Jon S

    2016-08-01

    To remember a previous event, it is often helpful to use goal-directed control processes to constrain what comes to mind during retrieval. Behavioral studies have demonstrated that incidental learning of new "foil" words in a recognition test is superior if the participant is trying to remember studied items that were semantically encoded compared to items that were non-semantically encoded. Here, we applied subsequent memory analysis to fMRI data to understand the neural mechanisms underlying the "foil effect". Participants encoded information during deep semantic and shallow non-semantic tasks and were tested in a subsequent blocked memory task to examine how orienting retrieval towards different types of information influences the incidental encoding of new words presented as foils during the memory test phase. To assess memory for foils, participants performed a further surprise old/new recognition test involving foil words that were encountered during the previous memory test blocks as well as completely new words. Subsequent memory effects, distinguishing successful versus unsuccessful incidental encoding of foils, were observed in regions that included the left inferior frontal gyrus and posterior parietal cortex. The left inferior frontal gyrus exhibited disproportionately larger subsequent memory effects for semantic than non-semantic foils, and significant overlap in activity during semantic, but not non-semantic, initial encoding and foil encoding. The results suggest that orienting retrieval towards different types of foils involves re-implementing the neurocognitive processes that were involved during initial encoding. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. How predictive quantitative modelling of tissue organisation can inform liver disease pathogenesis.

    Science.gov (United States)

    Drasdo, Dirk; Hoehme, Stefan; Hengstler, Jan G

    2014-10-01

    From the more than 100 liver diseases described, many of those with high incidence rates manifest themselves by histopathological changes, such as hepatitis, alcoholic liver disease, fatty liver disease, fibrosis, and, in its later stages, cirrhosis, hepatocellular carcinoma, primary biliary cirrhosis and other disorders. Studies of disease pathogeneses are largely based on integrating -omics data pooled from cells at different locations with spatial information from stained liver structures in animal models. Even though this has led to significant insights, the complexity of interactions as well as the involvement of processes at many different time and length scales constrains the possibility to condense disease processes in illustrations, schemes and tables. The combination of modern imaging modalities with image processing and analysis, and mathematical models opens up a promising new approach towards a quantitative understanding of pathologies and of disease processes. This strategy is discussed for two examples, ammonia metabolism after drug-induced acute liver damage, and the recovery of liver mass as well as architecture during the subsequent regeneration process. This interdisciplinary approach permits integration of biological mechanisms and models of processes contributing to disease progression at various scales into mathematical models. These can be used to perform in silico simulations to promote unravelling the relation between architecture and function as below illustrated for liver regeneration, and bridging from the in vitro situation and animal models to humans. In the near future novel mechanisms will usually not be directly elucidated by modelling. However, models will falsify hypotheses and guide towards the most informative experimental design. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

  5. Damage and protection cost curves for coastal floods within the 600 largest European cities

    Science.gov (United States)

    Prahl, Boris F.; Boettle, Markus; Costa, Luís; Kropp, Jürgen P.; Rybski, Diego

    2018-01-01

    The economic assessment of the impacts of storm surges and sea-level rise in coastal cities requires high-level information on the damage and protection costs associated with varying flood heights. We provide a systematically and consistently calculated dataset of macroscale damage and protection cost curves for the 600 largest European coastal cities opening the perspective for a wide range of applications. Offering the first comprehensive dataset to include the costs of dike protection, we provide the underpinning information to run comparative assessments of costs and benefits of coastal adaptation. Aggregate cost curves for coastal flooding at the city-level are commonly regarded as by-products of impact assessments and are generally not published as a standalone dataset. Hence, our work also aims at initiating a more critical discussion on the availability and derivation of cost curves. PMID:29557944

  6. Damage and protection cost curves for coastal floods within the 600 largest European cities

    Science.gov (United States)

    Prahl, Boris F.; Boettle, Markus; Costa, Luís; Kropp, Jürgen P.; Rybski, Diego

    2018-03-01

    The economic assessment of the impacts of storm surges and sea-level rise in coastal cities requires high-level information on the damage and protection costs associated with varying flood heights. We provide a systematically and consistently calculated dataset of macroscale damage and protection cost curves for the 600 largest European coastal cities opening the perspective for a wide range of applications. Offering the first comprehensive dataset to include the costs of dike protection, we provide the underpinning information to run comparative assessments of costs and benefits of coastal adaptation. Aggregate cost curves for coastal flooding at the city-level are commonly regarded as by-products of impact assessments and are generally not published as a standalone dataset. Hence, our work also aims at initiating a more critical discussion on the availability and derivation of cost curves.

  7. Using time-to-contact information to assess potential collision modulates both visual and temporal prediction networks

    Directory of Open Access Journals (Sweden)

    Jennifer T Coull

    2008-09-01

    Full Text Available Accurate estimates of the time-to-contact (TTC of approaching objects are crucial for survival. We used an ecologically valid driving simulation to compare and contrast the neural substrates of egocentric (head-on approach and allocentric (lateral approach TTC tasks in a fully factorial, event-related fMRI design. Compared to colour control tasks, both egocentric and allocentric TTC tasks activated left ventral premotor cortex/frontal operculum and inferior parietal cortex, the same areas that have previously been implicated in temporal attentional orienting. Despite differences in visual and cognitive demands, both TTC and temporal orienting paradigms encourage the use of temporally predictive information to guide behaviour, suggesting these areas may form a core network for temporal prediction. We also demonstrated that the temporal derivative of the perceptual index tau (tau-dot held predictive value for making collision judgements and varied inversely with activity in primary visual cortex (V1. Specifically, V1 activity increased with the increasing likelihood of reporting a collision, suggesting top-down attentional modulation of early visual processing areas as a function of subjective collision. Finally, egocentric viewpoints provoked a response bias for reporting collisions, rather than no-collisions, reflecting increased caution for head-on approaches. Associated increases in SMA activity suggest motor preparation mechanisms were engaged, despite the perceptual nature of the task.

  8. Health Insurance Premium Increases for the 5 Largest School Districts in the United States, 2004–2008

    Science.gov (United States)

    Cantillo, John R.

    2010-01-01

    Background Local school districts are often one of the largest, if not the largest, employers in their respective communities. Like many large employers, school districts offer health insurance to their employees. There is a lack of information about the rate of health insurance premiums in US school districts relative to other employers. Objective To assess the change in the costs of healthcare insurance in the 5 largest public school districts in the United States, between 2004 and 2008, as representative of large public employers in the country. Methods Data for this study were drawn exclusively from a survey sent to the 5 largest public school districts in the United States. The survey requested responses on 3 data elements for each benefit plan offered from 2004 through 2008; these included enrollment, employee costs, and employer costs. Results The premium growth for the 5 largest school districts has slowed down and is consistent with other purchasers—Kaiser/Health Research & Educational Trust and the Federal Employee Health Benefit Program. The average increase in health insurance premium for the schools was 5.9% in 2008, and the average annual growth rate over the study period was 7.5%. For family coverage, these schools provide the most generous employer contribution (80.8%) compared with the employer contribution reported by other employers (73.5%) for 2008. Conclusions Often the largest employers in their communities, school districts demonstrate a commitment to provide choice of benefits and affordability for employees and their families. Despite constraints typical of public employers, the 5 largest school districts in the United States have decelerated in premium growth consistent with other purchasers, albeit at a slower pace. PMID:25126311

  9. Health insurance premium increases for the 5 largest school districts in the United States, 2004-2008.

    Science.gov (United States)

    Cantillo, John R

    2010-03-01

    Local school districts are often one of the largest, if not the largest, employers in their respective communities. Like many large employers, school districts offer health insurance to their employees. There is a lack of information about the rate of health insurance premiums in US school districts relative to other employers. To assess the change in the costs of healthcare insurance in the 5 largest public school districts in the United States, between 2004 and 2008, as representative of large public employers in the country. Data for this study were drawn exclusively from a survey sent to the 5 largest public school districts in the United States. The survey requested responses on 3 data elements for each benefit plan offered from 2004 through 2008; these included enrollment, employee costs, and employer costs. The premium growth for the 5 largest school districts has slowed down and is consistent with other purchasers-Kaiser/Health Research & Educational Trust and the Federal Employee Health Benefit Program. The average increase in health insurance premium for the schools was 5.9% in 2008, and the average annual growth rate over the study period was 7.5%. For family coverage, these schools provide the most generous employer contribution (80.8%) compared with the employer contribution reported by other employers (73.5%) for 2008. Often the largest employers in their communities, school districts demonstrate a commitment to provide choice of benefits and affordability for employees and their families. Despite constraints typical of public employers, the 5 largest school districts in the United States have decelerated in premium growth consistent with other purchasers, albeit at a slower pace.

  10. Watching the Creation of Southern California's Largest Reservoir

    Science.gov (United States)

    2001-01-01

    The new Diamond Valley Lake Reservoir near the city of Hemet in Riverside County is billed as the largest earthworks construction project in U.S.history. Construction began in 1995 and involved 31 million cubic meters of foundation excavation and 84 million cubic meters of embankment construction. This set of MISR images captures the most recent phase in the reservoir's activation. At the upper left is a natural-color view acquired by the instrument's vertical-viewing (nadir) camera on March 14, 2000 (Terra orbit 1273), shortly after the Metropolitan Water District began filling the reservoir with water from the Colorado River and Northern California. Water appears darker than the surrounding land. The image at the upper right was acquired nearly one year later on March 1, 2001 (Terra orbit 6399), and shows a clear increase in the reservoir's water content. When full, the lake will hold nearly a trillion liters of water.According to the Metropolitan Water District, the 7 kilometer x 3 kilometer reservoir nearly doubles Southern California's above-groundwater storage capacity. In addition to routine water management, Diamond Valley Lake is designed to provide protection against drought and a six-month emergency supply in the event of earthquake damage to a major aqueduct. In the face of electrical power shortages, it is also expected to reduce dependence on the pumping of water from northern mountains during the high-demand summer months. An unexpected result of site excavation was the uncovering of mastodon and mammoth skeletons along with bones from extinct species not previously thought to have been indigenous to the area, such as the giant long-horned bison and North American lion. A museum and interpretive center is being built to protect these finds.The lower MISR image, from May 20, 2001 (Terra orbit 7564), is a false-color view combining data from the instrument's 26-degree forward view (displayed as blue) with data from the 26-degree backward view

  11. Drilling the Bushveld Complex- the world's largest layered mafic intrusion

    Science.gov (United States)

    Ashwal, L. D.; Webb, S. J.; Trumbull, R. B.

    2013-12-01

    The fact that surprising new discoveries can be made in layered mafic intrusions (e.g., subtle 100-150 m cyclicity in apparently homogeneous cumulates over 1000s of m) means that we are still in the first-order characterization phase of understanding these objects. Accordingly, we have secured funding from ICDP for a planning workshop to be held in Johannesburg in early 2014, aimed at scientific drilling of the Bushveld Complex, the world's largest layered mafic intrusion. Science objectives include, but are not limited to: 1. Magma chamber processes & melt evolution. How many melts/magmas/mushes were involved, what were their compositions and how did they interact? What, if anything, is missing from the Complex, and where did it go? Did Bushveld magmatism have an effect upon Earth's atmosphere at 2 Ga? 2. Crust-mantle interactions & origin of Bushveld granitoids. Are Bushveld granites & rhyolites crustal melts, differentiates from the mafic magmas or products of immiscibility? How can the evolved isotopic signatures in the mafic rocks (e.g., epsilon Nd to -8) be understood? 3. Origin of ore deposits. What were the relative roles of gravity settling, magma mixing, immiscibility and hydrothermal fluid transport in producing the PGE, Cr and V deposits? We have identified 3 potential drilling targets representing a total of ~12 km of drill core. Exact locations of drill sites are to be discussed at the workshop. Target A- East-Central Bushveld Complex. We propose 3 overlapping 3 km boreholes that will provide the first roof-to-floor continuous coverage of the Rustenburg Layered Suite. These boreholes will represent a curated, internationally available reference collection of Bushveld material for present and future research. Target B- Southeastern Bushveld Complex. We propose a single borehole of ~2 km depth, collared in Rooiberg felsite, and positioned to intersect the Roof Zone, Upper Zone, Main Zone and floor of the Complex. Amongst other things, this site will

  12. Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels

    Directory of Open Access Journals (Sweden)

    McDermott Drew

    2009-08-01

    Full Text Available Abstract Background Proteins interact through specific binding interfaces that contain many residues in domains. Protein interactions thus occur on three different levels of a concept hierarchy: whole-proteins, domains, and residues. Each level offers a distinct and complementary set of features for computationally predicting interactions, including functional genomic features of whole proteins, evolutionary features of domain families and physical-chemical features of individual residues. The predictions at each level could benefit from using the features at all three levels. However, it is not trivial as the features are provided at different granularity. Results To link up the predictions at the three levels, we propose a multi-level machine-learning framework that allows for explicit information flow between the levels. We demonstrate, using representative yeast interaction networks, that our algorithm is able to utilize complementary feature sets to make more accurate predictions at the three levels than when the three problems are approached independently. To facilitate application of our multi-level learning framework, we discuss three key aspects of multi-level learning and the corresponding design choices that we have made in the implementation of a concrete learning algorithm. 1 Architecture of information flow: we show the greater flexibility of bidirectional flow over independent levels and unidirectional flow; 2 Coupling mechanism of the different levels: We show how this can be accomplished via augmenting the training sets at each level, and discuss the prevention of error propagation between different levels by means of soft coupling; 3 Sparseness of data: We show that the multi-level framework compounds data sparsity issues, and discuss how this can be dealt with by building local models in information-rich parts of the data. Our proof-of-concept learning algorithm demonstrates the advantage of combining levels, and opens up

  13. Chebyshev polynomial functions based locally recurrent neuro-fuzzy information system for prediction of financial and energy market data

    Directory of Open Access Journals (Sweden)

    A.K. Parida

    2016-09-01

    Full Text Available In this paper Chebyshev polynomial functions based locally recurrent neuro-fuzzy information system is presented for the prediction and analysis of financial and electrical energy market data. The normally used TSK-type feedforward fuzzy neural network is unable to take the full advantage of the use of the linear fuzzy rule base in accurate input–output mapping and hence the consequent part of the rule base is made nonlinear using polynomial or arithmetic basis functions. Further the Chebyshev polynomial functions provide an expanded nonlinear transformation to the input space thereby increasing its dimension for capturing the nonlinearities and chaotic variations in financial or energy market data streams. Also the locally recurrent neuro-fuzzy information system (LRNFIS includes feedback loops both at the firing strength layer and the output layer to allow signal flow both in forward and backward directions, thereby making the LRNFIS mimic a dynamic system that provides fast convergence and accuracy in predicting time series fluctuations. Instead of using forward and backward least mean square (FBLMS learning algorithm, an improved Firefly-Harmony search (IFFHS learning algorithm is used to estimate the parameters of the consequent part and feedback loop parameters for better stability and convergence. Several real world financial and energy market time series databases are used for performance validation of the proposed LRNFIS model.

  14. A marine heatwave drives massive losses from the world’s largest seagrass carbon stocks

    KAUST Repository

    Arias-Ortiz, A.

    2018-03-29

    Seagrass ecosystems contain globally significant organic carbon (C) stocks. However, climate change and increasing frequency of extreme events threaten their preservation. Shark Bay, Western Australia, has the largest C stock reported for a seagrass ecosystem, containing up to 1.3% of the total C stored within the top metre of seagrass sediments worldwide. On the basis of field studies and satellite imagery, we estimate that 36% of Shark Bay’s seagrass meadows were damaged following a marine heatwave in 2010/2011. Assuming that 10 to 50% of the seagrass sediment C stock was exposed to oxic conditions after disturbance, between 2 and 9 Tg CO could have been released to the atmosphere during the following three years, increasing emissions from land-use change in Australia by 4–21% per annum. With heatwaves predicted to increase with further climate warming, conservation of seagrass ecosystems is essential to avoid adverse feedbacks on the climate system.

  15. A general scaling law reveals why the largest animals are not the fastest.

    Science.gov (United States)

    Hirt, Myriam R; Jetz, Walter; Rall, Björn C; Brose, Ulrich

    2017-08-01

    Speed is the fundamental constraint on animal movement, yet there is no general consensus on the determinants of maximum speed itself. Here, we provide a general scaling model of maximum speed with body mass, which holds across locomotion modes, ecosystem types and taxonomic groups. In contrast to traditional power-law scaling, we predict a hump-shaped relationship resulting from a finite acceleration time for animals, which explains why the largest animals are not the fastest. This model is strongly supported by extensive empirical data (474 species, with body masses ranging from 30 μg to 100 tonnes) from terrestrial as well as aquatic ecosystems. Our approach unravels a fundamental constraint on the upper limit of animal movement, thus enabling a better understanding of realized movement patterns in nature and their multifold ecological consequences.

  16. A marine heatwave drives massive losses from the world's largest seagrass carbon stocks

    Science.gov (United States)

    Arias-Ortiz, A.; Serrano, O.; Masqué, P.; Lavery, P. S.; Mueller, U.; Kendrick, G. A.; Rozaimi, M.; Esteban, A.; Fourqurean, J. W.; Marbà, N.; Mateo, M. A.; Murray, K.; Rule, M. J.; Duarte, C. M.

    2018-04-01

    Seagrass ecosystems contain globally significant organic carbon (C) stocks. However, climate change and increasing frequency of extreme events threaten their preservation. Shark Bay, Western Australia, has the largest C stock reported for a seagrass ecosystem, containing up to 1.3% of the total C stored within the top metre of seagrass sediments worldwide. On the basis of field studies and satellite imagery, we estimate that 36% of Shark Bay's seagrass meadows were damaged following a marine heatwave in 2010/2011. Assuming that 10 to 50% of the seagrass sediment C stock was exposed to oxic conditions after disturbance, between 2 and 9 Tg CO2 could have been released to the atmosphere during the following three years, increasing emissions from land-use change in Australia by 4-21% per annum. With heatwaves predicted to increase with further climate warming, conservation of seagrass ecosystems is essential to avoid adverse feedbacks on the climate system.

  17. Long-Range Reduced Predictive Information Transfers of Autistic Youths in EEG Sensor-Space During Face Processing.

    Science.gov (United States)

    Khadem, Ali; Hossein-Zadeh, Gholam-Ali; Khorrami, Anahita

    2016-03-01

    The majority of previous functional/effective connectivity studies conducted on the autistic patients converged to the underconnectivity theory of ASD: "long-range underconnectivity and sometimes short-rang overconnectivity". However, to the best of our knowledge the total (linear and nonlinear) predictive information transfers (PITs) of autistic patients have not been investigated yet. Also, EEG data have rarely been used for exploring the information processing deficits in autistic subjects. This study is aimed at comparing the total (linear and nonlinear) PITs of autistic and typically developing healthy youths during human face processing by using EEG data. The ERPs of 12 autistic youths and 19 age-matched healthy control (HC) subjects were recorded while they were watching upright and inverted human face images. The PITs among EEG channels were quantified using two measures separately: transfer entropy with self-prediction optimality (TESPO), and modified transfer entropy with self-prediction optimality (MTESPO). Afterwards, the directed differential connectivity graphs (dDCGs) were constructed to characterize the significant changes in the estimated PITs of autistic subjects compared with HC ones. By using both TESPO and MTESPO, long-range reduction of PITs of ASD group during face processing was revealed (particularly from frontal channels to right temporal channels). Also, it seemed the orientation of face images (upright or upside down) did not modulate the binary pattern of PIT-based dDCGs, significantly. Moreover, compared with TESPO, the results of MTESPO were more compatible with the underconnectivity theory of ASD in the sense that MTESPO showed no long-range increase in PIT. It is also noteworthy that to the best of our knowledge it is the first time that a version of MTE is applied for patients (here ASD) and it is also its first use for EEG data analysis.

  18. Development of cesium 137 plant uptake predicting model using geographical information systems

    International Nuclear Information System (INIS)

    Lomonos, O.V.

    2002-01-01

    Soil-plant system is a critical component of food chain in processes of Cs 137 migration. In this component it is possible to decrease greatly Cs 137 uptake in food chain. Development of Cs 137 migration model in soil-plant system enable to determine amount of Cs 137 in plant uptake and evaluate agricultural produce accordance with modern ecological requirements. Also this model can help with management of agricultural production. Geographical information systems (GIS) have a wide propagation in radioecology at present time. Models using GIS have several advantages: relative simplicity of evaluation, visualization of evaluated results etc. As a result, plots with possible Cs 137 uptake increasing could be easily discovered. Physical decay, Cs 137 sorption and fixation by soil, Cs 137 vertical migration in soil profile and plant uptake are the main components of the Cs 137 migration model in soil-plant system. Content of biologically available Cs 137 calculated taking into account all of these components. Using GIS with Cs 137 migration model in soil-plant system lets efficiently discover those factors that have major influence on Cs 137 plant uptake increasing. This model improves agricultural production on territories, which polluted by Cs 137

  19. Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species

    Science.gov (United States)

    Then, Amy Y.; Hoenig, John M; Hall, Norman G.; Hewitt, David A.

    2015-01-01

    Many methods have been developed in the last 70 years to predict the natural mortality rate, M, of a stock based on empirical evidence from comparative life history studies. These indirect or empirical methods are used in most stock assessments to (i) obtain estimates of M in the absence of direct information, (ii) check on the reasonableness of a direct estimate of M, (iii) examine the range of plausible M estimates for the stock under consideration, and (iv) define prior distributions for Bayesian analyses. The two most cited empirical methods have appeared in the literature over 2500 times to date. Despite the importance of these methods, there is no consensus in the literature on how well these methods work in terms of prediction error or how their performance may be ranked. We evaluate estimators based on various combinations of maximum age (tmax), growth parameters, and water temperature by seeing how well they reproduce >200 independent, direct estimates of M. We use tenfold cross-validation to estimate the prediction error of the estimators and to rank their performance. With updated and carefully reviewed data, we conclude that a tmax-based estimator performs the best among all estimators evaluated. The tmax-based estimators in turn perform better than the Alverson–Carney method based on tmax and the von Bertalanffy K coefficient, Pauly’s method based on growth parameters and water temperature and methods based just on K. It is possible to combine two independent methods by computing a weighted mean but the improvement over the tmax-based methods is slight. Based on cross-validation prediction error, model residual patterns, model parsimony, and biological considerations, we recommend the use of a tmax-based estimator (M=4.899tmax−0.916">M=4.899t−0.916maxM=4.899tmax−0.916, prediction error = 0.32) when possible and a growth-based method (M=4.118K0.73L∞−0.33">M=4.118K0.73L−0.33∞M=4.118K0.73L∞−0.33 , prediction error

  20. Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

    Directory of Open Access Journals (Sweden)

    Lemke Ney

    2009-09-01

    Full Text Available Abstract Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing

  1. Coupled information diffusion--pest dynamics models predict delayed benefits of farmer cooperation in pest management programs.

    Science.gov (United States)

    Rebaudo, François; Dangles, Olivier

    2011-10-01

    Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' "diffusion of innovation theory". In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.

  2. Predicting long-term average concentrations of traffic-related air pollutants using GIS-based information

    Science.gov (United States)

    Hochadel, Matthias; Heinrich, Joachim; Gehring, Ulrike; Morgenstern, Verena; Kuhlbusch, Thomas; Link, Elke; Wichmann, H.-Erich; Krämer, Ursula

    Global regression models were developed to estimate individual levels of long-term exposure to traffic-related air pollutants. The models are based on data of a one-year measurement programme including geographic data on traffic and population densities. This investigation is part of a cohort study on the impact of traffic-related air pollution on respiratory health, conducted at the westerly end of the Ruhr-area in North-Rhine Westphalia, Germany. Concentrations of NO 2, fine particle mass (PM 2.5) and filter absorbance of PM 2.5 as a marker for soot were measured at 40 sites spread throughout the study region. Fourteen-day samples were taken between March 2002 and March 2003 for each season and site. Annual average concentrations for the sites were determined after adjustment for temporal variation. Information on traffic counts in major roads, building densities and community population figures were collected in a geographical information system (GIS). This information was used to calculate different potential traffic-based predictors: (a) daily traffic flow and maximum traffic intensity of buffers with radii from 50 to 10 000 m and (b) distances to main roads and highways. NO 2 concentration and PM 2.5 absorbance were strongly correlated with the traffic-based variables. Linear regression prediction models, which involved predictors with radii of 50 to 1000 m, were developed for the Wesel region where most of the cohort members lived. They reached a model fit ( R2) of 0.81 and 0.65 for NO 2 and PM 2.5 absorbance, respectively. Regression models for the whole area required larger spatial scales and reached R2=0.90 and 0.82. Comparison of predicted values with NO 2 measurements at independent public monitoring stations showed a satisfactory association ( r=0.66). PM 2.5 concentration, however, was only slightly correlated and thus poorly predictable by traffic-based variables ( rGIS-based regression models offer a promising approach to assess individual levels of

  3. City-ecological perspectives of the development of high urbanized multifunctional centers of the largest Russian cities

    Directory of Open Access Journals (Sweden)

    Kolesnikov Sergey Anatol’evich

    2015-01-01

    Full Text Available This article presents some results of the author’s dissertation research dedicated to formation of an architectural typology of high urbanized multifunctional units of urban structure of the largest cities (further HUMUUS as centers of social activity, which include buildings, constructions, transportation equipment and open spaces, where human flows transpose, start and end with the purpose of bringing into this space a concentrated maximum of goods, services and information with minimum time expenditures. This article draws attention to the development analysis of the structure-forming functions of HUMUUS and their town planning and environmental impact on the surrounding area. The study of planning structures of the largest Russian cities (Samara, Kazan, Nizhny Novgorod made it possible to identify a number of main objects, in which structure-forming functions of HUMUUS are materialized: railroad complex (historically formed, developed, dominated, system-wide road junction, transport interchange hub (providing intraurban messages, public office and business centers, leisure and entertainment centers, shopping centers. Basing on researches of Russian and foreign experience, it is possible to predict with full confidence the following trends and streams of environmental and urban development of HUMUUS in the near-term perspective: Strengthening of the environmental and urban frame by network evolution of HUMUUS; Inclusion of green areas of HUMUUS in the system of citywide green areas; Increment of the interest of the investors to the public road junction for the purpose of reorganization of them to full HUMUUS with all characteristics of high-urbanized and environmental and urban reorganization (separation of traffic and pedestrian flows, maximum capacity, multiple-level system, multifunctional, increase in landscaped green space, reconstruction of engineering systems and communications, the use of modern ecological building designs and

  4. Comparative Analysis Of Three Largest World Models Of Business Excellence

    Directory of Open Access Journals (Sweden)

    Jasminka Samardžija

    2009-07-01

    Full Text Available Business excellence has become the strongest means of achieving competitive advantage of companies while total management of quality has become the road that ensures support of excellent results recognized by many world companies. Despite many differences, we can conclude that models have many common elements. By the audit in 2005, the DP and MBNQA moved the focus from excellence of product, i.e service, onto the excellence of quality of the entire organization process. Thus, the quality got strategic dimension instead of technical one and the accent passed from the technical quality on the total excellence of all organization processes. The joint movement goes to the direction of good management and appreciation of systems thinking. The very structure of EFOM model criteria itself is adjusted to strategic dimension of quality and that is why the model underwent only short audits within the criteria themselves. Essentially, the model remained unchanged. In all models, the accent is on the satisfaction of buyers, employees and community. National rewards for quality have an important role in promotion and giving a prize to excellence in organization performances. Moreover, they raise quality standards of companies and the country profile as a whole. Considering the GDP per capita and the percentage of certification level of companies, Croatia has all the predispositions for introduction the EFQM model of business excellence with the basic aim of deficit decrease in foreign trade balance and strengthening of competitiveness as the necessary preliminary work for the entrance in the competitive market of the EU. Quality management was introduced in many organizations. The methods used at that time developed in the course of years, and what are to predict is the continuation of the evolution road model as well as the method of business excellence.

