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Sample records for short-term earthquake prediction

  1. Short-Term Foreshocks and Earthquake Prediction

    NASA Astrophysics Data System (ADS)

    Papadopoulos, G. A.; Minadakis, G.; Orfanogiannaki, K.

    2016-12-01

    Foreshock recognition before main shocks depends on various factors, e.g. geophysical, catalogue completeness, foreshock definition, spatiotemporal windows. Foreshocks move towards the main shock epicenter, their number increases with the inverse of time, their b-value drops. However, only in very few single foreshock sequences these 3-D patterns were recognized at the same time, e.g. before the 2009 L' Aquila (Italy) earthquake (Mw6.3) and the 2010, 2014 and 2015 major earthquakes (Mw8+) that ruptured at the subduction zone of Chile. For the first time we found statistically significant 3-D foreshock patterns before small-to-moderate earthquakes. We present two good examples of earthquakes occurring on 4 March 2012 (Mw5.2) and 3 July 2013 (Mw4.8) in Athos and Polyphyto, both in North Greece. The great similarity with the patterns found before strong and major earthquakes indicates that the foreshock process is scale invariant in a wide magnitude range. It is likely that the process is independent of the faulting type at least for dip-slip faulting. There is also a trend of the main shock magnitude to scale with the foreshock area. These findings imply that foreshock activity is likely governed by pattern universality which may also reflect universality in the deformation process thus opening new ways for the foreshock utilization in the prediction of the main shock.

  2. Statistical short-term earthquake prediction.

    PubMed

    Kagan, Y Y; Knopoff, L

    1987-06-19

    A statistical procedure, derived from a theoretical model of fracture growth, is used to identify a foreshock sequence while it is in progress. As a predictor, the procedure reduces the average uncertainty in the rate of occurrence for a future strong earthquake by a factor of more than 1000 when compared with the Poisson rate of occurrence. About one-third of all main shocks with local magnitude greater than or equal to 4.0 in central California can be predicted in this way, starting from a 7-year database that has a lower magnitude cut off of 1.5. The time scale of such predictions is of the order of a few hours to a few days for foreshocks in the magnitude range from 2.0 to 5.0.

  3. Is Earthquake Prediction Possible from Short-Term Foreshocks?

    NASA Astrophysics Data System (ADS)

    Papadopoulos, Gerassimos; Avlonitis, Markos; Di Fiore, Boris; Minadakis, George

    2015-04-01

    Foreshocks preceding mainshocks in the short-term, ranging from minutes to a few months prior the mainshock, have been known from several decades ago. Understanding the generation mechanisms of foreshocks was supported by seismicity observations and statistics, laboratory experiments, theoretical considerations and simulation results. However, important issues remain open. For example, (1) How foreshocks are defined? (2) Why only some mainshocks are preceded by foreshocks but others do not? (2) Is the mainshock size dependent on some attributes of the foreshock sequence? (3) Is that possible to discriminate foreshocks from other seismicity styles (e.g. swarms, aftershocks)? To approach possible replies to these issues we reviewed about 400 papers, reports, books and other documents referring to foreshocks as well as to relevant laboratory experiments. We found that different foreshock definitions are used by different authors. We found also that the ratio of mainshocks preceded by foreshocks increases with the increase of monitoring capabilities and that foreshock activity is dependent on source mechanical properties and favoured by material heterogeneity. Also, the mainshock size does not depend on the largest foreshock size but rather by the foreshock area. Seismicity statistics may account for an effective discrimination of foreshocks from other seismicity styles since during foreshock activities the seismicity rate increases with the inverse of time and, at the same, the b-value of the G-R relationship as a rule drops significantly. Our literature survey showed that only the last years the seismicity catalogs organized in some well monitored areas are adequately complete to search for foreshock activities. Therefore, we investigated for a set of "good foreshock examples" covering a wide range of mainshock magnitudes from 4.5 to 9 in Japan (Tohoku 2011), S. California, Italy (including L' Aquila 2009) and Greece. The good examples used indicate that foreshocks

  4. Reported geomagnetic and ionospheric precursors to earthquakes: Summary, reanalysis, and implications for short-term prediction

    NASA Astrophysics Data System (ADS)

    Thomas, J. N.; Masci, F.; Love, J. J.; Johnston, M. J.

    2012-12-01

    Earthquakes are one of the most devastating natural phenomena on earth, causing high deaths tolls and large financial losses each year. If precursory signals could be regularly and reliably identified, then the hazardous effects of earthquakes might be mitigated. Unfortunately, it is not at all clear that short-term earthquake prediction is either possible or practical, and the entire subject remains controversial. Still, many claims of successful earthquake precursor observations have been published, and among these are reports of geomagnetic and ionospheric anomalies prior to earthquake occurrence. Given the importance of earthquake prediction, reports of earthquake precursors need to be analyzed and checked for reliability and reproducibility. We have done this for numerous such reports, including the Loma Prieta, Guam, Hector Mine, Tohoku, and L'Aquila earthquakes. We have found that these reported earthquake precursors: 1) often lack time series observations from long before and long after the earthquakes and near and far from the earthquakes, 2) are not statistically correlated with the earthquakes and do not relate to the earthquake source mechanisms, 3) are not followed by similar, but much larger, signals during the subsequent earthquake when the primary energy release occurs, 4) are nonuniform in that they occur at different spatial and temporal regimes relative to the earthquakes and with different magnitudes and frequencies, and 5) can often be explained by other non-earthquake related mechanisms or normal geomagnetic activity. Thus we conclude that these reported precursors could not be used to predict the time or location of the earthquakes. Based on our findings, we suggest a protocol for examining precursory reports, something that will help guide future research in this area.

  5. Short-term earthquake prediction: Current status of seismo-electromagnetics

    NASA Astrophysics Data System (ADS)

    Uyeda, Seiya; Nagao, Toshiyasu; Kamogawa, Masashi

    2009-05-01

    Loss of human lives as a result of earthquakes is caused overwhelmingly by the collapse of buildings within less than a few minutes of main shocks. The most urgent countermeasure consists of two key elements. One is strengthening of weak structures and the other is short-term earthquake prediction. Short-term prediction needs precursors. Although some promising precursors are reported, the prevailing views in Japan and elsewhere are overly pessimistic. The pessimism largely roots in the fact that short-term precursors are generally non-seismic and tools developed for seismology are not designed to detect them. Nonetheless, nationally funded large-scale earthquake prediction programs always emphasize the need to reinforce seismometer networks. They do not take into account the views of those in the science community who point to the importance of non-seismic precursors. While there are well-founded causes to be skeptical, the situation needs to be improved. One reason for skepticism is that the observations of precursors have not yet been perfect enough and another is that some important fundamental aspects of non-seismic precursors are still unresolved. We review some of these problems.

  6. Four Examples of Short-Term and Imminent Prediction of Earthquakes

    NASA Astrophysics Data System (ADS)

    zeng, zuoxun; Liu, Genshen; Wu, Dabin; Sibgatulin, Victor

    2014-05-01

    We show here 4 examples of short-term and imminent prediction of earthquakes in China last year. They are Nima Earthquake(Ms5.2), Minxian Earthquake(Ms6.6), Nantou Earthquake (Ms6.7) and Dujiangyan Earthquake (Ms4.1) Imminent Prediction of Nima Earthquake(Ms5.2) Based on the comprehensive analysis of the prediction of Victor Sibgatulin using natural electromagnetic pulse anomalies and the prediction of Song Song and Song Kefu using observation of a precursory halo, and an observation for the locations of a degasification of the earth in the Naqu, Tibet by Zeng Zuoxun himself, the first author made a prediction for an earthquake around Ms 6 in 10 days in the area of the degasification point (31.5N, 89.0 E) at 0:54 of May 8th, 2013. He supplied another degasification point (31N, 86E) for the epicenter prediction at 8:34 of the same day. At 18:54:30 of May 15th, 2013, an earthquake of Ms5.2 occurred in the Nima County, Naqu, China. Imminent Prediction of Minxian Earthquake (Ms6.6) At 7:45 of July 22nd, 2013, an earthquake occurred at the border between Minxian and Zhangxian of Dingxi City (34.5N, 104.2E), Gansu province with magnitude of Ms6.6. We review the imminent prediction process and basis for the earthquake using the fingerprint method. 9 channels or 15 channels anomalous components - time curves can be outputted from the SW monitor for earthquake precursors. These components include geomagnetism, geoelectricity, crust stresses, resonance, crust inclination. When we compress the time axis, the outputted curves become different geometric images. The precursor images are different for earthquake in different regions. The alike or similar images correspond to earthquakes in a certain region. According to the 7-year observation of the precursor images and their corresponding earthquake, we usually get the fingerprint 6 days before the corresponding earthquakes. The magnitude prediction needs the comparison between the amplitudes of the fingerpringts from the same

  7. Foreshock Sequences and Short-Term Earthquake Predictability on East Pacific Rise Transform Faults

    NASA Astrophysics Data System (ADS)

    McGuire, J. J.; Boettcher, M. S.; Jordan, T. H.

    2004-12-01

    A predominant view of continental seismicity postulates that all earthquakes initiate in a similar manner regardless of their eventual size and that earthquake triggering can be described by an Endemic Type Aftershock Sequence (ETAS) model [e.g. Ogata, 1988, Helmstetter and Sorenette 2002]. These null hypotheses cannot be rejected as an explanation for the relative abundances of foreshocks and aftershocks to large earthquakes in California [Helmstetter et al., 2003]. An alternative location for testing this hypothesis is mid-ocean ridge transform faults (RTFs), which have many properties that are distinct from continental transform faults: most plate motion is accommodated aseismically, many large earthquakes are slow events enriched in low-frequency radiation, and the seismicity shows depleted aftershock sequences and high foreshock activity. Here we use the 1996-2001 NOAA-PMEL hydroacoustic seismicity catalog for equatorial East Pacific Rise transform faults to show that the foreshock/aftershock ratio is two orders of magnitude greater than the ETAS prediction based on global RTF aftershock abundances. We can thus reject the null hypothesis that there is no fundamental distinction between foreshocks, mainshocks, and aftershocks on RTFs. We further demonstrate (retrospectively) that foreshock sequences on East Pacific Rise transform faults can be used to achieve statistically significant short-term prediction of large earthquakes (magnitude ≥ 5.4) with good spatial (15-km) and temporal (1-hr) resolution using the NOAA-PMEL catalogs. Our very simplistic approach produces a large number of false alarms, but it successfully predicts the majority (70%) of M≥5.4 earthquakes while covering only a tiny fraction (0.15%) of the total potential space-time volume with alarms. Therefore, it achieves a large probability gain (about a factor of 500) over random guessing, despite not using any near field data. The predictability of large EPR transform earthquakes suggests

  8. The USGS plan for short-term prediction of the anticipated Parkfield earthquake

    USGS Publications Warehouse

    Bakun, W.H.

    1988-01-01

    Aside from the goal of better understanding the Parkfield earthquake cycle, it is the intention of the U.S Geological Survey to attempt to issue a warning shortly before the anticipated earthquake. Although short-term earthquake warnings are not yet generally feasible, the wealth of information available for the previous significant Parkfield earthquakes suggests that if the next earthquake follows the pattern of "characteristic" Parkfield shocks, such a warning might be possible. Focusing on earthquake precursors reported for the previous  "characteristic" shocks, particulary the 1934 and 1966 events, the USGS developed a plan* in late 1985 on which to base earthquake warnings for Parkfield and has assisted State, county, and local officials in the Parkfield area to prepare a coordinated, reasonable response to a warning, should one be issued. 

  9. From a physical approach to earthquake prediction, towards long and short term warnings ahead of large earthquakes

    NASA Astrophysics Data System (ADS)

    Stefansson, R.; Bonafede, M.

    2012-04-01

    For 20 years the South Iceland Seismic Zone (SISZ) was a test site for multinational earthquake prediction research, partly bridging the gap between laboratory tests samples, and the huge transform zones of the Earth. The approach was to explore the physics of processes leading up to large earthquakes. The book Advances in Earthquake Prediction, Research and Risk Mitigation, by R. Stefansson (2011), published by Springer/PRAXIS, and an article in the August issue of the BSSA by Stefansson, M. Bonafede and G. Gudmundsson (2011) contain a good overview of the findings, and more references, as well as examples of partially successful long and short term warnings based on such an approach. Significant findings are: Earthquakes that occurred hundreds of years ago left scars in the crust, expressed in volumes of heterogeneity that demonstrate the size of their faults. Rheology and stress heterogeneity within these volumes are significantly variable in time and space. Crustal processes in and near such faults may be observed by microearthquake information decades before the sudden onset of a new large earthquake. High pressure fluids of mantle origin may in response to strain, especially near plate boundaries, migrate upward into the brittle/elastic crust to play a significant role in modifying crustal conditions on a long and short term. Preparatory processes of various earthquakes can not be expected to be the same. We learn about an impending earthquake by observing long term preparatory processes at the fault, finding a constitutive relationship that governs the processes, and then extrapolating that relationship into near space and future. This is a deterministic approach in earthquake prediction research. Such extrapolations contain many uncertainties. However the long time pattern of observations of the pre-earthquake fault process will help us to put probability constraints on our extrapolations and our warnings. The approach described is different from the usual

  10. On the short-term earthquake prediction: renormalization algorithm and observational evidence in S. California, E. Mediterranean, and Japan

    NASA Astrophysics Data System (ADS)

    Keilis-Borok, V.; Shebalin, P.; Zaliapin, I.; Novikova, O.; Gabrielov, A.

    2002-12-01

    Our point of departure is provided by premonitory seismicity patterns found in models and observations. They reflect increase of earthquake correlation range and seismic activity within "intermediate" lead-time of years before a strong earthquake. A combination of these patterns, in renormalized definition, precedes within months eight out of nine strong earthquakes in S. California, E. Mediterranean, and Japan. We suggest on that basis a hypothetical short-term prediction algorithm, to be tested by advance prediction. The algorithm is self-adapting and can be transferred without readaptation from earthquake to earthquake and from area to area. If confirmed, it will have a simple, albeit non-unique, qualitative interpretation. The suggested algorithm is designed to provide a short-term approximation to an intermediate-term prediction. It remains not clear, whether it could be used independently.

  11. Short-term foreshock activity and its value for the earthquake prediction

    NASA Astrophysics Data System (ADS)

    Orfanogiannaki, Katerina; Daskalaki, Elena; Minadakis, George; Papadopoulos, Gerasimos

    2014-05-01

    Seismicity often occurs in space-time clusters: swarms, short-term foreshocks, aftershocks. Swarms are space-time clusters that do not conclude with a mainshock. Earthquake statistics shows that in areas of good seismicity monitoring foreshocks precede sizeable (M5.5 or more) mainshocks at a rate of about half percent. Therefore, discrimination between foreshocks and swarms is of crucial importance with the aim to use foreshocks as a diagnostic of forthcoming strong mainshock in real-time conditions. We analyzed seismic sequences in Greece and Italy with the application of our algorithm FORMA (Foreshocks-Mainshock-Aftershocks) and discriminate between foreshocks and swarms based on the seismicity significant changes in the space-time-magnitude domains. We support that different statistical properties is a diagnostic of foreshocks (e.g. b-value drop) against swarms (b-value increase). A complementary approach is based on the development of Poisson Hidden Markov Models (PHMM's) which are introduced to model significant temporal seismicity changes. In a PHMM the unobserved sequence of states is a finite-state Markov chain and the distribution of the observation at any time is Poissonian with rate depending only on the current state of the chain. Thus, PHMM allows a region to have varying seismicity rate. PHMM is a promising diagnostic since the transition from one state to another does not only depend on the total number of events involved but also on the current state of the system. A third methodological experiment was performed based on the complex network theory. We found that the earthquake networks examined form a scale-free degree distribution. By computing their basic statistical measures, such as the Average Clustering Coefficient, Mean Path Length and Entropy, we found that they underline the strong space-time clustering of swarms, foreshocks and aftershocks but also their important differences. Therefore, network theory is an additional, promising tool to

  12. Earthquake prediction

    NASA Technical Reports Server (NTRS)

    Turcotte, Donald L.

    1991-01-01

    The state of the art in earthquake prediction is discussed. Short-term prediction based on seismic precursors, changes in the ratio of compressional velocity to shear velocity, tilt and strain precursors, electromagnetic precursors, hydrologic phenomena, chemical monitors, and animal behavior is examined. Seismic hazard assessment is addressed, and the applications of dynamical systems to earthquake prediction are discussed.

  13. Earthquake prediction

    NASA Technical Reports Server (NTRS)

    Turcotte, Donald L.

    1991-01-01

    The state of the art in earthquake prediction is discussed. Short-term prediction based on seismic precursors, changes in the ratio of compressional velocity to shear velocity, tilt and strain precursors, electromagnetic precursors, hydrologic phenomena, chemical monitors, and animal behavior is examined. Seismic hazard assessment is addressed, and the applications of dynamical systems to earthquake prediction are discussed.

  14. Short-term Drought Prediction in India.

    NASA Astrophysics Data System (ADS)

    Shah, R.; Mishra, V.

    2014-12-01

    Medium range soil moisture drought forecast helps in decision making in the field of agriculture and water resources management. Part of skills in medium range drought forecast comes from precipitation. Proper evaluation and correction of precipitation forecast may improve drought predictions. Here, we evaluate skills of ensemble mean precipitation forecast from Global Ensemble Forecast System (GEFS) for medium range drought predictions over India. Climatological mean (CLIM) of historic data (OBS) are used as reference forecast to evaluate GEFS precipitation forecast. Analysis was conducted based on forecast initiated on 1st and 15th dates of each month for lead up to 7-days. Correlation and RMSE were used to estimate skill scores of accumulated GEFS precipitation forecast from lead 1 to 7-days. Volumetric indices based on the 2X2 contingency table were used to check missed and falsely predicted historic volume of daily precipitation from GEFS in different regions and at different thresholds. GEFS showed improvement in correlation of 0.44 over CLIM during the monsoon season and 0.55 during the winter season. Lower RMSE was showed by GEFS than CLIM. Ratio of RMSE in GEFS and CLIM comes out as 0.82 and 0.4 (perfect skill is at zero) during the monsoon and winter season, respectively. We finally used corrected GEFS forecast to derive the Variable Infiltration Capacity (VIC) model, which was used to develop short-term forecast of hydrologic and agricultural (soil moisture) droughts in India.

  15. Short-term predictions in forex trading

    NASA Astrophysics Data System (ADS)

    Muriel, A.

    2004-12-01

    Using a kinetic equation that is used to model turbulence (Physica A, 1985-1988, Physica D, 2001-2003), we redefine variables to model the time evolution of the foreign exchange rates of three major currencies. We display live and predicted data for one period of trading in October, 2003.

  16. Testing new methodologies for short -term earthquake forecasting: Multi-parameters precursors

    NASA Astrophysics Data System (ADS)

    Ouzounov, Dimitar; Pulinets, Sergey; Tramutoli, Valerio; Lee, Lou; Liu, Tiger; Hattori, Katsumi; Kafatos, Menas

    2014-05-01

    We are conducting real-time tests involving multi-parameter observations over different seismo-tectonics regions in our investigation of phenomena preceding major earthquakes. Our approach is based on a systematic analysis of several selected parameters, namely: gas discharge; thermal infrared radiation; ionospheric electron density; and atmospheric temperature and humidity, which we believe are all associated with the earthquake preparation phase. We are testing a methodology capable to produce alerts in advance of major earthquakes (M > 5.5) in different regions of active earthquakes and volcanoes. During 2012-2013 we established a collaborative framework with PRE-EARTHQUAKE (EU) and iSTEP3 (Taiwan) projects for coordinated measurements and prospective validation over seven testing regions: Southern California (USA), Eastern Honshu (Japan), Italy, Greece, Turkey, Taiwan (ROC), Kamchatka and Sakhalin (Russia). The current experiment provided a "stress test" opportunity to validate the physical based earthquake precursor approach over regions of high seismicity. Our initial results are: (1) Real-time tests have shown the presence of anomalies in the atmosphere and ionosphere before most of the significant (M>5.5) earthquakes; (2) False positives exist and ratios are different for each region, varying between 50% for (Southern Italy), 35% (California) down to 25% (Taiwan, Kamchatka and Japan) with a significant reduction of false positives as soon as at least two geophysical parameters are contemporarily used; (3) Main problems remain related to the systematic collection and real-time integration of pre-earthquake observations. Our findings suggest that real-time testing of physically based pre-earthquake signals provides a short-term predictive power (in all three important parameters, namely location, time and magnitude) for the occurrence of major earthquakes in the tested regions and this result encourages testing to continue with a more detailed analysis of

  17. Improving the Short-Term Prediction of Suicidal Behavior

    PubMed Central

    Glenn, Catherine R.; Nock, Matthew K.

    2015-01-01

    Aspirational Goal 3 of the National Action Alliance for Suicide Prevention’s Research Prioritization Task Force is to predict who is at risk for attempting suicide in the near future. Despite decades of research devoted to the study of risk and protective factors for suicide and suicidal behavior, surprisingly little is known about the short-term prediction of these behaviors. In this paper, we propose several questions that, if answered, could improve the identification of short-term, or imminent, risk for suicidal behavior. First, what factors predict the transition from suicidal thoughts to attempts? Second, what factors are particularly strong predictors of making this transition over the next hours, days, or weeks? Third, what are the most important objective markers of short-term risk for suicidal behavior? And fourth, what method of combining information about risk and protective factors yields the best prediction? We propose that the next generation of research on the assessment and prediction of suicidal behavior should shift, from cross-sectional studies of bivariate risk and protective factors, to prospective studies aimed at identifying multivariate, short-term prediction indices, examining methods of synthesizing this information, and testing the ability to predict and prevent suicidal events. PMID:25145736

  18. Short-term earthquake probabilities during the L'Aquila earthquake sequence in central Italy, 2009

    NASA Astrophysics Data System (ADS)

    Falcone, G.; Murru, M.; Zhuang, J.; Console, R.

    2014-12-01

    We compare the forecasting performance of several statistical models, which are used to describe the occurrence process of earthquakes, in forecasting the short-term earthquake probabilities during the occurrence of the L'Aquila earthquake sequence in central Italy, 2009. These models include the Proximity to Past Earthquakes (PPE) model and different versions of the Epidemic Type Aftershock Sequence (ETAS) model. We used the information gains corresponding to the Poisson and binomial scores to evaluate the performance of these models. It is shown that all ETAS models work better than the PPE model. However, when comparing the different types of the ETAS models, the one with the same fixed exponent coefficient α = 2.3 for both the productivity function and the scaling factor in the spatial response function, performs better in forecasting the active aftershock sequence than the other models with different exponent coefficients when the Poisson score is adopted. These latter models perform only better when a lower magnitude threshold of 2.0 and the binomial score are used. The reason is likely due to the fact that the catalog does not contain an event of magnitude similar to the L'Aquila main shock (Mw 6.3) in the training period (April 16, 2005 to March 15, 2009). In this case the a-value is under-estimated and thus also the forecasted seismicity is underestimated when the productivity function is extrapolated to high magnitudes. These results suggest that the training catalog used for estimating the model parameters should include earthquakes of similar magnitudes as the main shock when forecasting seismicity is during an aftershock sequences.

  19. Comparison of Short-term and Long-term Earthquake Forecast Models for Southern California

    NASA Astrophysics Data System (ADS)

    Helmstetter, A.; Kagan, Y. Y.; Jackson, D. D.

    2004-12-01

    Many earthquakes are triggered in part by preceding events. Aftershocks are the most obvious examples, but many large earthquakes are preceded by smaller ones. The large fluctuations of seismicity rate due to earthquake interactions thus provide a way to improve earthquake forecasting significantly. We have developed a model to estimate daily earthquake probabilities in Southern California, using the Epidemic Type Earthquake Sequence model [Kagan and Knopoff, 1987; Ogata, 1988]. The forecasted seismicity rate is the sum of a constant external loading and of the aftershocks of all past earthquakes. The background rate is estimated by smoothing past seismicity. Each earthquake triggers aftershocks with a rate that increases exponentially with its magnitude and which decreases with time following Omori's law. We use an isotropic kernel to model the spatial distribution of aftershocks for small (M≤5.5) mainshocks, and a smoothing of the location of early aftershocks for larger mainshocks. The model also assumes that all earthquake magnitudes follow the Gutenberg-Richter law with a unifom b-value. We use a maximum likelihood method to estimate the model parameters and tests the short-term and long-term forecasts. A retrospective test using a daily update of the forecasts between 1985/1/1 and 2004/3/10 shows that the short-term model decreases the uncertainty of an earthquake occurrence by a factor of about 10.

  20. Power system very short-term load prediction

    SciTech Connect

    Trudnowski, D.J.; Johnson, J.M.; Whitney, P.

    1997-02-01

    A fundamental objective of a power-system operating and control scheme is to maintain a match between the system`s overall real-power load and generation. To accurately maintain this match, modern energy management systems require estimates of the future total system load. Several strategies and tools are available for estimating system load. Nearly all of these estimate the future load in 1-hour steps over several hours (or time frames very close to this). While hourly load estimates are very useful for many operation and control decisions, more accurate estimates at closer intervals would also be valuable. This is especially true for emerging Area Generation Control (AGC) strategies such as look-ahead AGC. For these short-term estimation applications, future load estimates out to several minutes at intervals of 1 to 5 minutes are required. The currently emerging operation and control strategies being developed by the BPA are dependent on accurate very short-term load estimates. To meet this need, the BPA commissioned the Pacific Northwest National Laboratory (PNNL) and Montana Tech (an affiliate of the University of Montana) to develop an accurate load prediction algorithm and computer codes that automatically update and can reliably perform in a closed-loop controller for the BPA system. The requirements include accurate load estimation in 5-minute steps out to 2 hours. This report presents the results of this effort and includes: a methodology and algorithms for short-term load prediction that incorporates information from a general hourly forecaster; specific algorithm parameters for implementing the predictor in the BPA system; performance and sensitivity studies of the algorithms on BPA-supplied data; an algorithm for filtering power system load samples as a precursor to inputting into the predictor; and FORTRAN 77 subroutines for implementing the algorithms.

  1. SHORT-TERM SOLAR FLARE PREDICTION USING MULTIRESOLUTION PREDICTORS

    SciTech Connect

    Yu Daren; Huang Xin; Hu Qinghua; Zhou Rui; Wang Huaning; Cui Yanmei

    2010-01-20

    Multiresolution predictors of solar flares are constructed by a wavelet transform and sequential feature extraction method. Three predictors-the maximum horizontal gradient, the length of neutral line, and the number of singular points-are extracted from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms. A maximal overlap discrete wavelet transform is used to decompose the sequence of predictors into four frequency bands. In each band, four sequential features-the maximum, the mean, the standard deviation, and the root mean square-are extracted. The multiresolution predictors in the low-frequency band reflect trends in the evolution of newly emerging fluxes. The multiresolution predictors in the high-frequency band reflect the changing rates in emerging flux regions. The variation of emerging fluxes is decoupled by wavelet transform in different frequency bands. The information amount of these multiresolution predictors is evaluated by the information gain ratio. It is found that the multiresolution predictors in the lowest and highest frequency bands contain the most information. Based on these predictors, a C4.5 decision tree algorithm is used to build the short-term solar flare prediction model. It is found that the performance of the short-term solar flare prediction model based on the multiresolution predictors is greatly improved.

  2. Human short-term spatial memory: precision predicts capacity.

    PubMed

    Banta Lavenex, Pamela; Boujon, Valérie; Ndarugendamwo, Angélique; Lavenex, Pierre

    2015-03-01

    Here, we aimed to determine the capacity of human short-term memory for allocentric spatial information in a real-world setting. Young adults were tested on their ability to learn, on a trial-unique basis, and remember over a 1-min interval the location(s) of 1, 3, 5, or 7 illuminating pads, among 23 pads distributed in a 4m×4m arena surrounded by curtains on three sides. Participants had to walk to and touch the pads with their foot to illuminate the goal locations. In contrast to the predictions from classical slot models of working memory capacity limited to a fixed number of items, i.e., Miller's magical number 7 or Cowan's magical number 4, we found that the number of visited locations to find the goals was consistently about 1.6 times the number of goals, whereas the number of correct choices before erring and the number of errorless trials varied with memory load even when memory load was below the hypothetical memory capacity. In contrast to resource models of visual working memory, we found no evidence that memory resources were evenly distributed among unlimited numbers of items to be remembered. Instead, we found that memory for even one individual location was imprecise, and that memory performance for one location could be used to predict memory performance for multiple locations. Our findings are consistent with a theoretical model suggesting that the precision of the memory for individual locations might determine the capacity of human short-term memory for spatial information. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Reducing variability in short term orbital lifetime prediction

    NASA Astrophysics Data System (ADS)

    Kebschull, Christopher; Flegel, Sven Kevin; Braun, Vitali; Gelhaus, Johannes; Möckel, Marek; Wiedemann, Carsten; Vörsmann, Peter

    2013-04-01

    Within the last year three major re-entries occurred. The satellites UARS, ROSAT and Phobos-Grunt entered Earth's atmosphere with fragments reaching the surface. Due to a number of uncertainties in propagating an object's trajectory the exact place and time of a satellite's re-entry is hard to determine. Major influences when predicting the re-entry time are the changing precision of the available orbital data, the satellite's ballistic coefficient, the activity of the sun which influences the Earth's atmosphere and the underlying quality of the atmospheric model. In this paper a method is presented which can reduce the variability in short-term orbital lifetime prediction induced by fluctuating orbital data accuracies. A re-entry campaign is used as a reference for this purpose. For a window of a few weeks before the re-entry the position data of a synthetic object is disturbed considering different degrees of orbital data errors. As a result different predictions will exist for the generated position data of a given day. Using a regression algorithm on the available data an average position is obtained, which is then used for the orbital lifetime prediction. The effect of this measure is a more consistent prediction of the orbital lifetime. The paper concludes with the comparison of the generated re-entry windows in various test cases for the original and the averaged data.

  4. Models for short term malaria prediction in Sri Lanka

    PubMed Central

    Briët, Olivier JT; Vounatsou, Penelope; Gunawardena, Dissanayake M; Galappaththy, Gawrie NL; Amerasinghe, Priyanie H

    2008-01-01

    Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed. PMID:18460204

  5. Identification of anomalous ULF emission related to short term earthquake precursor

    NASA Astrophysics Data System (ADS)

    Sihotang, Bertalina; Ahadi, Suaidi

    2017-07-01

    The observation of ULF emission recorded in geomagnetic station is a powerful study of short term earthquake precursor. Anomalies that arise when there is no disturbance magnetic storm can be considered as precursors of the earthquake. Data used in this research were geomagnetic data recorded in LWA station as a main station, GSI station and TSI station as reference station and earthquake data. The earthquakes were on September 23, 2015 (Mw. 5.1), October 1, 2015 (Mw 5.4), and November 18, 2015 (Mw. 5.2). In determining onset time and lead time, polarization ratio Z/H at frequency of 0.012 Hz was used. Lead time detected were 4 days, 7 days, 4 days before the earthquakes respectively. The azimuth of anomalies ULF emission was investigated with Single Station Transfer Function (SSTF) that represent earthquake preparation zone. The azimuth of anomalous ULF emissions for each earthquakes were 217.3°, 208.5°, and 184.3°.

  6. Short-term wind speed predictions with machine learning techniques

    NASA Astrophysics Data System (ADS)

    Ghorbani, M. A.; Khatibi, R.; FazeliFard, M. H.; Naghipour, L.; Makarynskyy, O.

    2016-02-01

    Hourly wind speed forecasting is presented by a modeling study with possible applications to practical problems including farming wind energy, aircraft safety and airport operations. Modeling techniques employed in this paper for such short-term predictions are based on the machine learning techniques of artificial neural networks (ANNs) and genetic expression programming (GEP). Recorded values of wind speed were used, which comprised 8 years of collected data at the Kersey site, Colorado, USA. The January data over the first 7 years (2005-2011) were used for model training; and the January data for 2012 were used for model testing. A number of model structures were investigated for the validation of the robustness of these two techniques. The prediction results were compared with those of a multiple linear regression (MLR) method and with the Persistence method developed for the data. The model performances were evaluated using the correlation coefficient, root mean square error, Nash-Sutcliffe efficiency coefficient and Akaike information criterion. The results indicate that forecasting wind speed is feasible using past records of wind speed alone, but the maximum lead time for the data was found to be 14 h. The results show that different techniques would lead to different results, where the choice between them is not easy. Thus, decision making has to be informed of these modeling results and decisions should be arrived at on the basis of an understanding of inherent uncertainties. The results show that both GEP and ANN are equally credible selections and even MLR should not be dismissed, as it has its uses.

  7. Predicting short-term stock fluctuations by using processing fluency

    PubMed Central

    Alter, Adam L.; Oppenheimer, Daniel M.

    2006-01-01

    Three studies investigated the impact of the psychological principle of fluency (that people tend to prefer easily processed information) on short-term share price movements. In both a laboratory study and two analyses of naturalistic real-world stock market data, fluently named stocks robustly outperformed stocks with disfluent names in the short term. For example, in one study, an initial investment of $1,000 yielded a profit of $112 more after 1 day of trading for a basket of fluently named shares than for a basket of disfluently named shares. These results imply that simple, cognitive approaches to modeling human behavior sometimes outperform more typical, complex alternatives. PMID:16754871

  8. Short-term earthquake risk assessment considering time-dependent b-values

    NASA Astrophysics Data System (ADS)

    Gulia, Laura; Tormann, Thessa; Wiemer, Stefan

    2015-04-01

    Observations from laboratory experiments measuring acoustic emissions during loading cycles in pressurized rock samples have repeatedly suggested that small events in the precursory phase of an impending large event change in their relative size distribution. In particular, they highlight a systematic b-value decrease during the stress increase period before the main event. A number of large natural events, but not all of them, have been shown to have a precursory decrease in the b-value at very different time scales, from months to a few days before the subsequent mainshock. At present short term-forecast models such as STEP and ETAS consider the generic probability that an event can trigger subsequent seismicity in the near field; the rate increasing during the foreshock sequences can offer a probability gain for a significant earthquake to happen. While the probability gain of a stationary Poissonian background is substantial, selected case studies have shown through cost-benefit analysis that the absolute probability remains too low to warrant actions. This was shown for example by van Stiphout et al. (2010, GRL), for the 2009 a Mw 6.3 earthquake that hit the city of L'Aquila (Central Italy) after three months of foreshock activity. We here analyze the probability gain of a novel generation of short term forecast models which considers both the change in the seismicity rates and the temporal changes in the b-value. Changes in earthquake probability are then translated also into time-dependent hazard and risk. Preliminary results suggest that the precursory b-value decrease in the L'Aquila case results in an additional probability increase of a M6.3 event of about a factor of 30-50, which then surpasses the cost-benefit threshold for short-term evacuation in selected cases.

  9. Short-Term Forecasting of Taiwanese Earthquakes Using a Universal Model of Fusion-Fission Processes

    PubMed Central

    Cheong, Siew Ann; Tan, Teck Liang; Chen, Chien-Chih; Chang, Wu-Lung; Liu, Zheng; Chew, Lock Yue; Sloot, Peter M. A.; Johnson, Neil F.

    2014-01-01

    Predicting how large an earthquake can be, where and when it will strike remains an elusive goal in spite of the ever-increasing volume of data collected by earth scientists. In this paper, we introduce a universal model of fusion-fission processes that can be used to predict earthquakes starting from catalog data. We show how the equilibrium dynamics of this model very naturally explains the Gutenberg-Richter law. Using the high-resolution earthquake catalog of Taiwan between Jan 1994 and Feb 2009, we illustrate how out-of-equilibrium spatio-temporal signatures in the time interval between earthquakes and the integrated energy released by earthquakes can be used to reliably determine the times, magnitudes, and locations of large earthquakes, as well as the maximum numbers of large aftershocks that would follow. PMID:24406467

  10. Short-term forecasting of Taiwanese earthquakes using a universal model of fusion-fission processes.

    PubMed

    Cheong, Siew Ann; Tan, Teck Liang; Chen, Chien-Chih; Chang, Wu-Lung; Liu, Zheng; Chew, Lock Yue; Sloot, Peter M A; Johnson, Neil F

    2014-01-10

    Predicting how large an earthquake can be, where and when it will strike remains an elusive goal in spite of the ever-increasing volume of data collected by earth scientists. In this paper, we introduce a universal model of fusion-fission processes that can be used to predict earthquakes starting from catalog data. We show how the equilibrium dynamics of this model very naturally explains the Gutenberg-Richter law. Using the high-resolution earthquake catalog of Taiwan between Jan 1994 and Feb 2009, we illustrate how out-of-equilibrium spatio-temporal signatures in the time interval between earthquakes and the integrated energy released by earthquakes can be used to reliably determine the times, magnitudes, and locations of large earthquakes, as well as the maximum numbers of large aftershocks that would follow.

  11. On Earthquake Prediction in Japan

    PubMed Central

    UYEDA, Seiya

    2013-01-01

    Japan’s National Project for Earthquake Prediction has been conducted since 1965 without success. An earthquake prediction should be a short-term prediction based on observable physical phenomena or precursors. The main reason of no success is the failure to capture precursors. Most of the financial resources and manpower of the National Project have been devoted to strengthening the seismographs networks, which are not generally effective for detecting precursors since many of precursors are non-seismic. The precursor research has never been supported appropriately because the project has always been run by a group of seismologists who, in the present author’s view, are mainly interested in securing funds for seismology — on pretense of prediction. After the 1995 Kobe disaster, the project decided to give up short-term prediction and this decision has been further fortified by the 2011 M9 Tohoku Mega-quake. On top of the National Project, there are other government projects, not formally but vaguely related to earthquake prediction, that consume many orders of magnitude more funds. They are also un-interested in short-term prediction. Financially, they are giants and the National Project is a dwarf. Thus, in Japan now, there is practically no support for short-term prediction research. Recently, however, substantial progress has been made in real short-term prediction by scientists of diverse disciplines. Some promising signs are also arising even from cooperation with private sectors. PMID:24213204

  12. On earthquake prediction in Japan.

    PubMed

    Uyeda, Seiya

    2013-01-01

    Japan's National Project for Earthquake Prediction has been conducted since 1965 without success. An earthquake prediction should be a short-term prediction based on observable physical phenomena or precursors. The main reason of no success is the failure to capture precursors. Most of the financial resources and manpower of the National Project have been devoted to strengthening the seismographs networks, which are not generally effective for detecting precursors since many of precursors are non-seismic. The precursor research has never been supported appropriately because the project has always been run by a group of seismologists who, in the present author's view, are mainly interested in securing funds for seismology - on pretense of prediction. After the 1995 Kobe disaster, the project decided to give up short-term prediction and this decision has been further fortified by the 2011 M9 Tohoku Mega-quake. On top of the National Project, there are other government projects, not formally but vaguely related to earthquake prediction, that consume many orders of magnitude more funds. They are also un-interested in short-term prediction. Financially, they are giants and the National Project is a dwarf. Thus, in Japan now, there is practically no support for short-term prediction research. Recently, however, substantial progress has been made in real short-term prediction by scientists of diverse disciplines. Some promising signs are also arising even from cooperation with private sectors.

  13. Impact of Short-term Changes In Earthquake Hazard on Risk In Christchurch, New Zealand

    NASA Astrophysics Data System (ADS)

    Nyst, M.

    2012-12-01

    The recent Mw 7.1, 4 September 2010 Darfield, and Mw 6.2, 22 February 2011 Christchurch, New Zealand earthquakes and the following aftershock activity completely changed the existing view on earthquake hazard of the Christchurch area. Not only have several faults been added to the New Zealand fault database, the main shocks were also followed by significant increases in seismicity due to high aftershock activity throughout the Christchurch region that is still on-going. Probabilistic seismic hazard assessment (PSHA) models take into account a stochastic event set, the full range of possible events that can cause damage or loss at a particular location. This allows insurance companies to look at their risk profiles via average annual losses (AAL) and loss-exceedance curves. The loss-exceedance curve is derived from the full suite of seismic events that could impact the insured exposure and plots the probability of exceeding a particular loss level over a certain period. Insurers manage their risk by focusing on a certain return period exceedance benchmark, typically between the 100 and 250 year return period loss level, and then reserve the amount of money needed to account for that return period loss level, their so called capacity. This component of risk management is not too sensitive to short-term changes in risk due to aftershock seismicity, as it is mostly dominated by longer-return period, larger magnitude, more damaging events. However, because the secondairy uncertainties are taken into account when calculating the exceedance probability, even the longer return period losses can still experience significant impact from the inclusion of time-dependent earthquake behavior. AAL is calculated by summing the product of the expected loss level and the annual rate for all events in the event set that cause damage or loss at a particular location. This relatively simple metric is an important factor in setting the annual premiums. By annualizing the expected losses

  14. Short-term earthquake forecasting based on an epidemic clustering model

    NASA Astrophysics Data System (ADS)

    Console, Rodolfo; Murru, Maura; Falcone, Giuseppe

    2016-04-01

    . The implementation of this step could be problematic for seismicity characterized by long-term recurrence. However, the separation of the data base of the data base collected in the past in two separate sections (one on which the best fit of the parameters is carried out, and the other on which the hypothesis is tested) can be a viable solution, known as retrospective-forward testing. In this study we show examples of application of the above mentioned concepts to the analysis of the Italian catalog of instrumental seismicity, making use of an epidemic algorithm developed to model short-term clustering features. This model, for which a precursory anomaly is just the occurrence of seismic activity, doesn't need the retrospective categorization of earthquakes in terms of foreshocks, mainshocks and aftershocks. It was introduced more than 15 years ago and tested so far in a number of real cases. It is now being run by several seismological centers around the world in forward real-time mode for testing purposes.

  15. Distribution of Short-Term and Lifetime Predicted Risks of Cardiovascular Diseases in Peruvian Adults

    PubMed Central

    Quispe, Renato; Bazo-Alvarez, Juan Carlos; Burroughs Peña, Melissa S; Poterico, Julio A; Gilman, Robert H; Checkley, William; Bernabé-Ortiz, Antonio; Huffman, Mark D; Miranda, J Jaime

    2015-01-01

    Background Short-term risk assessment tools for prediction of cardiovascular disease events are widely recommended in clinical practice and are used largely for single time-point estimations; however, persons with low predicted short-term risk may have higher risks across longer time horizons. Methods and Results We estimated short-term and lifetime cardiovascular disease risk in a pooled population from 2 studies of Peruvian populations. Short-term risk was estimated using the atherosclerotic cardiovascular disease Pooled Cohort Risk Equations. Lifetime risk was evaluated using the algorithm derived from the Framingham Heart Study cohort. Using previously published thresholds, participants were classified into 3 categories: low short-term and low lifetime risk, low short-term and high lifetime risk, and high short-term predicted risk. We also compared the distribution of these risk profiles across educational level, wealth index, and place of residence. We included 2844 participants (50% men, mean age 55.9 years [SD 10.2 years]) in the analysis. Approximately 1 of every 3 participants (34% [95% CI 33 to 36]) had a high short-term estimated cardiovascular disease risk. Among those with a low short-term predicted risk, more than half (54% [95% CI 52 to 56]) had a high lifetime predicted risk. Short-term and lifetime predicted risks were higher for participants with lower versus higher wealth indexes and educational levels and for those living in urban versus rural areas (P<0.01). These results were consistent by sex. Conclusions These findings highlight potential shortcomings of using short-term risk tools for primary prevention strategies because a substantial proportion of Peruvian adults were classified as low short-term risk but high lifetime risk. Vulnerable adults, such as those from low socioeconomic status and those living in urban areas, may need greater attention regarding cardiovascular preventive strategies. PMID:26254303

  16. Very short-term earthquake precursors from GPS signal interference: Case studies on moderate and large earthquakes in Taiwan

    NASA Astrophysics Data System (ADS)

    Yeh, Yu-Lien; Cheng, Kai-Chien; Wang, Wei-Hau; Yu, Shui-Beih

    2016-04-01

    We set up a GPS network with 17 Continuous GPS (CGPS) stations in southwestern Taiwan to monitor real-time crustal deformation. We found that systematic perturbations in GPS signals occurred just a few minutes prior to the occurrence of several moderate and large earthquakes, including the recent 2013 Nantou (ML = 6.5) and Rueisuei (ML = 6.4) earthquakes in Taiwan. The anomalous pseudorange readings were several millimeters higher or lower than those in the background time period. These systematic anomalies were found as a result of interference of GPS L-band signals by electromagnetic emissions (EMs) prior to the mainshocks. The EMs may occur in the form of harmonic or ultra-wide-band radiation and can be generated during the formation of Mode I cracks at the final stage of earthquake nucleation. We estimated the directivity of the likely EM sources by calculating the inner product of the position vector from a GPS station to a given satellite and the vector of anomalous ground motions recorded by the GPS. The results showed that the predominant inner product generally occurred when the satellite was in the direction either toward or away from the epicenter with respect to the GPS network. Our findings suggest that the GPS network may serve as a powerful tool to detect very short-term earthquake precursors and presumably to locate a large earthquake before it occurs.

  17. Visual short term memory related brain activity predicts mathematical abilities.

    PubMed

    Boulet-Craig, Aubrée; Robaey, Philippe; Lacourse, Karine; Jerbi, Karim; Oswald, Victor; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Jolicoeur, Pierre; Lippé, Sarah

    2017-07-01

    Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities are significantly related. Moreover, both processes activate similar brain regions within the parietal cortex, in particular, the intraparietal sulcus; however, it is still unclear whether the neuronal underpinnings of VSTM directly correlate with mathematical operation and reasoning abilities. The main objective was to investigate the association between parieto-occipital brain activity during the retention period of a VSTM task and performance in mathematics. The authors measured mathematical abilities and VSTM capacity as well as brain activity during memory maintenance using magnetoencephalography (MEG) in 19 healthy adult participants. Event-related magnetic fields (ERFs) were computed on the MEG data. Linear regressions were used to estimate the strength of the relation between VSTM related brain activity and mathematical abilities. The amplitude of parieto-occipital cerebral activity during the retention of visual information was related to performance in 2 standardized mathematical tasks: mathematical reasoning and calculation fluency. The findings show that brain activity during retention period of a VSTM task is associated with mathematical abilities. Contributions of VSTM processes to numerical cognition should be considered in cognitive interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  18. Very short-term earthquake precursors from GPS signal interference based on the 2013 Nantou and Rueisuei earthquakes, Taiwan

    NASA Astrophysics Data System (ADS)

    Yeh, Yu-Lien; Cheng, Kai-Chien; Wang, Wei-Hau; Yu, Shui-Beih

    2015-12-01

    We set up a GPS network with 17 Continuous GPS (CGPS) stations in southwestern Taiwan to monitor real-time crustal deformation. We found that systematic perturbations in GPS signals occurred just a few minutes prior to the 2013 Nantou (ML = 6.5) and Rueisuei (ML = 6.4) earthquakes in Taiwan. The anomalous pseudorange readings were several millimeters higher or lower than those in the background time period. These systematic anomalies were found as a result of interference of GPS L-band signals by electromagnetic emissions (EMs) prior to the mainshocks. The EMs may occur in the form of harmonic or ultra-wide-band radiation and can be generated during the formation of Mode I cracks at the final stage of earthquake nucleation. We estimated the directivity of the likely EM sources by calculating the inner product of the position vector from a GPS station to a given satellite and the vector of anomalous ground motions recorded by the GPS. The results showed that the predominant inner product generally occurred when the satellite was in the direction either toward or away from the epicenter with respect to the GPS network. Our findings suggest that the GPS network may serve as a powerful tool to detect very short-term earthquake precursors and presumably to locate a large earthquake before it occurs. Nevertheless, a direct measurement of EMs at the site of the GPS array is required in future studies to confirm this hypothesis.

  19. Earthquake prediction with electromagnetic phenomena

    SciTech Connect

    Hayakawa, Masashi

    2016-02-01

    Short-term earthquake (EQ) prediction is defined as prospective prediction with the time scale of about one week, which is considered to be one of the most important and urgent topics for the human beings. If this short-term prediction is realized, casualty will be drastically reduced. Unlike the conventional seismic measurement, we proposed the use of electromagnetic phenomena as precursors to EQs in the prediction, and an extensive amount of progress has been achieved in the field of seismo-electromagnetics during the last two decades. This paper deals with the review on this short-term EQ prediction, including the impossibility myth of EQs prediction by seismometers, the reason why we are interested in electromagnetics, the history of seismo-electromagnetics, the ionospheric perturbation as the most promising candidate of EQ prediction, then the future of EQ predictology from two standpoints of a practical science and a pure science, and finally a brief summary.

  20. Short-Term Price Prediction and the Selection of Indicators

    NASA Astrophysics Data System (ADS)

    Tanaka-Yamawaki, M.; Tokuoka, S.; Awaji, K.

    Although the prediction of the future price is known to be hard due to the strong randomness inherent in the price fluctuation, intra-day price movements are expected to be predicted by reading out the patterns observed in tick-wise price motions. Our first task on this line of thought is to identify the set of effective variables suitable for studying the problem. We have first constructed a price prediction generator that computes the best prediction by reading the data tick by tick. We report in this article the effect of the adaptive choice of the best combination of technical indicators out of ten popular indicators, and also the result of using a set of novel dimensionless dynamical indicators constructed from the local values of derivatives and the second derivatives of the price times series. We have obtained a good performance of nearly 70 percent of correctly predicted direction of motion at 10 ticks ahead of the prediction time by means of adaptive choice of the technical indicators, and even better performance in the second attempt of using the two dimensionless dynamical indicators.

  1. Earthquake catalogs for the 2017 Central and Eastern U.S. short-term seismic hazard model

    USGS Publications Warehouse

    Mueller, Charles S.

    2017-01-01

    The U. S. Geological Survey (USGS) makes long-term seismic hazard forecasts that are used in building codes. The hazard models usually consider only natural seismicity; non-tectonic (man-made) earthquakes are excluded because they are transitory or too small. In the past decade, however, thousands of earthquakes related to underground fluid injection have occurred in the central and eastern U.S. (CEUS), and some have caused damage.  In response, the USGS is now also making short-term forecasts that account for the hazard from these induced earthquakes. Seismicity statistics are analyzed to develop recurrence models, accounting for catalog completeness. In the USGS hazard modeling methodology, earthquakes are counted on a map grid, recurrence models are applied to estimate the rates of future earthquakes in each grid cell, and these rates are combined with maximum-magnitude models and ground-motion models to compute the hazard The USGS published a forecast for the years 2016 and 2017.Here, we document the development of the seismicity catalogs for the 2017 CEUS short-term hazard model.  A uniform earthquake catalog is assembled by combining and winnowing pre-existing source catalogs. The initial, final, and supporting earthquake catalogs are made available here.

  2. Predictable earthquakes?

    NASA Astrophysics Data System (ADS)

    Martini, D.

    2002-12-01

    acceleration) and global number of earthquake for this period from published literature which give us a great picture about the dynamical geophysical phenomena. Methodology: The computing of linear correlation coefficients gives us a chance to quantitatively characterise the relation among the data series, if we suppose a linear dependence in the first step. The correlation coefficients among the Earth's rotational acceleration and Z-orbit acceleration (perpendicular to the ecliptic plane) and the global number of the earthquakes were compared. The results clearly demonstrate the common feature of both the Earth's rotation and Earth's Z-acceleration around the Sun and also between the Earth's rotational acceleration and the earthquake number. This fact might means a strong relation among these phenomena. The mentioned rather strong correlation (r = 0.75) and the 29 year period (Saturn's synodic period) was clearly shown in the counted cross correlation function, which gives the dynamical characteristic of correlation, of Earth's orbital- (Z-direction) and rotational acceleration. This basic period (29 year) was also obvious in the earthquake number data sets with clear common features in time. Conclusion: The Core, which involves the secular variation of the Earth's magnetic field, is the only sufficiently mobile part of the Earth with a sufficient mass to modify the rotation which probably effects on the global time distribution of the earthquakes. Therefore it might means that the secular variation of the earthquakes is inseparable from the changes in Earth's magnetic field, i.e. the interior process of the Earth's core belongs to the dynamical state of the solar system. Therefore if the described idea is real the global distribution of the earthquakes in time is predictable.

  3. Invited contribution: an objective approach to the development of short-term tests predictive of carcinogenicity.

    PubMed

    Rosenkranz, H S; Ennever, F K; Chankong, V; Pet-Edwards, J; Haimes, Y Y

    1986-12-01

    The Carcinogenicity Prediction and Battery Selection procedure was developed to address two problems: (1) the identification of highly predictive, yet cost-effective, batteries of short-term tests and (2) the objective prediction of the potential carcinogenicity of chemicals based upon the results of short-term tests even when a mixture of positive and negative results is obtained. In the present report the usefulness of the Carcinogenicity Prediction and Battery Selection procedure is demonstrated using benzo[a]pyrene, benzoin and diethylstilbestrol as examples. In addition, its applicability in the analysis of all the possible outcomes of a battery is illustrated together with an analysis of the worth of additional testing.

  4. The nature of earthquake prediction

    USGS Publications Warehouse

    Lindh, A.G.

    1991-01-01

    Earthquake prediction is inherently statistical. Although some people continue to think of earthquake prediction as the specification of the time, place, and magnitude of a future earthquake, it has been clear for at least a decade that this is an unrealistic and unreasonable definition. the reality is that earthquake prediction starts from the long-term forecasts of place and magnitude, with very approximate time constraints, and progresses, at least in principle, to a gradual narrowing of the time window as data and understanding permit. Primitive long-term forecasts are clearly possible at this time on a few well-characterized fault systems. Tightly focuses monitoring experiments aimed at short-term prediction are already underway in Parkfield, California, and in the Tokai region in Japan; only time will tell how much progress will be possible. 

  5. Short-term memory predictions across the lifespan: monitoring span before and after conducting a task.

    PubMed

    Bertrand, Julie Marilyne; Moulin, Chris John Anthony; Souchay, Céline

    2017-05-01

    Our objective was to explore metamemory in short-term memory across the lifespan. Five age groups participated in this study: 3 groups of children (4-13 years old), and younger and older adults. We used a three-phase task: prediction-span-postdiction. For prediction and postdiction phases, participants reported with a Yes/No response if they could recall in order a series of images. For the span task, they had to actually recall such series. From 4 years old, children have some ability to monitor their short-term memory and are able to adjust their prediction after experiencing the task. However, accuracy still improves significantly until adolescence. Although the older adults had a lower span, they were as accurate as young adults in their evaluation, suggesting that metamemory is unimpaired for short-term memory tasks in older adults. •We investigate metamemory for short-term memory tasks across the lifespan. •We find younger children cannot accurately predict their span length. •Older adults are accurate in predicting their span length. •People's metamemory accuracy was related to their short-term memory span.

  6. Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

    PubMed

    Limongi, Roberto; Silva, Angélica M

    2016-11-01

    The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

  7. Modeling long- and short-term slow slip events and their interaction with large earthquakes along the Hikurangi subduction zone

    NASA Astrophysics Data System (ADS)

    Shibazaki, B.; Matsuzawa, T.; Wallace, L. M.; Ito, Y.

    2015-12-01

    Recent high-resolution geodetic observations revealed the occurrence of various slow slip events (SSEs) along the Hikurangi subduction plate interfaces. Long-term SSEs with a duration of 1.5 years (e.g., Manawatu SSEs) occur at the deeper portion of the Hikurangi subduction zone, and shallow short-term SSEs with a duration of 1-3 weeks occur along the northern and central parts of the subduction zone. Wallace et al. (2012) reported a sequence of simultaneous short-term and long-term SSEs along the Hikurangi subduction zone during 2010-2011. In the present study, we perform quasi-dynamic modeling on short-term and long-term SSEs along the Hikurangi subduction zone using a rate- and state-dependent friction law, while assigning realistic configurations of the plate interface. Based on the study of interseismic coupling by Wallace et al. (2009), we set the seismogenic zone where a-b is negative. We reproduce the long-term Manawatu SSEs and short-term shallow SSEs by setting the effective stress of these zones at 2.56 MPa and 0.48-0.64 MPa, respectively. The effective stress of the Manawatu SSE zone is approximately five times larger than that of the short-term SSE zones. However, the ratio of effective stress to critical displacement of the Manawatu SSE zone is smaller than that of the short-term SSE zones. A sequence of simultaneous short-term SSEs and the long-term Manawatu SSE can be reproduced as observed by Wallace et al. (2012). Long-term SSEs often trigger short-term SSEs that are located at the shallower extension of the Manawatu SSE zone. We also investigate the interaction between the SSEs and large earthquakes. A large earthquake nucleates at the southern segment and propagates to the northern narrow seismic zones. Slips occur even at the SSE zones, and these slips contribute to the size of the earthquake. The occurrence of the various slip processes suggests heterogeneous distributions of constitutive law parameters along the Hikurangi subduction zone.

  8. Real-time Seismicity Evaluation as a Tool for the Earthquake and Tsunami Short-Term Hazard Assessment (Invited)

    NASA Astrophysics Data System (ADS)

    Papadopoulos, G. A.

    2010-12-01

    Seismic activity is a 3-D process varying in the space-time-magnitude domains. When in a target area the short-term activity deviates significantly from the usual (background) seismicity, then the modes of activity may include swarms, temporary quiescence, foreshock-mainshock-aftershock sequences, doublets and multiplets. This implies that making decision for civil protection purposes requires short-term seismic hazard assessment and evaluation. When a sizable earthquake takes place the critical question is about the nature of the event: mainshock or a foreshock which foreshadows the occurrence of a biger one? Also, the seismicity increase or decrease in a target area may signify either precursory changes or just transient seismicity variations (e.g. swarms) which do not conclude with a strong earthquake. Therefore, the real-time seismicity evaluation is the backbone of the short-term hazard assessment. The algorithm FORMA (Foreshock-Mainshock-Aftershock) is presented which detects and updates automatically and in near real-time significant variations of the seismicity according to the earthquake data flow from the monitoring center. The detection of seismicity variations is based on an expert system which for a given target area indicates the mode of seismicity from the variation of two parameters: the seismicity rate, r, and the b-value of the magnitude-frequency relation. Alert levels are produced according to the significance levels of the changes of r and b. The good performance of FORMA was verified retrospectively in several earthquake cases, e.g. for the L’ Aquila, Italy, 2009 earthquake sequence (Mmax 6.3) (Papadopoulos et al., 2010). Real-time testing was executed during January 2010 with the strong earthquake activity (Mmax 5.6) in the Corinth Rift, Central Greece. Evaluation outputs were publicly documented on a nearly daily basis with successful results. Evaluation of coastal and submarine earthquake activity is also of crucial importance for the

  9. Long-term associative learning predicts verbal short-term memory performance.

    PubMed

    Jones, Gary; Macken, Bill

    2017-10-02

    Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

  10. A Strategy for Short-Term Earthquake Forecasting Based on Combined Ground and Space-Based Observations

    NASA Astrophysics Data System (ADS)

    Kafatos, M.; Papadopoulos, G. A.; Karastathis, V. K.; Minadakis, G.; Ouzounov, D.; Pulinets, S. A.; Tramutoli, V.; Tsinganos, K.

    2014-12-01

    No standard methodologies regarding the short-term (hours, days, few weeks) forecasting of earthquakes have been widely adopted so far. However, promising approaches from ground-based (e.g. foreshocks) and space-based (e.g. thermal anomalies) observations have been described. We propose to apply a multidisciplinary strategy by performing real-time experiments towards the identification of space-time windows having increased probability beyond chance for the occurrence of strong earthquakes (M>5.5). This is a new collaborative study which will continue the best practices achieved from other projects such as the EU-FP7 PRE-EARTHQUAKE and the ongoing ISSI project LAICa. The test region covers the entire Greece which is of the highest seismicity all over western Eurasia, while closer attention will be given to the Corinth Rift (Central Greece) which is an asymmetric half-graben of high seismicity opening rapidly with geodetic extension rates up to about 15mmyr-1. Ground-based observations will mainly include seismicity, magnetometers and radon measurements while space observations will include the ones that may provide thermal anomalies, GPS and TEC. The strategy will include the development of a system operating in real-time basis with strong tools and protocols for the collection, archiving and evaluation of the different types of data. The software part of the system may incorporate three basic interfaces implemented via open source technology: (1) The up-streaming software interface for the collection and archiving of data; (2) The backend real-time software interface incorporating all the available models; (3) The frontend WEBGIS software interface that will allow for data representation and mapping. The establishment of some certain rules for issuing non-public seismic alerts is needed. Therefore, in this paper we will also discuss the significance of the proposed work for the issues of earthquake forecasting/prediction statements and what critical new

  11. Multi-parameter observation of pre-earthquake signals and their potential for short -term earthquake forecasting

    NASA Astrophysics Data System (ADS)

    Kalenda, Pavel; Ouzounov, Dimitar; Bobrovskiy, Vadim; Neumann, Libor; Boborykina, Olga; Nazarevych, Andrij; Šebela, Stanka; Kvetko, Július; Shen, Wen-Bin

    2013-04-01

    We present methodologies for the multi-parameter observations of pre-earthquake phenomena and their retrospective/prospective testing. The hypothesis that the strongest earthquakes depend on the global stress field leads to global observations and a multi-parameter and multi-sensors approach. In 2012 we performed coordinated tests of several geophysical and environmental parameters, which are associated with the earthquakes preparation processes, namely: 1) Rocks deformation measurements (Kalenda et al. 2012); 2) Subterranean non-stationary electric processes (Bobrovskij 2011); 3) superconducting gravimeters (SGs) records and broadband seismometers (BS) time series (Shen et al); and 4) satellite infra-red observations (10-13 μm) measured at the top of the atmosphere (Ouzounov et al , 2011). In the retrospective test for the two most recent major events in Asia: Wenchuan earthquake (2008,China) and the latest Tohoku earthquake/tsunami (2011, Japan) our combined analysis showed a coordinated appearance of anomalies in advance (days) that could be explained by a coupling process between the observed physical parameters and the earthquake preparation processes. In 2012 three internal retrospective alerts were issued in advance (days) associated with the following events: M7.7 Okhotsk sea of August 14; M7.3 Honshu EQ of December 7 and M7.1 Banda sea EQ on December 10. Not all observations were able to detect anomalies before the M 7.4 Guatemala EQ of November 11. We discuss the reliability of each observation, their time lag, ability to localize and estimate the magnitude of the main shock. References Bobrovskij V. (2011): Kamchatkian Subterranean Electric Operative Forerunners of Catastrophic Earthquake with M9, occurred close to Honshu Island 2011/03/11 . IUGG Meeting Melbourne, 2011. postrer. Kalenda P. et al. (2012): Tilts, global tectonics and earthquake prediction. SWB, London, 247pp. Ozounov D. et al. (2011): Atmosphere-Ionosphere Response to the M9 Tohoku

  12. Predicting Changes in Cultural Sensitivity among Students of Spanish during Short-Term Study Abroad

    ERIC Educational Resources Information Center

    Martinsen, Rob

    2011-01-01

    Short-term study abroad programs of less than a semester are becoming increasingly popular among undergraduate students in the United States. However, little research has examined the changes in students' cultural sensitivity through their participation in such programs or what factors may predict growth and improvement in such areas. This study…

  13. Predicting Changes in Cultural Sensitivity among Students of Spanish during Short-Term Study Abroad

    ERIC Educational Resources Information Center

    Martinsen, Rob

    2011-01-01

    Short-term study abroad programs of less than a semester are becoming increasingly popular among undergraduate students in the United States. However, little research has examined the changes in students' cultural sensitivity through their participation in such programs or what factors may predict growth and improvement in such areas. This study…

  14. Predicting Time Series from Short-Term High-Dimensional Data

    NASA Astrophysics Data System (ADS)

    Ma, Huanfei; Zhou, Tianshou; Aihara, Kazuyuki; Chen, Luonan

    The prediction of future values of time series is a challenging task in many fields. In particular, making prediction based on short-term data is believed to be difficult. Here, we propose a method to predict systems' low-dimensional dynamics from high-dimensional but short-term data. Intuitively, it can be considered as a transformation from the inter-variable information of the observed high-dimensional data into the corresponding low-dimensional but long-term data, thereby equivalent to prediction of time series data. Technically, this method can be viewed as an inverse implementation of delayed embedding reconstruction. Both methods and algorithms are developed. To demonstrate the effectiveness of the theoretical result, benchmark examples and real-world problems from various fields are studied.

  15. Least squares support vector machine for short-term prediction of meteorological time series

    NASA Astrophysics Data System (ADS)

    Mellit, A.; Pavan, A. Massi; Benghanem, M.

    2013-01-01

    The prediction of meteorological time series plays very important role in several fields. In this paper, an application of least squares support vector machine (LS-SVM) for short-term prediction of meteorological time series (e.g. solar irradiation, air temperature, relative humidity, wind speed, wind direction and pressure) is presented. In order to check the generalization capability of the LS-SVM approach, a K-fold cross-validation and Kolmogorov-Smirnov test have been carried out. A comparison between LS-SVM and different artificial neural network (ANN) architectures (recurrent neural network, multi-layered perceptron, radial basis function and probabilistic neural network) is presented and discussed. The comparison showed that the LS-SVM produced significantly better results than ANN architectures. It also indicates that LS-SVM provides promising results for short-term prediction of meteorological data.