  5. Turning the rumor of May 11, 2011 earthquake prediction In Rome, Italy, into an information day on earthquake hazard

    Science.gov (United States)

    Amato, A.; Cultrera, G.; Margheriti, L.; Nostro, C.; Selvaggi, G.; INGVterremoti Team

    2011-12-01

    A devastating earthquake had been predicted for May 11, 2011 in Rome. This prediction was never released officially by anyone, but it grew up in the Internet and was amplified by media. It was erroneously ascribed to Raffaele Bendandi, an Italian self-taught natural scientist who studied planetary motions. Indeed, around May 11, 2011, a planetary alignment was really expected and this contributed to give credibility to the earthquake prediction among people. During the previous months, INGV was overwhelmed with requests for information about this supposed prediction by Roman inhabitants and tourists. Given the considerable mediatic impact of this expected earthquake, INGV decided to organize an Open Day in its headquarter in Rome for people who wanted to learn more about the Italian seismicity and the earthquake as natural phenomenon. The Open Day was preceded by a press conference two days before, in which we talked about this prediction, we presented the Open Day, and we had a scientific discussion with journalists about the earthquake prediction and more in general on the real problem of seismic risk in Italy. About 40 journalists from newspapers, local and national tv's, press agencies and web news attended the Press Conference and hundreds of articles appeared in the following days, advertising the 11 May Open Day. The INGV opened to the public all day long (9am - 9pm) with the following program: i) meetings with INGV researchers to discuss scientific issues; ii) visits to the seismic monitoring room, open 24h/7 all year; iii) guided tours through interactive exhibitions on earthquakes and Earth's deep structure; iv) lectures on general topics from the social impact of rumors to seismic risk reduction; v) 13 new videos on channel YouTube.com/INGVterremoti to explain the earthquake process and give updates on various aspects of seismic monitoring in Italy; vi) distribution of books and brochures. Surprisingly, more than 3000 visitors came to visit INGV

  6. Alternative Fuels Data Center: America's Largest Home Runs on Biodiesel in

    Science.gov (United States)

    North Carolina America's Largest Home Runs on Biodiesel in North Carolina to someone by E-mail Share Alternative Fuels Data Center: America's Largest Home Runs on Biodiesel in North Carolina on Facebook Tweet about Alternative Fuels Data Center: America's Largest Home Runs on Biodiesel in North

  7. Information

    International Nuclear Information System (INIS)

    Boyard, Pierre.

    1981-01-01

    The fear for nuclear energy and more particularly for radioactive wastes is analyzed in the sociological context. Everybody agree on the information need, information is available but there is a problem for their diffusion. Reactions of the public are analyzed and journalists, scientists and teachers have a role to play [fr

  8. Scaling relationships among drivers of aquatic respiration from the smallest to the largest freshwater ecosystems

    Science.gov (United States)

    Hall, Ed K; Schoolmaster, Donald; Amado, A.M; Stets, Edward G.; Lennon, J.T.; Domaine, L.; Cotner, J.B.

    2016-01-01

    To address how various environmental parameters control or constrain planktonic respiration (PR), we used geometric scaling relationships and established biological scaling laws to derive quantitative predictions for the relationships among key drivers of PR. We then used empirical measurements of PR and environmental (soluble reactive phosphate [SRP], carbon [DOC], chlorophyll a [Chl-a)], and temperature) and landscape parameters (lake area [LA] and watershed area [WA]) from a set of 44 lakes that varied in size and trophic status to test our hypotheses. We found that landscape-level processes affected PR through direct effects on DOC and temperature and indirectly via SRP. In accordance with predictions made from known relationships and scaling laws, scale coefficients (the parameter that describes the shape of a relationship between 2 variables) were found to be negative and have an absolute value 1, others respiration from small pond catchments to the largest body of freshwater on the planet, Lake Superior, these findings should be applicable to controls of PR for the great majority of temperate aquatic ecosystems.

  9. A New Prediction Model for Transformer Winding Hotspot Temperature Fluctuation Based on Fuzzy Information Granulation and an Optimized Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Li Zhang

    2017-12-01

    Full Text Available Winding hotspot temperature is the key factor affecting the load capacity and service life of transformers. For the early detection of transformer winding hotspot temperature anomalies, a new prediction model for the hotspot temperature fluctuation range based on fuzzy information granulation (FIG and the chaotic particle swarm optimized wavelet neural network (CPSO-WNN is proposed in this paper. The raw data are firstly processed by FIG to extract useful information from each time window. The extracted information is then used to construct a wavelet neural network (WNN prediction model. Furthermore, the structural parameters of WNN are optimized by chaotic particle swarm optimization (CPSO before it is used to predict the fluctuation range of the hotspot temperature. By analyzing the experimental data with four different prediction models, we find that the proposed method is more effective and is of guiding significance for the operation and maintenance of transformers.

  10. A study of the predictive model on the user reaction time using the information amount and similarity

    International Nuclear Information System (INIS)

    Lee, Sungjin; Heo, Gyunyoung; Chang, S.H.

    2004-01-01

    Human operations through a user interface are divided into two types. The one is the single operation that is performed on a static interface. The other is the sequential operation that achieves a goal by handling several displays through operator's navigation in the crt-based console. Sequential operation has similar meaning with continuous task. Most operations in recently developed computer applications correspond to the sequential operation, and the single operation can be considered as a part of the sequential operation. In the area of HCI (human computer interaction) evaluation, the Hick-Hyman law counts as the most powerful theory. The most important factor in the equation of Hick-Hyman law about choice reaction time is the quantified amount of information conveyed by a statement, stimulus, or event. Generally, we can expect that if there are some similarities between a series of interfaces, human operator is able to use his attention resource effectively. That is the performance of human operator is increased by the similarity. The similarity may be able to affect the allocation of attention resource based on separate STSS (short-term sensory store) and long-term memory. There are theories related with this concept, which are task switching paradigm and the law of practice. However, it is not easy to explain the human operator performance with only the similarity or the information amount. There are few theories to explain the performance with the combination of the similarity and the information amount. The objective of this paper is to purpose and validate the quantitative and predictive model on the user reaction time in CRT-based displays. Another objective is to validate various theories related with human cognition and perception, which are Hick-Hyman law and the law of practice as representative theories. (author)

  11. Application of the largest Lyapunov exponent and non-linear fractal extrapolation algorithm to short-term load forecasting

    International Nuclear Information System (INIS)

    Wang Jianzhou; Jia Ruiling; Zhao Weigang; Wu Jie; Dong Yao

    2012-01-01

    Highlights: ► The maximal predictive step size is determined by the largest Lyapunov exponent. ► A proper forecasting step size is applied to load demand forecasting. ► The improved approach is validated by the actual load demand data. ► Non-linear fractal extrapolation method is compared with three forecasting models. ► Performance of the models is evaluated by three different error measures. - Abstract: Precise short-term load forecasting (STLF) plays a key role in unit commitment, maintenance and economic dispatch problems. Employing a subjective and arbitrary predictive step size is one of the most important factors causing the low forecasting accuracy. To solve this problem, the largest Lyapunov exponent is adopted to estimate the maximal predictive step size so that the step size in the forecasting is no more than this maximal one. In addition, in this paper a seldom used forecasting model, which is based on the non-linear fractal extrapolation (NLFE) algorithm, is considered to develop the accuracy of predictions. The suitability and superiority of the two solutions are illustrated through an application to real load forecasting using New South Wales electricity load data from the Australian National Electricity Market. Meanwhile, three forecasting models: the gray model, the seasonal autoregressive integrated moving average approach and the support vector machine method, which received high approval in STLF, are selected to compare with the NLFE algorithm. Comparison results also show that the NLFE model is outstanding, effective, practical and feasible.

  12. Ownership, financing, and management strategies of the ten largest for-profit nursing home chains in the United States.

    Science.gov (United States)

    Harrington, Charlene; Hauser, Clarilee; Olney, Brian; Rosenau, Pauline Vaillancourt

    2011-01-01

    This study examined the ownership, financing, and management strategies of the 10 largest for-profit nursing home chains in the United States, including the four largest chains purchased by private equity corporations. Descriptive data were collected from Internet searches, company reports, and other sources for the decade 1998-2008. Since 1998, the largest chains have made many changes in their ownership and structure, and some have converted from publicly traded companies to private ownership. This study shows the increasing complexity of corporate nursing home ownership and the lack of public information about ownership and financial status. The chains have used strategies to maximize shareholder and investor value that include increasing Medicare revenues, occupancy rates, and company diversification, establishing multiple layers of corporate ownership, developing real estate investment trusts, and creating limited liability companies. These strategies enhance shareholder and investor profits, reduce corporate taxes, and reduce liability risk. There is a need for greater transparency in ownership and financial reporting and for more government oversight of the largest for-profit chains, including those owned by private equity companies.

  13. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV).

    Science.gov (United States)

    Poblete, Tomas; Ortega-Farías, Samuel; Moreno, Miguel Angel; Bardeen, Matthew

    2017-10-30

    Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψ stem ). However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV) is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI) that use information between 500-800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN) models derived from multispectral images to predict the Ψ stem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R²) obtained between ANN outputs and ground-truth measurements of Ψ stem were between 0.56-0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψ stem with a mean absolute error (MAE) of 0.1 MPa, root mean square error (RMSE) of 0.12 MPa, and relative error (RE) of -9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26-0.27 MPa, 0.32-0.34 MPa and -24.2-25.6%, respectively.

  14. Time to Death after Terminal Withdrawal of Mechanical Ventilation: Specific Respiratory and Physiologic Parameters May Inform Physician Predictions.

    Science.gov (United States)

    Long, Ann C; Muni, Sarah; Treece, Patsy D; Engelberg, Ruth A; Nielsen, Elizabeth L; Fitzpatrick, Annette L; Curtis, J Randall

    2015-12-01

    Discussions about withdrawal of life-sustaining therapies often include family members of critically ill patients. These conversations should address essential components of the dying process, including expected time to death after withdrawal. The study objective was to aid physician communication about the dying process by identifying predictors of time to death after terminal withdrawal of mechanical ventilation. We conducted an observational analysis from a single-center, before-after evaluation of an intervention to improve palliative care. We studied 330 patients who died after terminal withdrawal of mechanical ventilation. Predictors included patient demographics, laboratory, respiratory, and physiologic variables, and medication use. The median time to death for the entire cohort was 0.58 hours (interquartile range (IQR) 0.22-2.25 hours) after withdrawal of mechanical ventilation. Using Cox regression, independent predictors of shorter time to death included higher positive end-expiratory pressure (per 1 cm H2O hazard ratio [HR], 1.07; 95% CI 1.04-1.11); higher static pressure (per 1 cm H2O HR, 1.03; 95% CI 1.01-1.04); extubation prior to death (HR, 1.41; 95% CI 1.06-1.86); and presence of diabetes (HR, 1.75; 95% CI 1.25-2.44). Higher noninvasive mean arterial pressure predicted longer time to death (per 1 mmHg HR, 0.98; 95% CI 0.97-0.99). Comorbid illness and key respiratory and physiologic parameters may inform physician predictions of time to death after withdrawal of mechanical ventilation. An understanding of the predictors of time to death may facilitate discussions with family members of dying patients and improve communication about end-of-life care.

  15. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV

    Directory of Open Access Journals (Sweden)

    Tomas Poblete

    2017-10-01

    Full Text Available Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψstem. However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI that use information between 500–800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN models derived from multispectral images to predict the Ψstem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R2 obtained between ANN outputs and ground-truth measurements of Ψstem were between 0.56–0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψstem with a mean absolute error (MAE of 0.1 MPa, root mean square error (RMSE of 0.12 MPa, and relative error (RE of −9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26–0.27 MPa, 0.32–0.34 MPa and −24.2–25.6%, respectively.

  16. Informe

    Directory of Open Access Journals (Sweden)

    Egon Lichetenberger

    1950-10-01

    Full Text Available Informe del doctor Egon Lichetenberger ante el Consejo Directivo de la Facultad, sobre el  curso de especialización en Anatomía Patológica patrocinado por la Kellogg Foundation (Departamento de Patología

  17. Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information

    DEFF Research Database (Denmark)

    Hebsgaard, Stefan M.; Korning, Peter G.; Tolstrup, Niels

    1996-01-01

    Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local predicition of splice sites, is refin...

  18. Signalign: An Ontology of DNA as Signal for Comparative Gene Structure Prediction Using Information-Coding-and-Processing Techniques.

    Science.gov (United States)

    Yu, Ning; Guo, Xuan; Gu, Feng; Pan, Yi

    2016-03-01

    Conventional character-analysis-based techniques in genome analysis manifest three main shortcomings-inefficiency, inflexibility, and incompatibility. In our previous research, a general framework, called DNA As X was proposed for character-analysis-free techniques to overcome these shortcomings, where X is the intermediates, such as digit, code, signal, vector, tree, graph network, and so on. In this paper, we further implement an ontology of DNA As Signal, by designing a tool named Signalign for comparative gene structure analysis, in which DNA sequences are converted into signal series, processed by modified method of dynamic time warping and measured by signal-to-noise ratio (SNR). The ontology of DNA As Signal integrates the principles and concepts of other disciplines including information coding theory and signal processing into sequence analysis and processing. Comparing with conventional character-analysis-based methods, Signalign can not only have the equivalent or superior performance, but also enrich the tools and the knowledge library of computational biology by extending the domain from character/string to diverse areas. The evaluation results validate the success of the character-analysis-free technique for improved performances in comparative gene structure prediction.

  19. The influence of active region information on the prediction of solar flares: an empirical model using data mining

    Directory of Open Access Journals (Sweden)

    M. Núñez

    2005-11-01

    Full Text Available Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL, for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered correlations are described in terms of easy-to-read rules. The results indicate that active region dynamics is essential for predicting solar flares.

  20. In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool

    Science.gov (United States)

    The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to address needs for rapid, cost effective methods of species extrapolation of chemical susceptibility. Specifically, the SeqAPASS tool compares the primary sequence (Level 1), functiona...

  1. The epidemiological trends of head injury in the largest Canadian adult trauma center from 1986 to 2007.

    Science.gov (United States)

    Cadotte, David W; Vachhrajani, Shobhan; Pirouzmand, Farhad

    2011-06-01

    This study documents the epidemiology of head injury over the course of 22 years in the largest Level I adult trauma center in Canada. This information defines the current state, changing pattern, and relative distribution of demographic factors in a defined group of trauma patients. It will aid in hypothesis generation to direct etiological research, administrative resource allocation, and preventative strategies. Data on all the trauma patients treated at Sunnybrook Health Sciences Centre (SHSC) from 1986 to 2007 were collected in a consecutive, prospective fashion. The authors reviewed these data from the Sunnybrook Trauma Registry Database in a retrospective fashion. The aggregate data on head injury included demographic data, cause of injury, and Injury Severity Score (ISS). The collected data were analyzed using univariate techniques to depict the trend of variables over years. The authors used the length of stay (LOS) and number of deaths per year (case fatality rate) as crude measures of outcome. A total of 16,678 patients were treated through the Level I trauma center at SHSC from January 1986 to December 2007. Of these, 9315 patients met the inclusion criteria (ISS > 12, head Abbreviated Injury Scale score > 0). The median age of all trauma patients was 36 years, and 69.6% were male. The median ISS of the head-injury patients was 27. The median age of this group of patients increased by 12 years over the study period. Motorized vehicle accidents accounted for the greatest number of head injuries (60.3%) although the relative percentage decreased over the study period. The median transfer time of patients sustaining a head injury was 2.58 hours, and there was an approximately 45 minute improvement over the 22-year study period. The median LOS in our center decreased from 19 to 10 days over the study period. The average case fatality rate was 17.4% over the study period. In multivariate analysis, more severe injuries were associated with increased LOS as

  2. First Experience from the World Largest fully commercial Solar Heating Plant

    DEFF Research Database (Denmark)

    Heller, Alfred; Furbo, Simon

    1997-01-01

    The first experience from the largest solar heating plant in the world is given. The plant is situated in Marstal and is has a total area of 8000 square m.......The first experience from the largest solar heating plant in the world is given. The plant is situated in Marstal and is has a total area of 8000 square m....

  3. Revisiting the phylogeny of Ocellularieae, the second largest tribe within Graphidaceae (lichenized Ascomycota: Ostropales)

    Science.gov (United States)

    Ekaphan Kraichak; Sittiporn Parnmen; Robert Lücking; Eimy Rivas Plata; Andre Aptroot; Marcela E.S. Caceres; Damien Ertz; Armin Mangold; Joel A. Mercado-Diaz; Khwanruan Papong; Dries Van der Broeck; Gothamie Weerakoon; H. Thorsten. Lumbsch; NO-VALUE

    2014-01-01

    We present an updated 3-locus molecular phylogeny of tribe Ocellularieae, the second largest tribe within subfamily Graphidoideae in the Graphidaceae. Adding 165 newly generated sequences from the mitochondrial small subunit rDNA (mtSSU), the nuclear large subunit rDNA (nuLSU), and the second largest subunit of the DNA-directed RNA polymerase II (RPB2), we currently...

  4. Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

    Science.gov (United States)

    Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

    2015-12-01

    Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

  5. Distribution and Modeled Transport of Plastic Pollution in the Great Lakes, the World's Largest Freshwater Resource

    Directory of Open Access Journals (Sweden)

    Rachel N. Cable

    2017-07-01

    Full Text Available Most plastic pollution originates on land. As such, freshwater bodies serve as conduits for the transport of plastic litter to the ocean. Understanding the concentrations and fluxes of plastic litter in freshwater ecosystems is critical to our understanding of the global plastic litter budget and underpins the success of future management strategies. We conducted a replicated field survey of surface plastic concentrations in four lakes in the North American Great Lakes system, the largest contiguous freshwater system on the planet. We then modeled plastic transport to resolve spatial and temporal variability of plastic distribution in one of the Great Lakes, Lake Erie. Triplicate surface samples were collected at 38 stations in mid-summer of 2014. Plastic particles >106 μm in size were quantified. Concentrations were highest near populated urban areas and their water infrastructure. In the highest concentration trawl, nearly 2 million fragments km−2 were found in the Detroit River—dwarfing previous reports of Great Lakes plastic abundances by over 4-fold. Yet, the accuracy of single trawl counts was challenged: within-station plastic abundances varied 0- to 3-fold between replicate trawls. In the smallest size class (106–1,000 μm, false positive rates of 12–24% were determined analytically for plastic vs. non-plastic, while false negative rates averaged ~18%. Though predicted to form in summer by the existing Lake Erie circulation model, our transport model did not predict a permanent surface “Lake Erie Garbage Patch” in its central basin—a trend supported by field survey data. Rather, general eastward transport with recirculation in the major basins was predicted. Further, modeled plastic residence times were drastically influenced by plastic buoyancy. Neutrally buoyant plastics—those with the same density as the ambient water—were flushed several times slower than plastics floating at the water's surface and exceeded the

  6. Short communication: Use of genomic and metabolic information as well as milk performance records for prediction of subclinical ketosis risk via artificial neural networks.

    Science.gov (United States)

    Ehret, A; Hochstuhl, D; Krattenmacher, N; Tetens, J; Klein, M S; Gronwald, W; Thaller, G

    2015-01-01

    Subclinical ketosis is one of the most prevalent metabolic disorders in high-producing dairy cows during early lactation. This renders its early detection and prevention important for both economical and animal-welfare reasons. Construction of reliable predictive models is challenging, because traits like ketosis are commonly affected by multiple factors. In this context, machine learning methods offer great advantages because of their universal learning ability and flexibility in integrating various sorts of data. Here, an artificial-neural-network approach was applied to investigate the utility of metabolic, genetic, and milk performance data for the prediction of milk levels of β-hydroxybutyrate within and across consecutive weeks postpartum. Data were collected from 218 dairy cows during their first 5wk in milk. All animals were genotyped with a 50,000 SNP panel, and weekly information on the concentrations of the milk metabolites glycerophosphocholine and phosphocholine as well as milk composition data (milk yield, fat and protein percentage) was available. The concentration of β-hydroxybutyric acid in milk was used as target variable in all prediction models. Average correlations between observed and predicted target values up to 0.643 could be obtained, if milk metabolite and routine milk recording data were combined for prediction at the same day within weeks. Predictive performance of metabolic as well as milk performance-based models was higher than that of models based on genetic information. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  7. Quantitative predictions from competition theory with incomplete information on model parameters tested against experiments across diverse taxa

    OpenAIRE

    Fort, Hugo

    2017-01-01

    We derive an analytical approximation for making quantitative predictions for ecological communities as a function of the mean intensity of the inter-specific competition and the species richness. This method, with only a fraction of the model parameters (carrying capacities and competition coefficients), is able to predict accurately empirical measurements covering a wide variety of taxa (algae, plants, protozoa).

  8. Physical and Cognitive Functioning After 3 Years Can Be Predicted Using Information From the Diagnostic Process in Recently Diagnosed Multiple Sclerosis

    NARCIS (Netherlands)

    de Groot, V.; Beckerman, H.; Uitdehaag, B.M.J.; Hintzen, R.Q.; Minneboo, A.; Heymans, M.W.; Lankhorst, G.J.; Polman, C.H.; Bouter, L.M.

    2009-01-01

    de Groot V, Beckerman H, Uitdehaag BM, Hintzen RQ, Minneboo A, Heymans MW, Lankhorst GJ, Polman CH, Bouter LM, on behalf of the Functional Prognostication and Disability (FuPro) Study Group. Physical and cognitive functioning after 3 years can be predicted using information from the diagnostic

  9. Mortgage loans: an analysis of the portfolios of the largest banks in Brazil

    Directory of Open Access Journals (Sweden)

    Bruno Vinícius Ramos Fernandes

    2013-05-01

    Full Text Available Given the current macroeconomic environment experienced in Brazil, where inflation has stabilized and the basic interest rate of the economy is in one of their historical lows, demand for mortgages is increasing. In this context, the mortgage is presented with great emphasis to meet the demand for purchasing housing in addition to being a catalyst for the reduction of the high housing deficit. From a descriptive and empirical-analytic was analyzed the mortgage loan portfolio of the largest banks of the country between the years 2001 and 2010 through Quarterly Financial Information (IFT available on the Central Bank website. It was settled a comparative relationship between the data in order to check the development of mortgage portfolios over the years and the factors that influenced this evolution, and evaluate the timeliness and quality of those loans. For the evolution of the portfolio there was an economic context in which Brazil was included in the period, and observed that for most of these operations are long term the banks are more exposed to market risk. With regard to credit risk parse that, over the years, Brazilian banks are presenting a mortgage loan portfolio with lower risk, and it is found that institutions with real estate credits with higher levels of portfolio risk are subject to have higher losses on such operations in the possibility of default.

  10. Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

    Directory of Open Access Journals (Sweden)

    Guisan Antoine

    2009-04-01

    Full Text Available Abstract Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a real absences b pseudo-absences selected randomly from the background and c two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97, and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have

  11. Predicting the future trend of popularity by network diffusion

    Science.gov (United States)

    Zeng, An; Yeung, Chi Ho

    2016-06-01

    Conventional approaches to predict the future popularity of products are mainly based on extrapolation of their current popularity, which overlooks the hidden microscopic information under the macroscopic trend. Here, we study diffusion processes on consumer-product and citation networks to exploit the hidden microscopic information and connect consumers to their potential purchase, publications to their potential citers to obtain a prediction for future item popularity. By using the data obtained from the largest online retailers including Netflix and Amazon as well as the American Physical Society citation networks, we found that our method outperforms the accurate short-term extrapolation and identifies the potentially popular items long before they become prominent.

  12. Predicting the future trend of popularity by network diffusion.

    Science.gov (United States)

    Zeng, An; Yeung, Chi Ho

    2016-06-01

    Conventional approaches to predict the future popularity of products are mainly based on extrapolation of their current popularity, which overlooks the hidden microscopic information under the macroscopic trend. Here, we study diffusion processes on consumer-product and citation networks to exploit the hidden microscopic information and connect consumers to their potential purchase, publications to their potential citers to obtain a prediction for future item popularity. By using the data obtained from the largest online retailers including Netflix and Amazon as well as the American Physical Society citation networks, we found that our method outperforms the accurate short-term extrapolation and identifies the potentially popular items long before they become prominent.

  13. A marine heatwave drives massive losses from the world’s largest seagrass carbon stocks

    KAUST Repository

    Arias-Ortiz, Ariane; Serrano, Oscar; Masqué , Pere; Lavery, P. S.; Mueller, U.; Kendrick, G. A.; Rozaimi, M.; Esteban, A.; Fourqurean, J. W.; Marbà , N.; Mateo, M. A.; Murray, K.; Rule, M. J.; Duarte, Carlos M.

    2018-01-01

    Seagrass ecosystems contain globally significant organic carbon (C) stocks. However, climate change and increasing frequency of extreme events threaten their preservation. Shark Bay, Western Australia, has the largest C stock reported for a seagrass

  14. New Chicago-Indiana computer network will handle dataflow from world's largest scientific experiment

    CERN Multimedia

    2006-01-01

    "Massive quantities of data will soon begin flowing from the largest scientific instrument ever built into an international netword of computer centers, including one operated jointly by the University of Chicago and Indiana University." (1,5 page)

  15. Lagisza, world's largest CFB boiler, begins commercial operation

    Energy Technology Data Exchange (ETDEWEB)

    Nuortimo, K. [Foster Wheeler, Varkaus (Finland)

    2010-04-15

    Early operating experience with the Lagisza circulating fluidised bed (CFB) boiler in Poland - the world's largest such boiler to date, and also the first one with supercritical steam conditions - has been positive. 3 figs., 4 tabs.

  16. Analytic approximation to the largest eigenvalue distribution of a white Wishart matrix

    CSIR Research Space (South Africa)

    Vlok, JD

    2012-08-14

    Full Text Available offers largely simplified computation and provides statistics such as the mean value and region of support of the largest eigenvalue distribution. Numeric results from the literature are compared with the approximation and Monte Carlo simulation results...

  17. The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes.

    Science.gov (United States)

    Clark, Samuel A; Hickey, John M; Daetwyler, Hans D; van der Werf, Julius H J

    2012-02-09

    The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values. Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated. The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy. An animal's relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.

  18. An implementation of an aeroacoustic prediction model for broadband noise from a vertical axis wind turbine using a CFD informed methodology

    Science.gov (United States)

    Botha, J. D. M.; Shahroki, A.; Rice, H.

    2017-12-01

    This paper presents an enhanced method for predicting aerodynamically generated broadband noise produced by a Vertical Axis Wind Turbine (VAWT). The method improves on existing work for VAWT noise prediction and incorporates recently developed airfoil noise prediction models. Inflow-turbulence and airfoil self-noise mechanisms are both considered. Airfoil noise predictions are dependent on aerodynamic input data and time dependent Computational Fluid Dynamics (CFD) calculations are carried out to solve for the aerodynamic solution. Analytical flow methods are also benchmarked against the CFD informed noise prediction results to quantify errors in the former approach. Comparisons to experimental noise measurements for an existing turbine are encouraging. A parameter study is performed and shows the sensitivity of overall noise levels to changes in inflow velocity and inflow turbulence. Noise sources are characterised and the location and mechanism of the primary sources is determined, inflow-turbulence noise is seen to be the dominant source. The use of CFD calculations is seen to improve the accuracy of noise predictions when compared to the analytic flow solution as well as showing that, for inflow-turbulence noise sources, blade generated turbulence dominates the atmospheric inflow turbulence.

  19. Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

    Science.gov (United States)

    Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

    2016-01-01

    3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

  20. When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation.

    Directory of Open Access Journals (Sweden)

    Young Bin Kim

    Full Text Available Bitcoin is an online currency that is used worldwide to make online payments. It has consequently become an investment vehicle in itself and is traded in a way similar to other open currencies. The ability to predict the price fluctuation of Bitcoin would therefore facilitate future investment and payment decisions. In order to predict the price fluctuation of Bitcoin, we analyse the comments posted in the Bitcoin online forum. Unlike most research on Bitcoin-related online forums, which is limited to simple sentiment analysis and does not pay sufficient attention to note-worthy user comments, our approach involved extracting keywords from Bitcoin-related user comments posted on the online forum with the aim of analytically predicting the price and extent of transaction fluctuation of the currency. The effectiveness of the proposed method is validated based on Bitcoin online forum data ranging over a period of 2.8 years from December 2013 to September 2016.

  1. When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation.

    Science.gov (United States)

    Kim, Young Bin; Lee, Jurim; Park, Nuri; Choo, Jaegul; Kim, Jong-Hyun; Kim, Chang Hun

    2017-01-01

    Bitcoin is an online currency that is used worldwide to make online payments. It has consequently become an investment vehicle in itself and is traded in a way similar to other open currencies. The ability to predict the price fluctuation of Bitcoin would therefore facilitate future investment and payment decisions. In order to predict the price fluctuation of Bitcoin, we analyse the comments posted in the Bitcoin online forum. Unlike most research on Bitcoin-related online forums, which is limited to simple sentiment analysis and does not pay sufficient attention to note-worthy user comments, our approach involved extracting keywords from Bitcoin-related user comments posted on the online forum with the aim of analytically predicting the price and extent of transaction fluctuation of the currency. The effectiveness of the proposed method is validated based on Bitcoin online forum data ranging over a period of 2.8 years from December 2013 to September 2016.

  2. Solar energy potential of the largest buildings in the United States

    Science.gov (United States)

    Wence, E. R.; Grodsky, S.; Hernandez, R. R.

    2017-12-01

    Sustainable pathways of land use for energy are necessary to mitigate climate change and limit conversion of finite land resources needed for conservation and food production. Large, commercial buildings (LCBs) are increasing in size and number throughout the United States (US) and may serve as suitable recipient environments for photovoltaic (PV) solar energy infrastructure that may support a low carbon, low land footprint energy transition. In this study, we identified, characterized, and evaluated the technical potential of the largest, commercial building rooftops (i.e., exceeding 110,000 m2) and their associated parking lots in the US for PV solar energy systems using Aurora, a cloud-based solar optimization platform. We also performed a case study of building-specific electricity generation: electricity consumption balance. Further, we quantified the environmental co-benefit of land sparing and associated avoided emissions (t-CO2-eq) conferred under the counterfactual scenario that solar development would otherwise proceed as a ground-mounted, utility-scale PV installation of equal nominal capacity. We identified and mapped 37 LCBs (by rooftop area) across 18 states in the US, spanning from as far north as the state of Minnesota to as far south as Florida. Rooftop footprints range from 427,297 to 113,689 m2 and have a cumulative surface area of 99.8 million ft2. We characterize the LCBs as either: distribution/warehouse, factory, shopping center, or administrative office/facility. Three of the 37 LCBs currently support rooftop PV and the numbers of associated, detached buildings number up to 38. This study elucidates the extent to which LCBs and their respective parking lots can serve as suitable sites for PV solar energy generation. Lastly, this study demonstrates research-based applications of the Aurora energy modeling platform and informs decision-making focused on redirecting energy development towards human-modified landscapes to prioritize land use for

  3. A study of the predictive model on the user reaction time using the information amount and its similarity

    International Nuclear Information System (INIS)

    Lee, Sung Jin; Heo, Gyun Young; Chang, Soon Heung

    2004-01-01

    There are lots of studies on the user interface evaluation since it started. Recent studies focus on the contextual information of the user interface. We knew that the user reaction time increases as the amount of information increases. But, the relation between the contextual information and the user reaction time may be unknown. In this study, we proposed the similarity as one of the contextual information. We can expect that the similarity decreases the user reaction time. The goal of this study is to find some correlation about the user reaction time with both the information amount and the similarity. The experiment was performed with 20 participants. The results of experiment demonstrated our proposals

  4. The Relevance Voxel Machine (RVoxM): A Self-Tuning Bayesian Model for Informative Image-Based Prediction

    DEFF Research Database (Denmark)

    Sabuncu, Mert R.; Van Leemput, Koen

    2012-01-01

    This paper presents the relevance voxel machine (RVoxM), a dedicated Bayesian model for making predictions based on medical imaging data. In contrast to the generic machine learning algorithms that have often been used for this purpose, the method is designed to utilize a small number of spatially...

  5. Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information.

    Directory of Open Access Journals (Sweden)

    Antonio Montresor

    2016-04-01

    Full Text Available Estimating the reduction in levels of infection during implementation of soil-transmitted helminth (STH control programmes is important to measure their performance and to plan interventions. Markov modelling techniques have been used with some success to predict changes in STH prevalence following treatment in Viet Nam. The model is stationary and to date, the prediction has been obtained by calculating the transition probabilities between the different classes of intensity following the first year of drug distribution and assuming that these remain constant in subsequent years. However, to run this model longitudinal parasitological data (including intensity of infection are required for two consecutive years from at least 200 individuals. Since this amount of data is not often available from STH control programmes, the possible application of the model in control programme is limited. The present study aimed to address this issue by adapting the existing Markov model to allow its application when a more limited amount of data is available and to test the predictive capacities of these simplified models.We analysed data from field studies conducted with different combination of three parameters: (i the frequency of drug administration; (ii the drug distributed; and (iii the target treatment population (entire population or school-aged children only. This analysis allowed us to define 10 sets of standard transition probabilities to be used to predict prevalence changes when only baseline data are available (simplified model 1. We also formulated three equations (one for each STH parasite to calculate the predicted prevalence of the different classes of intensity from the total prevalence. These equations allowed us to design a simplified model (SM2 to obtain predictions when the classes of intensity at baseline were not known. To evaluate the performance of the simplified models, we collected data from the scientific literature on changes in

  6. PREDICTIVE VALUE OF THE DEFERRED TAXES GENERATED BY THE SUBVENTIONS FOR INVESTMENTS – ESSENTIAL ELEMENT FOR PRESENTING THE INFORMATION IN THE FINANCIAL STATEMENTS

    Directory of Open Access Journals (Sweden)

    PALIU – POPA LUCIA

    2015-12-01

    Full Text Available Most information underlying the decision to invest at the level of a company, are provided by the accountancy, this becoming today a common language with respect to the businesses on the international markets, and the accountancy normalization was extrapolated from the national level to the international level, due to the needs concerning the comparability and the transparency of the entities financial statements, without considering the geopolitical area where they were built. These issues justify the approaches for improving both accounting treatments and the procedures for elaborating and presenting data within the financial statements such that the users to benefit from credible and transparent information. One of the major issues arising with respect to the performance of an entity aims to prepare a unique situation on the company performance, namely:“the statement of the comprehensive income”, having as primordial objective the facility of forecasting the performance, within which the deferred taxes generated by the subventions for investments are an essential element with an important predictive value. In this context, starting from the main differences between the provisions of the national, Anglo-Saxon accounting regulations and those of the international reference system with respect to the predictive value of the deferred taxes and continuing with the occurrence and evolution of the deferred taxes generated by the subventions for investments, the study proposes to highlight the predictive value of the deferred taxes generated by the subventions for investments, provided o the users by the information of annual financial statements.

  7. Astronomer's new guide to the galaxy: largest map of cold dust revealed

    Science.gov (United States)

    2009-07-01

    visible from the APEX site on Chajnantor, as well as combining it with infrared observations to be made by the ESA Herschel Space Observatory. We look forward to new discoveries made with these maps, which will also serve as a guide for future observations with ALMA", said Leonardo Testi from ESO, who is a member of the ATLASGAL team and the European Project Scientist for the ALMA project. Note [1] The map was constructed from individual APEX observations in radiation at 870 µm (0.87 mm) wavelength. More information: The ATLASGAL observations are presented in a paper by Frederic Schuller et al., ATLASGAL -- The APEX Telescope Large Area Survey of the Galaxy at 870 µm, published in Astronomy & Astrophysics. ATLASGAL is a collaboration between the Max Planck Institute for Radio Astronomy, the Max Planck Institute for Astronomy, ESO, and the University of Chile. LABOCA (Large APEX Bolometer Camera), one of APEX's major instruments, is the world's largest bolometer camera (a "thermometer camera", or thermal camera that measures and maps the tiny changes in temperature that occur when sub-millimetre wavelength light falls on its absorbing surface; see ESO 35/07). LABOCA's large field of view and high sensitivity make it an invaluable tool for imaging the "cold Universe". LABOCA was built by the Max Planck Institute for Radio Astronomy. The Atacama Pathfinder Experiment (APEX) telescope is a 12-metre telescope, located at 5100 m altitude on the arid plateau of Chajnantor in the Chilean Andes. APEX operates at millimetre and submillimetre wavelengths. This wavelength range is a relatively unexplored frontier in astronomy, requiring advanced detectors and an extremely high and dry observatory site, such as Chajnantor. APEX, the largest submillimetre-wave telescope operating in the southern hemisphere, is a collaboration between the Max Planck Institute for Radio Astronomy, the Onsala Space Observatory and ESO. Operation of APEX at Chajnantor is entrusted to ESO. APEX is a

  8. Distribution of the largest aftershocks in branching models of triggered seismicity: Theory of the universal Baath law

    International Nuclear Information System (INIS)

    Saichev, A.; Sornette, D.

    2005-01-01

    Using the epidemic-type aftershock sequence (ETAS) branching model of triggered seismicity, we apply the formalism of generating probability functions to calculate exactly the average difference between the magnitude of a mainshock and the magnitude of its largest aftershock over all generations. This average magnitude difference is found empirically to be independent of the mainshock magnitude and equal to 1.2, a universal behavior known as Baath's law. Our theory shows that Baath's law holds only sufficiently close to the critical regime of the ETAS branching process. Allowing for error bars ±0.1 for Baath's constant value around 1.2, our exact analytical treatment of Baath's law provides new constraints on the productivity exponent α and the branching ratio n: 0.9 < or approx. α≤1 and 0.8 < or approx. n≤1. We propose a method for measuring α based on the predicted renormalization of the Gutenberg-Richter distribution of the magnitudes of the largest aftershock. We also introduce the 'second Baath law for foreshocks': the probability that a main earthquake turns out to be the foreshock does not depend on its magnitude ρ

  9. The Multivariate Largest Lyapunov Exponent as an Age-Related Metric of Quiet Standing Balance

    Directory of Open Access Journals (Sweden)

    Kun Liu

    2015-01-01

    Full Text Available The largest Lyapunov exponent has been researched as a metric of the balance ability during human quiet standing. However, the sensitivity and accuracy of this measurement method are not good enough for clinical use. The present research proposes a metric of the human body’s standing balance ability based on the multivariate largest Lyapunov exponent which can quantify the human standing balance. The dynamic multivariate time series of ankle, knee, and hip were measured by multiple electrical goniometers. Thirty-six normal people of different ages participated in the test. With acquired data, the multivariate largest Lyapunov exponent was calculated. Finally, the results of the proposed approach were analysed and compared with the traditional method, for which the largest Lyapunov exponent and power spectral density from the centre of pressure were also calculated. The following conclusions can be obtained. The multivariate largest Lyapunov exponent has a higher degree of differentiation in differentiating balance in eyes-closed conditions. The MLLE value reflects the overall coordination between multisegment movements. Individuals of different ages can be distinguished by their MLLE values. The standing stability of human is reduced with the increment of age.

  10. Identifying the node spreading influence with largest k-core values

    International Nuclear Information System (INIS)

    Lin, Jian-Hong; Guo, Qiang; Dong, Wen-Zhao; Tang, Li-Ying; Liu, Jian-Guo

    2014-01-01

    Identifying the nodes with largest spreading influence of complex networks is one of the most promising domains. By taking into account the neighbors' k-core values, we present an improved neighbors' k-core (INK) method which is the sum of the neighbors' k-core values with a tunable parameter α to evaluate the node spreading influence with largest k-core values. Comparing with the Susceptible–Infected–Recovered (SIR) results for four real networks, the INK method could identify the node spreading influence with largest k-core values more accurately than the ones generated by the degree k, closeness C, betweenness B and coreness centrality method. - Highlights: • We present an improved neighbors' k-core (INK) method to evaluate the node spreading influence with largest k-core values. • The INK method could identify the node spreading influence with largest k-core values more accurately. • Kendall's tau τ of INK method with α=1 are highly identical to rank the node influence

  11. Oak habitat recovery on California's largest islands: Scenarios for the role of corvid seed dispersal

    Science.gov (United States)

    Pesendorfer, Mario B.; Baker, Christopher M.; Stringer, Martin; McDonald-Madden, Eve; Bode, Michael; McEachern, A. Kathryn; Morrison, Scott A.; Sillett, T. Scott

    2018-01-01

    Seed dispersal by birds is central to the passive restoration of many tree communities. Reintroduction of extinct seed dispersers can therefore restore degraded forests and woodlands. To test this, we constructed a spatially explicit simulation model, parameterized with field data, to consider the effect of different seed dispersal scenarios on the extent of oak populations. We applied the model to two islands in California's Channel Islands National Park (USA), one of which has lost a key seed disperser.We used an ensemble modelling approach to simulate island scrub oak (Quercus pacifica) demography. The model was developed and trained to recreate known population changes over a 20-year period on 250-km2 Santa Cruz Island, and incorporated acorn dispersal by island scrub-jays (Aphelocoma insularis), deer mice (Peromyscus maniculatus) and gravity, as well as seed predation. We applied the trained model to 215-km2 Santa Rosa Island to examine how reintroducing island scrub-jays would affect the rate and pattern of oak population expansion. Oak habitat on Santa Rosa Island has been greatly reduced from its historical extent due to past grazing by introduced ungulates, the last of which were removed by 2011.Our simulation model predicts that a seed dispersal scenario including island scrub-jays would increase the extent of the island scrub oak population on Santa Rosa Island by 281% over 100 years, and by 544% over 200 years. Scenarios without jays would result in little expansion. Simulated long-distance seed dispersal by jays also facilitates establishment of discontinuous patches of oaks, and increases their elevational distribution.Synthesis and applications. Scenario planning provides powerful decision support for conservation managers. We used ensemble modelling of plant demographic and seed dispersal processes to investigate whether the reintroduction of seed dispersers could provide cost-effective means of achieving broader ecosystem restoration goals on

  12. Predicting long-term performance of engineered geologic carbon dioxide storage systems to inform decisions amidst uncertainty

    Science.gov (United States)

    Pawar, R.

    2016-12-01

    Risk assessment and risk management of engineered geologic CO2 storage systems is an area of active investigation. The potential geologic CO2 storage systems currently under consideration are inherently heterogeneous and have limited to no characterization data. Effective risk management decisions to ensure safe, long-term CO2 storage requires assessing and quantifying risks while taking into account the uncertainties in a storage site's characteristics. The key decisions are typically related to definition of area of review, effective monitoring strategy and monitoring duration, potential of leakage and associated impacts, etc. A quantitative methodology for predicting a sequestration site's long-term performance is critical for making key decisions necessary for successful deployment of commercial scale geologic storage projects where projects will require quantitative assessments of potential long-term liabilities. An integrated assessment modeling (IAM) paradigm which treats a geologic CO2 storage site as a system made up of various linked subsystems can be used to predict long-term performance. The subsystems include storage reservoir, seals, potential leakage pathways (such as wellbores, natural fractures/faults) and receptors (such as shallow groundwater aquifers). CO2 movement within each of the subsystems and resulting interactions are captured through reduced order models (ROMs). The ROMs capture the complex physical/chemical interactions resulting due to CO2 movement and interactions but are computationally extremely efficient. The computational efficiency allows for performing Monte Carlo simulations necessary for quantitative probabilistic risk assessment. We have used the IAM to predict long-term performance of geologic CO2 sequestration systems and to answer questions related to probability of leakage of CO2 through wellbores, impact of CO2/brine leakage into shallow aquifer, etc. Answers to such questions are critical in making key risk management

  13. A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

    Science.gov (United States)

    Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

    2018-06-01

    The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  14. Behavioral change theories can inform the prediction of young adults' adoption of a plant-based diet.

    Science.gov (United States)

    Wyker, Brett A; Davison, Kirsten K

    2010-01-01

    Drawing on the Theory of Planned Behavior (TPB) and the Transtheoretical Model (TTM), this study (1) examines links between stages of change for following a plant-based diet (PBD) and consuming more fruits and vegetables (FV); (2) tests an integrated theoretical model predicting intention to follow a PBD; and (3) identifies associated salient beliefs. Cross-sectional. Large public university in the northeastern United States. 204 college students. TPB and TTM constructs were assessed using validated scales. Outcome, normative, and control beliefs were measured using open-ended questions. The overlap between stages of change for FV consumption and adopting a PBD was assessed using Spearman rank correlation analysis and cross-tab comparisons. The proposed model predicting adoption of a PBD was tested using structural equation modeling (SEM). Salient beliefs were coded using automatic response coding software. No association was found between stages of change for FV consumption and following a PBD. Results from SEM analyses provided support for the proposed model predicting intention to follow a PBD. Gender differences in salient beliefs for following a PBD were found. Results demonstrate the potential for effective theory-driven and stage-tailored public health interventions to promote PBDs. Copyright 2010 Society for Nutrition Education. Published by Elsevier Inc. All rights reserved.

  15. A Mechanistically Informed User-Friendly Model to Predict Greenhouse Gas (GHG) Fluxes and Carbon Storage from Coastal Wetlands

    Science.gov (United States)

    Abdul-Aziz, O. I.; Ishtiaq, K. S.

    2015-12-01

    We present a user-friendly modeling tool on MS Excel to predict the greenhouse gas (GHG) fluxes and estimate potential carbon sequestration from the coastal wetlands. The dominant controls of wetland GHG fluxes and their relative mechanistic linkages with various hydro-climatic, sea level, biogeochemical and ecological drivers were first determined by employing a systematic data-analytics method, including Pearson correlation matrix, principal component and factor analyses, and exploratory partial least squares regressions. The mechanistic knowledge and understanding was then utilized to develop parsimonious non-linear (power-law) models to predict wetland carbon dioxide (CO2) and methane (CH4) fluxes based on a sub-set of climatic, hydrologic and environmental drivers such as the photosynthetically active radiation, soil temperature, water depth, and soil salinity. The models were tested with field data for multiple sites and seasons (2012-13) collected from the Waquoit Bay, MA. The model estimated the annual wetland carbon storage by up-scaling the instantaneous predicted fluxes to an extended growing season (e.g., May-October) and by accounting for the net annual lateral carbon fluxes between the wetlands and estuary. The Excel Spreadsheet model is a simple ecological engineering tool for coastal carbon management and their incorporation into a potential carbon market under a changing climate, sea level and environment. Specifically, the model can help to determine appropriate GHG offset protocols and monitoring plans for projects that focus on tidal wetland restoration and maintenance.

  16. Perceived Threat and Corroboration: Key Factors That Improve a Predictive Model of Trust in Internet-based Health Information and Advice

    Science.gov (United States)

    Harris, Peter R; Briggs, Pam

    2011-01-01

    Background How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. Objective The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Methods Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. Results We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ2 5 = 10

  17. Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study.

    Science.gov (United States)

    Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng

    2015-09-22

    The increasing rate of health care expenditures in the United States has placed a significant burden on the nation's economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. In the HealthInfoNet, Maine's health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient's next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree-based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes.

  18. Discovery of the Largest Orbweaving Spider Species: The Evolution of Gigantism in Nephila

    OpenAIRE

    Kuntner, Matja?; Coddington, Jonathan A.

    2009-01-01

    Background More than 41,000 spider species are known with about 400?500 added each year, but for some well-known groups, such as the giant golden orbweavers, Nephila, the last valid described species dates from the 19th century. Nephila are renowned for being the largest web-spinning spiders, making the largest orb webs, and are model organisms for the study of extreme sexual size dimorphism (SSD) and sexual biology. Here, we report on the discovery of a new, giant Nephila species from Africa...

  19. Predicting masking release of lateralized speech

    DEFF Research Database (Denmark)

    Chabot-Leclerc, Alexandre; MacDonald, Ewen; Dau, Torsten

    2016-01-01

    . The largest masking release (MR) was observed when all maskers were on the opposite side of the target. The data in the conditions containing only energetic masking and modulation masking could be accounted for using a binaural extension of the speech-based envelope power spectrum model [sEPSM; Jørgensen et...... al., 2013, J. Acoust. Soc. Am. 130], which uses a short-term equalization-cancellation process to model binaural unmasking. In the conditions where informational masking (IM) was involved, the predicted SRTs were lower than the measured values because the model is blind to confusions experienced...

  20. Accuration of Time Series and Spatial Interpolation Method for Prediction of Precipitation Distribution on the Geographical Information System

    Science.gov (United States)

    Prasetyo, S. Y. J.; Hartomo, K. D.

    2018-01-01

    The Spatial Plan of the Province of Central Java 2009-2029 identifies that most regencies or cities in Central Java Province are very vulnerable to landslide disaster. The data are also supported by other data from Indonesian Disaster Risk Index (In Indonesia called Indeks Risiko Bencana Indonesia) 2013 that suggest that some areas in Central Java Province exhibit a high risk of natural disasters. This research aims to develop an application architecture and analysis methodology in GIS to predict and to map rainfall distribution. We propose our GIS architectural application of “Multiplatform Architectural Spatiotemporal” and data analysis methods of “Triple Exponential Smoothing” and “Spatial Interpolation” as our significant scientific contribution. This research consists of 2 (two) parts, namely attribute data prediction using TES method and spatial data prediction using Inverse Distance Weight (IDW) method. We conduct our research in 19 subdistricts in the Boyolali Regency, Central Java Province, Indonesia. Our main research data is the biweekly rainfall data in 2000-2016 Climatology, Meteorology, and Geophysics Agency (In Indonesia called Badan Meteorologi, Klimatologi, dan Geofisika) of Central Java Province and Laboratory of Plant Disease Observations Region V Surakarta, Central Java. The application architecture and analytical methodology of “Multiplatform Architectural Spatiotemporal” and spatial data analysis methodology of “Triple Exponential Smoothing” and “Spatial Interpolation” can be developed as a GIS application framework of rainfall distribution for various applied fields. The comparison between the TES and IDW methods show that relative to time series prediction, spatial interpolation exhibit values that are approaching actual. Spatial interpolation is closer to actual data because computed values are the rainfall data of the nearest location or the neighbour of sample values. However, the IDW’s main weakness is that some

  1. The Role of Emotion Regulation in the Predictive Association between Social Information Processing and Aggressive Behavior in Adolescents

    Science.gov (United States)

    Calvete, Esther; Orue, Izaskun

    2012-01-01

    The primary aim of this study was to assess the moderating role of emotion regulation in the relationship between some components of social information processing (hostile interpretation and anger) and aggressive behavior. The secondary aim was to assess whether emotion regulation, hostile interpretation, and anger account for gender differences…

  2. Prediction of Intelligibility of Noisy and Time-Frequency Weighted Speech based on Mutual Information Between Amplitude Envelopes

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, C.H.

    2013-01-01

    of Shannon information the critical-band amplitude envelopes of the noisy/processed signal convey about the corresponding clean signal envelopes. The resulting intelligibility predictor turns out to be a simple function of the correlation between noisy/processed and clean amplitude envelopes. The proposed...

  3. A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

    Science.gov (United States)

    Zhang, Xiaotian; Yin, Jian; Zhang, Xu

    2018-03-02

    Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

  4. Informed decision making about predictive DNA tests: arguments for more public visibility of personal deliberations about the good life.

    Science.gov (United States)

    Boenink, Marianne; van der Burg, Simone

    2010-05-01

    Since its advent, predictive DNA testing has been perceived as a technology that may have considerable impact on the quality of people's life. The decision whether or not to use this technology is up to the individual client. However, to enable well considered decision making both the negative as well as the positive freedom of the individual should be supported. In this paper, we argue that current professional and public discourse on predictive DNA-testing is lacking when it comes to supporting positive freedom, because it is usually framed in terms of risk and risk management. We show how this 'risk discourse' steers thinking on the good life in a particular way. We go on to argue that empirical research into the actual deliberation and decision making processes of individuals and families may be used to enrich the environment of personal deliberation in three ways: (1) it points at a richer set of values that deliberators can take into account, (2) it acknowledges the shared nature of genes, and (3) it shows how one might frame decisions in a non-binary way. We argue that the public sharing and discussing of stories about personal deliberations offers valuable input for others who face similar choices: it fosters their positive freedom to shape their view of the good life in relation to DNA-diagnostics. We conclude by offering some suggestions as to how to realize such public sharing of personal stories.

  5. Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

    Science.gov (United States)

    2012-01-01

    Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence

  6. Africa's largest long-lasting insecticide-treated net producer: lessons from A to Z Textiles.

    Science.gov (United States)

    Masum, Hassan; Shah, Ronak; Schroeder, Karl; Daar, Abdallah S; Singer, Peter A

    2010-12-13

    Field trials have demonstrated the efficacy of insecticide-treated nets, and the WHO has recently endorsed a shift toward Long-Lasting Insecticide Treated nets (LLINs) due to factors such as reduced distribution costs. However, the need for LLINs poses several challenges. Is it possible to manufacture LLINs in large quantities in the African continent, where malaria is most endemic? When production is located in low-income countries, what role is played by local funding and employment, scaling up manufacturing, and partnerships? What factors influence availability and pricing? A case study of A to Z Textiles was undertaken to answer the question of how large-scale production of LLINs can occur in a low income setting. One of the largest sources of bed nets for Africa, A to Z Textiles is Africa-based, and its Tanzanian operations have a production capacity of 30 million LLINs per year, along with full WHO recommendation for its nets. Our analysis is based on semi-structured interviews with key informants familiar with A to Z, site visits in Tanzania, and literature reviews.This paper discusses the history and current status of A to Z Textiles, identifies the factors that led to its success, and suggests policy considerations that could support similar initiatives in the future. Local funding, scaling up manufacturing, technology transfer, and partnerships all played important roles in A to Z's ascent, as did perceived benefits of local employment and capacity-building. Regulatory issues and procurement rules acted as barriers. A to Z cost-effectively manufactures high-quality LLINs where malaria is most endemic. With a production capacity of 30 million LLINs per year, and full WHOPES (WHO Pesticide Evaluation Scheme) certification, A to Z Textiles demonstrates how key health goods can be successfully produced in the low-income countries that use them. Its example may be instructive and of high interest to readers in the malaria community, especially in developing

  7. Africa's largest long-lasting insecticide-treated net producer: lessons from A to Z Textiles

    Directory of Open Access Journals (Sweden)

    Daar Abdallah S

    2010-12-01

    Full Text Available Abstract Background Field trials have demonstrated the efficacy of insecticide-treated nets, and the WHO has recently endorsed a shift toward Long-Lasting Insecticide Treated nets (LLINs due to factors such as reduced distribution costs. However, the need for LLINs poses several challenges. Is it possible to manufacture LLINs in large quantities in the African continent, where malaria is most endemic? When production is located in low-income countries, what role is played by local funding and employment, scaling up manufacturing, and partnerships? What factors influence availability and pricing? Discussion A case study of A to Z Textiles was undertaken to answer the question of how large-scale production of LLINs can occur in a low income setting. One of the largest sources of bed nets for Africa, A to Z Textiles is Africa-based, and its Tanzanian operations have a production capacity of 30 million LLINs per year, along with full WHO recommendation for its nets. Our analysis is based on semi-structured interviews with key informants familiar with A to Z, site visits in Tanzania, and literature reviews. This paper discusses the history and current status of A to Z Textiles, identifies the factors that led to its success, and suggests policy considerations that could support similar initiatives in the future. Local funding, scaling up manufacturing, technology transfer, and partnerships all played important roles in A to Z’s ascent, as did perceived benefits of local employment and capacity-building. Regulatory issues and procurement rules acted as barriers. A to Z cost-effectively manufactures high-quality LLINs where malaria is most endemic. Summary With a production capacity of 30 million LLINs per year, and full WHOPES (WHO Pesticide Evaluation Scheme certification, A to Z Textiles demonstrates how key health goods can be successfully produced in the low-income countries that use them. Its example may be instructive and of high interest to

  8. CERN: Digital image analysis in the world's largest research center for particle physics

    CERN Multimedia

    2005-01-01

    Those interested in researching into the smallest building blocks that matter is made up of need the largest instruments. CERN, near Geneva, Switzerland is where the most powerful circular accelerator in the world is being built: the Large Hadron Collider (LHC) for proton collisions. It has a circumference of 26.7 km (4 pages)

  9. Mass balance of Greenland's three largest outlet glaciers - 2000–2010

    NARCIS (Netherlands)

    Howat, I.M.; Ahn, Y.; Joughin, I.; van den Broeke, M.R.; Lenaerts, J.T.M.; Smith, B.