  16. The short-term prediction of universal time and length of day using atmospheric angular momentum

    NASA Technical Reports Server (NTRS)

    Freedman, A. P.; Steppe, J. A.; Dickey, J. O.; Eubanks, T. M.; Sung, L.-Y.

    1994-01-01

    The ability to predict short-term variations in the Earth's rotation has gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Earth's orientation corresponding to the rotation angle, can be measured by number of high-precision space geodetic techniques. A Kalman filter developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed times series and a set of predictions for UT1, as well as for additional Earth orientation components. These UT1 predictions utilize an empirically derived random walk stochastic model for the length of the day (LOD) and require frequent and up-to-date measurements of either UT1 or LOD to keep errors from quickly accumulating. Recent studies have shown that LOD variations are correlated with changes in the Earth's axial atmospheric angular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely available from meteorological analysis centers; these data can supplement geodetic measurements to improve the short-term prediction of LOD and have therefore been incorporated as independent data types in the JPL Kalman filter. We find that AAM and, to a lesser extent, AAM forecast data are extremely helpful in generating accurate near-real-time estimates of UT1 and LOD and in improving short-term predictions of these quantities out to about 10 days.

  17. The short-term prediction of universal time and length of day using atmospheric angular momentum

    NASA Technical Reports Server (NTRS)

    Freedman, A. P.; Steppe, J. A.; Dickey, J. O.; Eubanks, T. M.; Sung, L.-Y.

    1994-01-01

    The ability to predict short-term variations in the Earth's rotation has gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Earth's orientation corresponding to the rotation angle, can be measured by number of high-precision space geodetic techniques. A Kalman filter developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed times series and a set of predictions for UT1, as well as for additional Earth orientation components. These UT1 predictions utilize an empirically derived random walk stochastic model for the length of the day (LOD) and require frequent and up-to-date measurements of either UT1 or LOD to keep errors from quickly accumulating. Recent studies have shown that LOD variations are correlated with changes in the Earth's axial atmospheric angular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely available from meteorological analysis centers; these data can supplement geodetic measurements to improve the short-term prediction of LOD and have therefore been incorporated as independent data types in the JPL Kalman filter. We find that AAM and, to a lesser extent, AAM forecast data are extremely helpful in generating accurate near-real-time estimates of UT1 and LOD and in improving short-term predictions of these quantities out to about 10 days.

  18. Short-term prediction of wind power using EMD and chaotic theory

    NASA Astrophysics Data System (ADS)

    An, Xueli; Jiang, Dongxiang; Zhao, Minghao; Liu, Chao

    2012-02-01

    Due to the strong non-linear, complexity and non-stationary characteristics of wind farm power, a hybrid prediction model with empirical mode decomposition (EMD), chaotic theory, and grey theory is constructed. The EMD is used to decompose the wind farm power into several intrinsic mode function (IMF) components and one residual component. The grey forecasting model is used to predict the residual component. For the IMF components, identify their characteristics, if it is chaotic time series use largest Lyapunov exponent prediction method to predict. If not, use grey forecasting model to predict. Prediction results of residual component and all IMF components are aggregated to produce the ultimate predicted result for wind farm power. The ultimate predicted result shows that the proposed method has good prediction accuracy, can be used for short-term prediction of wind farm power.

  19. Improved Short-Term Clock Prediction Method for Real-Time Positioning

    PubMed Central

    Lv, Yifei; Dai, Zhiqiang; Zhao, Qile; Yang, Sheng; Zhou, Jinning; Liu, Jingnan

    2017-01-01

    The application of real-time precise point positioning (PPP) requires real-time precise orbit and clock products that should be predicted within a short time to compensate for the communication delay or data gap. Unlike orbit correction, clock correction is difficult to model and predict. The widely used linear model hardly fits long periodic trends with a small data set and exhibits significant accuracy degradation in real-time prediction when a large data set is used. This study proposes a new prediction model for maintaining short-term satellite clocks to meet the high-precision requirements of real-time clocks and provide clock extrapolation without interrupting the real-time data stream. Fast Fourier transform (FFT) is used to analyze the linear prediction residuals of real-time clocks. The periodic terms obtained through FFT are adopted in the sliding window prediction to achieve a significant improvement in short-term prediction accuracy. This study also analyzes and compares the accuracy of short-term forecasts (less than 3 h) by using different length observations. Experimental results obtained from International GNSS Service (IGS) final products and our own real-time clocks show that the 3-h prediction accuracy is better than 0.85 ns. The new model can replace IGS ultra-rapid products in the application of real-time PPP. It is also found that there is a positive correlation between the prediction accuracy and the short-term stability of on-board clocks. Compared with the accuracy of the traditional linear model, the accuracy of the static PPP using the new model of the 2-h prediction clock in N, E, and U directions is improved by about 50%. Furthermore, the static PPP accuracy of 2-h clock products is better than 0.1 m. When an interruption occurs in the real-time model, the accuracy of the kinematic PPP solution using 1-h clock prediction product is better than 0.2 m, without significant accuracy degradation. This model is of practical significance

  20. Prediction of short-term distributions of load extremes of offshore wind turbines

    NASA Astrophysics Data System (ADS)

    Wang, Ying-guang

    2016-12-01

    This paper proposes a new methodology to select an optimal threshold level to be used in the peak over threshold (POT) method for the prediction of short-term distributions of load extremes of offshore wind turbines. Such an optimal threshold level is found based on the estimation of the variance-to-mean ratio for the occurrence of peak values, which characterizes the Poisson assumption. A generalized Pareto distribution is then fitted to the extracted peaks over the optimal threshold level and the distribution parameters are estimated by the method of the maximum spacing estimation. This methodology is applied to estimate the short-term distributions of load extremes of the blade bending moment and the tower base bending moment at the mudline of a monopile-supported 5MW offshore wind turbine as an example. The accuracy of the POT method using the optimal threshold level is shown to be better, in terms of the distribution fitting, than that of the POT methods using empirical threshold levels. The comparisons among the short-term extreme response values predicted by using the POT method with the optimal threshold levels and with the empirical threshold levels and by using direct simulation results further substantiate the validity of the proposed new methodology.

  1. Tidal Current Short-Term Prediction Based on Support Vector Regression

    NASA Astrophysics Data System (ADS)

    Guozhen, Yang; Haifeng, Wang; Hui, Qian; Jianming, Fang

    2017-05-01

    The traditional method of short-term tidal current prediction, harmonic method, typically needs more than 18 years of history records. The method in the article uses univariate feature selection and F-test to reduce the dimension of the data fed to support vector regressor, which reduces the need of history records to less than a year. Model parameters are selected by grid searching and cross-validation. History records from two datasets are used to build prediction models, spanning 3 months and 1 year respectively. Mean average errors of both datasets after normalizing are less than 0.05.

  2. Do short-term markers of treatment efficacy predict long-term sequelae of PID?

    PubMed Central

    Trautmann, Gail M.; Kip, Kevin E.; Richter, Holly E.; Soper, David E.; Peipert, Jeffrey F.; Nelson, Deborah B.; Trout, Wayne; Schubeck, Dianne; Bass, Debra C.; Ness, Roberta B.

    2008-01-01

    Objective To assess whether short-term markers, often used to measure clinical cure after treatment for pelvic inflammatory disease (PID), predict sequelae of lack of pregnancy, recurrent PID, and chronic pelvic pain. Study Design Women with mild-to-moderate PID were assessed after treatment initiation at five days for tenderness (n=713) and at thirty days for tenderness, cervical infections and endometritis (n=298). Pregnancy, recurrent PID and chronic pelvic pain were evaluated after 84 months, on average. Results Pelvic tenderness at five and at thirty days significantly elevated the risk for developing chronic pelvic pain; tenderness at thirty days was also significantly associated with recurrent PID. However, pelvic tenderness at five and at thirty days were only modestly clinically predictive of chronic pelvic pain or recurrent PID (positive predictive values 22.1–66.9%). No short-term marker significantly influenced the likelihood of achieving a pregnancy. Conclusion Tenderness at 5 or 30 days did not accurately predict the occurrence of PID-related reproductive morbidities. CONCISE Tenderness at 5 or 30 days and microbiologic cure post-pelvic inflammatory disease treatment did not accurately predict long-term sequelae including chronic pelvic pain, fertility, and recurrence. PMID:18166300

  3. Learning and generalization tasks predict short-term cognitive outcome in nondemented elderly.

    PubMed

    Myers, Catherine E; Kluger, Alan; Golomb, James; Gluck, Mark A; Ferris, Steven

    2008-06-01

    This study examines whether behavioral measures obtained in nondemented elderly can predict cognitive status at 2-year follow-up. Prior studies have established that delayed paragraph recall can help predict short-term risk for decline to mild cognitive impairment and Alzheimer disease. It was examined whether prediction accuracy can be improved by adding a discrimination-and-generalization task that has previously been shown to be disrupted in nondemented elderly with hippocampal atrophy, a risk factor for Alzheimer disease. Fifty nondemented, medically healthy elderly patients received baseline clinical diagnosis and cognitive testing; 2 years later, patients received a follow-up clinical diagnosis of normal, mild cognitive impairment, or probable Alzheimer disease. In all, 2 baseline variables, delayed paragraph recall and generalization performance, were predictive of follow-up outcome with sensitivity of 81% and specificity of 91%-better than the classification accuracy based on either of these measures alone. These preliminary results suggest that these behavioral tasks may be useful tools in predicting short-term cognitive outcome in nondemented elderly.

  4. Short Term Weather Forecasting and Long Term Climate Predictions in Mesoamerica

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Daniel, I.; Mecikalski, J.; Graves, S.

    2008-05-01

    The SERVIR project utilizes several predictive models to support regional monitoring and decision support in Mesoamerica. Short term forecasts ranging from a few hours to several days produce more than 30 data products that are used daily by decision makers, as well as news organizations in the region. The forecast products can be visualized in both two and three dimensional viewers such as Google Maps and Google Earth. Other viewers developed specifically for the Mesoamerican region by the University of Alabama in Huntsville and the Institute for the Application of Geospatial Technologies in Auburn New York can also be employed. In collaboration with the NASA Short Term Prediction Research and Transition (SpoRT) Center SERVIR utilizes the Weather Research and Forecast (WRF) model to produce short-term (24 hr) regional weather forecasts twice a day. Temperature, precipitation, wind, and other variables are forecast in 10km and 30km grids over the Mesoamerica region. Using the PSU/NCAR Mesoscale Model, known as MM5, SERVIR produces 48 hour- forecasts of soil temperature, two meter surface temperature, three hour accumulated precipitation, winds at different heights, and other variables. These are forecast hourly in 9km grids. Working in collaboration with the Atmospheric Science Department of the University of Alabama in Huntsville produces a suite of short-term (0-6 hour) weather prediction products are generated. These "convective initiation" products predict the onset of thunderstorm rainfall and lightning within a 1-hour timeframe. Models are also employed for long term predictions. The SERVIR project, under USAID funding, has developed comprehensive regional climate change scenarios of Mesoamerica for future years: 2010, 2015, 2025, 2050, and 2099. These scenarios were created using the Pennsylvania State University/National Center for Atmospheric Research (MM5) model and processed on the Oak Ridge National Laboratory Cheetah supercomputer. The goal of these

  5. Earthquakes: Predicting the unpredictable?

    USGS Publications Warehouse

    Hough, S.E.

    2005-01-01

    The earthquake prediction pendulum has swung from optimism in the 1970s to rather extreme pessimism in the 1990s. Earlier work revealed evidence of possible earthquake precursors: physical changes in the planet that signal that a large earthquake is on the way. Some respected earthquake scientists argued that earthquakes are likewise fundamentally unpredictable. The fate of the Parkfield prediction experiment appeared to support their arguments: A moderate earthquake had been predicted along a specified segment of the central San Andreas fault within five years of 1988, but had failed to materialize on schedule. At some point, however, the pendulum began to swing back. Reputable scientists began using the "P-word" in not only polite company, but also at meetings and even in print. If the optimism regarding earthquake prediction can be attributed to any single cause, it might be scientists' burgeoning understanding of the earthquake cycle.

  6. Earthquakes: Predicting the unpredictable?

    USGS Publications Warehouse

    Hough, Susan E.

    2005-01-01

    The earthquake prediction pendulum has swung from optimism in the 1970s to rather extreme pessimism in the 1990s. Earlier work revealed evidence of possible earthquake precursors: physical changes in the planet that signal that a large earthquake is on the way. Some respected earthquake scientists argued that earthquakes are likewise fundamentally unpredictable. The fate of the Parkfield prediction experiment appeared to support their arguments: A moderate earthquake had been predicted along a specified segment of the central San Andreas fault within five years of 1988, but had failed to materialize on schedule. At some point, however, the pendulum began to swing back. Reputable scientists began using the "P-word" in not only polite company, but also at meetings and even in print. If the optimism regarding earthquake prediction can be attributed to any single cause, it might be scientists' burgeoning understanding of the earthquake cycle.

  7. Computational classifiers for predicting the short-term course of Multiple sclerosis

    PubMed Central

    2011-01-01

    Background The aim of this study was to assess the diagnostic accuracy (sensitivity and specificity) of clinical, imaging and motor evoked potentials (MEP) for predicting the short-term prognosis of multiple sclerosis (MS). Methods We obtained clinical data, MRI and MEP from a prospective cohort of 51 patients and 20 matched controls followed for two years. Clinical end-points recorded were: 1) expanded disability status scale (EDSS), 2) disability progression, and 3) new relapses. We constructed computational classifiers (Bayesian, random decision-trees, simple logistic-linear regression-and neural networks) and calculated their accuracy by means of a 10-fold cross-validation method. We also validated our findings with a second cohort of 96 MS patients from a second center. Results We found that disability at baseline, grey matter volume and MEP were the variables that better correlated with clinical end-points, although their diagnostic accuracy was low. However, classifiers combining the most informative variables, namely baseline disability (EDSS), MRI lesion load and central motor conduction time (CMCT), were much more accurate in predicting future disability. Using the most informative variables (especially EDSS and CMCT) we developed a neural network (NNet) that attained a good performance for predicting the EDSS change. The predictive ability of the neural network was validated in an independent cohort obtaining similar accuracy (80%) for predicting the change in the EDSS two years later. Conclusions The usefulness of clinical variables for predicting the course of MS on an individual basis is limited, despite being associated with the disease course. By training a NNet with the most informative variables we achieved a good accuracy for predicting short-term disability. PMID:21649880

  8. Earthquake Prediction and Forecasting

    NASA Astrophysics Data System (ADS)

    Jackson, David D.

    Prospects for earthquake prediction and forecasting, and even their definitions, are actively debated. Here, "forecasting" means estimating the future earthquake rate as a function of location, time, and magnitude. Forecasting becomes "prediction" when we identify special conditions that make the immediate probability much higher than usual and high enough to justify exceptional action. Proposed precursors run from aeronomy to zoology, but no identified phenomenon consistently precedes earthquakes. The reported prediction of the 1975 Haicheng, China earthquake is often proclaimed as the most successful, but the success is questionable. An earthquake predicted to occur near Parkfield, California in 1988±5 years has not happened. Why is prediction so hard? Earthquakes start in a tiny volume deep within an opaque medium; we do not know their boundary conditions, initial conditions, or material properties well; and earthquake precursors, if any, hide amongst unrelated anomalies. Earthquakes cluster in space and time, and following a quake earthquake probability spikes. Aftershocks illustrate this clustering, and later earthquakes may even surpass earlier ones in size. However, the main shock in a cluster usually comes first and causes the most damage. Specific models help reveal the physics and allow intelligent disaster response. Modeling stresses from past earthquakes may improve forecasts, but this approach has not yet been validated prospectively. Reliable prediction of individual quakes is not realistic in the foreseeable future, but probabilistic forecasting provides valuable information for reducing risk. Recent studies are also leading to exciting discoveries about earthquakes.

  9. Sensory evoked potentials to predict short-term progression of disability in multiple sclerosis.

    PubMed

    Margaritella, N; Mendozzi, L; Garegnani, M; Colicino, E; Gilardi, E; Deleonardis, L; Tronci, F; Pugnetti, L

    2012-08-01

    To devise a multivariate parametric model for short-term prediction of disability using the Expanded Disability Status Scale (EDSS) and multimodal sensory EP (mEP). A total of 221 multiple sclerosis (MS) patients who underwent repeated mEP and EDSS assessments at variable time intervals over a 20-year period were retrospectively analyzed. Published criteria were used to compute a cumulative score (mEPS) of abnormalities for each of 908 individual tests. Data of a statistically balanced sample of 58 patients were fed to a parametrical regression analysis using time-lagged EDSS and mEPS along with other clinical variables to estimate future EDSS scores at 1 year. Whole sample cross-sectional mEPS were moderately correlated with EDSS, whereas longitudinal mEPS were not. Using the regression model, lagged mEPS and lagged EDSS along with clinical variables provided better future EDSS estimates. The R (2) measure of fit was significant and 72% of EDSS estimates showed an error value of ±0.5. A parametrical regression model combining EDSS and mEPS accurately predicts short-term disability in MS patients and could be used to optimize decisions concerning treatment.

  10. Study on short term prediction using observed water quality from 8-day intervals in Nakdong river

    NASA Astrophysics Data System (ADS)

    Kim, M.; Shon, T.; Joo, J.; Kim, J.; Shin, H.

    2012-12-01

    There are lots of accidents on water quality, like green algal blooms, occurring in Nakdong river which is one of the largest river in Korea. This is because of climate change around the world. It is essential to develop scientific and quantitative assessment methods. In this study, artificial neural network based on back propagation algorithm, which is simple and flexible method, was used for forecasting the water quality on the purpose of water resources management. Especially, as used observed water quality data from 8-day intervals in Nakdong river, it makes to increase the accuracy of water quality forecast over short term. This was established for predicting the water quality factors 1, 3, and 7 days ahead. The best model, as evaluated by its performance functions with RMSE and R2, was selected and applied to established models of BOD, DO, COD, and Chl-a using artificial neural network. The results showed that the models were suitable for 1 and 3 days forecasts in particular. This method is strong and convenient to predict water quality factors over the short term easily based on observed data. It is possible to overcome and manage problems related to the water resources. In the future, this will be a powerful method because it is basically based on observed water quality data.

  11. Neural activity in the hippocampus predicts individual visual short-term memory capacity.

    PubMed

    von Allmen, David Yoh; Wurmitzer, Karoline; Martin, Ernst; Klaver, Peter

    2013-07-01

    Although the hippocampus had been traditionally thought to be exclusively involved in long-term memory, recent studies raised controversial explanations why hippocampal activity emerged during short-term memory tasks. For example, it has been argued that long-term memory processes might contribute to performance within a short-term memory paradigm when memory capacity has been exceeded. It is still unclear, though, whether neural activity in the hippocampus predicts visual short-term memory (VSTM) performance. To investigate this question, we measured BOLD activity in 21 healthy adults (age range 19-27 yr, nine males) while they performed a match-to-sample task requiring processing of object-location associations (delay period  =  900 ms; set size conditions 1, 2, 4, and 6). Based on individual memory capacity (estimated by Cowan's K-formula), two performance groups were formed (high and low performers). Within whole brain analyses, we found a robust main effect of "set size" in the posterior parietal cortex (PPC). In line with a "set size × group" interaction in the hippocampus, a subsequent Finite Impulse Response (FIR) analysis revealed divergent hippocampal activation patterns between performance groups: Low performers (mean capacity  =  3.63) elicited increased neural activity at set size two, followed by a drop in activity at set sizes four and six, whereas high performers (mean capacity  =  5.19) showed an incremental activity increase with larger set size (maximal activation at set size six). Our data demonstrated that performance-related neural activity in the hippocampus emerged below capacity limit. In conclusion, we suggest that hippocampal activity reflected successful processing of object-location associations in VSTM. Neural activity in the PPC might have been involved in attentional updating.

  12. Development of a fast and reliable method for long- and short-term wine age prediction.

    PubMed

    Pereira, Ana C; Reis, Marco S; Saraiva, Pedro M; Marques, José C

    2011-10-30

    Wine age prediction based on its intrinsic characteristics can provide significant assistance to oenologists' quality evaluations, concerning wine ageing process control and wine quality assurance. Simpler, faster, cheaper and affordable analytical procedures would be greatly welcome to establish such a practice. In this study, we present a new and reliable strategy to predict wine age, in the long and short-term, centered on the use of wine UV-vis absorbance data, coupled with proper chemometric techniques. The strategy followed consists essentially in first pre-processing the UV-vis data, secondly to carry out variable selection over such pre-processed data sets, and finally to use the set of selected variables for developing a PLS model focused on wine age prediction. We tested different data pre-processing methodologies, namely first and second derivatives, multiplicative scatter correction, standard normal variate and orthogonal signal correction, as well as different variable selection approaches, specifically interval partial least squares, VIPS, genetic algorithms and the wavelet transformation combined with a genetic algorithm. In both case studies, regarding long and short-term ageing periods, we have found out that it is indeed possible to predict wine ages, in our case Madeira wine ages, with an accuracy of 1.4 years for longer ageing periods, and of 3 months for wines of an age comprised in the first two years of ageing. The genetic algorithm revealed to be very useful for proper wavelet coefficients selection, leading to the most parsimonious model among all those analyzed, which also presents the best predictive performance found. Copyright © 2011 Elsevier B.V. All rights reserved.

  13. Short term prediction of dynamic hydra precipitation activity using a microwave radiometer over Eastern Himalaya, India

    NASA Astrophysics Data System (ADS)

    Singh, S.

    2015-12-01

    First ever study of the feasibility of ground based radiometric study to predict a very short term based rain precipitation study has been conducted in eastern Himalaya, Darjeeling (27.01°N, 88.15°E, 2200 masl). Short term prediction or nowcasting relates to forecasting convective precipitation for time periods less than a few hours to avoid its effect on agriculture, aviation and lifestyle. Theoretical models involving radiometric predictions are not well understood and lack in temporal and spatial resolution. In this study specific utilization of a microwave Radiometer (Radiometrics Corporation, USA) for online monitoring of precipitable rainfall activity has been observed repeatability of data has been established. Previous few studies have shown the increase of water vapour and corresponding Brightness Temperature, but in mountain climatic conditions over Darjeeling, due to presence of fog 90 % of the year, water vapour monitoring related predictions can lead to false alarms. The measurement of blackbody emission noise in the bands of 23.8 GHz and 31.4 GHz, using a quadratic regression retrieval algorithm is converted to atmospheric parameters like integrated water vapour and liquid water content. It has been found in our study that the liquid water shows significant activity prior to precipitation events even for mild and stratiform rainfall. The alarm can be generated well 20 mins before the commencement of actual rain events even in the upper atmosphere of 6 Kms, measured by a rain radar also operating in 24 Ghz microwave band. Although few rain events were found and reported which do not respond in the microwave liquid water channel. Efforts to identify such rain events and their possible explanation is going on and shall be reported in near future. Such studies are important to predict flash flooding in the Himalayas. Darjeeling owing to its geographical conditions experiences mild to very heavy rain. Such studies help improve aspects of Himalayas as

  14. Early Measurement of Indocyanine Green Clearance Accurately Predicts Short-Term Outcomes After Liver Transplantation.

    PubMed

    Olmedilla, Luis; Lisbona, Cristina J; Pérez-Peña, José M; López-Baena, José A; Garutti, Ignacio; Salcedo, Magdalena; Sanz, Javier; Tisner, Manuel; Asencio, José M; Fernández-Quero, Lorenzo; Bañares, Rafael

    2016-03-01

    There are no accurate tools to predict short-term mortality or the need for early retransplantation after liver transplantation (LT). A noninvasive measurement of indocyanine green clearance, the plasma disappearance rate (PDR), has been associated with initial graft function. We evaluated the ability of PDR to predict early mortality or retransplantation after LT. In this observational prospective study, 332 LT were analyzed. Donor, recipient, and intraoperative data were investigated. The ensuing score was prospectively evaluated in a validation cohort of 77 patients. Thirty-three patients reached the main endpoint. By multivariate analysis, the only independent predictors of the endpoint were PDR (odds ratio [OR], 0.85; 95% confidence interval, 0.79-0.92) and international normalized ratio (OR, 1.45; 95% confidence interval, 1.17-1.82). A risk score weighted by the OR was built using cutoff values of 2.2 or greater for international normalized ratio (1 point) and less than 10%/min for PDR (2 points). Four categories (0 to 3) were possible. The risk of early death or retransplantation was associated with the score (0, 4.4%; 1, 6.5%; 2, 12%; and 3, 50%; χ for trend, P < 0.001). The score was also associated with duration of mechanical ventilation and intensive care unit stay. The score had a good diagnostic performance in the validation cohort (sensitivity, 60%; specificity, 95.5%; positive predictive value, 66.7%; negative predictive value, 94.1%). A simple score obtained within the first day after LT predicts short-term survival and need for retransplantation and may prove useful when selecting diagnostic and therapeutic strategies.

  15. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.

    PubMed

    Li, Xiang; Peng, Ling; Yao, Xiaojing; Cui, Shaolong; Hu, Yuan; You, Chengzeng; Chi, Tianhe

    2017-09-08

    Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13-24 h prediction tasks (MAPE = 31.47%). Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Chaotic analysis and short-term prediction of ozone pollution in Malaysian urban area

    NASA Astrophysics Data System (ADS)

    Hamid, Nor Zila Abd; Noorani, Mohd Salmi Md; Hamiza Adenan, Nur

    2017-09-01

    This study focuses on the analysis and prediction of hourly ozone (O3) pollution in one of Malaysian urban area namely Shah Alam through chaotic approach. This approach begins by detecting the chaotic behavior of the O3 pollution using phase space plot and Cao method. Then, the local mean approximation method is used for prediction purposes. The O3 pollution observed at Shah Alam is detected as chaotic in behavior. Due to the chaotic behavior, only short-term prediction is allowed. Thus, the one-hour ahead prediction is done through the local mean approximation method. The prediction result shows that correlation coefficient value between the observed and predicted time series is near to one. This excellent prediction result shows in particular that the local mean approximation method can be used to predict the O3 pollution in urban area. In general, chaotic approach is a useful approach that can be used to analyze and predict the O3 pollution time series.

  17. Global velocity constrained cloud motion prediction for short-term solar forecasting

    NASA Astrophysics Data System (ADS)

    Chen, Yanjun; Li, Wei; Zhang, Chongyang; Hu, Chuanping

    2016-09-01

    Cloud motion is the primary reason for short-term solar power output fluctuation. In this work, a new cloud motion estimation algorithm using a global velocity constraint is proposed. Compared to the most used Particle Image Velocity (PIV) algorithm, which assumes the homogeneity of motion vectors, the proposed method can capture the accurate motion vector for each cloud block, including both the motional tendency and morphological changes. Specifically, global velocity derived from PIV is first calculated, and then fine-grained cloud motion estimation can be achieved by global velocity based cloud block researching and multi-scale cloud block matching. Experimental results show that the proposed global velocity constrained cloud motion prediction achieves comparable performance to the existing PIV and filtered PIV algorithms, especially in a short prediction horizon.

  18. Physical bases of the generation of short-term earthquake precursors: A complex model of ionization-induced geophysical processes in the lithosphere-atmosphere-ionosphere-magnetosphere system

    NASA Astrophysics Data System (ADS)

    Pulinets, S. A.; Ouzounov, D. P.; Karelin, A. V.; Davidenko, D. V.

    2015-07-01

    This paper describes the current understanding of the interaction between geospheres from a complex set of physical and chemical processes under the influence of ionization. The sources of ionization involve the Earth's natural radioactivity and its intensification before earthquakes in seismically active regions, anthropogenic radioactivity caused by nuclear weapon testing and accidents in nuclear power plants and radioactive waste storage, the impact of galactic and solar cosmic rays, and active geophysical experiments using artificial ionization equipment. This approach treats the environment as an open complex system with dissipation, where inherent processes can be considered in the framework of the synergistic approach. We demonstrate the synergy between the evolution of thermal and electromagnetic anomalies in the Earth's atmosphere, ionosphere, and magnetosphere. This makes it possible to determine the direction of the interaction process, which is especially important in applications related to short-term earthquake prediction. That is why the emphasis in this study is on the processes proceeding the final stage of earthquake preparation; the effects of other ionization sources are used to demonstrate that the model is versatile and broadly applicable in geophysics.

  19. Baroreflex Sensitivity Predicts Short-Term Outcome of Postural Tachycardia Syndrome in Children

    PubMed Central

    Li, Hongxia; Liao, Ying; Wang, Yuli; Liu, Ping; Sun, Chufan; Chen, Yonghong; Tang, Chaoshu; Jin, Hongfang; Du, Junbao

    2016-01-01

    Objective The study was designed to examine if baroreflex sensitivity (BRS) could predict the short-term outcome of postural tachycardia syndrome (POTS) in children. Methods Seventy-seven children subjects were included in the study. Among them, 45 children were in the POTS group and another 32 healthy children were in the control group. A ninety-day clinical follow-up was conducted and the symptom score before and after the follow-up was calculated for POTS patients by using POTS score system. Hemodynamics and continuous BRS monitoring were recorded by Finapres Medical System-FMS (FinometerPRO, FMS Company, Netherlands). According to the symptom score change during follow-up period, POTS patients were further divided into subgroup A (n = 24) with symptom score decreased by at least two points and subgroup B (n = 21) with symptom score decreased by less than two points. The predictive value of BRS in the short-term outcome of POTS in children was analyzed using receiver-operating characteristic (ROC) curve. Results BRS of POTS children was significantly higher than that of the healthy children (18.76±9.96 ms/mmHg vs 10±5.42 ms/mmHg, P<0.01). It was higher in subgroup B than that of subgroup A (24.7±9.9 ms/mmHg vs 13.5±6.6 ms/mmHg, P <0.01). BRS was positively correlated with HR change in POTS Group (r = 0.304, P <0.05). Area under curve (AUC) was 0.855 (95% of confidence interval 0.735–0.975), and BRS of 17.01 ms/mmHg as a cut-off value yielded the predictive sensitivity of 85.7% and specificity of 87.5%. Conclusions BRS is a useful index to predict the short-term outcome of POTS in children. PMID:27936059

  20. Possibility of short-term probabilistic forecasts for large earthquakes making good use of the limitations of existing catalogs

    NASA Astrophysics Data System (ADS)

    Hirata, Yoshito; Iwayama, Koji; Aihara, Kazuyuki

    2016-10-01

    Earthquakes are quite hard to predict. One of the possible reasons can be the fact that the existing catalogs of past earthquakes are limited at most to the order of 100 years, while their characteristic time scale is sometimes greater than that time span. Here we rather use these limitations positively and characterize some large earthquake events as abnormal events that are not included there. When we constructed probabilistic forecasts for large earthquakes in Japan based on similarity and difference to their past patterns—which we call known and unknown abnormalities, respectively—our forecast achieved probabilistic gains of 5.7 and 2.4 against a time-independent model for main shocks with the magnitudes of 7 or above. Moreover, the two abnormal conditions covered 70% of days whose maximum magnitude was 7 or above.

  1. Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

    PubMed

    Ak, Ronay; Fink, Olga; Zio, Enrico

    2016-08-01

    The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

  2. Prediction of Non-Genotoxic Carcinogenicity Based on Genetic Profiles of Short Term Exposure Assays.

    PubMed

    Pérez, Luis Orlando; González-José, Rolando; García, Pilar Peral

    2016-10-01

    Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

  3. Prediction of Non-Genotoxic Carcinogenicity Based on Genetic Profiles of Short Term Exposure Assays

    PubMed Central

    Pérez, Luis Orlando; González-José, Rolando; García, Pilar Peral

    2016-01-01

    Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points. PMID:27818731

  4. Saddle Pulmonary Embolism: Laboratory and Computed Tomographic Pulmonary Angiographic Findings to Predict Short-term Mortality.

    PubMed

    Liu, Min; Miao, Ran; Guo, Xiaojuan; Zhu, Li; Zhang, Hongxia; Hou, Qing; Guo, Youmin; Yang, Yuanhua

    2017-02-01

    Saddle pulmonary embolism (SPE) is rare type of acute pulmonary embolism and there is debate about its treatment and prognosis. Our aim is to assess laboratory and computed tomographic pulmonary angiographic (CTPA) findings to predict short-term mortality in patients with SPE. This was a five-centre, retrospective study. The clinical information, laboratory and CTPA findings of 88 consecutive patients with SPE were collected. One-month mortality after diagnosis of SPE was the primary end-point. The correlation of laboratory and CTPA findings with one-month mortality was analysed with area under curve (AUC) of receiver operating characteristic (ROC) curves and logistic regression analysis. Eighteen patients with SPE died within one month. Receiver operating characteristic curves revealed that the cutoff values for the right and left atrial diameter ratio, the right ventricular area and left ventricular area ratio (RVa/LVa ratio), Mastora score, septal angle, N-terminal pro-brain natriuretic peptide and cardiac troponin I (cTnI) for detecting early mortality were 2.15, 2.13, 69%, 57°, 3036 pg/mL and 0.18ng/mL, respectively. Using logistic regression analysis of laboratory and CTPA findings with regard to one-month mortality of SPE, RVa/LVa ratio and cTnI were shown to be independently associated with early death. A combination of cTnI and RVa/LVa ratio revealed an increase in the AUC value, but the difference did not reach significance compared with RVa/LVa or cTnI, alone (P>0.05). In patients with SPE, both the RVa/LVa ratio on CTPA and cTnI appear valuable for the prediction of short-term mortality. Copyright © 2016 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

  5. Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

    NASA Astrophysics Data System (ADS)

    Mohammed, E.; Wang, S.; Yu, J.

    2017-05-01

    This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

  6. A score to predict short-term risk of COPD exacerbations (SCOPEX).

    PubMed

    Make, Barry J; Eriksson, Göran; Calverley, Peter M; Jenkins, Christine R; Postma, Dirkje S; Peterson, Stefan; Östlund, Ollie; Anzueto, Antonio

    2015-01-01

    There is no clinically useful score to predict chronic obstructive pulmonary disease (COPD) exacerbations. We aimed to derive this by analyzing data from three existing COPD clinical trials of budesonide/formoterol, formoterol, or placebo in patients with moderate-to-very-severe COPD and a history of exacerbations in the previous year. Predictive variables were selected using Cox regression for time to first severe COPD exacerbation. We determined absolute risk estimates for an exacerbation by identifying variables in a binomial model, adjusting for observation time, study, and treatment. The model was further reduced to clinically useful variables and the final regression coefficients scaled to obtain risk scores of 0-100 to predict an exacerbation within 6 months. Receiver operating characteristic (ROC) curves and the corresponding C-index were used to investigate the discriminatory properties of predictive variables. The best predictors of an exacerbation in the next 6 months were more COPD maintenance medications prior to the trial, higher mean daily reliever use, more exacerbations during the previous year, lower forced expiratory volume in 1 second/forced vital capacity ratio, and female sex. Using these risk variables, we developed a score to predict short-term (6-month) risk of COPD exacerbations (SCOPEX). Budesonide/formoterol reduced future exacerbation risk more than formoterol or as-needed short-acting β2-agonist (salbutamol). SCOPEX incorporates easily identifiable patient characteristics and can be readily applied in clinical practice to target therapy to reduce COPD exacerbations in patients at the highest risk.

  7. Using Long-Short-Term-Memory Recurrent Neural Networks to Predict Aviation Engine Vibrations

    NASA Astrophysics Data System (ADS)

    ElSaid, AbdElRahman Ahmed

    This thesis examines building viable Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) neurons to predict aircraft engine vibrations. The different networks are trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, and this database contains multiple types of engines. Further, LSTM RNNs provide a "memory" of the contribution of previous time series data which can further improve predictions of future vibration values. LSTM RNNs were used over traditional RNNs, as those suffer from vanishing/exploding gradients when trained with back propagation. The study managed to predict vibration values for 1, 5, 10, and 20 seconds in the future, with 2.84% 3.3%, 5.51% and 10.19% mean absolute error, respectively. These neural networks provide a promising means for the future development of warning systems so that suitable actions can be taken before the occurrence of excess vibration to avoid unfavorable situations during flight.

  8. Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

    PubMed

    Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

    2017-03-01

    Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online.

  9. Short-Term Variation of the Fetal Heart Rate for Predicting Neonatal Acidosis in Preeclampsia.

    PubMed

    Aernout, Eva Marie; Devos, Patrick; Deruelle, Philippe; Houfflin-Debarge, Véronique; Subtil, Damien

    2015-01-01

    The aim of this study was to measure the performance of short-term variation (STV) in predicting the onset of neonatal acidosis in fetuses at risk due to maternal preeclampsia. This retrospective study examined data from a series of 159 women with singleton pregnancies, hospitalized for preeclampsia in a level 3 reference maternity hospital in northern France, with an STV measurement in the 24 h preceding cesarean delivery and a measurement of the newborn's arterial cord pH at birth. The main outcome was determined by a correlation between STV and neonatal pH. The last computerized fetal heart rate analysis took place a mean of 7.9 ± 6.3 h before birth, and neonatal acidosis was diagnosed in 38 newborns (23.9%). Although STV and umbilical artery pH at birth were significantly correlated (x03C1; = 0.16, p < 0.05), the performance of STV in predicting neonatal acidosis was poor, with an area under the ROC curve of 0.63. The sensitivity reached only 50.0% and the specificity 71.9% at the best STV threshold for predicting acidosis. The performance of STV for screening for neonatal acidosis is poor in women with preeclampsia. The divergent results between studies are probably due to the variable intervals between STV measurement and birth. © 2015 S. Karger AG, Basel.

  10. Short-term solar flare prediction using multi-model integration method

    NASA Astrophysics Data System (ADS)

    Liu, Jin-Fu; Li, Fei; Wan, Jie; Yu, Da-Ren

    2017-03-01

    A multi-model integration method is proposed to develop a multi-source and heterogeneous model for short-term solar flare prediction. Different prediction models are constructed on the basis of extracted predictors from a pool of observation databases. The outputs of the base models are normalized first because these established models extract predictors from many data resources using different prediction methods. Then weighted integration of the base models is used to develop a multi-model integrated model (MIM). The weight set that single models assign is optimized by a genetic algorithm. Seven base models and data from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms are used to construct the MIM, and then its performance is evaluated by cross validation. Experimental results showed that the MIM outperforms any individual model in nearly every data group, and the richer the diversity of the base models, the better the performance of the MIM. Thus, integrating more diversified models, such as an expert system, a statistical model and a physical model, will greatly improve the performance of the MIM.

  11. Markers of preparatory attention predict visual short-term memory performance.

    PubMed

    Murray, Alexandra M; Nobre, Anna C; Stokes, Mark G

    2011-05-01

    Visual short-term memory (VSTM) is limited in capacity. Therefore, it is important to encode only visual information that is most likely to be relevant to behaviour. Here we asked which aspects of selective biasing of VSTM encoding predict subsequent memory-based performance. We measured EEG during a selective VSTM encoding task, in which we varied parametrically the memory load and the precision of recall required to compare a remembered item to a subsequent probe item. On half the trials, a spatial cue indicated that participants only needed to encode items from one hemifield. We observed a typical sequence of markers of anticipatory spatial attention: early attention directing negativity (EDAN), anterior attention directing negativity (ADAN), late directing attention positivity (LDAP); as well as of VSTM maintenance: contralateral delay activity (CDA). We found that individual differences in preparatory brain activity (EDAN/ADAN) predicted cue-related changes in recall accuracy, indexed by memory-probe discrimination sensitivity (d'). Importantly, our parametric manipulation of memory-probe similarity also allowed us to model the behavioural data for each participant, providing estimates for the quality of the memory representation and the probability that an item could be retrieved. We found that selective encoding primarily increased the probability of accurate memory recall; that ERP markers of preparatory attention predicted the cue-related changes in recall probability.

  12. Short-term solar flare prediction using multi-model integration method

    NASA Astrophysics Data System (ADS)

    Liu, Jin-Fu; Li, Fei; Wan, Jie; Yu, Da-Ren

    2017-03-01

    A multi-model integration method is proposed to develop a multi-source and heterogeneous model for short-term solar flare prediction. Different prediction models are constructed on the basis of extracted predictors from a pool of observation databases. The outputs of the base models are normalized first because these established models extract predictors from many data resources using different prediction methods. Then weighted integration of the base models is used to develop a multi-model integrated model (MIM). The weight set that single models assign is optimized by a genetic algorithm. Seven base models and data from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms are used to construct the MIM, and then its performance is evaluated by cross validation. Experimental results showed that the MIM outperforms any individual model in nearly every data group, and the richer the diversity of the base models, the better the performance of the MIM. Thus, integrating more diversified models, such as an expert system, a statistical model and a physical model, will greatly improve the performance of the MIM.

  13. Interpersonal violence and the prediction of short-term risk of repeat suicide attempt

    PubMed Central

    Haglund, Axel; Lindh, Åsa U.; Lysell, Henrik; Renberg, Ellinor Salander; Jokinen, Jussi; Waern, Margda; Runeson, Bo

    2016-01-01

    In this multi-center cohort study, suicide attempters presenting to hospital (N = 355, 63% women) were interviewed using the Karolinska Interpersonal Violence Scale (KIVS) and followed-up by medical record review. Main outcome was non-fatal or fatal repeat suicide attempt within six months. Also, repeat attempt using a violent method was used as an additional outcome in separate analyses. Data were analyzed for the total group and for men and women separately. Repeat attempts were observed within six months in 78 persons (22%) and 21 (6%) of these used a violent method. KIVS total score of 6 or more was associated with repeat suicide attempt within six months (OR = 1.81, CI 1.08–3.02) and predicted new attempts with a sensitivity of 62% and a specificity of 53%. A three-fold increase in odds ratio was observed for repeat attempt using a violent method (OR = 3.40, CI 1.22–9.49). An association between exposure to violence in adulthood and violent reattempt was seen in women (OR = 1.38, CI 1.06–1.82). The overall conclusions are that information about interpersonal violence may help predict short-term risk for repeat suicide attempt, and that structured assessment of interpersonal violence may be of value in risk assessment after attempted suicide. PMID:27841333

  14. A score to predict short-term risk of COPD exacerbations (SCOPEX)

    PubMed Central

    Make, Barry J; Eriksson, Göran; Calverley, Peter M; Jenkins, Christine R; Postma, Dirkje S; Peterson, Stefan; Östlund, Ollie; Anzueto, Antonio

    2015-01-01

    Background There is no clinically useful score to predict chronic obstructive pulmonary disease (COPD) exacerbations. We aimed to derive this by analyzing data from three existing COPD clinical trials of budesonide/formoterol, formoterol, or placebo in patients with moderate-to-very-severe COPD and a history of exacerbations in the previous year. Methods Predictive variables were selected using Cox regression for time to first severe COPD exacerbation. We determined absolute risk estimates for an exacerbation by identifying variables in a binomial model, adjusting for observation time, study, and treatment. The model was further reduced to clinically useful variables and the final regression coefficients scaled to obtain risk scores of 0–100 to predict an exacerbation within 6 months. Receiver operating characteristic (ROC) curves and the corresponding C-index were used to investigate the discriminatory properties of predictive variables. Results The best predictors of an exacerbation in the next 6 months were more COPD maintenance medications prior to the trial, higher mean daily reliever use, more exacerbations during the previous year, lower forced expiratory volume in 1 second/forced vital capacity ratio, and female sex. Using these risk variables, we developed a score to predict short-term (6-month) risk of COPD exacerbations (SCOPEX). Budesonide/formoterol reduced future exacerbation risk more than formoterol or as-needed short-acting β2-agonist (salbutamol). Conclusion SCOPEX incorporates easily identifiable patient characteristics and can be readily applied in clinical practice to target therapy to reduce COPD exacerbations in patients at the highest risk. PMID:25670896

  15. Short-term response of the solid Earth to cryosphere fluctuations and the earthquake cycle in south-central Alaska

    NASA Astrophysics Data System (ADS)

    Sauber, J. M.; Freymueller, J. T.; Han, S. C.; Davis, J. L.; Ruppert, N. A.

    2016-12-01

    In southern Alaska surface deformation and gravimetric change are associated with the seismic cycle as well as a strong seasonal cycle of snow accumulation and melt and a variable rate of glacier mass wastage. Numerical modeling of the solid Earth response to cryosphere change on a variety of temporal and spatial scales plays a critical role in supporting the interpretation of time-variable gravity and other geodetic data. In this study we calculate the surface displacements and stresses associated with variable spatial and temporal cryospheric loading and unloading in south-central coastal Alaska. A challenging aspect of estimating the response of the solid Earth to short-term (months to 102 years) regional cryospheric fluctuations is choosing the rock mechanics constitutive laws appropriate to this region. Here we report calculated differences in the predicted surface displacements and stresses during the GRACE time period (2002 to present). Broad-scale, GRACE-derived estimates of cryospheric mass change, along with independent snow melt onset/refreeze timing, snow depth and annual glacier wastage estimates from a variety of methods, were used to approximate the magnitude and timing of cryospheric load changes. We used the CIG finite element code PyLith to enable input of spatially complex surface loads. An as example of our evaluation of the influence of variable short-term surface loads, we calculated and contrasted the predicted surface displacements and stresses for a cooler than average and higher precipitation water year (WY12) versus a warmer than average year (WY05). Our calculation of these comparative stresses is motivated by our earlier empirical evaluation of the influence of short-term cryospheric fluctuations on the background seismic rate between 1988-2006 (Sauber and Ruppert, 2008). During the warmer than average years between 2002-2006 we found a stronger seasonal dependency in the frequency of small tectonic events in the Icy Bay region relative

  16. Foreshocks and short-term hazard assessment of large earthquakes using complex networks: the case of the 2009 L'Aquila earthquake

    NASA Astrophysics Data System (ADS)

    Daskalaki, Eleni; Spiliotis, Konstantinos; Siettos, Constantinos; Minadakis, Georgios; Papadopoulos, Gerassimos A.

    2016-08-01

    The monitoring of statistical network properties could be useful for the short-term hazard assessment of the occurrence of mainshocks in the presence of foreshocks. Using successive connections between events acquired from the earthquake catalog of the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for the case of the L'Aquila (Italy) mainshock (Mw = 6.3) of 6 April 2009, we provide evidence that network measures, both global (average clustering coefficient, small-world index) and local (betweenness centrality) ones, could potentially be exploited for forecasting purposes both in time and space. Our results reveal statistically significant increases in the topological measures and a nucleation of the betweenness centrality around the location of the epicenter about 2 months before the mainshock. The results of the analysis are robust even when considering either large or off-centered the main event space windows.

  17. Short-term test for predicting the potential of xenobiotics to impair reproductive success in fish

    SciTech Connect

    Landner, L.; Neilson, A.H.; Soerensen, L.T.; Taernholm, A.V.; Viktor, T.

    1985-06-01

    Short-term screening tests with the zebra fish (Brachydanio rerio) have been developed for predicting the potential of xenobiotics to impair reproductive success in fish. The aim was to find simple and sensitive test parameters and to simulate exposure situations typical for anadromous fish species (salmonids), which generally cross heavily polluted coastal areas or estuaries before they reach uncontaminated upstream spawning areas. Therefore, particular attention was directed to tests designed to assess adverse effects induced during gametogenesis in adult fish. The test protocol involves exposure of adults prior to, but not during, spawning and the effects are measured in the offspring as alterations in hatching frequency and hatching rate of eggs, and survival and stress tolerance of embryos and larvae. Some representative examples of the application of these tests are given, and it is shown that impairment of reproductive success can be induced by exposure of parent fish prior to spawning at concentrations of xenobiotics at least five times lower than those yielding effects during direct exposure of embryos and larvae. It is suggested that, in hazard assessment programs, tests of the effect of xenobiotics on the offspring of preexposed adults be routinely incorporated.

  18. Short-term Operation of Multi-purpose Reservoir using Model Predictive Control

    NASA Astrophysics Data System (ADS)

    Uysal, Gokcen; Schwanenberg, Dirk; Alvarado Montero, Rodolfo; Sensoy, Aynur; Arda Sorman, Ali

    2017-04-01

    Operation of water structures especially with conflicting water supply and flood mitigation objectives is under more stress attributed to growing water demand and changing hydro-climatic conditions. Model Predictive Control (MPC) based optimal control solutions has been successfully applied to different water resources applications. In this study, Feedback Control (FBC) and MPC get combined and an improved joint optimization-simulation operating scheme is proposed. Water supply and flood control objectives are fulfilled by incorporating the long term water supply objectives into a time-dependent variable guide curve policy whereas the extreme floods are attenuated by means of short-term optimization based on MPC. A final experiment is carried out to assess the lead time performance and reliability of forecasts in a hindcasting experiment with imperfect, perturbed forecasts. The framework is tested in Yuvacık Dam reservoir where the main water supply reservoir of Kocaeli City in the northwestern part of Turkey (the Marmara region) and it requires a challenging gate operation due to restricted downstream flow conditions.

  19. A first look at global flash drought: long term change and short term predictability

    NASA Astrophysics Data System (ADS)

    Yuan, Xing; Wang, Linying; Ji, Peng

    2017-04-01

    "Flash drought" became popular after the unexpected 2012 central USA drought, mainly due to its rapid development, low predictability and devastating impacts on water resources and crop yields. A pilot study by Mo and Lettenmaier (2015) found that flash drought, based on a definition of concurrent heat extreme, soil moisture deficit and evapotranspiration (ET) enhancement at pentad scale, were in decline over USA during recent 100 years. Meanwhile, a recent work indicated that the occurrence of flash drought in China was doubled during the past 30 years, where a severe flash drought in the summer of 2013 ravaged 13 provinces in southern China. As global warming increases the frequency of heat waves and accelerates the hydrological cycle, the flash drought is expected to increase in general, but its trend might also be affected by interannual to decadal climate oscillations. To consolidate the hotspots of flash drought and the effects of climate change on flash drought, a global inventory is being conducted by using multi-source observations (in-situ, satellite and reanalysis), CMIP5 historical simulations and future projections under different forcing scenarios, as well as global land surface hydrological modeling for key variables including surface air temperature, soil moisture and ET. In particular, a global picture of the flash drought distribution, the contribution of naturalized and anthropogenic forcings to global flash drought change, and the risk of global flash drought in the future, will be presented. Besides investigating the long-term change of flash drought, providing reliable early warning is also essential to developing adaptation strategies. While regional drought early warning systems have been emerging in recent decade, forecasting of flash drought is still at an exploratory stage due to limited understanding of flash drought predictability. Here, a set of sub-seasonal to seasonal (S2S) hindcast datasets are being used to assess the short term

  20. Using Claims Data to Generate Clinical Flags Predicting Short-term Risk of Continued Psychiatric Hospitalizations

    PubMed Central

    Stein, Bradley D.; Pangilinan, Maria; Sorbero, Mark J; Marcus, Sue; Donahue, Sheila; Xu, Yan; Smith, Thomas E; Essock, Susan M

    2014-01-01

    Objective As health information technology advances, efforts to use administrative data to inform real-time treatment planning for individuals are increasing, despite few empirical studies demonstrating that such administrative data predict subsequent clinical events. Medicaid claims for individuals with frequent psychiatric hospitalizations were examined to test how well patterns of service use predict subsequent high short-term risk of continued psychiatric hospitalizations. Methods Medicaid claims files from New York and Pennsylvania were used to identify Medicaid recipients aged 18-64 with two or more inpatient psychiatric admissions during a target year ending March 31, 2009. Definitions from a quality-improvement initiative were used to identify patterns of inpatient and outpatient service use and prescription fills suggestive of clinical concerns. Generalized estimating equations and Markov models were applied to examine claims through March, 2011, to see what patterns of service use were sufficiently predictive of additional hospitalizations to be clinically useful. Results 11,801 unique individuals in New York and 1,859 in Pennsylvania identified met the cohort definition. In both Pennsylvania and New York, multiple recent hospitalizations, but not failure to use outpatient services or failure to fill medication prescriptions, were significant predictors of high risk of continued frequent hospitalizations, with odds ratios greater than 4.0. Conclusions Administrative data can be used to identify individuals at high risk of continued frequent hospitalizations. Such information could be used by payers and system administrators to authorize special services (e.g., mobile outreach) for such individuals as part of efforts to promote service engagement and prevent rapid rehospitalizations. PMID:25022360

  1. Short-term and Imminent Precursors of Haiti M7.0 Earthquake: Earth Degassing and Thermal Vortex Rotated Movement

    NASA Astrophysics Data System (ADS)

    Qiang, Z.; Qiang, J.; Zeng, Z.; Wang, J.; Xie, H.

    2010-12-01

    The introduction of fracture theory in geology into seismology is hindering the development of seismology and impeding the progress of earthquake forecast. The study of thermal infrared images of the same time but on different days, 30 days prior to the earthquake, one at 17:45:14,Dec.10 UTC,2009 and the other at 17:45:14,Dec.14 UTC,2009, shows that the brightness temperature increases from 296-297°C into 302-303°C in the Cuba Ils., Haiti Isl. Of Gulf of Mexico and Caribbean Sea and adjacent area. The area of temperature increase takes the shape of an elliptic circle 4000Km long in the NW direction and 1000Km wide in the NE direction with an area of about 4,000,000Km2 . P axis is stretch in NNE21° direction. The strike of the fracture is NW 3300. The elliptic circle structure had left handed rotation. 12 to 10days before the quake the cloud belt had extended from Port-au-Prince into Atlantic ocean(25°N,-31.5W)with its width of 50-100Km and lasted more than 50 hours. Earthquake can be predicted using the satellite thermal infrared brightness temperature anomalous method and combining the method of array of infrasonic instruments. The autors thank Dr. Helen Wood, former Chairman of CEOS (Committee of Earth Observation Satellite) and Dr. Axel Graumann of NOAA for providing the satellite images used in this study. Thermal Vortex Rotated Movement and Structure Prior to Haiti Earthquake Earth degassing from the epicenter of Haiti Earthquake, Clould belt extends 4,000 km for 50 hours.

  2. Prototype operational earthquake prediction system

    USGS Publications Warehouse

    Spall, Henry

    1986-01-01

    An objective if the U.S. Earthquake Hazards Reduction Act of 1977 is to introduce into all regions of the country that are subject to large and moderate earthquakes, systems for predicting earthquakes and assessing earthquake risk. In 1985, the USGS developed for the Secretary of the Interior a program for implementation of a prototype operational earthquake prediction system in southern California.

  3. Predicting Short Term Runoff Efficiency Using Antecedent Soil Moisture Estimates From Ground Penetrating Radar Data

    NASA Astrophysics Data System (ADS)

    Hermance, J. F.; Bohidar, R. N.

    2002-05-01

    Hydrologists universally recognize the importance of antecedent soil moisture conditions for predicting the response of catchments to storm events. We describe a pilot study involving a series of repeat geophysical measurements over a 5 month period to determine the water content of the subsurface immediately before a sequence of precipitation events. We correlate the resultant streamflow "response" of the local catchment to each event with the antecedent soil moisture at our reference site using a metric commonly employed by hydrologists: the ratio Qef/W, referred to here as the "short term runoff efficiency", which is simply the time-integrated volume of event flow (Qef) at the catchment's outflow point normalized by the volume of total precipitation (W) over its area. To determine the volumetric water content (Cw) of soils, past studies suggest the effectiveness of pulsed radio frequency methods, such as time domain reflectometry (TDR), or ground-penetrating radar (GPR). To first order, for typical field conditions and procedures, the velocity of a radio pulse in the subsurface is inversely proportional to the square root of the bulk dielectric constant, which in turn is proportional to the soil's water content. For this study, the advantage of GPR over conventional TDR measurements is that the GPR procedure determines average velocities from two-way traveltimes to an interface at depth, resulting in estimates of average physical properties over much larger volumes of the subsurface than would TDR. Our hydrologic data are USGS daily averaged discharges from the Ten Mile River (watershed area = 138 km2; 53.2 mi2) in southern New England. Daily values of precipitation were provided by personnel from the Seekonk Water District Office (MA) adjacent to the field site. Our hydrograph separation was facilitated by the observation that the event flow seems to be adequately represented by a simple composite cascaded linear reservoir model. The GPR data involved a series

  4. Short-Term Prediction Research and Transition (SPoRT) Center: Transitioning Satellite Data to Operations

    NASA Technical Reports Server (NTRS)

    Zavodsky, Bradley

    2012-01-01

    The Short-term Prediction Research and Transition (SPoRT) Center located at NASA Marshall Space Flight Center has been conducting testbed activities aimed at transitioning satellite products to National Weather Service operational end users for the last 10 years. SPoRT is a NASA/NOAA funded project that has set the bar for transition of products to operational end users through a paradigm of understanding forecast challenges and forecaster needs, displaying products in end users decision support systems, actively assessing the operational impact of these products, and improving products based on forecaster feedback. Aiming for quality partnerships rather than a large quantity of data users, SPoRT has become a community leader in training operational forecasters on the use of up-and-coming satellite data through the use of legacy instruments and proxy data. Traditionally, SPoRT has supplied satellite imagery and products from NASA instruments such as the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). However, recently, SPoRT has been funded by the GOES-R and Joint Polar Satellite System (JPSS) Proving Grounds to accelerate the transition of selected imagery and products to help improve forecaster awareness of upcoming operational data from the Visible Infrared Imager Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Baseline Imager (ABI), and Geostationary Lightning Mapper (GLM). This presentation provides background on the SPoRT Center, the SPoRT paradigm, and some example products that SPoRT is excited to work with forecasters to evaluate.

  5. Earthquake prediction, societal implications

    NASA Astrophysics Data System (ADS)

    Aki, Keiiti

    1995-07-01

    "If I were a brilliant scientist, I would be working on earthquake prediction." This is a statement from a Los Angeles radio talk show I heard just after the Northridge earthquake of January 17, 1994. Five weeks later, at a monthly meeting of the Southern California Earthquake Center (SCEC), where more than two hundred scientists and engineers gathered to exchange notes on the earthquake, a distinguished French geologist who works on earthquake faults in China envied me for working now in southern California. This place is like northeastern China 20 years ago, when high seismicity and research activities led to the successful prediction of the Haicheng earthquake of February 4, 1975 with magnitude 7.3. A difficult question still haunting us [Aki, 1989] is whether the Haicheng prediction was founded on the physical reality of precursory phenomena or on the wishful thinking of observers subjected to the political pressure which encouraged precursor reporting. It is, however, true that a successful life-saving prediction like the Haicheng prediction can only be carried out by the coordinated efforts of decision makers and physical scientists.

  6. An Application in the Ultra Short-term Prediction of UT1--UTC Based on Grey System Model

    NASA Astrophysics Data System (ADS)

    Lei, Y.; Zhao, D. N.; Cai, H. B.

    2016-05-01

    This work presents an application of the grey system model in the prediction of UT1--UTC. The short-term prediction of UT1--UTC is studied up to 30 days by means of the grey system model. The EOP (Earth orientation parameter) C04 time series with daily values from the International Earth Rotation and Reference Systems Service (IERS) serve as the data base. The results of the prediction are analyzed and compared with those obtained by the artificial neural network (ANN), the combination of least squares (LS) and autoregressive (AR) model (LS+AR), and the Earth Orientation Parameters Prediction Comparison Campaign (EOP PCC). The accuracies of the ultra short-term (1--10 d) prediction are comparable to those obtained by the other prediction methods. The presented method is easy to use.

  7. Short-Term Predictive Validity of Cluster Analytic and Dimensional Classification of Child Behavioral Adjustment in School

    ERIC Educational Resources Information Center

    Kim, Sangwon; Kamphaus, Randy W.; Baker, Jean A.

    2006-01-01

    A constructive debate over the classification of child psychopathology can be stimulated by investigating the validity of different classification approaches. We examined and compared the short-term predictive validity of cluster analytic and dimensional classifications of child behavioral adjustment in school using the Behavior Assessment System…

  8. Attentional Demands Predict Short-Term Memory Load Response in Posterior Parietal Cortex

    ERIC Educational Resources Information Center

    Magen, Hagit; Emmanouil, Tatiana-Aloi; McMains, Stephanie A.; Kastner, Sabine; Treisman, Anne

    2009-01-01

    Limits to the capacity of visual short-term memory (VSTM) indicate a maximum storage of only 3 or 4 items. Recently, it has been suggested that activity in a specific part of the brain, the posterior parietal cortex (PPC), is correlated with behavioral estimates of VSTM capacity and might reflect a capacity-limited store. In three experiments that…

  9. Attentional Demands Predict Short-Term Memory Load Response in Posterior Parietal Cortex

    ERIC Educational Resources Information Center

    Magen, Hagit; Emmanouil, Tatiana-Aloi; McMains, Stephanie A.; Kastner, Sabine; Treisman, Anne

    2009-01-01

    Limits to the capacity of visual short-term memory (VSTM) indicate a maximum storage of only 3 or 4 items. Recently, it has been suggested that activity in a specific part of the brain, the posterior parietal cortex (PPC), is correlated with behavioral estimates of VSTM capacity and might reflect a capacity-limited store. In three experiments that…

  10. Order Short-Term Memory Capacity Predicts Nonword Reading and Spelling in First and Second Grade

    ERIC Educational Resources Information Center

    Binamé, Florence; Poncelet, Martine

    2016-01-01

    Recent theories of short-term memory (STM) distinguish between item information, which reflects the temporary activation of long-term representations stored in the language system, and serial-order information, which is encoded in a specific representational system that is independent of the language network. Some studies examining the…

  11. Order Short-Term Memory Capacity Predicts Nonword Reading and Spelling in First and Second Grade

    ERIC Educational Resources Information Center

    Binamé, Florence; Poncelet, Martine

    2016-01-01

    Recent theories of short-term memory (STM) distinguish between item information, which reflects the temporary activation of long-term representations stored in the language system, and serial-order information, which is encoded in a specific representational system that is independent of the language network. Some studies examining the…

  12. UTILITY OF SHORT-TERM BASEMENT SCREENING RADON MEASUREMENTS TO PREDICT YEAR-LONG RESIDENTIAL RADON CONCENTRATIONS ON UPPER FLOORS.

    PubMed

    Barros, Nirmalla; Steck, Daniel J; William Field, R

    2016-11-01

    This study investigated temporal and spatial variability between basement radon concentrations (measured for ∼7 d using electret ion chambers) and basement and upper floor radon concentrations (measured for 1 y using alpha track detectors) in 158 residences in Iowa, USA. Utility of short-term measurements to approximate a person's residential radon exposure and effect of housing/occupant factors on predictive ability were evaluated. About 60 % of basement short-term, 60 % of basement year-long and 30 % of upper floor year-long radon measurements were equal to or above the United States Environmental Protection Agency's radon action level of 148 Bq m(-3) Predictive value of a positive short-term test was 44 % given the year-long living space concentration was equal to or above this action level. Findings from this study indicate that cumulative radon-related exposure was more closely approximated by upper floor year-long measurements than short-term or year-long measurements in the basement. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Cardiovascular lifetime risk predicts incidence of coronary calcification in individuals with low short-term risk: the Dallas Heart Study.

    PubMed

    Paixao, Andre R M; Ayers, Colby R; Rohatgi, Anand; Das, Sandeep R; de Lemos, James A; Khera, Amit; Lloyd-Jones, Donald; Berry, Jarett D

    2014-11-25

    The absence of coronary artery calcium (CAC) in middle age is associated with very low short-term risk for coronary events. However, the long-term implications of a CAC score of 0 are uncertain, particularly among individuals with high cardiovascular lifetime risk. We sought to characterize the association between predicted lifetime risk and incident CAC among individuals with low short-term risk. We included 754 Dallas Heart Study participants with serial CAC scans (6.9 years apart) and both low short-term risk and baseline CAC=0. Lifetime risk for cardiovascular disease was estimated according to risk factor burden. Among this group, 365 individuals (48.4%) were at low lifetime risk and 389 (51.6%) at high lifetime risk. High lifetime risk was associated with higher annualized CAC incidence (4.2% versus 2.7%; P < 0.001). Similarly, mean follow-up CAC scores were higher among participants with high lifetime risk (7.8 versus 2.4 Agatston units). After adjustment for age, sex, and race, high lifetime risk remained independently associated with incident CAC (OR 1.60; 95% CI 1.12 to 2.27; P=0.01). When assessing risk factor burden at the follow-up visit, 66.7% of CAC incidence observed in the low lifetime risk group occurred among individuals reclassified to a higher short- or long-term risk category. Among individuals with low short-term risk and CAC scores of 0, high lifetime risk is associated with a higher incidence of CAC. These findings highlight the importance of lifetime risk even among individuals with very low short-term risk. © 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

  14. Increased hippocampal accumulation of autophagosomes predicts short-term recognition memory impairment in aged mice.

    PubMed

    Soontornniyomkij, Virawudh; Risbrough, Victoria B; Young, Jared W; Soontornniyomkij, Benchawanna; Jeste, Dilip V; Achim, Cristian L

    2012-04-01

    Constitutive macroautophagy involved in the turnover of defective long-lived proteins and organelles is crucial for neuronal homeostasis. We hypothesized that macroautophagic dysregulation in selective brain regions was associated with memory impairment in aged mice. We used the single-trial object recognition test to measure short-term memory in 18 aged mice compared to 22 young mice and employed immunohistochemistry to assess cellular distribution of proteins involved in the selective degradation of ubiquitinated proteins via macroautophagy. Values of the discrimination ratio (DR, a measure of short-term recognition memory performance) in aged mice were significantly lower than those in young mice (median, 0.54 vs. 0.67; p = 0.005, U test). Almost exclusively in aged mice, there were clusters of puncta immunoreactive for microtubule-associated protein 1 light chain 3 (LC3), ubiquitin- and LC3-binding protein p62, and ubiquitin in neuronal processes predominantly in the hippocampal formation, olfactory bulb/tubercle, and cerebellar cortex. The hippocampal burden of clustered puncta immunoreactive for LC3 and p62 exhibited inverse linear correlations with DR in aged mice (ρ = -0.48 and -0.55, p = 0.044 and 0.018, respectively, Spearman's rank correlation). These findings suggest that increased accumulation of autophagosomes within neuronal processes in selective brain regions is characteristic of aging. The dysregulation of macroautophagy can adversely affect the turnover of aggregate-prone proteins and defective organelles, which may contribute to memory impairment in aged mice.