    2011-01-01

    Acceleration of Greenland's three largest outlet glaciers, Helheim, Kangerdlugssuaq and Jakobshavn Isbræ, accounted for a substantial portion of the ice sheet's mass loss over the past decade. Rapid changes in their discharge, however, make their cumulative mass-change uncertain. We derive monthly

  10. Key U.S.-built part fails during testing for world's largest particle collider

    CERN Multimedia

    2007-01-01

    "Scientists are scrambling to redesign a key U.S.-built part that broke "with a loud bang and a cloud of dust" during a high-pressure test for the world's largest particle physics collider that is supposed to start up in November, officials sais Tuesday." (1,5 page)

  11. CERN, World's largest particle physics lab, selects Progress SonicMQ

    CERN Document Server

    2007-01-01

    "Progress Software Corporation (NADAQ: PRGS), a global supplier of application insfrastructure software used to develop, deploy, integrate and manage business applications, today announced that CERN the world's largest physis laboratory and particle accelerator, has chosen Progress® SonicMQ® for mission-critical message delivery." (1 page)

  12. Phase space reconstruction and estimation of the largest Lyapunov exponent for gait kinematic data

    Energy Technology Data Exchange (ETDEWEB)

    Josiński, Henryk [Silesian University of Technology, Akademicka 16, 44-100 Gliwice (Poland); Świtoński, Adam [Polish-Japanese Institute of Information Technology, Aleja Legionów 2, 41-902 Bytom (Poland); Silesian University of Technology, Akademicka 16, 44-100 Gliwice (Poland); Michalczuk, Agnieszka; Wojciechowski, Konrad [Polish-Japanese Institute of Information Technology, Aleja Legionów 2, 41-902 Bytom (Poland)

    2015-03-10

    The authors describe an example of application of nonlinear time series analysis directed at identifying the presence of deterministic chaos in human motion data by means of the largest Lyapunov exponent. The method was previously verified on the basis of a time series constructed from the numerical solutions of both the Lorenz and the Rössler nonlinear dynamical systems.

  13. Discovery of the largest orbweaving spider species: the evolution of gigantism in Nephila.

    Science.gov (United States)

    Kuntner, Matjaz; Coddington, Jonathan A

    2009-10-21

    More than 41,000 spider species are known with about 400-500 added each year, but for some well-known groups, such as the giant golden orbweavers, Nephila, the last valid described species dates from the 19(th) century. Nephila are renowned for being the largest web-spinning spiders, making the largest orb webs, and are model organisms for the study of extreme sexual size dimorphism (SSD) and sexual biology. Here, we report on the discovery of a new, giant Nephila species from Africa and Madagascar, and review size evolution and SSD in Nephilidae. We formally describe N. komaci sp. nov., the largest web spinning species known, and place the species in phylogenetic context to reconstruct the evolution of mean size (via squared change parsimony). We then test female and male mean size correlation using phylogenetically independent contrasts, and simulate nephilid body size evolution using Monte Carlo statistics. Nephila females increased in size almost monotonically to establish a mostly African clade of true giants. In contrast, Nephila male size is effectively decoupled and hovers around values roughly one fifth of female size. Although N. komaci females are the largest Nephila yet discovered, the males are also large and thus their SSD is not exceptional.

  14. Discovery of the largest orbweaving spider species: the evolution of gigantism in Nephila.

    Directory of Open Access Journals (Sweden)

    Matjaz Kuntner

    2009-10-01

    Full Text Available More than 41,000 spider species are known with about 400-500 added each year, but for some well-known groups, such as the giant golden orbweavers, Nephila, the last valid described species dates from the 19(th century. Nephila are renowned for being the largest web-spinning spiders, making the largest orb webs, and are model organisms for the study of extreme sexual size dimorphism (SSD and sexual biology. Here, we report on the discovery of a new, giant Nephila species from Africa and Madagascar, and review size evolution and SSD in Nephilidae.We formally describe N. komaci sp. nov., the largest web spinning species known, and place the species in phylogenetic context to reconstruct the evolution of mean size (via squared change parsimony. We then test female and male mean size correlation using phylogenetically independent contrasts, and simulate nephilid body size evolution using Monte Carlo statistics.Nephila females increased in size almost monotonically to establish a mostly African clade of true giants. In contrast, Nephila male size is effectively decoupled and hovers around values roughly one fifth of female size. Although N. komaci females are the largest Nephila yet discovered, the males are also large and thus their SSD is not exceptional.

  15. World's third-largest producer of nuclear power. Japan in need of energy

    International Nuclear Information System (INIS)

    Anon.

    2008-01-01

    Japan is the third largest oil consumer in the world behind the United States and China, and the second largest net importer of oil. Japan boasts one of the largest economies in the world. The country continues to experience a moderate economic recovery that began in 2003, following a decade of economic stagnation. Japan's real gross domestic product (GDP) grew by 2.5% in 2005 and 2.3% in 2004. The modest upturn over the last few years reflects higher business confidence in Japan, a surge in export demand led by exports to China, and robust consumer spending. Unemployment in Japan fell to 4.4% in 2005, down from an early 2003 peak of 5.5%. Japan has virtually no domestic oil or natural gas reserves, and in 2005 was the second largest net importer of crude oil in the world. Despite the country's dearth of hydrocarbon resources, Japanese companies have actively pursued upstream oil and natural gas projects overseas. Japan remains one of the major exporters of energy-sector capital equipment, and Japanese companies provide engineering, construction, and project management services for energy projects. (orig.)

  16. Distribution of the Largest Eigenvalues of the Levi-Smirnov Ensemble

    International Nuclear Information System (INIS)

    Wieczorek, W.

    2004-01-01

    We calculate the distribution of the k-th largest eigenvalue in the random matrix Levi - Smirnov Ensemble (LSE), using the spectral dualism between LSE and chiral Gaussian Unitary Ensemble (GUE). Then we reconstruct universal spectral oscillations and we investigate an asymptotic behavior of the spectral distribution. (author)

  17. Unauthorized Disclosure: Can Behavioral Indicators Help Predict Who Will Commit Unauthorized Disclosure of Classified National Security Information?

    Science.gov (United States)

    2015-06-01

    Katherine Herbig, Espionage by the Numbers: A Statistical Overview, accessed April 14, 2015, http://www.wright.edu/rsp/Security/Treason/Numbers.htm 5...submitted for top-secret clearances with “derogatory financial information.”43 The debt amount reviewed was $500 in delinquency for at least 120 days, which...Investigative Service’s (DIS) “ delinquent debt criteria with amount of delinquent debt” and Defense Central Index of Investigation’s (DCII) final

  18. Predicting outcomes following cognitive behaviour therapy in child anxiety disorders: the influence of genetic, demographic and clinical information

    OpenAIRE

    Hudson, Jennifer L; Lester, Kathryn J; Lewis, Cathryn M; Tropeano, Maria; Creswell, Cathy; Collier, David A; Cooper, Peter; Lyneham, Heidi J; Morris, Talia; Rapee, Ronald M; Roberts, Susanna; Donald, Jennifer A; Eley, Thalia C

    2013-01-01

    Background. Within a therapeutic gene by environment (GxE) framework, we recently demonstrated that variation in \\ud the Serotonin Transporter Promoter Polymorphism; 5HTTLPR and marker rs6330 in Nerve Growth Factor gene; NGF is \\ud associated with poorer outcomes following cognitive behaviour therapy (CBT) for child anxiety disorders. The aim of this \\ud study was to explore one potential means of extending the translational reach of G×E data in a way that may be clinically \\ud informative. W...

  19. Prediction of Driver’s Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques

    Science.gov (United States)

    Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

    2017-01-01

    Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver’s intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver’s intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver’s intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver’s intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics. PMID:28604582

  20. Prediction of Driver’s Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Il-Hwan Kim

    2017-06-01

    Full Text Available Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver’s intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver’s intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN models, and the augmented information is fed to a support vector machine (SVM to detect the driver’s intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver’s intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics.

  1. Response Surface Approximation for Fatigue Life Prediction and Its Application to Multi-Criteria Optimization With a Priori Preference Information

    International Nuclear Information System (INIS)

    Baek, Seok Heum; Joo, Won Sik; Cho, Seok Swoo

    2009-01-01

    In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability

  2. Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

    Science.gov (United States)

    2011-01-01

    Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der

  3. Bayesian integration of sensor information and a multivariate dynamic linear model for prediction of dairy cow mastitis.

    Science.gov (United States)

    Jensen, Dan B; Hogeveen, Henk; De Vries, Albert

    2016-09-01

    Rapid detection of dairy cow mastitis is important so corrective action can be taken as soon as possible. Automatically collected sensor data used to monitor the performance and the health state of the cow could be useful for rapid detection of mastitis while reducing the labor needs for monitoring. The state of the art in combining sensor data to predict clinical mastitis still does not perform well enough to be applied in practice. Our objective was to combine a multivariate dynamic linear model (DLM) with a naïve Bayesian classifier (NBC) in a novel method using sensor and nonsensor data to detect clinical cases of mastitis. We also evaluated reductions in the number of sensors for detecting mastitis. With the DLM, we co-modeled 7 sources of sensor data (milk yield, fat, protein, lactose, conductivity, blood, body weight) collected at each milking for individual cows to produce one-step-ahead forecasts for each sensor. The observations were subsequently categorized according to the errors of the forecasted values and the estimated forecast variance. The categorized sensor data were combined with other data pertaining to the cow (week in milk, parity, mastitis history, somatic cell count category, and season) using Bayes' theorem, which produced a combined probability of the cow having clinical mastitis. If this probability was above a set threshold, the cow was classified as mastitis positive. To illustrate the performance of our method, we used sensor data from 1,003,207 milkings from the University of Florida Dairy Unit collected from 2008 to 2014. Of these, 2,907 milkings were associated with recorded cases of clinical mastitis. Using the DLM/NBC method, we reached an area under the receiver operating characteristic curve of 0.89, with a specificity of 0.81 when the sensitivity was set at 0.80. Specificities with omissions of sensor data ranged from 0.58 to 0.81. These results are comparable to other studies, but differences in data quality, definitions of

  4. Predicting Condom Use Using the Information-Motivation-Behavioral Skills (IMB) Model: A Multivariate Latent Growth Curve Analysis

    Science.gov (United States)

    Senn, Theresa E.; Scott-Sheldon, Lori A. J.; Vanable, Peter A.; Carey, Michael P.

    2011-01-01

    Background The Information-Motivation-Behavioral Skills (IMB) model often guides sexual risk reduction programs even though no studies have examined covariation in the theory’s constructs in a dynamic fashion with longitudinal data. Purpose Using new developments in latent growth modeling, we explore how changes in information, motivation, and behavioral skills over 9 months relate to changes in condom use among STD clinic patients. Methods Participants (N = 1281, 50% female, 66% African American) completed measures of IMB constructs at three time points. We used parallel process latent growth modeling to examine associations among intercepts and slopes of IMB constructs. Results Initial levels of motivation, behavioral skills, and condom use were all positively associated, with behavioral skills partially mediating associations between motivation and condom use. Changes over time in behavioral skills positively related to changes in condom use. Conclusions Results support the key role of behavioral skills in sexual risk reduction, suggesting these skills should be targeted in HIV prevention interventions. PMID:21638196

  5. Differential genome-wide gene expression profiling of bovine largest and second-largest follicles: identification of genes associated with growth of dominant follicles

    Directory of Open Access Journals (Sweden)

    Takahashi Toru

    2010-02-01

    Full Text Available Abstract Background Bovine follicular development is regulated by numerous molecular mechanisms and biological pathways. In this study, we tried to identify differentially expressed genes between largest (F1 and second-largest follicles (F2, and classify them by global gene expression profiling using a combination of microarray and quantitative real-time PCR (QPCR analysis. The follicular status of F1 and F2 were further evaluated in terms of healthy and atretic conditions by investigating mRNA localization of identified genes. Methods Global gene expression profiles of F1 (10.7 +/- 0.7 mm and F2 (7.8 +/- 0.2 mm were analyzed by hierarchical cluster analysis and expression profiles of 16 representative genes were confirmed by QPCR analysis. In addition, localization of six identified transcripts was investigated in healthy and atretic follicles using in situ hybridization. The healthy or atretic condition of examined follicles was classified by progesterone and estradiol concentrations in follicular fluid. Results Hierarchical cluster analysis of microarray data classified the follicles into two clusters. Cluster A was composed of only F2 and was characterized by high expression of 31 genes including IGFBP5, whereas cluster B contained only F1 and predominantly expressed 45 genes including CYP19 and FSHR. QPCR analysis confirmed AMH, CYP19, FSHR, GPX3, PlGF, PLA2G1B, SCD and TRB2 were greater in F1 than F2, while CCL2, GADD45A, IGFBP5, PLAUR, SELP, SPP1, TIMP1 and TSP2 were greater in F2 than in F1. In situ hybridization showed that AMH and CYP19 were detected in granulosa cells (GC of healthy as well as atretic follicles. PlGF was localized in GC and in the theca layer (TL of healthy follicles. IGFBP5 was detected in both GC and TL of atretic follicles. GADD45A and TSP2 were localized in both GC and TL of atretic follicles, whereas healthy follicles expressed them only in GC. Conclusion We demonstrated that global gene expression profiling of F

  6. Citizen Science for Urban Forest Management? Predicting the Data Density and Richness of Urban Forest Volunteered Geographic Information

    Directory of Open Access Journals (Sweden)

    Alec Foster

    2017-09-01

    Full Text Available Volunteered geographic information (VGI has been heralded as a promising new data source for urban planning and policymaking. However, there are also concerns surrounding uneven levels of participation and spatial coverage, despite the promotion of VGI as a means to increase access to geographic knowledge production. To begin addressing these concerns, this research examines the spatial distribution and data richness of urban forest VGI in Philadelphia, Pennsylvania and San Francisco, California. Using ordinary least squares (OLS, general linear models (GLM, and spatial autoregressive models, our findings reveal that sociodemographic and environmental indicators are strong predictors of both densities of attributed trees and data richness. Although recent digital urban tree inventory applications present significant opportunities for collaborative data gathering, innovative research, and improved policymaking, asymmetries in the quantity and quality of the data may undermine their effectiveness. If these incomplete and uneven datasets are used in policymaking, environmental justice issues may arise.

  7. Estimating Prediction Uncertainty from Geographical Information System Raster Processing: A User's Manual for the Raster Error Propagation Tool (REPTool)

    Science.gov (United States)

    Gurdak, Jason J.; Qi, Sharon L.; Geisler, Michael L.

    2009-01-01

    The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.

  8. Analysis of Multiple Structural Changes in Financial Contagion Based on the Largest Lyapunov Exponents

    Directory of Open Access Journals (Sweden)

    Rui Wang

    2014-01-01

    Full Text Available A modified multiple structural changes model is built to test structural breaks of the financial system based on calculating the largest Lyapunov exponents of the financial time series. Afterwards, the Lorenz system is used as a simulation example to inspect the new model. As the Lorenz system has strong nonlinearity, the verification results show that the new model has good capability in both finding the breakpoint and revealing the changes in nonlinear characteristics of the time series. The empirical study based on the model used daily data from the S&P 500 stock index during the global financial crisis from 2005 to 2012. The results provide four breakpoints of the period, which divide the contagion into four stages: stationary, local outbreak, global outbreak, and recovery period. An additional significant result is the obvious chaos characteristic difference in the largest Lyapunov exponents and the standard deviation at various stages, particularly at the local outbreak stage.

  9. Five-factor model personality disorder prototypes in a community sample: self- and informant-reports predicting interview-based DSM diagnoses.

    Science.gov (United States)

    Lawton, Erin M; Shields, Andrew J; Oltmanns, Thomas F

    2011-10-01

    The need for an empirically validated, dimensional system of personality disorders is becoming increasingly apparent. While a number of systems have been investigated in this regard, the five-factor model of personality has demonstrated the ability to adequately capture personality pathology. In particular, the personality disorder prototypes developed by Lynam and Widiger (2001) have been tested in a number of samples. The goal of the present study is to extend this literature by validating the prototypes in a large, representative community sample of later middle-aged adults using both self and informant reports. We found that the prototypes largely work well in this age group. Schizoid, Borderline, Histrionic, Narcissistic, and Avoidant personality disorders demonstrate good convergent validity, with a particularly strong pattern of discriminant validity for the latter four. Informant-reported prototypes show similar patterns to self reports for all analyses. This demonstrates that informants are not succumbing to halo representations of the participants, but are rather describing participants in nuanced ways. It is important that informant reports add significant predictive validity for Schizoid, Antisocial, Borderline, Histrionic, and Narcissistic personality disorders. Implications of our results and directions for future research are discussed.

  10. Looking for a Location: Dissociated Effects of Event-Related Plausibility and Verb–Argument Information on Predictive Processing in Aphasia

    Science.gov (United States)

    Dickey, Michael Walsh; Warren, Tessa

    2016-01-01

    Purpose This study examined the influence of verb–argument information and event-related plausibility on prediction of upcoming event locations in people with aphasia, as well as older and younger, neurotypical adults. It investigated how these types of information interact during anticipatory processing and how the ability to take advantage of the different types of information is affected by aphasia. Method This study used a modified visual-world task to examine eye movements and offline photo selection. Twelve adults with aphasia (aged 54–82 years) as well as 44 young adults (aged 18–31 years) and 18 older adults (aged 50–71 years) participated. Results Neurotypical adults used verb argument status and plausibility information to guide both eye gaze (a measure of anticipatory processing) and image selection (a measure of ultimate interpretation). Argument status did not affect the behavior of people with aphasia in either measure. There was only limited evidence of interaction between these 2 factors in eye gaze data. Conclusions Both event-related plausibility and verb-based argument status contributed to anticipatory processing of upcoming event locations among younger and older neurotypical adults. However, event-related likelihood had a much larger role in the performance of people with aphasia than did verb-based knowledge regarding argument structure. PMID:27997951

  11. Looking for a Location: Dissociated Effects of Event-Related Plausibility and Verb-Argument Information on Predictive Processing in Aphasia.

    Science.gov (United States)

    Hayes, Rebecca A; Dickey, Michael Walsh; Warren, Tessa

    2016-12-01

    This study examined the influence of verb-argument information and event-related plausibility on prediction of upcoming event locations in people with aphasia, as well as older and younger, neurotypical adults. It investigated how these types of information interact during anticipatory processing and how the ability to take advantage of the different types of information is affected by aphasia. This study used a modified visual-world task to examine eye movements and offline photo selection. Twelve adults with aphasia (aged 54-82 years) as well as 44 young adults (aged 18-31 years) and 18 older adults (aged 50-71 years) participated. Neurotypical adults used verb argument status and plausibility information to guide both eye gaze (a measure of anticipatory processing) and image selection (a measure of ultimate interpretation). Argument status did not affect the behavior of people with aphasia in either measure. There was only limited evidence of interaction between these 2 factors in eye gaze data. Both event-related plausibility and verb-based argument status contributed to anticipatory processing of upcoming event locations among younger and older neurotypical adults. However, event-related likelihood had a much larger role in the performance of people with aphasia than did verb-based knowledge regarding argument structure.

  12. Theory development in health care informatics: Information and communication technology acceptance model (ICTAM) improves the explanatory and predictive power of technology acceptance models.

    Science.gov (United States)

    An, Ji-Young

    2006-01-01

    The purpose of this web-based study was to explain and predict consumers' acceptance and usage behavior of Internet health information and services. Toward this goal, the Information and Communication Technology Acceptance Model (ICTAM) was developed and tested. Individuals who received a flyer through the LISTSERV of HealthGuide were eligible to participate. The study population was eighteen years old and older who had used Internet health information and services for a minimum of 6 months. For the analyses, SPSS (version 13.0) and AMOS (version 5.0) were employed. More than half of the respondents were women (n = 110, 55%). The average age of the respondents was 35.16 years (S.D. = 10.07). A majority reported at least some college education (n = 126, 63%). All of the observed factors accounted for 75.53% of the total variance explained. The fit indices of the structural model were within an acceptable range: chi2/df = 2.38 (chi2 = 1786.31, df = 752); GFI = .71; RMSEA = .08; CFI = .86; NFI = .78. The results of this study provide empirical support for the continued development of ICTAM in the area of health consumers' information and communication technology acceptance.

  13. Five-Factor Model personality disorder prototypes in a community sample: Self- and informant-reports predicting interview-based DSM diagnoses

    Science.gov (United States)

    Lawton, Erin M.; Shields, Andrew J.; Oltmanns, Thomas F.

    2011-01-01

    The need for an empirically-validated, dimensional system of personality disorders is becoming increasingly apparent. While a number of systems have been investigated in this regard, the five-factor model of personality has demonstrated the ability to adequately capture personality pathology. In particular, the personality disorder prototypes developed by Lynam and Widiger (2001) have been tested in a number of samples. The goal of the present study is to extend this literature by validating the prototypes in a large, representative community sample of later middle-aged adults using both self and informant reports. We found that the prototypes largely work well in this age group. Schizoid, Borderline, Histrionic, Narcissistic, and Avoidant personality disorders demonstrate good convergent validity, with a particularly strong pattern of discriminant validity for the latter four. Informant-reported prototypes show similar patterns to self reports for all analyses. This demonstrates that informants are not succumbing to halo representations of the participants, but are rather describing participants in nuanced ways. Importantly, informant reports add significant predictive validity for Schizoid, Antisocial, Borderline, Histrionic, and Narcissistic personality disorders. Implications of our results and directions for future research are discussed. PMID:22200006

  14. An ecologically based model of alcohol-consumption decision making: evidence for the discriminative and predictive role of contextual reward and punishment information.

    Science.gov (United States)

    Bogg, Tim; Finn, Peter R

    2009-05-01

    Using insights from Ecological Systems Theory and Reinforcement Sensitivity Theory, the current study assessed the utility of a series of hypothetical role-based alcohol-consumption scenarios that varied in their presentation of rewarding and punishing information. The scenarios, along with measures of impulsive sensation seeking and a self-report of weekly alcohol consumption, were administered to a sample of alcohol-dependent and non-alcohol-dependent college-age individuals (N = 170). The results showed scenario attendance decisions were largely unaffected by alcohol-dependence status and variations in contextual reward and punishment information. In contrast to the attendance findings, the results for the alcohol-consumption decisions showed alcohol-dependent individuals reported a greater frequency of deciding to drink, as well as indicating greater alcohol consumption in the contexts of complementary rewarding or nonpunishing information. Regression results provided evidence for the criterion-related validity of scenario outcomes in an account of diagnostic alcohol problems. The results are discussed in terms of the conceptual and predictive gains associated with an assessment approach to alcohol-consumption decision making that combines situational information organized and balanced through the frameworks of Ecological Systems Theory and Reinforcement Sensitivity Theory.

  15. Investigation of Science Faculty with Education Specialties within the Largest University System in the United States

    OpenAIRE

    Bush, Seth D; Pelaez, Nancy; Rudd, James A, II; Stevens, Michael T; Tanner, Kimberly D; Williams, Kathy, PhD

    2011-01-01

    Efforts to improve science education include university science departments hiring Science Faculty with Education Specialties (SFES), scientists who take on specialized roles in science education within their discipline. Although these positions have existed for decades and may be growing more common, few reports have investigated the SFES approach to improving science education. We present comprehensive data on the SFES in the California State University (CSU) system, the largest university ...

  16. Opportunities for biodiversity gains under the world’s largest reforestation programme

    OpenAIRE

    Hua, Fangyuan; Wang, Xiaoyang; Zheng, Xinlei; Fisher, Brendan; Wang, Lin; Zhu, Jianguo; Tang, Ya; Yu, Douglas W.; Wilcove, David S.

    2016-01-01

    Reforestation is a critical means of addressing the environmental and social problems of deforestation. China’s Grain-for-Green Program (GFGP) is the world’s largest reforestation scheme. Here we provide the first nationwide assessment of the tree composition of GFGP forests and the first combined ecological and economic study aimed at understanding GFGP’s biodiversity implications. Across China, GFGP forests are overwhelmingly monocultures or compositionally simple mixed forests. Focusing on...

  17. Trend of CO2 emissions of the 30 largest power plants in Germany

    International Nuclear Information System (INIS)

    Hermann, Hauke

    2014-01-01

    The brochure on the trend of CO 2 emissions of the 30 largest power plants in Germany includes tables of the emissions of these power plants. The CO 2 emissions of these power plants in 2013 (25% of the total German greenhouse gas emissions) have increased by 5% compared to 2012. The total CO 2 emission sin Germany increased by 1.5%. The differences between brown coal and black coal fired power plants are discussed.

  18. Natural radionuclides in soil profiles surrounding the largest coal-fired power plant in Serbia

    OpenAIRE

    Tanić Milan N.; Janković-Mandić Ljiljana J.; Gajić Boško A.; Daković Marko Z.; Dragović Snežana D.; Bačić Goran G.

    2016-01-01

    This study evaluates the influence of the largest Serbian coal-fired power plant on radionuclide concentrations in soil profiles up to 50 cm in depth. Thirty soil profiles were sampled from the plant surroundings (up to 10 km distance) and analyzed using standard methods for soil physicochemical properties and gamma ray spectrometry for specific activities of natural radionuclides (40K, 226Ra and 232Th). Spatial and vertical distribution of radionuclides wa...

  19. THE MASS OF (4) VESTA DERIVED FROM ITS LARGEST GRAVITATIONAL EFFECTS

    International Nuclear Information System (INIS)

    Kuzmanoski, Mike; Novakovic, Bojan; Apostolovska, Gordana

    2010-01-01

    In this paper, we present a recalculated value of the mass of (4) Vesta, derived from its largest gravitational perturbations on selected asteroids during their mutual close encounters. This was done by using a new method for mass determination, which is based on the linking of pre-encounter observations to the orbit determined from post-encounter ones. The estimated weighted mean of the mass of (4) Vesta is (1.300 ± 0.001) x 10 -10 M sun .

  20. Prostate Cancer Screening in Jamaica: Results of the Largest National Screening Clinic Prostate Cancer Screening in Jamaica: Results of the Largest National Screening Clinic

    International Nuclear Information System (INIS)

    Morrison, B. F.; Aiken, W.; Mayhew, R.; Gordon, Y.; Reid, M.

    2016-01-01

    Prostate cancer is highly prevalent in Jamaica and is the leading cause of cancer-related deaths. Our aim was to evaluate the patterns of screening in the largest organized screening clinic in Jamaica at the Jamaica Cancer Society. A retrospective analysis of all men presenting for screening at the Jamaica Cancer Society from 1995 to 2005 was done. All patients had digital rectal examinations (DRE) and prostate specific antigen (PSA) tests done. Results of prostate biopsies were noted. 1117 men of mean age 59.9 ± 8.2 years presented for screening. The median documented PSA was 1.6 ng/mL (maximum of 5170 ng/mL). Most patients presented for only 1 screen. There was a gradual reduction in the mean age of presentation for screening over the period. Prostate biopsies were requested on 11% of screening visits; however, only 59% of these were done. 5.6% of all persons screened were found to have cancer. Of the cancers diagnosed, Gleason 6 adenocarcinoma was the commonest grade and median PSA was 8.9 ng/mL (range 1.5-1059 ng/mL). Older men tend to screen for prostate cancer in Jamaica. However, compliance with regular maintenance visits and requests for confirmatory biopsies are poor. Screening needs intervention in the Jamaican population.