  15. Earthquake Prediction is Coming

    ERIC Educational Resources Information Center

    MOSAIC, 1977

    1977-01-01

    Describes (1) several methods used in earthquake research, including P:S ratio velocity studies, dilatancy models; and (2) techniques for gathering base-line data for prediction using seismographs, tiltmeters, laser beams, magnetic field changes, folklore, animal behavior. The mysterious Palmdale (California) bulge is discussed. (CS)

  16. Earthquake Prediction is Coming

    ERIC Educational Resources Information Center

    MOSAIC, 1977

    1977-01-01

    Describes (1) several methods used in earthquake research, including P:S ratio velocity studies, dilatancy models; and (2) techniques for gathering base-line data for prediction using seismographs, tiltmeters, laser beams, magnetic field changes, folklore, animal behavior. The mysterious Palmdale (California) bulge is discussed. (CS)

  17. Pre-earthquake signatures in atmosphere/ionosphere and their potential for short-term earthquake forecasting. Case studies for 2015

    NASA Astrophysics Data System (ADS)

    Ouzounov, Dimitar; Pulinets, Sergey; Davidenko, Dmitry; Hernández-Pajares, Manuel; García-Rigo, Alberto; Petrrov, Leonid; Hatzopoulos, Nikolaos; Kafatos, Menas

    2016-04-01

    We are conducting validation studies on temporal-spatial pattern of pre-earthquake signatures in atmosphere and ionosphere associated with M>7 earthquakes in 2015. Our approach is based on the Lithosphere Atmosphere Ionosphere Coupling (LAIC) physical concept integrated with Multi-sensor-networking analysis (MSNA) of several non-correlated observations that can potentially yield predictive information. In this study we present two type of results: 1/ prospective testing of MSNA-LAIC for M7+ in 2015 and 2:/ retrospective analysis of temporal-spatial variations in atmosphere and ionosphere several days before the two M7.8 and M7.3 in Nepal and M8.3 Chile earthquakes. During the prospective test 18 earthquakes M>7 occurred worldwide, from which 15 were alerted in advance with the time lag between 2 up to 30 days and with different level of accuracy. The retrospective analysis included different physical parameters from space: Outgoing long-wavelength radiation (OLR obtained from NPOES, NASA/AQUA) on the top of the atmosphere, Atmospheric potential (ACP obtained from NASA assimilation models) and electron density variations in the ionosphere via GPS Total Electron Content (GPS/TEC). Concerning M7.8 in Nepal of April 24, rapid increase of OLR reached the maximum on April 21-22. GPS/TEC data indicate maximum value during April 22-24 periods. Strong negative TEC anomaly was detected in the crest of EIA (Equatorial Ionospheric Anomaly) on April 21st and strong positive on April 24th, 2015. For May 12 M7.3 aftershock similar pre- earthquake patterns in OLR and GPS/TEC were observed. Concerning the M8.3 Chile of Sept 16, the OLR strongest transient feature was observed of Sept 12. GPS/TEC analysis data confirm abnormal values on Sept 14. Also on the same day the degradation of EIA and disappearance of the crests of EIA as is characteristic for pre-dawn and early morning hours (11 LT) was observed. On Sept 16 co-seismic ionospheric signatures consistent with defined circular

  18. Predicting Predictable: Accuracy and Reliability of Earthquake Forecasts

    NASA Astrophysics Data System (ADS)

    Kossobokov, V. G.

    2014-12-01

    Earthquake forecast/prediction is an uncertain profession. The famous Gutenberg-Richter relationship limits magnitude range of prediction to about one unit. Otherwise, the statistics of outcomes would be related to the smallest earthquakes and may be misleading when attributed to the largest earthquakes. Moreover, the intrinsic uncertainty of earthquake sizing allows self-deceptive picking of justification "just from below" the targeted magnitude range. This might be important encouraging evidence but, by no means, can be a "helpful" additive to statistics of a rigid testing that determines reliability and efficiency of a farecast/prediction method. Usually, earthquake prediction is classified in respect to expectation time while overlooking term-less identification of earthquake prone areas, as well as spatial accuracy. The forecasts are often made for a "cell" or "seismic region" whose area is not linked to the size of target earthquakes. This might be another source for making a wrong choice in parameterization of an forecast/prediction method and, eventually, for unsatisfactory performance in a real-time application. Summing up, prediction of time and location of an earthquake of a certain magnitude range can be classified into categories listed in the Table below - Classification of earthquake prediction accuracy Temporal, in years Spatial, in source zone size (L) Long-term 10 Long-range Up to 100 Intermediate-term 1 Middle-range 5-10 Short-term 0.01-0.1 Narrow-range 2-3 Immediate 0.001 Exact 1 Note that a wide variety of possible combinations that exist is much larger than usually considered "short-term exact" one. In principle, such an accurate statement about anticipated seismic extreme might be futile due to the complexities of the Earth's lithosphere, its blocks-and-faults structure, and evidently nonlinear dynamics of the seismic process. The observed scaling of source size and preparation zone with earthquake magnitude implies exponential scales for

  19. Short-Term Mortality Prediction for Acute Lung Injury Patients: External Validation of the ARDSNet Prediction Model

    PubMed Central

    Damluji, Abdulla; Colantuoni, Elizabeth; Mendez-Tellez, Pedro A.; Sevransky, Jonathan E.; Fan, Eddy; Shanholtz, Carl; Wojnar, Margaret; Pronovost, Peter J.; Needham, Dale M.

    2011-01-01

    Objective An independent cohort of acute lung injury (ALI) patients was used to evaluate the external validity of a simple prediction model for short-term mortality previously developed using data from ARDS Network (ARDSNet) trials. Design, Setting, and Patients Data for external validation were obtained from a prospective cohort study of ALI patients from 13 ICUs at four teaching hospitals in Baltimore, Maryland. Measurements and Main Results Of the 508 non-trauma, ALI patients eligible for this analysis, 234 (46%) died in-hospital. Discrimination of the ARDSNet prediction model for inhospital mortality, evaluated by the area under the receiver operator characteristics curves (AUC), was 0.67 for our external validation dataset versus 0.70 and 0.68 using APACHE II and the ARDSNet validation dataset, respectively. In evaluating calibration of the model, predicted versus observed in-hospital mortality for the external validation dataset was similar for both low risk (ARDSNet model score = 0) and high risk (score = 3 or 4+) patient strata. However, for intermediate risk (score = 1 or 2) patients, observed in-hospital mortality was substantially higher than predicted mortality (25.3% vs. 16.5% and 40.6% vs. 31.0% for score = 1 and 2, respectively). Sensitivity analyses limiting our external validation data set to only those patients meeting the ARDSNet trial eligibility criteria and to those who received mechanical ventilation in compliance with the ARDSNet ventilation protocol, did not substantially change the model’s discrimination or improve its calibration. Conclusions Evaluation of the ARDSNet prediction model using an external ALI cohort demonstrated similar discrimination of the model as was observed with the ARDSNet validation dataset. However, there were substantial differences in observed versus predicted mortality among intermediate risk ALI patients. The ARDSNet model provided reasonable, but imprecise, estimates of predicted mortality when applied to our

  20. Short-term pre-2004 seismic subsidence near South Andaman: Is this a precursor slow slip prior to a megathrust earthquake?

    NASA Astrophysics Data System (ADS)

    Paul, J.; Rajendran, C. P.

    2015-11-01

    We report here on the campaign GPS data from the Andaman Islands just previous to the great 2004 Sumatra-Andaman earthquake. The campaign-mode acquisitions at Port Blair showed that the site started to subside between 2003 and 2004. In addition, during this period, the horizontal displacement of Port Blair with respect to Indian plate, deduced from 1996 to 2000 GPS data, changed its orientation to that obtained during the 26th Dec 2004 co-seismic. This short-term subsidence can be modeled as slip in the up-dip portion of the fault, a slip that is equivalent to an earthquake with moment magnitude of 6.3. Previously, slow slip was thought to appear at intermediate depths roughly 35-55 km but simple models of the deformation at this single site suggest slow slip at much shallower depth than this. This observation of subsidence obtained by GPS methods is in rough agreement with subsidence observed from tide gauge data. Campaign-mode GPS data between 1996 and 2000 suggest uplift for Port Blair during the inter-seismic period and so does the reported field observations of interseismic micro-atoll emergence. Lack of exposed land with GPS stations along the southern part of the thrust fault deprive of arriving at any indication of this preseismic subsidence in those areas. Although GPS data is lacking the geological indices reported from some sites on the Alaskan Coast, for example, imply short-term subsidence just previous to the great 1964 earthquake. The pre-earthquake subsidence recorded in Port Blair, therefore, may have global implications as a precursor signal of great earthquakes at least along some of the subduction zones.

  1. Accordion complication grading predicts short-term outcome after right colectomy.

    PubMed

    Klos, Coen L; Safar, Bashar; Hunt, Steven R; Wise, Paul E; Birnbaum, Elisa H; Mutch, Matthew G; Fleshman, James W; Dharmarajan, Sekhar

    2014-08-01

    The Accordion severity grading system is a novel system to score the severity of postoperative complications in a standardized fashion. This study aims to demonstrate the validity of the Accordion system in colorectal surgery by correlating severity grades with short-term outcomes after right colectomy for colon cancer. This is a retrospective cohort review of patients who underwent right colectomy for cancer between January 1, 2002, and January 31, 2007, at a single tertiary care referral center. Complications were categorized according to the Accordion severity grading system: grades 1 (mild), 2 (moderate), 3-5 (severe), and 6 (death). Outcome measures were hospital stay, 30-d readmission rate and 1-y survival. Correlation between Accordion grades and outcome measures is reflected by Spearman rho (ρ). One-year survival was obtained per Kaplan-Meier method and compared by logrank test for trend. Significance was set at P ≤ 0.05. Overall, 235 patients underwent right colectomy for cancer of which 122 (51.9%) had complications. In total, 52 (43%) had an Accordion grade 1 complication; 44 (36%) grade 2; four (3%) grade 3; 11 (9%) grade 4; seven (6%) grade 5; and four (3%) grade 6. There was significant correlation between Accordion grades and hospital stay (ρ = 0.495, P < 0.001) and 30-d readmission rate (ρ = 0.335, P < 0.001). There was a significant downward trend in 1-y survival as complication severity by Accordion grade increased (P = 0.02). The Accordion grading system is a useful tool to estimate short-term outcomes after right colectomy for cancer. High-grade Accordion complications are associated with longer hospital stay and increased risk of readmission and mortality. Published by Elsevier Inc.

  2. TP53 genotype but not p53 immunohistochemical result predicts response to preoperative short-term radiotherapy in rectal cancer.

    PubMed

    Kandioler, Daniela; Zwrtek, Ronald; Ludwig, Carmen; Janschek, Elisabeth; Ploner, Meinhard; Hofbauer, Friedrich; Kührer, Irene; Kappel, Sonja; Wrba, Friedrich; Horvath, Manfred; Karner, Josef; Renner, Karl; Bergmann, Michael; Karner-Hanusch, Judith; Pötter, Richard; Jakesz, Raimund; Teleky, Bela; Herbst, Friedrich

    2002-04-01

    To evaluate and compare the predictive power of p53 gene analysis versus p53 immunohistochemical staining in terms of response to preoperative short-term radiotherapy using 25 Gy in operable rectal cancer. Recent studies show that p53 may be a determinant of radiosensitivity being required for induction of apoptosis in case of radiation-induced DNA damage. Preirradiation biopsy samples of 64 patients with rectal carcinoma were analyzed. Genetic alterations of the p53 gene were detected by complete direct sequencing of exons 2 to 10. Expression of the nuclear phosphoprotein p53 was assessed by immunohistochemical staining. Results were correlated with histopathology of resected specimens and follow-up data, respectively. Mutations of the p53 gene were present in 45% of tumors. Patients with a normal p53 gene had a significant survival advantage. Comparing pre- and postradiotherapy T category, a reduction was seen in patients with normal p53 genotype only. A mutant p53 genotype was highly specific in indicating stable disease concerning T category after irradiation. Protein overexpression was detected in 61%. Overexpression of the p53 protein was not related to survival or response. The concordance between immunohistochemistry and sequencing was only 0.51. The authors show that downstaging after short-term radiation may occur but is seen in tumors with normal p53 gene only. Moreover, p53 genotype but not p53 immunohistochemistry is predictive for response to preoperative short-term radiotherapy and patient survival.

  3. Short-term volcano-tectonic earthquake forecasts based on a moving mean recurrence time algorithm: the El Hierro seismo-volcanic crisis experience

    NASA Astrophysics Data System (ADS)

    García, Alicia; De la Cruz-Reyna, Servando; Marrero, José M.; Ortiz, Ramón

    2016-05-01

    Under certain conditions, volcano-tectonic (VT) earthquakes may pose significant hazards to people living in or near active volcanic regions, especially on volcanic islands; however, hazard arising from VT activity caused by localized volcanic sources is rarely addressed in the literature. The evolution of VT earthquakes resulting from a magmatic intrusion shows some orderly behaviour that may allow the occurrence and magnitude of major events to be forecast. Thus governmental decision makers can be supplied with warnings of the increased probability of larger-magnitude earthquakes on the short-term timescale. We present here a methodology for forecasting the occurrence of large-magnitude VT events during volcanic crises; it is based on a mean recurrence time (MRT) algorithm that translates the Gutenberg-Richter distribution parameter fluctuations into time windows of increased probability of a major VT earthquake. The MRT forecasting algorithm was developed after observing a repetitive pattern in the seismic swarm episodes occurring between July and November 2011 at El Hierro (Canary Islands). From then on, this methodology has been applied to the consecutive seismic crises registered at El Hierro, achieving a high success rate in the real-time forecasting, within 10-day time windows, of volcano-tectonic earthquakes.

  4. Is It Possible to Predict Strong Earthquakes?

    NASA Astrophysics Data System (ADS)

    Polyakov, Y. S.; Ryabinin, G. V.; Solovyeva, A. B.; Timashev, S. F.

    2015-07-01

    The possibility of earthquake prediction is one of the key open questions in modern geophysics. We propose an approach based on the analysis of common short-term candidate precursors (2 weeks to 3 months prior to strong earthquake) with the subsequent processing of brain activity signals generated in specific types of rats (kept in laboratory settings) who reportedly sense an impending earthquake a few days prior to the event. We illustrate the identification of short-term precursors using the groundwater sodium-ion concentration data in the time frame from 2010 to 2014 (a major earthquake occurred on 28 February 2013) recorded at two different sites in the southeastern part of the Kamchatka Peninsula, Russia. The candidate precursors are observed as synchronized peaks in the nonstationarity factors, introduced within the flicker-noise spectroscopy framework for signal processing, for the high-frequency component of both time series. These peaks correspond to the local reorganizations of the underlying geophysical system that are believed to precede strong earthquakes. The rodent brain activity signals are selected as potential "immediate" (up to 2 weeks) deterministic precursors because of the recent scientific reports confirming that rodents sense imminent earthquakes and the population-genetic model of K irshvink (Soc Am 90, 312-323, 2000) showing how a reliable genetic seismic escape response system may have developed over the period of several hundred million years in certain animals. The use of brain activity signals, such as electroencephalograms, in contrast to conventional abnormal animal behavior observations, enables one to apply the standard "input-sensor-response" approach to determine what input signals trigger specific seismic escape brain activity responses.

  5. Usefulness of Single Column Model Diagnosis through Short-Term Predictions.

    NASA Astrophysics Data System (ADS)

    Bergman, John W.; Sardeshmukh, Prashant D.

    2003-11-01

    Single column models (SCMs) provide an economical framework for developing and diagnosing representations of diabatic processes in weather and climate models. Their economy is achieved at the price of ignoring interactions with the circulation dynamics and with neighboring columns. It has recently been emphasized that this decoupling can lead to spurious error growth in SCM integrations that can totally obscure the error growth due to errors in the column physics that one hopes to isolate through such integrations. This paper suggests one way around this “existential crisis” of single column modeling. The basic idea is to focus on short-term SCM forecast errors, at ranges of 6 h or less, before a grossly unrealistic model state develops and before complex diabatic interactions render a clear diagnosis impossible.To illustrate, a short-term forecast error diagnosis of the NCAR SCM is presented for tropical conditions observed during the Tropical Ocean and Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE). The 21-day observing period is divided into 84 6-h segments for this purpose. The SCM error evolution is shown to be nearly linear over these 6-h segments and, indeed, apart from a vertical mean bias, to be mainly an extrapolation of initial tendencies. The latter are then decomposed into contributions by various components of the column physics, and additional 6-h integrations are performed with each component separately and in combination with others to assess its contribution to the 6-h errors. Initial tendency and 6-h error diagnostics thus complement each other in diagnosing column physics errors by this approach.Although the SCM evolution from one time step to the next is nearly linear, the finite-amplitude adjustments made multiple times within each time step to the temperature and humidity to remove supersaturation and convective instabilities make it necessary to consider nonlinear interactions between the column physics

  6. Integration of stochastic simulation with multivariate analysis: short-term facility fit prediction.

    PubMed

    Stonier, Adam; Pain, David; Westlake, Ashley; Hutchinson, Nicholas; Thornhill, Nina F; Farid, Suzanne S

    2013-01-01

    This article describes a decision-support tool to help pinpoint the potential root causes of sub-optimal short-term facility fit issues in biopharmaceutical facilities. This was achieved by creating a tool that integrated stochastic simulation with advanced multivariate statistical analysis. Process fluctuations in product titers in cell culture, step yields, and chromatography eluate volumes were mimicked using Monte Carlo simulation data derived using a stochastic discrete-event simulation model. The resulting stochastic datasets, with the computed consequences on key metrics such as product mass loss and cost of goods, were examined using advanced multivariate statistical techniques. Principal component analysis combined with clustering algorithms was used to analyze the complex datasets from complete industrial batch processes for biopharmaceuticals. The challenge of visualizing the multidimensional nature of the dataset was addressed using hierarchical and k-means clustering as well as stacked parallel co-ordinate plots to help identify process fingerprints and characteristics of clusters leading to sub-optimal facility fit issues. Industrially-relevant case studies are presented that focus on technology transfer challenges for therapeutic antibodies moving from early phase to late phase clinical trials. The case study details how sub-optimal facility fit can be alleviated by allocating alternative product pool tanks. The impact of this operational change is then assessed by reviewing an updated process fingerprint. Copyright © 2013 American Institute of Chemical Engineers.

  7. [Value of cardiopulmonary risk index in predicting postoperative short-term prognosis in patients with lung cancer].

    PubMed

    Gu, Yueqing; Gao, Chengxin; Bai, Hao; Liao, Meilin

    2002-06-20

    To determine the value of preoperative cardiopulmonary risk index (CPRI) in predicting the short-term prognosis after lung resection in patients with lung cancer. Preoperative clinical data were used to generate a cardiac risk index (CRI) and a pulmonary risk index (PRI). And the value of cardiopulmonary risk index (CPRI) consisting of CRI and PRI in predicting postoperative prognosis was estimated in patients who underwent lung resection at Shanghai Chest Hospital in 1999. A total of 625 consecutive patients were studied. Postoperative complications occurred in 49 patients (7.8%), including 8 deaths within 30 days of operation. In the total group, CRI, PRI and CPRI scores ranged from 1 to 3, 0 to 5 and 1 to 7, respectively. There were 489 patients with CPRI < 4, and 136 with CPRI≥4. Using CPRI≥4 as a threshold for predicting postoperative complications, the sensitivity, specificity and accuracy rate were 75.5%, 82.8% and 82.2% respectively. The preoperative CPRI is one of the important indexes in predicting the short-term postoperative prognosis for patients with lung cancer. However, it can not completely predict all of postoperative risks, and should be used together with other factors.

  8. Autonomic Function Predicts Fitness Response to Short-Term High-Intensity Interval Training.

    PubMed

    Kiviniemi, A M; Tulppo, M P; Eskelinen, J J; Savolainen, A M; Kapanen, J; Heinonen, I H A; Hautala, A J; Hannukainen, J C; Kalliokoski, K K

    2015-11-01

    We tested the hypothesis that baseline cardiac autonomic function and its acute response to all-out interval exercise explains individual fitness responses to high-intensity interval training (HIT). Healthy middle-aged sedentary men performed HIT (n=12, 4-6×30 s of all-out cycling efforts with 4-min recovery) or aerobic training (AET, n=9, 40-60 min at 60% of peak workload in exercise test [Loadpeak]), comprising 6 sessions within 2 weeks. Low (LF) and high frequency (HF) power of R-R interval oscillation were analyzed from data recorded at supine and standing position (5+5 min) every morning during the intervention. A significant training effect (p< 0.001), without a training*group interaction, was observed in Loadpeak and peak oxygen consumption (VO2peak). Pre-training supine LF/HF ratio, an estimate of sympathovagal balance, correlated with training outcome in Loadpeak (Spearman's rho [rs]=-0.74, p=0.006) and VO2peak (rs=- 0.59, p=0.042) in the HIT but not the AET group. Also, the mean change in the standing LF/HF ratio in the morning after an acute HIT exercise during the 1(st) week of intervention correlated with training response in Loadpeak (rs=- 0.68, p=0.014) and VO2peak (rs=-0.60, p=0.039) with HIT but not with AET. In conclusion, pre-training cardiac sympathovagal balance and its initial alterations in response to acute HIT exercise were related to fitness responses to short-term HIT.

  9. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

    PubMed

    Shang, Qiang; Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

    2016-01-01

    Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

  10. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine

    PubMed Central

    Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

    2016-01-01

    Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust. PMID:27551829

  11. On spatiotemporal series analysis and its application to predict the regional short term climate process

    NASA Astrophysics Data System (ADS)

    Wang, Geli; Yang, Peicai; Lü, Daren

    2004-04-01

    Based on the theory of reconstructing state space, a technique for spatiotemporal series prediction is presented. By means of this technique and NCEP/NCAR data of the monthly mean geopotential height anomaly of the 500-hPa isobaric surface in the Northern Hemisphere, a regional prediction experiment is also carried out. If using the correlation coefficient R between the observed field and the prediction field to measure the prediction accuracy, the averaged R given by 48 prediction samples reaches 21%, which corresponds to the current prediction level for the short range climate process.

  12. Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models: 2. Laboratory earthquakes

    NASA Astrophysics Data System (ADS)

    Rubinstein, Justin L.; Ellsworth, William L.; Beeler, Nicholas M.; Kilgore, Brian D.; Lockner, David A.; Savage, Heather M.

    2012-02-01

    The behavior of individual stick-slip events observed in three different laboratory experimental configurations is better explained by a "memoryless" earthquake model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. We make similar findings in the companion manuscript for the behavior of natural repeating earthquakes. Taken together, these results allow us to conclude that the predictions of a characteristic earthquake model that assumes either fixed slip or fixed recurrence interval should be preferred to the predictions of the time- and slip-predictable models for all earthquakes. Given that the fixed slip and recurrence models are the preferred models for all of the experiments we examine, we infer that in an event-to-event sense the elastic rebound model underlying the time- and slip-predictable models does not explain earthquake behavior. This does not indicate that the elastic rebound model should be rejected in a long-term-sense, but it should be rejected for short-term predictions. The time- and slip-predictable models likely offer worse predictions of earthquake behavior because they rely on assumptions that are too simple to explain the behavior of earthquakes. Specifically, the time-predictable model assumes a constant failure threshold and the slip-predictable model assumes that there is a constant minimum stress. There is experimental and field evidence that these assumptions are not valid for all earthquakes.

  13. Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

    NASA Astrophysics Data System (ADS)

    Mohammed, E.; Wang, S.; Yu, J.

    2017-05-01

    Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

  14. Individual stress vulnerability is predicted by short-term memory and AMPA receptor subunit ratio in the hippocampus.

    PubMed

    Schmidt, Mathias V; Trümbach, Dietrich; Weber, Peter; Wagner, Klaus; Scharf, Sebastian H; Liebl, Claudia; Datson, Nicole; Namendorf, Christian; Gerlach, Tamara; Kühne, Claudia; Uhr, Manfred; Deussing, Jan M; Wurst, Wolfgang; Binder, Elisabeth B; Holsboer, Florian; Müller, Marianne B

    2010-12-15

    Increased vulnerability to aversive experiences is one of the main risk factors for stress-related psychiatric disorders as major depression. However, the molecular bases of vulnerability, on the one hand, and stress resilience, on the other hand, are still not understood. Increasing clinical and preclinical evidence suggests a central involvement of the glutamatergic system in the pathogenesis of major depression. Using a mouse paradigm, modeling increased stress vulnerability and depression-like symptoms in a genetically diverse outbred strain, and we tested the hypothesis that differences in AMPA receptor function may be linked to individual variations in stress vulnerability. Vulnerable and resilient animals differed significantly in their dorsal hippocampal AMPA receptor expression and AMPA receptor binding. Treatment with an AMPA receptor potentiator during the stress exposure prevented the lasting effects of chronic social stress exposure on physiological, neuroendocrine, and behavioral parameters. In addition, spatial short-term memory, an AMPA receptor-dependent behavior, was found to be predictive of individual stress vulnerability and response to AMPA potentiator treatment. Finally, we provide evidence that genetic variations in the AMPA receptor subunit GluR1 are linked to the vulnerable phenotype. Therefore, we propose genetic variations in the AMPA receptor system to shape individual stress vulnerability. Those individual differences can be predicted by the assessment of short-term memory, thereby opening up the possibility for a specific treatment by enhancing AMPA receptor function.

  15. Application of short-term water demand prediction model to Seoul.

    PubMed

    Joo, C N; Koo, J Y; Yu, M J

    2002-01-01

    To predict daily water demand for Seoul, Korea, the artificial neural network (ANN) was used. For the cross correlation, the factors affecting water demand such as maximum temperature, humidity, and wind speed as natural factors, holidays as a social factor and daily demand 1 day before were used. From the results of learning using various hidden layers and units in order to establish the structure of optimal ANN, the case of 3 hidden layers and numbers of unit with the same number of input factors showed the best result and, therefore, it was applied to seasonal water demand prediction. The performance of ANN was compared with a multiple regression method. We discuss the representation ability of the model building process and the applicability of the ANN approach for the daily water demand prediction. ANN provided reasonable results for time series prediction.

  16. Predictive model of short-term amputation during hospitalization of patients due to acute diabetic foot infections.

    PubMed

    Barberán, José; Granizo, Juan-José; Aguilar, Lorenzo; Alguacil, Rafael; Sainz, Felipe; Menéndez, Maria-Antonia; Giménez, Maria-José; Martínez, David; Prieto, José

    2010-12-01

    Factors predicting short-term amputation during hospital treatment of patients admitted for acute diabetic foot infections are of interest for clinicians managing the acute episode. A retrospective clinical records analysis of 78 consecutive patients hospitalized for acute diabetic foot infections was performed to identify predictive factors for short-term amputation by comparing the data of patients who ultimately required amputation and those who did not. Clinical/epidemiological, laboratory, imaging, and treatment variables were comparatively analyzed. A logistic regression model was performed, with amputation as the dependent variable and factors showing significant differences in the bivariate analysis as independent variables. A prediction score was calculated (and validated by ROC curve analysis) using beta coefficients for significant variables in the regression analysis to predict amputation. Of the 78 patients (70.5% with peripheral vasculopathy) included, 26 ultimately required amputation. In the bivariate analysis, white blood cell count, previous homolateral lesions, odor, lesion depth, sedimentation rate, Wagner ulcer grade, and arterial obstruction on Doppler study were significantly higher in patients ending in amputation. In the multivariate analysis, the risk of amputation was increased only by Wagner grade 4 or 5 (20-fold higher), obstruction (12.5-fold higher), and elevated sedimentation rate (6% higher per unit). Logistic regression predicted outcome in 76.9% of patients who underwent amputation and 92.3% of those who did not. The score calculated using beta coefficients for significant variables in the regression model (Wagner grades 4 and 5, obstruction on Doppler, and elevated sedimentation rate for the clinical, imaging, and laboratory data, respectively) correctly predicted amputation during hospital management of acute diabetic foot infections. Copyright © 2009 Elsevier España, S.L. All rights reserved.

  17. Evaluation of short-term climate change prediction in multi-model CMIP5 decadal hindcasts

    NASA Astrophysics Data System (ADS)

    Kim, Hye-Mi; Webster, Peter J.; Curry, Judith A.

    2012-05-01

    This study assesses the CMIP5 decadal hindcast/forecast simulations of seven state-of-the-art ocean-atmosphere coupled models. Each decadal prediction consists of simulations over a 10 year period each of which are initialized every five years from climate states of 1960/1961 to 2005/2006. Most of the models overestimate trends, whereby the models predict less warming or even cooling in the earlier decades compared to observations and too much warming in recent decades. All models show high prediction skill for surface temperature over the Indian, North Atlantic and western Pacific Oceans where the externally forced component and low-frequency climate variability is dominant. However, low prediction skill is found over the equatorial and North Pacific Ocean. The Atlantic Multidecadal Oscillation (AMO) index is predicted in most of the models with significant skill, while the Pacific Decadal Oscillation (PDO) index shows relatively low predictive skill. The multi-model ensemble has in general better-forecast quality than the single-model systems for global mean surface temperature, AMO and PDO.

  18. The value of an acute octreotide suppression test in predicting short-term efficacy of somatostatin analogues in acromegaly.

    PubMed

    Wang, Meng; Shen, Ming; He, Wenqiang; Yang, Yeping; Liu, Wenjuan; Lu, Yun; Ma, Zengyi; Ye, Zhao; Zhang, Yichao; Zhao, Xiaolong; Lu, Bin; Hu, Ji; Huang, Yun; Shou, Xuefei; Wang, Yongfei; Ye, Hongying; Li, Yiming; Li, Shiqi; Zhao, Yao; Zhang, Zhaoyun

    2016-09-30

    Predicting the efficacy of long-acting somatostatin analogues (SSA) remains a challenge. We aim to quantitatively evaluate the predictive value of the octreotide suppression test (OST) in short-term efficacy of SSA in active acromegaly. Sixty-seven newly diagnosed acromegaly patients were assessed with OST. Subsequently, all patients were treated with long-acting SSA for 3 months, followed by reassessment. Nine parameters were tested, including GHn (the nadir GH during OST), ΔGH1 (= [GH0h-GHn]/GH0h, GH0h was the baseline GH during OST), ΔGH2 (= [GHm-GHn]/GHm, GHm was the mean GH on day curve), AUC(0-6h) (the GH area under the curve during OST) , ΔAUC1 (= [GH0h-AUC(0-6h)]/GH0h), ΔAUC2 (=[GHm-AUC(0-6h)]/GHm), AUC(m-6h) (the GH AUC during OST where GHm was used instead of GH0h), ΔAUC1' (=[GH0h-AUC(m-6h)]/GH0h) and ΔAUC2' (=[GHm-AUC(m-6h)]/GHm). The Youden indices were calculated to determine the optimal cutoffs to predict the short-term efficacy of SSA. ΔGH2 more than 86.83%, ΔAUC2 more than -57.48% and ΔAUC2' more than -57.98% provided the best predictors of a good GH response (sensitivity 93.8%, specificity 85.7%). ΔGH2 more than 90.51% provided the best predictor of a good tumor size response (sensitivity 84.8%, specificity 87.5%). The percentage fall of GHn (ΔGH) was a better predictive parameter than GHn. OST showed higher efficiency in predicting the efficacy of octreotide LAR than lanreotide SR. In conclusion, OST is a valid tool to predict both GH and tumor size response to short-term efficacy of SSA in acromegaly, especially for octreotide LAR. GHm is better to be used as basal GH than GH0 during OST.

  19. Current affairs in earthquake prediction in Japan

    NASA Astrophysics Data System (ADS)

    Uyeda, Seiya

    2015-12-01

    As of mid-2014, the main organizations of the earthquake (EQ hereafter) prediction program, including the Seismological Society of Japan (SSJ), the MEXT Headquarters for EQ Research Promotion, hold the official position that they neither can nor want to make any short-term prediction. It is an extraordinary stance of responsible authorities when the nation, after the devastating 2011 M9 Tohoku EQ, most urgently needs whatever information that may exist on forthcoming EQs. Japan's national project for EQ prediction started in 1965, but it has made no success. The main reason for no success is the failure to capture precursors. After the 1995 Kobe disaster, the project decided to give up short-term prediction and this stance has been further fortified by the 2011 M9 Tohoku Mega-quake. This paper tries to explain how this situation came about and suggest that it may in fact be a legitimate one which should have come a long time ago. Actually, substantial positive changes are taking place now. Some promising signs are arising even from cooperation of researchers with private sectors and there is a move to establish an "EQ Prediction Society of Japan". From now on, maintaining the high scientific standards in EQ prediction will be of crucial importance.

  20. Predicting pathogen growth during short-term temperature abuse of raw sausage.

    PubMed

    Ingham, Steven C; Ingham, Barbara H; Borneman, Darand; Jaussaud, Emilie; Schoeller, Erica L; Hoftiezer, Nathan; Schwartzburg, Lauren; Burnham, Greg M; Norback, John P

    2009-01-01

    Lag-phase duration (LPD) and growth rate (GR) values were calculated from experimental data obtained using a previously described protocol (S. C. Ingham, M. A. Fanslau, G. M. Burnham, B. H. Ingham, J. P. Norback, and D. W. Schaffner, J. Food Prot. 70:1445-1456, 2007). These values were used to develop an interval accumulation-based tool designated THERM (temperature history evaluation for raw meats) for predicting growth or no growth of Salmonella serovars, Escherichia coli O157:H7, and Staphylococcus aureus in temperature-abused raw sausage. Data (time-temperature and pathogen log CFU per gram) were obtained from six inoculation experiments with Salmonella, E. coli O157:H7, and S. aureus in three raw pork sausage products stored under different temperature abuse conditions. The time-temperature history from each experiment was entered into THERM to predict pathogen growth. Predicted and experimental results were described as growth (> 0.3 log increase in CFU) or no growth (< or = 0.3 log increase in CFU) and compared. The THERM tool accurately predicted growth or no growth for all 18 pathogen-experiment combinations. When compared with the observed changes in log CFU values for the nine pathogen-experiment combinations in which pathogens grew, the predicted changes in log CFU values were within 0.3 log CFU for three combinations, exceeded observed values by 0.4 to 1.5 log CFU in four combinations, and were 1.2 to 1.4 log CFU lower in two combinations. The THERM tool approach appears to be useful for predicting pathogen growth versus no growth in raw sausage during temperature abuse, although further development and testing are warranted.

  1. Short term Heart Rate Variability to predict blood pressure drops due to standing: a pilot study.

    PubMed

    Sannino, G; Melillo, P; Stranges, S; De Pietro, G; Pecchia, L

    2015-01-01

    Standing from a bed or chair may cause a significant lowering of blood pressure (ΔBP), which may have severe consequences such as, for example, falls in older subjects. The goal of this study was to develop a mathematical model to predict the ΔBP due to standing in healthy subjects, based on their Heart Rate Variability, recorded in the 5 minutes before standing. Heart Rate Variability was extracted from an electrocardiogram, recorded from 10 healthy subjects during the 5 minutes before standing. The blood pressure value was measured before and after rising. A mathematical model aiming to predict ΔBP based on Heart Rate Variability measurements was developed using a robust multi-linear regression and was validated with the leave-one-subject-out cross-validation technique. The model predicted correctly the ΔBP in 80% of experiments, with an error below the measurement error of sphygmomanometer digital devices (± 4.5 mmHg), a false negative rate of 7.5% and a false positive rate of 10%. The magnitude of the ΔBP was associated with a depressed and less chaotic Heart Rate Variability pattern. The present study showes that blood pressure lowering due to standing can be predicted by monitoring the Heart Rate Variability in the 5 minutes before standing.

  2. Short term Heart Rate Variability to predict blood pressure drops due to standing: a pilot study

    PubMed Central

    2015-01-01

    Background Standing from a bed or chair may cause a significant lowering of blood pressure (ΔBP), which may have severe consequences such as, for example, falls in older subjects. The goal of this study was to develop a mathematical model to predict the ΔBP due to standing in healthy subjects, based on their Heart Rate Variability, recorded in the 5 minutes before standing. Methods Heart Rate Variability was extracted from an electrocardiogram, recorded from 10 healthy subjects during the 5 minutes before standing. The blood pressure value was measured before and after rising. A mathematical model aiming to predict ΔBP based on Heart Rate Variability measurements was developed using a robust multi-linear regression and was validated with the leave-one-subject-out cross-validation technique. Results The model predicted correctly the ΔBP in 80% of experiments, with an error below the measurement error of sphygmomanometer digital devices (±4.5 mmHg), a false negative rate of 7.5% and a false positive rate of 10%. The magnitude of the ΔBP was associated with a depressed and less chaotic Heart Rate Variability pattern. Conclusions The present study showes that blood pressure lowering due to standing can be predicted by monitoring the Heart Rate Variability in the 5 minutes before standing. PMID:26391336

  3. Ain't no mountain high enough? Setting high weight loss goals predict effort and short-term weight loss.

    PubMed

    De Vet, Emely; Nelissen, Rob M A; Zeelenberg, Marcel; De Ridder, Denise T D

    2013-05-01

    Although psychological theories outline that it might be beneficial to set more challenging goals, people attempting to lose weight are generally recommended to set modest weight loss goals. The present study explores whether the amount of weight loss individuals strive for is associated with more positive psychological and behavioral outcomes. Hereto, 447 overweight and obese participants trying to lose weight completed two questionnaires with a 2-month interval. Many participants set goals that could be considered unrealistically high. However, higher weight loss goals did not predict dissatisfaction but predicted more effort in the weight loss attempt, as well as more self-reported short-term weight loss when baseline commitment and motivation were controlled for.

  4. Land Use Regression Models for Ultrafine Particles and Black Carbon Based on Short-Term Monitoring Predict Past Spatial Variation.

    PubMed

    Montagne, Denise R; Hoek, Gerard; Klompmaker, Jochem O; Wang, Meng; Meliefste, Kees; Brunekreef, Bert

    2015-07-21

    Health effects of long-term exposure to ultrafine particles (UFP) have not been investigated in epidemiological studies because of the lack of spatially resolved UFP exposure data. Short-term monitoring campaigns used to develop land use regression (LUR) models for UFP typically had moderate performance. The aim of this study was to develop and evaluate spatial and spatiotemporal LUR models for UFP and Black Carbon (BC), including their ability to predict past spatial contrasts. We measured 30 min at each of 81 sites in Amsterdam and 80 in Rotterdam, The Netherlands in three different seasons. Models were developed using traffic, land use, reference site measurements, routinely measured pollutants and weather data. The percentage explained variation (R(2)) was 0.35-0.40 for BC and 0.33-0.42 for UFP spatial models. Traffic variables were present in every model. The coefficients for the spatial predictors were similar in spatial and spatiotemporal models. The BC LUR model explained 61% of the spatial variation in a previous campaign with longer sampling duration, better than the model R(2). The UFP LUR model explained 36% of UFP spatial variation measured 10 years earlier, similar to the model R(2). Short-term monitoring campaigns may be an efficient tool to develop LUR models.

  5. Short-term variability in body weight predicts long-term weight gain.

    PubMed

    Lowe, Michael R; Feig, Emily H; Winter, Samantha R; Stice, Eric

    2015-11-01

    Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation. In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo. A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later. Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting. Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131. © 2015 American Society for Nutrition.

  6. Short-term variability in body weight predicts long-term weight gain1

    PubMed Central

    Lowe, Michael R; Feig, Emily H; Winter, Samantha R; Stice, Eric

    2015-01-01

    Background: Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation. Objective: In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo. Design: A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later. Results: Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting. Conclusions: Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131. PMID:26354535

  7. Ultra Short-term Prediction of Pole Coordinates via Combination of Empirical Mode Decomposition and Neural Networks

    NASA Astrophysics Data System (ADS)

    Lei, Yu; Zhao, Danning; Cai, Hongbing

    2016-12-01

    It was shown in the previous study that the increase of pole coordinates prediction error for about 100 days in the future is mostly caused by irregular short period oscillations. In this paper, the ultra short-term prediction of pole coordinates is studied for 10 days in the future by means of combination of empirical mode decomposition (EMD) and neural networks (NN), denoted EMD-NN. In the algorithm, EMD is employed as a low pass filter for eliminating high frequency signals from observed pole coordinates data. Then the annual and Chandler wobbles are removed a priori from pole coordinates data with high frequency signals eliminated. Finally, the radial basis function (RBF) networks are used to model and predict the residuals. The prediction performance of the EMD-NN approach is compared with that of the NN-only solution and the prediction methods and techniques involved in the Earth orientation parameters prediction comparison campaign (EOP PCC). The results show that the prediction accuracy of the EMD-NN algorithm is better than that of the NN-only solution and is also comparable with that of the other existing prediction method and techniques.

  8. Testing an earthquake prediction algorithm

    USGS Publications Warehouse

    Kossobokov, V.G.; Healy, J.H.; Dewey, J.W.

    1997-01-01

    A test to evaluate earthquake prediction algorithms is being applied to a Russian algorithm known as M8. The M8 algorithm makes intermediate term predictions for earthquakes to occur in a large circle, based on integral counts of transient seismicity in the circle. In a retroactive prediction for the period January 1, 1985 to July 1, 1991 the algorithm as configured for the forward test would have predicted eight of ten strong earthquakes in the test area. A null hypothesis, based on random assignment of predictions, predicts eight earthquakes in 2.87% of the trials. The forward test began July 1, 1991 and will run through December 31, 1997. As of July 1, 1995, the algorithm had forward predicted five out of nine earthquakes in the test area, which success ratio would have been achieved in 53% of random trials with the null hypothesis.

  9. Predictive factors of short term outcome after liver transplantation: A review

    PubMed Central

    Bolondi, Giuliano; Mocchegiani, Federico; Montalti, Roberto; Nicolini, Daniele; Vivarelli, Marco; De Pietri, Lesley

    2016-01-01

    Liver transplantation represents a fundamental therapeutic solution to end-stage liver disease. The need for liver allografts has extended the set of criteria for organ acceptability, increasing the risk of adverse outcomes. Little is known about the early postoperative parameters that can be used as valid predictive indices for early graft function, retransplantation or surgical reintervention, secondary complications, long intensive care unit stay or death. In this review, we present state-of-the-art knowledge regarding the early post-transplantation tests and scores that can be applied during the first postoperative week to predict liver allograft function and patient outcome, thereby guiding the therapeutic and surgical decisions of the medical staff. Post-transplant clinical and biochemical assessment of patients through laboratory tests (platelet count, transaminase and bilirubin levels, INR, factor V, lactates, and Insulin Growth Factor 1) and scores (model for end-stage liver disease, acute physiology and chronic health evaluation, sequential organ failure assessment and model of early allograft function) have been reported to have good performance, but they only allow late evaluation of patient status and graft function, requiring days to be quantified. The indocyanine green plasma disappearance rate has long been used as a liver function assessment technique and has produced interesting, although not univocal, results when performed between the 1th and the 5th day after transplantation. The liver maximal function capacity test is a promising method of metabolic liver activity assessment, but its use is limited by economic cost and extrahepatic factors. To date, a consensual definition of early allograft dysfunction and the integration and validation of the above-mentioned techniques, through the development of numerically consistent multicentric prospective randomised trials, are necessary. The medical and surgical management of transplanted patients

  10. Use of "Crowd-Sourcing" and other collaborations to solve the short-term, earthquake forecasting problem

    NASA Astrophysics Data System (ADS)

    Bleier, T.; Heraud, J. A.; Dunson, J. C.

    2015-12-01

    QuakeFinder (QF) and its international collaborators have installed and currently maintain 165 three-axis induction magnetometer instrument sites in California, Peru, Taiwan, Greece, Chile and Sumatra. The data from these instruments are being analyzed for pre-quake signatures. This analysis consists of both private research by QuakeFinder, and institutional collaborators (PUCP in Peru, NCU in Taiwan, PUCC in Chile, NOA in Greece, Syiah Kuala University in Indonesia, LASP at U of Colo., Stanford, and USGS). Recently, NASA Hq and QuakeFinder tried a new approach to help with the analysis of this huge (50+TB) data archive. A collaboration with Apirio/TopCoder, Harvard University, Amazon, QuakeFinder, and NASA Hq. resulted in an open algorithm development contest called "Quest for Quakes" in which contestants (freelance algorithm developers) attempted to identify quakes from a subset of the QuakeFinder data (3TB). The contest included a $25K prize pool, and contained 100 cases where earthquakes (and null sets) included data from up to 5 remote sites, near and far from quakes greater than M4. These data sets were made available through Amazon.com to hundreds of contestants over a two week contest period. In a more traditional approach, several new algorithms were tried by actively sharing the QF data with universities over a longer period. These algorithms included Principal Component Analysis-PCA and deep neural networks in an effort to automatically identify earthquake signals within typical, noise-filled environments. This presentation examines the pros and cons of employing these two approaches, from both logistical and scientific perspectives.

  11. Short-term prediction of solar irradiance using time-series analysis

    SciTech Connect

    Chowdhury, B.H. . Dept. of Electrical Engineering)

    1990-01-01

    A new statistical model for solar irradiance prediction is described. The method makes use of the atmospheric parameterizations as well as a time-series model to forecast a sequence of global irradiance in the 3--10 min time frame. A survey of some of the prominent research of the recent past reveals a definite lack of irradiance models that approach subhourly intervals, especially in the range mentioned. In this article, accurate parameterizations of atmospheric phenomena are used in a prewhitening process so that a time-series model may be used effectively to forecast irradiance components up to an hour in advance in the 3--10 min time intervals. The model requires only previous global horizontal irradiance measurement at a site. Results show that when compared with actual data on two locations in the southeaster United States, the forecasts are quite accurate, and the model is site-independent. Under some instances, forecasts may be inaccurate when there are sudden transitional changes in the cloud cover moving across the sun. In order for the proposed irradiance model to predict such transitional changes correctly, frequent forecast updates become necessary.

  12. Space geodesy and earthquake prediction

    NASA Technical Reports Server (NTRS)

    Bilham, Roger

    1987-01-01

    Earthquake prediction is discussed from the point of view of a new development in geodesy known as space geodesy, which involves the use of extraterrestrial sources or reflectors to measure earth-based distances. Space geodesy is explained, and its relation to terrestrial geodesy is examined. The characteristics of earthquakes are reviewed, and the ways that they can be exploited by space geodesy to predict earthquakes is demonstrated.

  13. Space geodesy and earthquake prediction

    NASA Technical Reports Server (NTRS)

    Bilham, Roger

    1987-01-01

    Earthquake prediction is discussed from the point of view of a new development in geodesy known as space geodesy, which involves the use of extraterrestrial sources or reflectors to measure earth-based distances. Space geodesy is explained, and its relation to terrestrial geodesy is examined. The characteristics of earthquakes are reviewed, and the ways that they can be exploited by space geodesy to predict earthquakes is demonstrated.

  14. Predicting children's short-term exposure to pesticides: results of a questionnaire screening approach.

    PubMed Central

    Sexton, Ken; Adgate, John L; Eberly, Lynn E; Clayton, C Andrew; Whitmore, Roy W; Pellizzari, Edo D; Lioy, Paul J; Quackenboss, James J

    2003-01-01

    The ability of questionnaires to predict children's exposure to pesticides was examined as part of the Minnesota Children's Pesticide Exposure Study (MNCPES). The MNCPES focused on a probability sample of 102 children between the ages of 3 and 13 years living in either urban (Minneapolis and St. Paul, MN) or nonurban (Rice and Goodhue Counties in Minnesota) households. Samples were collected in a variety of relevant media (air, food, beverages, tap water, house dust, soil, urine), and chemical analyses emphasized three organophosphate insecticides (chlorpyrifos, diazinon, malathion) and a herbicide (atrazine). Results indicate that the residential pesticide-use questions and overall screening approach used in the MNCPES were ineffective for identifying and oversampling children/households with higher levels of individual target pesticides. PMID:12515690

  15. Exaggerated Claims About Earthquake Predictions

    NASA Astrophysics Data System (ADS)

    Kafka, Alan L.; Ebel, John E.

    2007-01-01

    The perennial promise of successful earthquake prediction captures the imagination of a public hungry for certainty in an uncertain world. Yet, given the lack of any reliable method of predicting earthquakes [e.g., Geller, 1997; Kagan and Jackson, 1996; Evans, 1997], seismologists regularly have to explain news stories of a supposedly successful earthquake prediction when it is far from clear just how successful that prediction actually was. When journalists and public relations offices report the latest `great discovery' regarding the prediction of earthquakes, seismologists are left with the much less glamorous task of explaining to the public the gap between the claimed success and the sober reality that there is no scientifically proven method of predicting earthquakes.

  16. Short-term predicted extinction of Andean populations of the lizard Stenocercus guentheri (Iguanidae: Tropidurinae).

    PubMed

    Andrango, María Belén; Sette, Carla; Torres-Carvajal, Omar

    2016-12-01

    We studied the thermal physiology of the Andean lizard Stenocercus guentheri in order to evaluate the possible effects of global warming on this species. We determined the preferred body temperature (Tpref), critical thermals (CTmin, CTmax), and hours of restriction and activity. Tpref was 32.14±1.83°C; CTmin was 8.31°C in adults and 9.14°C in juveniles, whereas CTmax was 43.28°C in adults and 41.68°C in juveniles. To assess extinction risk, we used the model created by Sinervo et al. (2010) and predicted that 16.7% of populations will have a high risk of extinction by 2020, with an increase to 26.7% by 2050. These results suggest that this species, despite being able to maintain its Tpref through behavioral thermoregulation and habitat selection, could be physiologically sensitive to climate warming; thus, the potential for local adaptation may be limited under a warmer climate. Further studies focusing on the ability of S. guentheri to evolve higher Tpref and thermal tolerances are needed to understand the ability of this species to respond to climate change. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Superoxide Dismutase: A Predicting Factor for Boar Semen Characteristics for Short-Term Preservation

    PubMed Central

    Nemec Svete, Alenka

    2014-01-01

    Superoxide dismutase (SOD), total antioxidant capacity (TAC), and thiobarbituric acid reactive substances (TBARS) in seminal plasma were evaluated on the basis of receiver operating characteristics (ROC) analysis as predictors for distinguishing satisfactory from unsatisfactory boar semen samples after storage. SOD on day 0 correlated significantly with progressive motility (r = −0.686; P < 0.05) and viability (r = −0.513; P < 0.05) after storage; TBARS correlated only with motility (r = −0.480; P < 0.05). Semen samples that, after 3 days of storage, fulfilled all criteria for semen characteristics (viability > 85%, motility > 70%, progressive motility > 25%, and normal morphology > 50%) had significantly lower SOD levels on the day 0 than those with at least one criterion not fulfilled (P < 0.05) following storage. SOD levels of less than 1.05 U/mL predicted with 87.5% accuracy that fresh semen will suit the requirements for satisfactory semen characteristics after storage, while semen with SOD levels higher than 1.05 U/mL will not fulfill with 100% accuracy at least one semen characteristic after storage. These results support the proposal that SOD in fresh boar semen can be used as a predictor of semen quality after storage. PMID:24729963

  18. Cognitive impairment predicts worse short-term response to spinal tap test in normal pressure hydrocephalus.

    PubMed

    Wolfsegger, Thomas; Topakian, Raffi

    2017-08-15

    In patients with idiopathic normal pressure hydrocephalus (iNPH), the spinal tap test (STT) is commonly used to predict ventriculoperitoneal shunt responsiveness. Clinical improvement following STT usually is measured by testing gait function. In our study, we investigated the impact of cognitive impairment on gait improvement after STT. 22 patients with the clinical and radiological diagnosis of iNPH underwent gait analyses (mobile measuring system Medilogic) before and 2-4h after STT in self-paced gait velocity over 7m. Prior to STT, cognition was evaluated by the Mini Mental State Examination (MMSE). MMSE<24/30 points was used to define the subgroup of patients with cognitive impairment (iNPH-CI). Spatio-temporal parameters of gait before STT vs. after STT were analyzed with ANOVA with repeated measures. 1. Baseline gait parameters did not differ between the two groups: patients with iNPH and normal cognition (n=11) and patients with iNPH-CI (n=11). 2. Following STT, there was significant improvement of gait parameters in patients without cognitive impairment, while patients with iNPH-CI did not benefit from STT. Subjects with iNPH have a higher probability of lack of gait improvement 2-4h following STT, if cognitive impairment is present. Further studies are needed to elucidate the associations of cognitive impairment and quantitative gait parameters measured early and at later time points after STT. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Long-term irradiance observation and short-term flare prediction with LYRA on PROBA2

    NASA Astrophysics Data System (ADS)

    Dammasch, Ingolf; Dominique, Marie; West, Matthew; Katsiyannis, Thanassis; Ryan, Daniel; Wauters, Laurence

    The solar radiometer LYRA on board the ESA micro-satellite PROBA2 has observed the Sun continuously since January 2010 in various spectral band passes, and has gained a considerable data base. Two of the LYRA channels cover the irradiance between soft X-ray and extreme ultraviolet. The variation of the sunspot number appears to show a strong similarity with the variation of these channels, when their long-range development is taken into account. The same holds for SXR levels observed by the GOES satellites. Due to LYRA's bandwidth and coverage of various active-region temperatures, its relatively smooth development may yield some information on the structure of the current solar cycle. On its websites, LYRA presents not only EUV and SXR time series in near real-time, but also information on flare parameters and long-term irradiance and sunspot levels. It will be demonstrated whether it is possible to aid space weather forecast with these statistical data, especially for the prediction of expected flare strength on a daily basis.

  20. Dissociation predicts symptom-related treatment outcome in short-term inpatient psychotherapy.

    PubMed

    Spitzer, Carsten; Barnow, Sven; Freyberger, Harald J; Grabe, Hans Joergen

    2007-08-01

    Previous research has indicated that dissociation might be a negative predictor of treatment outcome in cognitive behavioural therapy for patients with obsessive-compulsive and anxiety disorders. Using a naturalistic design it was hypothesized that higher levels of dissociation predict poorer outcome in inpatients with affective, anxiety and somatoform disorders participating in a brief psychodynamic psychotherapy. A total of 133 patients completed the Symptom Check List (SCL-90), the German short version of the Dissociative Experiences Scale and the Inventory of Interpersonal Problems at the beginning and the end of treatment. The Global Severity Index (GSI) of the SCL-90 was chosen as outcome criterion. A total of 62.4% of study participants were classified as treatment responders, that is, they showed a statistically significant change of their GSI scores. Controlling for general psychopathology, the non-responders had significantly higher baseline dissociation scores than the responders. In a logistic regression analysis with non-response as a dependent variable, a comorbid personality disorder, low baseline psychopathology and high dissociation levels emerged as relevant predictors, but interpersonal problems and other comorbid disorders did not. Dissociation has a negative impact on treatment outcome. It is suggested that dissociative subjects dissociate as a response to negative emotions arising in psychotherapy leading to a less favourable outcome. Additionally, dissociative patients may have an insecure attachment pattern negatively affecting the therapeutic relationship. Thus, dissociation may directly and indirectly influence the treatment process and outcome.

  1. A hybrid model for short-term bacillary dysentery prediction in Yichang City, China.

    PubMed

    Yan, Weirong; Xu, Yong; Yang, Xiaobing; Zhou, Yikai

    2010-07-01

    Bacillary dysentery is still a common and serious public health problem in China. This paper is aimed at developing and evaluating an innovative hybrid model, which combines the seasonal autoregressive integrated moving average (SARIMA) and the generalized regression neural network (GRNN) models, for bacillary dysentery forecasting. Data of monthly bacillary dysentery incidence in Yichang City from 2000-2007 was obtained from Yichang Disease Control and Prevention Center. The SARIMA and SARIMA-GRNN model were developed and validated by dividing the data file into two data sets: data from the past 5 years was used to construct the models, and data from January to June of the 6th year was used to validate them. Simulation and forecasting performance was evaluated and compared between the two models. The hybrid SARIMA-GRNN model was found to outperform the SARIMA model with the lower mean square error, mean absolute error, and mean absolute percentage error in simulation and prediction results. Developing and applying the SARIMA-GRNN hybrid model is an effective decision supportive method for producing reliable forecasts of bacillary dysentery for the study area.

  2. Short-term load and wind power forecasting using neural network-based prediction intervals.

    PubMed

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2014-02-01

    Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

  3. Inflammatory Activity on Natalizumab Predicts Short-Term but Not Long-Term Disability in Multiple Sclerosis

    PubMed Central

    Dahdaleh, Samer; Malik, Omar; Jones, Brynmor; Nicholas, Richard

    2017-01-01

    Background In people with multiple sclerosis treated with interferon-beta or glatiramer acetate, new MRI lesions and relapses during the first year of treatment predict a poor prognosis. Objective To study this association in those receiving natalizumab. Methods Data were collected on relapses, new MRI activity, and Modified Rio Score after initiation of natalizumab in an observational cohort of 161 patients with high baseline disability. These were correlated with Expanded Disability Status Scale (EDSS) progression at years 1, 2, 3, and 3–7 after treatment initiation, versus pre-treatment baseline. Results 46/161 patients had a relapse in the first year and 44/161 had EDSS progression by year 2. Relapses and Modified Rio Score in the first year of treatment predicted EDSS progression at year 1 and 2 after treatment initiation. However, this effect disappeared with longer follow-up. Paradoxically, there was a trend towards inflammatory activity on treatment (first year Modified Rio Score, relapses, and MRI activity) predicting a lower risk of EDSS progression by years 3–7, although this did not reach statistical significance. Those with and without EDSS progression did not differ in baseline age, EDSS, or pre-treatment relapse rate. Relapses in year 0–1 predicted further relapses in years 1–3. Conclusions Breakthrough inflammatory activity after natalizumab treatment is predictive of short-term outcome measures of relapses or EDSS progression, but does not predict longer term EDSS progression, in this cohort with high baseline disability. PMID:28081190

  4. Predicting short-term survival after liver transplantation on eight score systems: a national report from China Liver Transplant Registry.

    PubMed

    Ling, Qi; Dai, Haojiang; Zhuang, Runzhou; Shen, Tian; Wang, Weilin; Xu, Xiao; Zheng, Shusen

    2017-02-13

    To compare the performance of eight score systems (MELD, uMELD, MELD-Na. iMELD, UKELD, MELD-AS, CTP, and mCTP) in predicting the post-transplant mortality, we analyzed the data of 6,014 adult cirrhotic patients who underwent liver transplantation between January 2003 and December 2010 from the China Liver Transplant Registry database. In hepatitis B virus (HBV) group, MELD, uMELD and MELD-AS showed good predictive accuracies at 3-month mortality after liver transplantation; by comparison with other five models, MELD presented the best ability in predicting 3-month, 6-month and 1-year mortality, showing a significantly better predictive ability than UKELD and iMELD. In hepatitis C virus and Alcohol groups, the predictive ability did not differ significantly between MELD and other models. Patient survivals in different MELD categories were of statistically significant difference. Among patients with MELD score >35, a new prognostic model based on serum creatinine, need for hemodialysis and moderate ascites could identify the sickest one. In conclusion, MELD is superior to other score systems in predicting short-term post-transplant survival in patients with HBV-related liver disease. Among patients with MELD score >35, a new prognostic model can identify the sickest patients who should be excluded from waiting list to prevent wasteful transplantation.

  5. Inflammatory Activity on Natalizumab Predicts Short-Term but Not Long-Term Disability in Multiple Sclerosis.

    PubMed

    Raffel, Joel; Gafson, Arie R; Dahdaleh, Samer; Malik, Omar; Jones, Brynmor; Nicholas, Richard

    2017-01-01

    In people with multiple sclerosis treated with interferon-beta or glatiramer acetate, new MRI lesions and relapses during the first year of treatment predict a poor prognosis. To study this association in those receiving natalizumab. Data were collected on relapses, new MRI activity, and Modified Rio Score after initiation of natalizumab in an observational cohort of 161 patients with high baseline disability. These were correlated with Expanded Disability Status Scale (EDSS) progression at years 1, 2, 3, and 3-7 after treatment initiation, versus pre-treatment baseline. 46/161 patients had a relapse in the first year and 44/161 had EDSS progression by year 2. Relapses and Modified Rio Score in the first year of treatment predicted EDSS progression at year 1 and 2 after treatment initiation. However, this effect disappeared with longer follow-up. Paradoxically, there was a trend towards inflammatory activity on treatment (first year Modified Rio Score, relapses, and MRI activity) predicting a lower risk of EDSS progression by years 3-7, although this did not reach statistical significance. Those with and without EDSS progression did not differ in baseline age, EDSS, or pre-treatment relapse rate. Relapses in year 0-1 predicted further relapses in years 1-3. Breakthrough inflammatory activity after natalizumab treatment is predictive of short-term outcome measures of relapses or EDSS progression, but does not predict longer term EDSS progression, in this cohort with high baseline disability.

  6. Predicting short-term survival after liver transplantation on eight score systems: a national report from China Liver Transplant Registry

    PubMed Central

    Ling, Qi; Dai, Haojiang; Zhuang, Runzhou; Shen, Tian; Wang, Weilin; Xu, Xiao; Zheng, Shusen

    2017-01-01

    To compare the performance of eight score systems (MELD, uMELD, MELD-Na. iMELD, UKELD, MELD-AS, CTP, and mCTP) in predicting the post-transplant mortality, we analyzed the data of 6,014 adult cirrhotic patients who underwent liver transplantation between January 2003 and December 2010 from the China Liver Transplant Registry database. In hepatitis B virus (HBV) group, MELD, uMELD and MELD-AS showed good predictive accuracies at 3-month mortality after liver transplantation; by comparison with other five models, MELD presented the best ability in predicting 3-month, 6-month and 1-year mortality, showing a significantly better predictive ability than UKELD and iMELD. In hepatitis C virus and Alcohol groups, the predictive ability did not differ significantly between MELD and other models. Patient survivals in different MELD categories were of statistically significant difference. Among patients with MELD score >35, a new prognostic model based on serum creatinine, need for hemodialysis and moderate ascites could identify the sickest one. In conclusion, MELD is superior to other score systems in predicting short-term post-transplant survival in patients with HBV-related liver disease. Among patients with MELD score >35, a new prognostic model can identify the sickest patients who should be excluded from waiting list to prevent wasteful transplantation. PMID:28198820

  7. Earthquake prediction; fact and fallacy

    USGS Publications Warehouse

    Hunter, R.N.

    1976-01-01

    Earthquake prediction is a young and growing area in the field of seismology. Only a few years ago, experts in seismology were declaring flatly that it was impossible. Now, some successes have been achieved and more are expected. Within a few years, earthquakes may be predicted as routinely as the weather, and possibly with greater accuracy. 

  8. Can We Predict Earthquakes?

    ScienceCinema

    Johnson, Paul

    2016-09-09

    The only thing we know for sure about earthquakes is that one will happen again very soon. Earthquakes pose a vital yet puzzling set of research questions that have confounded scientists for decades, but new ways of looking at seismic information and innovative laboratory experiments are offering tantalizing clues to what triggers earthquakes — and when.

  9. Can We Predict Earthquakes?

    SciTech Connect

    Johnson, Paul

    2016-08-31

    The only thing we know for sure about earthquakes is that one will happen again very soon. Earthquakes pose a vital yet puzzling set of research questions that have confounded scientists for decades, but new ways of looking at seismic information and innovative laboratory experiments are offering tantalizing clues to what triggers earthquakes — and when.

  10. Projected climate change impacts and short term predictions on staple crops in Sub-Saharan Africa

    NASA Astrophysics Data System (ADS)

    Mereu, V.; Spano, D.; Gallo, A.; Carboni, G.

    2013-12-01

    . Multiple combinations of soils and climate conditions, crop management and varieties were considered for the different Agro-Ecological Zones. The climate impact was assessed using future climate prediction, statistically and/or dynamically downscaled, for specific areas. Direct and indirect effects of different CO2 concentrations projected for the future periods were separately explored to estimate their effects on crops. Several adaptation strategies (e.g., introduction of full irrigation, shift of the ordinary sowing/planting date, changes in the ordinary fertilization management) were also evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analyzed at local, AEZ and country level, will be discussed.

  11. Total Serum Bilirubin within Three Months of Hepatoportoenterostomy Predicts Short-term Outcomes in Biliary Atresia

    PubMed Central

    Shneider, Benjamin L.; Magee, John C.; Karpen, Saul J.; Rand, Elizabeth B.; Narkewicz, Michael R.; Bass, Lee M.; Schwarz, Kathleen; Whitington, Peter F.; Bezerra, Jorge A.; Kerkar, Nanda; Haber, Barbara; Rosenthal, Philip; Turmelle, Yumirle P.; Molleston, Jean P.; Murray, Karen F.; Ng, Vicky L.; Wang, Kasper S.; Romero, Rene; Squires, Robert H.; Arnon, Ronen; Sherker, Averell H.; Moore, Jeffrey; Ye, Wen; Sokol, Ronald J.

    2015-01-01

    Objectives To prospectively assess the value of serum total bilirubin (TB) within 3 months of hepatoportoenterostomy (HPE) in infants with biliary atresia (BA) as a biomarker predictive of clinical sequelae of liver disease in the first two years of life. Study design Infants with BA undergoing HPE between June 2004-January 2011 were enrolled in a prospective, multicenter study. Complications were monitored until 2 years of age or the earliest of liver transplant (LT), death, or study withdrawal. TB below 2 mg/dL (34.2 μM) at any time in the first 3 months (TB<2.0, all others = TB≥2) after HPE was examined as a biomarker, using Kaplan-Meier survival and logistic regression. Results Fifty percent (68/137) of infants had TB<2.0 in the first 3 months after HPE. Transplant-free survival at 2 years was significantly higher in the TB<2.0 group vs. TB≥2 (86% vs. 20%, p<0.0001). Infants with TB≥2 had diminished weight gain (p<0.0001), greater probability of developing ascites (OR 6.4, 95% CI 2.9–14.1, p<0.0001), hypoalbuminemia (OR 7.6, 95% CI 3.2–17.7, p< 0.0001), coagulopathy (OR 10.8, 95% CI 3.1–38.2, p=0.0002), LT (OR 12.4, 95% CI 5.3–28.7, p<0.0001), or LT or death (OR 16.8, 95% CI 7.2–39.2, p<0.0001). Conclusions Infants whose TB does not fall below 2.0 mg/dL within 3 months of HPE were at high risk for early disease progression, suggesting they should be considered for LT in a timely fashion. Interventions increasing the likelihood of achieving TB <2.0 mg/dL within 3 months of HPE may enhance early outcomes. PMID:26725209

  12. Quantitative analysis of ventricular ectopic beats in short-term RR interval recordings to predict imminent ventricular tachyarrhythmia.

    PubMed

    Martínez-Alanis, Marisol; Ruiz-Velasco, Silvia; Lerma, Claudia

    2016-12-15

    Most approaches to predict ventricular tachyarrhythmias which are based on RR intervals consider only sinus beats, excluding premature ventricular complexes (PVCs). The method known as heartprint, which analyses PVCs and their characteristics, has prognostic value for fatal arrhythmias on long recordings of RR intervals (>70,000 beats). To evaluate characteristics of PVCs from short term recordings (around 1000 beats) and their prognostic value for imminent sustained tachyarrhythmia. We analyzed 132 pairs of short term RR interval recordings (one before tachyarrhythmia and one control) obtained from 78 patients. Patients were classified into two groups based on the history of accelerated heart rate (HR) (HR>90bpm) before a tachyarrhythmia episode. Heartprint indexes, such as mean coupling interval (meanCI) and the number of occurrences of the most prevalent form of PVCs (SNIB) were calculated. The predictive value of all the indexes and of the combination of different indexes was calculated. MeanCI shorter than 482ms and the occurrence of more repetitive arrhythmias (sNIB≥2.5), had a significant prognostic value for patients with accelerated heart rate: adjusted odds ratio of 2.63 (1.33-5.17) for meanCI and 2.28 (1.20-4.33) for sNIB. Combining these indexes increases the adjusted odds ratio: 10.94 (3.89-30.80). High prevalence of repeating forms of PVCs and shorter CI are potentially useful risk markers of imminent ventricular tachyarrhythmia. Knowing if a patient has history of VT/VF preceded by accelerated HR, improves the prognostic value of these risk markers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Alerts for Significant Seismicity Changes and the Short-term Prediction of the Mainshock from Foreshocks: Recent Experiences from Greece and Italy

    NASA Astrophysics Data System (ADS)

    Minadakis, G.; Orfanogiannaki, K.; Papadopoulos, G. A.

    2009-12-01

    The variation of seismicity in the space-time-size domains makes the earthquake process highly complex and the earthquake predictability extremely difficult. From operational point of view of particular interest is the identification of foreshocks as a short-term precursory signal before the mainshock. Although foreshock incidence has been detected before about 50% of strong mainshocks (M ≥ 5.5), foreshocks are characterized by some diagnostic features: they occur in the source of the mainshock up to about 10 days before the mainshock with probability more than 0.8; their number, N, increases with time t as of N~1/t, and the b-value of the G-R relation drops with respect to the b-value in the background seismicity, in the swarms and in the aftershock period. Therefore, the discrimination between foreshocks and other states of seismicity, i.e. background seismicity, swarms, aftershocks, is of crucial importance. In a given target area this can be done by determining the seismicity variations in time and size from the significant changes of the seismicity rate, r, and the b-value of the G-R relation. We have developed the algorithm FORMA (FORshock-Mainshock-Aftershock) specially designed to detect such changes of r, based on the z-test (significance level, p), and of the b-value based on the Utsu-test (significance level, P). Also, FORMA is capable to update the earthquake catalogue at any time automatically by computer networking and to produce alert levels with time step of 1 day for the detection of changes in the states of seismicity based on the concurrent significant variations of r and b. We set-up FORMA to produce four alert levels: green (p ≥ 0.9, P ≥ 0.1), yellow (p ≥ 0.90, 0.1 ≥P ≥ 0.05), blue (p ≥ 0.95, 0.1 ≥P ≥ 0.05), and red (p ≥ 0.95, P ≤ 0.05). Results are presented for successful a posteriori application of the algorithm for the short-term prediction of some recent strong mainshocks in Greece and Italy, including the 6 April

  14. Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

    PubMed Central

    Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

    2012-01-01

    Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

  15. Short-term predictions by statistical methods in regions of varying dynamical error growth in a chaotic system

    NASA Astrophysics Data System (ADS)

    Mittal, A. K.; Singh, U. P.; Tiwari, A.; Dwivedi, S.; Joshi, M. K.; Tripathi, K. C.

    2015-08-01

    In a nonlinear, chaotic dynamical system, there are typically regions in which an infinitesimal error grows and regions in which it decays. If the observer does not know the evolution law, recourse is taken to non-dynamical methods, which use the past values of the observables to fit an approximate evolution law. This fitting can be local, based on past values in the neighborhood of the present value as in the case of Farmer-Sidorowich (FS) technique, or it can be global, based on all past values, as in the case of Artificial Neural Networks (ANN). Short-term predictions are then made using the approximate local or global mapping so obtained. In this study, the dependence of statistical prediction errors on dynamical error growth rates is explored using the Lorenz-63 model. The regions of dynamical error growth and error decay are identified by the bred vector growth rates or by the eigenvalues of the symmetric Jacobian matrix. The prediction errors by the FS and ANN techniques in these two regions are compared. It is found that the prediction errors by statistical methods do not depend on the dynamical error growth rate. This suggests that errors using statistical methods are independent of the dynamical situation and the statistical methods may be potentially advantageous over dynamical methods in regions of low dynamical predictability.

  16. Shared Neural Mechanisms for the Prediction of Own and Partner Musical Sequences after Short-term Piano Duet Training.

    PubMed

    Lappe, Claudia; Bodeck, Sabine; Lappe, Markus; Pantev, Christo

    2017-01-01

    Predictive mechanisms in the human brain can be investigated using markers for prediction violations like the mismatch negativity (MMN). Short-term piano training increases the MMN for melodic and rhythmic deviations in the training material. This increase occurs only when the material is actually played, not when it is only perceived through listening, suggesting that learning predictions about upcoming musical events are derived from motor involvement. However, music is often performed in concert with others. In this case, predictions about upcoming actions from a partner are a crucial part of the performance. In the present experiment, we use magnetoencephalography (MEG) to measure MMNs to deviations in one's own and a partner's musical material after both engaged in musical duet training. Event-related field (ERF) results revealed that the MMN increased significantly for own and partner material suggesting a neural representation of the partner's part in a duet situation. Source analysis using beamforming revealed common activations in auditory, inferior frontal, and parietal areas, similar to previous results for single players, but also a pronounced contribution from the cerebellum. In addition, activation of the precuneus and the medial frontal cortex was observed, presumably related to the need to distinguish between own and partner material.

  17. Flirting with disaster: short-term mating orientation and hostile sexism predict different types of sexual harassment.

    PubMed

    Diehl, Charlotte; Rees, Jonas; Bohner, Gerd

    2012-01-01

    We combine evolutionary and sociocultural accounts of sexual harassment, proposing that sexuality-related and hostility-related motives lead to different types of harassment. Specifically, men's short-term mating orientation (STMO) was hypothesized to predict only unwanted sexual attention but not gender harassment, whereas men's hostile sexism (HS) was hypothesized to predict both unwanted sexual attention and gender harassment. As part of an alleged computer-chat task, 100 male students could send sexualized personal remarks (representing unwanted sexual attention), sexist jokes (representing gender harassment), or nonharassing material to an attractive female target. Independently, participants' STMO, HS, and sexual harassment myth acceptance (SHMA) were assessed. Correlational and path analyses revealed that STMO specifically predicted unwanted sexual attention, whereas HS predicted both unwanted sexual attention and gender harassment. Furthermore, SHMA fully mediated the effect of HS on gender harassment, but did not mediate effects of STMO or HS on unwanted sexual attention. Results are discussed in relation to motivational explanations for sexual harassment and antiharassment interventions. © 2012 Wiley Periodicals, Inc.

  18. Earthquake Prediction in a Big Data World

    NASA Astrophysics Data System (ADS)

    Kossobokov, V. G.

    2016-12-01

    The digital revolution started just about 15 years ago has already surpassed the global information storage capacity of more than 5000 Exabytes (in optimally compressed bytes) per year. Open data in a Big Data World provides unprecedented opportunities for enhancing studies of the Earth System. However, it also opens wide avenues for deceptive associations in inter- and transdisciplinary data and for inflicted misleading predictions based on so-called "precursors". Earthquake prediction is not an easy task that implies a delicate application of statistics. So far, none of the proposed short-term precursory signals showed sufficient evidence to be used as a reliable precursor of catastrophic earthquakes. Regretfully, in many cases of seismic hazard assessment (SHA), from term-less to time-dependent (probabilistic PSHA or deterministic DSHA), and short-term earthquake forecasting (StEF), the claims of a high potential of the method are based on a flawed application of statistics and, therefore, are hardly suitable for communication to decision makers. Self-testing must be done in advance claiming prediction of hazardous areas and/or times. The necessity and possibility of applying simple tools of Earthquake Prediction Strategies, in particular, Error Diagram, introduced by G.M. Molchan in early 1990ies, and Seismic Roulette null-hypothesis as a metric of the alerted space, is evident. The set of errors, i.e. the rates of failure and of the alerted space-time volume, can be easily compared to random guessing, which comparison permits evaluating the SHA method effectiveness and determining the optimal choice of parameters in regard to a given cost-benefit function. These and other information obtained in such a simple testing may supply us with a realistic estimates of confidence and accuracy of SHA predictions and, if reliable but not necessarily perfect, with related recommendations on the level of risks for decision making in regard to engineering design, insurance

  19. Early systemic sclerosis: short-term disease evolution and factors predicting the development of new manifestations of organ involvement

    PubMed Central

    2012-01-01

    Introduction We investigated early systemic sclerosis (SSc) (that is, Raynaud's phenomenon with SSc marker autoantibodies and/or typical capillaroscopic findings and no manifestations other than puffy fingers or arthritis) versus undifferentiated connective tissue disease (UCTD) to identify predictors of short-term disease evolution. Methods Thirty-nine early SSc and 37 UCTD patients were investigated. At baseline, all patients underwent clinical evaluation, B-mode echocardiography, lung function tests and esophageal manometry to detect preclinical alterations of internal organs, and were re-assessed every year. Twenty-one early SSc and 24 UCTD patients, and 25 controls were also investigated for serum endothelial, T-cell and fibroblast activation markers. Results At baseline, 48.7% of early SSc and 37.8% of UCTD patients had at least one preclinical functional alteration (P > 0.05). Ninety-two percent of early SSc patients developed manifestations consistent with definite SSc (that is, skin sclerosis, digital ulcers/scars, two or more teleangectasias, clinically visible nailfold capillaries, cutaneous calcinosis, X-ray bibasilar lung fibrosis, X-ray esophageal dysmotility, ECG signs of myocardial fibrosis and laboratory signs of renal crisis) within five years versus 17.1% of UCTD patients (X2 = 12.26; P = 0.0005). Avascular areas (HR = 4.39 95% CI 1.18 to 16.3; P = 0.02), increased levels of soluble IL-2 receptor alpha (HR = 4.39; 95% CI 1.03 to 18.6; P = 0.03), and of procollagen III aminopropeptide predicted disease evolution (HR = 4.55; 95% CI 1.18 to 17; P = 0.04). Conclusion Most early SSc but only a few UCTD patients progress to definite SSc within a short-term follow-up. Measurement of circulating markers of T-cell and fibroblast activation might serve to identify early SSc patients who are more likely to develop features of definite SSc. PMID:22901779

  20. Identification and predicting short-term prognosis of early cardiorenal syndrome type 1: KDIGO is superior to RIFLE or AKIN.

    PubMed

    Li, Zhilian; Cai, Lu; Liang, Xinling; Du, Zhiming; Chen, Yuanhan; An, Shengli; Tan, Ning; Xu, Lixia; Li, Ruizhao; Li, Liwen; Shi, Wei

    2014-01-01

    Acute kidney injury (AKI) in patients hospitalized for acute heart failure (AHF) is usually type 1 of the cardiorenal syndrome (CRS) and has been associated with increased morbidity and mortality. Early recognition of AKI is critical. This study was to determine if the new KDIGO criteria (Kidney Disease: Improving Global Outcomes) for identification and short-term prognosis of early CRS type 1 was superior to the previous RIFLE and AKIN criteria. The association between AKI diagnosed by KDIGO but not by RIFLE or AKIN and in-hospital mortality was retrospectively evaluated in 1005 Chinese adult patients with AHF between July 2008 and May 2012. AKI was defined as RIFLE, AKIN and KDIGO criteria, respectively. Cox regression was used for multivariate analysis of in-hospital mortality. Within 7 days on admission, the incidence of CRS type 1 was 38.9% by KDIGO criteria, 34.7% by AKIN, and 32.1% by RIFLE. A total of 110 (10.9%) cases were additional diagnosed by KDIGO criteria but not by RIFLE or AKIN. 89.1% of them were in Stage 1 (AKIN) or Stage Risk (RIFLE). They accounted for 18.4% (25 cases) of the overall death. After adjustment, this proportion remained an independent risk factor for in-hospital mortality [odds ratios (OR)3.24, 95% confidence interval(95%CI) 1.97-5.35]. Kaplan-Meier curve showed AKI patients by RIFLE, AKIN, KDIGO and [K(+)R(-)+K(+)A(-)] had lower hospital survival than non-AKI patients (Log Rank P<0.001). KDIGO criteria identified significantly more CRS type 1 episodes than RIFLE or AKIN. AKI missed diagnosed by RIFLE or AKIN criteria was an independent risk factor for in-hospital mortality, indicating the new KDIGO criteria was superior to RIFLE and AKIN in predicting short-term outcomes in early CRS type 1.

  1. BCL2L12 Is a Novel Biomarker for the Prediction of Short-Term Relapse in Nasopharyngeal Carcinoma

    PubMed Central

    Fendri, Ali; Kontos, Christos K; Khabir, Abdelmajid; Mokdad-Gargouri, Raja; Scorilas, Andreas

    2011-01-01

    BCL2-like 12 (BCL2L12 ) is a new member of the apoptosis-related BCL2 gene family, members of which are implicated in various malignancies. Nasopharyngeal carcinoma is a highly metastatic, malignant epithelial tumor, with a high prevalence in Southeast Asia and North Africa. The purpose of the current study was to quantify and investigate the expression levels of the BCL2L12 gene in nasopharyngeal carcinoma biopsies and to assess its prognostic value. Total RNA was isolated from 89 malignant and hyperplastic nasopharyngeal biopsies from Tunisian patients. After testing the quality of the extracted RNA, cDNA was prepared by reverse transcription. A highly sensitive real-time polymerase chain reaction (PCR) method for BCL2L12 mRNA quantification was developed using SYBR® Green chemistry. GAPDH served as a reference gene. Relative quantification analysis was performed using the comparative CT (2−ΔΔCT) method. Higher BCL2L12 mRNA levels were detected in undifferentiated carcinomas of the nasopharynx, rather than in nonkeratinizing nasopharyngeal tumors (P = 0.045). BCL2L12 expression status was also found to be positively associated with the presence of distant metastases (P = 0.014). Kaplan-Meier survival analysis demonstrated that patients with BCL2L12-positive nasopharyngeal tumors have significantly shorter disease-free survival (P = 0.020). Cox regression analysis showed BCL2L12 expression to be an unfavorable and independent prognostic indicator of short-term relapse in nasopharyngeal carcinoma (P = 0.042). Our results suggest that mRNA expression of BCL2L12 may constitute a novel biomarker for the prediction of short-term relapse in nasopharyngeal carcinoma. PMID:21152697

  2. Identification and Predicting Short-Term Prognosis of Early Cardiorenal Syndrome Type 1: KDIGO Is Superior to RIFLE or AKIN

    PubMed Central

    Liang, Xinling; Du, Zhiming; Chen, Yuanhan; An, Shengli; Tan, Ning; Xu, Lixia; Li, Ruizhao; Li, Liwen; Shi, Wei

    2014-01-01

    Objective Acute kidney injury (AKI) in patients hospitalized for acute heart failure (AHF) is usually type 1 of the cardiorenal syndrome (CRS) and has been associated with increased morbidity and mortality. Early recognition of AKI is critical. This study was to determine if the new KDIGO criteria (Kidney Disease: Improving Global Outcomes) for identification and short-term prognosis of early CRS type 1 was superior to the previous RIFLE and AKIN criteria. Methods The association between AKI diagnosed by KDIGO but not by RIFLE or AKIN and in-hospital mortality was retrospectively evaluated in 1005 Chinese adult patients with AHF between July 2008 and May 2012. AKI was defined as RIFLE, AKIN and KDIGO criteria, respectively. Cox regression was used for multivariate analysis of in-hospital mortality. Results Within 7 days on admission, the incidence of CRS type 1 was 38.9% by KDIGO criteria, 34.7% by AKIN, and 32.1% by RIFLE. A total of 110 (10.9%) cases were additional diagnosed by KDIGO criteria but not by RIFLE or AKIN. 89.1% of them were in Stage 1 (AKIN) or Stage Risk (RIFLE). They accounted for 18.4% (25 cases) of the overall death. After adjustment, this proportion remained an independent risk factor for in-hospital mortality [odds ratios (OR)3.24, 95% confidence interval(95%CI) 1.97–5.35]. Kaplan-Meier curve showed AKI patients by RIFLE, AKIN, KDIGO and [K(+)R(−)+K(+)A(−)] had lower hospital survival than non-AKI patients (Log Rank P<0.001). Conclusion KDIGO criteria identified significantly more CRS type 1 episodes than RIFLE or AKIN. AKI missed diagnosed by RIFLE or AKIN criteria was an independent risk factor for in-hospital mortality, indicating the new KDIGO criteria was superior to RIFLE and AKIN in predicting short-term outcomes in early CRS type 1. PMID:25542014

  3. Increased Short-Term Variability of the QT Interval in Professional Soccer Players: Possible Implications for Arrhythmia Prediction

    PubMed Central

    Lengyel, Csaba; Orosz, Andrea; Hegyi, Péter; Komka, Zsolt; Udvardy, Anna; Bosnyák, Edit; Trájer, Emese; Pavlik, Gábor; Tóth, Miklós; Wittmann, Tibor; Papp, Julius Gy.; Varró, András; Baczkó, István

    2011-01-01

    Background Sudden cardiac death in competitive athletes is rare but it is significantly more frequent than in the normal population. The exact cause is seldom established and is mostly attributed to ventricular fibrillation. Myocardial hypertrophy and slow heart rate, both characteristic changes in top athletes in response to physical conditioning, could be associated with increased propensity for ventricular arrhythmias. We investigated conventional ECG parameters and temporal short-term beat-to-beat variability of repolarization (STVQT), a presumptive novel parameter for arrhythmia prediction, in professional soccer players. Methods Five-minute 12-lead electrocardiograms were recorded from professional soccer players (n = 76, all males, age 22.0±0.61 years) and age-matched healthy volunteers who do not participate in competitive sports (n = 76, all males, age 22.0±0.54 years). The ECGs were digitized and evaluated off-line. The temporal instability of beat-to-beat heart rate and repolarization were characterized by the calculation of short-term variability of the RR and QT intervals. Results Heart rate was significantly lower in professional soccer players at rest (61±1.2 vs. 72±1.5/min in controls). The QT interval was prolonged in players at rest (419±3.1 vs. 390±3.6 in controls, p<0.001). QTc was significantly longer in players compared to controls calculated with Fridericia and Hodges correction formulas. Importantly, STVQT was significantly higher in players both at rest and immediately after the game compared to controls (4.8±0.14 and 4.3±0.14 vs. 3.5±0.10 ms, both p<0.001, respectively). Conclusions STVQT is significantly higher in professional soccer players compared to age-matched controls, however, further studies are needed to relate this finding to increased arrhythmia propensity in this population. PMID:21526208

  4. Short-Term Precipitation Occurrence Prediction for Strong Convective Weather Using FY2-G Satellite Data: a Case Study of Shenzhen, South China

    NASA Astrophysics Data System (ADS)

    Chen, Kai; Liu, Jun; Guo, Shanxin; Chen, Jinsong; Liu, Ping; Qian, Jing; Chen, Huijuan; Sun, Bo

    2016-06-01

    Short-term precipitation commonly occurs in south part of China, which brings intensive precipitation in local region for very short time. Massive water would cause the intensive flood inside of city when precipitation amount beyond the capacity of city drainage system. Thousands people's life could be influenced by those short-term disasters and the higher city managements are required to facing these challenges. How to predict the occurrence of heavy precipitation accurately is one of the worthwhile scientific questions in meteorology. According to recent studies, the accuracy of short-term precipitation prediction based on numerical simulation model still remains low reliability, in some area where lack of local observations, the accuracy may be as low as 10%. The methodology for short term precipitation occurrence prediction still remains a challenge. In this paper, a machine learning method based on SVM was presented to predict short-term precipitation occurrence by using FY2-G satellite imagery and ground in situ observation data. The results were validated by traditional TS score which commonly used in evaluation of weather prediction. The results indicate that the proposed algorithm can present overall accuracy up to 90% for one-hour to six-hour forecast. The result implies the prediction accuracy could be improved by using machine learning method combining with satellite image. This prediction model can be further used to evaluated to predicted other characteristics of weather in Shenzhen in future.

  5. "Does short-term variation in fetal heart rate predict fetal acidaemia?" A systematic review and meta-analysis.

    PubMed

    Kapaya, Habiba; Jacques, Richard; Rahaim, Nadia; Anumba, Dilly

    2016-12-01

    To evaluate the association of short-term variation (STV) of the fetal heart rate in predicting fetal acidaemia at birth. The search strategy employed searching of electronic databases (MEDLINE, Web of Science, Scopus, and Google Scholar) and reference lists of relevant studies. Data were extracted from studies, adhering strictly to the following criteria: singleton pregnancy at ≥24 weeks' gestation, computerized CTG (index test) and calculation of STV before delivery. The outcome measure was arterial pH assessed in cord blood obtained at birth. Meta-analysis showed moderate accuracy of STV in predicting fetal acidaemia with a sensitivity of 0.57 (95% CI: 0.45-0.68), specificity of 0.81 (95% CI: 0.69-0.89), positive likelihood ratio of 3.14 (95% CI: 2.13-4.63) and negative likelihood ratio of 0.58, (95% CI: 0.46-0.72). However, in intra-uterine growth restricted fetuses, a small improvement in detecting acidaemia was observed; with a sensitivity of 0.63 (95% CI: 0.49-0.75) and negative likelihood ratio of 0.50 (95% CI: 0.31-0.80). STV appears to be a moderate predictor for fetal acidaemia. However, its usefulness as a stand-alone test in predicting acidaemia in clinical setting remains to be determined.

  6. Model predictions of features in microsaccade-related neural responses in a feedforward network with short-term synaptic depression

    NASA Astrophysics Data System (ADS)

    Zhou, Jian-Fang; Yuan, Wu-Jie; Zhou, Zhao; Zhou, Changsong

    2016-02-01

    Recently, the significant microsaccade-induced neural responses have been extensively observed in experiments. To explore the underlying mechanisms of the observed neural responses, a feedforward network model with short-term synaptic depression has been proposed [Yuan, W.-J., Dimigen, O., Sommer, W. and Zhou, C. Front. Comput. Neurosci. 7, 47 (2013)]. The depression model not only gave an explanation for microsaccades in counteracting visual fading, but also successfully reproduced several microsaccade-related features in experimental findings. These results strongly suggest that, the depression model is very useful to investigate microsaccade-related neural responses. In this paper, by using the model, we extensively study and predict the dependance of microsaccade-related neural responses on several key parameters, which could be tuned in experiments. Particularly, we provide a significant prediction that microsaccade-related neural response also complies with the property “sharper is better” observed in many contexts in neuroscience. Importantly, the property exhibits a power-law relationship between the width of input signal and the responsive effectiveness, which is robust against many parameters in the model. By using mean field theory, we analytically investigate the robust power-law property. Our predictions would give theoretical guidance for further experimental investigations of the functional role of microsaccades in visual information processing.

  7. Radon in earthquake prediction research.

    PubMed

    Friedmann, H

    2012-04-01

    The observation of anomalies in the radon concentration in soil gas and ground water before earthquakes initiated systematic investigations on earthquake precursor phenomena. The question what is needed for a meaningful earthquake prediction as well as what types of precursory effects can be expected is shortly discussed. The basic ideas of the dilatancy theory are presented which in principle can explain the occurrence of earthquake forerunners. The reasons for radon anomalies in soil gas and in ground water are clarified and a possible classification of radon anomalies is given.

  8. Can biological components predict short-term evolution in Autism Spectrum Disorders? A proof-of-concept study.

    PubMed

    Emberti Gialloreti, Leonardo; Benvenuto, Arianna; Battan, Barbara; Benassi, Francesca; Curatolo, Paolo

    2016-07-22

    The clinical and pathogenetic heterogeneity of Autism Spectrum Disorders (ASD) limits our ability to predict its short- and long-term evolution. Aim of this naturalistic study was to observe the clinical evolution of very young children with ASD for 12 months after first diagnosis, in order to identify those children who might develop a more positive trajectory and understand how a wide range of biological, clinical and familial factors can influence prognosis. Ninety-two children were characterized in terms of family history, prenatal and perinatal variables, and clinical conditions. The sample was divided into four subgroups based on the association of 22 biological, clinical and family history variables. Developmental Quotient (DQ), determined using the Psychoeducational Profile Revised (PEP-R), and symptoms severity, measured by means of the Autism Diagnostic Observation Schedule (ADOS), were evaluated at baseline (T0) and after one year (T1), while receiving treatment as usual. Changes in DQ and ADOS between baseline and follow-up and differences in the short-term evolution of the four subgroups were analyzed. At T1, 55.4 % of the children demonstrated some gains either of autistic symptomatology or of developmental skills. Mean ADOS score was 13.63 ± 3.67 at T0 and 10.85 ± 4.10 at T1 and mean DQ was 0.64 ± 0.14 at T0 and 0.66 ± 0.15 at T1. At follow-up, 33.7 % of the children showed an improvement in DQ and 37 % presented a less severe symptomatology, measured by means of ADOS. Overall, 15.2 % of the sample displayed major improvements both on developmental quotient and ADOS severity score; these children presented less EEG abnormalities and familial psychiatric disorders. The four subgroups, based on biological, clinical and familial variables, showed differing trends in terms of evolution. Categorizing very young children with ASD in terms of biological, clinical and familial variables can be instrumental in predicting short-term

  9. The NASA Short-term Prediction and Research Transition (SPoRT) Center: A Research to Operations Test Bed

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.

    2005-01-01

    Over the last three years, NASA/MSFC scientists have embarked on an effort to transition unique NASA EOS data/products and research technology to selected NWSEOs in the southeast U.S. This activity, called the Short-term Prediction and - Research Transition (SPoRT) program, supports the NASA Science Mission Directorate and its Earth-Sun System Mission to develop a scientific understanding of the Earth System and its response to natural or human-induced changes that will enable improved prediction capability for climate, weather, and natural hazards. The overarching question related to weather prediction is "How well can weather forecasting duration and reliability be improved by new space-based observations, data assimilation, and modeling?" The transition activity has included the real-time delivery of MODIS data and products to several NWS Forecast Offices. Local NWS FOs have used the MODIS data to complement the coarse resolution GOES data for a number of applications. Specialized products have also been developed and made available to local and remote offices for their weather applications. Data from &e Lightning Mapping Array (LMA) network has been used in severe storm forecasts at several offices in the region. At the regional scale and forecast horizons from 0-1 day, the next generation of high-resolution mesoscale forecast and data assimilation models have been used to provide local offices with unique weather forecasts not otherwise available. The continued use of near red-time infusion of NASA science products into high-resolution mesoscale forecast and decision-making models can be expected to improve the model initialization as well as short-term forecasts. A current focus of SPoRT is to expand collaborations to include contributions from the assimilation of AMSR-E data in the ADASIARPS forecast system (OU), inclusion of MODIS SSTs and AIRS thermodynamic profiles in the WRF, and to extend the distribution of real-time MODIS and AMSR-E data and products

  10. The NASA Short-term Prediction and Research Transition (SPoRT) Center: A Research to Operations Test Bed

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.

    2005-01-01

    Over the last three years, NASA/MSFC scientists have embarked on an effort to transition unique NASA EOS data/products and research technology to selected NWSEOs in the southeast U.S. This activity, called the Short-term Prediction and - Research Transition (SPoRT) program, supports the NASA Science Mission Directorate and its Earth-Sun System Mission to develop a scientific understanding of the Earth System and its response to natural or human-induced changes that will enable improved prediction capability for climate, weather, and natural hazards. The overarching question related to weather prediction is "How well can weather forecasting duration and reliability be improved by new space-based observations, data assimilation, and modeling?" The transition activity has included the real-time delivery of MODIS data and products to several NWS Forecast Offices. Local NWS FOs have used the MODIS data to complement the coarse resolution GOES data for a number of applications. Specialized products have also been developed and made available to local and remote offices for their weather applications. Data from &e Lightning Mapping Array (LMA) network has been used in severe storm forecasts at several offices in the region. At the regional scale and forecast horizons from 0-1 day, the next generation of high-resolution mesoscale forecast and data assimilation models have been used to provide local offices with unique weather forecasts not otherwise available. The continued use of near red-time infusion of NASA science products into high-resolution mesoscale forecast and decision-making models can be expected to improve the model initialization as well as short-term forecasts. A current focus of SPoRT is to expand collaborations to include contributions from the assimilation of AMSR-E data in the ADASIARPS forecast system (OU), inclusion of MODIS SSTs and AIRS thermodynamic profiles in the WRF, and to extend the distribution of real-time MODIS and AMSR-E data and products

  11. Implications for prediction and hazard assessment from the 2004 Parkfield earthquake.

    PubMed

    Bakun, W H; Aagaard, B; Dost, B; Ellsworth, W L; Hardebeck, J L; Harris, R A; Ji, C; Johnston, M J S; Langbein, J; Lienkaemper, J J; Michael, A J; Murray, J R; Nadeau, R M; Reasenberg, P A; Reichle, M S; Roeloffs, E A; Shakal, A; Simpson, R W; Waldhauser, F

    2005-10-13

    Obtaining high-quality measurements close to a large earthquake is not easy: one has to be in the right place at the right time with the right instruments. Such a convergence happened, for the first time, when the 28 September 2004 Parkfield, California, earthquake occurred on the San Andreas fault in the middle of a dense network of instruments designed to record it. The resulting data reveal aspects of the earthquake process never before seen. Here we show what these data, when combined with data from earlier Parkfield earthquakes, tell us about earthquake physics and earthquake prediction. The 2004 Parkfield earthquake, with its lack of obvious precursors, demonstrates that reliable short-term earthquake prediction still is not achievable. To reduce the societal impact of earthquakes now, we should focus on developing the next generation of models that can provide better predictions of the strength and location of damaging ground shaking.

  12. Ensemble forecasting of short-term system scale irrigation demands using real-time flow data and numerical weather predictions

    NASA Astrophysics Data System (ADS)

    Perera, Kushan C.; Western, Andrew W.; Robertson, David E.; George, Biju; Nawarathna, Bandara

    2016-06-01

    Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real-time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short-term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash-Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.

  13. Short-term prediction of UT1-UTC by combination of the grey model and neural networks

    NASA Astrophysics Data System (ADS)

    Lei, Yu; Guo, Min; Hu, Dan-dan; Cai, Hong-bing; Zhao, Dan-ning; Hu, Zhao-peng; Gao, Yu-ping

    2017-01-01

    UT1-UTC predictions especially short-term predictions are essential in various fields linked to reference systems such as space navigation and precise orbit determinations of artificial Earth satellites. In this paper, an integrated model combining the grey model GM(1, 1) and neural networks (NN) are proposed for predicting UT1-UTC. In this approach, the effects of the Solid Earth tides and ocean tides together with leap seconds are first removed from observed UT1-UTC data to derive UT1R-TAI. Next the derived UT1R-TAI time-series are de-trended using the GM(1, 1) and then residuals are obtained. Then the residuals are used to train a network. The subsequently predicted residuals are added to the GM(1, 1) to obtain the UT1R-TAI predictions. Finally, the predicted UT1R-TAI are corrected for the tides together with leap seconds to obtain UT1-UTC predictions. The daily values of UT1-UTC between January 7, 2010 and August 6, 2016 from the International Earth Rotation and Reference Systems Service (IERS) 08 C04 series are used for modeling and validation of the proposed model. The results of the predictions up to 30 days in the future are analyzed and compared with those by the GM(1, 1)-only model and combination of the least-squares (LS) extrapolation of the harmonic model including the linear part, annual and semi-annual oscillations and NN. It is found that the proposed model outperforms the other two solutions. In addition, the predictions are compared with those from the Earth Orientation Parameters Prediction Comparison Campaign (EOP PCC) lasting from October 1, 2005 to February 28, 2008. The results show that the prediction accuracy is inferior to that of those methods taking into account atmospheric angular momentum (AAM), i.e., Kalman filter and adaptive transform from AAM to LODR, but noticeably better that of the other existing methods and techniques, e.g., autoregressive filtering and least-squares collocation.

  14. Predictive validity of the Short-Term Assessment of Risk and Treatability for violent behavior in outpatient forensic psychiatric patients.

    PubMed

    Troquete, Nadine A C; van den Brink, Rob H S; Beintema, Harry; Mulder, Tamara; van Os, Titus W D P; Schoevers, Robert A; Wiersma, Durk

    2015-06-01

    It remains unclear whether prediction of violence based on historical factors can be improved by adding dynamic risks, protective strengths, selection of person-specific key strengths or critical vulnerabilities, and structured professional judgment (SPJ). We examine this in outpatient forensic psychiatry with the Short-Term Assessment of Risk and Treatability (START) at 3 and 6 months follow-up. An incident occurred during 33 (13%) out of 252 3-month and 44 (21%) out of 211 6-month follow-up periods (n = 188 unique clients). Pearson correlations for all predictor variables were in the expected directions. Prediction of recidivism based on historical factor ratings (odds ratio [OR] = 1.10) could not be improved through the addition of dynamic risk, protective strength, or key or critical factor scores (all ORs ns). The addition of the SPJ improved the model to modest accuracy (area under the curve [AUC] = .64) but made no independent significant contribution (OR = 1.55, p = .21) for the 3-month follow-up. For the 6-month follow-up, SPJ scores also increased predictive accuracy to modest (AUC = .67) and made a significant independent contribution to the prediction of the outcome (OR = 1.98, p = .04). Multicollinearity limits were unviolated. Limitations apply, however, results are similar to those from clinical, researcher rated samples and are discussed in the light of setting specific characteristics. Although it is too early to advocate implementing risk assessment instruments in clinical practice, we can conclude that clinicians in a heterogeneous outpatient forensic psychiatric setting can achieve similar results with the START as clinicians and research staff in more homogeneous inpatient settings.

  15. Sociological aspects of earthquake prediction

    USGS Publications Warehouse

    Spall, H.

    1979-01-01

    Henry Spall talked recently with Denis Mileti who is in the Department of Sociology, Colorado State University, Fort Collins, Colo. Dr. Mileti is a sociologst involved with research programs that study the socioeconomic impact of earthquake prediction

  16. The profound reach of the M8.6 11 April 2012 Indian Ocean earthquake: short-term global triggering followed by a longer-term global shadow

    NASA Astrophysics Data System (ADS)

    Pollitz, F. F.; Burgmann, R.; Stein, R. S.; Sevilgen, V.

    2013-12-01

    The M8.6 11 April 2012 Indian Ocean earthquake was an unusually large intra-oceanic strike-slip event. For several days the global M ≥ 4.5 and M ≥ 6.5 seismicity rate at remote distances (i.e. thousands of km from the mainshock) was elevated. The strike-slip mainshock appears through its Love waves to have triggered a global burst of strike-slip aftershocks over several days. But the M ≥ 6.5 rate subsequently dropped to zero for the succeeding 95 days, although the M ≤ 6.0 global rate was close to background during this period. Such an extended period without a M ≥ 6.5 event has happened rarely over the past century, and never after a large mainshock. Quiescent periods following previous large (M ≥ 8) mainshocks over the past century are either much shorter or begin so long after a given mainshock that no physical interpretation is warranted. The 2012 mainshock is unique in terms of both the short-lived global increase and subsequent long quiescent period. We believe that the two components are linked and interpret this pattern as the product of dynamic stressing of a global system of faults. Transient dynamic stresses can encourage short-term triggering but paradoxically, can also inhibit rupture temporarily until background tectonic loading restores the system to its pre-mainshock stress levels.

  17. Intraoperative improvement in left ventricular peak systolic velocity predicts better short-term outcome after transcatheter aortic valve implantation.

    PubMed

    Eidet, Jo; Dahle, Gry; Bugge, Jan Frederik; Bendz, Bjørn; Rein, Kjell Arne; Aaberge, Lars; Offstad, Jon Thomas; Fosse, Erik; Aakhus, Svend; Halvorsen, Per Steinar

    2016-01-01

    Left ventricular function is expected to improve after transcatheter aortic valve implantation due to the acute reduction in afterload, but does not occur in all patients. We hypothesized that the immediate intraoperative response in systolic left ventricular longitudinal motion during the procedure could be a predictor of short-term outcome. Sixty-four patients treated with transcatheter aortic valve implantation for severe aortic stenosis were included. Transoesophageal 4- and 2-chamber echocardiograms were obtained immediately prior to and ∼15 min after valve implantation. Patients were defined as responders if their average left ventricular longitudinal peak systolic velocity increased by ≥20% from the preimplantation value and was related to the 3-month outcome. Thirty-five patients were classified as responders, with an increase in the intraoperative longitudinal peak systolic velocity from an average of 2.2 ± 0.8 to 3.1 ± 1.1 cm/s (P < 0.001); the velocity was unchanged in the remaining 29 patients, who averaged 2.4 ± 1.1 cm/s. There were significantly fewer adverse cardiac events in the responder group at the 3-month follow-up (20 vs 45%, P = 0.03) and the New York Heart Association class was significantly better in the responders compared with non-responders. Responders had a significant reduction in N-terminal probrain natriuretic peptide levels [243 (113-361) vs 163 (64-273), P = 0.004] at the 3-month follow-up, whereas non-responders did not [469 (130-858) vs 289 (157-921), P = 0.48]. An immediate improvement in the longitudinal peak systolic velocity during the transcatheter aortic valve implantation procedure predicted a better short-term outcome and may be useful in identifying patients who are at risk of a less favourable outcome after transcatheter aortic valve implantation. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  18. Performance assessment of deterministic and probabilistic weather predictions for the short-term optimization of a tropical hydropower reservoir

    NASA Astrophysics Data System (ADS)

    Mainardi Fan, Fernando; Schwanenberg, Dirk; Alvarado, Rodolfo; Assis dos Reis, Alberto; Naumann, Steffi; Collischonn, Walter

    2016-04-01

    Hydropower is the most important electricity source in Brazil. During recent years, it accounted for 60% to 70% of the total electric power supply. Marginal costs of hydropower are lower than for thermal power plants, therefore, there is a strong economic motivation to maximize its share. On the other hand, hydropower depends on the availability of water, which has a natural variability. Its extremes lead to the risks of power production deficits during droughts and safety issues in the reservoir and downstream river reaches during flood events. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for the short-term reservoir management, the use of probabilistic ensemble forecasts and stochastic optimization techniques receives growing attention and a number of researches have shown its benefit. The present work shows one of the first hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project (HPP) Três Marias, located in southeast Brazil. The HPP reservoir is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control at Pirapora City located 120 km downstream of the dam. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts with 50 ensemble members of the ECMWF are used as forcing of the MGB-IPH hydrological model to generate streamflow forecasts over a period of 2 years. The online optimization depends on a deterministic and multi-stage stochastic version of a model predictive control scheme. Results for the perfect forecasts show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of

  19. Predicting short-term mortality in patients with acute exacerbation of chronic heart failure: The EAHFE-3D scale.

    PubMed

    Jacob, J; Miró, Ò; Herrero, P; Martín-Sánchez, F J; Gil, V; Tost, J; Aguirre, A; Escoda, R; Alquézar, A; Andueza, J A; Llorens, P

    2016-01-01

    Prognostic scales are needed in acute exacerbation of chronic heart failure to detect early mortality. The objective of this study is to create a prognostic scale (scale EAHFE-3D) to stratify the risk of death the very short term. We used the EAHFE database, a multipurpose, multicenter registry with prospective follow-up currently including 6,597 patients with acute heart failure attended at 34 Spanish Emergency Departments from 2007 to 2014. The following variables were collected: demographic, personal history, data of acute episode and 3-day mortality. The derivation cohort included patients recruited during 2009 and 2011 EAHFE registry spots (n=3,640). The classifying variable was all-cause 3-day mortality. A prognostic scale (3D-EAHFE scale) with the results of the multivariate analysis based on the weight of the OR was created. The 3D-EAHFE scale was validated using the cohort of patients included in 2014 spot (n=2,957). A total of 3,640 patients were used in the derivation cohort and 102 (2.8%) died at 3 days. The final scale contained the following variables (maximum 165 points): age≥75 years (30 points), baseline NYHA III-IV (15 points), systolic blood pressure<110mmHg (20 points), room-air oxygen saturation<90% (30 points), hyponatremia (20 points), inotropic or vasopressor treatment (30 points) and need for noninvasive mechanical ventilation (20 points); with a ROC curve of 0.80 (95% CI 0.76-0.84; P<.001). The validation cohort included 2,957 patients (66 died at 3 days, 2.2%), and the scale obtained a ROC curve of 0.76 (95% CI 0.70-0.82; P<.001). The risk groups consisted of very low risk (0-20 points), low risk (21-40 points), intermediate risk (41-60 points), high risk (61-80 points) and very high risk (>80 points), with a mortality (derivation/validation cohorts) of 0/0.5, 0.8/1.0, 2.9/2.8, 5.5/5.8 and 12.7/22.4%, respectively. EAHFE-3D scale may help to predict the very short term prognosis of patients with acute heart failure in 5 risk groups

  20. Experience of affects predicting sense of self and others in short-term dynamic and cognitive therapy.

    PubMed

    Berggraf, Lene; Ulvenes, Pål G; Oktedalen, Tuva; Hoffart, Asle; Stiles, Tore; McCullough, Leigh; Wampold, Bruce E

    2014-06-01

    The present study examined whether levels of activating affects (AA) and inhibitory affects (IA) were related to change toward more compassionate and realistic levels of sense of self (SoS) and sense of others (SoO). The sample included 47 patients diagnosed with cluster C personality disorders, who received 40 sessions of either cognitive therapy or short-term dynamic therapy (see the randomized controlled trial study, Svartberg, Stiles, & Seltzer, 2004). A total of 927 videotaped sessions were rated with the use of the observational instrument, Achievement of Therapeutic Objectives Scale. Longitudinal multilevel modeling enabled the examination of both between-person effects and within-person changes in level of AA and IA. Patients with better ability to experience AA at the start of therapy displayed significantly higher SoS and SoO across sessions compared with other patients. Patients who experienced higher levels of IA at the start of therapy displayed lower levels of SoS across sessions. A patient experiencing more AA than usual for him/her self within a session predicted an increased level of SoS and SoO at the next measuring point. There were no different change patterns in the 2 treatment groups. Results suggest that focus within therapy sessions on increasing patients' AA can help facilitate change in SoS and SoO toward more compassionate and realistic quality. (c) 2014 APA, all rights reserved.

  1. Interleukin-6 predicts short-term global functional decline in the oldest old: results from the BELFRAIL study.

    PubMed

    Adriaensen, Wim; Matheï, Catharina; Vaes, Bert; van Pottelbergh, Gijs; Wallemacq, Pierre; Degryse, Jean-Marie

    2014-01-01

    The chronic inflammatory state at old age may contribute to the pathophysiology of or reflect chronic conditions resulting in loss of physical and mental functioning. Therefore, our objective was to examine the predictive value of a large battery of serum inflammatory markers as risk indicators for global functional decline and its specific physical and mental determinants in the oldest old. Global functional decline and specific aspects of physical and mental functional decline were assessed during an average of 1.66 years (±0.21) in a sample of 303 persons aged 80 years or older of the BELFRAIL study. Serum levels of 14 inflammatory proteins, including cytokines, growth factors, and acute phase proteins, were measured at baseline. Almost 20 % of the participants had a significant global functional decline over time. Interleukin (IL)-6 serum levels were uniquely positively associated with global functional decline, even after correcting for multiple confounders (odds ratio 1.51). Odds ratios for the individual aspects (physical dependency, physical performance, cognition, and depression) of functioning were lower, and composite scores of physical or mental decline were not significant. The proportion of global functional decline exhibited a dose-response curve with increasing levels of IL-6. Thus, IL-6 is an independent risk indicator for accelerated global functional decline in the oldest old. Our results suggest that simple serum levels of IL-6 may be very useful in short-term identification or evaluation of global functional status in the oldest old.

  2. Prediction of short-term changes in symptom severity by baseline plasma homovanillic acid levels in schizophrenic patients receiving clozapine.

    PubMed

    Sumiyoshi, T; Hasegawa, M; Jayathilake, K; Meltzer, H Y

    1997-03-24

    The relationship between pretreatment levels of plasma homovanillic acid (pHVA) and the outcome of clozapine treatment was studied in 18 male patients with schizophrenia who were resistant to treatment with conventional neuroleptics. After 6 months of clozapine treatment, 7 patients demonstrated > or = 20% decrease in the Brief Psychiatric Rating Scale (BPRS) (responders), while 11 patients did not (non-responders). Responders and non-responders did not differ with respect to the baseline pHVA level. The BPRS Positive Symptom scores at 6 weeks and 3 months, but not those at baseline and 6 months, following initiation of clozapine treatment negatively correlated with pHVA levels for all patients. The correlations became stronger when only responders were included. No significant correlation between Positive Symptom scores and pHVA levels was observed for non-responders. The BPRS Total and Negative Symptom scores did not correlate with pHVA for all patients, responders or non-responders at any time. The percent decrease in the BPRS Positive Symptom scores from baseline at 6 weeks following clozapine treatment correlated significantly with pHVA levels in responders. These results suggest that pretreatment levels of pHVA can be used to predict relatively short-term changes in the positive symptoms of patients with schizophrenia receiving clozapine treatment, particularly for clozapine responders.

  3. Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models: 1. Repeating earthquakes

    NASA Astrophysics Data System (ADS)

    Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate H.; Uchida, Naoki

    2012-02-01

    The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

  4. Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

    USGS Publications Warehouse

    Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

    2012-01-01

    The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

  5. Intermediate-term earthquake prediction

    USGS Publications Warehouse

    Knopoff, L.

    1990-01-01

    The problems in predicting earthquakes have been attacked by phenomenological methods from pre-historic times to the present. The associations of presumed precursors with large earthquakes often have been remarked upon. the difficulty in identifying whether such correlations are due to some chance coincidence or are real precursors is that usually one notes the associations only in the relatively short time intervals before the large events. Only rarely, if ever, is notice taken of whether the presumed precursor is to be found in the rather long intervals that follow large earthquakes, or in fact is absent in these post-earthquake intervals. If there are enough examples, the presumed correlation fails as a precursor in the former case, while in the latter case the precursor would be verified. Unfortunately, the observer is usually not concerned with the 'uniteresting' intervals that have no large earthquakes

  6. JPSS Proving Ground Activities with NASA's Short-term Prediction Research and Transition (SPoRT) Center

    NASA Astrophysics Data System (ADS)

    Schultz, L. A.; Smith, M. R.; Fuell, K.; Stano, G. T.; LeRoy, A.; Berndt, E.

    2015-12-01

    Instruments aboard the Joint Polar Satellite System (JPSS) series of satellites will provide imagery and other data sets relevant to operational weather forecasts. To prepare current and future weather forecasters in application of these data sets, Proving Ground activities have been established that demonstrate future JPSS capabilities through use of similar sensors aboard NASA's Terra and Aqua satellites, and the S-NPP mission. As part of these efforts, NASA's Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama partners with near real-time providers of S-NPP products (e.g., NASA, UW/CIMSS, UAF/GINA, etc.) to demonstrate future capabilities of JPSS. This includes training materials and product distribution of multi-spectral false color composites of the visible, near-infrared, and infrared bands of MODIS and VIIRS. These are designed to highlight phenomena of interest to help forecasters digest the multispectral data provided by the VIIRS sensor. In addition, forecasters have been trained on the use of the VIIRS day-night band, which provides imagery of moonlit clouds, surface, and lights emitted by human activities. Hyperspectral information from the S-NPP/CrIS instrument provides thermodynamic profiles that aid in the detection of extremely cold air aloft, helping to map specific aviation hazards at high latitudes. Hyperspectral data also support the estimation of ozone concentration, which can highlight the presence of much drier stratospheric air, and map its interaction with mid-latitude or tropical cyclones to improve predictions of their strengthening or decay. Proving Ground activities are reviewed, including training materials and methods that have been provided to forecasters, and forecaster feedback on these products that has been acquired through formal, detailed assessment of their applicability to a given forecast threat or task. Future opportunities for collaborations around the delivery of training are proposed

  7. A Comparison Of Primitive Model Results Of The Short Term Wind Energy Prediction System (Sweps): WRF vs MM5

    NASA Astrophysics Data System (ADS)

    Unal, E.; Tan, E.; Mentes, S. S.; Caglar, F.; Turkmen, M.; Unal, Y. S.; Onol, B.; Ozdemir, E. T.

    2012-04-01

    Although discontinuous behavior of wind field makes energy production more difficult, wind energy is the fastest growing renewable energy sector in Turkey which is the 6th largest electricity market in Europe. Short-term prediction systems, which capture the dynamical and statistical nature of the wind field in spatial and time scales, need to be advanced in order to increase the wind power prediction accuracy by using appropriate numerical weather forecast models. Therefore, in this study, performances of the next generation mesoscale Numerical Weather Forecasting model, WRF, and The Fifth-Generation NCAR/Penn State Mesoscale Model, MM5, have been compared for the Western Part of Turkey. MM5 has been widely used by Turkish State Meteorological Service from which MM5 results were also obtained. Two wind farms of the West Turkey have been analyzed for the model comparisons by using two different model domain structures. Each model domain has been constructed by 3 nested domains downscaling from 9km to 1km resolution by the ratio of 3. Since WRF and MM5 models have no exactly common boundary layer, cumulus, and microphysics schemes, the similar physics schemes have been chosen for these two models in order to have reasonable comparisons. The preliminary results show us that, depending on the location of the wind farms, MM5 wind speed RMSE values are 1 to 2 m/s greater than that of WRF values. Since 1 to 2 m/s errors can be amplified when wind speed is converted to wind power; it is decided that the WRF model results are going to be used for the rest of the project.

  8. Prediction of earthquake-triggered landslide event sizes

    NASA Astrophysics Data System (ADS)

    Braun, Anika; Havenith, Hans-Balder; Schlögel, Romy

    2016-04-01

    Seismically induced landslides are a major environmental effect of earthquakes, which may significantly contribute to related losses. Moreover, in paleoseismology landslide event sizes are an important proxy for the estimation of the intensity and magnitude of past earthquakes and thus allowing us to improve seismic hazard assessment over longer terms. Not only earthquake intensity, but also factors such as the fault characteristics, topography, climatic conditions and the geological environment have a major impact on the intensity and spatial distribution of earthquake induced landslides. We present here a review of factors contributing to earthquake triggered slope failures based on an "event-by-event" classification approach. The objective of this analysis is to enable the short-term prediction of earthquake triggered landslide event sizes in terms of numbers and size of the affected area right after an earthquake event occurred. Five main factors, 'Intensity', 'Fault', 'Topographic energy', 'Climatic conditions' and 'Surface geology' were used to establish a relationship to the number and spatial extend of landslides triggered by an earthquake. The relative weight of these factors was extracted from published data for numerous past earthquakes; topographic inputs were checked in Google Earth and through geographic information systems. Based on well-documented recent earthquakes (e.g. Haiti 2010, Wenchuan 2008) and on older events for which reliable extensive information was available (e.g. Northridge 1994, Loma Prieta 1989, Guatemala 1976, Peru 1970) the combination and relative weight of the factors was calibrated. The calibrated factor combination was then applied to more than 20 earthquake events for which landslide distribution characteristics could be cross-checked. One of our main findings is that the 'Fault' factor, which is based on characteristics of the fault, the surface rupture and its location with respect to mountain areas, has the most important

  9. Geochemical challenge to earthquake prediction.

    PubMed

    Wakita, H

    1996-04-30

    The current status of geochemical and groundwater observations for earthquake prediction in Japan is described. The development of the observations is discussed in relation to the progress of the earthquake prediction program in Japan. Three major findings obtained from our recent studies are outlined. (i) Long-term radon observation data over 18 years at the SKE (Suikoen) well indicate that the anomalous radon change before the 1978 Izu-Oshima-kinkai earthquake can with high probability be attributed to precursory changes. (ii) It is proposed that certain sensitive wells exist which have the potential to detect precursory changes. (iii) The appearance and nonappearance of coseismic radon drops at the KSM (Kashima) well reflect changes in the regional stress state of an observation area. In addition, some preliminary results of chemical changes of groundwater prior to the 1995 Kobe (Hyogo-ken nanbu) earthquake are presented.

  10. Geochemical challenge to earthquake prediction.

    PubMed Central

    Wakita, H

    1996-01-01

    The current status of geochemical and groundwater observations for earthquake prediction in Japan is described. The development of the observations is discussed in relation to the progress of the earthquake prediction program in Japan. Three major findings obtained from our recent studies are outlined. (i) Long-term radon observation data over 18 years at the SKE (Suikoen) well indicate that the anomalous radon change before the 1978 Izu-Oshima-kinkai earthquake can with high probability be attributed to precursory changes. (ii) It is proposed that certain sensitive wells exist which have the potential to detect precursory changes. (iii) The appearance and nonappearance of coseismic radon drops at the KSM (Kashima) well reflect changes in the regional stress state of an observation area. In addition, some preliminary results of chemical changes of groundwater prior to the 1995 Kobe (Hyogo-ken nanbu) earthquake are presented. PMID:11607665

  11. A short-term predictive system for surface currents from a rapidly deployed coastal HF radar network

    NASA Astrophysics Data System (ADS)

    Barrick, Donald; Fernandez, Vicente; Ferrer, Maria I.; Whelan, Chad; Breivik, Øyvind

    2012-05-01

    In order to address the need for surface trajectory forecasts following deployment of coastal HF radar systems during emergency-response situations (e.g., search and rescue, oil spill), a short-term predictive system (STPS) based on only a few hours data background is presented. First, open-modal analysis (OMA) coefficients are fitted to 1-D surface currents from all available radar stations at each time interval. OMA has the effect of applying a spatial low-pass filter to the data, fills gaps, and can extend coverage to areas where radial vectors are available from a single radar only. Then, a set of temporal modes is fitted to the time series of OMA coefficients, typically over a short 12-h trailing period. These modes include tidal and inertial harmonics, as well as constant and linear trends. This temporal model is the STPS basis for producing up to a 12-h current vector forecast from which a trajectory forecast can be derived. We show results of this method applied to data gathered during the September 2010 rapid-response demonstration in northern Norway. Forecasted coefficients, currents, and trajectories are compared with the same measured quantities, and statistics of skill are assessed employing 16 24-h data sets. Forecasted and measured kinetic variances of the OMA coefficients typically agreed to within 10-15%. In one case where errors were larger, strong wind changes are suspected and examined as the cause. Sudden wind variability is not included properly within the STPS attack we presently employ and will be a subject for future improvement.

  12. Earthquake prediction in Japan and natural time analysis of seismicity

    NASA Astrophysics Data System (ADS)

    Uyeda, S.; Varotsos, P.

    2011-12-01

    M9 super-giant earthquake with huge tsunami devastated East Japan on 11 March, causing more than 20,000 casualties and serious damage of Fukushima nuclear plant. This earthquake was predicted neither short-term nor long-term. Seismologists were shocked because it was not even considered possible to happen at the East Japan subduction zone. However, it was not the only un-predicted earthquake. In fact, throughout several decades of the National Earthquake Prediction Project, not even a single earthquake was predicted. In reality, practically no effective research has been conducted for the most important short-term prediction. This happened because the Japanese National Project was devoted for construction of elaborate seismic networks, which was not the best way for short-term prediction. After the Kobe disaster, in order to parry the mounting criticism on their no success history, they defiantly changed their policy to "stop aiming at short-term prediction because it is impossible and concentrate resources on fundamental research", that meant to obtain "more funding for no prediction research". The public were and are not informed about this change. Obviously earthquake prediction would be possible only when reliable precursory phenomena are caught and we have insisted this would be done most likely through non-seismic means such as geochemical/hydrological and electromagnetic monitoring. Admittedly, the lack of convincing precursors for the M9 super-giant earthquake has adverse effect for us, although its epicenter was far out off shore of the range of operating monitoring systems. In this presentation, we show a new possibility of finding remarkable precursory signals, ironically, from ordinary seismological catalogs. In the frame of the new time domain termed natural time, an order parameter of seismicity, κ1, has been introduced. This is the variance of natural time kai weighted by normalised energy release at χ. In the case that Seismic Electric Signals

  13. Development of Short-term Molecular Thresholds to Predict Long-term Mouse Liver Tumor Outcomes: Phthalate Case Study

    EPA Science Inventory

    Short-term molecular profiles are a central component of strategies to model health effects of environmental chemicals. In this study, a 7 day mouse assay was used to evaluate transcriptomic and proliferative responses in the liver for a hepatocarcinogenic phthalate, di (2-ethylh...

  14. Development of Short-term Molecular Thresholds to Predict Long-term Mouse Liver Tumor Outcomes: Phthalate Case Study

    EPA Science Inventory

    Short-term molecular profiles are a central component of strategies to model health effects of environmental chemicals. In this study, a 7 day mouse assay was used to evaluate transcriptomic and proliferative responses in the liver for a hepatocarcinogenic phthalate, di (2-ethylh...

  15. Use of short-term test systems for the prediction of the hazard represented by potential chemical carcinogens

    SciTech Connect

    Glass, L.R.; Jones, T.D.; Easterly, C.E.; Walsh, P.J.

    1990-10-01

    It has been hypothesized that results from short-term bioassays will ultimately provide information that will be useful for human health hazard assessment. Historically, the validity of the short-term tests has been assessed using the framework of the epidemiologic/medical screens. In this context, the results of the carcinogen (long-term) bioassay is generally used as the standard. However, this approach is widely recognized as being biased and, because it employs qualitative data, cannot be used to assist in isolating those compounds which may represent a more significant toxicologic hazard than others. In contrast, the goal of this research is to address the problem of evaluating the utility of the short-term tests for hazard assessment using an alternative method of investigation. Chemicals were selected mostly from the list of carcinogens published by the International Agency for Research on Carcinogens (IARC); a few other chemicals commonly recognized as hazardous were included. Tumorigenicity and mutagenicity data on 52 chemicals were obtained from the Registry of Toxic Effects of Chemical Substances (RTECS) and were analyzed using a relative potency approach. The data were evaluated in a format which allowed for a comparison of the ranking of the mutagenic relative potencies of the compounds (as estimated using short-term data) vs. the ranking of the tumorigenic relative potencies (as estimated from the chronic bioassays). Although this was a preliminary investigation, it offers evidence that the short-term tests systems may be of utility in ranking the hazards represented by chemicals which may contribute to increased carcinogenesis in humans as a result of occupational or environmental exposures. 177 refs., 8 tabs.

  16. Multi-level prediction of short-term outcome of depression: non-verbal interpersonal processes, cognitions and personality traits.

    PubMed

    Geerts, E; Bouhuys, N

    1998-06-02

    It was hypothesized that personality factors determine the short-term outcome of depression, and that they may do this via non-verbal interpersonal interactions and via cognitive interpretations of non-verbal behaviour. Twenty-six hospitalized depressed patients entered the study. Personality factors in the study were Neuroticism (N) and Extraversion (E). Non-verbal interpersonal interactions were studied by measuring patients' 'support seeking behaviour' and interviewers' 'support giving behaviour' from videotaped clinical interviews. The attunement between patients' and interviewers' behaviour (reflecting interpersonal satisfaction) was calculated over the time course of the interviews. Cognitions were assessed by measuring the perception of emotions from schematic faces. A stepwise multiple regression analysis showed that the higher the levels of E were, the less negative emotions were perceived from ambiguous faces (A-neg), and the more the patients and the interviewers got non-verbally attuned during the baseline interviews, the more favourable the short-term outcome of depression (as assessed over 6 weeks) turned out to be (adj.R2 = 0.48, P = 0.001). High levels of A-neg explained the relationship between high levels of N and an unfavourable short-term outcome of the depression (Pearson's r between N and short-term outcome of depression, P = 0.041, partial correlation after correction for A-neg, P = 0.157). The results show that personality, non-verbal interpersonal behavioural processes and cognitive factors are partially independent and partially linked in their relationship with the short-term outcome of depression. Research on non-verbal behavioural processes extends the empirical basis for the integration of personality, cognitions and interpersonal factors in depression theory.

  17. The very short-term rainfall forecasting for a mountainous watershed by means of an ensemble numerical weather prediction system in Taiwan

    NASA Astrophysics Data System (ADS)

    Wu, Ming-Chang; Lin, Gwo-Fong

    2017-03-01

    During typhoons, accurate forecasts of rainfall are always desired for various kinds of disaster warning systems to reduce the impact of rainfall-induced disasters. However, rainfall forecasting, especially the very short-term (hourly) rainfall, is one of the most difficult tasks in hydrology due to the high variability in space and time and the complex physical process. In this study, the purpose is to provide effective forecasts of very short-term rainfall by means of the ensemble numerical weather prediction system in Taiwan. To this end, the ensemble forecasts of hourly rainfall from this ensemble numerical weather prediction system are analyzed to evaluate the performance. Furthermore, a methodology, which is based on the principle of analogue prediction, is proposed to effectively process these ensemble forecasts for improving the performance on very short-term rainfall forecasting. To clearly demonstrate the advantage of the proposed methodology, actual application is conducted on a mountainous watershed to yield 1- to 6-h ahead forecasts during typhoon events. The results indicate that the proposed methodology is better performed and more flexible than the conventional one. Generally, the proposed methodology provides improved performance for very short-term rainfall forecasting, especially for 1- to 2-h ahead forecasting. The improved forecasts provided by the proposed methodology are expected to be useful to support disaster warning systems, such as flash-flood, landslide, and debris flow warning systems, during typhoons.