  1. Use of citation analysis to predict the outcome of the 2001 Research Assessment Exercise for Unit of Assessment (UoA 61: Library and Information Management

    Directory of Open Access Journals (Sweden)

    Alison Holmes

    2001-01-01

    Full Text Available A citation study was carried out to predict the outcome of the 2001 Research Assessment Exercise. The correlation between scores achieved by academic departments in the UK in the 1996 Research Assessment Exercise, and the number of citations received by academics in those departments for articles published in the period 1994-2000, using the Institute for Scientific Information’s citation databases, was assessed. A citation study was carried out on all three hundred and thirty eight academics that teach in the UK library and information science schools. These authors between them received two thousand three hundred and one citations for articles they had published between 1994 and the present. The results were ranked by Department, and compared to the ratings awarded to the departments in the 1996 Higher Education Funding Council Research Assessment Exercise. On the assumption that RAE scores and citation counts are correlated, predictions were made for the likely RAE scores in the 2001 RAE. Comments were also made on the impact of staff movements from one Higher Education Institution to another.

  2. pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC.

    Science.gov (United States)

    Cheng, Xiang; Xiao, Xuan; Chou, Kuo-Chen

    2017-08-22

    One of the fundamental goals in cellular biochemistry is to identify the functions of proteins in the context of compartments that organize them in the cellular environment. To realize this, it is indispensable to develop an automated method for fast and accurate identification of the subcellular locations of uncharacterized proteins. The current study is focused on plant protein subcellular location prediction based on the sequence information alone. Although considerable efforts have been made in this regard, the problem is far from being solved yet. Most of the existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions. This kind of multiplex protein is particularly important for both basic research and drug design. Using the multi-label theory, we present a new predictor called "pLoc-mPlant" by extracting the optimal GO (Gene Ontology) information into the Chou's general PseAAC (Pseudo Amino Acid Composition). Rigorous cross-validation on the same stringent benchmark dataset indicated that the proposed pLoc-mPlant predictor is remarkably superior to iLoc-Plant, the state-of-the-art method for predicting plant protein subcellular localization. To maximize the convenience of most experimental scientists, a user-friendly web-server for the new predictor has been established at , by which users can easily get their desired results without the need to go through the complicated mathematics involved.

  3. pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information.

    Science.gov (United States)

    Cheng, Xiang; Xiao, Xuan; Chou, Kuo-Chen

    2018-05-01

    For in-depth understanding the functions of proteins in a cell, the knowledge of their subcellular localization is indispensable. The current study is focused on human protein subcellular location prediction based on the sequence information alone. Although considerable efforts have been made in this regard, the problem is far from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for both basic research and drug design. Using the multi-label theory, we present a new predictor called 'pLoc-mHum' by extracting the crucial GO (Gene Ontology) information into the general PseAAC (Pseudo Amino Acid Composition). Rigorous cross-validations on a same stringent benchmark dataset have indicated that the proposed pLoc-mHum predictor is remarkably superior to iLoc-Hum, the state-of-the-art method in predicting the human protein subcellular localization. To maximize the convenience of most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc-mHum/, by which users can easily get their desired results without the need to go through the complicated mathematics involved. xcheng@gordonlifescience.org. Supplementary data are available at Bioinformatics online.

  4. On the statistics of the largest geomagnetic storms per solar cycle

    International Nuclear Information System (INIS)

    Siscoe, G.L.

    1976-01-01

    The theory of extreme value statistics is applied to the first, second, and third largest geomagnetic storms in nine solar cycles measured by the average half-daily aa indices compiled by Mayaud. Analytic expressions giving the probability of the extremes per solar cycle as a contour function of storm magnitude are obtained by least squares fitting of the observations to the appropriate theoretical extreme value probability functions. The results are used to obtain the statistical characteristics (mode, median, mean, and standard deviation) for the extreme values. The results are applied to find the expected range of extreme values in a set as a function of the number of solar cycles in the set. We find that the expected range of the largest storm is quite narrow and is larger for the second and third largest storms. The observed range of the extreme half-daily aa index for the nine solar cycles is 354--546 γ. In a set of 100 cycles the range is expanded esentially to 311--680γ, an increase of only 39% in the range. The result supports the argument for a change in solar cycle statistics in the latter part of the Seventeenth Century (the Maunder minimum)

  5. Hospital Prices Increase in California, Especially Among Hospitals in the Largest Multi-hospital Systems

    Directory of Open Access Journals (Sweden)

    Glenn A. Melnick PhD

    2016-06-01

    Full Text Available A surge in hospital consolidation is fueling formation of ever larger multi-hospital systems throughout the United States. This article examines hospital prices in California over time with a focus on hospitals in the largest multi-hospital systems. Our data show that hospital prices in California grew substantially (+76% per hospital admission across all hospitals and all services between 2004 and 2013 and that prices at hospitals that are members of the largest, multi-hospital systems grew substantially more (113% than prices paid to all other California hospitals (70%. Prices were similar in both groups at the start of the period (approximately $9200 per admission. By the end of the period, prices at hospitals in the largest systems exceeded prices at other California hospitals by almost $4000 per patient admission. Our study findings are potentially useful to policy makers across the country for several reasons. Our data measure actual prices for a large sample of hospitals over a long period of time in California. California experienced its wave of consolidation much earlier than the rest of the country and as such our findings may provide some insights into what may happen across the United States from hospital consolidation including growth of large, multi-hospital systems now forming in the rest of the rest of the country.

  6. Collaborative spectrum sensing based on the ratio between largest eigenvalue and Geometric mean of eigenvalues

    KAUST Repository

    Shakir, Muhammad

    2011-12-01

    In this paper, we introduce a new detector referred to as Geometric mean detector (GEMD) which is based on the ratio of the largest eigenvalue to the Geometric mean of the eigenvalues for collaborative spectrum sensing. The decision threshold has been derived by employing Gaussian approximation approach. In this approach, the two random variables, i.e. The largest eigenvalue and the Geometric mean of the eigenvalues are considered as independent Gaussian random variables such that their cumulative distribution functions (CDFs) are approximated by a univariate Gaussian distribution function for any number of cooperating secondary users and received samples. The approximation approach is based on the calculation of exact analytical moments of the largest eigenvalue and the Geometric mean of the eigenvalues of the received covariance matrix. The decision threshold has been calculated by exploiting the CDF of the ratio of two Gaussian distributed random variables. In this context, we exchange the analytical moments of the two random variables with the moments of the Gaussian distribution function. The performance of the detector is compared with the performance of the energy detector and eigenvalue ratio detector. Analytical and simulation results show that our newly proposed detector yields considerable performance advantage in realistic spectrum sensing scenarios. Moreover, our results based on proposed approximation approach are in perfect agreement with the empirical results. © 2011 IEEE.

  7. Leveraging Open Standard Interfaces in Providing Efficient Discovery, Retrieval, and Information of NASA-Sponsored Observations and Predictions

    Science.gov (United States)

    Cole, M.; Alameh, N.; Bambacus, M.

    2006-05-01

    at http://esg.gsfc.nasa.gov) acts as a flexible and searchable registry of NASA-related resources (files, services, models, etc) and allows scientists, decision makers and others to discover and retrieve a wide variety of observations and predictions of natural and human phenomena related to Earth Science from NASA and other sources. To support the goals of the Applied Sciences national applications, GIO staff is also working with the national applications communities to identify opportunities where open standards-based discovery and access to NASA data can enhance the decision support process of the national applications. This paper describes the work performed to-date on that front, and summarizes key findings in terms of identified data sources and benefiting national applications. The paper also highlights the challenges encountered in making NASA-related data accessible in a cross-cutting fashion and identifies areas where interoperable approaches can be leveraged.

  8. Using the Job-Demands-Resources model to predict turnover in the information technology workforce – General effects and gender

    Directory of Open Access Journals (Sweden)

    Peter Hoonakker

    2014-01-01

    Full Text Available High employee turnover has always been a major issue for Information Technology (IT. In particular, turnover of women is very high. In this study, we used the Job Demand/Resources (JD-R model to examine the relationship between job demands and job resources, stress/burnout and job satisfaction/commitment, and turnover intention and tested the model for gender differences. Data were collected in five IT companies. A sample of 624 respondents (return rate: 56%; 54% males; mean age: 39.7 years was available for statistical analyses. Results of our study show that relationships between job demands and turnover intention are mediated by emotional exhaustion (burnout and relationships between job resources and turnover intention are mediated by job satisfaction. We found noticeable gender differences in these relationships, which can explain differences in turnover intention between male and female employees. The results of our study have consequences for organizational retention strategies to keep men and women in the IT work force.

  9. Lessons from the Largest Epidemic of Avian Influenza Viruses in Taiwan, 2015.

    Science.gov (United States)

    Chang, Ching-Fen; King, Chwan-Chuen; Wan, Cho-Hua; Chang, Yun-Cheng; Chan, Ta-Chien; David Lee, Chang-Chun; Chou, Po-Hao Borris; Li, Zheng-Rong Tiger; Li, Yao-Tsun; Tseng, Tzu-Jung; Lee, Pei-Fen; Chang, Chuan-Hsiung

    2016-05-01

    The largest epidemic of avian influenza (AI) in history attacked poultry and wild birds throughout Taiwan starting January 6, 2015. This study analyzed surveillance results, epidemiologic characteristics, and viral sequences by using government-released information, with the intention to provide recommendations to minimize future pandemic influenza. The H5 clade 2.3.4.4 highly pathogenic AI viruses (HPAIVs) had not been detected in Taiwan before 2015. During this epidemic, four types of etiologic agents were identified: the three novel subtypes H5N2, H5N8, and H5N3 clade 2.3.4.4 HPAIVs and one endemic chicken H5N2 subtype (Mexican-like lineage) of low pathogenic AI viruses. Cocirculation of mixed subtypes also occurred, with H5N2 clade 2.3.4.4 HPAIVs accompanied by the H5N8 and H5N3 subtypes or old H5N2 viruses in the same farm. More than 90% of domestic geese died from this AI epidemic; geese were affected the most at the early outbreaks. The epidemic peaked in mid-January for all three novel H5 subtypes. Spatial epidemiology found that most affected areas were located in southwestern coastal areas. In terrestrial poultry (mostly chickens), different geographic distributions of AI virus subtypes were detected, with hot spots of H5N2 clade 2.3.4.4 vs. past-endemic old H5N2 viruses in Changhwa (P = 0.03) and Yunlin (P = 0.007) counties, respectively, of central Taiwan. Phylogenetic and sequence analyses of all the early 10 Taiwan H5 clade 2.3.4.4 isolates covering the three subtypes showed that they were very different from the HA of the past local H5 viruses from domestic ducks (75%-80%) and chickens (70%-75%). However, they had the highest sequence identity percentages (99.53%-100%), with the HA of A/crane/Kagoshima/KU13/2014(H5N8) isolated on December 7, 2014, in Japan being higher than those of recent American and Korean H5 HPAIVs [A/Northern pintail/Washington/40964/2014 (H5N2) and A/gyrfalcon/Washington/41088-6/2014 (H5N8): 99.02%-99.54% and A/Baikal teal

  10. Perceived Physician-informed Weight Status Predicts Accurate Weight Self-Perception and Weight Self-Regulation in Low-income, African American Women.

    Science.gov (United States)

    Harris, Charlie L; Strayhorn, Gregory; Moore, Sandra; Goldman, Brian; Martin, Michelle Y

    2016-01-01

    Obese African American women under-appraise their body mass index (BMI) classification and report fewer weight loss attempts than women who accurately appraise their weight status. This cross-sectional study examined whether physician-informed weight status could predict weight self-perception and weight self-regulation strategies in obese women. A convenience sample of 118 low-income women completed a survey assessing demographic characteristics, comorbidities, weight self-perception, and weight self-regulation strategies. BMI was calculated during nurse triage. Binary logistic regression models were performed to test hypotheses. The odds of obese accurate appraisers having been informed about their weight status were six times greater than those of under-appraisers. The odds of those using an "approach" self-regulation strategy having been physician-informed were four times greater compared with those using an "avoidance" strategy. Physicians are uniquely positioned to influence accurate weight self-perception and adaptive weight self-regulation strategies in underserved women, reducing their risk for obesity-related morbidity.

  11. THE EVOLUTION OF THE WORLD’S LARGEST AUTOMAKERS IN THE PERIOD 2013-2014

    Directory of Open Access Journals (Sweden)

    Sorin-George TOMA

    2015-04-01

    Full Text Available The automotive industry has always represented an economic engine for many countries. It is dealing with the design, development, manufacture, marketing, and sale of the motor vehicles. Nowadays, this industry is full of intense competition between big auto groups fighting for higher profits and larger market shares. The key players in the automotive market are operating at a global scale in a highly competitive environment. In the last years, Toyota Motor and Volkswagen Group have proved to be the main competitors. The aim of our paper is to analyze the evolution of the world’s largest automakers in the period 2013-2014. The research type is literature review.

  12. Europe's largest solar thermal power plant. [200 kw thermal output supplemented by two 10-kw windmills

    Energy Technology Data Exchange (ETDEWEB)

    Bossel, U

    1976-03-01

    An overview is given over the solar heating plant which has recently been commissioned in the Camargue (France). This is the largest plant in Europe, with a mean heat output of about 200 kW, for the production of thermal energy from solar energy. The plant consists of 108 parabolic collectors (200 sq. metres) and 48 flat collectors (110 sq. metres). Two windmills with outputs of 10 kW each complete the system. The heat energy produced by the solar collectors is given up to 3 different stores, which in turn are connected to various consumers.

  13. OBJECT TRACKING WITH ROTATION-INVARIANT LARGEST DIFFERENCE INDEXED LOCAL TERNARY PATTERN

    Directory of Open Access Journals (Sweden)

    J Shajeena

    2017-02-01

    Full Text Available This paper presents an ideal method for object tracking directly in the compressed domain in video sequences. An enhanced rotation-invariant image operator called Largest Difference Indexed Local Ternary Pattern (LDILTP has been proposed. The Local Ternary Pattern which worked very well in texture classification and face recognition is now extended for rotation invariant object tracking. Histogramming the LTP code makes the descriptor resistant to translation. The histogram intersection is used to find the similarity measure. This method is robust to noise and retain contrast details. The proposed scheme has been verified on various datasets and shows a commendable performance.

  14. Female urethral diverticulum presenting with acute urinary retention: Reporting the largest diverticulum with review of literature

    Directory of Open Access Journals (Sweden)

    Manas Ranjan Pradhan

    2012-01-01

    Full Text Available Female urethral diverticulum is a rare entity with diverse spectrum of clinical manifestations. It is a very rare cause of bladder outlet obstruction and should be considered as a differential diagnosis in females presenting with acute urinary retention associated with a vaginal mass. Strong clinical suspicion combined with thorough physical examination and focused radiological investigations are vital for its diagnosis. Herein we report a case of giant urethral diverticulum presenting with acute urinary retention in a young female. It was managed by excision and urethral closure, and is the largest urethral diverticulum reported till date in the literature.

  15. WISMUT AG: Past, present and future of the largest uranium producer in Europe

    International Nuclear Information System (INIS)

    Madel, J.

    1990-01-01

    The author gives a brief summary of WISMUT AG the largest uranium producer operating in Europe. The jointly owned German-Soviet company operates its production facilities in the southern part of the former German Democratic Republic. Given the new political and economic frame in Germany and the Soviet Union WISMUT AG will receive due recognition. Uranium exploration, mining, and milling activities are summarized from 1946-1989, and a summary of present activities and projections of future activities in the area of decontamination, restoration, and recultivation of present and abandoned mining and milling sites are noted. A statement of WISMUT AG's projected role in the international nuclear fuels market is made

  16. How the largest electric and gas utility companies administer public relations

    Energy Technology Data Exchange (ETDEWEB)

    Bogart, J.D.

    1979-04-12

    This article describes the findings of a survey conducted by the author in the second half of 1978 to determine the sizes of the public relations staffs of the nation's largest operating electric and gas utilities, their budgets, organizational differences, and specific functions. Common public relations issues and major public relations problems of the utilities are identified, as well as recent trends or changes in budgeting and organization. Some functional variations of public relations departments among utility companies were detected and described.

  17. Line Balancing Using Largest Candidate Rule Algorithm In A Garment Industry: A Case Study

    Directory of Open Access Journals (Sweden)

    V. P.Jaganathan

    2014-12-01

    Full Text Available The emergence of fast changes in fashion has given rise to the need to shorten production cycle times in the garment industry. As effective usage of resources has a significant effect on the productivity and efficiency of production operations, garment manufacturers are urged to utilize their resources effectively in order to meet dynamic customer demand. This paper focuses specifically on line balancing and layout modification. The aim of assembly line balance in sewing lines is to assign tasks to the workstations, so that the machines of the workstation can perform the assigned tasks with a balanced loading. Largest Candidate Rule Algorithm (LCR has been deployed in this paper.

  18. Foreign exchange risk management : how are the largest non-financial companies in Norway managing their foreign exchange rate exposure?

    OpenAIRE

    Eriksen, Krister; Wedøe, Ola

    2010-01-01

    The purpose of this thesis is to investigate how the largest non-financial companies in Norway manage their foreign exchange rate exposure. This is investigated through the use of a survey distributed to a sample the largest non-financial firms in Norway. According to our results, the largest non-financial companies in Norway have a predefined strategy for managing foreign exchange risk, which is defined by the board of directors or by the management in the organisation. The companies’ mai...

  19. Methodology for predictive modeling of environmental transport and health effects for waste sites at the Savannah River Plant: Environmental information document

    International Nuclear Information System (INIS)

    Stephensen, D.E.; King, C.M.; Looney, B.B.; Grant, M.W.

    1987-03-01

    This document provides information on the methods used to predict chemical transport and the associated health risk for various postulated closure activities at waste sites. The document was prepared as background documentation for the Department of Energy's proposed Environmental Impact Statement (EIS) on waste management activities for groundwater protection at the Savannah River Plant (SRP). The various mathematical formulations used in the environmental transport analysis, the exposure assessment, and the health risk assessment used in the analysis of all foreseeable scenarios as defined by the National Environmental Policy Act (CFR, 1986) are presented in this document. The scenarios do not necessarily represent actual environmental conditions for every SRP waste site. This document was prepared in support of the National Environmental Policy Act process, but does not by itself satisfy federal or state regulatory requirements. 29 refs., 11 figs

  20. Can purchasing information be used to predict adherence to cardiovascular medications? An analysis of linked retail pharmacy and insurance claims data.

    Science.gov (United States)

    Krumme, Alexis A; Sanfélix-Gimeno, Gabriel; Franklin, Jessica M; Isaman, Danielle L; Mahesri, Mufaddal; Matlin, Olga S; Shrank, William H; Brennan, Troyen A; Brill, Gregory; Choudhry, Niteesh K

    2016-11-09

    The use of retail purchasing data may improve adherence prediction over approaches using healthcare insurance claims alone. Retrospective. A cohort of patients who received prescription medication benefits through CVS Caremark, used a CVS Pharmacy ExtraCare Health Care (ECHC) loyalty card, and initiated a statin medication in 2011. We evaluated associations between retail purchasing patterns and optimal adherence to statins in the 12 subsequent months. Among 11 010 statin initiators, 43% were optimally adherent at 12 months of follow-up. Greater numbers of store visits per month and dollar amount per visit were positively associated with optimal adherence, as was making a purchase on the same day as filling a prescription (ppurchase variables had low discriminative ability (C-statistic: 0.563), while models with both clinical and retail purchase variables achieved a C-statistic of 0.617. While the use of retail purchases may improve the discriminative ability of claims-based approaches, these data alone appear inadequate for adherence prediction, even with the addition of more complex analytical approaches. Nevertheless, associations between retail purchasing behaviours and adherence could inform the development of quality improvement interventions. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  1. Revisiting the impacts of oil price increases on monetary policy implementation in the largest oil importers

    Directory of Open Access Journals (Sweden)

    Nurtac Yildirim

    2015-06-01

    Full Text Available The aim of this paper is to test the impacts of oil price increases on monetary policy implementation in the largest oil importers. For that purpose, we estimate structural vector error correction (SVEC models to show the impacts of oil price increases on industrial production, consumer prices and immediate interest rates which are the elements of Taylor rule for the four largest oil importers (the USA, the EU, China and Japan. Our results indicate that oil price increases transmit to output and inflation and lead to fluctuations in industrial production, consumer prices and immediate interest rates which in turn influence the monetary policy stance in the following periods. The basic conclusion of research is that the channels through which oil prices affect output, inflation and interest rates should be identified by the monetary policy authorities of the USA, the EU, China and Japan. We also emphasize the importance of the determination of the optimal monetary policy framework to eliminate the negative consequences of oil price increases.

  2. Rehabilitation of the 6 largest hydropower plants in the Republic of Macedonia

    International Nuclear Information System (INIS)

    Chingoski, Vlatko; Savevski, Vasil

    2004-01-01

    In 1998, ESM (Electric Power Co. of Macedonia) received a loan from the International Bank for Reconstruction and Development (IBRD - The World bank) for the cost of the Power System Improvement Project, major part of which is the partial rehabilitation of the six largest HPPs in the Republic of Macedonia. Rehabilitation and life extension of these six largest hydro power plants is given the highest priority in the whole Power System Improvement Project mainly because these HPPs are, in general, fairly old, older than most of the thermal generation capacity and because a significant part of their equipment is wearing out, or is now obsolete with spare parts difficult to obtain. Furthermore, these plants play a vital role in the Macedonian Power System, providing peaking capacity, reserve capacity and frequency control. With the realization of this project, greater hydropower production is expected. It is also expected that HPPs will become a more vital part of the Macedonian Power System, which is also beneficial from an environmental aspect, due to greater usage of renewable energy resources in the country. (Original)

  3. Ownership structure and economic and socio-environmental disclosure in the largest Brazilian companies

    Directory of Open Access Journals (Sweden)

    Tatiana Aquino Almeida

    2016-01-01

    Full Text Available The disclosure of sustainable practices has become important in the search for competitive advantage, so as to meet the expectations of the various stakeholders. Thus, the study aims to investigate the relationship between the ownership structure and the economic and environmental voluntary disclosure in the largest Brazilian companies, analyzing ownership concentration and the identity of the controlling shareholder. For the analysis, we considered the economic, social and environmental perspectives, addressed both individually and jointly. The sample consists of 47 companies from the 100 largest public companies listed on BM&FBOVESPA, according to the magazine Exame Biggest and Best, edition 2013. The research is descriptive and quantitative, using Multiple Linear Regression for statistical analysis. The descriptive analysis of the prospects of (economic, social, environmental and sustainability disclosure showed lower average disclosure for the environmental aspect. The state control organizations stood out with the highest average in three of the four levels of disclosure: economic, social and sustainability. As regards the application of statistical analysis, the regression models were not statistically significant, indicating that, for the companies in the sample, the ownership structure does not influence the economic and socio-environmental disclosure.

  4. Dispersal syndromes in the largest protection area of the Atlantic Forest in the state of Paraiba, Brazil

    Directory of Open Access Journals (Sweden)

    Camila Ângelo Jerônimo Domingues

    2013-09-01

    Full Text Available The diaspore dispersal process is crucial for plant reproduction, since the diaspores must reach a suitable site to germinate. This paper aimed to study morphological aspects of diaspores and determine the dispersal syndromes of species occurring in the largest protection area of the Atlantic Forest in the state of Paraiba, Brazil, the Guaribas Biological Reserve. One conducted a monthly collection of fruits/seeds within the period from September 2007 to February 2009. All diaspores of the fruiting species were collected. After analyzing characteristics such as fruit and seed consistency, odor, color, size, and weight, one determined the dispersal syndrome of each species. One collected 3,080 diaspores belonging to 136 different species distributed into 27 families. Zoochory was the most abundant dispersal syndrome (58%, with 79 fruits adapted to it, followed by autochory (29%, and anemochory (13%. Throughout the study period, one found fruiting species, with a predominance of zoochoric fruits, a predictable fact in the Atlantic Forest, which provides fleshy fruits all the year round.

  5. THE POTENTIAL OF THE EQUITY WORKING CAPITAL IN THE PREDICTION OF BANKRUPTCY

    OpenAIRE

    Daniel BRÎNDESCU – OLARIU

    2014-01-01

    The current study evaluates the potential of the equity working capital in predicting corporate bankruptcy. The population subjected to the analysis included all companies form Timis County (largest Romanian County) with yearly sales of over 10000 lei. The interest for the equity working capital was based on the recommendations of the literature, as well as on the availability of information concerning its values to all stakeholders. The event on which the research was focused was repr...

  6. ESO Signs Largest-Ever European Industrial Contract For Ground-Based Astronomy Project ALMA

    Science.gov (United States)

    2005-12-01

    ESO, the European Organisation for Astronomical Research in the Southern Hemisphere, announced today that it has signed a contract with the consortium led by Alcatel Alenia Space and composed also of European Industrial Engineering (Italy) and MT Aerospace (Germany), to supply 25 antennas for the Atacama Large Millimeter Array (ALMA) project, along with an option for another seven antennas. The contract, worth 147 million euros, covers the design, manufacture, transport and on-site integration of the antennas. It is the largest contract ever signed in ground-based astronomy in Europe. The ALMA antennas present difficult technical challenges, since the antenna surface accuracy must be within 25 microns, the pointing accuracy within 0.6 arc seconds, and the antennas must be able to be moved between various stations on the ALMA site. This is especially remarkable since the antennas will be located outdoor in all weather conditions, without any protection. Moreover, the ALMA antennas can be pointed directly at the Sun. ALMA will have a collecting area of more than 5,600 square meters, allowing for unprecedented measurements of extremely faint objects. The signing ceremony took place on December 6, 2005 at ESO Headquarters in Garching, Germany. "This contract represents a major milestone. It allows us to move forward, together with our American and Japanese colleagues, in this very ambitious and unique project," said ESO's Director General, Dr. Catherine Cesarsky. "By building ALMA, we are giving European astronomers access to the world's leading submillimetre facility at the beginning of the next decade, thereby fulfilling Europe's desire to play a major role in this field of fundamental research." Pascale Sourisse, Chairman and CEO of Alcatel Alenia Space, said: "We would like to thank ESO for trusting us to take on this new challenge. We are bringing to the table not only our recognized expertise in antenna development, but also our long-standing experience in

  7. Deep, diverse and definitely different: unique attributes of the world's largest ecosystem

    Directory of Open Access Journals (Sweden)

    E. Ramirez-Llodra

    2010-09-01

    Full Text Available The deep sea, the largest biome on Earth, has a series of characteristics that make this environment both distinct from other marine and land ecosystems and unique for the entire planet. This review describes these patterns and processes, from geological settings to biological processes, biodiversity and biogeographical patterns. It concludes with a brief discussion of current threats from anthropogenic activities to deep-sea habitats and their fauna.

    Investigations of deep-sea habitats and their fauna began in the late 19th century. In the intervening years, technological developments and stimulating discoveries have promoted deep-sea research and changed our way of understanding life on the planet. Nevertheless, the deep sea is still mostly unknown and current discovery rates of both habitats and species remain high. The geological, physical and geochemical settings of the deep-sea floor and the water column form a series of different habitats with unique characteristics that support specific faunal communities. Since 1840, 28 new habitats/ecosystems have been discovered from the shelf break to the deep trenches and discoveries of new habitats are still happening in the early 21st century. However, for most of these habitats the global area covered is unknown or has been only very roughly estimated; an even smaller – indeed, minimal – proportion has actually been sampled and investigated. We currently perceive most of the deep-sea ecosystems as heterotrophic, depending ultimately on the flux on organic matter produced in the overlying surface ocean through photosynthesis. The resulting strong food limitation thus shapes deep-sea biota and communities, with exceptions only in reducing ecosystems such as inter alia hydrothermal vents or cold seeps. Here, chemoautolithotrophic bacteria play the role of primary producers fuelled by chemical energy sources rather than sunlight. Other ecosystems, such as seamounts, canyons or cold

  8. pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC.

    Science.gov (United States)

    Cheng, Xiang; Xiao, Xuan; Chou, Kuo-Chen

    2017-09-10

    Knowledge of subcellular locations of proteins is crucially important for in-depth understanding their functions in a cell. With the explosive growth of protein sequences generated in the postgenomic age, it is highly demanded to develop computational tools for timely annotating their subcellular locations based on the sequence information alone. The current study is focused on virus proteins. Although considerable efforts have been made in this regard, the problem is far from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions. This kind of multiplex proteins is particularly important for both basic research and drug design. Using the multi-label theory, we present a new predictor called "pLoc-mVirus" by extracting the optimal GO (Gene Ontology) information into the general PseAAC (Pseudo Amino Acid Composition). Rigorous cross-validation on a same stringent benchmark dataset indicated that the proposed pLoc-mVirus predictor is remarkably superior to iLoc-Virus, the state-of-the-art method in predicting virus protein subcellular localization. To maximize the convenience of most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc-mVirus/, by which users can easily get their desired results without the need to go through the complicated mathematics involved. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Testing the importance of family solidarity, community structure, information access, and social capital in predicting nutrition health knowledge and food choices in the Philippines.

    Science.gov (United States)

    Moxley, Robert L; Jicha, Karl A; Thompson, Gretchen H

    2011-01-01

    This study investigates the influence of family solidarity, community structure, information access, social capital, and socioeconomic status on the extent of nutrition and health knowledge (NHK) among primary household meal planners. In turn, we pose the question: does this knowledge influence dietary decision making? Data are taken from a survey determining socioeconomic impacts of vitamin A fortified peanut butter on Philippine households. Questions on the relationships of nutrition to health were selected to construct a knowledge index on which household respondents could be ranked. We then tested hypotheses regarding what types of individual, family-level, and community structural characteristics would predict performance on this index. The results indicate that the strongest predictors of NHK come from sociological theory related to family solidarity and community centrality, in addition to information accessibility and household income. Our findings also indicate that NHK influences dietary choices with regard to the purchase of a vitamin fortified staple food product, which is essential when addressing nutritional deficiency problems in developing countries.

  10. Climate prediction and predictability

    Science.gov (United States)

    Allen, Myles

    2010-05-01

    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the climateprediction.net project, running multiple versions of climate models on personal computers.

  11. Field Note: Threatening Tonle Sap: Challenges for Southeast-Asia’s largest Freshwater Lake

    Directory of Open Access Journals (Sweden)

    Kuenzer, Claudia

    2013-09-01

    Full Text Available The Tonle Sap ecosystem in Cambodia is Southeast Asia’s largest freshwater lake; strongly impacted by the Mekong river flood pulse. The lake is home to exceptional biodiversity, and rural communities living in free floating villages on the lake and on its shores. The fragile niche ecosystems as well as the rural livelihoods of Tonle Sap are under severe threat. Overfishing, illegal wood harvesting, further resource exploitation, and water quality deterioration all impact the stability of the socio-ecological system of Tonle Sap. At the same time, expected flood pulse changes due to regulatory measures in the context of hydropower development upstream on the Mekong are a severe threat for Tonle Sap’s ecosystem stability. The area needs to shift into the focus of attention of national and international re-searchers, stakeholders, and decision makers, to find suitable pathways for a future sustainable development of this unique and pristine region.

  12. Fifteen Years of Operation at NASA's National Transonic Facility with the World's Largest Adjustable Speed Drive

    Science.gov (United States)

    Sydnor, George H.; Bhatia, Ram; Krattiger, Hansueli; Mylius, Justus; Schafer, D.

    2012-01-01

    In September 1995, a project was initiated to replace the existing drive line at NASA's most unique transonic wind tunnel, the National Transonic Facility (NTF), with a single 101 MW synchronous motor driven by a Load Commutated Inverter (LCI). This Adjustable Speed Drive (ASD) system also included a custom four-winding transformer, harmonic filter, exciter, switch gear, control system, and feeder cable. The complete system requirements and design details have previously been presented and published [1], as well as the commissioning and acceptance test results [2]. The NTF was returned to service in December 1997 with the new drive system powering the fan. Today, this installation still represents the world s largest horizontal single motor/drive combination. This paper describes some significant events that occurred with the drive system during the first 15 years of service. These noteworthy issues are analyzed and root causes presented. Improvements that have substantially increased the long term viability of the system are given.

  13. Mauna Loa--history, hazards and risk of living with the world's largest volcano

    Science.gov (United States)

    Trusdell, Frank A.

    2012-01-01

    Mauna Loa on the Island Hawaiʻi is the world’s largest volcano. People residing on its flanks face many hazards that come with living on or near an active volcano, including lava flows, explosive eruptions, volcanic smog, damaging earthquakes, and local tsunami (giant seawaves). The County of Hawaiʻi (Island of Hawaiʻi) is the fastest growing County in the State of Hawaii. Its expanding population and increasing development mean that risk from volcano hazards will continue to grow. U.S. Geological Survey (USGS) scientists at the Hawaiian Volcano Observatory (HVO) closely monitor and study Mauna Loa Volcano to enable timely warning of hazardous activity and help protect lives and property.

  14. Quicksort, largest bucket, and min-wise hashing with limited independence

    DEFF Research Database (Denmark)

    Knudsen, Mathias Bæk Tejs; Stöckel, Morten

    2015-01-01

    Randomized algorithms and data structures are often analyzed under the assumption of access to a perfect source of randomness. The most fundamental metric used to measure how “random” a hash function or a random number generator is, is its independence: a sequence of random variables is said...... to be k-independent if every variable is uniform and every size k subset is independent. In this paper we consider three classic algorithms under limited independence. Besides the theoretical interest in removing the unrealistic assumption of full independence, the work is motivated by lower independence...... being more practical. We provide new bounds for randomized quicksort, min-wise hashing and largest bucket size under limited independence. Our results can be summarized as follows. Randomized Quicksort. When pivot elements are computed using a 5-independent hash function, Karloff and Raghavan, J.ACM’93...

  15. Contamination Control Assessment of the World's Largest Space Environment Simulation Chamber

    Science.gov (United States)

    Snyder, Aaron; Henry, Michael W.; Grisnik, Stanley P.; Sinclair, Stephen M.

    2012-01-01

    The Space Power Facility s thermal vacuum test chamber is the largest chamber in the world capable of providing an environment for space simulation. To improve performance and meet stringent requirements of a wide customer base, significant modifications were made to the vacuum chamber. These include major changes to the vacuum system and numerous enhancements to the chamber s unique polar crane, with a goal of providing high cleanliness levels. The significance of these changes and modifications are discussed in this paper. In addition, the composition and arrangement of the pumping system and its impact on molecular back-streaming are discussed in detail. Molecular contamination measurements obtained with a TQCM and witness wafers during two recent integrated system tests of the chamber are presented and discussed. Finally, a concluding remarks section is presented.

  16. What could we learn about high energy particle physics from cosmological observations at largest spatial scales ?

    Directory of Open Access Journals (Sweden)

    Gorbunov Dmitry

    2017-01-01

    Full Text Available The very well known example of cosmology testing particle physics is the number of relativistic particles (photons and three active neutrinos within the Standard Model at primordial nucleosynthesis. These days the earliest moment we can hope to probe with present cosmological data is the early time inflation. The particle physics conditions there and now are different because of different energy scales and different values of the scalar fields, that usually prohibits a reliable connection between the particle physics parameters at the two interesting epochs. The physics at the highest energy scales may be probed with observations at the largest spatial scales (just somewhat smaller than the size of the visible Universe. However, we are not (yet ready to make the tests realistic, because of lack of a self-consistent theoretical description of the presently favorite cosmological models to be valid right after inflation.

  17. The role and attributes of entrepreneurs at South Africa´s largest arts festival

    Directory of Open Access Journals (Sweden)

    E. Jonker

    2009-01-01

    Full Text Available The Klein Karoo National Arts Festival (KKNK in Oudtshoorn, South Africa, is the largest arts festival in South Africa. The purpose of this research was to determine the attributes and role of the entrepreneurs at the Klein Karoo National Arts Festival. This was done by means of a questionnaire survey (N=249. After data capturing was completed, two factor analyses were conducted. The first factor analysis revealed six factors (entrepreneurial attributes, namely organisational skills, resourcefulness, self-edification, explorative, acquired skill and drive, of which resourcefulness had the highest mean value. The second factor analysis identified the role of entrepreneurs at KKNK and revealed three primary roles, namely festival promotion, product promotion and income generation, of which product promotion had the highest mean value. This is the first time that the roles of entrepreneurs at festivals were investigated in South Africa.

  18. EVALUATION OF E-RECRUITMENT LEVEL AMONG THE LARGEST COMPANIES IN POLAND - PROJECT OF RESEARCH

    Directory of Open Access Journals (Sweden)

    Dorota Buchnowska

    2015-12-01

    Full Text Available The changes taking place in the labor market cause that it is increasingly difficult to recruit employees with the right skills and competencies to companies. To reach the right candidates, they use modern IT solutions, such as ATS (Applicant Tracking System, which are supporting the processes of recruitment. Among others, they enable the publication of job offers on the Internet - on corporate websites, job portals and business social networking services - and apply for jobs online through these channels. This article pre-sents the evolution of the use of the Internet, and particularly the social media, in the recruitment process and presents a projekt of comprehensive research, which aims is to analyze and evaluate of the level of development of e-recruitment in Poland among largest companies.

  19. Using largest Lyapunov exponent to confirm the intrinsic stability of boiling water reactors

    International Nuclear Information System (INIS)

    Gavilian-Moreno, Carlos; Espinosa-Paredes, Gilberto

    2016-01-01

    The aim of this paper is the study of instability state of boiling water reactors with a method based in largest Lyapunov exponents (LLEs). Detecting the presence of chaos in a dynamical system is an important problem that is solved by measuring the LLE. Lyapunov exponents quantify the exponential divergence of initially close state-space trajectories and estimate the amount of chaos in a system. This method was applied to a set of signals from several nuclear power plant (NPP) reactors under commercial operating conditions that experienced instabilities events, apparently each of a different nature. Laguna Verde and Forsmark NPPs with in-phase instabilities, and Cofrentes NPP with out-of-phases instability. This study presents the results of intrinsic instability in the boiling water reactors of three NPPs. In the analyzed cases the limit cycle was not reached, which implies that the point of equilibrium exerts influence and attraction on system evolution

  20. Using largest Lyapunov exponent to confirm the intrinsic stability of boiling water reactors

    Energy Technology Data Exchange (ETDEWEB)

    Gavilian-Moreno, Carlos [Iberdrola Generacion, S.A., Cofrentes Nuclear Power Plant, Project Engineering Department, Paraje le Plano S/N, Valencia (Spain); Espinosa-Paredes, Gilberto [Area de ingeniera en Recursos Energeticos, Universidad Autonoma Metropolitana-Iztapalapa, Mexico city (Mexico)

    2016-04-15

    The aim of this paper is the study of instability state of boiling water reactors with a method based in largest Lyapunov exponents (LLEs). Detecting the presence of chaos in a dynamical system is an important problem that is solved by measuring the LLE. Lyapunov exponents quantify the exponential divergence of initially close state-space trajectories and estimate the amount of chaos in a system. This method was applied to a set of signals from several nuclear power plant (NPP) reactors under commercial operating conditions that experienced instabilities events, apparently each of a different nature. Laguna Verde and Forsmark NPPs with in-phase instabilities, and Cofrentes NPP with out-of-phases instability. This study presents the results of intrinsic instability in the boiling water reactors of three NPPs. In the analyzed cases the limit cycle was not reached, which implies that the point of equilibrium exerts influence and attraction on system evolution.

  1. World's largest off-road tires to be recycled

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    2005-07-01

    Suncor Energy is the first company in Canada to use a new technology designed uniquely for tire recycling at oil sand facilities. The technology is owned by CuttingEdge Tire Recycling, a partnership between Denesoline Environmental Limited Partnership and Beaver Environmental Rubber Technologies Limited. Suncor has supported the development of this Aboriginal-owned and operated business by offering land, electricity, diesel fuel and stockpiles of used truck tires from its oil sand mining activities. These tires are the largest off-road tires in the world. In this new technology, tires that are worn-out through oil sand mining are shredded in a portable shredder before being recycled for subsequent use by the Alberta Recycling Management Association. 1 fig.

  2. Enhanced natural radiation exposure enhanced by human activity: the largest contributor to the Chinese population dose

    International Nuclear Information System (INIS)

    Pan Ziqiang; Liu Yanyang

    2011-01-01

    For the radiation exposure caused by human activities, the enhanced natural radiation exposure is the largest contributor to Chinese population dose. This problem has attracted social attention in recent years. Efforts have been made in several fields, such as radon indoors and in workplace, environmental problems associated with NORMs, occupational radiation hazards of non-uranium mine, and radiation dose evaluation for energy chain, but there are still many problems to be solved. In order to protect the health of workers and the public, while ensuring industrial production and economic development, it is also necessary to continue to strengthen research in all aspects above mentioned, and gradually promote the control of natural radiation exposure enhanced by human activities. (authors)

  3. The largest deep-ocean silicic volcanic eruption of the past century.

    Science.gov (United States)

    Carey, Rebecca; Soule, S Adam; Manga, Michael; White, James; McPhie, Jocelyn; Wysoczanski, Richard; Jutzeler, Martin; Tani, Kenichiro; Yoerger, Dana; Fornari, Daniel; Caratori-Tontini, Fabio; Houghton, Bruce; Mitchell, Samuel; Ikegami, Fumihiko; Conway, Chris; Murch, Arran; Fauria, Kristen; Jones, Meghan; Cahalan, Ryan; McKenzie, Warren

    2018-01-01

    The 2012 submarine eruption of Havre volcano in the Kermadec arc, New Zealand, is the largest deep-ocean eruption in history and one of very few recorded submarine eruptions involving rhyolite magma. It was recognized from a gigantic 400-km 2 pumice raft seen in satellite imagery, but the complexity of this event was concealed beneath the sea surface. Mapping, observations, and sampling by submersibles have provided an exceptionally high fidelity record of the seafloor products, which included lava sourced from 14 vents at water depths of 900 to 1220 m, and fragmental deposits including giant pumice clasts up to 9 m in diameter. Most (>75%) of the total erupted volume was partitioned into the pumice raft and transported far from the volcano. The geological record on submarine volcanic edifices in volcanic arcs does not faithfully archive eruption size or magma production.

  4. Largest solar installation on a hotel in Switzerland; Groesste Hotel-Solaranlage der Schweiz

    Energy Technology Data Exchange (ETDEWEB)

    Stadelmann, M.

    2008-07-01

    This article describes the solar thermal installation on the Hotel Europa in St. Moritz-Champfer, Switzerland. The installation provides heat energy for domestic hot water preparation and for the heating of the hotel's indoor swimming pool. A thirty-percent reduction of heating oil consumption has been obtained. The system, which is based on the 'low-flow' principle, provides the highest possible temperature difference while using low pumping energy. The hotel's hot-water circulation system, which ensures fast availability of hot water at the taps, is also discussed. This largest hotel solar installation is designed to meet heating and hot-water requirements during the summer season. The high requirements placed on the materials used are discussed. Schematics are provided and first operational experience is briefly discussed.

  5. Using Largest Lyapunov Exponent to Confirm the Intrinsic Stability of Boiling Water Reactors

    Directory of Open Access Journals (Sweden)

    Carlos J. Gavilán-Moreno

    2016-04-01

    Full Text Available The aim of this paper is the study of instability state of boiling water reactors with a method based in largest Lyapunov exponents (LLEs. Detecting the presence of chaos in a dynamical system is an important problem that is solved by measuring the LLE. Lyapunov exponents quantify the exponential divergence of initially close state-space trajectories and estimate the amount of chaos in a system. This method was applied to a set of signals from several nuclear power plant (NPP reactors under commercial operating conditions that experienced instabilities events, apparently each of a different nature. Laguna Verde and Forsmark NPPs with in-phase instabilities, and Cofrentes NPP with out-of-phases instability. This study presents the results of intrinsic instability in the boiling water reactors of three NPPs. In the analyzed cases the limit cycle was not reached, which implies that the point of equilibrium exerts influence and attraction on system evolution.

  6. From Pushing Paper to Pushing Dirt - Canada's Largest LLRW Cleanup Gets Underway - 13111

    International Nuclear Information System (INIS)

    Veen, Walter van; Lawrence, Dave

    2013-01-01

    The Port Hope Project is the larger of the two projects in the Port Hope Area Initiative (PHAI), Canada's largest low level radioactive waste (LLRW) cleanup. With a budget of approximately $1 billion, the Port Hope Project includes a broad and complex range of remedial elements from a state of the art water treatment plant, an engineered waste management facility, municipal solid waste removal, remediation of 18 major sites within the Municipality of Port Hope (MPH), sediment dredging and dewatering, an investigation of 4,800 properties (many of these homes) to identify LLRW and remediation of approximately 450 of these properties. This paper discusses the status of the Port Hope Project in terms of designs completed and regulatory approvals received, and sets out the scope and schedule for the remaining studies, engineering designs and remediation contracts. (authors)

  7. Mapping Biomass for REDD in the Largest Forest of Central Africa: the Democratic Republic of Congo

    Science.gov (United States)

    Shapiro, Aurelie; Saatchi, Sassan

    2014-05-01

    With the support of the International Climate Initiative (ICI) of the Federal Ministry of the Environment, Conservation, and Nuclear Security, the implementation of the German Development Bank KfW, the World Wide Fund for Nature (WWF) Germany, the University of California Los Angeles (UCLA) and local DRC partners will produce a national scale biomass map for the entire forest coverage of the Democratic Republic of Congo (DRC) along with feasibility assessments of different forest protection measures within a framework of a REDD+ model project. The « Carbon Map and Model (CO2M&M) » project will produce a national forest biomass map for the DRC, which will enable quantitative assessments of carbon stocks and emissions in the largest forest of the Congo Basin. This effort will support the national REDD (Reducing Emissions from Deforestation and Degradation) program in DRC, which plays a major role in sustainable development and poverty alleviation. This map will be developed from field data, complemented by airborne LiDAR (Light Detection and Ranging) and aerial photos, systematically sampled throughout the forests of the DRC and up-scaled to satellite images to accurately estimate carbon content in all forested areas. The second component of the project is to develop specific approaches for model REDD projects in key landscapes. This project represents the largest LiDAR-derived mapping effort in Africa, under unprecedented logistical constraints, which will provide one of the poorest nations in the world with the richest airborne and satellites derived datasets for analyzing forest structure, biomass and biodiversity.

  8. Dissolved Oxygen Dynamics in Backwaters of North America's Largest River Swamp

    Science.gov (United States)

    Bueche, S. M.; Xu, Y. J.; Reiman, J. H.

    2017-12-01

    The Atchafalaya River (AR) is the largest distributary of the Mississippi River flowing through south-central Louisiana, creating North America's largest river swamp basin - the Atchafalaya River Basin (ARB). Prior to human settlement, the AR's main channel was highly connected to this large wetland ecosystem. However, due to constructed levee systems and other human modifications, much of the ARB is now hydrologically disconnected from the AR's main channel except during high flow events. This lack of regular inputs of fresh, oxygenated water to these wetlands, paired with high levels of organic matter decomposition in wetlands, has caused low oxygen-deprived hypoxic conditions in the ARB's back waters. In addition, due to the incredibly nutrient-rich and warm nature of the ARB, microbial decomposition in backwater areas with limited flow often results in potentially stressful, if not lethal, levels of DO for organisms during and after flood pulses. This study aims to investigate dynamics of dissolved oxygen in backwaters of the Atchafalaya River Basin, intending to answer a crucial question about hydrological and water quality connectivity between the river's mainstem and its floodplain. Specifically, the study will 1) conduct field water quality measurements, 2) collect composite water samples for chemical analysis of nutrients and carbon, 3) investigate DO dynamics over different seasons for one year, and 4) determine the major factors that affect DO dynamics in this unique swamp ecosystem. The study is currently underway; therefore, in this presentation we will share the major findings gained in the past several months and discuss backwater effects on river chemistry.

  9. Is Kasei Valles (Mars) the largest volcanic channel in the solar system?

    Science.gov (United States)

    Leverington, David W.

    2018-02-01

    With a length of more than 2000 km and widths of up to several hundred kilometers, Kasei Valles is the largest outflow system on Mars. Superficially, the scabland-like character of Kasei Valles is evocative of terrestrial systems carved by catastrophic aqueous floods, and the system is widely interpreted as a product of outbursts from aquifers. However, as at other Martian outflow channels, clear examples of fluvial sedimentary deposits have proven difficult to identify here. Though Kasei Valles lacks several key properties expected of aqueous systems, its basic morphological and contextual properties are aligned with those of ancient volcanic channels on Venus, the Moon, Mercury, and Earth. There is abundant evidence that voluminous effusions of low-viscosity magmas occurred at the head of Kasei Valles, the channel system acted as a conduit for associated flows, and mare-style volcanic plains developed within its terminal basin. Combined mechanical and thermal incision rates of at least several meters per day are estimated to have been readily achieved at Kasei Valles by 20-m-deep magmas flowing with viscosities of 1 Pa s across low topographic slopes underlain by bedrock. If Kasei Valles formed through incision by magma, it would be the largest known volcanic channel in the solar system. The total volume of magma erupted at Kasei Valles is estimated here to have possibly reached or exceeded ∼5 × 106 km3, a volume comparable in magnitude to those that characterize individual Large Igneous Provinces on Earth. Development of other large outflow systems on Mars is expected to have similarly involved eruption of up to millions of cubic kilometers of magma.

  10. Drought and flood effects on macrobenthic communities in the estuary of Australia's largest river system

    Science.gov (United States)

    Dittmann, Sabine; Baring, Ryan; Baggalley, Stephanie; Cantin, Agnes; Earl, Jason; Gannon, Ruan; Keuning, Justine; Mayo, Angela; Navong, Nathavong; Nelson, Matt; Noble, Warwick; Ramsdale, Tanith

    2015-11-01

    Estuaries are prone to drought and flood events, which can vary in frequency and intensity depending on water management and climate change. We investigated effects of two different drought and flow situations, including a four year long drought (referred to as Millennium drought) and a major flood event, on the macrobenthic community in the estuary and coastal lagoon of the Murray Mouth and Coorong, where freshwater inflows are strictly regulated. The analysis is based on ten years of annual monitoring of benthic communities and environmental conditions in sediment and water. The objectives were to identify changes in diversity, abundance, biomass and distribution, as well as community shifts and environmental drivers for the respective responses. The Millennium drought led to decreased taxonomic richness, abundance and biomass of macrobenthos as hypersaline conditions developed and water levels dropped. More taxa were found under very high salinities than predicted from the Remane diagram. When a flood event broke the Millennium drought, recovery took longer than from a shorter drought followed by small flows. A flow index was developed to assess the biological response subject to the duration of the preceding drought and flow volumes. The index showed higher taxonomic richness, abundance and biomass at intermediate and more continuous flow conditions. Abundance increased quickly after flows were restored, but the benthic community was initially composed of small bodied organisms and biomass increased only after several years once larger organisms became more abundant. Individual densities and constancy of distribution dropped during the drought for almost all macrobenthic taxa, but recoveries after the flood were taxon specific. Distinct benthic communities were detected over time before and after the drought and flood events, and spatially, as the benthic community in the hypersaline Coorong was split off with a salinity threshold of 64 identified by LINKTREE

  11. Significant human impact on the flux and δ(34)S of sulfate from the largest river in North America.

    Science.gov (United States)

    Killingsworth, Bryan A; Bao, Huiming

    2015-04-21

    Riverine dissolved sulfate (SO4(2-)) flux and sulfur stable isotope composition (δ(34)S) yield information on the sources and processes affecting sulfur cycling on different spatial and temporal scales. However, because pristine preindustrial natural baselines of riverine SO4(2-) flux and δ(34)S cannot be directly measured, anthropogenic impact remains largely unconstrained. Here we quantify natural and anthropogenic SO4(2-) flux and δ(34)S for North America's largest river, the Mississippi, by means of an exhaustive source compilation and multiyear monitoring. Our data and analysis show that, since before industrialization to the present, Mississippi River SO4(2-) has increased in flux from 7.0 to 27.8 Tg SO4(2-) yr(-1), and in mean δ(34)S from -5.0‰, within 95% confidence limits of -14.8‰ to 4.1‰ (assuming normal distribution for mixing model input parameters), to -2.7 ± 1.6‰, reflecting an impressive footprint of bedrocks particular to this river basin and human activities. Our first-order modern Mississippi River sulfate partition is 25 ± 6% natural and 75% ± 6% anthropogenic sources. Furthermore, anthropogenic coal usage is implicated as the dominant source of modern Mississippi River sulfate, with an estimated 47 ± 5% and 13% of total Mississippi River sulfate due to coal mining and burning, respectively.

  12. BEHAVIOR OF THE TEN LARGEST BRAZILIAN BANKS DURING THE SUBPRIME CRISIS: AN ANALYSIS BASED ON FINANCIAL INDICATORS

    Directory of Open Access Journals (Sweden)

    Rosane Maria Pio da Silva

    2012-06-01

    Full Text Available The aim of this paper is to demonstrate the behavior of the ten largest Brazilian banks between June 2008 and September 2009, based on the analysis of financial indicators. Therefore, 16 three-monthly indices were calculated, extracted from financial statement information, which characterizes a documentary research. The indices were separated in five categories: liquidity, capital, profitability, income and market. The obtained results appointed that most financial institutions in the sample were able to manage their resources so as to gain conditions to maintain credit initially. Then, as from the first term of 2009, driven by public banks, they increased their credit operations. In addition, most banks revealed an anti-cyclical trend to encourage productive activities, preferably activities with higher liquidity levels, to the detriment of profitability, which reveals a more conservative attitude. Finally, it was verified that government initiatives, the Brazilian economic balance and the resources the banks offered helped to produce an environment to reactivate business activities during the most acute period of the subprime crisis.

  13. An analysis of audit committee effectiveness at the largest listed companies in South Africa from a CFO and audit committee perspective

    Directory of Open Access Journals (Sweden)

    Ben Marx

    2009-12-01

    regarding IT-related aspects. Value of research: The study provides valuable information on audit committee practices and the effectiveness of audit committees at the largest listed companies in South Africa. These findings can therefore serve as guidelines for best practice standards for audit committees at other companies and institutions. Conclusion: Audit committees at the largest listed companies in South Africa were found to be well established and according to the views of the CFOs and audit committee chairs to be functioning effectively. Further research regarding the subject field of audit committees should focus on the status and effective functioning thereof at smaller companies, unlisted entities, higher education institutions and public sector entities.

  14. Predicting residential indoor concentrations of nitrogen dioxide, fine particulate matter, and elemental carbon using questionnaire and geographic information system based data

    Science.gov (United States)

    Baxter, Lisa K.; Clougherty, Jane E.; Paciorek, Christopher J.; Wright, Rosalind J.; Levy, Jonathan I.

    Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households. As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3-4 day samples of nitrogen dioxide (NO 2) and fine particulate matter (PM 2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor. The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM 2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO 2 with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50 m buffer of a home and distance from a truck route as important contributors to indoor levels of NO 2 and EC, respectively. The Bayesian approach also highlighted the uncertanity in the

  15. Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

    Science.gov (United States)

    Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

    2008-01-01

    This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

  16. A Mine of Information.

    Science.gov (United States)

    Williams, Lisa B.

    1986-01-01

    Business researchers and marketers find certain databases useful for finding information on investments, competitors, products, and markets. Colleges can use these same databases to get background on corporate prospects. The largest data source available, DIALOG Information Services and some other databases are described. (MLW)

  17. Landscapes of thermal inequity: disproportionate exposure to urban heat in the three largest US cities

    Science.gov (United States)

    Mitchell, Bruce C.; Chakraborty, Jayajit

    2015-11-01

    Heat waves are the most significant cause of mortality in the US compared to other natural hazards. Prior studies have found increased heat exposure for individuals of lower socioeconomic status in several US cities, but few comparative analyses of the social distribution of urban heat have been conducted. To address this gap, our paper examines and compares the environmental justice consequences of urban heat risk in the three largest US cities: New York City, Los Angeles, and Chicago. Risk to urban heat is estimated on the basis of three characteristics of the urban thermal landscape: land surface temperature, vegetation abundance, and structural density of the built urban environment. These variables are combined to develop an urban heat risk index, which is then statistically compared with social vulnerability indicators representing socioeconomic status, age, disability, race/ethnicity, and linguistic isolation. The results indicate a consistent and significant statistical association between lower socioeconomic and minority status and greater urban heat risk, in all three cities. Our findings support a growing body of environmental justice literature that indicates the presence of a landscape of thermal inequity in US cities and underscores the need to conduct comparative analyses of social inequities in exposure to urban heat.