  18. Implementation of the Short-Term Ensemble Prediction System (STEPS) in Belgium and verification of case studies

    NASA Astrophysics Data System (ADS)

    Foresti, Loris; Reyniers, Maarten; Delobbe, Laurent

    2014-05-01

    The Short-Term Ensemble Prediction System (STEPS) is a probabilistic precipitation nowcasting scheme developed at the Australian Bureau of Meteorology in collaboration with the UK Met Office. In order to account for the multiscaling nature of rainfall structures, the radar field is decomposed into an 8 levels multiplicative cascade using a Fast Fourier Transform. The cascade is advected using the velocity field estimated with optical flow and evolves stochastically according to a hierarchy of auto-regressive processes. This allows reproducing the empirical observation that the rate of temporal evolution of the small scales is faster than the large scales. The uncertainty in radar rainfall measurement and the unknown future development of the velocity field are also considered by stochastic modelling in order to reflect their typical spatial and temporal variability. Recently, a 4 years national research program has been initiated by the University of Leuven, the Royal Meteorological Institute (RMI) of Belgium and 3 other partners: PLURISK ("forecasting and management of extreme rainfall induced risks in the urban environment"). The project deals with the nowcasting of rainfall and subsequent urban inundations, as well as socio-economic risk quantification, communication, warning and prevention. At the urban scale it is widely recognized that the uncertainty of hydrological and hydraulic models is largely driven by the input rainfall estimation and forecast uncertainty. In support to the PLURISK project the RMI aims at integrating STEPS in the current operational deterministic precipitation nowcasting system INCA-BE (Integrated Nowcasting through Comprehensive Analysis). This contribution will illustrate examples of STEPS ensemble and probabilistic nowcasts for a few selected case studies of stratiform and convective rain in Belgium. The paper focuses on the development of STEPS products for potential hydrological users and a preliminary verification of the nowcasts

  19. Hypothesis testing and earthquake prediction.

    PubMed Central

    Jackson, D D

    1996-01-01

    Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions. PMID:11607663

  20. Hypothesis testing and earthquake prediction.

    PubMed

    Jackson, D D

    1996-04-30

    Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions.

  1. An initial investigation on developing a new method to predict short-term breast cancer risk based on deep learning technology

    NASA Astrophysics Data System (ADS)

    Qiu, Yuchen; Wang, Yunzhi; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Liu, Hong; Zheng, Bin

    2016-03-01

    In order to establish a new personalized breast cancer screening paradigm, it is critically important to accurately predict the short-term risk of a woman having image-detectable cancer after a negative mammographic screening. In this study, we developed and tested a novel short-term risk assessment model based on deep learning method. During the experiment, a number of 270 "prior" negative screening cases was assembled. In the next sequential ("current") screening mammography, 135 cases were positive and 135 cases remained negative. These cases were randomly divided into a training set with 200 cases and a testing set with 70 cases. A deep learning based computer-aided diagnosis (CAD) scheme was then developed for the risk assessment, which consists of two modules: adaptive feature identification module and risk prediction module. The adaptive feature identification module is composed of three pairs of convolution-max-pooling layers, which contains 20, 10, and 5 feature maps respectively. The risk prediction module is implemented by a multiple layer perception (MLP) classifier, which produces a risk score to predict the likelihood of the woman developing short-term mammography-detectable cancer. The result shows that the new CAD-based risk model yielded a positive predictive value of 69.2% and a negative predictive value of 74.2%, with a total prediction accuracy of 71.4%. This study demonstrated that applying a new deep learning technology may have significant potential to develop a new short-term risk predicting scheme with improved performance in detecting early abnormal symptom from the negative mammograms.

  2. Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data.

    PubMed

    Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; Flather, Curtis H; VanDerWal, Jeremy; Akçakaya, H Resit; Thogmartin, Wayne E; Albright, Thomas P; Vavrus, Stephen J; Heglund, Patricia J

    2016-12-01

    Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate

  3. The politics of earthquake prediction

    SciTech Connect

    Olson, R.S.

    1989-01-01

    This book gives an account of the politics, scientific and public, generated from the Brady-Spence prediction of a massive earthquake to take place within several years in central Peru. Though the disaster did not happen, this examination of the events serves to highlight American scientific processes and the results of scientific interaction with the media and political bureaucracy.

  4. INTEGRATION OF SHORT-TERM CO-SEISMIC DEFORMATION (InSAR) IN THE GEOMORPHIC DEVELOPMENT OF AN ACTIVELY UPLIFTING FOOTWALL, L’AQUILA EARTHQUAKE (06 APRIL, 2009), ITALY

    NASA Astrophysics Data System (ADS)

    Berti, C.; Pazzaglia, F. J.; Ramage, J. M.; Miccadei, E.; Piacentini, T.

    2009-12-01

    Central Italy is a well know region of frequent seismic activity focused along the topographic axis of the Apennines, with several, damaging > M. 5 events in the past decade. Conversely, the integrated effect of these earthquakes in shaping the long term development of the landscape is a poorly understood, but potentially powerful process in describing the region’s paleoseismicity and steadiness of hazardous earthquakes. The recent M. 6.3 L’Aquila earthquake of 06 April, 2009 ruptured a fault in a region of well-known geologic, geomorphic, and geodetic constraining data including hanging wall continental basin Quaternary deposits, footwall stream networks with distinct knickpoints, a dense GPS network, and InSAR interferometry. Collectively, the geodetic data describe the short-term, co- and immediately post-seismic behavior of the earthquake, whereas the geologic and geomorphic data record how discrete rupture events are encoded in the landscape and reflected in processes actively shaping the topography. Envisat and ALOS derived interferograms generated using ROI PAC show close spatial overlap of the InSAR-determined rupture and the Paganica fault, separating a deeply incised, uplifted carbonate footwall block and an actively subsiding Quaternary continental basin. Deposition in the continental basin has been unsteady and is commonly attributed to climate-modulated sediment flux from the uplifted footwall. We note however, that the longitudinal profiles of streams in the footwall are marked by distinct knickpoints that do not correspond to known or obvious lithologic or structural controls. Rather, the knickpoints are located a linear distance from the Paganica fault and at a topographic elevation consistent with detachment-limited stream-power erosional retreat processes instigated by instantaneous base level fall at the mountain front. Furthermore, the magnitude of river incision and elevation of the knickpoints scales with the co-seismic deformation pattern

  5. Using the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to Predict the Occurrence of Short-Term Coronary Heart Disease Events in Women.

    PubMed

    McSweeney, Jean C; Cleves, Mario A; Fischer, Ellen P; Pettey, Christina M; Beasley, Brittany

    2017-08-19

    Few instruments capture symptoms that predict cardiac events in the short-term. This study examines the ability of the McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey to predict acute cardiac events within 3 months of administration and to identify the prodromal symptoms most associated with short-term risk in women without known coronary heart disease. The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey was administered to 1,097 women referred to a cardiologist for initial coronary heart disease evaluation. Logistic regression models were used to examine prodromal symptoms individually and in combination to identify the subset of symptoms most predictive of an event within 3 months. Fifty-one women had an early cardiac event. In bivariate analyses, 4 of 30 prodromal symptoms were significantly associated with event occurrence within 90 days. In adjusted analyses, women reporting arm pain or discomfort and unusual fatigue were more likely (OR, 4.67; 95% CI, 2.08-10.48) to have a cardiac event than women reporting neither. The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey may assist in predicting short-term coronary heart disease events in women without known coronary heart disease. Copyright © 2017 Jacobs Institute of Women's Health. All rights reserved.

  6. Projected Applications of a "Weather in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.; Molthan, Andrew; Zavodsky, Bradley T.; Case, Jonathan L.; LaFontaine, Frank J.; Srikishen, Jayanthi

    2010-01-01

    The NASA Short-term Prediction Research and Transition Center (SPoRT)'s new "Weather in a Box" resources will provide weather research and forecast modeling capabilities for real-time application. Model output will provide additional forecast guidance and research into the impacts of new NASA satellite data sets and software capabilities. By combining several research tools and satellite products, SPoRT can generate model guidance that is strongly influenced by unique NASA contributions.

  7. Earthquake predictions using seismic velocity ratios

    USGS Publications Warehouse

    Sherburne, R. W.

    1979-01-01

    Since the beginning of modern seismology, seismologists have contemplated predicting earthquakes. The usefulness of earthquake predictions to the reduction of human and economic losses and the value of long-range earthquake prediction to planning is obvious. Not as clear are the long-range economic and social impacts of earthquake prediction to a speicifc area. The general consensus of opinion among scientists and government officials, however, is that the quest of earthquake prediction is a worthwhile goal and should be prusued with a sense of urgency. 

  8. Intermediate-term earthquake prediction.

    PubMed Central

    Keilis-Borok, V I

    1996-01-01

    An earthquake of magnitude M and linear source dimension L(M) is preceded within a few years by certain patterns of seismicity in the magnitude range down to about (M - 3) in an area of linear dimension about 5L-10L. Prediction algorithms based on such patterns may allow one to predict approximately 80% of strong earthquakes with alarms occupying altogether 20-30% of the time-space considered. An area of alarm can be narrowed down to 2L-3L when observations include lower magnitudes, down to about (M - 4). In spite of their limited accuracy, such predictions open a possibility to prevent considerable damage. The following findings may provide for further development of prediction methods: (i) long-range correlations in fault system dynamics and accordingly large size of the areas over which different observed fields could be averaged and analyzed jointly, (ii) specific symptoms of an approaching strong earthquake, (iii) the partial similarity of these symptoms worldwide, (iv) the fact that some of them are not Earth specific: we probably encountered in seismicity the symptoms of instability common for a wide class of nonlinear systems. Images Fig. 1 Fig. 2 Fig. 4 Fig. 5 PMID:11607660

  9. Intermediate-term earthquake prediction.

    PubMed

    Keilis-Borok, V I

    1996-04-30

    An earthquake of magnitude M and linear source dimension L(M) is preceded within a few years by certain patterns of seismicity in the magnitude range down to about (M - 3) in an area of linear dimension about 5L-10L. Prediction algorithms based on such patterns may allow one to predict approximately 80% of strong earthquakes with alarms occupying altogether 20-30% of the time-space considered. An area of alarm can be narrowed down to 2L-3L when observations include lower magnitudes, down to about (M - 4). In spite of their limited accuracy, such predictions open a possibility to prevent considerable damage. The following findings may provide for further development of prediction methods: (i) long-range correlations in fault system dynamics and accordingly large size of the areas over which different observed fields could be averaged and analyzed jointly, (ii) specific symptoms of an approaching strong earthquake, (iii) the partial similarity of these symptoms worldwide, (iv) the fact that some of them are not Earth specific: we probably encountered in seismicity the symptoms of instability common for a wide class of nonlinear systems.

  10. Dim prospects for earthquake prediction

    NASA Astrophysics Data System (ADS)

    Geller, Robert J.

    I was misquoted by C. Lomnitz's [1998] Forum letter (Eos, August 4, 1998, p. 373), which said: [I wonder whether Sasha Gusev [1998] actually believes that branding earthquake prediction a ‘proven nonscience’ [Geller, 1997a] is a paradigm for others to copy.”Readers are invited to verify for themselves that neither “proven nonscience” norv any similar phrase was used by Geller [1997a].

  11. Risk factors and prediction of very short term versus short/intermediate term post-stroke mortality: a data mining approach.

    PubMed

    Easton, Jonathan F; Stephens, Christopher R; Angelova, Maia

    2014-11-01

    Data mining and knowledge discovery as an approach to examining medical data can limit some of the inherent bias in the hypothesis assumptions that can be found in traditional clinical data analysis. In this paper we illustrate the benefits of a data mining inspired approach to statistically analysing a bespoke data set, the academic multicentre randomised control trial, U.K Glucose Insulin in Stroke Trial (GIST-UK), with a view to discovering new insights distinct from the original hypotheses of the trial. We consider post-stroke mortality prediction as a function of days since stroke onset, showing that the time scales that best characterise changes in mortality risk are most naturally defined by examination of the mortality curve. We show that certain risk factors differentiate between very short term and intermediate term mortality. In particular, we show that age is highly relevant for intermediate term risk but not for very short or short term mortality. We suggest that this is due to the concept of frailty. Other risk factors are highlighted across a range of variable types including socio-demographics, past medical histories and admission medication. Using the most statistically significant risk factors we build predictive classification models for very short term and short/intermediate term mortality. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  12. Comparison of Ultrafine Particle and Black Carbon Concentration Predictions from a Mobile and Short-Term Stationary Land-Use Regression Model.

    PubMed

    Kerckhoffs, Jules; Hoek, Gerard; Messier, Kyle P; Brunekreef, Bert; Meliefste, Kees; Klompmaker, Jochem O; Vermeulen, Roel

    2016-12-06

    Mobile and short-term monitoring campaigns are increasingly used to develop land-use regression (LUR) models for ultrafine particles (UFP) and black carbon (BC). It is not yet established whether LUR models based on mobile or short-term stationary measurements result in comparable models and concentration predictions. The goal of this paper is to compare LUR models based on stationary (30 min) and mobile UFP and BC measurements from a single campaign. An electric car collected both repeated stationary and mobile measurements in Amsterdam and Rotterdam, The Netherlands. A total of 2964 road segments and 161 stationary sites were sampled over two seasons. Our main comparison was based on predicted concentrations of the mobile and stationary monitoring LUR models at 12 682 residential addresses in Amsterdam. Predictor variables in the mobile and stationary LUR model were comparable, resulting in highly correlated predictions at external residential addresses (R(2) of 0.89 for UFP and 0.88 for BC). Mobile model predictions were, on average, 1.41 and 1.91 times higher than stationary model predictions for UFP and BC, respectively. LUR models based upon mobile and stationary monitoring predicted highly correlated UFP and BC concentration surfaces, but predicted concentrations based on mobile measurements were systematically higher.

  13. Applications of NASA and NOAA Satellite Observations by NASA's Short-term Prediction Research and Transition (SPoRT) Center in Response to Natural Disasters

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

    2012-01-01

    NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

  14. Recent earthquake prediction research in Japan.

    PubMed

    Mogi, K

    1986-07-18

    Japan has experienced many major earthquake disasters in the past. Early in this century research began that was aimed at predicting the occurrence of earthquakes, and in 1965 an earthquake prediction program was started as a national project. In 1978 a program for constant monitoring and assessment was formally inaugurated with the goal of forecasting the major earthquake that is expected to occur in the near future in the Tokai district of central Honshu Island. The issue of predicting the anticipated Tokai earthquake is discussed in this article as well as the results of research on major recent earthquakes in Japan-the Izu earthquakes (1978 and 1980) and the Japan Sea earthquake (1983).

  15. The art versus science of predicting prognosis: can a prognostic index predict short-term mortality better than experienced nurses do?

    PubMed

    Casarett, David J; Farrington, Sue; Craig, Teresa; Slattery, Julie; Harrold, Joan; Oldanie, Betty; Roy, Jason; Biehl, Richard; Teno, Joan

    2012-06-01

    To determine whether a prognostic index could predict one-week mortality more accurately than hospice nurses can. An electronic health record-based retrospective cohort study of 21,074 hospice patients was conducted in three hospice programs in the Southeast, Northeast, and Midwest United States. Model development used logistic regression with bootstrapped confidence intervals and multiple imputation to account for missing data. The main outcome measure was mortality within 7 days of hospice enrollment. A total of 21,074 patients were admitted to hospice between October 1, 2008 and May 31, 2011, and 5562 (26.4%) died within 7 days. An optimal predictive model included the Palliative Performance Scale (PPS) score, admission from a hospital, and gender. The model had a c-statistic of 0.86 in the training sample and 0.84 in the validation sample, which was greater than that of nurses' predictions (0.72). The index's performance was best for patients with pulmonary disease (0.89) and worst for patients with cancer and dementia (both 0.80). The index's predictions of mortality rates in each index category were within 5.0% of actual rates, whereas nurses underestimated mortality by up to 18.9%. Using the optimal index threshold (<3), the index's predictions had a better c-statistic (0.78 versus 0.72) and higher sensitivity (74.4% versus 47.8%) than did nurses' predictions but a lower specificity (80.6% versus 95.1%). Although nurses can often identify patients who will die within 7 days, a simple model based on available clinical information offers improved accuracy and could help to identify those patients who are at high risk for short-term mortality.

  16. Prediction of short-term newborn infectious morbidity based on maternal characteristics in patients with PPROM and Ureaplasma species infection.

    PubMed

    Mikołajczyk, Mateusz; Wirstlein, Przemysław Krzysztof; Wróbel, Magdalena; Mazela, Jan; Chojnacka, Karolina; Skrzypezak, Jana

    2015-09-01

    Preterm premature rupture of membranes (PPROM) complicates about 5% of pregnancies. Ureaplasma species is the most common pathogen found in the amniotic fluid in pregnancieneonatal outcome. The aim of the following study was to evaluate the impact of colonization with the Ureaplasma spp. on pregnant women with PPROM, coin fection with different microorganisms, and antimicrobial treatment on neonatal outcome. The study included 30 women with PPROM hospitalized in Division of Reproduction in s complicated by PPROM. It is speculated that it requires a coin fection to produce unfavorable Poznan's K. Marcinkowski University of Medical Sciences. Swabs from cenvical canal were obtained for the identifidation of bacterial and ureaplasma tic infections by culture and POR. The presence of any infection during the pregnancy a fter PP ROM was con firmed in 22 patients (Ureaplasma spp. in 12 patients, coin fection in 10 women). The cure rate for Ureaplasma species and other infections was 17% (2/12 patients) and 23% (5/22 patients), respectively There was no correlation between Ureaplasma species infection, coin fection, and cure status with the infection in the newborn. The PPROM to delivery duration also did not affect the newborn infection status. A negative relationship with leukocyte level was detected in patient with newborn infection. The presence of colonization with Ureaplasma species is not attributable to neonatal short-term morbidity The evaluation of maternal biochemical and microbiological data, regardless of the duration of the pregnancy after PPROM or the cure status, does not add any insight into the newborn infection status.

  17. Prognostic nutritional index predicts short-term outcomes after liver resection for hepatocellular carcinoma within the Milan criteria

    PubMed Central

    Li, Na; Ren, Yifan; Shi, Aihua; Lv, Yi; He, Haiqi

    2016-01-01

    Background The prognostic nutritional index (PNI) is calculated based on the serum albumin concentration and the total lymphocyte count. The aim of this study was to investigate the prognostic ability of the PNI for postoperative complications after liver resection to treat hepatocellular carcinoma (HCC) within the Milan criteria. Results Postoperative complications were observed in 166 (44.6%) patients. The optimal cutoff value of the PNI was set at 45.6 for postoperative complications. Patients in the PNI-low (PNI < 45.6) group were more likely to have postoperative complications, more blood loss, a longer surgery time and a longer hospital stay than patients in the PNI-high group (PNI > 45.6). Our regression analysis demonstrated that the preoperative PNI and albumin-bilirubin (ALBI) score were significantly associated with postoperative complications (Pearson correlation coefficient, -0.865, p < 0.001). The multivariate analysis revealed that the PNI was an independent predictor of postoperative complications. Materials and Methods Three-hundred and seventy-two patients who underwent partial hepatectomy for HCC from 2003 to 2014 were identified. The cutoff value of the PNI was determined by a receiver operating characteristic (ROC) curve analysis. Univariate and multivariate analyses were performed to identify clinicopathological features associated with postoperative complications. Conclusion The PNI may be a significant prognostic factor for evaluating short-term outcomes of patients with HCC after partial hepatectomy. PMID:27835570

  18. The Predictive Validity of the Short-Term Assessment of Risk and Treatability (START) for Multiple Adverse Outcomes in a Secure Psychiatric Inpatient Setting.

    PubMed

    O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L

    2016-04-01

    The Short-Term Assessment of Risk and Treatability (START) aims to assist mental health practitioners to estimate an individual's short-term risk for a range of adverse outcomes via structured consideration of their risk ("Vulnerabilities") and protective factors ("Strengths") in 20 areas. It has demonstrated predictive validity for aggression but this is less established for other outcomes. We collated START assessments for N = 200 adults in a secure mental health hospital and ascertained 3-month risk event incidence using the START Outcomes Scale. The specific risk estimates, which are the tool developers' suggested method of overall assessment, predicted aggression, self-harm/suicidality, and victimization, and had incremental validity over the Strength and Vulnerability scales for these outcomes. The Strength scale had incremental validity over the Vulnerability scale for aggressive outcomes; therefore, consideration of protective factors had demonstrable value in their prediction. Further evidence is required to support use of the START for the full range of outcomes it aims to predict.

  19. The parkfield, california, earthquake prediction experiment.

    PubMed

    Bakun, W H; Lindh, A G

    1985-08-16

    Five moderate (magnitude 6) earthquakes with similar features have occurred on the Parkfield section of the San Andreas fault in central California since 1857. The next moderate Parkfield earthquake is expected to occur before 1993. The Parkfield prediction experiment is designed to monitor the details of the final stages of the earthquake preparation process; observations and reports of seismicity and aseismic slip associated with the last moderate Parkfield earthquake in 1966 constitute much of the basis of the design of the experiment.

  20. Predicting Sexual Harassment From Hostile Sexism and Short-Term Mating Orientation: Relative Strength of Predictors Depends on Situational Priming of Power Versus Sex.

    PubMed

    Diehl, Charlotte; Rees, Jonas; Bohner, Gerd

    2016-12-09

    Previous research has shown that short-term mating orientation (STMO) and hostile sexism (HS) selectively predict different types of sexual harassment. In a priming experiment, we studied the situational malleability of those effects. Male participants could repeatedly send sexist jokes (gender harassment), harassing remarks (unwanted sexual attention), or nonharassing messages to a (computer-simulated) female target. Before entering the laboratory, participants were unobtrusively primed with the concepts of either sexuality or power. As hypothesized, sexuality priming strengthened the link between STMO and unwanted sexual attention, whereas power priming strengthened the link between HS and gender harassment. Practical implications are discussed.

  1. The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

    NASA Astrophysics Data System (ADS)

    Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

    2017-08-01

    The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

  2. Prediction of earthquake response spectra

    USGS Publications Warehouse

    Joyner, W.B.; Boore, David M.

    1982-01-01

    We have developed empirical equations for predicting earthquake response spectra in terms of magnitude, distance, and site conditions, using a two-stage regression method similar to the one we used previously for peak horizontal acceleration and velocity. We analyzed horizontal pseudo-velocity response at 5 percent damping for 64 records of 12 shallow earthquakes in Western North America, including the recent Coyote Lake and Imperial Valley, California, earthquakes. We developed predictive equations for 12 different periods between 0.1 and 4.0 s, both for the larger of two horizontal components and for the random horizontal component. The resulting spectra show amplification at soil sites compared to rock sites for periods greater than or equal to 0.3 s, with maximum amplification exceeding a factor of 2 at 2.0 s. For periods less than 0.3 s there is slight deamplification at the soil sites. These results are generally consistent with those of several earlier studies. A particularly significant aspect of the predicted spectra is the change of shape with magnitude (confirming earlier results by McGuire and by Irifunac and Anderson). This result indicates that the conventional practice of scaling a constant spectral shape by peak acceleration will not give accurate answers. The Newmark and Hall method of spectral scaling, using both peak acceleration and peak velocity, largely avoids this error. Comparison of our spectra with the Nuclear Regulatory Commission's Regulatory Guide 1.60 spectrum anchored at the same value at 0.1 s shows that the Regulatory Guide 1.60 spectrum is exceeded at soil sites for a magnitude of 7.5 at all distances for periods greater than about 0.5 s. Comparison of our spectra for soil sites with the corresponding ATC-3 curve of lateral design force coefficient for the highest seismic zone indicates that the ATC-3 curve is exceeded within about 7 km of a magnitude 6.5 earthquake and within about 15 km of a magnitude 7.5 event. The amount by

  3. The ethics of earthquake prediction.

    PubMed

    Sol, Ayhan; Turan, Halil

    2004-10-01

    Scientists' responsibility to inform the public about their results may conflict with their responsibility not to cause social disturbance by the communication of these results. A study of the well-known Brady-Spence and Iben Browning earthquake predictions illustrates this conflict in the publication of scientifically unwarranted predictions. Furthermore, a public policy that considers public sensitivity caused by such publications as an opportunity to promote public awareness is ethically problematic from (i) a refined consequentialist point of view that any means cannot be justified by any ends, and (ii) a rights view according to which individuals should never be treated as a mere means to ends. The Parkfield experiment, the so-called paradigm case of cooperation between natural and social scientists and the political authorities in hazard management and risk communication, is also open to similar ethical criticism. For the people in the Parkfield area were not informed that the whole experiment was based on a contested seismological paradigm.

  4. A toxicokinetic and toxicodynamic modeling approach using Myriophyllum spicatum to predict effects caused by short-term exposure to a sulfonylurea.

    PubMed

    Heine, Simon; Schild, Frederik; Schmitt, Walter; Krebber, Ralph; Görlitz, Gerhard; Preuss, Thomas G

    2016-02-01

    Toxicokinetic and toxicodynamic models are a promising tool to address the effects of time-variable chemical exposure. Standard toxicity tests usually rely on static concentrations, but these chemical exposure patterns are unlikely to appear in the field, where time-variable exposure of chemicals is typical. In the present study, toxicodynamic processes were integrated into an existing model that includes the toxicokinetics and growth of the aquatic plant Myriophyllum spicatum, to predict the impact on plant growth of 2 iofensulfuron short-term exposure patterns. To establish a method that can be used with standard data from risk assessments, the toxicodynamics of iofensulfuron were based on effect data from a 14-d standard toxicity test using static concentrations. Modeling showed that the toxicokinetic and toxicodynamic growth model of M. spicatum can be successfully used to predict effects of short-term iofensulfuron exposure by using effect data from a standard toxicity test. A general approach is presented, in which time-variable chemical exposures can be evaluated more realistically without conducting additional toxicity studies. © 2015 SETAC.

  5. Predicting short-term institutional aggression in forensic patients: a multi-trait method for understanding subtypes of aggression.

    PubMed

    Vitacco, Michael J; Van Rybroek, Gregory J; Rogstad, Jill E; Yahr, Laura E; Tomony, James D; Saewert, Emily

    2009-08-01

    Accurately predicting inpatient aggression is an important endeavor. The current study investigated inpatient aggression over a six-month time period in a sample of 152 male forensic patients. We assessed constructs of psychopathy, anger, and active symptoms of mental illness and tested their ability to predict reactive and instrumental aggression. Across all levels of analyses, anger and active symptoms of mental illness predicted reactive aggression. Traits of psychopathy, which demonstrated no relationship to reactive aggression, were a robust predictor of instrumental aggression. This study (a) reestablishes psychopathy as a clinically useful construct in predicting inpatient instrumental aggression, (b) provides some validation for the reactive/instrumental aggression paradigm in forensic inpatients, and (c) makes recommendations for integrating risk assessment results into treatment interventions.

  6. Does the stress response predict the ability of wild birds to adjust to short-term captivity? A study of the rock pigeon (Columbia livia)

    PubMed Central

    Parenteau, Charline; Trouvé, Colette; Angelier, Nicole

    2016-01-01

    Although the transfer of wild animals to captivity is crucial for conservation purposes, this process is often challenging because some species or individuals do not adjust well to captive conditions. Chronic stress has been identified as a major concern for animals held on long-term captivity. Surprisingly, the first hours or days of captivity have been relatively overlooked. However, they are certainly very stressful, because individuals are being transferred to a totally novel and confined environment. To ensure the success of conservation programmes, it appears crucial to better understand the proximate causes of interspecific and interindividual variability in the sensitivity to these first hours of captivity. In that respect, the study of stress hormones is relevant, because the hormonal stress response may help to assess whether specific individuals or species adjust, or not, to such captive conditions (‘the stress response-adjustment to captivity hypothesis’). We tested this hypothesis in rock pigeons by measuring their corticosterone stress response and their ability to adjust to short-term captivity (body mass loss and circulating corticosterone levels after a day of captivity). We showed that an increased corticosterone stress response is associated with a lower ability to adjust to short-term captivity (i.e. higher body mass loss and circulating corticosterone levels). Our study suggests, therefore, that a low physiological sensitivity to stress may be beneficial for adjusting to captivity. Future studies should now explore whether the stress response can be useful to predict the ability of individuals from different populations or species to not only adjust to short-term but also long-term captivity. PMID:28083117

  7. Does the stress response predict the ability of wild birds to adjust to short-term captivity? A study of the rock pigeon (Columbia livia).

    PubMed

    Angelier, Frédéric; Parenteau, Charline; Trouvé, Colette; Angelier, Nicole

    2016-12-01

    Although the transfer of wild animals to captivity is crucial for conservation purposes, this process is often challenging because some species or individuals do not adjust well to captive conditions. Chronic stress has been identified as a major concern for animals held on long-term captivity. Surprisingly, the first hours or days of captivity have been relatively overlooked. However, they are certainly very stressful, because individuals are being transferred to a totally novel and confined environment. To ensure the success of conservation programmes, it appears crucial to better understand the proximate causes of interspecific and interindividual variability in the sensitivity to these first hours of captivity. In that respect, the study of stress hormones is relevant, because the hormonal stress response may help to assess whether specific individuals or species adjust, or not, to such captive conditions ('the stress response-adjustment to captivity hypothesis'). We tested this hypothesis in rock pigeons by measuring their corticosterone stress response and their ability to adjust to short-term captivity (body mass loss and circulating corticosterone levels after a day of captivity). We showed that an increased corticosterone stress response is associated with a lower ability to adjust to short-term captivity (i.e. higher body mass loss and circulating corticosterone levels). Our study suggests, therefore, that a low physiological sensitivity to stress may be beneficial for adjusting to captivity. Future studies should now explore whether the stress response can be useful to predict the ability of individuals from different populations or species to not only adjust to short-term but also long-term captivity.

  8. Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

    PubMed

    Almaraashi, Majid

    2017-01-01

    Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data.

  9. Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems

    PubMed Central

    2017-01-01

    Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data. PMID:28806754

  10. Comparison of short-term rainfall forecasts for model-based flow prediction in urban drainage systems.

    PubMed

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas; Borup, Morten; Ahm, Malte; Nielsen, Jesper Ellerbæk; Grum, Morten; Rasmussen, Michael R; Gill, Rasphall; Mikkelsen, Peter Steen

    2013-01-01

    Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real-time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 h. The best performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times.

  11. Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band

    NASA Astrophysics Data System (ADS)

    de Montera, L.; Mallet, C.; Barthès, L.; Golé, P.

    2008-08-01

    This paper shows how nonlinear models originally developed in the finance field can be used to predict rain attenuation level and volatility in Earth-to-Satellite links operating at the Extremely High Frequencies band (EHF, 20 50 GHz). A common approach to solving this problem is to consider that the prediction error corresponds only to scintillations, whose variance is assumed to be constant. Nevertheless, this assumption does not seem to be realistic because of the heteroscedasticity of error time series: the variance of the prediction error is found to be time-varying and has to be modeled. Since rain attenuation time series behave similarly to certain stocks or foreign exchange rates, a switching ARIMA/GARCH model was implemented. The originality of this model is that not only the attenuation level, but also the error conditional distribution are predicted. It allows an accurate upper-bound of the future attenuation to be estimated in real time that minimizes the cost of Fade Mitigation Techniques (FMT) and therefore enables the communication system to reach a high percentage of availability. The performance of the switching ARIMA/GARCH model was estimated using a measurement database of the Olympus satellite 20/30 GHz beacons and this model is shown to outperform significantly other existing models. The model also includes frequency scaling from the downlink frequency to the uplink frequency. The attenuation effects (gases, clouds and rain) are first separated with a neural network and then scaled using specific scaling factors. As to the resulting uplink prediction error, the error contribution of the frequency scaling step is shown to be larger than that of the downlink prediction, indicating that further study should focus on improving the accuracy of the scaling factor.

  12. Predictability of Solar Radiation for Photovoltaics systems over Europe: from short-term to seasonal time-scales

    NASA Astrophysics Data System (ADS)

    De Felice, Matteo; Petitta, Marcello; Ruti, Paolo

    2014-05-01

    Photovoltaic diffusion is steadily growing on Europe, passing from a capacity of almost 14 GWp in 2011 to 21.5 GWp in 2012 [1]. Having accurate forecast is needed for planning and operational purposes, with the possibility to model and predict solar variability at different time-scales. This study examines the predictability of daily surface solar radiation comparing ECMWF operational forecasts with CM-SAF satellite measurements on the Meteosat (MSG) full disk domain. Operational forecasts used are the IFS system up to 10 days and the System4 seasonal forecast up to three months. Forecast are analysed considering average and variance of errors, showing error maps and average on specific domains with respect to prediction lead times. In all the cases, forecasts are compared with predictions obtained using persistence and state-of-art time-series models. We can observe a wide range of errors, with the performance of forecasts dramatically affected by orography and season. Lower errors are on southern Italy and Spain, with errors on some areas consistently under 10% up to ten days during summer (JJA). Finally, we conclude the study with some insight on how to "translate" the error on solar radiation to error on solar power production using available production data from solar power plants. [1] EurObserver, "Baromètre Photovoltaïque, Le journal des énergies renouvables, April 2012."

  13. Predicting Long-term Temperature Increase for Time-Dependent SAR Levels with a Single Short-term Temperature Response

    PubMed Central

    Carluccio, Giuseppe; Bruno, Mary; Collins, Christopher M.

    2015-01-01

    Purpose Present a novel method for rapid prediction of temperature in vivo for a series of pulse sequences with differing levels and distributions of specific energy absorption rate (SAR). Methods After the temperature response to a brief period of heating is characterized, a rapid estimate of temperature during a series of periods at different heating levels is made using a linear heat equation and Impulse-Response (IR) concepts. Here the initial characterization and long-term prediction for a complete spine exam are made with the Pennes’ bioheat equation where, at first, core body temperature is allowed to increase and local perfusion is not. Then corrections through time allowing variation in local perfusion are introduced. Results The fast IR-based method predicted maximum temperature increase within 1% of that with a full finite difference simulation, but required less than 3.5% of the computation time. Even higher accelerations are possible depending on the time step size chosen, with loss in temporal resolution. Correction for temperature-dependent perfusion requires negligible additional time, and can be adjusted to be more or less conservative than the corresponding finite difference simulation. Conclusion With appropriate methods, it is possible to rapidly predict temperature increase throughout the body for actual MR examinations. (200/200 words) PMID:26096947

  14. A knowledge-based system for the diagnosis and prediction of short-term climatic changes in the North Atlantic

    SciTech Connect

    Rodionov, S.; Martin, J.H.

    1996-08-01

    Understanding and predicting climate change is the key problem in climatology. The most well-accepted current approach to this problem involves the development of general circulation models (GCMs). This approach is based on modeling fundamental physical principles in large computer programs. At the same time, however, an increasingly large proportion of the available information regarding the climate system exists in the form of heuristics, or empirical rules of thumb. The objective of the CESNA (Climatic Expert System For the North Atlantic) project is to develop a practical system that can manipulate this qualitative information in such a way as to facilitate insights into observed and anticipated climate changes. The methods used to reach this objective are based on concepts and techniques derived artificial intelligence research on representing and reasoning with uncertain knowledge. A recently completed evaluation of the prototype CESNA measured how well it could predict the sea temperature of the Kola section of the barents sea for the period 1965 to 1991 with a one-year lead time. The system`s predictions paralleled the observed temperatures with remarkable accuracy. Similar results were obtained for two other regions, the northwest Atlantic and the southeastern United States. Qualitatively, these experiments show that even though some rules may be poor predictors in a given year, the combined evidence from the remaining results in an accurate prediction. 37 refs., 1 fig.

  15. An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction.

    PubMed

    Ak, Ronay; Vitelli, Valeria; Zio, Enrico

    2015-11-01

    We consider the task of performing prediction with neural networks (NNs) on the basis of uncertain input data expressed in the form of intervals. We aim at quantifying the uncertainty in the prediction arising from both the input data and the prediction model. A multilayer perceptron NN is trained to map interval-valued input data onto interval outputs, representing the prediction intervals (PIs) of the real target values. The NN training is performed by nondominated sorting genetic algorithm-II, so that the PIs are optimized both in terms of accuracy (coverage probability) and dimension (width). Demonstration of the proposed method is given in two case studies: 1) a synthetic case study, in which the data have been generated with a 5-min time frequency from an autoregressive moving average model with either Gaussian or Chi-squared innovation distribution and 2) a real case study, in which experimental data consist of wind speed measurements with a time step of 1 h. Comparisons are given with a crisp (single-valued) approach. The results show that the crisp approach is less reliable than the interval-valued input approach in terms of capturing the variability in input.

  16. Predicting long-term temperature increase for time-dependent SAR levels with a single short-term temperature response.

    PubMed

    Carluccio, Giuseppe; Bruno, Mary; Collins, Christopher M

    2016-05-01

    Present a novel method for rapid prediction of temperature in vivo for a series of pulse sequences with differing levels and distributions of specific energy absorption rate (SAR). After the temperature response to a brief period of heating is characterized, a rapid estimate of temperature during a series of periods at different heating levels is made using a linear heat equation and impulse-response (IR) concepts. Here the initial characterization and long-term prediction for a complete spine exam are made with the Pennes' bioheat equation where, at first, core body temperature is allowed to increase and local perfusion is not. Then corrections through time allowing variation in local perfusion are introduced. The fast IR-based method predicted maximum temperature increase within 1% of that with a full finite difference simulation, but required less than 3.5% of the computation time. Even higher accelerations are possible depending on the time step size chosen, with loss in temporal resolution. Correction for temperature-dependent perfusion requires negligible additional time and can be adjusted to be more or less conservative than the corresponding finite difference simulation. With appropriate methods, it is possible to rapidly predict temperature increase throughout the body for actual MR examinations. © 2015 Wiley Periodicals, Inc.

  17. Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

    PubMed Central

    Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

    2014-01-01

    Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

  18. Signal Detection and Earthquake Catalogue Development Using a Short-term, Over 800-station, Mixed-mode Seismic Array Deployed Above the Socorro Magma Body, NM

    NASA Astrophysics Data System (ADS)

    Bilek, S. L.; Schmandt, B.; Hansen, S. M.; Worthington, L. L.; Aster, R. C.

    2015-12-01

    Magma movement and emplacement within the crust is an important aspect to understanding crustal formation and deformation. The 19-km deep Socorro Magma Body, the second largest mid-crustal continental magma body known worldwide, produces measurable crustal deformation and seismicity within the Rio Grande Rift region in central New Mexico. There have been a variety of studies to estimate the location and size of this feature as well as possible changes related to magma or fluid migration. The extent of the feature has been previously estimated by observation of reflected phases arising from earthquakes located above the feature recorded by a sparse local seismic network. To improve our understanding of the spatial extent of the Socorro Magma Body, we deployed a mixed mode seismic array for 2 weeks over the northern portion of the magma body consisting of 7 3-component broadband seismometers and over 800 Fairfield vertical-component autonomous node seismographs with integral 10 Hz seismometers. This array will allow for us to improve our estimates of spatial extent of the body and possible heterogeneities resulting from fluid or magma migration at shallower depths. Here we focus on initial steps to analyze this large volume of data, in conjunction with other local and regional seismic stations, to determine a local and teleseismic earthquake catalog during the deployment time period. These earthquakes will then be used to probe the structure of the Socorro Magma Body and its surroundings. We employ multiple strategies for building this catalog, including standard amplitude-based detection tools with the broadband data, triggering algorithms with the node data, and back-projection of the node data over limited sections of the array. Initial results suggest a number of previously undetected earthquakes located beneath the array, as well as regional events from an earthquake sequence in Arizona.

  19. Raising the science awareness of first year undergraduate students via an earthquake prediction seminar

    NASA Astrophysics Data System (ADS)

    Gilstrap, T. D.

    2011-12-01

    The public is fascinated with and fearful of natural hazards such as earthquakes. After every major earthquake there is a surge of interest in earthquake science and earthquake prediction. Yet many people do not understand the challenges of earthquake prediction and the need to fund earthquake research. An earthquake prediction seminar is offered to first year undergraduate students to improve their understanding of why earthquakes happen, how earthquake research is done and more specifically why it is so challenging to issue short-term earthquake prediction. Some of these students may become scientists but most will not. For the majority this is an opportunity to learn how science research works and how it is related to policy and society. The seminar is seven weeks long, two hours per week and has been taught every year for the last four years. The material is presented conceptually; there is very little quantitative work involved. The class starts with a field trip to the Randolph College Seismic Station where students learn about seismographs and the different types of seismic waves. Students are then provided with basic background on earthquakes. They learn how to pick arrival times using real seismograms, how to use earthquake catalogues, how to predict the arrival of an earthquake wave at any location on Earth. Next they learn about long, intermediate, short and real time earthquake prediction. Discussions are an essential part of the seminar. Students are challenged to draw their own conclusions on the pros and cons of earthquake prediction. Time is designated to discuss the political and economic impact of earthquake prediction. At the end of the seven weeks students are required to write a paper and discuss the need for earthquake prediction. The class is not focused on the science but rather the links between the science issues and their economical and political impact. Weekly homework assignments are used to aid and assess students' learning. Pre and

  20. Predicting short-term positive affect in individuals with social anxiety disorder: The role of selected personality traits and emotion regulation strategies.

    PubMed

    Weisman, Jaclyn S; Rodebaugh, Thomas L; Lim, Michelle H; Fernandez, Katya C

    2015-08-01

    Recently, research has provided support for a moderate, inverse relationship between social anxiety and dispositional positive affect. However, the dynamics of this relationship remain poorly understood. The present study evaluates whether certain personality traits and emotion regulation variables predict short-term positive affect for individuals with social anxiety disorder and healthy controls. Positive affect as measured by two self-report instruments was assessed before and after two tasks in which the participant conversed with either a friend or a romantic partner. Tests of models examining the hypothesized prospective predictors revealed that the paths did not differ significantly across diagnostic group and both groups showed the hypothesized patterns of endorsement for the emotion regulation variables. Further, a variable reflecting difficulty redirecting oneself when distressed prospectively predicted one measure of positive affect. Additional research is needed to explore further the role of emotion regulation strategies on positive emotions for individuals higher in social anxiety. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Predicting Short-Term Positive Affect in Individuals with Social Anxiety Disorder: The Role of Selected Personality Traits and Emotion Regulation Strategies

    PubMed Central

    Weisman, Jaclyn S.; Rodebaugh, Thomas L.; Lim, Michelle H.; Fernandez, Katya C.

    2015-01-01

    Recently, research has provided support for a moderate, inverse relationship between social anxiety and dispositional positive affect. However, the dynamics of this relationship remain poorly understood. The present study evaluates whether certain personality traits and emotion regulation variables predict short-term positive affect for individuals with social anxiety disorder and healthy controls. Positive affect as measured by two self-report instruments was assessed before and after two tasks in which the participant conversed with either a friend or a romantic partner. Tests of models examining the hypothesized prospective predictors revealed that the paths did not differ significantly across diagnostic group and both groups showed the hypothesized patterns of endorsement for the emotion regulation variables. Further, a variable reflecting difficulty redirecting oneself when distressed prospectively predicted one measure of positive affect. Additional research is needed to explore further the role of emotion regulation strategies on positive emotions for individuals higher in social anxiety. PMID:26119140

  2. Earthquake Prediction: Is It Better Not to Know?

    ERIC Educational Resources Information Center

    MOSAIC, 1977

    1977-01-01

    Discusses economic, social and political consequences of earthquake prediction. Reviews impact of prediction on China's recent (February, 1975) earthquake. Diagrams a chain of likely economic consequences from predicting an earthquake. (CS)

  3. Earthquake Prediction: Is It Better Not to Know?

    ERIC Educational Resources Information Center

    MOSAIC, 1977

    1977-01-01

    Discusses economic, social and political consequences of earthquake prediction. Reviews impact of prediction on China's recent (February, 1975) earthquake. Diagrams a chain of likely economic consequences from predicting an earthquake. (CS)

  4. Short-term predictive validity of the static-99 and static-99-R for indigenous and nonindigenous Australian sexual offenders.

    PubMed

    Smallbone, Stephen; Rallings, Mark

    2013-06-01

    Actuarial risk assessment (Static-99 and Static-99-R) scores were obtained for 399 Australian adult sexual offenders who were subsequently released from prison and followed up with searches of police arrest records (mean follow-up period = 29 months; range = 15-53 months). Indigenous offenders (n = 67; 16.8%) scored significantly higher on both the Static-99 (M = 4.04 vs. 2.89, p < .001) and Static-99-R (M = 3.72 vs. 2.22, p < .001), were more than twice as likely to be arrested for sexual offenses (9.0% vs. 4.1%, ns), and were significantly more likely to be arrested for nonsexual violent (28.4% vs. 1.9%, p < .001), any violent (including sexual; 37% vs. 5.9%, p < .001), and any offenses (58.2% vs. 21.6%, p < .001). For the combined groups, predictive accuracy of both instruments was comparable to results reported elsewhere. Predictive accuracy of the Static-99 was similar for indigenous and nonindigenous offenders. The Static-99-R was only marginally predictive of any violent recidivism (AUC = .65, 95% CI = [.52, .79]), and did not predict sexual (AUC = .61, 95% CI = [.45, .77]) or nonsexual violent recidivism (AUC = .65, 95% CI = [.48, .78]), for indigenous offenders. Higher risk scores, indigenous race, and unsupervised release all contributed unique variance to any violent recidivism. Results suggest that the Static-99 may be appropriate for assessing Australian indigenous sexual offenders, but more research is needed to test the validity of the Static-99-R for this population. We conclude that practitioners should consider the potential effects of racial differences and postrelease factors, as well as static risk factors, in their assessments.

  5. Relevance analysis and short-term prediction of PM2.5 concentrations in Beijing based on multi-source data

    NASA Astrophysics Data System (ADS)

    Ni, X. Y.; Huang, H.; Du, W. P.

    2017-02-01

    The PM2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM2.5. In this paper, we attempted to realize the relevance analysis and short-term prediction of PM2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO2, SO2, PM10) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO2, PM10, and the daily number of microblog entries with key words 'Beijing; Air pollution' show high mathematical correlation with PM2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM2.5 and it also helps to broaden the application of big data and the multi-source data mining methods.

  6. Global empirical model of TEC response to geomagnetic activity: Short-term (24 hours ahead) prediction model

    NASA Astrophysics Data System (ADS)

    Andonov, Borislav

    2013-04-01

    A global empirical model of the rTEC=(TECobs-TECmed)/TECmed depending on the geomagnetic activity (described by the Kp-index) and at a given moment is built by using global TEC data for full 13 years between 1999 and 2011.The data are downloaded from the CODE (Center for Orbit Determination in Europe) database in the Astronomical Institute, University of Bern. By using a 2D cross-correlation analysis it is found that the ionospheric response to the geomagnetic activity revealed both positive and negative phases of the response. The both phases of the ionospheric response have different duration and time delay with respect to the geomagnetic storm. It was found that these two parameters of the ionospheric response depend on the season, geographical/geomagnetic coordinates and local time. The rTEC response is represented by 2D (longitude-time) sine waves with different zonal wavenumbers and periods being harmonics of the diurnal period. The input data for the current and predicted geomagnetic activity are obtained from the MAK model developed in NIGGG-BAS, which uses the solar wind measurements from the ACE satellite. The background condition is defined by the recent CODE TEC maps. For each current hour the model provides predicted global TEC maps in geographic frame for the next 24 hours.

  7. Short-Term Prediction of Traffic Rate Interval Router Using Hybrid Training of Dynamic Synapse Neural Network Structure

    NASA Astrophysics Data System (ADS)

    Shakiba, M.; Teshnehlab, M.; Zokaie, S.; Zakermoshfegh, M.

    In this study, a hybrid learning algorithm for training the Dynamic Synapse Neural Network (DSNN) to high accurate prediction of congestion in TCP computer networks is introduced. The idea behind this technique is to inform the TCP transmitters of congestion before it happens and to make transmitters decrease their data sending rate to a level which does not overflow the routers buffer. Traffic rate data are available in the format of time series and these real data are used to train and predict the future traffic rate condition. Hybrid learning algorithm aims to solve main problems of the Gradient Descent (GD) based method for the optimization of the DSNN, which are instability, local minima and the problem of generalization of trained network to the test data. In this method, Adaptable Weighted Particle Swarm Optimization (AWPSO) as a global optimizer is used to optimize the parameters of synaptic plasticity and the GD algorithm is used to optimize the weighted parameters of DSNN. As AWPSO is a derivative free optimization technique, a simpler method for the train of DSNN is achieved. Also the results are compared to GD algorithm.

  8. Estimation and Short-Term Prediction of the Course of the HIV Epidemic Using Demographic and Health Survey Methodology-Like Data.

    PubMed

    Blaizot, Stéphanie; Riche, Benjamin; Maman, David; Mukui, Irene; Kirubi, Beatrice; Etard, Jean-François; Ecochard, René

    2015-01-01

    Mathematical models have played important roles in the understanding of epidemics and in the study of the impacts of various behavioral or medical measures. However, modeling accurately the future spread of an epidemic requires context-specific parameters that are difficult to estimate because of lack of data. Our objective is to propose a methodology to estimate context-specific parameters using Demographic and Health Survey (DHS)-like data that can be used in mathematical modeling of short-term HIV spreading. The model splits the population according to sex, age, HIV status, and antiretroviral treatment status. To estimate context-specific parameters, we used individuals' histories included in DHS-like data and a statistical analysis that used decomposition of the Poisson likelihood. To predict the course of the HIV epidemic, sex- and age-specific differential equations were used. This approach was applied to recent data from Kenya. The approach allowed the estimation of several key epidemiological parameters. Women had a higher infection rate than men and the highest infection rate in the youngest age groups (15-24 and 25-34 years) whereas men had the highest infection rate in age group 25-34 years. The immunosuppression rates were similar between age groups. The treatment rate was the highest in age group 35-59 years in both sexes. The results showed that, within the 15-24 year age group, increasing male circumcision coverage and antiretroviral therapy coverage at CD4 ≤ 350/mm3 over the current 70% could have short-term impacts. The study succeeded in estimating the model parameters using DHS-like data rather than literature data. The analysis provides a framework for using the same data for estimation and prediction, which can improve the validity of context-specific predictions and help designing HIV prevention campaigns.

  9. Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult.

    PubMed

    Paolini, Brielle M; Laurienti, Paul J; Simpson, Sean L; Burdette, Jonathan H; Lyday, Robert G; Rejeski, W Jack

    2015-01-01

    Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL) remain popular, the rate of success is highly variable. Clearly, self-regulation of eating behavior is a challenge and patterns of activity across the brain may be an important determinant of success. The current study prospectively examined whether integration across the Hot-State Brain Network of Appetite (HBN-A) predicts WL after 6-months of treatment in older adults. Our metric for network integration was global efficiency (GE). The present work is a sub-study (n = 56) of an ongoing randomized clinical trial involving WL. Imaging involved a baseline food-cue visualization functional MRI (fMRI) scan following an overnight fast. Using graph theory to build functional brain networks, we demonstrated that regions of the HBN-A (insula, anterior cingulate cortex (ACC), superior temporal pole (STP), amygdala and the parahippocampal gyrus) were highly integrated as evidenced by the results of a principal component analysis (PCA). After accounting for known correlates of WL (baseline weight, age, sex, and self-regulatory efficacy) and treatment condition, which together contributed 36.9% of the variance in WL, greater GE in the HBN-A was associated with an additional 19% of the variance. The ACC of the HBN-A was the primary driver of this effect, accounting for 14.5% of the variance in WL when entered in a stepwise regression following the covariates, p = 0.0001. The HBN-A is comprised of limbic regions important in the processing of emotions and visceral sensations and the ACC is key for translating such processing into behavioral consequences. The improved integration of these regions may enhance awareness of body and emotional states leading to more successful self-regulation and to greater WL. This is the first study among older adults to prospectively demonstrate that, following an overnight fast, GE of the HBN-A during a food visualization task is predictive of

  10. Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult

    PubMed Central

    Paolini, Brielle M.; Laurienti, Paul J.; Simpson, Sean L.; Burdette, Jonathan H.; Lyday, Robert G.; Rejeski, W. Jack

    2015-01-01

    Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL) remain popular, the rate of success is highly variable. Clearly, self-regulation of eating behavior is a challenge and patterns of activity across the brain may be an important determinant of success. The current study prospectively examined whether integration across the Hot-State Brain Network of Appetite (HBN-A) predicts WL after 6-months of treatment in older adults. Our metric for network integration was global efficiency (GE). The present work is a sub-study (n = 56) of an ongoing randomized clinical trial involving WL. Imaging involved a baseline food-cue visualization functional MRI (fMRI) scan following an overnight fast. Using graph theory to build functional brain networks, we demonstrated that regions of the HBN-A (insula, anterior cingulate cortex (ACC), superior temporal pole (STP), amygdala and the parahippocampal gyrus) were highly integrated as evidenced by the results of a principal component analysis (PCA). After accounting for known correlates of WL (baseline weight, age, sex, and self-regulatory efficacy) and treatment condition, which together contributed 36.9% of the variance in WL, greater GE in the HBN-A was associated with an additional 19% of the variance. The ACC of the HBN-A was the primary driver of this effect, accounting for 14.5% of the variance in WL when entered in a stepwise regression following the covariates, p = 0.0001. The HBN-A is comprised of limbic regions important in the processing of emotions and visceral sensations and the ACC is key for translating such processing into behavioral consequences. The improved integration of these regions may enhance awareness of body and emotional states leading to more successful self-regulation and to greater WL. This is the first study among older adults to prospectively demonstrate that, following an overnight fast, GE of the HBN-A during a food visualization task is predictive of

  11. Patterns of waste generation: A gradient boosting model for short-term waste prediction in New York City.

    PubMed

    Johnson, Nicholas E; Ianiuk, Olga; Cazap, Daniel; Liu, Linglan; Starobin, Daniel; Dobler, Gregory; Ghandehari, Masoud

    2017-04-01

    Historical municipal solid waste (MSW) collection data supplied by the New York City Department of Sanitation (DSNY) was used in conjunction with other datasets related to New York City to forecast municipal solid waste generation across the city. Spatiotemporal tonnage data from the DSNY was combined with external data sets, including the Longitudinal Employer Household Dynamics data, the American Community Survey, the New York City Department of Finance's Primary Land Use and Tax Lot Output data, and historical weather data to build a Gradient Boosting Regression Model. The model was trained on historical data from 2005 to 2011 and validation was performed both temporally and spatially. With this model, we are able to accurately (R2>0.88) forecast weekly MSW generation tonnages for each of the 232 geographic sections in NYC across three waste streams of refuse, paper and metal/glass/plastic. Importantly, the model identifies regularity of urban waste generation and is also able to capture very short timescale fluctuations associated to holidays, special events, seasonal variations, and weather related events. This research shows New York City's waste generation trends and the importance of comprehensive data collection (especially weather patterns) in order to accurately predict waste generation. Copyright © 2017. Published by Elsevier Ltd.

  12. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite

    PubMed Central

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN usingimages of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN. PMID:26447470

  13. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

    PubMed

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  14. Short-Term Pulmonary Function Trends Are Predictive of Mortality in Interstitial Lung Disease Associated With Systemic Sclerosis.

    PubMed

    Goh, Nicole S; Hoyles, Rachel K; Denton, Christopher P; Hansell, David M; Renzoni, Elisabetta A; Maher, Toby M; Nicholson, Andrew G; Wells, Athol U

    2017-08-01

    To determine the prognostic value of pulmonary function test (PFT) trends at 1 and 2 years in interstitial lung disease (ILD) associated with systemic sclerosis (SSc). The prognostic significance of PFT trends at 1 year (n = 162) and 2 years (n = 140) was examined against 15-year survival in patients with SSc-associated ILD. PFT trends, expressed as continuous change and as categorical change in separate analyses, were examined against mortality in univariate and multivariate models. SSc-associated ILD was defined at presentation as either limited lung fibrosis or extensive lung fibrosis, using the United Kingdom Raynaud's and Scleroderma Association severity staging system. One-year PFT trends were predictive of mortality only in patients with extensive lung fibrosis: categorical change in the forced vital capacity (FVC), alone or in combination with categorical change in the diffusing capacity for carbon monoxide (DLco), had greater prognostic significance than continuous change in the FVC or trends in other PFT variables. Taking into account both prognostic value and sensitivity to change, the optimal definition of progression for trial purposes was an FVC and DLco composite end point, consisting of either an FVC decline from baseline of ≥10% or an FVC decline of 5-9% in association with a DLco decline of ≥15%. At 2 years, gas transfer trends had the greatest prognostic significance, in the whole cohort and in those with limited lung fibrosis. However, in patients with extensive lung fibrosis, the above-defined FVC and DLco composite end point was the strongest prognostic determinant. Larger changes in the FVC:DLco ratio than in the carbon monoxide transfer coefficient were required to achieve prognostic significance. Based on linkages to long-term outcomes, these findings provide support for use of routine spirometry and gas transfer monitoring in patients with SSc-associated ILD, with further evaluation of a composite FVC and DLco end point

  15. Use of a Comprehensive Geriatric Assessment to Predict Short-Term Postoperative Outcome in Elderly Patients With Colorectal Cancer

    PubMed Central

    Lee, Yoon Hyun; Oh, Heung-Kwon; Ihn, Myong Hoon; Kim, Jee Hyun; Son, Il Tae; Kang, Sung Il; Kim, Gwang Il; Ahn, Soyeon; Kang, Sung-Bum

    2016-01-01

    Purpose This study was conducted to identify the effectiveness of a preoperative comprehensive geriatric assessment (CGA) for predicting postoperative morbidity in elderly patients who underwent surgery for colorectal cancer. Methods Elderly patients (≥70 years old) who underwent surgery for colorectal cancer at a tertiary hospital in Korea were identified, and their cases were analyzed using data from a prospectively collected database to establish an association between major postsurgical complications and 'high-risk' patient as defined by the CGA. Results A total of 240 patients, with a mean age of 76.7 ± 5.2 years, were enrolled. Ninety-five patients (39.6%) were classified as "high-risk" and 99 patients (41.3%) as having postoperative complications. The univariate analysis indicated that risk factors for postoperative complications were age, American Society of Anesthesiologists physical status classification, serum hemoglobin, carcinoembryonic antigen, cancer stage, and "high-risk" status. The multivariable analyses indicated that "high-risk" status (odds ratio, 2.107; 95% confidence interval, 1.168–3.804; P = 0.013) and elevated preoperative carcinoembryonic antigen (odds ratio, 2.561; 95% confidence interval, 1.346–4.871, P = 0.004) were independently associated with postoperative complications. A multivariable analysis of the individual CGA domains indicated that high comorbidities and low activities of daily living were significantly related with postoperative complications. Conclusion A preoperative CGA indicating "high-risk" was associated with major postoperative complications in elderly patients who underwent surgery for colorectal cancer. Thus, using the CGA to identify elderly colorectal-cancer patients who should be given more care during postoperative management may be clinically beneficial. PMID:27847786

  16. The PER (Preoperative Esophagectomy Risk) Score: A Simple Risk Score to Predict Short-Term and Long-Term Outcome in Patients with Surgically Treated Esophageal Cancer

    PubMed Central

    Reeh, Matthias; Metze, Johannes; Uzunoglu, Faik G.; Nentwich, Michael; Ghadban, Tarik; Wellner, Ullrich; Bockhorn, Maximilian; Kluge, Stefan; Izbicki, Jakob R.; Vashist, Yogesh K.

    2016-01-01

    Abstract Esophageal resection in patients with esophageal cancer (EC) is still associated with high mortality and morbidity rates. We aimed to develop a simple preoperative risk score for the prediction of short-term and long-term outcomes for patients with EC treated by esophageal resection. In total, 498 patients suffering from esophageal carcinoma, who underwent esophageal resection, were included in this retrospective cohort study. Three preoperative esophagectomy risk (PER) groups were defined based on preoperative functional evaluation of different organ systems by validated tools (revised cardiac risk index, model for end-stage liver disease score, and pulmonary function test). Clinicopathological parameters, morbidity, and mortality as well as disease-free survival (DFS) and overall survival (OS) were correlated to the PER score. The PER score significantly predicted the short-term outcome of patients with EC who underwent esophageal resection. PER 2 and PER 3 patients had at least double the risk of morbidity and mortality compared to PER 1 patients. Furthermore, a higher PER score was associated with shorter DFS (P < 0.001) and OS (P < 0.001). The PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P < 0.001) and OS (HR 2.2; P < 0.001). The PER score allows preoperative objective allocation of patients with EC into different risk categories for morbidity, mortality, and long-term outcomes. Thus, multicenter studies are needed for independent validation of the PER score. PMID:26886613

  17. Prediction of the effect of atrasentan on renal and heart failure outcomes based on short-term changes in multiple risk markers.

    PubMed

    Schievink, Bauke; de Zeeuw, Dick; Smink, Paul A; Andress, Dennis; Brennan, John J; Coll, Blai; Correa-Rotter, Ricardo; Hou, Fan Fan; Kohan, Donald; Kitzman, Dalane W; Makino, Hirofumi; Parving, Hans-Henrik; Perkovic, Vlado; Remuzzi, Giuseppe; Tobe, Sheldon; Toto, Robert; Hoekman, Jarno; Lambers Heerspink, Hiddo J

    2016-05-01

    A recent phase II clinical trial (Reducing Residual Albuminuria in Subjects with Diabetes and Nephropathy with AtRasentan trial and an identical trial in Japan (RADAR/JAPAN)) showed that the endothelin A receptor antagonist atrasentan lowers albuminuria, blood pressure, cholesterol, hemoglobin, and increases body weight in patients with type 2 diabetes and nephropathy. We previously developed an algorithm, the Parameter Response Efficacy (PRE) score, which translates short-term drug effects into predictions of long-term effects on clinical outcomes. We used the PRE score on data from the RADAR/JAPAN study to predict the effect of atrasentan on renal and heart failure outcomes. We performed a post-hoc analysis of the RADAR/JAPAN randomized clinical trials in which 211 patients with type-2 diabetes and nephropathy were randomly assigned to atrasentan 0.75 mg/day, 1.25 mg/day, or placebo. A PRE score was developed in a background set of completed clinical trials using multivariate Cox models. The score was applied to baseline and week-12 risk marker levels of RADAR/JAPAN participants, to predict atrasentan effects on clinical outcomes. Outcomes were defined as doubling serum creatinine or end-stage renal disease and hospitalization for heart failure. The PRE score predicted renal risk changes of -23% and -30% for atrasentan 0.75 and 1.25 mg/day, respectively. PRE scores also predicted a small non-significant increase in heart failure risk for atrasentan 0.75 and 1.25 mg/day (+2% vs. +7%). Selecting patients with >30% albuminuria reduction from baseline (responders) improved renal outcome to almost 50% risk reduction, whereas non-responders showed no renal benefit. Based on the RADAR/JAPAN study, with short-term changes in risk markers, atrasentan is expected to decrease renal risk without increased risk of heart failure. Within this population albuminuria responders appear to contribute to the predicted improvements, whereas non-responders showed no benefit

  18. The U.S. Earthquake Prediction Program

    USGS Publications Warehouse

    Wesson, R.L.; Filson, J.R.

    1981-01-01

    There are two distinct motivations for earthquake prediction. The mechanistic approach aims to understand the processes leading to a large earthquake. The empirical approach is governed by the immediate need to protect lives and property. With our current lack of knowledge about the earthquake process, future progress cannot be made without gathering a large body of measurements. These are required not only for the empirical prediction of earthquakes, but also for the testing and development of hypotheses that further our understanding of the processes at work. The earthquake prediction program is basically a program of scientific inquiry, but one which is motivated by social, political, economic, and scientific reasons. It is a pursuit that cannot rely on empirical observations alone nor can it carried out solely on a blackboard or in a laboratory. Experiments must be carried out in the real Earth. 

  19. The October 1992 Parkfield, California, earthquake prediction

    USGS Publications Warehouse

    Langbein, J.

    1992-01-01

    A magnitude 4.7 earthquake occurred near Parkfield, California, on October 20, 992, at 05:28 UTC (October 19 at 10:28 p.m. local or Pacific Daylight Time).This moderate shock, interpreted as the potential foreshock of a damaging earthquake on the San Andreas fault, triggered long-standing federal, state and local government plans to issue a public warning of an imminent magnitude 6 earthquake near Parkfield. Although the predicted earthquake did not take place, sophisticated suites of instruments deployed as part of the Parkfield Earthquake Prediction Experiment recorded valuable data associated with an unusual series of events. this article describes the geological aspects of these events, which occurred near Parkfield in October 1992. The accompnaying article, an edited version of a press conference b Richard Andrews, the Director of the California Office of Emergency Service (OES), describes governmental response to the prediction.   

  20. Predictive validity of the Short-Term Assessment of Risk and Treatability (START) for multiple adverse outcomes: The effect of diagnosis.

    PubMed

    Marriott, Rebecca; O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L

    2017-10-01

    The Short-Term Assessment of Risk and Treatability (START) assists risk assessment for seven risk outcomes based on scoring of risk and protective factors and assignment of clinically-informed risk levels. Its predictive validity for violence and self-harm has been established in males with schizophrenia, but accuracy across pathologically diverse samples is unknown. Routine START assessments and 3-month risk outcome data of N = 527 adult, inpatients in a UK secure mental health facility were collected. The sample was divided into diagnostic groups; predictive validity was established using receiver operating characteristics regression (rocreg) analysis in which potential covariates were controlled. In most single-diagnosis groups START risk factors ('vulnerabilities'), protective factors ('strengths'), and clinically-informed estimates predicted multiple risk outcomes with effect sizes similar to previous research. Self-harm was not predicted among patients with an organic diagnosis. The START risk estimates predicted physical aggression in all diagnostic groups, and verbal aggression, self-harm and self-neglect in most diagnostic groups. The START can assist assessment of aggressive, self-harm, and self-neglect across a range of diagnostic groups. Further research with larger sample sizes of those with multiple diagnoses is required. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Prediction of long-term cumulative incidences based on short-term parametric model for competing risks: application in early breast cancer.