  18. KEPLER-1647B: THE LARGEST AND LONGEST-PERIOD KEPLER TRANSITING CIRCUMBINARY PLANET

    Energy Technology Data Exchange (ETDEWEB)

    Kostov, Veselin B. [NASA Goddard Space Flight Center, Mail Code 665, Greenbelt, MD 20771 (United States); Orosz, Jerome A.; Welsh, William F.; Short, Donald R. [Department of Astronomy, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182 (United States); Doyle, Laurance R. [SETI Institute, 189 Bernardo Avenue, Mountain View, CA 94043 (United States); Principia College, IMoP, One Maybeck Place, Elsah, IL 62028 (United States); Fabrycky, Daniel C. [Department of Astronomy and Astrophysics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); Haghighipour, Nader [Institute for Astronomy, University of Hawaii-Manoa, Honolulu, HI 96822 (United States); Quarles, Billy [Department of Physics and Physical Science, The University of Nebraska at Kearney, Kearney, NE 68849 (United States); Cochran, William D.; Endl, Michael [McDonald Observatory, The University of Texas as Austin, Austin, TX 78712-0259 (United States); Ford, Eric B. [Department of Astronomy and Astrophysics, The Pennsylvania State University, 428A Davey Lab, University Park, PA 16802 (United States); Gregorio, Joao [Atalaia Group and Crow-Observatory, Portalegre (Portugal); Hinse, Tobias C. [Korea Astronomy and Space Science Institute (KASI), Advanced Astronomy and Space Science Division, Daejeon 305-348 (Korea, Republic of); Isaacson, Howard [Department of Astronomy, University of California Berkeley, 501 Campbell Hall, Berkeley, CA 94720 (United States); Jenkins, Jon M. [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Jensen, Eric L. N. [Department of Physics and Astronomy, Swarthmore College, Swarthmore, PA 19081 (United States); Kane, Stephen [Department of Physics and Astronomy, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA 94132 (United States); Kull, Ilya, E-mail: veselin.b.kostov@nasa.gov [Department of Astronomy and Astrophysics, Tel Aviv University, 69978 Tel Aviv (Israel); and others

    2016-08-10

    We report the discovery of a new Kepler transiting circumbinary planet (CBP). This latest addition to the still-small family of CBPs defies the current trend of known short-period planets orbiting near the stability limit of binary stars. Unlike the previous discoveries, the planet revolving around the eclipsing binary system Kepler-1647 has a very long orbital period (∼1100 days) and was at conjunction only twice during the Kepler mission lifetime. Due to the singular configuration of the system, Kepler-1647b is not only the longest-period transiting CBP at the time of writing, but also one of the longest-period transiting planets. With a radius of 1.06 ± 0.01 R {sub Jup}, it is also the largest CBP to date. The planet produced three transits in the light curve of Kepler-1647 (one of them during an eclipse, creating a syzygy) and measurably perturbed the times of the stellar eclipses, allowing us to measure its mass, 1.52 ± 0.65 M {sub Jup}. The planet revolves around an 11-day period eclipsing binary consisting of two solar-mass stars on a slightly inclined, mildly eccentric ( e {sub bin} = 0.16), spin-synchronized orbit. Despite having an orbital period three times longer than Earth’s, Kepler-1647b is in the conservative habitable zone of the binary star throughout its orbit.

  19. Evidence for protection of targeted reef fish on the largest marine reserve in the Caribbean.

    Science.gov (United States)

    Pina-Amargós, Fabián; González-Sansón, Gaspar; Martín-Blanco, Félix; Valdivia, Abel

    2014-01-01

    Marine reserves can restore fish abundance and diversity in areas impacted by overfishing, but the effectiveness of reserves in developing countries where resources for enforcement are limited, have seldom been evaluated. Here we assess whether the establishment in 1996 of the largest marine reserve in the Caribbean, Gardens of the Queen in Cuba, has had a positive effect on the abundance of commercially valuable reef fish species in relation to neighboring unprotected areas. We surveyed 25 sites, including two reef habitats (reef crest and reef slope), inside and outside the marine reserve, on five different months, and over a one-and-a-half year period. Densities of the ten most frequent, highly targeted, and relatively large fish species showed a significant variability across the archipelago for both reef habitats that depended on the month of survey. These ten species showed a tendency towards higher abundance inside the reserve in both reef habitats for most months during the study. Average fish densities pooled by protection level, however, showed that five out of these ten species were at least two-fold significantly higher inside than outside the reserve at one or both reef habitats. Supporting evidence from previously published studies in the area indicates that habitat complexity and major benthic communities were similar inside and outside the reserve, while fishing pressure appeared to be homogeneous across the archipelago before reserve establishment. Although poaching may occur within the reserve, especially at the boundaries, effective protection from fishing was the most plausible explanation for the patterns observed.

  20. Investigation of science faculty with education specialties within the largest university system in the United States.

    Science.gov (United States)

    Bush, Seth D; Pelaez, Nancy J; Rudd, James A; Stevens, Michael T; Tanner, Kimberly D; Williams, Kathy S

    2011-01-01

    Efforts to improve science education include university science departments hiring Science Faculty with Education Specialties (SFES), scientists who take on specialized roles in science education within their discipline. Although these positions have existed for decades and may be growing more common, few reports have investigated the SFES approach to improving science education. We present comprehensive data on the SFES in the California State University (CSU) system, the largest university system in the United States. We found that CSU SFES were engaged in three key arenas including K-12 science education, undergraduate science education, and discipline-based science education research. As such, CSU SFES appeared to be well-positioned to have an impact on science education from within science departments. However, there appeared to be a lack of clarity and agreement about the purpose of these SFES positions. In addition, formal training in science education among CSU SFES was limited. Although over 75% of CSU SFES were fulfilled by their teaching, scholarship, and service, our results revealed that almost 40% of CSU SFES were seriously considering leaving their positions. Our data suggest that science departments would likely benefit from explicit discussions about the role of SFES and strategies for supporting their professional activities.

  1. Sources and distribution of microplastics in China's largest inland lake - Qinghai Lake.

    Science.gov (United States)

    Xiong, Xiong; Zhang, Kai; Chen, Xianchuan; Shi, Huahong; Luo, Ze; Wu, Chenxi

    2018-04-01

    Microplastic pollution was studied in China's largest inland lake - Qinghai Lake in this work. Microplastics were detected with abundance varies from 0.05 × 10 5 to 7.58 × 10 5 items km -2 in the lake surface water, 0.03 × 10 5 to 0.31 × 10 5 items km -2 in the inflowing rivers, 50 to 1292 items m -2 in the lakeshore sediment, and 2 to 15 items per individual in the fish samples, respectively. Small microplastics (0.1-0.5 mm) dominated in the lake surface water while large microplastics (1-5 mm) are more abundant in the river samples. Microplastics were predominantly in sheet and fiber shapes in the lake and river water samples but were more diverse in the lakeshore sediment samples. Polymer types of microplastics were mainly polyethylene (PE) and polypropylene (PP) as identified using Raman Spectroscopy. Spatially, microplastic abundance was the highest in the central part of the lake, likely due to the transport of lake current. Based on the higher abundance of microplastics near the tourist access points, plastic wastes from tourism are considered as an important source of microplastics in Qinghai Lake. As an important area for wildlife conservation, better waste management practice should be implemented, and waste disposal and recycling infrastructures should be improved for the protection of Qinghai Lake. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. The largest human cognitive performance dataset reveals insights into the effects of lifestyle factors and aging

    Directory of Open Access Journals (Sweden)

    Daniel A Sternberg

    2013-06-01

    Full Text Available Making new breakthroughs in understanding the processes underlying human cognition may depend on the availability of very large datasets that have not historically existed in psychology and neuroscience. Lumosity is a web-based cognitive training platform that has grown to include over 600 million cognitive training task results from over 35 million individuals, comprising the largest existing dataset of human cognitive performance. As part of the Human Cognition Project, Lumosity’s collaborative research program to understand the human mind, Lumos Labs researchers and external research collaborators have begun to explore this dataset in order uncover novel insights about the correlates of cognitive performance. This paper presents two preliminary demonstrations of some of the kinds of questions that can be examined with the dataset. The first example focuses on replicating known findings relating lifestyle factors to baseline cognitive performance in a demographically diverse, healthy population at a much larger scale than has previously been available. The second example examines a question that would likely be very difficult to study in laboratory-based and existing online experimental research approaches: specifically, how learning ability for different types of cognitive tasks changes with age. We hope that these examples will provoke the imagination of researchers who are interested in collaborating to answer fundamental questions about human cognitive performance.

  3. Reconstructing the population history of the largest tribe of India: the Dravidian speaking Gond.

    Science.gov (United States)

    Chaubey, Gyaneshwer; Tamang, Rakesh; Pennarun, Erwan; Dubey, Pavan; Rai, Niraj; Upadhyay, Rakesh Kumar; Meena, Rajendra Prasad; Patel, Jayanti R; van Driem, George; Thangaraj, Kumarasamy; Metspalu, Mait; Villems, Richard

    2017-04-01

    The Gond comprise the largest tribal group of India with a population exceeding 12 million. Linguistically, the Gond belong to the Gondi-Manda subgroup of the South Central branch of the Dravidian language family. Ethnographers, anthropologists and linguists entertain mutually incompatible hypotheses on their origin. Genetic studies of these people have thus far suffered from the low resolution of the genetic data or the limited number of samples. Therefore, to gain a more comprehensive view on ancient ancestry and genetic affinities of the Gond with the neighbouring populations speaking Indo-European, Dravidian and Austroasiatic languages, we have studied four geographically distinct groups of Gond using high-resolution data. All the Gond groups share a common ancestry with a certain degree of isolation and differentiation. Our allele frequency and haplotype-based analyses reveal that the Gond share substantial genetic ancestry with the Indian Austroasiatic (ie, Munda) groups, rather than with the other Dravidian groups to whom they are most closely related linguistically.

  4. A study on the regionalization of tornadogenesis for the domestic largest scale of tornado

    International Nuclear Information System (INIS)

    Sugimoto, Soichiro; Nohara, Daisuke; Hirakuchi, Hiromaru

    2014-01-01

    A new regulatory guide has been issued by the Nuclear Regulation Authority of Japan since the last year. According to this guide, electric power companies have to assess the influence of tornadoes on their nuclear power plants for operation. The purpose of this study is to evaluate the likelihood of the occurrence of F3 tornadoes, which are the largest encountered in Japan, and to consider the possibility of the regionalization of the maximum wind speed. Then, mesoscale analysis with a numerical meteorological model and re-analysis data is performed along with synoptic scale analysis. Especially, tornado parameters such as SReH (Storm Relative Helicity) and CAPE (Convective Available Potential Energy) are used for evaluating the potential tornadogenesis of F3 tornado. Both analyses indicate that favorable meteorological condition tends to occur in the coastal zones in the Pacific side west of Ibaraki and around Kyushu island. The frequency in these zones is different from the one in the other area in the order of 1 or 2, which is large enough for regionalization. (author)

  5. Vascular access in lipoprotein apheresis: a retrospective analysis from the UK's largest lipoprotein apheresis centre.

    Science.gov (United States)

    Doherty, Daniel J; Pottle, Alison; Malietzis, George; Hakim, Nadey; Barbir, Mahmoud; Crane, Jeremy S

    2018-01-01

    Lipoprotein apheresis (LA) has proven to be an effective, safe and life-saving therapy. Vascular access is needed to facilitate this treatment but has recognised complications. Despite consistency in treatment indication and duration there are no guidelines in place. The aim of this study is to characterise vascular access practice at the UK's largest LA centre and forward suggestions for future approaches. A retrospective analysis of vascular access strategies was undertaken in all patients who received LA treatment in the low-density lipoprotein (LDL) Apheresis Unit at Harefield Hospital (Middlesex, UK) from November 2000 to March 2016. Fifty-three former and current patients underwent 4260 LA treatments. Peripheral vein cannulation represented 79% of initial vascular access strategies with arteriovenous (AV) fistula use accounting for 15%. Last used method of vascular access was peripheral vein cannulation in 57% versus AV fistula in 32%. Total AV fistula failure rate was 37%. Peripheral vein cannulation remains the most common method to facilitate LA. Practice trends indicate a move towards AV fistula creation; the favoured approach receiving support from the expert body in this area. AV fistula failure rate is high and of great concern, therefore we suggest the implementation of upper limb ultrasound vascular mapping in all patients who meet treatment eligibility criteria. We encourage close ties between apheresis units and specialist surgical centres to facilitate patient counselling and monitoring. Further prospective data regarding fistula failure is needed in this expanding treatment field.

  6. Sistema Faro, Isla de Mona, Puerto Rico: speleogenesis of the worlds largest flank margin cave

    International Nuclear Information System (INIS)

    Lace, M. J.; Kambesis, P. N.; Mylroie, J. E.

    2016-01-01

    Isla de Mona, a small, uplifted carbonate plateau jutting out of the waters of the Mona Passage, is an incredibly fragile and densely karstic environment. Expedition work was conducted by the Isla de Mona Project in cooperation with the Departamento Recursos Naturales y Ambientales de Puerto Rico (DRNA), including contributions from many researchers and cavers volunteering from across the U.S and Puerto Rico in the course of 12 separate expeditions, spanning a 14 year period (1998 to 2013). Over 200 caves have been documented on the island to date, the majority of this inventory is composed of flank margin caves but also includes sea caves, pit caves and talus caves. The most extensive example of cave development on the island is Sistema Faro - a sprawling maze-like series of chambers formed within the eastern point of the island with over 40 cliffside entrances overlooking the Caribbean Sea. Detailed cartography and analysis of the geomorphology and development of the Sistema Faro has helped form a complex model of carbonate island cave development as a function of tectonic uplift, lithology, sea level changes, karst hydrogeology and cliff retreat. This communication examines the roles these controls have played in the genesis of the world's largest flank margin cave. (Author)

  7. Stand Up for the Burrup: Saving the Largest Aboriginal Rock Art Precinct in Australia

    Directory of Open Access Journals (Sweden)

    Jenny Gregory

    2009-12-01

    Full Text Available The Dampier Rock Art Precinct contains the largest and most ancient collection of Aboriginal rock art in Australia. The cultural landscape created by generations of Aboriginal people includes images of long-extinct fauna and demonstrates the response of peoples to a changing climate over thousands of years as well as the continuity of lived experience. Despite Australian national heritage listing in 2007, this cultural landscape continues to be threatened by industrial development. Rock art on the eastern side of the archipelago, on the Burrup Peninsula, was relocated following the discovery of adjacent off-shore gas reserves so that a major gas plant could be constructed. Work has now begun on the construction of a second major gas plant nearby. This article describes the rock art of the Dampier Archipelago and the troubled history of European-Aboriginal contact history, before examining the impact of industry on the region and its environment. The destruction of Aboriginal rock art to meet the needs of industry is an example of continuing indifference to Aboriginal culture. While the complex struggle to protect the cultural landscape of the Burrup, in particular, involving Indigenous people, archaeologists, historians, state and federal politicians, government bureaucrats and multi-national companies, eventually led to national heritage listing, it is not clear that the battle to save the Burrup has been won.

  8. Percolation under noise: Detecting explosive percolation using the second-largest component

    Science.gov (United States)

    Viles, Wes; Ginestet, Cedric E.; Tang, Ariana; Kramer, Mark A.; Kolaczyk, Eric D.

    2016-05-01

    We consider the problem of distinguishing between different rates of percolation under noise. A statistical model of percolation is constructed allowing for the birth and death of edges as well as the presence of noise in the observations. This graph-valued stochastic process is composed of a latent and an observed nonstationary process, where the observed graph process is corrupted by type-I and type-II errors. This produces a hidden Markov graph model. We show that for certain choices of parameters controlling the noise, the classical (Erdős-Rényi) percolation is visually indistinguishable from a more rapid form of percolation. In this setting, we compare two different criteria for discriminating between these two percolation models, based on the interquartile range (IQR) of the first component's size, and on the maximal size of the second-largest component. We show through data simulations that this second criterion outperforms the IQR of the first component's size, in terms of discriminatory power. The maximal size of the second component therefore provides a useful statistic for distinguishing between different rates of percolation, under physically motivated conditions for the birth and death of edges, and under noise. The potential application of the proposed criteria for the detection of clinically relevant percolation in the context of applied neuroscience is also discussed.

  9. North Andean origin and diversification of the largest ithomiine butterfly genus

    Science.gov (United States)

    Lisa De-Silva, Donna; Mota, Luísa L.; Chazot, Nicolas; Mallarino, Ricardo; Silva-Brandão, Karina L.; Piñerez, Luz Miryam Gómez; Freitas, André V.L.; Lamas, Gerardo; Joron, Mathieu; Mallet, James; Giraldo, Carlos E.; Uribe, Sandra; Särkinen, Tiina; Knapp, Sandra; Jiggins, Chris D.; Willmott, Keith R.; Elias, Marianne

    2017-01-01

    The Neotropics harbour the most diverse flora and fauna on Earth. The Andes are a major centre of diversification and source of diversity for adjacent areas in plants and vertebrates, but studies on insects remain scarce, even though they constitute the largest fraction of terrestrial biodiversity. Here, we combine molecular and morphological characters to generate a dated phylogeny of the butterfly genus Pteronymia (Nymphalidae: Danainae), which we use to infer spatial, elevational and temporal diversification patterns. We first propose six taxonomic changes that raise the generic species total to 53, making Pteronymia the most diverse genus of the tribe Ithomiini. Our biogeographic reconstruction shows that Pteronymia originated in the Northern Andes, where it diversified extensively. Some lineages colonized lowlands and adjacent montane areas, but diversification in those areas remained scarce. The recent colonization of lowland areas was reflected by an increase in the rate of evolution of species’ elevational ranges towards present. By contrast, speciation rate decelerated with time, with no extinction. The geological history of the Andes and adjacent regions have likely contributed to Pteronymia diversification by providing compartmentalized habitats and an array of biotic and abiotic conditions, and by limiting dispersal between some areas while promoting interchange across others. PMID:28387233

  10. Level of patient and operator dose in the largest cardiac centre in Greece

    International Nuclear Information System (INIS)

    Tsapaki, V.; Patsilinakos, S.; Voudris, V.; Magginas, A.; Pavlidis, S.; Maounis, T.; Theodorakis, G.; Koutelou, M.; Vrantza, T.; Nearchou, M.; Nikolaki, N.; Kollaros, N.; Kyrozi, E.; Kottou, S.; Karaiskos, P.; Neofotistou, E.; Cokkinos, D.

    2008-01-01

    The objective of this study was to investigate the patient and staff doses in the most frequent interventional cardiology (IC) procedures performed in Onassio, the largest Cardiac Centre in Greece. Data were collected from three digital X-ray systems for 212 coronary angiographies, 203 percutaneous transluminal coronary angio-plasties (PTCA) and 134 various electrophysiological studies. Patient skin dose was measured using suitably calibrated slow radiotherapy films and cardiologist dose using suitably calibrated thermoluminescent dosemeters placed on left arm, hand and foot. Patient median dose area product (DAP) (all examinations) ranged between 6.7 and 83.5 Gy cm 2 . Patient median skin dose in PTCA was 799 mGy (320-1660 mGy) and in RF ablation 160 mGy (35-1920 mGy). Median arm, hand and foot dose to the cardiologist were 12.6, 27 and 13 μSv, respectively, per procedure. The great range of radiation doses received by both patients and operators confirms the need for continuous monitoring of all IC techniques. (authors)

  11. DISCOVERY OF THE LARGEST KNOWN LENSED IMAGES FORMED BY A CRITICALLY CONVERGENT LENSING CLUSTER

    International Nuclear Information System (INIS)

    Zitrin, Adi; Broadhurst, Tom

    2009-01-01

    We identify the largest known lensed images of a single spiral galaxy, lying close to the center of the distant cluster MACS J1149.5+2223 (z = 0.544). These images cover a total area of ≅150 mbox '' and are magnified ≅200 times. Unusually, there is very little image distortion, implying that the central mass distribution is almost uniform over a wide area (r ≅ 200 kpc) with a surface density equal to the critical density for lensing, corresponding to maximal lens magnification. Many fainter multiply lensed galaxies are also uncovered by our model, outlining a very large tangential critical curve, of radius r ≅ 170 kpc, posing a potential challenge for the standard LCDM cosmology. Because of the uniform central mass distribution, a particularly clean measurement of the mass of the brightest cluster galaxy is possible here, for which we infer stars contribute most of the mass within a limiting radius of ≅30 kpc, with a mass-to-light ratio of M/L B ≅ 4.5(M/L) sun . This cluster with its uniform and central mass distribution acts analogously to a regular magnifying glass, converging light without distorting the images, resulting in the most powerful lens yet discovered for accessing the faint high-z universe.

  12. Epidemiological study of hepatitis A, B and C in the largest Afro-Brazilian isolated community.

    Science.gov (United States)

    Matos, Márcia A D; Reis, Nádia Rúbia S; Kozlowski, Aline G; Teles, Sheila A; Motta-Castro, Ana Rita C; Mello, Francisco C A; Gomes, Selma A; Martins, Regina M B

    2009-09-01

    This study was conducted to estimate the prevalence and molecular epidemiological features of viral hepatitis A, B and C in the Kalunga population, which represents the largest Afro-Brazilian isolated community. Among 878 individuals studied, the overall prevalence of anti-hepatitis A virus antibodies was 80.9%, with a significant rise from 44.8% to near 100% between the first and fourth decade of life. Rates for hepatitis B surface antigen (HBsAg) and antibody to hepatitis B core antigen (anti-HBc) of 1.8% and 35.4%, respectively, were found. Increasing age, male gender, illiteracy and history of multiple sexual partners were associated with hepatitis B virus (HBV) infection. An occult HBV infection rate of 1.7% (5/295) was found among anti-HBc-positive individuals. HBV genotype A (subtype Aa) was dominant in this community. Only 5/878 individuals (0.6%) were positive for anti-hepatitis C virus (HCV). HCV RNA was detected in three of them, who were infected with genotype 1 (subtype 1a). These findings point out high, intermediate and low endemicity for hepatitis A, B and C, respectively, in the Kalunga community in Brazil. Circulation of HBV genotype A (subtype Aa) in this Afro-Brazilian isolated community indicates the introduction of this virus during the slave trade from Africa to Brazil.

  13. Bubble nucleation in simple and molecular liquids via the largest spherical cavity method

    International Nuclear Information System (INIS)

    Gonzalez, Miguel A.; Abascal, José L. F.; Valeriani, Chantal; Bresme, Fernando

    2015-01-01

    In this work, we propose a methodology to compute bubble nucleation free energy barriers using trajectories generated via molecular dynamics simulations. We follow the bubble nucleation process by means of a local order parameter, defined by the volume of the largest spherical cavity (LSC) formed in the nucleating trajectories. This order parameter simplifies considerably the monitoring of the nucleation events, as compared with the previous approaches which require ad hoc criteria to classify the atoms and molecules as liquid or vapor. The combination of the LSC and the mean first passage time technique can then be used to obtain the free energy curves. Upon computation of the cavity distribution function the nucleation rate and free-energy barrier can then be computed. We test our method against recent computations of bubble nucleation in simple liquids and water at negative pressures. We obtain free-energy barriers in good agreement with the previous works. The LSC method provides a versatile and computationally efficient route to estimate the volume of critical bubbles the nucleation rate and to compute bubble nucleation free-energies in both simple and molecular liquids

  14. Rise and Fall of one of World's largest deltas; the Mekong delta in Vietnam

    Science.gov (United States)

    Minderhoud, P. S. J.; Eslami Arab, S.; Pham, H. V.; Erkens, G.; van der Vegt, M.; Oude Essink, G.; Stouthamer, E.; Hoekstra, P.

    2017-12-01

    The Mekong delta is the third's largest delta in the world. It is home to almost 20 million people and an important region for the food security in South East Asia. As most deltas, the Mekong delta is the dynamic result of a balance of sediment supply, sea level rise and subsidence, hosting a system of fresh and salt water dynamics. Ongoing urbanization, industrialization and intensification of agricultural practices in the delta, during the past decades, resulted in growing domestic, agricultural and industrial demands, and have led to a dramatic increase of fresh water use. Since the year 2000, the amount of fresh groundwater extracted from the subsurface increased by 500%. This accelerated delta subsidence as the groundwater system compacts, with current sinking rates exceeding global sea level rise up to an order of magnitude. These high sinking rates have greatly altered the sediment budget of the delta and, with over 50% of the Mekong delta surface elevated less than 1 meter above sea level, greatly increase vulnerability to flooding and storm surges and ultimately, permanent inundation. Furthermore, as the increasingly larger extractions rapidly reduce the fresh groundwater reserves, groundwater salinization subsequently increases. On top of that, dry season low-flows by the Mekong river cause record salt water intrusion in the delta's estuarine system, creating major problems for rice irrigation. We present the work of three years research by the Dutch-Vietnamese `Rise and Fall' project on land subsidence and salinization in both groundwater and surface water in the Vietnamese Mekong delta.

  15. Corporate social responsibility of the 100 largest Indian companies – an analysis of website communication

    Directory of Open Access Journals (Sweden)

    Avinash Mulky

    2013-01-01

    Full Text Available Corporate social responsibility has become an important concept in the business world in recent decades. CSR is important in all countries but is particularly relevant in emerging markets where the levels of human development are not high. The United Nations Development Programme has created the Human Development Index (HDI to measure the human development in countries. The present study analyzes the CSR communication on the websites of the 100 largest Indian companies. The objective was to examine the reported CSR activities and determine whether the activities address the dimensions and indicators of the HDI. The study uses content analysis to classify the CSR activities into categories corresponding to HDI parameters. The findings indicate that about two thirds of the companies are using their websites to communicate CSR. Of the companies which reported CSR, about eighty percent report support for primary education and about seventy percent undertake livelihood support activities. The level of corporate involvement in the health dimension of human development is quite low. Reduction of infant and maternal mortality does not get much corporate attention. This study will add to the literature on CSR in emerging markets and will be useful for firms in India and other emerging markets that are planning CSR activities aimed at human development parameters.

  16. Natural radionuclides in soil profiles surrounding the largest coal-fired power plant in Serbia

    Directory of Open Access Journals (Sweden)

    Tanić Milan N.

    2016-01-01

    Full Text Available This study evaluates the influence of the largest Serbian coal-fired power plant on radionuclide concentrations in soil profiles up to 50 cm in depth. Thirty soil profiles were sampled from the plant surroundings (up to 10 km distance and analyzed using standard methods for soil physicochemical properties and gamma ray spectrometry for specific activities of natural radionuclides (40K, 226Ra and 232Th. Spatial and vertical distribution of radionuclides was determined and analyzed to show the relations between the specific activities in the soil and soil properties and the most influential factors of natural radionuclide variability were identified. The radiological indices for surface soil were calculated and radiological risk assessment was performed. The measured specific activities were similar to values of background levels for Serbia. The sampling depth did not show any significant influence on specific activities of natural radionuclides. The strongest predictor of specific activities of the investigated radionuclides was soil granulometry. All parameters of radiological risk assessment were below the recommended values and adopted limits. It appears that the coal-fired power plant does not have a significant impact on the spatial and vertical distribution of natural radionuclides in the area of interest, but technologically enhanced natural radioactivity as a consequence of the plant operations was identified within the first 1.5 km from the power plant. [Projekat Ministarstva nauke Republike Srbije br. III43009 i br. III41005

  17. Largest known Mesozoic multituberculate from Eurasia and implications for multituberculate evolution and biology.

    Science.gov (United States)

    Xu, Li; Zhang, Xingliao; Pu, Hanyong; Jia, Songhai; Zhang, Jiming; Lü, Junchang; Meng, Jin

    2015-10-22

    A new multituberculate, Yubaartar zhongyuanensis gen. and sp. nov., is reported from the Upper Cretaceous of Luanchuan County, Henan Province, China. The holotype of the new taxon is a partial skeleton with nearly complete cranium and associated lower jaws with in situ dentitions. The new species is the southern-most record of a Late Cretaceous multituberculate from outside of the Mongolian Plateau in Asia and represents the largest known Mesozoic multituberculate from Eurasia. The new specimen displays some intriguing features previously unknown in multituberculates, such as the first evidence of replacement of the ultimate upper premolar and a unique paleopathological case in Mesozoic mammals in which the animal with a severely broken right tibia could heal and survive in natural condition. The phylogenetic analysis based on craniodental characters places Yubaartar as the immediate outgroup of Taeniolabidoidea, a group consisting of a North American clade and an Asian clade. This relationship indicates at least a faunal interchange of multituberculates before the K-Pg transition. The new evidence further supports the hypothesis that disparity in dental complexity, which relates to animal diets, increased with generic richness and disparity in body size, and that an adaptive shift towards increased herbivory across the K-Pg transitional interval.