    PubMed

    Cabarrou, B; Belin, L; Somda, S M; Falcou, M C; Pierga, J Y; Kirova, Y; Delord, J P; Asselain, B; Filleron, T

    2016-04-01

    Use of parametric statistical models can be a solution to reduce the follow-up period time required to estimate long-term survival. Mould and Boag were the first to use the lognormal model. Competing risks methodology seems more suitable when a particular event type is of interest than classical survival analysis. The objective was to evaluate the ability of the Jeong and Fine model to predict long-term cumulative incidence. Survival data recorded by Institut Curie (Paris) from 4761 breast cancer patients treated and followed between 1981 and 2013 were used. Long-term cumulative incidence rates predicted by the model using short-term follow-up data were compared to non-parametric estimation using complete follow-up data. 20- or 25-year cumulative incidence rates for loco-regional recurrence and distant metastasis predicted by the model using a maximum of 10 years of follow-up data had a maximum difference of around 6 % compared to non-parametric estimation. Prediction rates were underestimated for the third and composite event (contralateral or second cancer or death). Predictive ability of Jeong and Fine model on breast cancer data was generally good considering the short follow-up period time used for the estimation especially when a proportion of patient did not experience loco-regional recurrence or distant metastasis.

  2. Near-field strain observations of the October 2013 Ruisui, Taiwan, earthquake: source parameters and limits of very short-term strain detection

    NASA Astrophysics Data System (ADS)

    Canitano, Alexandre; Hsu, Ya-Ju; Lee, Hsin-Ming; Linde, Alan T.; Sacks, Selwyn

    2015-08-01

    Volumetric strain changes associated with the October 2013 M w 6.2 Ruisui earthquake were recorded by a network made up with four borehole Sacks-Evertson dilatometers in eastern Taiwan. These instruments are located within 25-30 km of the seismic source providing also high-resolution near-field observations. Co-seismic offsets larger than a few 102 n ɛ were seen by most of the sensors. We relocated the 30 km × 30 km fault plane through a grid-search approach. The inferred fault parameters (217°, 48°, 49°) are in reasonable agreement with those resulting from the inversions of long-period seismic waves (209°, 59°, 50°) as well as from GPS data inversion (200°, 45°, 42°). Moreover, analysis of the 100-Hz sampling data 10 s before seismic radiations indicate no pre-seismic strain change emergent from the instrumental noise level (from 10 -2 to 10 -1 n ɛ). Such an observation sets limits on any precursory change in a nucleation area, taken to have dimensions of about 250-300 m, seconds before the mainshock. Thus, the upper limit of any pre-seismic moment is about 10 -5 % of the total seismic moment of the Ruisui earthquake.

  3. Localization of intermediate-term earthquake prediction

    NASA Astrophysics Data System (ADS)

    Kossobokov, V. G.; Keilis-Borok, V. I.; Smith, S. W.

    1990-11-01

    Relative seismic quiescence within a region which has already been diagnosed as having entered a "Time of Increased Probability" (TIP) for the occurrence of a strong earthquake can be used to refine the locality in which the earthquake may be expected to occur. A simple algorithm with parameters fitted from the data in Northern California preceding the 1980 magnitude 7.0 earthquake offshore from Eureka depicts relative quiescence within the region of a TTP. The procedure was tested, without readaptation of parameters, on 17 other strong earthquake occurrences in North America, Japan, and Eurasia, most of which were in regions for which a TIP had been previously diagnosed. The localization algorithm successfully outlined a region within which the subsequent earthquake occurred for 16 of these 17 strong earthquakes. The area of prediction in each case was reduced significantly, ranging between 7% and 25% of the total area covered by the TIP.

  4. Maternal serum calponin 1 level as a biomarker for the short-term prediction of preterm birth in women with threatened preterm labor.

    PubMed

    Cetin, Orkun; Karaman, Erbil; Boza, Baris; Cim, Numan; Sahin, Hanım Guler

    2017-01-26

    To assess the utility of maternal serum calponin 1 level in the prediction of delivery within 7 days among pregnancies complicated with threatened preterm labor. Eligible women who presented at 24-34 weeks of gestation with threatened preterm labor underwent sampling for serum calponin 1 level and cervical length measurement. They were followed up until delivery prospectively and the perinatal outcomes of the patients were recorded. Of 73 women included in the study, 36 women delivered within 7 days and 37 women delivered beyond 7 days after admission. The maternal serum calponin 1 level was significantly high in women who delivered within 7 days (p: 0.031). The threshold value of 2 ng/mL for maternal serum calponin 1 predicted delivery within 7 days with 61.1% sensitivity and 62.2 specificity (area under curve, 0.658, confidence interval 0.53-0.79). The general accuracy values for maternal cervical length measurement (≤25 mm), serum calponin 1 level (>2 ng/mL) and the combination of two tests to predict delivery within 7 days was found to be 64.4%, 61.6% and 72.1%, respectively. The maternal serum calponin 1 level may be a useful biomarker in short-term prediction of preterm birth among pregnancies complicated with threatened preterm labor, in addition to cervical length measurement.

  5. Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.; Molthan, Andrew L.; Zavodsky, Bradley; Case, Jonathan L.; LaFontaine, Frank J.

    2010-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPo

  6. Correlation of the Virological Response to Short-Term Maraviroc Monotherapy with Standard and Deep-Sequencing-Based Genotypic Tropism Prediction Methods

    PubMed Central

    Gonzalez-Serna, A.; McGovern, R. A.; Harrigan, P. R.; Vidal, F.; Poon, A. F. Y.; Ferrando-Martinez, S.; Abad, M. A.; Genebat, M.; Leal, M.

    2012-01-01

    Genotypic tropism testing methods are emerging as the first step before prescription of the CCR5 antagonist maraviroc (MVC) to HIV-infected patients in Europe. Studies validating genotypic tests have included other active drugs that could have potentially convoluted the effects of MVC. The maraviroc clinical test (MCT) is an in vivo drug sensitivity test based on the virological response to a short-term exposure to MVC monotherapy. Thus, our aim was to compare the results of genotypic tropism testing methods with the short-term virological response to MVC monotherapy. A virological response in the MCT was defined as a ≥1-log10 decrease in HIV RNA or undetectability after 8 days of drug exposure. Seventy-three patients undergoing the MCT were included in this study. We used both standard genotypic methods (n = 73) and deep sequencing (n = 27) on MCT samples at baseline. For the standard methods, the most widely used genotypic algorithms for analyzing the V3 loop sequence, geno2pheno and PSSM, were used. For deep sequencing, the geno2pheno algorithm was used with a false-positive rate cutoff of 3.5. The discordance rates between the standard genotypic methods and the virological response were approximately 20% (including mostly patients without a virological response). Interestingly, these discordance rates were similar to that obtained from deep sequencing (18.5%). The discordance rates between the genotypic methods (tropism assays predictive of the use of the CCR5 coreceptor) and the MCT (in vivo MVC sensitivity assay) indicate that the algorithms used by genotypic methods are still not sufficiently optimized. PMID:22143533

  7. Projected Applications of a ``Climate in a Box'' Computing System at the NASA Short-term Prediction Research and Transition (SPoRT) Center

    NASA Astrophysics Data System (ADS)

    Jedlovec, G.; Molthan, A.; Zavodsky, B.; Case, J.; Lafontaine, F.

    2010-12-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to “Climate in a Box” systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the “Climate in a Box” system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA’s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the “Climate in a Box” system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed

  8. Nutritional parameters predicting pressure ulcers and short-term mortality in patients with minimal conscious state as a result of traumatic and non-traumatic acquired brain injury.

    PubMed

    Montalcini, Tiziana; Moraca, Marta; Ferro, Yvelise; Romeo, Stefano; Serra, Sebastiano; Raso, Maria Girolama; Rossi, Francesco; Sannita, Walter G; Dolce, Giuliano; Pujia, Arturo

    2015-09-17

    The association between malnutrition and worse outcomes as pressure ulcers and mortality is well established in a variety of setting. Currently none investigation was conducted in patients with long-term consequences of the acquired brain injury in which recovery from brain injury could be influenced by secondary complications. The aim of this study was to investigate the association between various nutritional status parameters (in particular albumin) and pressure ulcers formation and short-term mortality in minimal conscious state patients. In this prospective, observational study of 5-months duration, a 30 patients sample admitted to a Neurological Institute was considered. All patients underwent a complete medical examination. Anthropometric parameters like mid-arm circumference and mid-arm muscle circumference and nutritional parameters as serum albumin and blood hemoglobin concentration were assessed. At univariate and logistic regression analysis, mid-arm circumference (p = 0.04; beta = -0.89), mid-arm muscle circumference (p = 0.050; beta = -1.29), hemoglobin (p = 0.04, beta -1.1) and albumin (p = 0.04, beta -7.91) were inversely associated with pressure ulcers. The area under the ROC curve for albumin to predict sores was 0.76 (p = 0.02) and mortality was 0.83 (p = 0.03). Patient with lower albumin had significantly higher short-term mortality than those with higher serum albumin (p = 0.03; χ(2) test = 6.47). Albumin, haemoglobin and mid-arm circumference are inversely associated with pressure ulcers. Albumin is a prognostic index in MCS patients. Since albumin and haemoglobin could be affected by a variety of factors, this association suggests to optimize nutrition and investigate on other mechanism leading to mortality and pressure ulcers.

  9. Foreshocks and earthquake prediction: recent results from Greece experience

    NASA Astrophysics Data System (ADS)

    Papadopoulos, G. A.; Daskalaki, E.; Minadakis, G.; Orfanogiannaki, K.

    2009-04-01

    Foreshock activity has been proposed since 60's as one of the most potential tools for the short-term prediction of the mainshock. However, the usually low earthquake detectability of the seismic monitoring systems makes it difficult to identify significant foreshock seismicity patterns in near real-time conditions. The gradual improvement of the monitoring systems in the last years makes it possible to detect more reliably the precursory nature of the foreshock activity. This is exactly the case of Greece which is characterized by the highest seismicity in the western Eurasia. We use data from the routine Greek seismicity catalogue of the time interval 1985-2008 and identify a posteriori foreshock activity occurring before strong earthquakes of Ms ≥ 5.5. The criteria to identify significant foreshock activity includes the next: time window up to 1 year before the strong earthquake, space window no more that 50 km from the epicenter of the strong earthquake, increase of the seismicity rate in the particular space-time window at a significance level of at least 95% with respect to the background seismicity rate in the same area. The results indicate that at least of about 50% of the strong earthquakes were preceded by significant foreshock activity. However, further examination of the records in particular seismograph stations of the national Greek seismograph system showed that foreshock activity is not always evident in the routine seismicity catalogue because of reasons related to the detection capabilities of the system. We propose the systematic, automatic monitoring of the daily seismicity with the purpose to identify in near real-time foreshock activity. We demonstrate the algorithm FORMA which is designed to perform such an automatic detection.

  10. Short-Term Surveillance of Cytokines and C-Reactive Protein Cannot Predict Efficacy of Fecal Microbiota Transplantation for Ulcerative Colitis.

    PubMed

    Zhang, Ting; Cui, Bota; Li, Pan; He, Zhi; Long, Chuyan; Wei, Lu; Peng, Zhaoyuan; Ji, Guozhong; Zhang, Faming

    2016-01-01

    There were no reports on predicting long-term efficacy of fecal microbiota transplantation (FMT) for ulcerative colitis (UC). This study aimed to detect short-term changes of cytokines and C-reactive protein (CRP) in patients with UC undergoing FMT, and to evaluate the predictive value of CRP and cytokines for the long-term efficacy of FMT. Nineteen patients with moderate to severe UC (Mayo score ≥ 6) were treated with single fresh FMT through mid-gut. Serum samples were collected before and three days post-FMT. Clinical responses were evaluated by a minimum follow-up of three months. Patients with clinical improvement and remission at the assessment point of three-month were included as response group, while patients without clinical improvement or remission were included as non-response group. Serum concentrations of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-10, IL-11, IL-17A, IFN-γ, TNF, TNFR-1, TNFR-2, MCP-1, G-CSF, GM-CSF) and CRP were assayed to predict the clinical response of FMT. In total, 10.5% (2/19) of patients achieved clinical remission and 47.4% (9/19) achieved clinical improvement (Response group, including clinical remission and clinical improvement), 42.1% (8/19) failed to benefit from FMT (Non-response group). In both Response group and Non-response group, the level of CRP at three days after FMT didn't show significant decrease compared with that before FMT (p>0.05). However, in Response group, CRP level at three months after FMT decreased significantly than that before FMT (p<0.05). Compared with healthy controls (n = 9), patients with UC showed a higher baseline level of serum IL-6, TNFR-2 and G-CSF, and a lower level of IL-2 and IL-4 (p<0.05). In both Response group and Non-response group, none of the eleven detectable cytokines showed a significant difference between the value at three days after FMT and that before FMT (p>0.05). Patients with moderate to severe UC presented a complex disorder of cytokines. However, the efficacy of FMT for

  11. Short-Term Surveillance of Cytokines and C-Reactive Protein Cannot Predict Efficacy of Fecal Microbiota Transplantation for Ulcerative Colitis

    PubMed Central

    Li, Pan; He, Zhi; Long, Chuyan; Wei, Lu; Peng, Zhaoyuan; Ji, Guozhong; Zhang, Faming

    2016-01-01

    Objective There were no reports on predicting long-term efficacy of fecal microbiota transplantation (FMT) for ulcerative colitis (UC). This study aimed to detect short-term changes of cytokines and C-reactive protein (CRP) in patients with UC undergoing FMT, and to evaluate the predictive value of CRP and cytokines for the long-term efficacy of FMT. Methods Nineteen patients with moderate to severe UC (Mayo score ≥ 6) were treated with single fresh FMT through mid-gut. Serum samples were collected before and three days post-FMT. Clinical responses were evaluated by a minimum follow-up of three months. Patients with clinical improvement and remission at the assessment point of three-month were included as response group, while patients without clinical improvement or remission were included as non-response group. Serum concentrations of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-10, IL-11, IL-17A, IFN-γ, TNF, TNFR-1, TNFR-2, MCP-1, G-CSF, GM-CSF) and CRP were assayed to predict the clinical response of FMT. Results In total, 10.5% (2/19) of patients achieved clinical remission and 47.4% (9/19) achieved clinical improvement (Response group, including clinical remission and clinical improvement), 42.1% (8/19) failed to benefit from FMT (Non-response group). In both Response group and Non-response group, the level of CRP at three days after FMT didn’t show significant decrease compared with that before FMT (p>0.05). However, in Response group, CRP level at three months after FMT decreased significantly than that before FMT (p<0.05). Compared with healthy controls (n = 9), patients with UC showed a higher baseline level of serum IL-6, TNFR-2 and G-CSF, and a lower level of IL-2 and IL-4 (p<0.05). In both Response group and Non-response group, none of the eleven detectable cytokines showed a significant difference between the value at three days after FMT and that before FMT (p>0.05). Conclusions Patients with moderate to severe UC presented a complex disorder of

  12. A short-term predictor of satellite-observed fire activity in the North American boreal forest: Toward improving the prediction of smoke emissions

    NASA Astrophysics Data System (ADS)

    Peterson, David; Hyer, Edward; Wang, Jun

    2013-06-01

    A statistical model, based on numerical weather prediction (NWP), is developed to predict the subsequent day's satellite observations of fire activity in the North American boreal forest during the fire season (24-h forecast). In conjunction with the six components of the Canadian Forest Fire Danger Rating System and other NWP outputs, fire data from the MODerate Resolution Imaging Spectroradiometer (MODIS) and the Geostationary Operational Environmental Satellites (GOES) are used to examine the meteorological separability between the largest fire growth and decay events, with a focus on central Alaska during the large fire season of 2004. This combined information is analyzed in three steps including a maximum likelihood classification, multiple regression, and empirical correction, from which the meteorological effects on fire growth and decay are statistically established to construct the fire prediction model. Both MODIS and GOES fire observations show that the NWP-based fire prediction model is an improvement over the forecast of persistence commonly used by near-real-time fire emission inventories. Results from an independent test (2005 fire season) show that the root-mean-square error (RMSE) of predicted MODIS fire observations is reduced by 5.2% compared with a persistence forecast. Improvements are strongest (RMSE reduction of 11.4%) for cases with observed decay or extinction of fires. Similar results are obtained from additional independent tests using the 2004 and 2005 GOES satellite fire observations. This study uniquely demonstrates the value and importance of combining NWP data and satellite fire observations to predict biomass-burning emissions, which is a critical step toward producing a global short-term fire prediction model and improving operational forecasts of smoke transport at large spatial scales.

  13. Strong ground motion prediction using virtual earthquakes.

    PubMed

    Denolle, M A; Dunham, E M; Prieto, G A; Beroza, G C

    2014-01-24

    Sedimentary basins increase the damaging effects of earthquakes by trapping and amplifying seismic waves. Simulations of seismic wave propagation in sedimentary basins capture this effect; however, there exists no method to validate these results for earthquakes that have not yet occurred. We present a new approach for ground motion prediction that uses the ambient seismic field. We apply our method to a suite of magnitude 7 scenario earthquakes on the southern San Andreas fault and compare our ground motion predictions with simulations. Both methods find strong amplification and coupling of source and structure effects, but they predict substantially different shaking patterns across the Los Angeles Basin. The virtual earthquake approach provides a new approach for predicting long-period strong ground motion.

  14. Earthquake prediction; new studies yield promising results

    USGS Publications Warehouse

    Robinson, R.

    1974-01-01

    On Agust 3, 1973, a small earthquake (magnitude 2.5) occurred near Blue Mountain Lake in the Adirondack region of northern New York State. This seemingly unimportant event was of great significance, however, because it was predicted. Seismologsits at the Lamont-Doherty geologcal Observatory of Columbia University accurately foretold the time, place, and magnitude of the event. Their prediction was based on certain pre-earthquake processes that are best explained by a hypothesis known as "dilatancy," a concept that has injected new life and direction into the science of earthquake prediction. Although much mroe reserach must be accomplished before we can expect to predict potentially damaging earthquakes with any degree of consistency, results such as this indicate that we are on a promising road. 

  15. Indocyanine green clearance test combined with MELD score in predicting the short-term prognosis of patients with acute liver failure.

    PubMed

    Feng, Hong-Ling; Li, Qian; Wang, Lin; Yuan, Gui-Yu; Cao, Wu-Kui

    2014-06-01

    Acute liver failure (ALF) is an acute severe deterioration of liver function with high mortality. Early and accurate prognostic assessment of patients with ALF is critically important. Although the model for end-stage liver disease (MELD) scores and King's College Hospital (KCH) criteria are well-accepted as predictive tools, their accuracy is unsatisfactory. The indocyanine green (ICG) clearance test (ICGR15, ICG retention rate at the 15 minutes) is a sensitive indicator of liver function. In this study, we investigated the efficacy of the ICGR15 for the short-term prognosis in patients with ALF. We compared the predictive value of ICGR15 with the MELD scores and KCH criteria. Sixty-nine patients who had been diagnosed with ALF were recruited retrospectively. ICGR15 had been performed by ICG pulse spectrophotometry and relevant clinical and laboratory indices were analyzed within 24 hours of diagnosis. In addition, the MELD scores and KCH criteria were calculated. The three-month mortality of all patients was 47.83%. Age, serum total bilirubin and creatinine concentrations, international normalized ratio for prothrombin time, ICGR15, MELD scores and KCH criteria differed significantly between surviving and deceased patients. A positive correlation was observed between ICGR15 and MELD scores (r=0.328, P=0.006). The ICGR15-MELD model, Logit(P)=0.096XICGR15+0.174XMELD score-9.346, was constructed by logistic regression analysis. The area under the receiver operating characteristic curve was 0.855. When set the cut-off point to -0.4684, the sensitivity was 87.90% and specificity, 72.20%. The area under the receiver operating characteristic curve of the ICGR15-MELD model (0.855) was significantly higher than that of the ICGR15 (0.793), MELD scores (0.776) and KCH criteria (0.659). Based on this cut-off value, the patients were divided into two groups. The mortality was 74.36% in the first group (ICGR15-MELD≥-0.4686) and 13.33% in the second group (ICGR15-MELD<-0

  16. The NASA Short-term Prediction Research and Transition (SPoRT) Center: A Collaborative Model for Accelerating Research into Operations

    NASA Technical Reports Server (NTRS)

    Goodman, S. J.; Lapenta, W.; Jedlovec, G.; Dodge, J.; Bradshaw, T.

    2003-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama was created to accelerate the infusion of NASA earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The principal focus of experimental products is on the regional scale with an emphasis on forecast improvements on a time scale of 0-24 hours. The SPoRT Center research is aligned with the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues ranging from convective initiation to 24-hr quantitative precipitation forecasting. The SPoRT Center, together with its other interagency partners, universities, and the NASA/NOAA Joint Center for Satellite Data Assimilation, provides a means and a process to effectively transition NASA Earth Science Enterprise observations and technology to National Weather Service operations and decision makers at both the global/national and regional scales. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future.

  17. Prenatal maternal cortisol measures predict learning and short-term memory performance in 3- but not 5-month-old infants.

    PubMed

    Thompson, Laura A; Morgan, Gin; Unger, Cynthia A; Covey, LeeAnna A

    2017-09-01

    Little is known about relations between maternal prenatal stress and specific cognitive processes-learning and memory-in infants. A modified crib-mobile task was employed in a longitudinal design to test relations between maternal prenatal cortisol, prenatal subjective stress and anxiety, psychosocial variables, and learning and memory in 3- and 5-month-old infants. Results revealed that maternal prenatal cortisol was affected by particular psychosocial variables (e.g., maternal age, whether or not the infant's grandmother provided childcare, financial status), but was unrelated to measures of maternal depression, anxiety, and stress. Although maternal prenatal cortisol was not predictive of learning or memory performance in 5-month-old infants, higher levels of basal maternal cortisol and reduced prenatal cortisol response was predictive of some learning and short-term memory measures in 3-month-old infants. These results suggest an influence of maternal neuroendocrine functioning on fetal neurological development, and the importance of separate examination of subjective and biological measures of stress. © 2017 Wiley Periodicals, Inc.

  18. The NASA Short-term Prediction Research and Transition (SPoRT) Center: A Collaborative Model for Accelerating Research into Operations

    NASA Technical Reports Server (NTRS)

    Goodman, S. J.; Lapenta, W.; Jedlovec, G.; Dodge, J.; Bradshaw, T.

    2003-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama was created to accelerate the infusion of NASA earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The principal focus of experimental products is on the regional scale with an emphasis on forecast improvements on a time scale of 0-24 hours. The SPoRT Center research is aligned with the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues ranging from convective initiation to 24-hr quantitative precipitation forecasting. The SPoRT Center, together with its other interagency partners, universities, and the NASA/NOAA Joint Center for Satellite Data Assimilation, provides a means and a process to effectively transition NASA Earth Science Enterprise observations and technology to National Weather Service operations and decision makers at both the global/national and regional scales. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future.

  19. Short term response is predictive of long term response to acetylcholinesterase inhibitors in Alzheimer’s disease: A starting point to explore Bayesian approximation in clinical practice

    PubMed Central

    Rota, Eugenia; Ferrero, Patrizia; Ursone, Rita; Migliaretti, Giuseppe

    2007-01-01

    This study was aimed at identifying, in 203 patients with Alzheimer's disease followed during long-term treatment with Acetylcholinesterase inhibitors (ChEIs), the predictive factors of the clinical response among cognition (MMSE), functioning (BADL and IADL) measures and age and gender at the baseline (T0). The ANCOVA test showed a significant association between MMSE scores at time T0 and T3, and the variation T9 to T0, T15 to T0 and T21 to T0 of the MMSE scores, using also gender, age and drug as covariates. The significance was higher for the patients affected by mild dementia. Regarding functional activities, a significant relationship was detected, by the ANCOVA test, only between the scores at T3 and the variation T15 to T0 for BADL, and the variation T9 to T0, T15 to T0 for IADL, respectively. Our results confirm, in a real world setting, that ChEIs provide long-term cognitive benefit, which is correlated to, and predictable by, the short-term response (within the third month) as well as the cognitive status (evaluated by means of the MMSE) at the beginning of the treatment. These factors should be the basis of any cost/effectiveness algorithm in health economic decision models. PMID:18188418

  20. Short-term effects of medetomidine on photosynthesis and protein synthesis in periphyton, epipsammon and plankton communities in relation to predicted environmental concentrations.

    PubMed

    Ohlauson, Cecilia; Eriksson, Karl Martin; Blanck, Hans

    2012-01-01

    Medetomidine is a new antifouling substance, highly effective against barnacles. As part of a thorough ecotoxicological evaluation of medetomidine, its short-term effects on algal and bacterial communities were investigated and environmental concentrations were predicted with the MAMPEC model. Photosynthesis and bacterial protein synthesis for three marine communities, viz. periphyton, epipsammon and plankton were used as effect indicators, and compared with the predicted environmental concentrations (PECs). The plankton community showed a significant decrease in photosynthetic activity of 16% at 2 mg l⁻¹ of medetomidine, which was the only significant effect observed. PECs were estimated for a harbor, shipping lane and marina environment using three different model scenarios (MAMPEC default, Baltic and OECD scenarios). The highest PEC of 57 ng l⁻¹, generated for a marina with the Baltic scenario, was at least 10,000-fold lower than the concentration that significantly decreased photosynthetic activity. It is concluded that medetomidine does not cause any acute toxic effects on bacterial protein synthesis and only small acute effects on photosynthesis at high concentrations in marine microbial communities. It is also concluded that the hazard from medetomidine on these processes is low since the effect levels are much lower than the highest PEC.

  1. Baseline Magnetic Resonance Imaging of the Optic Nerve Provides Limited Predictive Information on Short-Term Recovery after Acute Optic Neuritis

    PubMed Central

    Berg, Sebastian; Kaschka, Iris; Utz, Kathrin S.; Huhn, Konstantin; Lämmer, Alexandra; Lämmer, Robert; Waschbisch, Anne; Kloska, Stephan; Lee, De-Hyung; Doerfler, Arnd; Linker, Ralf A.

    2015-01-01

    Background In acute optic neuritis, magnetic resonance imaging (MRI) may help to confirm the diagnosis as well as to exclude alternative diagnoses. Yet, little is known on the value of optic nerve imaging for predicting clinical symptoms or therapeutic outcome. Purpose To evaluate the benefit of optic nerve MRI for predicting response to appropriate therapy and recovery of visual acuity. Methods Clinical data as well as visual evoked potentials (VEP) and MRI results of 104 patients, who were treated at the Department of Neurology with clinically definite optic neuritis between December 2010 and September 2012 were retrospectively reviewed including a follow up within 14 days. Results Both length of the Gd enhancing lesion (r = -0.38; p = 0.001) and the T2 lesion (r = -0.25; p = 0.03) of the optic nerve in acute optic neuritis showed a medium correlation with visual acuity after treatment. Although visual acuity pre-treatment was little but nonsignificantly lower if Gd enhancement of the optic nerve was detected via orbital MRI, improvement of visual acuity after adequate therapy was significantly better (0.40 vs. 0.24; p = 0.04). Intraorbitally located Gd enhancing lesions were associated with worse visual improvement compared to canalicular, intracranial and chiasmal lesions (0.35 vs. 0.54; p = 0.02). Conclusion Orbital MRI is a broadly available, valuable tool for predicting the improvement of visual function. While the accurate individual prediction of long-term outcomes after appropriate therapy still remains difficult, lesion length of Gd enhancement and T2 lesion contribute to its prediction and a better short-term visual outcome may be associated with detection and localization of Gd enhancement along the optic nerve. PMID:25635863

  2. Mid-regional pro-adrenomedullin and copeptin to predict short-term prognosis of COPD exacerbations: a multicenter prospective blinded study

    PubMed Central

    Dres, Martin; Hausfater, Pierre; Foissac, Frantz; Bernard, Maguy; Joly, Luc-Marie; Sebbane, Mustapha; Philippon, Anne-Laure; Gil-Jardiné, Cédric; Schmidt, Jeannot; Maignan, Maxime; Treluyer, Jean-Marc; Roche, Nicolas

    2017-01-01

    Background Exacerbations of COPD (ECOPD) are a frequent cause of emergency room (ER) visits. Predictors of early outcome could help clinicians in orientation decisions. In the current study, we investigated whether mid-regional pro-adrenomedullin (MR-proADM) and copeptin, in addition to clinical evaluation, could predict short-term outcomes. Patients and methods This prospective blinded observational study was conducted in 20 French centers. Patients admitted to the ER for an ECOPD were considered for inclusion. A clinical risk score was calculated, and MR-proADM and copeptin levels were determined from a venous blood sample. The composite primary end point comprised 30-day death or transfer to the intensive care unit or a new ER visit. Results A total of 379 patients were enrolled in the study, of whom 277 were eventually investigated for the primary end point that occurred in 66 (24%) patients. In those patients, the median (interquartile range [IQR]) MR-proADM level was 1.02 nmol/L (0.77–1.48) versus 0.83 nmol/L (0.63–1.07) in patients who did not meet the primary end point (P=0.0009). In contrast, copeptin levels were similar in patients who met or did not meet the primary end point (P=0.23). MR-proADM levels increased with increasing clinical risk score category: 0.74 nmol/L (0.57–0.89), 0.83 nmol/L (0.62–1.12) and 0.95 nmol/L (0.75–1.29) for the low-, intermediate- and high-risk categories, respectively (P<0.001). MR-proADM was independently associated with the primary end point (odds ratio, 1.65; 95% confidence interval [CI], 1.10–2.48; P=0.015). MR-proADM predicted the occurrence of primary end point with a sensitivity of 46% (95% CI, 33%–58%) and a specificity of 79% (95% CI, 74–84). Conclusion MR-proADM but not copeptin was significantly associated with outcomes at 30 days, even after adjustment for clinical risk category. Overall, MR-proADM, alone or combined with the clinical risk score, was a moderate strong predictor of short-term

  3. Comparison Between Soluble ST2 and High-Sensitivity Troponin I in Predicting Short-Term Mortality for Patients Presenting to the Emergency Department With Chest Pain

    PubMed Central

    Marino, Rossella; Magrini, Laura; Orsini, Francesca; Russo, Veronica; Cardelli, Patrizia; Salerno, Gerardo; Hur, Mina

    2017-01-01

    Background High-sensitivity cardiac troponin I (hs-cTnI) and the soluble isoform of suppression of tumorigenicity 2 (sST2) are useful prognostic biomarkers in acute coronary syndrome (ACS). The aim of this study was to test the short term prognostic value of sST2 compared with hs-cTnI in patients with chest pain. Methods Assays for hs-cTnI and sST2 were performed in 157 patients admitted to the Emergency Department (ED) for chest pain at arrival. In-hospital and 30-day follow-up mortalities were assessed. Results The incidence of ACS was 37%; 33 patients were diagnosed with ST elevation myocardial infarction (STEMI), and 25 were diagnosed with non-ST elevation myocardial infarction (NSTEMI). Compared with the no acute coronary syndrome (NO ACS) group, the median level of hs-cTnI was higher in ACS patients: 7.22 (5.24-14) pg/mL vs 68 (15.33-163.50) pg/mL (P<0.0001). In all patients, the sST2 level at arrival showed higher independent predictive power than hs-cTnI (odds ratio [OR] 20.13, P<0.0001 and OR 2.61, P<0.0008, respectively). sST2 at ED arrival showed a greater prognostic value for cardiovascular events in STEMI (area under the curve [AUC] 0.80, P<0.001) than NSTEMI patients (AUC 0.72, P<0.05). Overall, 51% of the STEMI patients with an sST2 value>35 ng/mL at ED arrival died during the 30-day follow-up. Conclusions sST2 has a greater prognostic value for 30-day cardiac mortality after discharge in patients presenting to the ED for chest pain compared with hs-cTnI. In STEMI patients, an sST2 value >35 ng/mL at ED arrival showed the highest predictive power for short-term mortality. PMID:28029000

  4. Possibility of Earthquake-prediction by analyzing VLF signals

    NASA Astrophysics Data System (ADS)

    Ray, Suman; Chakrabarti, Sandip Kumar; Sasmal, Sudipta

    2016-07-01

    Prediction of seismic events is one of the most challenging jobs for the scientific community. Conventional ways for prediction of earthquakes are to monitor crustal structure movements, though this method has not yet yield satisfactory results. Furthermore, this method fails to give any short-term prediction. Recently, it is noticed that prior to any seismic event a huge amount of energy is released which may create disturbances in the lower part of D-layer/E-layer of the ionosphere. This ionospheric disturbance may be used as a precursor of earthquakes. Since VLF radio waves propagate inside the wave-guide formed by lower ionosphere and Earth's surface, this signal may be used to identify ionospheric disturbances due to seismic activity. We have analyzed VLF signals to find out the correlations, if any, between the VLF signal anomalies and seismic activities. We have done both the case by case study and also the statistical analysis using a whole year data. In both the methods we found that the night time amplitude of VLF signals fluctuated anomalously three days before the seismic events. Also we found that the terminator time of the VLF signals shifted anomalously towards night time before few days of any major seismic events. We calculate the D-layer preparation time and D-layer disappearance time from the VLF signals. We have observed that this D-layer preparation time and D-layer disappearance time become anomalously high 1-2 days before seismic events. Also we found some strong evidences which indicate that it may possible to predict the location of epicenters of earthquakes in future by analyzing VLF signals for multiple propagation paths.

  5. Pilot study on the short-term prediction of symptoms in children with hay fever monitored with e-Health technology.

    PubMed

    Costa, C; Menesatti, P; Brighetti, M A; Travaglini, A; Rimatori, V; Di Rienzo Businco, A; Pelosi, S; Bianchi, A; Matricardi, P M; Tripodi, S

    2014-11-01

    Forecasting symptoms of pollen-related allergic rhinoconjunctivitis at the level of individual patients would be useful to improve disease control and plan pharmacological intervention. Information Technology nowadays facilitates a more efficient and easier monitoring of patients with chronic diseases. We aimed this study at testing the efficiency of a model to short-term forecast symptoms of pollen-AR at the "individual" patient level. We analysed the data prospectively acquired from a group of 21 Italian children affected by pollen-related allergic rhinoconjunctivitis and recorded their symptoms and medication "Average Combined Score" (ACS) on a daily basis during April-June 2010-2011 through an informatics platform (Allergymonitor™). The dataset used for prediction included 15 variables in four categories: (A) date, (B) meteo-climatic, (C) atmospheric concentration of 5 pollen taxa, and (D) intensity of the patient's IgE sensitization. A Partial Least Squares Discriminant Analysis approach was used in order to predict ACS values above a fixed threshold value (0.5). The best performing predicting model correctly classified 77.8% ± 10.3% and 75.5% ± 13.2% of the recorded days in the model and test years, respectively. In this model, 9/21 patients showed ≥ 80% correct classification of the recorded days in both years. A better performance was associated with a higher degree of patient's atopic sensitization and a time lag > 1. Symptom forecasts of seasonal allergic rhinitis are possible in highly polysensitised patients in areas with complex pollen exposure. However, only predictive models tailored to the individual patient's allergic susceptibility are accurate enough. Multicenter studies in large population samples adopting the same acquisition data system on smart phones are now needed to confirm this encouraging outcome.

  6. Short-term improvement in insomnia symptoms predicts long-term improvements in sleep, pain, and fatigue in older adults with comorbid osteoarthritis and insomnia.

    PubMed

    Vitiello, Michael V; McCurry, Susan M; Shortreed, Susan M; Baker, Laura D; Rybarczyk, Bruce D; Keefe, Francis J; Von Korff, Michael

    2014-08-01

    In a primary care population of 367 older adults (aged ⩾60 years) with osteoarthritis (OA) pain and insomnia, we examined the relationship between short-term improvement in sleep and long-term sleep, pain, and fatigue outcomes through secondary analyses of randomized controlled trial data. Study participants, regardless of experimental treatment received, were classified either as improvers (⩾30% baseline to 2-month reduction on the Insomnia Severity Index [ISI]) or as nonimprovers. After controlling for treatment arm and potential confounders, improvers showed significant, sustained improvements across 18 months compared with nonimprovers in pain severity (P<0.001, adjusted mean difference=-0.51 [95% CI: -0.80, -0.21), arthritis symptoms (P<0.001, 0.63 [0.26, 1.00]), and fear avoidance (P=0.009, -2.27 [-3.95, -0.58]) but not in catastrophizing or depression. Improvers also showed significant, sustained improvements in ISI (P<0.001, -3.03 [-3.74, -2.32]), Pittsburgh Sleep Quality Index Total (P<0.001, -1.45 [-1.97, -0.93]) and general sleep quality (P<0.001, -0.28 [-0.39, -0.16]) scores, Flinders Fatigue Scale (P<0.001, -1.99 [-3.01, -0.98]), and Dysfunctional Beliefs About Sleep Scale (P=0.037, -2.44 [-4.74, -0.15]), but no improvements on the Functional Outcomes of Sleep Questionnaire or the Epworth Sleepiness Scale. We conclude that short-term (2-month) improvements in sleep predicted long-term (9- and 18-month) improvements for multiple measures of sleep, chronic pain, and fatigue. These improvements were not attributable to nonspecific benefits for psychological well-being, such as reduced depression. These findings are consistent with benefits of improved sleep for chronic pain and fatigue among older persons with osteoarthritis pain and comorbid insomnia if robust improvements in sleep are achieved and sustained. ClinicalTrials.gov Identifier: NCT01142349. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All

  7. Predicting short-term outcome in well-being following suicidal behaviour: the conjoint effects of social perfectionism and positive future thinking.

    PubMed

    O'Connor, Rory C; Whyte, Marie-Claire; Fraser, Louisa; Masterton, George; Miles, Jeremy; MacHale, Siobhan

    2007-07-01

    This study investigated an integrative, psychological model of suicidality involving the relationship between perfectionism and future thinking to predict short-term outcome in well-being following a suicidal episode. Two hundred and sixty-seven adults hospitalized following a self-harm episode completed a range of clinical and psychological measures in hospital and were followed up approximately two months after discharge. Hierarchical regression analyses confirmed that, among the suicidal self-harmers who had a history of repetitive self-harm (n=65), outcome among low social perfectionists changed as a function of positive future thinking such that outcome was better for those high on positive thoughts compared with those low on positive future thoughts. There was no such positive change in outcome among the high social perfectionists. There were also no significant interactive effects evident among the non-repetitive self-harmers (n=61). These findings extend recent research to suggest that socially prescribed perfectionism and positive future thinking (but not negative future thinking) are implicated in outcome following repetitive suicidality. Implications for theory and clinical practice are discussed.

  8. The Prediction of Long-Term Coating Performance from Short-Term Electrochemical Data. Part 2; Comparison of Electrochemical Data to Field Exposure Results for Coatings on Steel

    NASA Technical Reports Server (NTRS)

    Contu, F.; Taylor, S. R.; Calle, L. M.; Hintze, P. E.; Curran, J. P.; Li, W.

    2009-01-01

    The pace of coatings development is limited by the time required to assess their corrosion protection properties. This study takes a step f orward from Part I in that it correlates the corrosion performance of organic coatings assessed by a series of short-term electrochemical measurement with 18-month beachside exposure results of duplicate pan els. A series of 19 coating systems on A36 steel substrates were test ed in a completely blind study using the damage tolerance test (DTT). In the DTT, a through-film pinhole defect is created, and the electro chemical characteristics of the defect are then monitored over the ne xt 4 to 7 days while immersed in 0.SM NaCl. The open circuit potentia l, anodic potentiostatic polarization tests and electrochemical imped ance spectroscopy were used to study the corrosion behavior of the co ating systems. The beachside exposure tests were conducted at the Ken nedy Space Center according to ASTM D610-01. It was found that for 79 % of the coatings systems examined, the 18 month beachside exposure r esults could be predicted by two independent laboratory tests obtained within 7 days.

  9. G-Protein/β-Arrestin-Linked Fluctuating Network of G-Protein-Coupled Receptors for Predicting Drug Efficacy and Bias Using Short-Term Molecular Dynamics Simulation

    PubMed Central

    Ichikawa, Osamu; Fujimoto, Kazushi; Yamada, Atsushi; Okazaki, Susumu; Yamazaki, Kazuto

    2016-01-01

    The efficacy and bias of signal transduction induced by a drug at a target protein are closely associated with the benefits and side effects of the drug. In particular, partial agonist activity and G-protein/β-arrestin-biased agonist activity for the G-protein-coupled receptor (GPCR) family, the family with the most target proteins of launched drugs, are key issues in drug discovery. However, designing GPCR drugs with appropriate efficacy and bias is challenging because the dynamic mechanism of signal transduction induced by ligand—receptor interactions is complicated. Here, we identified the G-protein/β-arrestin-linked fluctuating network, which initiates large-scale conformational changes, using sub-microsecond molecular dynamics (MD) simulations of the β2-adrenergic receptor (β2AR) with a diverse collection of ligands and correlation analysis of their G protein/β-arrestin efficacy. The G-protein-linked fluctuating network extends from the ligand-binding site to the G-protein-binding site through the connector region, and the β-arrestin-linked fluctuating network consists of the NPxxY motif and adjacent regions. We confirmed that the averaged values of fluctuation in the fluctuating network detected are good quantitative indexes for explaining G protein/β-arrestin efficacy. These results indicate that short-term MD simulation is a practical method to predict the efficacy and bias of any compound for GPCRs. PMID:27187591

  10. The PreViBOSS project: study the short term predictability of the visibility change during the Fog life cycle, from surface and satellite observation

    NASA Astrophysics Data System (ADS)

    Elias, T.; Haeffelin, M.; Ramon, D.; Gomes, L.; Brunet, F.; Vrac, M.; Yiou, P.; Hello, G.; Petithomme, H.

    2010-07-01

    Fog prejudices major activities as transport and Earth observation, by critically reducing atmospheric visibility with no continuity in time and space. Fog is also an essential factor of air quality and climate as it modifies particle properties of the surface atmospheric layer. Complexity, diversity and the fine scale of processes make uncertain by current numerical weather prediction models, not only visibility diagnosis but also fog event prediction. Extensive measurements of atmospheric parameters are made on the SIRTA since 1997 to document physical processes over the atmospheric column, in the Paris suburb area, typical of an environment intermittently under oceanic influence and affected by urban and industrial pollution. The ParisFog field campaign hosted in SIRTA during 6-month in winter 2006-2007 resulted in the deployment of instrumentation specifically dedicated to study physical processes in the fog life cycle: thermodynamical, radiative, dynamical, microphysical processes. Analysis of the measurements provided a preliminary climatology of the episodes of reduced visibility, chronology of processes was delivered by examining time series of measured parameters and a closure study was performed on optical and microphysical properties of particles (aerosols to droplets) during the life cycle of a radiative fog, providing the relative contribution of several particle groups to extinction in clear-sky conditions, in haze and in fog. PreViBOSS is a 3-year project scheduled to start this year. The aim is to improve the short term prediction of changes in atmospheric visibility, at a local scale. It proposes an innovative approach: applying the Generalised Additive Model statistical method to the detailed and extended dataset acquired at SIRTA. This method offers the opportunity to explore non linear relationships between parameters, which are not yet integrated in current numerical models. Emphasis will be put on aerosols and their impact on the fog life

  11. Methodology to predict long-term cancer survival from short-term data using Tobacco Cancer Risk and Absolute Cancer Cure models

    NASA Astrophysics Data System (ADS)

    Mould, R. F.; Lederman, M.; Tai, P.; Wong, J. K. M.

    2002-11-01

    Three parametric statistical models have been fully validated for cancer of the larynx for the prediction of long-term 15, 20 and 25 year cancer-specific survival fractions when short-term follow-up data was available for just 1-2 years after the end of treatment of the last patient. In all groups of cases the treatment period was only 5 years. Three disease stage groups were studied, T1N0, T2N0 and T3N0. The models are the Standard Lognormal (SLN) first proposed by Boag (1949 J. R. Stat. Soc. Series B 11 15-53) but only ever fully validated for cancer of the cervix, Mould and Boag (1975 Br. J. Cancer 32 529-50), and two new models which have been termed Tobacco Cancer Risk (TCR) and Absolute Cancer Cure (ACC). In each, the frequency distribution of survival times of defined groups of cancer deaths is lognormally distributed: larynx only (SLN), larynx and lung (TCR) and all cancers (ACC). All models each have three unknown parameters but it was possible to estimate a value for the lognormal parameter S a priori. By reduction to two unknown parameters the model stability has been improved. The material used to validate the methodology consisted of case histories of 965 patients, all treated during the period 1944-1968 by Dr Manuel Lederman of the Royal Marsden Hospital, London, with follow-up to 1988. This provided a follow-up range of 20- 44 years and enabled predicted long-term survival fractions to be compared with the actual survival fractions, calculated by the Kaplan and Meier (1958 J. Am. Stat. Assoc. 53 457-82) method. The TCR and ACC models are better than the SLN model and for a maximum short-term follow-up of 6 years, the 20 and 25 year survival fractions could be predicted. Therefore the numbers of follow-up years saved are respectively 14 years and 19 years. Clinical trial results using the TCR and ACC models can thus be analysed much earlier than currently possible. Absolute cure from cancer was also studied, using not only the prediction models which

  12. Analytical Conditions for Compact Earthquake Prediction Approaches

    NASA Astrophysics Data System (ADS)

    Sengor, T.

    2009-04-01

    This paper concerns itself with The atmosphere and ionosphere include non-uniform electric charge and current distributions during the earthquake activity. These charges and currents move irregularly when an activity is scheduled for an earthquake at the future. The electromagnetic characteristics of the region over the earth change to domains where irregular transportations of non-uniform electric charges are observed; therefore, the electromagnetism in the plasma, which moves irregularly and contains non-uniform charge distributions, is studied. These cases of charge distributions are called irregular and non-uniform plasmas. It is called the seismo-plasma if irregular and non-uniform plasma defines a real earthquake activity, which will come to truth. Some signals involving the above-mentioned coupling effects generate some analytical conditions giving the predictability of seismic processes [1]-[5]. These conditions will be discussed in this paper. 2 References [1] T. Sengor, "The electromagnetic device optimization modeling of seismo-electromagnetic processes," IUGG Perugia 2007. [2] T. Sengor, "The electromagnetic device optimization modeling of seismo-electromagnetic processes for Marmara Sea earthquakes," EGU 2008. [3] T. Sengor, "On the exact interaction mechanism of electromagnetically generated phenomena with significant earthquakes and the observations related the exact predictions before the significant earthquakes at July 1999-May 2000 period," Helsinki Univ. Tech. Electrom. Lab. Rept. 368, May 2001. [4] T. Sengor, "The Observational Findings Before The Great Earthquakes Of December 2004 And The Mechanism Extraction From Associated Electromagnetic Phenomena," Book of XXVIIIth URSI GA 2005, pp. 191, EGH.9 (01443) and Proceedings 2005 CD, New Delhi, India, Oct. 23-29, 2005. [5] T. Sengor, "The interaction mechanism among electromagnetic phenomena and geophysical-seismic-ionospheric phenomena with extraction for exact earthquake prediction genetics," 10

  13. [Application of the concetrations ratio of soluble receptor tyrosine kinase type 1, and placental growth factor for short-term prediction and diagnosis of preeclampsia].

    PubMed

    Bubeníková, Š; Cíchová, A; Roubalová, L; Durdová, V; Vlk, R

    Bring a comprehensive overview of the available information about applications of the concetration ratio of soluble receptor tyrosine kinase type 1 (sFlt-1), and placental growth factor for short-term prediction and diagnosis of preeclampsia. Overview study. Department of Midwifery, Faculty of Health Sciences, Olomouc; Department of Clinical Biochemistry, University Hospital Olomouc; Department of Obstetrics and Gynecology, University Hospital Olomouc; Department of Obstetrics and Gynecology, 2nd Faculty of Medicine, Charles University in Prague and Motol University Hospital. Analysis of literary sources and databases Ovid, Medline (2001-2016). Preeclampsia is a multisystem disease with not fully understood etiology. This disease occurs in 2-5% of pregnant women. Preeclampsia is one of the main causes of global maternal and perinatal morbidity and mortality. It manifests itself as a newborn hypertension and proteinuria after 20 weeks of pregnancy in previously normotensive women. The only effective treatment is the delivery of the child. Diagnosis of preeclampsia comprises measuring blood pressure and proteinuria. These indicators have low diagnostic sensitivity and specificity. In preeclampsia, there is a decrease of serum levels of placental growth factor (PlGF). Soluble receptor tyrosine kinase type 1 (sFlt-1) is an antagonist of PlGF. Increased levels of sFlt-1 in proportion to the reduced level of PlGF are associated with an increased risk of preeclampsia. The sFlt-1/PlGF ratio can be a better predictive marker in the diagnosis of pre-eclampsia after 20 weeks of gestation.

  14. Ischemia-modified albumin predicts short-term outcome and 1-year mortality in patients attending the emergency department for acute ischemic chest pain.

    PubMed

    Consuegra-Sanchez, Luciano; Bouzas-Mosquera, Alberto; Sinha, Manas K; Collinson, Paul O; Gaze, David C; Kaski, Juan Carlos

    2008-05-01

    The primary study aim was to determine whether ischemia-modified albumin (IMA) predicts adverse outcome in patients attending the emergency department (ED) with acute chest pain. Ischemia-modified albumin is a sensitive marker of myocardial ischemia. However, little is known about its ability to predict outcome in patients presenting to the ED with acute chest pain. We prospectively studied 207 patients who presented to the ED with acute chest pain suggestive of acute coronary syndrome within 3 h of the onset of symptoms. Blood samples for IMA assessment were obtained on admission. We evaluated a 30-day combined end point (cardiac death, myocardial infarction, recurrent angina) and 1-year all-cause mortality. A total of 31 (15%) patients experienced the 30-day composite end point and 16 patients (7.7%) died during the 1-year follow-up. Short-term combined end point (9.6% vs 20.4%, P = 0.03) and 1-year mortality rate (11.7% vs 3.8%, log rank 3.978, P = 0.046) were significantly higher in patients with IMA levels >93.3 U/ml compared to patients with lower IMA. On multivariate analysis, IMA remained an independent predictor of both 30-day combined end point (odds ratio 1.04, 95% confidence interval [CI] 1.01-1.07, P = 0.01) and 1-year mortality (hazard ratio 1.038, 95% CI 1.006-1.070, P = 0.018). Ischemia-modified albumin is an independent predictor of short-and long-term adverse outcomes in patients presenting to the ED with typical acute chest pain.

  15. Development of a short-term irradiance prediction system using post-processing tools on WRF-ARW meteorological forecasts in Spain

    NASA Astrophysics Data System (ADS)

    Rincón, A.; Jorba, O.; Baldasano, J. M.

    2010-09-01

    The increased contribution of solar energy in power generation sources requires an accurate estimation of surface solar irradiance conditioned by geographical, temporal and meteorological conditions. The knowledge of the variability of these factors is essential to estimate the expected energy production and therefore help stabilizing the electricity grid and increase the reliability of available solar energy. The use of numerical meteorological models in combination with statistical post-processing tools may have the potential to satisfy the requirements for short-term forecasting of solar irradiance for up to several days ahead and its application in solar devices. In this contribution, we present an assessment of a short-term irradiance prediction system based on the WRF-ARW mesoscale meteorological model (Skamarock et al., 2005) and several post-processing tools in order to improve the overall skills of the system in an annual simulation of the year 2004 in Spain. The WRF-ARW model is applied with 4 km x 4 km horizontal resolution and 38 vertical layers over the Iberian Peninsula. The hourly model irradiance is evaluated against more than 90 surface stations. The stations are used to assess the temporal and spatial fluctuations and trends of the system evaluating three different post-processes: Model Output Statistics technique (MOS; Glahn and Lowry, 1972), Recursive statistical method (REC; Boi, 2004) and Kalman Filter Predictor (KFP, Bozic, 1994; Roeger et al., 2003). A first evaluation of the system without post-processing tools shows an overestimation of the surface irradiance, due to the lack of atmospheric absorbers attenuation different than clouds not included in the meteorological model. This produces an annual BIAS of 16 W m-2 h-1, annual RMSE of 106 W m-2 h-1 and annual NMAE of 42%. The largest errors are observed in spring and summer, reaching RMSE of 350 W m-2 h-1. Results using Kalman Filter Predictor show a reduction of 8% of RMSE, 83% of BIAS

  16. Microearthquake networks and earthquake prediction

    USGS Publications Warehouse

    Lee, W.H.K.; Steward, S. W.

    1979-01-01

    A microearthquake network is a group of highly sensitive seismographic stations designed primarily to record local earthquakes of magnitudes less than 3. Depending on the application, a microearthquake network will consist of several stations or as many as a few hundred . They are usually classified as either permanent or temporary. In a permanent network, the seismic signal from each is telemetered to a central recording site to cut down on the operating costs and to allow more efficient and up-to-date processing of the data. However, telemetering can restrict the location sites because of the line-of-site requirement for radio transmission or the need for telephone lines. Temporary networks are designed to be extremely portable and completely self-contained so that they can be very quickly deployed. They are most valuable for recording aftershocks of a major earthquake or for studies in remote areas.  

  17. Intermediate- and long-term earthquake prediction.

    PubMed

    Sykes, L R

    1996-04-30

    Progress in long- and intermediate-term earthquake prediction is reviewed emphasizing results from California. Earthquake prediction as a scientific discipline is still in its infancy. Probabilistic estimates that segments of several faults in California will be the sites of large shocks in the next 30 years are now generally accepted and widely used. Several examples are presented of changes in rates of moderate-size earthquakes and seismic moment release on time scales of a few to 30 years that occurred prior to large shocks. A distinction is made between large earthquakes that rupture the entire downdip width of the outer brittle part of the earth's crust and small shocks that do not. Large events occur quasi-periodically in time along a fault segment and happen much more often than predicted from the rates of small shocks along that segment. I am moderately optimistic about improving predictions of large events for time scales of a few to 30 years although little work of that type is currently underway in the United States. Precursory effects, like the changes in stress they reflect, should be examined from a tensorial rather than a scalar perspective. A broad pattern of increased numbers of moderate-size shocks in southern California since 1986 resembles the pattern in the 25 years before the great 1906 earthquake. Since it may be a long-term precursor to a great event on the southern San Andreas fault, that area deserves detailed intensified study.

  18. Intermediate- and long-term earthquake prediction.

    PubMed Central

    Sykes, L R

    1996-01-01

    Progress in long- and intermediate-term earthquake prediction is reviewed emphasizing results from California. Earthquake prediction as a scientific discipline is still in its infancy. Probabilistic estimates that segments of several faults in California will be the sites of large shocks in the next 30 years are now generally accepted and widely used. Several examples are presented of changes in rates of moderate-size earthquakes and seismic moment release on time scales of a few to 30 years that occurred prior to large shocks. A distinction is made between large earthquakes that rupture the entire downdip width of the outer brittle part of the earth's crust and small shocks that do not. Large events occur quasi-periodically in time along a fault segment and happen much more often than predicted from the rates of small shocks along that segment. I am moderately optimistic about improving predictions of large events for time scales of a few to 30 years although little work of that type is currently underway in the United States. Precursory effects, like the changes in stress they reflect, should be examined from a tensorial rather than a scalar perspective. A broad pattern of increased numbers of moderate-size shocks in southern California since 1986 resembles the pattern in the 25 years before the great 1906 earthquake. Since it may be a long-term precursor to a great event on the southern San Andreas fault, that area deserves detailed intensified study. Images Fig. 1 PMID:11607658

  19. Short-term energy outlook: Methodology

    NASA Astrophysics Data System (ADS)

    Cornett, C.; Paxson, D.; Reznek, A. P.; Chu, C.; Sitzer, S.; Gamson, N.; Childress, J. P.; Paul, S.; Weigel, H.; Sutton, S.

    1981-05-01

    Detailed discussions of forecasting methodology and analytical topics concerning short-term energy markets are presented. Major assumptions necessary to make the energy forecasts are also discussed. Supplementary analyses of topics related to short-term energy forecasting are also given. The discussions relate to the forecasts prepared using the short term integrated forecasting system. This set of computer models uses data from various sources to develop energy supply and demand balances. Econmetric models used to predict the demand for petroleum products, natural gas, coal, and electricity are discussed. Price prediction models are also discussed. The role of oil inventories in world oil markets is reviewed. Various relationship between weather patterns and energy consumption are discussed.

  20. Short-term prediction of the foF2 critical frequency in the high latitude ionosphere for DIAS extending services

    NASA Astrophysics Data System (ADS)

    Tsagouri, Ioanna; Belehaki, Anna

    2013-04-01

    Ionospheric forecasting products and services for Europe are provided routinely by the European Digital upper Atmosphere Server, DIAS (http://dias.space.noa.gr). These include alerts and warnings for upcoming ionospheric storm time disturbances as well as single station and regional ionospheric forecasts up to 24 hours ahead for the middle latitude European region. However, in order to meet the users' requirements, it is planned within the Space Situational Awareness Programme of the European Space Agency the extension of the DIAS forecasting services to cover the whole European region, including Scandinavia. To this effect, the Solar Wind driven autoregression model for Ionospheric short-term Forecast (SWIF) will be applied. In the operational mode, SWIF combines historical and real-time ionospheric observations with solar wind parameters obtained in real time at L1 point from ACE spacecraft through the cooperation of an autoregression forecasting algorithm, namely TSAR with an empirical ionospheric storm time model, namely STIM that is triggered by solar wind disturbances detected by STIM's alert detection algorithm. The ionospheric storm time response is then empirically formulated taken into account the latitude and the local time of the observation point at the storm onset. SWIF's prediction efficiency was recently fully documented for the middle latitude ionosphere. As a first step towards the operational implementation of the SWIF for high latitude ionospheric forecasts, the work presented here includes the evaluation of the SWIF's performance over high latitude locations and under disturbed geophysical conditions based on historical data. For this purpose, all available high latitude foF2 observations obtained during a significant number of selected storm events occurred in the previous as well as the current solar cycle are analyzed in respect with the foF2 reference level and the model's predictions. The results verify the validity of STIM's storm alert

  1. Use of Biofeedback Combined With Diet for Treatment of Obstructed Defecation Associated With Paradoxical Puborectalis Contraction (Anismus): Predictive Factors and Short-term Outcome.

    PubMed

    Murad-Regadas, Sthela M; Regadas, Francisco S Pinheiro; Bezerra, Carla C Rocha; de Oliveira, Maura T Coutinho Cajazeiras; Regadas Filho, Francisco S Pinheiro; Rodrigues, Lusmar Veras; Almeida, Saulo Santiago; da Silva Fernandes, Graziela O

    2016-02-01

    Numerous studies have described the use of biofeedback therapy for the treatment of anismus. Success rates vary widely, but few data are available regarding factors predictive of success. Our aim was to evaluate short-term results of biofeedback associated with diet in patients with obstructed defecation because of anismus and to investigate factors that may affect the results. Patients were identified from a single-institution prospectively maintained database. This study was conducted in a tertiary hospital. Consecutive patients who had obstructed defecation associated with anismus and were treated with biofeedback associated with diet were eligible. Each patient underwent anal manometry and/or dynamic anal ultrasound. Patients with anismus and were treated with biofeedback associated with diet. Patients classed as having a satisfactory response to therapy and those classed as having an unsatisfactory response were compared with regard to sex, age, Cleveland Clinic Florida constipation score, functional factors (anal resting and squeeze pressures and reversal of paradoxical puborectalis contraction on manometry), and anatomic factors in women (history of vaginal delivery, number of vaginal deliveries, menopause, hysterectomy, and previous anorectal surgery). A total of 116 patients were included (75 women and 41 men). Overall, 59% were classed as having a satisfactory response (decrease in constipation score, >50%). Patients with satisfactory responses to biofeedback plus diet did not differ from those with unsatisfactory responses with regard to clinical, anatomic, and physiological factors. This was not a randomized controlled trial. Biofeedback combined with diet is a valuable treatment option for patients with obstructed defecation syndrome associated with anismus, and more than half of our patients of both sexes achieved a satisfactory response. Improvement was not related to reversal of paradoxical contraction of puborectalis muscles at manometry. Patient

  2. Potentiation of E-4031-induced torsade de pointes by HMR1556 or ATX-II is not predicted by action potential short-term variability or triangulation

    PubMed Central

    Michael, G; Dempster, J; Kane, K A; Coker, S J

    2007-01-01

    Background and purpose: Torsade de pointes (TdP) can be induced by a reduction in cardiac repolarizing capacity. The aim of this study was to assess whether I Ks blockade or enhancement of I Na could potentiate TdP induced by I Kr blockade and to investigate whether short-term variability (STV) or triangulation of action potentials preceded TdP. Experimental approach: Experiments were performed in open-chest, pentobarbital-anaesthetized, α1-adrenoceptor-stimulated, male New Zealand White rabbits, which received three consecutive i.v. infusions of either the I Kr blocker E-4031 (1, 3 and 10 nmol kg−1 min−1), the I Ks blocker HMR1556 (25, 75 and 250 nmol kg−1 min−1) or E-4031 and HMR1556 combined. In a second study rabbits received either the same doses of E-4031, the I Na enhancer, ATX-II (0.4, 1.2 and 4.0 nmol kg−1) or both of these drugs. ECGs and epicardial monophasic action potentials were recorded. Key results: HMR1556 alone did not cause TdP but increased E-4031-induced TdP from 25 to 80%. ATX-II alone caused TdP in 38% of rabbits, as did E-4031; 75% of rabbits receiving both drugs had TdP. QT intervals were prolonged by all drugs but the extent of QT prolongation was not related to the occurrence of TdP. No changes in STV were detected and triangulation was only increased after TdP occurred. Conclusions and implications: Giving modulators of ion channels in combination substantially increased TdP but, in this model, neither STV nor triangulation of action potentials could predict TdP. PMID:17965747

  3. Gender differences in the predictive role of self-rated health on short-term risk of mortality among older adults

    PubMed Central

    Assari, Shervin

    2016-01-01

    Objectives: Despite the well-established association between self-rated health and mortality, research findings have been inconsistent regarding how men and women differ on this link. Using a national sample in the United States, this study compared American male and female older adults for the predictive role of baseline self-rated health on the short-term risk of mortality. Methods: This longitudinal study followed 1500 older adults (573 men (38.2%) and 927 women (61.8%)) aged 66 years or older for 3 years from 2001 to 2004. The main predictor of interest was self-rated health, which was measured using a single item in 2001. The outcome was the risk of all-cause mortality during the 3-year follow-up period. Demographic factors (race and age), socio-economic factors (education and marital status), and health behaviors (smoking and drinking) were covariates. Gender was the focal moderator. We ran logistic regression models in the pooled sample and also stratified by gender, with self-rated health treated as either nominal variables, poor compared to other levels (i.e. fair, good, or excellent) or excellent compared to other levels (i.e. good, fair, or poor), or an ordinal variable. Results: In the pooled sample, baseline self-rated health predicted mortality risk, regardless of how the variable was treated. We found a significant interaction between gender and poor self-rated health, indicating a stronger effect of poor self-rated health on mortality risk for men compared to women. Gender did not interact with excellent self-rated health on mortality. Conclusion: Perceived poor self-rated health better reflects risk of mortality over a short period of time for older men compared to older women. Clinicians may need to take poor self-rated health of older men very seriously. Future research should test whether the differential predictive validity of self-rated health based on gender is due to a different meaning of poor self-rated health for older men and women

  4. The earthquake prediction experiment at Parkfield, California

    USGS Publications Warehouse

    Roeloffs, E.; Langbein, J.

    1994-01-01

    Since 1985, a focused earthquake prediction experiment has been in progress along the San Andreas fault near the town of Parkfield in central California. Parkfield has experienced six moderate earthquakes since 1857 at average intervals of 22 years, the most recent a magnitude 6 event in 1966. The probability of another moderate earthquake soon appears high, but studies assigning it a 95% chance of occurring before 1993 now appear to have been oversimplified. The identification of a Parkfield fault "segment" was initially based on geometric features in the surface trace of the San Andreas fault, but more recent microearthquake studies have demonstrated that those features do not extend to seismogenic depths. On the other hand, geodetic measurements are consistent with the existence of a "locked" patch on the fault beneath Parkfield that has presently accumulated a slip deficit equal to the slip in the 1966 earthquake. A magnitude 4.7 earthquake in October 1992 brought the Parkfield experiment to its highest level of alert, with a 72-hour public warning that there was a 37% chance of a magnitude 6 event. However, this warning proved to be a false alarm. Most data collected at Parkfield indicate that strain is accumulating at a constant rate on this part of the San Andreas fault, but some interesting departures from this behavior have been recorded. Here we outline the scientific arguments bearing on when the next Parkfield earthquake is likely to occur and summarize geophysical observations to date.

  5. An Exemplar-Familiarity Model Predicts Short-Term and Long-Term Probe Recognition across Diverse Forms of Memory Search

    ERIC Educational Resources Information Center

    Nosofsky, Robert M.; Cox, Gregory E.; Cao, Rui; Shiffrin, Richard M.

    2014-01-01

    Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across…

  6. A Short-term In vivo Screen using Fetal Testosterone Production, a Key Event in the Phthalate Adverse Outcome Pathway, to Predict Disruption of Sexual Differentiation.

    EPA Science Inventory

    This study was designed to develop and validate a short-term in vivo protocol termed the Fetal Phthalate Screen (FPS) to detect phthalate esters (PEs) and other chemicals that disrupt fetal testosterone synthesis and testis gene expression in rats. We propose that the FPS can be ...

  7. An Exemplar-Familiarity Model Predicts Short-Term and Long-Term Probe Recognition across Diverse Forms of Memory Search

    ERIC Educational Resources Information Center

    Nosofsky, Robert M.; Cox, Gregory E.; Cao, Rui; Shiffrin, Richard M.

    2014-01-01

    Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across…

  8. The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness, and Verbal Short-Term Memory in Reading Skills: A Review

    ERIC Educational Resources Information Center

    Melby-Lervag, Monica

    2012-01-01

    The acknowledgement that educational achievement is highly dependent on successful reading development has led to extensive research on its underlying factors. A strong argument has been made for a causal relationship between reading and phoneme awareness; similarly, causal relations have been suggested for reading with short-term memory and rhyme…

  9. The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness and Verbal Short-Term Memory in Reading Skills: A Review

    ERIC Educational Resources Information Center

    Melby-Lervag, Monica

    2012-01-01

    The acknowledgement that educational achievement is highly dependent on successful reading development, has led to extensive research on its underlying factors. Evidence clearly suggests that the relation between reading skills, phoneme awareness, rhyme awareness, and verbal short-term memory is more than a mere association. A strong argument has…

  10. Development of Short-term Molecular Thresholds to Predict Long-term Mouse Liver Tumor Outcomes: Phthalate Case StudyTo be

    EPA Science Inventory

    Molecular Thresholds for Early Key Events in Liver Tumorgensis: PhthalateCase StudyTriangleShort-term changes in molecular profiles are a central component of strategies to model health effects of environmental chemicals such as phthalates, for which there is widespread human exp...

  11. The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness and Verbal Short-Term Memory in Reading Skills: A Review

    ERIC Educational Resources Information Center

    Melby-Lervag, Monica

    2012-01-01

    The acknowledgement that educational achievement is highly dependent on successful reading development, has led to extensive research on its underlying factors. Evidence clearly suggests that the relation between reading skills, phoneme awareness, rhyme awareness, and verbal short-term memory is more than a mere association. A strong argument has…

  12. The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness, and Verbal Short-Term Memory in Reading Skills: A Review

    ERIC Educational Resources Information Center

    Melby-Lervag, Monica

    2012-01-01

    The acknowledgement that educational achievement is highly dependent on successful reading development has led to extensive research on its underlying factors. A strong argument has been made for a causal relationship between reading and phoneme awareness; similarly, causal relations have been suggested for reading with short-term memory and rhyme…

  13. Development of Short-term Molecular Thresholds to Predict Long-term Mouse Liver Tumor Outcomes: Phthalate Case StudyTo be

    EPA Science Inventory

    Molecular Thresholds for Early Key Events in Liver Tumorgensis: PhthalateCase StudyTriangleShort-term changes in molecular profiles are a central component of strategies to model health effects of environmental chemicals such as phthalates, for which there is widespread human exp...

  14. A Short-term In vivo Screen using Fetal Testosterone Production, a Key Event in the Phthalate Adverse Outcome Pathway, to Predict Disruption of Sexual Differentiation.

    EPA Science Inventory

    This study was designed to develop and validate a short-term in vivo protocol termed the Fetal Phthalate Screen (FPS) to detect phthalate esters (PEs) and other chemicals that disrupt fetal testosterone synthesis and testis gene expression in rats. We propose that the FPS can be ...

  15. Predicting Patient Change from Therapist Competence and Patient-Therapist Complementarity in Short-Term Anxiety-Provoking Psychotherapy: A Pilot Study.

    ERIC Educational Resources Information Center

    Svartberg, Martin; Stiles, Tore C.

    1992-01-01

    Examined therapist competence and patient-therapist complementarity as to their interrelation and their unique, collective, and interactive contributions to patient change in 20 sessions of short-term anxiety-provoking psychotherapy. Found that competence in early sessions did not relate to patient change. Patient-therapist complementarity ratings…

  16. Earthquakes.

    ERIC Educational Resources Information Center

    Walter, Edward J.

    1977-01-01

    Presents an analysis of the causes of earthquakes. Topics discussed include (1) geological and seismological factors that determine the effect of a particular earthquake on a given structure; (2) description of some large earthquakes such as the San Francisco quake; and (3) prediction of earthquakes. (HM)

  17. Earthquakes.

    ERIC Educational Resources Information Center

    Walter, Edward J.

    1977-01-01

    Presents an analysis of the causes of earthquakes. Topics discussed include (1) geological and seismological factors that determine the effect of a particular earthquake on a given structure; (2) description of some large earthquakes such as the San Francisco quake; and (3) prediction of earthquakes. (HM)

  18. On some methods for assessing earthquake predictions

    NASA Astrophysics Data System (ADS)

    Molchan, G.; Romashkova, L.; Peresan, A.

    2017-09-01

    A regional approach to the problem of assessing earthquake predictions inevitably faces a deficit of data. We point out some basic limits of assessment methods reported in the literature, considering the practical case of the performance of the CN pattern recognition method in the prediction of large Italian earthquakes. Along with the classical hypothesis testing, a new game approach, the so-called parimutuel gambling (PG) method, is examined. The PG, originally proposed for the evaluation of the probabilistic earthquake forecast, has been recently adapted for the case of 'alarm-based' CN prediction. The PG approach is a non-standard method; therefore it deserves careful examination and theoretical analysis. We show that the PG alarm-based version leads to an almost complete loss of information about predicted earthquakes (even for a large sample). As a result, any conclusions based on the alarm-based PG approach are not to be trusted. We also show that the original probabilistic PG approach does not necessarily identifies the genuine forecast correctly among competing seismicity rate models, even when applied to extensive data.

  19. Physically based prediction of earthquake induced landsliding

    NASA Astrophysics Data System (ADS)

    Marc, Odin; Meunier, Patrick; Hovius, Niels; Gorum, Tolga; Uchida, Taro

    2015-04-01

    Earthquakes are an important trigger of landslides and can contribute significantly to sedimentary or organic matter fluxes. We present a new physically based expression for the prediction of total area and volume of populations of earthquake-induced landslides. This model implements essential seismic processes, linking key parameters such as ground acceleration, fault size, earthquake source depth and seismic moment. To assess the model we have compiled and normalized a database of landslide inventories for 40 earthquakes. We have found that low landscape steepness systematically leads to overprediction of the total area and volume of landslides. When this effect is accounted for, the model is able to predict within a factor of 2 the landslide areas and associated volumes for about two thirds of the cases in our databases. This is a significant improvement on a previously published empirical expression based only on earthquake moment, even though the prediction of total landslide area is more difficult than that of volume because it is affected by additional parameters such as the depth and continuity of soil cover. Some outliers in terms of observed landslide intensity are likely to be associated with exceptional rock mass properties in the epicentral area. Others may be related to seismic source complexities ignored by the model. However, most cases in our catalogue seem to be relatively unaffected by these two effects despite the variety of lithologies and tectonic settings they cover. This makes the model suitable for integration into landscape evolution models, and application to the assessment of secondary hazards and risks associated with earthquakes.

  20. The nonlinear predictability of the electrotelluric field variations data analyzed with support vector machines as an earthquake precursor.

    PubMed

    Ifantis, A; Papadimitriou, S

    2003-10-01

    This work investigates the nonlinear predictability of the Electro Telluric Field (ETF) variations data in order to develop new intelligent tools for the difficult task of earthquake prediction. Support Vector Machines trained on a signal window have been used to predict the next sample. We observe a significant increase at this short-term unpredictability of the ETF signal at about two weeks time period before the major earthquakes that took place in regions near the recording devices. The unpredictability increase can be attributed to a quick time variation of the dynamics that produce the ETF signal due to the earthquake generation process. Thus, this increase can be taken into advantage for signaling for an increased possibility of a large earthquake within the next few days in the neighboring region of the recording station.

  1. Predictive value of non-fasting remnant cholesterol for short-term outcome of diabetics with new-onset stable coronary artery disease.

    PubMed

    Hong, Li-Feng; Yan, Xiao-Ni; Lu, Zhen-Hua; Fan, Ying; Ye, Fei; Wu, Qiong; Luo, Song-Hui; Yang, Bo; Li, Jian-Jun

    2017-01-13

    The relationship between non-fasting remnant cholesterol and cardiovascular outcome in the era of potent statin therapy remained to be elucidated. A cohort study of three hundred and twenty eight diabetics diagnosed with new-onset stable coronary artery disease (CAD) by coronary angiography were enrolled. All cases were followed up for an average duration of twelve months. The association between baseline remnant cholesterol levels and major cardiovascular outcomes were evaluated using the receivers operating characteristic (ROC) curves and Cox proportional hazards regression analysis. During a period of 12-month's follow-up, 14.3% patients (47/328) underwent pre-specified adverse outcomes. The remnant cholesterol associated with high sensitivity C-reactive protein, neutrophil count and fibrinogen (R (2) = 0.20, 0.12 and 0.14; P = 0.000, 0.036 and 0.010 respectively). Area under the ROC curves (AUC) indicated discriminatory power of the remnant cholesterol to predict the adverse outcomes for this population (AUC = 0.64, P < 0.005). Kaplan-Meier curve suggested that the lower levels of remnant cholesterol showed relatively lower cardiac events for diabetic patients with stable CAD (Log rank X (2) = 8.94, P = 0.04). However, according to multivariate Cox proportional hazards regression, apart from hemoglobin A1C (Hazard ratio [H.R.] =1.38, 95% CI: 1.14-1.66, P = 0.001) and Gensini scores (H.R. = 1.00, 95% CI: 1.00-1.02; P = 0.035), remnant cholesterol did not qualify as an independent predictor of adverse prognosis in these settings (H.R. = 1.05, 95% CI: 0.46-2.37, P = 0.909). Non-fasting remnant cholesterol was associated with inflammatory biomarkers and high incidence of revascularization, but not qualified as an independent predictor for short-term prognosis of diabetics with new-onset stable coronary artery disease.

  2. 76 FR 19123 - National Earthquake Prediction Evaluation Council (NEPEC)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-06

    ....S. Geological Survey National Earthquake Prediction Evaluation Council (NEPEC) AGENCY: U.S... Earthquake Prediction Evaluation Council (NEPEC) will hold a 1-day meeting on April 16, 2011. The meeting... the Director of the U.S. Geological Survey on proposed earthquake predictions, on the completeness and...

  3. A radon detector for earthquake prediction

    NASA Astrophysics Data System (ADS)

    Dacey, James

    2010-04-01

    Recent events in Haiti and Chile remind us of the devastation that can be wrought by an earthquake, especially when it strikes without warning. For centuries, people living in seismically active regions have reported a number of strange occurrences immediately prior to a quake, including unexpected weather phenomena and even unusual behaviour among animals. In more recent times, some scientists have suggested other precursors, such as sporadic bursts of electromagnetic radiation from the fault zone. Unfortunately, none of these suggestions has led to a robust, scientific method for earthquake prediction. Now, however, a group of physicists, led by physics Nobel laureate Georges Charpak, has developed a new detector that could measure one of the more testable earthquake precursors - the suggestion that radon gas is released from fault zones prior to earth slipping, writes James Dacey.

  4. Signals of ENPEMF Used in Earthquake Prediction

    NASA Astrophysics Data System (ADS)

    Hao, G.; Dong, H.; Zeng, Z.; Wu, G.; Zabrodin, S. M.

    2012-12-01

    The signals of Earth's natural pulse electromagnetic field (ENPEMF) is a combination of the abnormal crustal magnetic field pulse affected by the earthquake, the induced field of earth's endogenous magnetic field, the induced magnetic field of the exogenous variation magnetic field, geomagnetic pulsation disturbance and other energy coupling process between sun and earth. As an instantaneous disturbance of the variation field of natural geomagnetism, ENPEMF can be used to predict earthquakes. This theory was introduced by A.A Vorobyov, who expressed a hypothesis that pulses can arise not only in the atmosphere but within the Earth's crust due to processes of tectonic-to-electric energy conversion (Vorobyov, 1970; Vorobyov, 1979). The global field time scale of ENPEMF signals has specific stability. Although the wave curves may not overlap completely at different regions, the smoothed diurnal ENPEMF patterns always exhibit the same trend per month. The feature is a good reference for observing the abnormalities of the Earth's natural magnetic field in a specific region. The frequencies of the ENPEMF signals generally locate in kilo Hz range, where frequencies within 5-25 kilo Hz range can be applied to monitor earthquakes. In Wuhan, the best observation frequency is 14.5 kilo Hz. Two special devices are placed in accordance with the S-N and W-E direction. Dramatic variation from the comparison between the pulses waveform obtained from the instruments and the normal reference envelope diagram should indicate high possibility of earthquake. The proposed detection method of earthquake based on ENPEMF can improve the geodynamic monitoring effect and can enrich earthquake prediction methods. We suggest the prospective further researches are about on the exact sources composition of ENPEMF signals, the distinction between noise and useful signals, and the effect of the Earth's gravity tide and solid tidal wave. This method may also provide a promising application in

  5. Predictive factors of short-term survival from acute myocardial infarction in early and late patients in Isfahan and Najafabad, Iran

    PubMed Central

    Abdolazimi, Mohammad; Khosravi, Alireza; Sadeghi, Masoumeh; Mohammadian-Hafshejani, Abdollah; Sarrafzadegan, Nizal; Salehiniya, Hamid; Golshahi, Jafar

    2016-01-01

    BACKGROUND Cardiovascular disease (CVD) is the primary cause of mortality in the world and Iran. The aim of this study was to determine the prognostic factors of short-term survival from acute myocardial infarction (AMI) in early and late patients in the Najafabad and Isfahan County, Iran. METHODS This hospital-based cohort study was conducted using the hospital registry of 1999-2009 in Iran. All patients (n = 14426) with an AMI referred to hospitals of Isfahan and Najafabad were investigated. To determine prognostic factors of short-term (28-days) survival in early and late patients, unadjusted and adjusted hazard ratio (HR) was calculated using univariate and multivariate Cox regression. RESULTS The short-term (28-day) survival rate of early and late patients was 96.64% and 89.42% (P < 0.001), respectively. In 80% of early and 79.3% of late patients, mortality occurred during the first 7 days of disease occurrence. HR of death was higher in women in the two groups; it was 1.97 in early patients was (CI95%: 1.32-2.92) and 1.35 in late patients (CI95%: 1.19-1.53) compared to men. HR of death had a rising trend with the increasing of age in the two groups. CONCLUSION Short-term survival rate was higher in early patients than in late patients. In addition, case fatality rate (CFR) of AMI in women was higher than in men. In both groups, sex, age, an atomic location of myocardial infarction based on the International Classification of Disease, Revision 10 (ICD10), cardiac enzymes, and clinical symptoms were significant predictors of survival in early and late patients following AMI. PMID:27429625

  6. Earthquake prediction: Simple methods for complex phenomena

    NASA Astrophysics Data System (ADS)

    Luen, Bradley

    2010-09-01

    Earthquake predictions are often either based on stochastic models, or tested using stochastic models. Tests of predictions often tacitly assume predictions do not depend on past seismicity, which is false. We construct a naive predictor that, following each large earthquake, predicts another large earthquake will occur nearby soon. Because this "automatic alarm" strategy exploits clustering, it succeeds beyond "chance" according to a test that holds the predictions _xed. Some researchers try to remove clustering from earthquake catalogs and model the remaining events. There have been claims that the declustered catalogs are Poisson on the basis of statistical tests we show to be weak. Better tests show that declustered catalogs are not Poisson. In fact, there is evidence that events in declustered catalogs do not have exchangeable times given the locations, a necessary condition for the Poisson. If seismicity followed a stochastic process, an optimal predictor would turn on an alarm when the conditional intensity is high. The Epidemic-Type Aftershock (ETAS) model is a popular point process model that includes clustering. It has many parameters, but is still a simpli_cation of seismicity. Estimating the model is di_cult, and estimated parameters often give a non-stationary model. Even if the model is ETAS, temporal predictions based on the ETAS conditional intensity are not much better than those of magnitude-dependent automatic (MDA) alarms, a much simpler strategy with only one parameter instead of _ve. For a catalog of Southern Californian seismicity, ETAS predictions again o_er only slight improvement over MDA alarms

  7. Earthquakes

    ERIC Educational Resources Information Center

    Roper, Paul J.; Roper, Jere Gerard

    1974-01-01

    Describes the causes and effects of earthquakes, defines the meaning of magnitude (measured on the Richter Magnitude Scale) and intensity (measured on a modified Mercalli Intensity Scale) and discusses earthquake prediction and control. (JR)

  8. Earthquakes

    ERIC Educational Resources Information Center

    Roper, Paul J.; Roper, Jere Gerard

    1974-01-01

    Describes the causes and effects of earthquakes, defines the meaning of magnitude (measured on the Richter Magnitude Scale) and intensity (measured on a modified Mercalli Intensity Scale) and discusses earthquake prediction and control. (JR)

  9. On the earthquake predictability of fault interaction models

    PubMed Central

    Marzocchi, W; Melini, D

    2014-01-01

    Space-time clustering is the most striking departure of large earthquakes occurrence process from randomness. These clusters are usually described ex-post by a physics-based model in which earthquakes are triggered by Coulomb stress changes induced by other surrounding earthquakes. Notwithstanding the popularity of this kind of modeling, its ex-ante skill in terms of earthquake predictability gain is still unknown. Here we show that even in synthetic systems that are rooted on the physics of fault interaction using the Coulomb stress changes, such a kind of modeling often does not increase significantly earthquake predictability. Earthquake predictability of a fault may increase only when the Coulomb stress change induced by a nearby earthquake is much larger than the stress changes caused by earthquakes on other faults and by the intrinsic variability of the earthquake occurrence process. PMID:26074643

  10. On the earthquake predictability of fault interaction models

    NASA Astrophysics Data System (ADS)

    Marzocchi, W.; Melini, D.

    2014-12-01

    Space-time clustering is the most striking departure of large earthquakes occurrence process from randomness. These clusters are usually described ex-post by a physics-based model in which earthquakes are triggered by Coulomb stress changes induced by other surrounding earthquakes. Notwithstanding the popularity of this kind of modeling, its ex-ante skill in terms of earthquake predictability gain is still unknown. Here we show that even in synthetic systems that are rooted on the physics of fault interaction using the Coulomb stress changes, such a kind of modeling often does not increase significantly earthquake predictability. Earthquake predictability of a fault may increase only when the Coulomb stress change induced by a nearby earthquake is much larger than the stress changes caused by earthquakes on other faults and by the intrinsic variability of the earthquake occurrence process.

  11. Neural network models for earthquake magnitude prediction using multiple seismicity indicators.

    PubMed

    Panakkat, Ashif; Adeli, Hojjat

    2007-02-01

    Neural networks are investigated for predicting the magnitude of the largest seismic event in the following month based on the analysis of eight mathematically computed parameters known as seismicity indicators. The indicators are selected based on the Gutenberg-Richter and characteristic earthquake magnitude distribution and also on the conclusions drawn by recent earthquake prediction studies. Since there is no known established mathematical or even empirical relationship between these indicators and the location and magnitude of a succeeding earthquake in a particular time window, the problem is modeled using three different neural networks: a feed-forward Levenberg-Marquardt backpropagation (LMBP) neural network, a recurrent neural network, and a radial basis function (RBF) neural network. Prediction accuracies of the models are evaluated using four different statistical measures: the probability of detection, the false alarm ratio, the frequency bias, and the true skill score or R score. The models are trained and tested using data for two seismically different regions: Southern California and the San Francisco bay region. Overall the recurrent neural network model yields the best prediction accuracies compared with LMBP and RBF networks. While at the present earthquake prediction cannot be made with a high degree of certainty this research provides a scientific approach for evaluating the short-term seismic hazard potential of a region.

  12. 77 FR 53225 - National Earthquake Prediction Evaluation Council (NEPEC)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-31

    ... Geological Survey National Earthquake Prediction Evaluation Council (NEPEC) AGENCY: Department of the... National Earthquake Prediction Evaluation Council (NEPEC) will hold a 1\\1/2\\ day meeting on September 17 and 18, 2012, at the U.S. Geological Survey National Earthquake Information Center (NEIC), 1711...

  13. A physical interpretation of the Haicheng earthquake prediction.

    PubMed

    Scholz, C H

    1977-05-12

    A possible explanation for the successful prediction of the 1975 Haicheng earthquake is that the earthquake was triggered by a deformation front that propagated 1,000 km through NE China at a velocity of about 110 km yr(-1). The various phenomena that were used to predict the earthquake can be explained by the deformation front.

  14. Evaluation of Short-Term Bioassays to Predict Functional Impairment. Development of Cardiovascular Bioassays in Laboratory Animals/Directory of Institutions/Individuals.

    DTIC Science & Technology

    1980-10-01

    BHT ), BUTYLATED HYDROXYANISOLE ( BHA ) AND SODIUM BISULFITE I• GI 4i Fr L3IJJ,,G bt- jK-4i0? 1JJ6 n --a, - I - ORGANIZATION: ALTON OCHSNER MEDICAL...recommends those tests which are suitable for use in a screening progra A variety of testing techniques have been developed to detect ardiovascular...damage; however, few of these are well developed or have demon trated ability to detect damage in short-term screening. Those tests that are sufficiently

  15. Earthquake Predictability: Results From Aggregating Seismicity Data And Assessment Of Theoretical Individual Cases Via Synthetic Data

    NASA Astrophysics Data System (ADS)

    Adamaki, A.; Roberts, R.

    2016-12-01

    For many years an important aim in seismological studies has been forecasting the occurrence of large earthquakes. Despite some well-established statistical behavior of earthquake sequences, expressed by e.g. the Omori law for aftershock sequences and the Gutenburg-Richter distribution of event magnitudes, purely statistical approaches to short-term earthquake prediction have in general not been successful. It seems that better understanding of the processes leading to critical stress build-up prior to larger events is necessary to identify useful precursory activity, if this exists, and statistical analyses are an important tool in this context. There has been considerable debate on the usefulness or otherwise of foreshock studies for short-term earthquake prediction. We investigate generic patterns of foreshock activity using aggregated data and by studying not only strong but also moderate magnitude events. Aggregating empirical local seismicity time series prior to larger events observed in and around Greece reveals a statistically significant increasing rate of seismicity over 20 days prior to M>3.5 earthquakes. This increase cannot be explained by tempo-spatial clustering models such as ETAS, implying genuine changes in the mechanical situation just prior to larger events and thus the possible existence of useful precursory information. Because of tempo-spatial clustering, including aftershocks to foreshocks, even if such generic behavior exists it does not necessarily follow that foreshocks have the potential to provide useful precursory information for individual larger events. Using synthetic catalogs produced based on different clustering models and different presumed system sensitivities we are now investigating to what extent the apparently established generic foreshock rate acceleration may or may not imply that the foreshocks have potential in the context of routine forecasting of larger events. Preliminary results suggest that this is the case, but

  16. Short-term energy outlook

    SciTech Connect

    Not Available

    1990-11-07

    The Energy Information Administration (EIA) presents future scenarios of quarterly short-term energy supply, demand, and prices for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes previous estimate errors, compares recent scenarios with those of other forecasting services, and discusses current topics of the short-term energy markets. (See Short-Term Energy Outlook: Annual Supplement, DOE/EIA-0202.) The principal users of the Outlook are managers and energy analysts in private industry and government. The scenario period for this issue of the Outlook extends from the fourth quarter of 1990 through the fourth quarter of 1991. Some data for the third quarter of 1990 are preliminary EIA estimates of actual data (for example, some petroleum estimates are based on statistics from the Weekly Petroleum Status Report) or are derived from internal model simulations using the latest exogenous information available (for example, some electricity demand estimates are based on recent weather data). 11 figs., 13 tabs.

  17. Short-term solar activity forecasting

    NASA Technical Reports Server (NTRS)

    Xie-Zhen, C.; Ai-Di, Z.

    1979-01-01

    A method of forecasting the level of activity of every active region on the surface of the Sun within one to three days is proposed in order to estimate the possibility of the occurrence of ionospheric disturbances and proton events. The forecasting method is a probability process based on statistics. In many of the cases, the accuracy in predicting the short term solar activity was in the range of 70%, although there were many false alarms.

  18. From Earthquake Prediction Research to Time-Variable Seismic Hazard Assessment Applications

    NASA Astrophysics Data System (ADS)

    Bormann, Peter

    2011-01-01

    The first part of the paper defines the terms and classifications common in earthquake prediction research and applications. This is followed by short reviews of major earthquake prediction programs initiated since World War II in several countries, for example the former USSR, China, Japan, the United States, and several European countries. It outlines the underlying expectations, concepts, and hypotheses, introduces the technologies and methodologies applied and some of the results obtained, which include both partial successes and failures. Emphasis is laid on discussing the scientific reasons why earthquake prediction research is so difficult and demanding and why the prospects are still so vague, at least as far as short-term and imminent predictions are concerned. However, classical probabilistic seismic hazard assessments, widely applied during the last few decades, have also clearly revealed their limitations. In their simple form, they are time-independent earthquake rupture forecasts based on the assumption of stable long-term recurrence of earthquakes in the seismotectonic areas under consideration. Therefore, during the last decade, earthquake prediction research and pilot applications have focused mainly on the development and rigorous testing of long and medium-term rupture forecast models in which event probabilities are conditioned by the occurrence of previous earthquakes, and on their integration into neo-deterministic approaches for improved time-variable seismic hazard assessment. The latter uses stress-renewal models that are calibrated for variations in the earthquake cycle as assessed on the basis of historical, paleoseismic, and other data, often complemented by multi-scale seismicity models, the use of pattern-recognition algorithms, and site-dependent strong-motion scenario modeling. International partnerships and a global infrastructure for comparative testing have recently been developed, for example the Collaboratory for the Study of

  19. An exemplar-familiarity model predicts short-term and long-term probe recognition across diverse forms of memory search.

    PubMed

    Nosofsky, Robert M; Cox, Gregory E; Cao, Rui; Shiffrin, Richard M

    2014-11-01

    Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across diverse conditions that manipulated relations between targets and foils across trials. Subjects saw lists of from 1 to 16 items followed by a single item recognition probe. In a varied-mapping condition, targets and foils could switch roles across trials; in a consistent-mapping condition, targets and foils never switched roles; and in an all-new condition, on each trial a completely new set of items formed the memory set. In the varied-mapping and all-new conditions, mean correct response times (RTs) and error proportions were curvilinear increasing functions of memory set size, with the RT results closely resembling ones from hybrid visual-memory search experiments reported by Wolfe (2012). In the consistent-mapping condition, new-probe RTs were invariant with set size, whereas old-probe RTs increased slightly with increasing study-test lag. With appropriate choice of psychologically interpretable free parameters, the model accounted well for the complete set of results. The work provides support for the hypothesis that a common set of processes involving exemplar-based familiarity may govern long-term and short-term probe recognition across wide varieties of memory- search conditions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  20. 76 FR 69761 - National Earthquake Prediction Evaluation Council (NEPEC)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-09

    ....S. Geological Survey National Earthquake Prediction Evaluation Council (NEPEC) AGENCY: U.S. Geological Survey. ACTION: Notice of Meeting. SUMMARY: Pursuant to Public Law 96-472, the National Earthquake... Government. The Council shall advise the Director of the U.S. Geological Survey on proposed earthquake...

  1. An evaluation of the seismic- window theory for earthquake prediction.

    USGS Publications Warehouse

    McNutt, M.; Heaton, T.H.

    1981-01-01

    Reports studies designed to determine whether earthquakes in the San Francisco Bay area respond to a fortnightly fluctuation in tidal amplitude. It does not appear that the tide is capable of triggering earthquakes, and in particular the seismic window theory fails as a relevant method of earthquake prediction. -J.Clayton

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    headquarters until 9 p.m.: families, school classes with and without teachers, civil protection groups, journalists. This initiative, built up in a few weeks, had a very large feedback, also due to the media highlighting the presumed prediction. Although we could not rule out the possibility of a strong earthquake in central Italy (with effects in Rome) we tried to explain the meaning of short term earthquake prediction vs. probabilistic seismic hazard assessment. Despite many people remained with the fear (many decided to take a day off and leave the town or stay in public parks), we contributed to reduce this feeling and therefore the social cost of this strange Roman day. Moreover, another lesson learned is that these (fortunately sporadic) circumstances, when people's attention is high, are important opportunities for science communication. We thank all the INGV colleagues who contributed to the May 11 Open Day, in particular the Press Office, the Educational and Outreach laboratory, the Graphics Laboratory and SissaMedialab. P.S. no large earthquake happened

  3. Short-term suboptimal response criteria for predicting long-term non-response to first-line disease modifying therapies in multiple sclerosis: A systematic review and meta-analysis.

    PubMed

    Río, Jordi; Ruiz-Peña, Juan Luís

    2016-02-15

    There is no consensus about short-term suboptimal response to first-line treatments in relapsing-remitting multiple sclerosis. We searched studies with interferon beta or glatiramer acetate in which a long-term (≥ 2 years (y)) outcome could be predicted using short-term (≤ 1 y) suboptimal response criteria (EDSS-, imaging- and/or relapse-based). We obtained pooled diagnostic accuracy parameters for the 1-y criteria used to predict disability progression between 2-5 y. We selected 45 articles. Eight studies allowed calculating pooled estimates of 16 criteria. The three criteria with best accuracy were: new or enlarging T2-weighted lesions (newT2) ≥ 1 (pooled sensitivity: 85.5%; specificity:70.2%; positive predictive value:48.0%; negative predictive value:93.8%), newT2 ≥ 2 (62.4%, 83.6%, 55.0% and 87.3%, respectively) and RIO score ≥ 2 (55.8%, 84.4%, 47.8% and 88.2%). Pooled percentages of suboptimal responders were 43.3%, 27.6% and 23.7%, respectively. Pooled diagnostic odds ratios were 14.6 (95% confidence interval: 1.4-155), 9.2 (1.4-59.0) and 8.2 (3.5-19.2). All criteria had a limited predictive value. RIO score ≥ 2 at 1-y combined fair accuracy and consistency, limiting the probability of disability progression in the next years to 1 in 8 optimal responders. NewT2 ≥ 1 at 1-y had similar positive predictive value, but diminished the false negatives to 1 in 16 patients. More sensitive measures of treatment failure at short term are needed.

  4. Prediction of Earthquakes by Lunar Cicles

    NASA Astrophysics Data System (ADS)

    Rodriguez, G.

    2007-05-01

    Prediction of Earthquakes by Lunar Cicles Author ; Guillermo Rodriguez Rodriguez Afiliation Geophysic and Astrophysicist. Retired I have exposed this idea to many meetings of EGS, UGS, IUGG 95, from 80, 82.83,and AGU 2002 Washington and 2003 Niza I have thre aproximition in Time 1º Earthquakes hapen The same day of the years every 18 or 19 years (cicle Saros ) Some times in the same place or anhother very far . In anhother moments of the year , teh cicle can be are ; 14 years, 26 years, 32 years or the multiples o 18.61 years expecial 55, 93, 224, 150 ,300 etcetc. For To know the day in the year 2º Over de cicle o one Lunation ( Days over de date of new moon) The greats Earthquakes hapens with diferents intervals of days in the sucesives lunations (aproximately one month) like we can be see in the grafic enclosed. For to know the day of month 3º Over each day I have find that each 28 day repit aproximately the same hour and minute. The same longitude and the same latitud in all earthquakes , also the littles ones . This is very important because we can to proposse only the precaution of wait it in the street or squares Whenever some times the cicles can be longuers or more littles This is my special way of cientific metode As consecuence of the 1º and 2º principe we can look The correlation between years separated by cicles of the 1º tipe For example 1984 and 2002 0r 2003 and consecutive years include 2007...During 30 years I have look de dates. I am in my subconcense the way but I can not make it in scientific formalisme

  5. Functional Mitral Regurgitation Predicts Short-Term Adverse Events in Patients With Acute Heart Failure and Reduced Left Ventricular Ejection Fraction.

    PubMed

    De la Espriella, Rafael; Santas, Enrique; Miñana, Gema; Bodí, Vicent; Valero, Ernesto; Payá, Rafael; Núñez, Eduardo; Payá, Ana; Chorro, Francisco J; Bayés-Genis, Antoni; Sanchis, Juan; Núñez, Julio

    2017-10-15

    Functional mitral regurgitation (FMR) is a common finding in patients with acute heart failure (AHF) and reduced left ventricular ejection fraction (heart failure and reduced ejection fraction [HFrEF]). However, its clinical impact remains unclear. We aimed to evaluate the association between the severity of FMR after clinical stabilization and short-term adverse outcomes after a hospitalization for AHF. We prospectively included 938 consecutive patients with HFrEF discharged after a hospitalization for AHF, after excluding those with organic valve disease, congenital heart disease, or aortic valve disease. FMR was assessed semiquantitatively by color Doppler analysis of the regurgitant jet area, and its severity was categorized as none or mild (grade 0 or 1), moderate (grade 2), or severe (grade 3 or 4). FMR was assessed at 120 ± 24 hours after admission. The primary end point was the composite of all-cause mortality and rehospitalization at 90 days. At discharge, 533 (56.8%), 253 (26.9%), and 152 (16.2%) patients showed none-mild, moderate, and severe FMR. At the 90-day follow-up, 161 patients (17.2%) either died (n = 49) or were readmitted (n = 112). Compared with patients with none or mild FMR, rates of the composite end point were higher for patients with moderate and severe FMRs (p <0.001). After the multivariable adjustment, those with moderate and severe FMRs had a significantly higher risk of reaching the end point (hazard ratio = 1.50, 95% confidence interval 1.04 to 2.17, p = 0.027; and hazard ratio = 1.63, 95% confidence interval 1.07 to 2.48, p = 0.023, respectively). In conclusion, FMR is a common finding in patients with HFrEF, and its presence, when moderate or severe, identifies a subgroup at higher risk of adverse clinical outcomes at short term. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Material contrast does not predict earthquake rupture propagation direction

    USGS Publications Warehouse

    Harris, R.A.; Day, S.M.

    2005-01-01

    Earthquakes often occur on faults that juxtapose different rocks. The result is rupture behavior that differs from that of an earthquake occurring on a fault in a homogeneous material. Previous 2D numerical simulations have studied simple cases of earthquake rupture propagation where there is a material contrast across a fault and have come to two different conclusions: 1) earthquake rupture propagation direction can be predicted from the material contrast, and 2) earthquake rupture propagation direction cannot be predicted from the material contrast. In this paper we provide observational evidence from 70 years of earthquakes at Parkfield, CA, and new 3D numerical simulations. Both the observations and the numerical simulations demonstrate that earthquake rupture propagation direction is unlikely to be predictable on the basis of a material contrast. Copyright 2005 by the American Geophysical Union.

  7. Predictable 'meta-mechanisms' emerge from feedbacks between transpiration and plant growth and cannot be simply deduced from short-term mechanisms.

    PubMed

    Tardieu, François; Parent, Boris

    2016-08-29

    Growth under water deficit is controlled by short-term mechanisms but, because of numerous feedbacks, the combination of these mechanisms over time often results in outputs that cannot be deduced from the simple inspection of individual mechanisms. It can be analysed with dynamic models in which causal relationships between variables are considered at each time-step, allowing calculation of outputs that are routed back to inputs for the next time-step and that can change the system itself. We first review physiological mechanisms involved in seven feedbacks of transpiration on plant growth, involving changes in tissue hydraulic conductance, stomatal conductance, plant architecture and underlying factors such as hormones or aquaporins. The combination of these mechanisms over time can result in non-straightforward conclusions as shown by examples of simulation outputs: 'over production of abscisic acid (ABA) can cause a lower concentration of ABA in the xylem sap ', 'decreasing root hydraulic conductance when evaporative demand is maximum can improve plant performance' and 'rapid root growth can decrease yield'. Systems of equations simulating feedbacks over numerous time-steps result in logical and reproducible emergent properties that can be viewed as 'meta-mechanisms' at plant level, which have similar roles as mechanisms at cell level.

  8. Low residual proliferation after short-term letrozole therapy is an early predictive marker of response in high proliferative ER-positive breast cancer.

    PubMed

    Bedard, Philippe L; Singhal, Sandeep K; Ignatiadis, Michail; Bradbury, Ian; Haibe-Kains, Benjamin; Desmedt, Christine; Loi, Sherene; Evans, Dean B; Michiels, Stefan; Dixon, J Michael; Miller, William R; Piccart, Martine J; Sotiriou, Christos

    2011-12-01

    The gene expression grade index (GGI) is a 97-gene algorithm that measures proliferation and divides intermediate histological grade tumors into two distinct groups. We investigated the association between early changes in GGI and clinical response to neoadjuvant letrozole and compared this to Ki67 values. The paired gene expression data at the beginning and after 10-14 days of neoadjuvant letrozole treatment were available for 52 post-menopausal patients with estrogen receptor (ER)-positive breast cancer. Baseline values and changes in GGI, Ki67, and RNA expression modules representing oncogenic signaling pathways were compared to sonographic tumor volume changes after 3 months of treatment in the subsets of patients defined by high and low baseline GGI. The clinical response was observed in 80% genomic low-grade (24/30) and 59% genomic high-grade (13/22) tumors (P=0.10). Low residual proliferation after 10-14 days of neoadjuvant letrozole therapy, measured by either GGI or Ki67, was associated with sonographic response in genomic high-grade (GGI, P=0.003; Ki67, P=0.017) but not genomic low-grade (GGI, P=0.25; Ki67, P=1.0) tumors. The analysis of expression modules suggested that sonographic response to letrozole in genomic high-grade tumors was associated with an early reduction in IGF1 signaling (unadjusted P=0.018). The major conclusion of this study is that the early assessment of proliferation after short-term endocrine therapy may be useful to evaluate endocrine responsiveness, particularly in genomic high-grade ER-positive breast cancer.

  9. A short-term in vivo screen using fetal testosterone production, a key event in the phthalate adverse outcome pathway, to predict disruption of sexual differentiation.

    PubMed

    Furr, Johnathan R; Lambright, Christy S; Wilson, Vickie S; Foster, Paul M; Gray, Leon E

    2014-08-01

    This study was designed to develop and validate a short-term in vivo protocol termed the Fetal Phthalate Screen (FPS) to detect phthalate esters (PEs) and other chemicals that disrupt fetal testosterone synthesis and testis gene expression in rats. We propose that the FPS can be used to screen chemicals that produce adverse developmental outcomes via disruption of the androgen synthesis pathway more rapidly and efficiently, and with fewer animals than a postnatal one-generation study. Pregnant rats were dosed from gestational day (GD) 14 to 18 at one dose level with one of 27 chemicals including PEs, PE alternatives, pesticides known to inhibit steroidogenesis, an estrogen and a potent PPARα agonist and ex vivo testis testosterone production (T Prod) was measured on GD 18. We also included some chemicals with "unknown" activity including DMEP, DHeP, DHEH, DPHCH, DAP, TOTM, tetrabromo-diethyl hexyl phthalate (BrDEHP), and a relatively potent environmental estrogen BPAF. Dose-response studies also were conducted with this protocol with 11 of the above chemicals to determine their relative potencies. CD-1 mice also were exposed to varying dose levels of DPeP from GD 13 to 17 to determine if DPeP reduced T Prod in this species since there is a discrepancy among the results of in utero studies of PEs in mice. Compared to the known male reproductive effects of the PEs in rats the FPS correctly identified all known "positives" and "negatives" tested. Seven of eight "unknowns" tested were "negatives", they did not reduce T Prod, whereas DAP produced an "equivocal" response. Finally, a dose-response study with DPeP in CD-1 mice revealed that fetal T Prod can be inhibited by exposure to a PE in utero in this species, but at a higher dose level than required in rats.Key words. Phthalate Syndrome, Fetal endocrine biomarkers, Phthalate adverse outcome pathway, testosterone production, fetal rat testis.

  10. Stigma in science: the case of earthquake prediction.

    PubMed

    Joffe, Helene; Rossetto, Tiziana; Bradley, Caroline; O'Connor, Cliodhna

    2017-05-17

    This paper explores how earthquake scientists conceptualise earthquake prediction, particularly given the conviction of six earthquake scientists for manslaughter (subsequently overturned) on 22 October 2012 for having given inappropriate advice to the public prior to the L'Aquila earthquake of 6 April 2009. In the first study of its kind, semi-structured interviews were conducted with 17 earthquake scientists and the transcribed interviews were analysed thematically. The scientists primarily denigrated earthquake prediction, showing strong emotive responses and distancing themselves from earthquake 'prediction' in favour of 'forecasting'. Earthquake prediction was regarded as impossible and harmful. The stigmatisation of the subject is discussed in the light of research on boundary work and stigma in science. The evaluation reveals how mitigation becomes the more favoured endeavour, creating a normative environment that disadvantages those who continue to pursue earthquake prediction research. Recommendations are made for communication with the public on earthquake risk, with a focus on how scientists portray uncertainty. 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

  11. Research on earthquake prediction from infrared cloud images

    NASA Astrophysics Data System (ADS)

    Fan, Jing; Chen, Zhong; Yan, Liang; Gong, Jing; Wang, Dong

    2015-12-01

    In recent years, the occurrence of large earthquakes is frequent all over the word. In the face of the inevitable natural disasters, the prediction of the earthquake is particularly important to avoid more loss of life and property. Many achievements in the field of predict earthquake from remote sensing images have been obtained in the last few decades. But the traditional prediction methods presented do have the limitations of can't forecast epicenter location accurately and automatically. In order to solve the problem, a new predicting earthquakes method based on extract the texture and emergence frequency of the earthquake cloud is proposed in this paper. First, strengthen the infrared cloud images. Second, extract the texture feature vector of each pixel. Then, classified those pixels and converted to several small suspected area. Finally, tracking the suspected area and estimate the possible location. The inversion experiment of Ludian earthquake show that this approach can forecast the seismic center feasible and accurately.

  12. Modified-Fibonacci-Dual-Lucas method for earthquake prediction

    NASA Astrophysics Data System (ADS)

    Boucouvalas, A. C.; Gkasios, M.; Tselikas, N. T.; Drakatos, G.

    2015-06-01

    The FDL method makes use of Fibonacci, Dual and Lucas numbers and has shown considerable success in predicting earthquake events locally as well as globally. Predicting the location of the epicenter of an earthquake is one difficult challenge the other being the timing and magnitude. One technique for predicting the onset of earthquakes is the use of cycles, and the discovery of periodicity. Part of this category is the reported FDL method. The basis of the reported FDL method is the creation of FDL future dates based on the onset date of significant earthquakes. The assumption being that each occurred earthquake discontinuity can be thought of as a generating source of FDL time series The connection between past earthquakes and future earthquakes based on FDL numbers has also been reported with sample earthquakes since 1900. Using clustering methods it has been shown that significant earthquakes (<6.5R) can be predicted with very good accuracy window (+-1 day). In this contribution we present an improvement modification to the FDL method, the MFDL method, which performs better than the FDL. We use the FDL numbers to develop possible earthquakes dates but with the important difference that the starting seed date is a trigger planetary aspect prior to the earthquake. Typical planetary aspects are Moon conjunct Sun, Moon opposite Sun, Moon conjunct or opposite North or South Modes. In order to test improvement of the method we used all +8R earthquakes recorded since 1900, (86 earthquakes from USGS data). We have developed the FDL numbers for each of those seeds, and examined the earthquake hit rates (for a window of 3, i.e. +-1 day of target date) and for <6.5R. The successes are counted for each one of the 86 earthquake seeds and we compare the MFDL method with the FDL method. In every case we find improvement when the starting seed date is on the planetary trigger date prior to the earthquake. We observe no improvement only when a planetary trigger coincided with

  13. Usefulness of fecal calprotectin for the early prediction of short-term outcomes of remission-induction treatments in ulcerative colitis in comparison with two-item patient-reported outcome.

    PubMed

    Toyonaga, Takahiko; Kobayashi, Taku; Nakano, Masaru; Saito, Eiko; Umeda, Satoko; Okabayashi, Shinji; Ozaki, Ryo; Hibi, Toshifumi

    2017-01-01

    Fecal calprotectin (FC) is well accepted as a non-invasive biomarker which objectively reflects colonic inflammation in ulcerative colitis (UC). However, its value as a marker of response during the early phase of remission induction treatment has not been well studied. The aim of this study is to evaluate the significance of FC for predicting the short-term outcomes of remission induction treatment in patients with UC. A prospective observational study was conducted among 31 patients with active UC. FC was monitored with two-item patient-reported outcome (PRO2), partial Mayo score (PMS), and Lichtiger clinical activity index (CAI) during the first 4 weeks of remission induction treatment. Clinical response was defined as a decrease in CAI of 3 or more points below baseline. Mucosal healing (MH) was defined as Mayo endoscopic subscore 0 or 1. Within-day and within-stool variability of FC were assessed during the first week of treatment. In week 4-clinical responders, PRO2, PMS, and CAI significantly decreased from day 3, however, FC did not show significant reduction until week 2. Among all markers, the decrease in PRO2 at week 4 most accurately predicted MH at week 12. Within-day variability of FC was remarkably wide even at the first week in clinical responders. Within-stool variability was extremely small. PRO2 predicted the short-term outcomes of remission induction treatment earlier than FC possibly because of the wide within-day variability of FC in active UC.

  14. A test to evaluate the earthquake prediction algorithm, M8

    USGS Publications Warehouse

    Healy, John H.; Kossobokov, Vladimir G.; Dewey, James W.

    1992-01-01

    A test of the algorithm M8 is described. The test is constructed to meet four rules, which we propose to be applicable to the test of any method for earthquake prediction:  1. An earthquake prediction technique should be presented as a well documented, logical algorithm that can be used by  investigators without restrictions. 2. The algorithm should be coded in a common programming language and implementable on widely available computer systems. 3. A test of the earthquake prediction technique should involve future predictions with a black box version of the algorithm in which potentially adjustable parameters are fixed in advance. The source of the input data must be defined and ambiguities in these data must be resolved automatically by the algorithm. 4. At least one reasonable null hypothesis should be stated in advance of testing the earthquake prediction method, and it should be stated how this null hypothesis will be used to estimate the statistical significance of the earthquake predictions. The M8 algorithm has successfully predicted several destructive earthquakes, in the sense that the earthquakes occurred inside regions with linear dimensions from 384 to 854 km that the algorithm had identified as being in times of increased probability for strong earthquakes. In addition, M8 has successfully "post predicted" high percentages of strong earthquakes in regions to which it has been applied in retroactive studies. The statistical significance of previous predictions has not been established, however, and post-prediction studies in general are notoriously subject to success-enhancement through hindsight. Nor has it been determined how much more precise an M8 prediction might be than forecasts and probability-of-occurrence estimates made by other techniques. We view our test of M8 both as a means to better determine the effectiveness of M8 and as an experimental structure within which to make observations that might lead to improvements in the algorithm

  15. Time-predictable recurrence model for large earthquakes

    SciTech Connect

    Shimazaki, K.; Nakata, T.

    1980-04-01

    We present historical and geomorphological evidence of a regularity in earthquake recurrence at three different sites of plate convergence around the Japan arcs. The regularity shows that the larger an earthquake is, the longer is the following quiet period. In other words, the time interval between two successive large earthquakes is approximately proportional to the amount of coseismic displacement of the preceding earthquake and not of the following earthquake. The regularity enables us, in principle, to predict the approximate occurrence time of earthquakes. The data set includes 1) a historical document describing repeated measurements of water depth at Murotsu near the focal region of Nankaido earthquakes, 2) precise levelling and /sup 14/C dating of Holocene uplifted terraces in the southern boso peninsula facing the Sagami trough, and 3) similar geomorphological data on exposed Holocene coral reefs in Kikai Island along the Ryukyu arc.

  16. Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

    PubMed Central

    Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

    2017-01-01

    Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

  17. Onboard Short Term Plan Viewer

    NASA Technical Reports Server (NTRS)

    Hall, Tim; LeBlanc, Troy; Ulman, Brian; McDonald, Aaron; Gramm, Paul; Chang, Li-Min; Keerthi, Suman; Kivlovitz, Dov; Hadlock, Jason

    2011-01-01

    Onboard Short Term Plan Viewer (OSTPV) is a computer program for electronic display of mission plans and timelines, both aboard the International Space Station (ISS) and in ISS ground control stations located in several countries. OSTPV was specifically designed both (1) for use within the limited ISS computing environment and (2) to be compatible with computers used in ground control stations. OSTPV supplants a prior system in which, aboard the ISS, timelines were printed on paper and incorporated into files that also contained other paper documents. Hence, the introduction of OSTPV has both reduced the consumption of resources and saved time in updating plans and timelines. OSTPV accepts, as input, the mission timeline output of a legacy, print-oriented, UNIX-based program called "Consolidated Planning System" and converts the timeline information for display in an interactive, dynamic, Windows Web-based graphical user interface that is used by both the ISS crew and ground control teams in real time. OSTPV enables the ISS crew to electronically indicate execution of timeline steps, launch electronic procedures, and efficiently report to ground control teams on the statuses of ISS activities, all by use of laptop computers aboard the ISS.

  18. Gambling score in earthquake prediction analysis

    NASA Astrophysics Data System (ADS)

    Molchan, G.; Romashkova, L.

    2011-03-01

    The number of successes and the space-time alarm rate are commonly used to characterize the strength of an earthquake prediction method and the significance of prediction results. It has been recently suggested to use a new characteristic to evaluate the forecaster's skill, the gambling score (GS), which incorporates the difficulty of guessing each target event by using different weights for different alarms. We expand parametrization of the GS and use the M8 prediction algorithm to illustrate difficulties of the new approach in the analysis of the prediction significance. We show that the level of significance strongly depends (1) on the choice of alarm weights, (2) on the partitioning of the entire alarm volume into component parts and (3) on the accuracy of the spatial rate measure of target events. These tools are at the disposal of the researcher and can affect the significance estimate. Formally, all reasonable GSs discussed here corroborate that the M8 method is non-trivial in the prediction of 8.0 ≤M < 8.5 events because the point estimates of the significance are in the range 0.5-5 per cent. However, the conservative estimate 3.7 per cent based on the number of successes seems preferable owing to two circumstances: (1) it is based on relative values of the spatial rate and hence is more stable and (2) the statistic of successes enables us to construct analytically an upper estimate of the significance taking into account the uncertainty of the spatial rate measure.

  19. Quantifying characteristic growth dynamics in a semiarid grassland ecosystem by predicting short-term NDVI phenology from daily rainfall: a simple 4 parameter coupled-reservoir model

    USDA-ARS?s Scientific Manuscript database

    Predicting impacts of the magnitude and seasonal timing of rainfall pulses in water-limited grassland ecosystems concerns ecologists, climate scientists, hydrologists, and a variety of stakeholders. This report describes a simple, effective procedure to emulate the seasonal response of grassland bio...

  20. Short-term prediction of Betula airborne pollen concentration in Vigo (NW Spain) using logistic additive models and partially linear models

    NASA Astrophysics Data System (ADS)

    Cotos-Yáñez, Tomas R.; Rodríguez-Rajo, F. J.; Jato, M. V.

    Betula pollen is a common cause of pollinosis in localities in NW Spain and between 13% and 60% of individuals who are immunosensitive to pollen grains respond positively to its allergens. It is important in the case of all such people to be able to predict pollen concentrations in advance. We therefore undertook an aerobiological study in the city of Vigo (Pontevedra, Spain) from 1995 to 2001, using a Hirst active-impact pollen trap (VPPS 2000) situated in the city centre. Vigo presents a temperate maritime climate with a mean annual temperature of 14.9 °C and 1,412 mm annual total precipitation. This paper analyses two ways of quantifying the prediction of pollen concentration: first by means of a generalized additive regression model with the object of predicting whether the series of interest exceeds a certain threshold; second using a partially linear model to obtain specific prediction values for pollen grains. Both models use a self-explicative part and another formed by exogenous meteorological factors. The models were tested with data from 2001 (year in which the total precipitation registered was almost twice the climatological average overall during the flowering period), which were not used in formulating the models. A highly satisfactory classification and good forecasting results were achieved with the first and second approaches respectively. The estimated line taking into account temperature and a calm S-SW wind, corresponds to the real line recorded during 2001, which gives us an idea of the proposed model's validity.

  1. Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study).

    PubMed

    Thomas, Diana M; Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

    2015-03-01

    Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve's capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. © 2015 American Society for Nutrition.

  2. Long-term predictability of regions and dates of strong earthquakes

    NASA Astrophysics Data System (ADS)

    Kubyshen, Alexander; Doda, Leonid; Shopin, Sergey

    2016-04-01

    parameters and seismic events. Further development of the H-104 method is the plotting of H-104 trajectories in two-dimensional time coordinates. The method provides the dates of future earthquakes for several (3-4) sequential time intervals multiple of 104 days. The H-104 method could be used together with the empirical scheme for short-term earthquake prediction reducing the date uncertainty. Using the H-104 method, it is developed the following long-term forecast of seismic activity. 1. The total number of M6+ earthquakes expected in the time frames: - 10.01-07.02: 14; - 08.02-08.03: 17; - 09.03-06.04: 9. 3. The potential days of M6+ earthquakes expected in the period of 10.01.2016-06.04.2016 are the following: - in January: 17, 18, 23, 24, 26, 28, 31; - in February: 01, 02, 05, 12, 15, 18, 20, 23; - in March: 02, 04, 05, 07 (M7+ is possible), 09, 10, 17 (M7+ is possible), 19, 20 (M7+ is possible), 23 (M7+ is possible), 30; - in April: 02, 06. The work was financially supported by the Ministry of Education and Science of the Russian Federation (contract No. 14.577.21.0109, project UID RFMEFI57714X0109)

  3. Role of assessment components and recent adverse outcomes in risk estimation and prediction: Use of the Short Term Assessment of Risk and Treatability (START) in an adult secure inpatient mental health service.

    PubMed

    O'Shea, Laura E; Dickens, Geoffrey L

    2016-06-30

    The Short Term Assessment of Risk and Treatability is a structured judgement tool used to inform risk estimation for multiple adverse outcomes. In research, risk estimates outperform the tool's strength and vulnerability scales for violence prediction. Little is known about what its'component parts contribute to the assignment of risk estimates and how those estimates fare in prediction of non-violent adverse outcomes compared with the structured components. START assessment and outcomes data from a secure mental health service (N=84) was collected. Binomial and multinomial regression analyses determined the contribution of selected elements of the START structured domain and recent adverse risk events to risk estimates and outcomes prediction for violence, self-harm/suicidality, victimisation, and self-neglect. START vulnerabilities and lifetime history of violence, predicted the violence risk estimate; self-harm and victimisation estimates were predicted only by corresponding recent adverse events. Recent adverse events uniquely predicted all corresponding outcomes, with the exception of self-neglect which was predicted by the strength scale. Only for victimisation did the risk estimate outperform prediction based on the START components and recent adverse events. In the absence of recent corresponding risk behaviour, restrictions imposed on the basis of START-informed risk estimates could be unwarranted and may be unethical.

  4. The initial subevent of the 1994 Northridge, California, earthquake: Is earthquake size predictable?

    USGS Publications Warehouse

    Kilb, Debi; Gomberg, J.

    1999-01-01

    We examine the initial subevent (ISE) of the M?? 6.7, 1994 Northridge, California, earthquake in order to discriminate between two end-member rupture initiation models: the 'preslip' and 'cascade' models. Final earthquake size may be predictable from an ISE's seismic signature in the preslip model but not in the cascade model. In the cascade model ISEs are simply small earthquakes that can be described as purely dynamic ruptures. In this model a large earthquake is triggered by smaller earthquakes; there is no size scaling between triggering and triggered events and a variety of stress transfer mechanisms are possible. Alternatively, in the preslip model, a large earthquake nucleates as an aseismically slipping patch in which the patch dimension grows and scales with the earthquake's ultimate size; the byproduct of this loading process is the ISE. In this model, the duration of the ISE signal scales with the ultimate size of the earthquake, suggesting that nucleation and earthquake size are determined by a more predictable, measurable, and organized process. To distinguish between these two end-member models we use short period seismograms recorded by the Southern California Seismic Network. We address questions regarding the similarity in hypocenter locations and focal mechanisms of the ISE and the mainshock. We also compare the ISE's waveform characteristics to those of small earthquakes and to the beginnings of earthquakes with a range of magnitudes. We find that the focal mechanisms of the ISE and mainshock are indistinguishable, and both events may have nucleated on and ruptured the same fault plane. These results satisfy the requirements for both models and thus do not discriminate between them. However, further tests show the ISE's waveform characteristics are similar to those of typical small earthquakes in the vicinity and more importantly, do not scale with the mainshock magnitude. These results are more consistent with the cascade model.

  5. Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study)123

    PubMed Central

    Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

    2015-01-01

    Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve’s capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Results: Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). Conclusions: The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. The POUNDS Lost study was registered at clinicaltrials.gov as NCT00072995. PMID:25733628

  6. Short Term Exogenic Climate Change Forcing

    NASA Astrophysics Data System (ADS)

    Krahenbuhl, Daniel

    Several short term exogenic forcings affecting Earth's climate are but recently identified. Lunar nutation periodicity has implications for numerical meteorological prediction. Abrupt shifts in solar wind bulk velocity, particle density, and polarity exhibit correlation with terrestrial hemispheric vorticity changes, cyclonic strengthening and the intensification of baroclinic disturbances. Galactic Cosmic ray induced tropospheric ionization modifies cloud microphysics, and modulates the global electric circuit. This dissertation is constructed around three research questions: (1): What are the biweekly declination effects of lunar gravitation upon the troposphere? (2): How do United States severe weather reports correlate with heliospheric current sheet crossings? and (3): How does cloud cover spatially and temporally vary with galactic cosmic rays? Study 1 findings show spatial consistency concerning lunar declination extremes upon Rossby longwaves. Due to the influence of Rossby longwaves on synoptic scale circulation, our results could theoretically extend numerical meteorological forecasting. Study 2 results indicate a preference for violent tornadoes to occur prior to a HCS crossing. Violent tornadoes (EF3+) are 10% more probable to occur near, and 4% less probable immediately after a HCS crossing. The distribution of hail and damaging wind reports do not mirror this pattern. Polarity is critical for the effect. Study 3 results confirm anticorrelation between solar flux and low-level marine-layer cloud cover, but indicate substantial regional variability between cloud cover altitude and GCRs. Ultimately, this dissertation serves to extend short term meteorological forecasting, enhance climatological modeling and through analysis of severe violent weather and heliospheric events, protect property and save lives.

  7. The 2008 Wenchuan Earthquake and the Rise and Fall of Earthquake Prediction in China

    NASA Astrophysics Data System (ADS)

    Chen, Q.; Wang, K.

    2009-12-01

    Regardless of the future potential of earthquake prediction, it is presently impractical to rely on it to mitigate earthquake disasters. The practical approach is to strengthen the resilience of our built environment to earthquakes based on hazard assessment. But this was not common understanding in China when the M 7.9 Wenchuan earthquake struck the Sichuan Province on 12 May 2008, claiming over 80,000 lives. In China, earthquake prediction is a government-sanctioned and law-regulated measure of disaster prevention. A sudden boom of the earthquake prediction program in 1966-1976 coincided with a succession of nine M > 7 damaging earthquakes in the densely populated region of the country and the political chaos of the Cultural Revolution. It climaxed with the prediction of the 1975 Haicheng earthquake, which was due mainly to an unusually pronounced foreshock sequence and the extraordinary readiness of some local officials to issue imminent warning and evacuation order. The Haicheng prediction was a success in practice and yielded useful lessons, but the experience cannot be applied to most other earthquakes and cultural environments. Since the disastrous Tangshan earthquake in 1976 that killed over 240,000 people, there have been two opposite trends in China: decreasing confidence in prediction and increasing emphasis on regulating construction design for earthquake resilience. In 1976, most of the seismic intensity XI areas of Tangshan were literally razed to the ground, but in 2008, many buildings in the intensity XI areas of Wenchuan did not collapse. Prediction did not save life in either of these events; the difference was made by construction standards. For regular buildings, there was no seismic design in Tangshan to resist any earthquake shaking in 1976, but limited seismic design was required for the Wenchuan area in 2008. Although the construction standards were later recognized to be too low, those buildings that met the standards suffered much less

  8. Introduction to the special issue on the 2004 Parkfield earthquake and the Parkfield earthquake prediction experiment

    USGS Publications Warehouse

    Harris, R.A.; Arrowsmith, J.R.

    2006-01-01

    The 28 September 2004 M 6.0 Parkfield earthquake, a long-anticipated event on the San Andreas fault, is the world's best recorded earthquake to date, with state-of-the-art data obtained from geologic, geodetic, seismic, magnetic, and electrical field networks. This has allowed the preearthquake and postearthquake states of the San Andreas fault in this region to be analyzed in detail. Analyses of these data provide views into the San Andreas fault that show a complex geologic history, fault geometry, rheology, and response of the nearby region to the earthquake-induced ground movement. Although aspects of San Andreas fault zone behavior in the Parkfield region can be modeled simply over geological time frames, the Parkfield Earthquake Prediction Experiment and the 2004 Parkfield earthquake indicate that predicting the fine details of future earthquakes is still a challenge. Instead of a deterministic approach, forecasting future damaging behavior, such as that caused by strong ground motions, will likely continue to require probabilistic methods. However, the Parkfield Earthquake Prediction Experiment and the 2004 Parkfield earthquake have provided ample data to understand most of what did occur in 2004, culminating in significant scientific advances.

  9. Soviet prediction of a major earthquake

    USGS Publications Warehouse

    Simpson, D.W.

    1979-01-01

    On November 1, 1978, a magnitude 7 earthquake occurred north of the Pamir Mountains near the Tadjiskistan-Kirghizia border, 150 kilometers east of Garm in Soviet Central Asia. Although the earthquake was felt in Tashkent, Dushanbe, and the Fergana Valley, the epicentral area was uninhabited at that time of year, and no damage was reported. 

  10. External validation of the simple clinical score and the HOTEL score, two scores for predicting short-term mortality after admission to an acute medical unit.

    PubMed

    Stræde, Mia; Brabrand, Mikkel

    2014-01-01

    Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Pre-planned prospective observational cohort study. Danish 460-bed regional teaching hospital. We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774-0.879) for 30-day mortality, and goodness-of-fit test, χ(2) = 2.68 (10 degrees of freedom), P = 0.998 and χ(2) = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901-0.962) for 24-hours mortality and goodness-of-fit test, χ(2) = 5.56 (10 degrees of freedom), P = 0.234. We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision.

  11. External Validation of the Simple Clinical Score and the HOTEL Score, Two Scores for Predicting Short-Term Mortality after Admission to an Acute Medical Unit

    PubMed Central

    Stræde, Mia; Brabrand, Mikkel

    2014-01-01

    Background Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Methods Pre-planned prospective observational cohort study. Setting Danish 460-bed regional teaching hospital. Findings We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774–0.879) for 30-day mortality, and goodness-of-fit test, χ2 = 2.68 (10 degrees of freedom), P = 0.998 and χ2 = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901–0.962) for 24-hours mortality and goodness-of-fit test, χ2 = 5.56 (10 degrees of freedom), P = 0.234. Conclusion We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision. PMID:25144186

  12. Magnetic resonance imaging-based measures predictive of short-term surgical outcome in patients with Chiari malformation Type I: a pilot study.

    PubMed

    Alperin, Noam; Loftus, James Ryan; Bagci, Ahmet M; Lee, Sang H; Oliu, Carlos J; Shah, Ashish H; Green, Barth A

    2017-01-01

    OBJECTIVE This study identifies quantitative imaging-based measures in patients with Chiari malformation Type I (CM-I) that are associated with positive outcomes after suboccipital decompression with duraplasty. METHODS Fifteen patients in whom CM-I was newly diagnosed underwent MRI preoperatively and 3 months postoperatively. More than 20 previously described morphological and physiological parameters were derived to assess quantitatively the impact of surgery. Postsurgical clinical outcomes were assessed in 2 ways, based on resolution of the patient's chief complaint and using a modified Chicago Chiari Outcome Scale (CCOS). Statistical analyses were performed to identify measures that were different between the unfavorable- and favorable-outcome cohorts. Multivariate analysis was used to identify the strongest predictors of outcome. RESULTS The strongest physiological parameter predictive of outcome was the preoperative maximal cord displacement in the upper cervical region during the cardiac cycle, which was significantly larger in the favorable-outcome subcohorts for both outcome types (p < 0.05). Several hydrodynamic measures revealed significantly larger preoperative-to-postoperative changes in the favorable-outcome subcohort. Predictor sets for the chief-complaint classification included the cord displacement, percent venous drainage through the jugular veins, and normalized cerebral blood flow with 93.3% accuracy. Maximal cord displacement combined with intracranial volume change predicted outcome based on the modified CCOS classification with similar accuracy. CONCLUSIONS Tested physiological measures were stronger predictors of outcome than the morphological measures in patients with CM-I. Maximal cord displacement and intracranial volume change during the cardiac cycle together with a measure that reflects the cerebral venous drainage pathway emerged as likely predictors of decompression outcome in patients with CM-I.