  18. Complex biogeographic scenarios revealed in the diversification of the largest woodpecker radiation in the New World.

    Science.gov (United States)

    Navarro-Sigüenza, Adolfo G; Vázquez-Miranda, Hernán; Hernández-Alonso, Germán; García-Trejo, Erick A; Sánchez-González, Luis A

    2017-07-01

    Phylogenetic relationships and patterns of evolution within Melanerpes, one of the most diverse groups of New World woodpeckers (22-23 lineages), have been complicated due to complex plumages and morphological adaptations. In an attempt to resolve these issues, we obtained sequence data from four nuclear introns and two mitochondrial protein-coding genes for 22 of the 24 currently recognized species in the genus. We performed phylogenetic analyses involving Maximum Likelihood and Bayesian Inference, species-tree divergence dating, and biogeographic reconstructions. Tree topologies from the concatenated and species-tree analyses of the mtDNA and nDNA showed broadly similar patterns, with three relatively well-supported groups apparent: (a) the Sphyrapicus clade (four species); (b) the typical Melanerpes clade, which includes temperate and subtropical dry forest black-backed species; and (c) the mostly barred-backed species, here referred to as the "Centurus" clade. The phylogenetic position of Melanerpes superciliaris regarding the rest of Melanerpes is ambiguous as it is recovered as sister to the rest of Melanerpes or as sister to a group including Sphyrapicus+Melanerpes. Our species tree estimations recovered the same well-delimited highly-supported clades. Geographic range evolution (estimated in BioGeoBEARS) was best explained by a DIVALIKE+j model, which includes vicariance, founder effect speciation, and anagenetic dispersal (range expansion) as important processes involved in the diversification of the largest radiation of woodpeckers in the New World. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Psyche's UV Reflectance Spectra: Exploring the origins of the largest exposed-core metallic asteroid

    Science.gov (United States)

    Becker, Tracy

    2016-10-01

    (16) Psyche is the largest of the M-class asteroids, and is presumed to be the exposed core of a differentiated asteroid stripped of its mantle through hit-and-run collisions. However, other origins for Psyche have been proposed, including that it formed from a highly-reduced, metal rich material in the inner solar system or that its surface is olivine that has been space weathered. If (16) Psyche is an exposed core, then studying its properties enhances our understanding of the cores of all terrestrial planets, including the Earth's. If it accreted in the inner part of the solar system and was later injected into the asteroid belt, then Psyche sheds light on the conditions and subsequent evolution of the early solar system. Lastly, if Psyche is weathered olivine, then olivine may be more abundant in the solar system than currently measured, rectifying the so-called Great Dunite Shortage. Our program to obtain high-resolution UV spectra of Psyche with the COS G140L mode and the STIS NUV MAMA G230L mode to measure spectral signatures between 90 - 315 nm is designed to distinguish between the 3 hypothesized cases. These observations will enable identification of absorption bands, especially Fe-O charge transfer bands and will be sensitive to spectral blueing that occurs at UV wavelengths for space-weathered objects. When combined, the presence of these UV features, or not, provides a novel test of Psyche formation theories.

  20. Carbon footprint of premium quality export bananas: case study in Ecuador, the world's largest exporter.

    Science.gov (United States)

    Iriarte, Alfredo; Almeida, Maria Gabriela; Villalobos, Pablo

    2014-02-15

    Nowadays, the new international market demands challenge the food producing countries to include the measurement of the environmental impact generated along the production process for their products. In order to comply with the environmentally responsible market requests the measurement of the greenhouse gas emissions of Ecuadorian agricultural goods has been promoted employing the carbon footprint concept. Ecuador is the largest exporter of bananas in the world. Within this context, this study is a first assessment of the carbon footprint of the Ecuadorian premium export banana (Musa AAA) using a considerable amount of field data. The system boundaries considered from agricultural production to delivery in a European destination port. The data collected over three years permitted identifying the hot spot stages. For the calculation, the CCaLC V3.0 software developed by the University of Manchester is used. The carbon footprint of the Ecuadorian export banana ranged from 0.45 to 1.04 kg CO2-equivalent/kg banana depending on the international overseas transport employed. The principal contributors to the carbon footprint are the on farm production and overseas transport stages. Mitigation and reduction strategies were suggested for the main emission sources in order to achieve sustainable banana production. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Characterization of the largest relic Eurasian wild grapevine reservoir in Southern Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Arroyo-García, R.; Cantos, M.; Lara, M.; López, M.A.; Gallardo, A.; Ocete, C.A.; Pérez, A.; Bánáti, B.; García, J.L.; Ocete, R.

    2016-11-01

    Wild grapevine is becoming a threatened species in the Iberian Peninsula due to human impacts. The aim of this work was to carry out a holistic study for six years of the largest wild grapevine population found up to date in SW Iberian Peninsula. This population has 115 vines. Ampelographic and soil characteristics have been studied. Evaluation of its environment has also been studied by describing the main parasitic species and natural enemies of pests. The ability of this plant material for its micropropagation and storage in slow-growth conditions has been tested. Microvinification resulted in a wine with good acidity and medium color intensity, two interesting characteristics under a warm climatology. Finally, the identification of private alleles in this wild population, absent in other locations from the Northern and Southern Iberian territories, is a very valuable feature and confirms the importance of establishing conservation programs. The population here studied is genetically unique and potentially useful for commercial rootstocks and cultivars breeding that would improve viticulture and enology. (Author)

  2. State-owned companies dominate list of largest non-U.S. producers

    International Nuclear Information System (INIS)

    Beck, R.J.; Williamson, M.

    1994-01-01

    Because state-owned oil and gas companies dominate Oil and Gas Journal's list of largest non-US producers, data aren't fully comparable with those of the OGJ300. Many state companies report only production and reserves, with little or no financial data. Companies on the OGJ100, therefore, cannot be ranked by assets or revenues. Instead, they are listed by regions, based on location of corporate headquarters. There was no change in makeup of the top 20 holders of crude oil reserves. These companies' reserves totaled 872.3 billion bbl in 1993. The top 20 non-US companies now control 87.3 % of total world crude oil reserves, according to OGJ estimates. This is up marginally from 87.2 % of total world oil reserves in 1992. The top 20 had 87.7 % of total world reserves in 1991 and 85.5 % in 1990. The table lists company name, total assets, revenues, net income, capital and exploratory expenditures, worldwide oil production, gas production, oil and gas reserves worldwide

  3. Estimation of the largest enterprises’ impact on the socio-economic development of territories

    Directory of Open Access Journals (Sweden)

    Ekaterina Dmitrievna Razgulina

    2014-07-01

    Full Text Available The key basic trends of modern society development are associated with the transfer of some government functions to big business. Thus, scientific and public circles argue about social partnership between government, business and employees and offer different variants of the corporate social responsibility concept. The article presents the experience to assess social responsibility of business on the example of the largest chemical enterprises located in the Vologda and Novgorod oblasts. The evaluation results have revealed a number of problems hindering the formation of socially responsible behavior of enterprises, particularly the lack of standardized reporting on corporate social responsibility; provision of formal corporate social responsibility report; business’ non-system participation in social and economic development of territories. According to the authors, the development of a special model to regulate participants’ mutual relations can increase social responsibility of Russian business. Unified interests and resources of business and government promote the development of an agreed strategy in the field of regional social-economic development

  4. Evaluation of several priority pollutants in zebra mussels (Dreissena polymorpha) in the largest Italian subalpine lakes

    International Nuclear Information System (INIS)

    Riva, Consuelo; Binelli, Andrea; Provini, Alfredo

    2008-01-01

    Zebra mussel (Dreissena polymorpha) has been used for the biomonitoring of several POPs (PCBs, DDTs, HCB and HCHs) in the largest Italian subalpine great lakes (Lake Maggiore, Garda, Como, Iseo and Lugano). Samplings were carried out in April 2003 at 15 locations selected according to industrial and anthropic levels of lakes. Results have pointed out high DDT levels in D. polymorpha specimens from Lake Maggiore (700-1400 ng/g lipids, 5-9 times higher than those measured in mussels of other Italian lakes), due to a contamination from a chemical plant located on one of the main lake inlet that occurred in 1996. On the contrary, PCB levels (400-2509 ng/g lipids) highlighted an overall pollution, with some sporadic peaks of contamination. Data showed a moderate increase trend compared to those found in a previous monitoring campaign carried out in 1996. Future monitoring is needed in order to confirm this tendency. - Significant levels of DDTs and PCBs are still present in the Italian subalpine great lakes

  5. Evaluation of several priority pollutants in zebra mussels (Dreissena polymorpha) in the largest Italian subalpine lakes

    Energy Technology Data Exchange (ETDEWEB)

    Riva, Consuelo [Department of Biology, Ecology Section, University of Milan, Via Celoria 26, 20133 Milan (Italy)], E-mail: consuelo.riva@unimi.it; Binelli, Andrea; Provini, Alfredo [Department of Biology, Ecology Section, University of Milan, Via Celoria 26, 20133 Milan (Italy)

    2008-02-15

    Zebra mussel (Dreissena polymorpha) has been used for the biomonitoring of several POPs (PCBs, DDTs, HCB and HCHs) in the largest Italian subalpine great lakes (Lake Maggiore, Garda, Como, Iseo and Lugano). Samplings were carried out in April 2003 at 15 locations selected according to industrial and anthropic levels of lakes. Results have pointed out high DDT levels in D. polymorpha specimens from Lake Maggiore (700-1400 ng/g lipids, 5-9 times higher than those measured in mussels of other Italian lakes), due to a contamination from a chemical plant located on one of the main lake inlet that occurred in 1996. On the contrary, PCB levels (400-2509 ng/g lipids) highlighted an overall pollution, with some sporadic peaks of contamination. Data showed a moderate increase trend compared to those found in a previous monitoring campaign carried out in 1996. Future monitoring is needed in order to confirm this tendency. - Significant levels of DDTs and PCBs are still present in the Italian subalpine great lakes.

  6. Monitoring coastal pollution associated with the largest oil refinery complex of Venezuela

    Directory of Open Access Journals (Sweden)

    Aldo Croquer

    2016-06-01

    Full Text Available This study evaluated pollution levels in water and sediments of Península de Paraguaná and related these levels with benthic macrofauna along a coastal area where the largest Venezuelan oil refineries have operated over the past 60 years. For this, the concentration of heavy metals, of hydrocarbon compounds and the community structure of the macrobenthos were examined at 20 sites distributed along 40 km of coastline for six consecutive years, which included windy and calm seasons. The spatial variability of organic and inorganic compounds showed considerably high coastal pollution along the study area, across both years and seasons. The southern sites, closest to the refineries, had consistently higher concentrations of heavy metals and organic compounds in water and sediments when compared to those in the north. The benthic community was dominated by polychaetes at all sites, seasons and years, and their abundance and distribution were significantly correlated with physical and chemical characteristics of the sediments. Sites close to the oil refineries were consistently dominated by families known to tolerate xenobiotics, such as Capitellidae and Spionidae. The results from this study highlight the importance of continuing long-term environmental monitoring programs to assess the impact of effluent discharge and spill events from the oil refineries that operate in the western coast of Paraguaná, Venezuela.

  7. Bedrock Canyons Carved by the Largest Known Floods on Earth and Mars

    Science.gov (United States)

    Lamb, M. P.; Lapôtre, M. G. A.; Larsen, I. J.; Williams, R. M. E.

    2017-12-01

    The surface of Earth is a dynamic and permeable interface where the rocky crust is sculpted by ice, wind and water resulting in spectacular mountain ranges, vast depositional basins and environments that support life. These landforms and deposits contain a rich, yet incomplete, record of Earth history that we are just beginning to understand. Some of the most dramatic landforms are the huge bedrock canyons carved by catastrophic floods. On Mars, similar bedrock canyons, known as Outflow Channels, are the most important indicators of large volumes of surface water in the past. Despite their importance and now decades of observations of canyon morphology, we lack a basic understanding of how the canyons formed, which limits our ability to reconstruct flood discharge, duration and water volume. In this presentation I will summarize recent work - using mechanistic numerical models and field observations - that suggests that bedrock canyons carved by megafloods rapidly evolve to a size and shape such that boundary shear stresses just exceed that required to entrain fractured blocks of rock. The threshold shear stress constraint allows for quantitative reconstruction of the largest known floods on Earth and Mars, and implies far smaller discharges than previous methods that assume flood waters fully filled the canyons to high water marks.

  8. KEPLER-1647B: THE LARGEST AND LONGEST-PERIOD KEPLER TRANSITING CIRCUMBINARY PLANET

    International Nuclear Information System (INIS)

    Kostov, Veselin B.; Orosz, Jerome A.; Welsh, William F.; Short, Donald R.; Doyle, Laurance R.; Fabrycky, Daniel C.; Haghighipour, Nader; Quarles, Billy; Cochran, William D.; Endl, Michael; Ford, Eric B.; Gregorio, Joao; Hinse, Tobias C.; Isaacson, Howard; Jenkins, Jon M.; Jensen, Eric L. N.; Kane, Stephen; Kull, Ilya

    2016-01-01

    We report the discovery of a new Kepler transiting circumbinary planet (CBP). This latest addition to the still-small family of CBPs defies the current trend of known short-period planets orbiting near the stability limit of binary stars. Unlike the previous discoveries, the planet revolving around the eclipsing binary system Kepler-1647 has a very long orbital period (∼1100 days) and was at conjunction only twice during the Kepler mission lifetime. Due to the singular configuration of the system, Kepler-1647b is not only the longest-period transiting CBP at the time of writing, but also one of the longest-period transiting planets. With a radius of 1.06 ± 0.01 R Jup , it is also the largest CBP to date. The planet produced three transits in the light curve of Kepler-1647 (one of them during an eclipse, creating a syzygy) and measurably perturbed the times of the stellar eclipses, allowing us to measure its mass, 1.52 ± 0.65 M Jup . The planet revolves around an 11-day period eclipsing binary consisting of two solar-mass stars on a slightly inclined, mildly eccentric ( e bin = 0.16), spin-synchronized orbit. Despite having an orbital period three times longer than Earth’s, Kepler-1647b is in the conservative habitable zone of the binary star throughout its orbit.

  9. Seasonal variations of trace elements in precipitation at the largest city in Tibet, Lhasa

    Science.gov (United States)

    Guo, Junming; Kang, Shichang; Huang, Jie; Zhang, Qianggong; Tripathee, Lekhendra; Sillanpää, Mika

    2015-02-01

    Precipitation samples were collected from March 2010 to August 2012 at an urban site in Lhasa, the capital and largest city of Tibet. The volume weighted mean (VWM) concentrations of 17 trace elements in precipitation were higher during the non-monsoon season than in the monsoon season, but inverse seasonal variations occurred for wet deposition fluxes of most of the trace elements. Concentrations for most of trace elements were negatively correlated with precipitation amount, indicating that below-cloud scavenging of trace elements was an important mechanism contributing to wet deposition of these elements. The elements Al, Sc, V, Cr, Mn, Fe, Mn, Ni, and U displayed low crustal enrichment factors (EFs), whereas Co, Cu, Zn, As, Cd Sn, Pb, and Bi showed high EF values in precipitation, suggesting that anthropogenic activities might be important contributors of these elements at Lhasa. However, this present work indicates a much lower anthropogenic emission at Lhasa than in seriously polluted regions. Our study will not only provide insights for assessing the current status of the atmospheric environment in Lhasa but also enhance our understanding for updating the baseline for environmental protection over the Tibetan Plateau.

  10. The largest subsea hot tap (future tap flange) at Angel Field, Australia

    Energy Technology Data Exchange (ETDEWEB)

    Lad, Deepak; Drysdale, Colin [T.D. Williamson (United States); Naidoo, Sashie [T.D. Williamson (Australia)

    2008-07-01

    A subsea hot tap was conducted near the gas production platforms in Angel Field, Australia in September 2007 and verified as the largest no. 900 subsea hot tap by Australian authorities. This paper outlines the subsea tapping process, risks and safety issues in deep water environment, including the need to ensure 100% system accuracy and that the machine fluids used to operate the subsea tapping machines were environmentally friendly. The testing phase included land and water testing. In the land tests, issues relating to metal hardness, temperature, pressure and ocean currents that affected machine stability, torque and cutting rate were considered. All preliminary design and testing focused on being able to mount the tapping machine to a pre-existing hot-tap flange and conduct the tapping operation, start to finish, preferably without changing the cutter. The water depth tests took place inside a pressurized, underwater hyperbaric chamber. The equipment repeated the land testing process in conditions duplicating that of the actual project site. Timing was also measured in multiple climatic conditions (except water depth) to obtain an estimation of various scenarios. The field tapping process was conducted without problems in over six hours with a single cutter and without any stalls. (author)

  11. Dragon bridge - the world largest dragon-shaped (ARCH steel bridge as element of smart city

    Directory of Open Access Journals (Sweden)

    Chinh Luong Minh

    2016-01-01

    Full Text Available Dragon Bridge - The world’s largest dragon-shaped steel bridge, with an installation cost of $85 million USD, features 6 lanes for two separate directions, 666 meters of undulating steel in the shape of a dragon in the Ly Dynasty, the symbol of prosperity in Vietnamese culture. This unique and beautifully lit bridge, which also breathes fire and sprays water. It’s the purposeful integration of the lighting hardware articulates the dragon’s form, and the fire-breathing dragon head. This project transcends the notion of monumental bridge with dynamic colour-changing lighting, creating an iconic sculpture in the skyline that is both reverent and whimsical. The signature feature of the bridge was the massive undulating support structure resembling a dragon flying over the river. The dragon is prominent in Vietnamese culture as a symbol of power and nobility. Dragon Bridge stands out as a model of innovation. It has received worldwide attention in the design community and from the global media for its unique arch support system. Dragon Bridge serves as an example of how aesthetic quality of a design can serve cultural, economic and functional purposes. The article presents design solutions of the object and the evaluation of the technical condition before putting the facility into service.

  12. Making detailed predictions makes (some) predictions worse

    Science.gov (United States)

    Kelly, Theresa F.

    In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

  13. Companies on Facebook : How many of the 100  largest Swedish Companies have a Facebook page, and how do they use it?

    OpenAIRE

    Björkqvist, Johanna; Johannesson, Erik; Jorikson, Linn

    2011-01-01

    Purpose: The purpose of  this thesis is to see if the 100 largest Swedish companies are present on  Facebook, and if they are, how they use their business pages. Further the  customers’ perception of companies’ use of Facebook will be included. To  investigate this, three research questions were created. Background: As Web 2.0 and  its application has changed, the use of Internet, both for companies and  customers, there has been change in how information is delivered and how  people take in ...

  14. Ruptura de aneurismas de aorta abdominal. Herramienta informática para su predicción // Rupture of abdominal aortic aneurysm. Software for its prediction

    Directory of Open Access Journals (Sweden)

    Guillermo Villalta‐Alonso

    2011-01-01

    Full Text Available La ruptura de los aneurismas de aorta abdominal representa un evento clínico muy importantedebido a su alta tasa de mortalidad. Los indicadores empleados actualmente para decidir eltratamiento a pacientes con aneurismas son el diámetro máximo transversal y la tasa de crecimiento,los que pueden ser considerados insuficientes, pues no tienen una base teórica físicamentefundamentada. En el presente artículo se definen los fundamentos para el diseño de una herramientainformática para PC que permita predecir, con suficiente precisión para ser clínicamente relevante, elriesgo de ruptura de aneurismas de aorta abdominal sobre bases personalizadas del paciente. Laherramienta consta de 3 módulos, que están diseñados para procesar toda la información delpaciente e integrarla mediante un modelo que incorpora la interrelación de los factores biomecánicosde diferentes naturalezas (biológicos, estructurales y geométrico y escalas (temporal y dimensional,con el objetivo de calcular un indicador numérico y personalizado del riesgo de ruptura. Estaherramienta debe constituir un elemento auxiliar del facultativo médico en la toma de decisionesrespecto del tratamiento adecuado a pacientes con aneurisma.Palabras claves: AAA, riesgo de ruptura, modelo multiescala, predicción, herramienta informática.___________________________________________________________________AbstractThe rupture of abdominal aortic aneurysm (AAA represents an important clinical event due to its highmortality rate. Currently the criteria to decide on the treatment of AAA patients are the peaktransverse diameter and the growth rate which can be considered insufficient because they have nota reasonable physical base. The foundations for the design of PC software to predict, with sufficientaccuracy to be clinically relevant, the risk of AAA rupture on patient-specific basis are defined in thispaper. The software consists of 3 modules which are designed for processing all

  15. Rewriting the Landform History of One of Africa's Three Largest Basins

    Science.gov (United States)

    Wilkinson, Justin

    2014-01-01

    The Kalahari Basin in southern Africa - one of the largest basins in Africa, along with the Congo and Chad basins - has attracted attention since David Livingstone traveled through the area in the 1840s. It is a semiarid desert with a large freshwater swampland known as the Okavango Swamp (150 km radius). This prominent megafan (a fan with radii >100 km), with its fingers of dark green forests projecting into the dun colors of the dunes of the Kalahari semi-desert, has been well photographed by astronauts over the years. The study area in the northern Kalahari basin is centered on the Okavango megafan of northwest Botswana, whose swampland has become well known as an African wildlife preserve of importance to biology and tourism alike. The Okavango River is unusual because it has deposited not one but two megafans along its course: the Okavango megafan and the Cubango megafan. The Okavango megafan is one of only three well-known megafans in Africa. Megafans on Earth were once thought to be rare, but recent research has documented 68 in Africa alone. Eleven megafans, plus three more candidates, have been documented in the area immediately surrounding the Okavango feature. These 11 megafans occupy the flattest and smoothest terrains adjacent to the neighboring upland and stand out as the darkest areas in the roughness map of the area. Megafan terrains occupy at least 200,000 sq km of the study area. The roughness map shown is based on an algorithm used first on Mars to quantify topographic roughness. Research of Earth's flattest terrains is just beginning with the aid of such maps, and it appears that these terrains are analogous to the flattest regions of Mars. Implications: 1. The variability in depositional style in each subbasin may apply Africa-wide: rift megafan length is dominated by rift width, whereas Owambo subbasin megafans are probably controlled by upland basin size; Zambezi subbasin megafans appear more like foreland basin types, with the position of

  16. Indication and implementation of lipidapheresis, rheopheresis, or immunoadsorption (lessons learnt from Germany's largest apheresis center).

    Science.gov (United States)

    Heigl, Franz; Hettich, Reinhard; Lotz, Norbert; Reeg, Harduin; Eder, Bernadette; Steckholzer-Kroth, Karin; Browatzki, Michael; Harre, Kerstin; Arendt, Rainer

    2009-12-29

    Efficient modes of extracorporeal blood purification are available today for apheresis treatment of progressive atherosclerosis, autoimmune disease, or for improving hemorheology. Advanced technology and sophisticated care render apheresis treatment selective, safe and tolerable. Our task is to constantly update indications for apheresis based on best evidence available and good clinical practice, as well as, to determine how apheresis therapy can be made available to those in need or with otherwise refractory disease. Presenting examples of lipid apheresis, rheopheresis, or immunoadsorption for treatment of hypercholesterolemia, hyperlipoproteinemia (a), acute hearing loss, refractory or exacerbating multiple sclerosis, we highlight real world obstacles for implementation of treatment, resulting in still too many patients with proven or recommended indication left untreated. Based on the experience of the largest apheresis center in Germany, with more than 3,300 treatments per year, we depict the necessary structure for identification of patients, defining indication, referral, implementation of therapy, and reimbursement. Apheresis is unfamiliar to most patients and many practitioners or consultants. Nephrologists, performing >90% of apheresis treatments in Germany, have to form a network for referral comprising all regional care-givers, general practitioners as well as the respective specialists (mainly, cardiologists, endocrinologists, diabetologists, ORL specialists, neurologists, ophthalmologists, or rheumatologists), and insurances or other cost-bearing parties for offering a scientifically approved therapeutic regimen and comprehensive care. We have realized this concept in a high volume apheresis center acting in a closely knit network characterized by an unrelenting effort at ongoing medical education. As a consequence, we include approximately 10 times more patients with appropriate diagnoses in our apheresis program as compared to the national average

  17. Evidence for protection of targeted reef fish on the largest marine reserve in the Caribbean

    Directory of Open Access Journals (Sweden)

    Fabián Pina-Amargós

    2014-02-01

    Full Text Available Marine reserves can restore fish abundance and diversity in areas impacted by overfishing, but the effectiveness of reserves in developing countries where resources for enforcement are limited, have seldom been evaluated. Here we assess whether the establishment in 1996 of the largest marine reserve in the Caribbean, Gardens of the Queen in Cuba, has had a positive effect on the abundance of commercially valuable reef fish species in relation to neighboring unprotected areas. We surveyed 25 sites, including two reef habitats (reef crest and reef slope, inside and outside the marine reserve, on five different months, and over a one-and-a-half year period. Densities of the ten most frequent, highly targeted, and relatively large fish species showed a significant variability across the archipelago for both reef habitats that depended on the month of survey. These ten species showed a tendency towards higher abundance inside the reserve in both reef habitats for most months during the study. Average fish densities pooled by protection level, however, showed that five out of these ten species were at least two-fold significantly higher inside than outside the reserve at one or both reef habitats. Supporting evidence from previously published studies in the area indicates that habitat complexity and major benthic communities were similar inside and outside the reserve, while fishing pressure appeared to be homogeneous across the archipelago before reserve establishment. Although poaching may occur within the reserve, especially at the boundaries, effective protection from fishing was the most plausible explanation for the patterns observed.

  18. Phylogenetics and diversification of tanagers (Passeriformes: Thraupidae), the largest radiation of Neotropical songbirds.

    Science.gov (United States)

    Burns, Kevin J; Shultz, Allison J; Title, Pascal O; Mason, Nicholas A; Barker, F Keith; Klicka, John; Lanyon, Scott M; Lovette, Irby J

    2014-06-01

    Thraupidae is the second largest family of birds and represents about 4% of all avian species and 12% of the Neotropical avifauna. Species in this family display a wide range of plumage colors and patterns, foraging behaviors, vocalizations, ecotypes, and habitat preferences. The lack of a complete phylogeny for tanagers has hindered the study of this evolutionary diversity. Here, we present a comprehensive, species-level phylogeny for tanagers using six molecular markers. Our analyses identified 13 major clades of tanagers that we designate as subfamilies. In addition, two species are recognized as distinct branches on the tanager tree. Our topologies disagree in many places with previous estimates of relationships within tanagers, and many long-recognized genera are not monophyletic in our analyses. Our trees identify several cases of convergent evolution in plumage ornaments and bill morphology, and two cases of social mimicry. The phylogeny produced by this study provides a robust framework for studying macroevolutionary patterns and character evolution. We use our new phylogeny to study diversification processes, and find that tanagers show a background model of exponentially declining diversification rates. Thus, the evolution of tanagers began with an initial burst of diversification followed by a rate slowdown. In addition to this background model, two later, clade-specific rate shifts are supported, one increase for Darwin's finches and another increase for some species of Sporophila. The rate of diversification within these two groups is exceptional, even when compared to the overall rapid rate of diversifi