  13. A short-term ionospheric forecasting empirical regional model (IFERM) to predict the critical frequency of the F2 layer during moderate, disturbed, and very disturbed geomagnetic conditions over the European area

    NASA Astrophysics Data System (ADS)

    Pietrella, M.

    2012-02-01

    A short-term ionospheric forecasting empirical regional model (IFERM) has been developed to predict the state of the critical frequency of the F2 layer (foF2) under different geomagnetic conditions. IFERM is based on 13 short term ionospheric forecasting empirical local models (IFELM) developed to predict foF2 at 13 ionospheric observatories scattered around the European area. The forecasting procedures were developed by taking into account, hourly measurements of foF2, hourly quiet-time reference values of foF2 (foF2QT), and the hourly time-weighted accumulation series derived from the geomagnetic planetary index ap, (ap(τ)), for each observatory. Under the assumption that the ionospheric disturbance index ln(foF2/foF2QT) is correlated to the integrated geomagnetic disturbance index ap(τ), a set of statistically significant regression coefficients were established for each observatory, over 12 months, over 24 h, and under 3 different ranges of geomagnetic activity. This data was then used as input to compute short-term ionospheric forecasting of foF2 at the 13 local stations under consideration. The empirical storm-time ionospheric correction model (STORM) was used to predict foF2 in two different ways: scaling both the hourly median prediction provided by IRI (STORM_foF2MED,IRI model), and the foF2QT values (STORM_foF2QT model) from each local station. The comparison between the performance of STORM_foF2MED,IRI, STORM_foF2QT, IFELM, and the foF2QT values, was made on the basis of root mean square deviation (r.m.s.) for a large number of periods characterized by moderate, disturbed, and very disturbed geomagnetic activity. The results showed that the 13 IFELM perform much better than STORM_foF2,sub>MED,IRI and STORM_foF2QT especially in the eastern part of the European area during the summer months (May, June, July, and August) and equinoctial months (March, April, September, and October) under disturbed and very disturbed geomagnetic conditions, respectively

  14. A New Bayesian Network-Based Risk Stratification Model for Prediction of Short-term and Long-term LVAD Mortality

    PubMed Central

    Loghmanpour, Natasha A.; Kanwar, Manreet K.; Druzdzel, Marek J.; Benza, Raymond L.; Murali, Srinivas; Antaki, James F.

    2015-01-01

    Existing risk assessment tools for patient selection for left ventricular assist devices (LVADs) such as the Destination Therapy Risk Score (DTRS) and HeartMate II Risk Score (HMRS) have limited predictive ability. This study aims to overcome the limitations of traditional statistical methods by performing the first application of Bayesian analysis to the comprehensive INTERMACS dataset and comparing it to HMRS. We retrospectively analyzed 8,050 continuous flow (CF) LVAD patients and 226 pre-implant variables. We then derived Bayesian models for mortality at each of five time endpoints post-implant (30 day, 90 day, 6 month, 1 year, and 2 year), achieving accuracies of 95, 90, 90, 83, and 78%, Kappa values of 0.43, 0.37, 0.37, 0.45, and 0.43, and area under the ROC of 91, 82, 82, 80 and 81% respectively. This was in comparison to the HMRS with an ROC of 57 and 60% at 90-days and 1-year, respectively. Pre-implant interventions such as dialysis, ECMO, and ventilators were major contributing risk markers. Bayesian models have the ability to reliably represent the complex causal relationships of multiple variables on clinical outcomes. Their potential to develop a reliable risk stratification tool for use in clinical decision making on LVAD patients encourages further investigation. PMID:25710772

  15. A new Bayesian network-based risk stratification model for prediction of short-term and long-term LVAD mortality.

    PubMed

    Loghmanpour, Natasha A; Kanwar, Manreet K; Druzdzel, Marek J; Benza, Raymond L; Murali, Srinivas; Antaki, James F

    2015-01-01

    Existing risk assessment tools for patient selection for left ventricular assist devices (LVADs) such as the Destination Therapy Risk Score and HeartMate II Risk Score (HMRS) have limited predictive ability. This study aims to overcome the limitations of traditional statistical methods by performing the first application of Bayesian analysis to the comprehensive Interagency Registry for Mechanically Assisted Circulatory Support dataset and comparing it to HMRS. We retrospectively analyzed 8,050 continuous flow LVAD patients and 226 preimplant variables. We then derived Bayesian models for mortality at each of five time end-points postimplant (30 days, 90 days, 6 month, 1 year, and 2 years), achieving accuracies of 95%, 90%, 90%, 83%, and 78%, Kappa values of 0.43, 0.37, 0.37, 0.45, and 0.43, and area under the receiver operator characteristic (ROC) of 91%, 82%, 82%, 80%, and 81%, respectively. This was in comparison to the HMRS with an ROC of 57% and 60% at 90 days and 1 year, respectively. Preimplant interventions, such as dialysis, ECMO, and ventilators were major contributing risk markers. Bayesian models have the ability to reliably represent the complex causal relations of multiple variables on clinical outcomes. Their potential to develop a reliable risk stratification tool for use in clinical decision making on LVAD patients encourages further investigation.

  16. Quantitative Earthquake Prediction on Global and Regional Scales

    SciTech Connect

    Kossobokov, Vladimir G.

    2006-03-23

    The Earth is a hierarchy of volumes of different size. Driven by planetary convection these volumes are involved into joint and relative movement. The movement is controlled by a wide variety of processes on and around the fractal mesh of boundary zones, and does produce earthquakes. This hierarchy of movable volumes composes a large non-linear dynamical system. Prediction of such a system in a sense of extrapolation of trajectory into the future is futile. However, upon coarse-graining the integral empirical regularities emerge opening possibilities of prediction in a sense of the commonly accepted consensus definition worked out in 1976 by the US National Research Council. Implications of the understanding hierarchical nature of lithosphere and its dynamics based on systematic monitoring and evidence of its unified space-energy similarity at different scales help avoiding basic errors in earthquake prediction claims. They suggest rules and recipes of adequate earthquake prediction classification, comparison and optimization. The approach has already led to the design of reproducible intermediate-term middle-range earthquake prediction technique. Its real-time testing aimed at prediction of the largest earthquakes worldwide has proved beyond any reasonable doubt the effectiveness of practical earthquake forecasting. In the first approximation, the accuracy is about 1-5 years and 5-10 times the anticipated source dimension. Further analysis allows reducing spatial uncertainty down to 1-3 source dimensions, although at a cost of additional failures-to-predict. Despite of limited accuracy a considerable damage could be prevented by timely knowledgeable use of the existing predictions and earthquake prediction strategies. The December 26, 2004 Indian Ocean Disaster seems to be the first indication that the methodology, designed for prediction of M8.0+ earthquakes can be rescaled for prediction of both smaller magnitude earthquakes (e.g., down to M5.5+ in Italy) and

  17. Predictive capacity of a multimarker strategy to determine short-term mortality in patients attending a hospital emergency Department for acute heart failure. BIO-EAHFE study.

    PubMed

    Herrero-Puente, Pablo; Prieto-García, Belén; García-García, María; Jacob, Javier; Martín-Sánchez, F Javier; Pascual-Figal, Domingo; Bueno, Héctor; Gil, Victor; Llorens, Pere; Vázquez-Alvarez, Joaquin; Romero-Pareja, Rodolfo; Sanchez-Gonzalez, Marta; Miró, Òscar

    2017-03-01

    A multimarker strategy may help determine the prognosis of patients with acute heart failure (AHF). The aim of this study was to evaluate the capacity of mid-regional pro-adrenomedullin (MRproADM), copeptin and interleukin-6 (IL-6) combined with conventional clinical and biochemical markers to predict the 30-day mortality of patients with AHF. We performed an observational, multicenter, prospective study of patients attended in the emergency department (ED) for AHF. We collected clinical and biochemical data as well as comorbidities and biomarker values. The endpoint variable was mortality at 7, 14, 30, 90 and 180days. The clinical model included: gender, age, blood pressure values, hemoglobin, sodium <135mmol/L and estimated glomerular filtration <60mL/min/1.73m2. We made receiver operating curves (ROC) curves, and areas under the curve (AUC) and survival analysis for each model and calculated the hazard ratio (HR) and its 95% confidence interval. A total of 547 individuals were included: 55.6% were women with a mean age of 79.9 (9.5) years. Copeptin alone showed greater discriminatory power for 30-mortality [AUC 0.70 (0.62-0.78)]. The AUC for 30-day mortality of the clinical model plus copeptin and NTproBNP was 0.75 (0.67-0.83), being better than the clinical model alone with 0.67 (0.58-0.76; p=0.19). The discriminatory power of the different biomarkers alone, in combination or together with the clinical model decreased over time. The combination of a clinical model with copeptin and NTproBNP, which are available in the ED, is able to prognose early mortality in patients with an episode of AHF. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Low immediate postoperative serum-cortisol nadir predicts the short-term, but not long-term, remission after pituitary surgery for Cushing's disease.

    PubMed

    Ramm-Pettersen, Jon; Halvorsen, Helene; Evang, Johan Arild; Rønning, Pål; Hol, Per Kristian; Bollerslev, Jens; Berg-Johnsen, Jon; Helseth, Eirik

    2015-10-25

    Cushing's disease is an ACTH-producing pituitary adenoma, and the primary treatment is microscopic or endoscopic transsphenoidal selective adenectomy. The aims of the present study were to evaluate whether the early postoperative S-cortisol level can serve as a prognostic marker for short- and long-term remission, and retrospectively review our own short and long term results after surgery for Cushing's disease. This single centre, retrospective study consists of 19 consecutive patients with Cushing's disease who underwent transsphenoidal surgery. S-cortisol was measured every 6 h after the operation without any glucocorticoid replacement. We have follow-up on all patients, with a mean follow-up of 68 months. At the three-month follow-up, 16 patients (84 %) were in remission; at 12 months, 18 (95 %) were in remission and at the final follow-up (mean 68 months), 13 (68 %) were in remission. Five-years recurrence rate was 26 %. The mean postoperative S-cortisol nadir was significantly lower in the group of patients in remission than in the non-remission group at 3 months, but there was no difference between those in long-term remission compared to those in long-term non-remission. The optimal cut-off value for classifying 3-month remission was 74 nmol/l. We achieved a 95 % 1-year remission rate with transsphenoidal surgery for Cushing's disease in this series of consecutive patients. However, the 5-year recurrence rate was 26 %, showing the need for regular clinical and biochemical controls in this patient group. The mean postoperative serum-cortisol nadir was significantly lower in patients in remission at 3 months compared to patients not in remission at 3 months, but a low postoperative S-cortisol did not predict long-term remission.

  19. Atmospheric emissions of Cu and Zn from coal combustion in China: Spatio-temporal distribution, human health effects, and short-term prediction.

    PubMed

    Li, Rui; Li, Junlin; Cui, Lulu; Wu, Yu; Fu, Hongbo; Chen, Jianmin; Chen, Mindong

    2017-10-01

    China has become the largest coal consumer and important emitter of trace metals in the world. A multiple-year inventory of atmospheric copper (Cu) and zinc (Zn) emissions from coal combustion in 30 provinces of China and 4 economic sectors (power plant, industry sector, residential sector, and others) for the period of 1995-2014 has been calculated. The results indicated that the total emissions of Cu and Zn increased from 5137.70 t and 11484.16 t in 1995-7099.24 t and 14536.61 t in 2014, at an annual average growth rate of 1.90% and 1.33%, respectively. The industrial sector ranked as the leading source, followed by power plants, the residential use, and other sectors. The emissions of Cu and Zn were predominantly concentrated in the northern and eastern regions of China due to the enormous consumption of coal by the industrial and the power sectors. The emissions of Cu and Zn were closely associated with mortality and life expectancy (LE) on the basis of multiple regression analysis. Spatial econometric models suggested that Cu and Zn emissions displayed significantly positive relevance with mortality, while they exhibited negative correlation with LE. The influence of the Cu emission peaked in the north of China for both mortality and LE, while the impacts of the Zn emission on mortality and LE reached a maximum value in Xinjiang Province. The results of the grey prediction model suggested that the Cu emission would decrease to 5424.73 t, whereas the Zn emissions could reach 17402.13 t in 2020. Analysis of more specific data are imperative in order to estimate the emissions of both metals, to assess their human health effects, and then to adopt effective measures to prevent environmental pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Admission white blood cell count predicts short-term clinical outcomes in patients with uncomplicated Stanford type B acute aortic dissection

    PubMed Central

    Chen, Zhao-Ran; Huang, Bi; Lu, Hai-Song; Zhao, Zhen-Hua; Hui, Ru-Tai; Yang, Yan-Min; Fan, Xiao-Han

    2017-01-01

    Objectives Inflammation has been shown to be related with acute aortic dissection (AAD). The present study aimed to evaluate the association of white blood cell counts (WBCc) on admission with both in-hospital and long-term all-cause mortality in patients with uncomplicated Stanford type B AAD. Methods From 2008 to 2010, a total of 377 consecutive patients with uncomplicated type B AAD were enrolled and then followed up. Clinical data and WBCc on admission were collected. The primary end points were in-hospital death and long-term all-cause death. Results The in-hospital death rate was 4.2%, and the long-term all-cause mortality rate was 6.9% during a median follow-up of 18.9 months. WBCc on admission was identified as a risk factor for in-hospital death by univariate Cox regression analysis as both a continuous variable and a categorical variable using a cut off of 11.0 × 109 cell/L (all P < 0.05). After adjusting for age, sex and other risk factors, elevated admission WBCc was still a significant predictor for in-hospital death as both a continuous variable [hazard ratio (HR): 1.052, 95% CI: 1.024–1.336, P = 0.002] and a categorical variable using a cut off of 11.0 × 109 cell/L (HR: 2.056, 95% CI: 1.673–5.253, P = 0.034). No relationship was observed between WBCc on admission and long-term all-cause death. Conclusions Our results indicate that elevated WBCc upon admission might be used as a predictor for increased risk of in-hospital death in uncomplicated type B AAD. There might be no predictive value of WBCc for the long-term survival of type B AAD. PMID:28270842

  1. Earthquake prediction: the interaction of public policy and science.

    PubMed

    Jones, L M

    1996-04-30

    Earthquake prediction research has searched for both informational phenomena, those that provide information about earthquake hazards useful to the public, and causal phenomena, causally related to the physical processes governing failure on a fault, to improve our understanding of those processes. Neither informational nor causal phenomena are a subset of the other. I propose a classification of potential earthquake predictors of informational, causal, and predictive phenomena, where predictors are causal phenomena that provide more accurate assessments of the earthquake hazard than can be gotten from assuming a random distribution. Achieving higher, more accurate probabilities than a random distribution requires much more information about the precursor than just that it is causally related to the earthquake.

  2. Earthquake prediction: the interaction of public policy and science.

    PubMed Central

    Jones, L M

    1996-01-01

    Earthquake prediction research has searched for both informational phenomena, those that provide information about earthquake hazards useful to the public, and causal phenomena, causally related to the physical processes governing failure on a fault, to improve our understanding of those processes. Neither informational nor causal phenomena are a subset of the other. I propose a classification of potential earthquake predictors of informational, causal, and predictive phenomena, where predictors are causal phenomena that provide more accurate assessments of the earthquake hazard than can be gotten from assuming a random distribution. Achieving higher, more accurate probabilities than a random distribution requires much more information about the precursor than just that it is causally related to the earthquake. PMID:11607656

  3. Earthquake prediction: The interaction of public policy and science

    USGS Publications Warehouse

    Jones, L.M.

    1996-01-01

    Earthquake prediction research has searched for both informational phenomena, those that provide information about earthquake hazards useful to the public, and causal phenomena, causally related to the physical processes governing failure on a fault, to improve our understanding of those processes. Neither informational nor causal phenomena are a subset of the other. I propose a classification of potential earthquake predictors of informational, causal, and predictive phenomena, where predictors are causal phenomena that provide more accurate assessments of the earthquake hazard than can be gotten from assuming a random distribution. Achieving higher, more accurate probabilities than a random distribution requires much more information about the precursor than just that it is causally related to the earthquake.

  4. Use of the low-frequency/high-frequency ratio of heart rate variability to predict short-term deterioration in emergency department patients with sepsis.

    PubMed

    Barnaby, Douglas P; Fernando, Shannon M; Ferrick, Kevin J; Herry, Christophe L; Seely, Andrew J E; Bijur, Polly E; Gallagher, E John

    2017-08-18

    To examine the ability of the low-frequency/high-frequency (LF/HF) ratio of heart rate variability (HRV) analysis to identify patients with sepsis at risk of early deterioration. This is a prospective observational cohort study of patients with sepsis presenting to the Montefiore Medical Center ED from December 2014 through September 2015. On presentation, a single ECG Holter recording was obtained and analysed to obtain the LF/HF ratio of HRV. Initial Sequential Organ Failure Assessment (SOFA) scores were computed. Patients were followed for 72 hours to identify those with early deterioration. 466 patients presenting to the ED with sepsis were analysed. Thirty-two (7%) reached at least one endpoint within 72 hours. An LF/HF ratio <1 had a sensitivity and specificity of 34% (95% CI (19% to 53%)) and 82% (95% CI (78% to 85%)), respectively, with positive and negative likelihood ratios of 1.9 (95% CI (1.1 to 3.2)) and 0.8 (95% CI (0.6 to 1.0)). An initial SOFA score ≥3 had a sensitivity and specificity of 38% (95% CI (22% to 56%)) and 92% (95% CI (89% to 95%)), with positive and negative likelihood ratios of 4.9 (95% CI (2.8 to 8.6)) and 0.7 (95% CI (0.5 to 0.9)). The composite measure of HRV+SOFA had improved sensitivity (56%, 95% CI (38% to 73%)) but at the expense of specificity (77%, 95% CI (72% to 80%)), with positive and negative likelihood ratios of 2.4 (95% CI (1.7 to 3.4)) and 0.6 (95% CI (0.4 to 0.9)). Receiver operating characteristic analysis did not identify a superior alternate threshold for the LF/HF ratio. Kaplan-Meier survival functions differed significantly (p=0.02) between low (<1) and high (≥1) LF/HF groups. While we found a statistically significant relationship between HRV, SOFA and HRV+SOFA, and early deterioration, none reliably functioned as a clinical predictive tool. More complex multivariable models will likely be required to construct models with clinical utility. © Article author(s) (or their employer(s) unless otherwise

  5. Economics of solar energy: Short term costing

    NASA Astrophysics Data System (ADS)

    Klee, H.

    The solar economics based on life cycle costs are refuted as both imaginary and irrelevant. It is argued that predicting rates of inflation and fuel escalation, expected life, maintenance costs, and legislation over the next ten to twenty years is pure guesswork. Furthermore, given the high mobility level of the U.S. population, the average consumer is skeptical of long run arguments which will pay returns only to the next owners. In the short term cost analysis, the house is sold prior to the end of the expected life of the system. The cash flow of the seller and buyer are considered. All the relevant factors, including the federal tax credit and the added value of the house because of the solar system are included.

  6. Multiple asperity model for earthquake prediction

    USGS Publications Warehouse

    Wyss, M.; Johnston, A.C.; Klein, F.W.

    1981-01-01

    Large earthquakes often occur as multiple ruptures reflecting strong variations of stress level along faults. Dense instrument networks with which the volcano Kilauea is monitored provided detailed data on changes of seismic velocity, strain accumulation and earthquake occurrence rate before the 1975 Hawaii 7.2-mag earthquake. During the ???4 yr of preparation time the mainshock source volume had separated into crustal volumes of high stress levels embedded in a larger low-stress volume, showing respectively high- and low-stress precursory anomalies. ?? 1981 Nature Publishing Group.

  7. Implications of fault constitutive properties for earthquake prediction.

    PubMed

    Dieterich, J H; Kilgore, B

    1996-04-30

    The rate- and state-dependent constitutive formulation for fault slip characterizes an exceptional variety of materials over a wide range of sliding conditions. This formulation provides a unified representation of diverse sliding phenomena including slip weakening over a characteristic sliding distance Dc, apparent fracture energy at a rupture front, time-dependent healing after rapid slip, and various other transient and slip rate effects. Laboratory observations and theoretical models both indicate that earthquake nucleation is accompanied by long intervals of accelerating slip. Strains from the nucleation process on buried faults generally could not be detected if laboratory values of Dc apply to faults in nature. However, scaling of Dc is presently an open question and the possibility exists that measurable premonitory creep may precede some earthquakes. Earthquake activity is modeled as a sequence of earthquake nucleation events. In this model, earthquake clustering arises from sensitivity of nucleation times to the stress changes induced by prior earthquakes. The model gives the characteristic Omori aftershock decay law and assigns physical interpretation to aftershock parameters. The seismicity formulation predicts large changes of earthquake probabilities result from stress changes. Two mechanisms for foreshocks are proposed that describe observed frequency of occurrence of foreshock-mainshock pairs by time and magnitude. With the first mechanism, foreshocks represent a manifestation of earthquake clustering in which the stress change at the time of the foreshock increases the probability of earthquakes at all magnitudes including the eventual mainshock. With the second model, accelerating fault slip on the mainshock nucleation zone triggers foreshocks.

  8. Short-term intercultural psychotherapy: ethnographic inquiry.

    PubMed

    Seeley, Karen M

    2004-01-01

    This article examines the challenges specific to short-term intercultural treatments and recently developed approaches to intercultural treatments based on notions of cultural knowledge and cultural competence. The article introduces alternative approaches to short-term intercultural treatments based on ethnographic inquiry adapted for clinical practice. Such approaches allow clinicians conducting short-term intercultural treatments to foreground clients' indigenous conceptions of selfhood, mind, relationship, and emotional disturbance, and thus to more fully grasp their internal, interpersonal, and external worlds. This article demonstrates the uses of clinically adapted ethnographic inquiry in three short-term intercultural cases.

  9. Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

    ERIC Educational Resources Information Center

    Seeley, Karen M.

    2004-01-01

    This article examines the challenges specific to short-term intercultural treatments and recently developed approaches to intercultural treatments based on notions of cultural knowledge and cultural competence. The article introduces alternative approaches to short-term intercultural treatments based on ethnographic inquiry adapted for clinical…

  10. Prospects for earthquake prediction and control

    USGS Publications Warehouse

    Healy, J.H.; Lee, W.H.K.; Pakiser, L.C.; Raleigh, C.B.; Wood, M.D.

    1972-01-01

    The San Andreas fault is viewed, according to the concepts of seafloor spreading and plate tectonics, as a transform fault that separates the Pacific and North American plates and along which relative movements of 2 to 6 cm/year have been taking place. The resulting strain can be released by creep, by earthquakes of moderate size, or (as near San Francisco and Los Angeles) by great earthquakes. Microearthquakes, as mapped by a dense seismograph network in central California, generally coincide with zones of the San Andreas fault system that are creeping. Microearthquakes are few and scattered in zones where elastic energy is being stored. Changes in the rate of strain, as recorded by tiltmeter arrays, have been observed before several earthquakes of about magnitude 4. Changes in fluid pressure may control timing of seismic activity and make it possible to control natural earthquakes by controlling variations in fluid pressure in fault zones. An experiment in earthquake control is underway at the Rangely oil field in Colorado, where the rates of fluid injection and withdrawal in experimental wells are being controlled. ?? 1972.

  11. Tracking Earthquake Cascades

    NASA Astrophysics Data System (ADS)

    Jordan, T. H.

    2011-12-01

    In assessing their risk to society, earthquakes are best characterized as cascades that can propagate from the natural environment into the socio-economic (built) environment. Strong earthquakes rarely occur as isolated events; they usually cluster in foreshock-mainshock-aftershock sequences, seismic swarms, and extended sequences of large earthquakes that propagate along major fault systems. These cascades are regulated by stress-mediated interactions among faults driven by tectonic loading. Within these cascades, each large event can itself cause a chain reaction in which the primary effects of faulting and ground shaking induce secondary effects, including tsunami, landslides, liquefaction, and set off destructive processes within the built environment, such as fires and radiation leakage from nuclear plants. Recent earthquakes have demonstrated how the socio-economic effects of large earthquakes can reverberate for many years. To reduce earthquake risk and improve the resiliency of communities to earthquake damage, society depends on five geotechnologies for tracking earthquake cascades: long-term probabilistic seismic hazard analysis (PSHA), short-term (operational) earthquake forecasting, earthquake early warning, tsunami warning, and the rapid production of post-event information for response and recovery (see figure). In this presentation, I describe how recent advances in earthquake system science are leading to improvements in this geotechnology pipeline. In particular, I will highlight the role of earthquake simulations in predicting strong ground motions and their secondary effects before and during earthquake cascades

  12. In-situ fluid-pressure measurements for earthquake prediction: An example from a deep well at Hi Vista, California

    USGS Publications Warehouse

    Healy, J.H.; Urban, T.C.

    1985-01-01

    Short-term earthquake prediction requires sensitive instruments for measuring the small anomalous changes in stress and strain that precede earthquakes. Instruments installed at or near the surface have proven too noisy for measuring anomalies of the size expected to occur, and it is now recognized that even to have the possibility of a reliable earthquake-prediction system will require instruments installed in drill holes at depths sufficient to reduce the background noise to a level below that of the expected premonitory signals. We are conducting experiments to determine the maximum signal-to-noise improvement that can be obtained in drill holes. In a 592 m well in the Mojave Desert near Hi Vista, California, we measured water-level changes with amplitudes greater than 10 cm, induced by earth tides. By removing the effects of barometric pressure and the stress related to earth tides, we have achieved a sensitivity to volumetric strain rates of 10-9 to 10-10 per day. Further improvement may be possible, and it appears that a successful earthquake-prediction capability may be achieved with an array of instruments installed in drill holes at depths of about 1 km, assuming that the premonitory strain signals are, in fact, present. ?? 1985 Birkha??user Verlag.

  13. Risk and return: evaluating Reverse Tracing of Precursors earthquake predictions

    NASA Astrophysics Data System (ADS)

    Zechar, J. Douglas; Zhuang, Jiancang

    2010-09-01

    In 2003, the Reverse Tracing of Precursors (RTP) algorithm attracted the attention of seismologists and international news agencies when researchers claimed two successful predictions of large earthquakes. These researchers had begun applying RTP to seismicity in Japan, California, the eastern Mediterranean and Italy; they have since applied it to seismicity in the northern Pacific, Oregon and Nevada. RTP is a pattern recognition algorithm that uses earthquake catalogue data to declare alarms, and these alarms indicate that RTP expects a moderate to large earthquake in the following months. The spatial extent of alarms is highly variable and each alarm typically lasts 9 months, although the algorithm may extend alarms in time and space. We examined the record of alarms and outcomes since the prospective application of RTP began, and in this paper we report on the performance of RTP to date. To analyse these predictions, we used a recently developed approach based on a gambling score, and we used a simple reference model to estimate the prior probability of target earthquakes for each alarm. Formally, we believe that RTP investigators did not rigorously specify the first two `successful' predictions in advance of the relevant earthquakes; because this issue is contentious, we consider analyses with and without these alarms. When we included contentious alarms, RTP predictions demonstrate statistically significant skill. Under a stricter interpretation, the predictions are marginally unsuccessful.

  14. Prediction of Future Great Earthquake Locations from Cumulative Stresses Released by Prior Earthquakes

    NASA Astrophysics Data System (ADS)

    Lee, J.; Hong, T. K.

    2014-12-01

    There are 17 great earthquakes with magnitude greater than or equal to 8.5 in the world since 1900. The great events cause significant damages to the humanity. The prediction of potential maximum magnitudes of earthquakes is important for seismic hazard mitigation. In this study, we calculate the Coulomb stress changes around the active plate margins for 507 events with magnitudes greater than 7.0 during 1976-2013 to estimate the cumulative stress releases. We investigate the spatio-temporal variations of ambient stress field from the cumulative Coulomb stress changes as a function of plate motion speed, plate age and dipping angle. It is observed that the largest stress drop occur in relatively high plate velocity in the convergent margins between Nazca and South American plates, between Pacific and North American plates, between Philippine Sea and Eurasian plates, and between Pacific and Australian plates. It is intriguing to note that the great earthquakes such as Tohoku-Oki earthquake and Maule earthquake occur in the highest plate velocity. On the other hand, the largest stress drop occur in the margins with relatively slow plate speeds such as the boundaries between Cocos and North American plates and between Indo-Australian and Eurasian plates. Earthquakes occur dominantly in the regions with positive Coulomb stress changes, suggesting that post-earthquakes are controlled by the stresses released from prior earthquakes. We find strong positive correlations between Coulomb stress changes and plate speeds. The observation suggests that large stress drop was controlled by high plate speed, suggesting possible prediction of potential maximum magnitudes of events.

  15. Operational earthquake forecasting can enhance earthquake preparedness

    USGS Publications Warehouse

    Jordan, T.H.; Marzocchi, W.; Michael, A.J.; Gerstenberger, M.C.

    2014-01-01

    We cannot yet predict large earthquakes in the short term with much reliability and skill, but the strong clustering exhibited in seismic sequences tells us that earthquake probabilities are not constant in time; they generally rise and fall over periods of days to years in correlation with nearby seismic activity. Operational earthquake forecasting (OEF) is the dissemination of authoritative information about these time‐dependent probabilities to help communities prepare for potentially destructive earthquakes. The goal of OEF is to inform the decisions that people and organizations must continually make to mitigate seismic risk and prepare for potentially destructive earthquakes on time scales from days to decades. To fulfill this role, OEF must provide a complete description of the seismic hazard—ground‐motion exceedance probabilities as well as short‐term rupture probabilities—in concert with the long‐term forecasts of probabilistic seismic‐hazard analysis (PSHA).

  16. Research in earthquake prediction - the Parkfield prediction experiment

    USGS Publications Warehouse

    Spall, Henry

    1986-01-01

    The 15-mile-long Parkfield, California, section of the Sam Andreas fault is the best understood earthquake source region in the world. Moderate-sized earthquakes of local magnitude 5 3/4 occurred at Parkfield in 1881, 1901, 1922, 1934, and 1966.

  17. Relation between Intelligence and Short-Term Memory

    ERIC Educational Resources Information Center

    Cohen, Ronald L.; Sandberg, Tor

    1977-01-01

    Intelligence and short-term memory correlations in children were measured using probed serial recall of supraspan digit lists. Results showed the predictive power of intelligence to range from a maximum in the case of recall for recency items to practically zero in the case of primacy items. (Author/MV)

  18. Relation between Intelligence and Short-Term Memory

    ERIC Educational Resources Information Center

    Cohen, Ronald L.; Sandberg, Tor

    1977-01-01

    Intelligence and short-term memory correlations in children were measured using probed serial recall of supraspan digit lists. Results showed the predictive power of intelligence to range from a maximum in the case of recall for recency items to practically zero in the case of primacy items. (Author/MV)

  19. Interference-Based Forgetting in Verbal Short-Term Memory

    ERIC Educational Resources Information Center

    Lewandowsky, Stephan; Geiger, Sonja M.; Oberauer, Klaus

    2008-01-01

    This article presents four experiments that tested predictions of SOB (Serial Order in a Box), an interference-based theory of short-term memory. Central to SOB is the concept of novelty-sensitive encoding, which holds that items are encoded to the extent that they differ from already-encoded information. On the additional assumption that…

  20. Implications of fault constitutive properties for earthquake prediction.

    PubMed Central

    Dieterich, J H; Kilgore, B

    1996-01-01

    The rate- and state-dependent constitutive formulation for fault slip characterizes an exceptional variety of materials over a wide range of sliding conditions. This formulation provides a unified representation of diverse sliding phenomena including slip weakening over a characteristic sliding distance Dc, apparent fracture energy at a rupture front, time-dependent healing after rapid slip, and various other transient and slip rate effects. Laboratory observations and theoretical models both indicate that earthquake nucleation is accompanied by long intervals of accelerating slip. Strains from the nucleation process on buried faults generally could not be detected if laboratory values of Dc apply to faults in nature. However, scaling of Dc is presently an open question and the possibility exists that measurable premonitory creep may precede some earthquakes. Earthquake activity is modeled as a sequence of earthquake nucleation events. In this model, earthquake clustering arises from sensitivity of nucleation times to the stress changes induced by prior earthquakes. The model gives the characteristic Omori aftershock decay law and assigns physical interpretation to aftershock parameters. The seismicity formulation predicts large changes of earthquake probabilities result from stress changes. Two mechanisms for foreshocks are proposed that describe observed frequency of occurrence of foreshock-mainshock pairs by time and magnitude. With the first mechanism, foreshocks represent a manifestation of earthquake clustering in which the stress change at the time of the foreshock increases the probability of earthquakes at all magnitudes including the eventual mainshock. With the second model, accelerating fault slip on the mainshock nucleation zone triggers foreshocks. Images Fig. 3 PMID:11607666

  1. Implications of fault constitutive properties for earthquake prediction

    USGS Publications Warehouse

    Dieterich, J.H.; Kilgore, B.

    1996-01-01

    The rate- and state-dependent constitutive formulation for fault slip characterizes an exceptional variety of materials over a wide range of sliding conditions. This formulation provides a unified representation of diverse sliding phenomena including slip weakening over a characteristic sliding distance D(c), apparent fracture energy at a rupture front, time- dependent healing after rapid slip, and various other transient and slip rate effects. Laboratory observations and theoretical models both indicate that earthquake nucleation is accompanied by long intervals of accelerating slip. Strains from the nucleation process on buried faults generally could not be detected if laboratory values of D, apply to faults in nature. However, scaling of D(c) is presently an open question and the possibility exists that measurable premonitory creep may precede some earthquakes. Earthquake activity is modeled as a sequence of earthquake nucleation events. In this model, earthquake clustering arises from sensitivity of nucleation times to the stress changes induced by prior earthquakes. The model gives the characteristic Omori aftershock decay law and assigns physical interpretation to aftershock parameters. The seismicity formulation predicts large changes of earthquake probabilities result from stress changes. Two mechanisms for foreshocks are proposed that describe observed frequency of occurrence of foreshock-mainshock pairs by time and magnitude. With the first mechanism, foreshocks represent a manifestation of earthquake clustering in which the stress change at the time of the foreshock increases the probability of earthquakes at all magnitudes including the eventual mainshock. With the second model, accelerating fault slip on the mainshock nucleation zone triggers foreshocks.

  2. PET/CT with (18)F-FDG predicts short-term outcome in stage II/III breast cancer patients upstaged to N2/3 nodal disease.

    PubMed

    Teixeira, S C; Koolen, B B; Elkhuizen, P H M; Vrancken Peeters, M-J T F D; Stokkel, M P M; Rodenhuis, S; van der Noort, V; Rutgers, E J T; Valdés Olmos, R A

    2017-04-01

    (18)F-FDG PET/CT has high positive predictive value for the detection of avid lymph node metastases in breast cancer patients. We analysed the effect of upstaging lymph nodes by PET/CT on short-term outcome in stage II/III breast cancer patients. A total of 278 stage II/III primary breast cancer patients (mean age 48.9 years, range 19-75 years) were re-staged with (18)F-FDG PET/CT before start of pre-operative systemic treatment (PST). Patients were divided in three groups based on risk for local recurrence: a low - (T2N0), intermediate - (T0-2N1 and T3N0) and a high-risk group (T0-3N2-3, T3N1 and T4). Within these groups we looked at local recurrence-free survival (LRFS), recurrence-free survival (RFS) and overall survival (OS) within the first 3 years of follow-up. With a median follow-up (FU) of 50 months the RFS, LRFS and OS were 87%, 88% and 92% respectively for the whole group. PET/CT upstaged 43 patients from the low- and intermediate risk group to the high-risk group, based on detection of ≥4 avid axillary nodes or occult N2/3-disease. Patients upstaged with PET/CT had more events for all three analyses compared to the original risk groups, which resulted in a significantly worse RFS (69.8%; p = 0.03) a nearly significantly worse LRFS (p = 0.052) and no effect in OS (p = 0.433). Additional PET/CT staging allows breast cancer patients to be treated according to the true stage, still stage II/III breast cancer patients upstaged to N2/3 by PET/CT have worse short-term outcome, despite adjustment of treatment, than patients staged high-risk with conventional imaging. Copyright © 2016 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

  3. Usefulness of an Upright T-Wave in Lead aVR for Predicting the Short-Term Prognosis of Incident Hemodialysis Patients: A Potential Tool for Screening High-Risk Hemodialysis Patients.

    PubMed

    Matsukane, Ai; Hayashi, Toshihide; Tanaka, Yuri; Iwasaki, Masaki; Kubo, Shun; Asakawa, Takasuke; Takahashi, Yasunori; Imamura, Yoshihiko; Hirahata, Koichi; Joki, Nobuhiko; Hase, Hiroki

    2015-10-01

    An upright T-wave in lead aVR (aVRT) has recently been reported to be associated with cardiovascular death and mortality among the general population and patients with prior cardiovascular disease (CVD). However, evidence for the predictive ability of aVRT in patients with chronic kidney disease is lacking. Therefore, a hospital-based, prospective, cohort study was conducted to evaluate the predictive ability of an upright aVRT for the short-term prognosis in incident hemodialysis patients. Among 208 patients who started maintenance hemodialysis, 79 with preexisting CVD (CVD cohort) and 129 with no history of CVD (non-CVD cohort), were studied. An upright and non-upright aVRT were defined as a wave with a positive deflection in amplitude of ≥0 mV and a negative deflection in amplitude of <0 mV, respectively. The endpoint was all-cause death. Overall, the prevalence of an upright aVRT was 22.6% at baseline. During the mean follow-up period of 2.1 ± 1.0 years, 33 deaths occurred. Cumulative survival rates at 3 years after starting dialysis in patients with an upright and non-upright aVRT were 50.0 and 80.7%, respectively, in the CVD cohort and 92.0 and 91.3%, respectively, in the non-CVD cohort. In the CVD cohort, multivariate Cox regression analysis showed that an upright aVRT was an independent predictor of death after adjusting for confounding variables. Among Japanese hemodialysis patients at high risk for CVD, an upright aVRT seems to be useful for predicting death.

  4. Usefulness of an Upright T-Wave in Lead aVR for Predicting the Short-Term Prognosis of Incident Hemodialysis Patients: A Potential Tool for Screening High-Risk Hemodialysis Patients

    PubMed Central

    Matsukane, Ai; Hayashi, Toshihide; Tanaka, Yuri; Iwasaki, Masaki; Kubo, Shun; Asakawa, Takasuke; Takahashi, Yasunori; Imamura, Yoshihiko; Hirahata, Koichi; Joki, Nobuhiko; Hase, Hiroki

    2015-01-01

    Background/Aims An upright T-wave in lead aVR (aVRT) has recently been reported to be associated with cardiovascular death and mortality among the general population and patients with prior cardiovascular disease (CVD). However, evidence for the predictive ability of aVRT in patients with chronic kidney disease is lacking. Therefore, a hospital-based, prospective, cohort study was conducted to evaluate the predictive ability of an upright aVRT for the short-term prognosis in incident hemodialysis patients. Methods Among 208 patients who started maintenance hemodialysis, 79 with preexisting CVD (CVD cohort) and 129 with no history of CVD (non-CVD cohort), were studied. An upright and non-upright aVRT were defined as a wave with a positive deflection in amplitude of ≥0 mV and a negative deflection in amplitude of <0 mV, respectively. The endpoint was all-cause death. Results Overall, the prevalence of an upright aVRT was 22.6% at baseline. During the mean follow-up period of 2.1 ± 1.0 years, 33 deaths occurred. Cumulative survival rates at 3 years after starting dialysis in patients with an upright and non-upright aVRT were 50.0 and 80.7%, respectively, in the CVD cohort and 92.0 and 91.3%, respectively, in the non-CVD cohort. In the CVD cohort, multivariate Cox regression analysis showed that an upright aVRT was an independent predictor of death after adjusting for confounding variables. Conclusion Among Japanese hemodialysis patients at high risk for CVD, an upright aVRT seems to be useful for predicting death. PMID:26648943

  5. Sun-earth environment study to understand earthquake prediction

    NASA Astrophysics Data System (ADS)

    Mukherjee, S.

    2007-05-01

    Earthquake prediction is possible by looking into the location of active sunspots before it harbours energy towards earth. Earth is a restless planet the restlessness turns deadly occasionally. Of all natural hazards, earthquakes are the most feared. For centuries scientists working in seismically active regions have noted premonitory signals. Changes in thermosphere, Ionosphere, atmosphere and hydrosphere are noted before the changes in geosphere. The historical records talk of changes of the water level in wells, of strange weather, of ground-hugging fog, of unusual behaviour of animals (due to change in magnetic field of the earth) that seem to feel the approach of a major earthquake. With the advent of modern science and technology the understanding of these pre-earthquake signals has become stronger enough to develop a methodology of earthquake prediction. A correlation of earth directed coronal mass ejection (CME) from the active sunspots has been possible to develop as a precursor of the earthquake. Occasional local magnetic field and planetary indices (Kp values) changes in the lower atmosphere that is accompanied by the formation of haze and a reduction of moisture in the air. Large patches, often tens to hundreds of thousands of square kilometres in size, seen in night-time infrared satellite images where the land surface temperature seems to fluctuate rapidly. Perturbations in the ionosphere at 90 - 120 km altitude have been observed before the occurrence of earthquakes. These changes affect the transmission of radio waves and a radio black out has been observed due to CME. Another heliophysical parameter Electron flux (Eflux) has been monitored before the occurrence of the earthquakes. More than hundreds of case studies show that before the occurrence of the earthquakes the atmospheric temperature increases and suddenly drops before the occurrence of the earthquakes. These changes are being monitored by using Sun Observatory Heliospheric observatory

  6. Rock friction and its implications for earthquake prediction examined via models of Parkfield earthquakes.

    PubMed Central

    Tullis, T E

    1996-01-01

    The friction of rocks in the laboratory is a function of time, velocity of sliding, and displacement. Although the processes responsible for these dependencies are unknown, constitutive equations have been developed that do a reasonable job of describing the laboratory behavior. These constitutive laws have been used to create a model of earthquakes at Parkfield, CA, by using boundary conditions appropriate for the section of the fault that slips in magnitude 6 earthquakes every 20-30 years. The behavior of this model prior to the earthquakes is investigated to determine whether or not the model earthquakes could be predicted in the real world by using realistic instruments and instrument locations. Premonitory slip does occur in the model, but it is relatively restricted in time and space and detecting it from the surface may be difficult. The magnitude of the strain rate at the earth's surface due to this accelerating slip seems lower than the detectability limit of instruments in the presence of earth noise. Although not specifically modeled, microseismicity related to the accelerating creep and to creep events in the model should be detectable. In fact the logarithm of the moment rate on the hypocentral cell of the fault due to slip increases linearly with minus the logarithm of the time to the earthquake. This could conceivably be used to determine when the earthquake was going to occur. An unresolved question is whether this pattern of accelerating slip could be recognized from the microseismicity, given the discrete nature of seismic events. Nevertheless, the model results suggest that the most likely solution to earthquake prediction is to look for a pattern of acceleration in microseismicity and thereby identify the microearthquakes as foreshocks. Images Fig. 4 Fig. 4 Fig. 5 Fig. 7 PMID:11607668

  7. Rock friction and its implications for earthquake prediction examined via models of Parkfield earthquakes.

    PubMed

    Tullis, T E

    1996-04-30

    The friction of rocks in the laboratory is a function of time, velocity of sliding, and displacement. Although the processes responsible for these dependencies are unknown, constitutive equations have been developed that do a reasonable job of describing the laboratory behavior. These constitutive laws have been used to create a model of earthquakes at Parkfield, CA, by using boundary conditions appropriate for the section of the fault that slips in magnitude 6 earthquakes every 20-30 years. The behavior of this model prior to the earthquakes is investigated to determine whether or not the model earthquakes could be predicted in the real world by using realistic instruments and instrument locations. Premonitory slip does occur in the model, but it is relatively restricted in time and space and detecting it from the surface may be difficult. The magnitude of the strain rate at the earth's surface due to this accelerating slip seems lower than the detectability limit of instruments in the presence of earth noise. Although not specifically modeled, microseismicity related to the accelerating creep and to creep events in the model should be detectable. In fact the logarithm of the moment rate on the hypocentral cell of the fault due to slip increases linearly with minus the logarithm of the time to the earthquake. This could conceivably be used to determine when the earthquake was going to occur. An unresolved question is whether this pattern of accelerating slip could be recognized from the microseismicity, given the discrete nature of seismic events. Nevertheless, the model results suggest that the most likely solution to earthquake prediction is to look for a pattern of acceleration in microseismicity and thereby identify the microearthquakes as foreshocks.

  8. Initiation process of earthquakes and its implications for seismic hazard reduction strategy.

    PubMed

    Kanamori, H

    1996-04-30

    For the average citizen and the public, "earthquake prediction" means "short-term prediction," a prediction of a specific earthquake on a relatively short time scale. Such prediction must specify the time, place, and magnitude of the earthquake in question with sufficiently high reliability. For this type of prediction, one must rely on some short-term precursors. Examinations of strain changes just before large earthquakes suggest that consistent detection of such precursory strain changes cannot be expected. Other precursory phenomena such as foreshocks and nonseismological anomalies do not occur consistently either. Thus, reliable short-term prediction would be very difficult. Although short-term predictions with large uncertainties could be useful for some areas if their social and economic environments can tolerate false alarms, such predictions would be impractical for most modern industrialized cities. A strategy for effective seismic hazard reduction is to take full advantage of the recent technical advancements in seismology, computers, and communication. In highly industrialized communities, rapid earthquake information is critically important for emergency services agencies, utilities, communications, financial companies, and media to make quick reports and damage estimates and to determine where emergency response is most needed. Long-term forecast, or prognosis, of earthquakes is important for development of realistic building codes, retrofitting existing structures, and land-use planning, but the distinction between short-term and long-term predictions needs to be clearly communicated to the public to avoid misunderstanding.

  9. Initiation process of earthquakes and its implications for seismic hazard reduction strategy.

    PubMed Central

    Kanamori, H

    1996-01-01

    For the average citizen and the public, "earthquake prediction" means "short-term prediction," a prediction of a specific earthquake on a relatively short time scale. Such prediction must specify the time, place, and magnitude of the earthquake in question with sufficiently high reliability. For this type of prediction, one must rely on some short-term precursors. Examinations of strain changes just before large earthquakes suggest that consistent detection of such precursory strain changes cannot be expected. Other precursory phenomena such as foreshocks and nonseismological anomalies do not occur consistently either. Thus, reliable short-term prediction would be very difficult. Although short-term predictions with large uncertainties could be useful for some areas if their social and economic environments can tolerate false alarms, such predictions would be impractical for most modern industrialized cities. A strategy for effective seismic hazard reduction is to take full advantage of the recent technical advancements in seismology, computers, and communication. In highly industrialized communities, rapid earthquake information is critically important for emergency services agencies, utilities, communications, financial companies, and media to make quick reports and damage estimates and to determine where emergency response is most needed. Long-term forecast, or prognosis, of earthquakes is important for development of realistic building codes, retrofitting existing structures, and land-use planning, but the distinction between short-term and long-term predictions needs to be clearly communicated to the public to avoid misunderstanding. Images Fig. 8 PMID:11607657

  10. Testing an Earthquake Prediction Algorithm: The 2016 New Zealand and Chile Earthquakes

    NASA Astrophysics Data System (ADS)

    Kossobokov, Vladimir G.

    2017-05-01

    The 13 November 2016, M7.8, 54 km NNE of Amberley, New Zealand and the 25 December 2016, M7.6, 42 km SW of Puerto Quellon, Chile earthquakes happened outside the area of the on-going real-time global testing of the intermediate-term middle-range earthquake prediction algorithm M8, accepted in 1992 for the M7.5+ range. Naturally, over the past two decades, the level of registration of earthquakes worldwide has grown significantly and by now is sufficient for diagnosis of times of increased probability (TIPs) by the M8 algorithm on the entire territory of New Zealand and Southern Chile as far as below 40°S. The mid-2016 update of the M8 predictions determines TIPs in the additional circles of investigation (CIs) where the two earthquakes have happened. Thus, after 50 semiannual updates in the real-time prediction mode, we (1) confirm statistically approved high confidence of the M8-MSc predictions and (2) conclude a possibility of expanding the territory of the Global Test of the algorithms M8 and MSc in an apparently necessary revision of the 1992 settings.

  11. Radon measurements for earthquake prediction in northern India

    SciTech Connect

    Singh, B.; Virk, H.S. )

    1992-01-01

    Earthquake prediction is based on the observation of precursory phenomena, and radon has emerged as a useful precursor in recent years. In India, where 55% of the land area is in active seismic zones, considerable destruction was caused by the earthquakes of Kutch (1819), Shillong (1897), Kangra (1905), Bihar-Nepal (1934), Assam (1956), Koyna (1967), Bihar-Nepal (1988), and Uttarkashi (1991). Radon ([sup 222]Rn) is produced by the decay of radium ([sup 226]Ra) in the uranium decay series and is present in trace amounts almost everywhere on the earth, being distributed in soil, groundwater, and lower levels of atmosphere. The purpose of this study is to find the value in radon monitoring for earthquake prediction.

  12. Short-term MRI measurements as predictors of EDSS progression in relapsing-remitting multiple sclerosis: grey matter atrophy but not lesions are predictive in a real-life setting.

    PubMed

    von Gumberz, Johanna; Mahmoudi, Mina; Young, Kim; Schippling, Sven; Martin, Roland; Heesen, Christoph; Siemonsen, Susanne; Stellmann, Jan-Patrick

    2016-01-01

    patients and was independent from treatment status. None of the predefined classifications were predictive for progression. Explorative post-hoc analyses found lower baseline EDSS and higher grey matter atrophy (FreeSurfer) as best predictors (R (2) = 0.29) for EDSS progression and the accuracy was overall good (Area under the curve = 0.81). Beside EDSS at baseline, short-term grey matter atrophy is predictive for EDSS progression in treated and untreated RRMS. The development of atrophy measurements for individual risk counselling and evaluation of treatment response seems possible, but needs further validation in larger cohorts. MRI-atrophy estimates from the FreeSurfer toolbox seem to be more reliable than older methods.

  13. Short-term MRI measurements as predictors of EDSS progression in relapsing-remitting multiple sclerosis: grey matter atrophy but not lesions are predictive in a real-life setting

    PubMed Central

    Young, Kim; Schippling, Sven; Martin, Roland; Heesen, Christoph; Siemonsen, Susanne

    2016-01-01

    . Results Progression was observed in 24% of patients and was independent from treatment status. None of the predefined classifications were predictive for progression. Explorative post-hoc analyses found lower baseline EDSS and higher grey matter atrophy (FreeSurfer) as best predictors (R2 = 0.29) for EDSS progression and the accuracy was overall good (Area under the curve = 0.81). Conclusion Beside EDSS at baseline, short-term grey matter atrophy is predictive for EDSS progression in treated and untreated RRMS. The development of atrophy measurements for individual risk counselling and evaluation of treatment response seems possible, but needs further validation in larger cohorts. MRI-atrophy estimates from the FreeSurfer toolbox seem to be more reliable than older methods. PMID:27688965

  14. Short-term memory across eye blinks.

    PubMed

    Irwin, David E

    2014-01-01

    The effect of eye blinks on short-term memory was examined in two experiments. On each trial, participants viewed an initial display of coloured, oriented lines, then after a retention interval they viewed a test display that was either identical or different by one feature. Participants kept their eyes open throughout the retention interval on some blocks of trials, whereas on others they made a single eye blink. Accuracy was measured as a function of the number of items in the display to determine the capacity of short-term memory on blink and no-blink trials. In separate blocks of trials participants were instructed to remember colour only, orientation only, or both colour and orientation. Eye blinks reduced short-term memory capacity by approximately 0.6-0.8 items for both feature and conjunction stimuli. A third, control, experiment showed that a button press during the retention interval had no effect on short-term memory capacity, indicating that the effect of an eye blink was not due to general motoric dual-task interference. Eye blinks might instead reduce short-term memory capacity by interfering with attention-based rehearsal processes.

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

    USGS Publications Warehouse

    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

  16. 78 FR 64973 - National Earthquake Prediction Evaluation Council (NEPEC)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-30

    ... proposed earthquake predictions, on the completeness and scientific validity of the available data related... Council will receive several briefings on the history and current state of scientific investigations of..., and will be asked to advise the USGS on priorities for instrumentation and scientific investigations...

  17. An Earthquake Prediction System Using The Time Series Analyses of Earthquake Property And Crust Motion

    NASA Astrophysics Data System (ADS)

    Takeda, F.

    2004-12-01

    of a large EQ within narrow limits in weeks or months (or a few years) ahead of time. We have developed such a short-term deterministic EQ forecasting system similar to those used for Typhoons and Hurricanes, which has been under a test operation at http://www.tec21.jp/ since June of 2003. [1,2] The system must divide Japan into a small area of about 5 deg by 5 deg for which Eq. 1 is reconstructed such that the regional CI-w and Aa,m,w,s (whose ED's are all reduced to three) become the deterministic measures to make the successful prediction tests on every large EQ (or swarm if any) of hindsight in the area. The current system has five areas to cover Japan. We focus on two examples to describe the system operation. One is the 2003/09/26 Tokachi EQ of M 8 in hindsight (the system was yet to cover this area at the event). To make a prediction test on the M 8 EQ, we assume our current date is back to 2003/08/31. The date prediction of the M 8-class EQ was only one day off. The focus prediction was within the very narrow limits. Another is a successful rollout of the most recent forecast on the 2004/05/30 EQ of M 6.7 off coast of the southern Kanto (Tokyo) area. Its forecasting at our website started 16 days ahead of time like forecasting an approaching typhoon. The final forecast issued one day before the actual event has confirmed a perfect prediction on the focus and date. The system also performs a state-space analysis of the daily crust motion observed by GPS (F1 data of GEONET) to detect any anomaly including a slow-slip motion precursory to the M 8 EQ. 1. F. Takeda, and M. Takeo, submitted to Chaos (2003). 2. F. Takeda, and M. Takeo, submitted to AIP Conf. Proc., ECC8 (2004).

  18. An Earthquake Prediction System Using The Time Series Analyses of Earthquake Property And Crust Motion

    SciTech Connect

    Takeda, Fumihide; Takeo, Makoto

    2004-12-09

    We have developed a short-term deterministic earthquake (EQ) forecasting system similar to those used for Typhoons and Hurricanes, which has been under a test operation at website http://www.tec21.jp/ since June of 2003. We use the focus and crust displacement data recently opened to the public by Japanese seismograph and global positioning system (GPS) networks, respectively. Our system divides the forecasting area into the five regional areas of Japan, each of which is about 5 deg. by 5 deg. We have found that it can forecast the focus, date of occurrence and magnitude (M) of an impending EQ (whose M is larger than about 6), all within narrow limits. We have two examples to describe the system. One is the 2003/09/26 EQ of M 8 in the Hokkaido area, which is of hindsight. Another is a successful rollout of the most recent forecast on the 2004/05/30 EQ of M 6.7 off coast of the southern Kanto (Tokyo) area.

  19. Earthquake Prediction in Large-scale Faulting Experiments

    NASA Astrophysics Data System (ADS)

    Junger, J.; Kilgore, B.; Beeler, N.; Dieterich, J.

    2004-12-01

    We study repeated earthquake slip of a 2 m long laboratory granite fault surface with approximately homogenous frictional properties. In this apparatus earthquakes follow a period of controlled, constant rate shear stress increase, analogous to tectonic loading. Slip initiates and accumulates within a limited area of the fault surface while the surrounding fault remains locked. Dynamic rupture propagation and slip of the entire fault surface is induced when slip in the nucleating zone becomes sufficiently large. We report on the event to event reproducibility of loading time (recurrence interval), failure stress, stress drop, and precursory activity. We tentatively interpret these variations as indications of the intrinsic variability of small earthquake occurrence and source physics in this controlled setting. We use the results to produce measures of earthquake predictability based on the probability density of repeating occurrence and the reproducibility of near-field precursory strain. At 4 MPa normal stress and a loading rate of 0.0001 MPa/s, the loading time is ˜25 min, with a coefficient of variation of around 10%. Static stress drop has a similar variability which results almost entirely from variability of the final (rather than initial) stress. Thus, the initial stress has low variability and event times are slip-predictable. The variability of loading time to failure is comparable to the lowest variability of recurrence time of small repeating earthquakes at Parkfield (Nadeau et al., 1998) and our result may be a good estimate of the intrinsic variability of recurrence. Distributions of loading time can be adequately represented by a log-normal or Weibel distribution but long term prediction of the next event time based on probabilistic representation of previous occurrence is not dramatically better than for field-observed small- or large-magnitude earthquake datasets. The gradually accelerating precursory aseismic slip observed in the region of

  20. Theoretical models of synaptic short term plasticity

    PubMed Central

    Hennig, Matthias H.

    2013-01-01

    Short term plasticity is a highly abundant form of rapid, activity-dependent modulation of synaptic efficacy. A shared set of mechanisms can cause both depression and enhancement of the postsynaptic response at different synapses, with important consequences for information processing. Mathematical models have been extensively used to study the mechanisms and roles of short term plasticity. This review provides an overview of existing models and their biological basis, and of their main properties. Special attention will be given to slow processes such as calcium channel inactivation and the effect of activation of presynaptic autoreceptors. PMID:23626536

  1. Development of a clinical prediction rule for identifying women with tension-type headache who are likely to achieve short-term success with joint mobilization and muscle trigger point therapy.

    PubMed

    Fernández-de-las-Peñas, César; Cleland, Joshua A; Palomeque-del-Cerro, Luis; Caminero, Ana Belén; Guillem-Mesado, Amparo; Jiménez-García, Rodrigo

    2011-02-01

    successful outcome (48%). Eight prognostic variables were retained in the regression model: mean age <44.5 years, presence of left sternocleidomastoid TrP, presence of suboccipital TrP, presence of left superior oblique muscle TrP, cervical rotation to the left > 69°, total tenderness score <20.5, NDI <18.5, referred pain area of right upper trapezius muscle TrP >42.23. The current clinical prediction rule may allow clinicians to make an a priori identification of women with TTH who are likely to experience short-term self-report improvement with a multimodal session including joint mobilizations and TrP therapies. Future studies are necessary to validate these findings. © 2010 American Headache Society.

  2. Three Millennia of Seemingly Time-Predictable Earthquakes, Tell Ateret

    NASA Astrophysics Data System (ADS)

    Agnon, Amotz; Marco, Shmuel; Ellenblum, Ronnie

    2014-05-01

    Among various idealized recurrence models of large earthquakes, the "time-predictable" model has a straightforward mechanical interpretation, consistent with simple friction laws. On a time-predictable fault, the time interval between an earthquake and its predecessor is proportional to the slip during the predecessor. The alternative "slip-predictable" model states that the slip during earthquake rupture is proportional to the preceding time interval. Verifying these models requires extended records of high precision data for both timing and amount of slip. The precision of paleoearthquake data can rarely confirm or rule out predictability, and recent papers argue for either time- or slip-predictable behavior. The Ateret site, on the trace of the Dead Sea fault at the Jordan Gorge segment, offers unique precision for determining space-time patterns. Five consecutive slip events, each associated with deformed and offset sets of walls, are correlated with historical earthquakes. Two correlations are based on detailed archaeological, historical, and numismatic evidence. The other three are tentative. The offsets of three of the events are determined with high precision; the other two are not as certain. Accepting all five correlations, the fault exhibits a striking time-predictable behavior, with a long term slip rate of 3 mm/yr. However, the 30 October 1759 ~0.5 m rupture predicts a subsequent rupture along the Jordan Gorge toward the end of the last century. We speculate that earthquakres on secondary faults (the 25 November 1759 on the Rachaya branch and the 1 January 1837 on the Roum branch, both M≥7) have disrupted the 3 kyr time-predictable pattern.

  3. Ground Motion Prediction Equation for Earthquakes in Oklahoma

    NASA Astrophysics Data System (ADS)

    Yenier, E.; Atkinson, G. M.; Baturan, D.

    2016-12-01

    A significant increase has been observed in seismic activity in Oklahoma, since 2010. Although it is difficult to categorize these earthquakes as natural or induced on an individual basis, most of them are believed to be related to changes in stress conditions due to large-scale wastewater injection in the region. The growing seismic activity has prompted reassessment of the earthquake hazard in Oklahoma and southern Kansas. Prediction of ground motions that may be produced by potential future events constitutes one of the key components in seismic hazard assessment. In this study, we develop a ground motion prediction equation (GMPE), using a rich earthquake dataset distributed over a wide area of Oklahoma. To this end, we use a "plug-and-play" generic GMPE that can be adjusted for use in any region by modifying a few key model parameters. We investigate the region-specific source and attenuation properties using recorded peak ground motions and response spectra. We determine stress parameters based on the observed spectral shape, and compare to those from naturally occurring earthquakes in central and eastern North America. We also examine the spatial and temporal variation of stress parameters to gain insights into the source characteristics of induced events in the region. We adjust the generic GMPE using the source and attenuation parameters and a calibration factor calculated from empirical data. The derived model can be used for prediction of ground motions in Oklahoma for a wide range of magnitudes and distances.

  4. Improving creativity performance by short-term meditation.

    PubMed

    Ding, Xiaoqian; Tang, Yi-Yuan; Tang, Rongxiang; Posner, Michael I

    2014-03-19

    One form of meditation intervention, the integrative body-mind training (IBMT) has been shown to improve attention, reduce stress and change self-reports of mood. In this paper we examine whether short-term IBMT can improve performance related to creativity and determine the role that mood may play in such improvement. Forty Chinese undergraduates were randomly assigned to short-term IBMT group or a relaxation training (RT) control group. Mood and creativity performance were assessed by the Positive and Negative Affect Schedule (PANAS) and Torrance Tests of Creative Thinking (TTCT) questionnaire respectively. As predicted, the results indicated that short-term (30 min per day for 7 days) IBMT improved creativity performance on the divergent thinking task, and yielded better emotional regulation than RT. In addition, cross-lagged analysis indicated that both positive and negative affect may influence creativity in IBMT group (not RT group). Our results suggested that emotion-related creativity-promoting mechanism may be attributed to short-term meditation.

  5. Improving creativity performance by short-term meditation

    PubMed Central

    2014-01-01

    Background One form of meditation intervention, the integrative body-mind training (IBMT) has been shown to improve attention, reduce stress and change self-reports of mood. In this paper we examine whether short-term IBMT can improve performance related to creativity and determine the role that mood may play in such improvement. Methods Forty Chinese undergraduates were randomly assigned to short-term IBMT group or a relaxation training (RT) control group. Mood and creativity performance were assessed by the Positive and Negative Affect Schedule (PANAS) and Torrance Tests of Creative Thinking (TTCT) questionnaire respectively. Results As predicted, the results indicated that short-term (30 min per day for 7 days) IBMT improved creativity performance on the divergent thinking task, and yielded better emotional regulation than RT. In addition, cross-lagged analysis indicated that both positive and negative affect may influence creativity in IBMT group (not RT group). Conclusions Our results suggested that emotion-related creativity-promoting mechanism may be attributed to short-term meditation. PMID:24645871

  6. Artificial neural network model for earthquake prediction with radon monitoring.

    PubMed

    Külahci, Fatih; Inceöz, Murat; Doğru, Mahmut; Aksoy, Ercan; Baykara, Oktay

    2009-01-01

    Apart from the linear monitoring studies concerning the relationship between radon and earthquake, an artificial neural networks (ANNs) model approach is presented starting out from non-linear changes of the eight different parameters during the earthquake occurrence. A three-layer Levenberg-Marquardt feedforward learning algorithm is used to model the earthquake prediction process in the East Anatolian Fault System (EAFS). The proposed ANN system employs individual training strategy with fixed-weight and supervised models leading to estimations. The average relative error between the magnitudes of the earthquakes acquired by ANN and measured data is about 2.3%. The relative error between the test and earthquake data varies between 0% and 12%. In addition, the factor analysis was applied on all data and the model output values to see the statistical variation. The total variance of 80.18% was explained with four factors by this analysis. Consequently, it can be concluded that ANN approach is a potential alternative to other models with complex mathematical operations.

  7. Analysing earthquake slip models with the spatial prediction comparison test

    NASA Astrophysics Data System (ADS)

    Zhang, Ling; Mai, P. Martin; Thingbaijam, Kiran K. S.; Razafindrakoto, Hoby N. T.; Genton, Marc G.

    2015-01-01

    Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (`model') and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

  8. Predictability of population displacement after the 2010 Haiti earthquake

    PubMed Central

    Lu, Xin; Bengtsson, Linus; Holme, Petter

    2012-01-01

    Most severe disasters cause large population movements. These movements make it difficult for relief organizations to efficiently reach people in need. Understanding and predicting the locations of affected people during disasters is key to effective humanitarian relief operations and to long-term societal reconstruction. We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, to 341 d after the devastating Haiti earthquake of January 12, 2010. Nineteen days after the earthquake, population movements had caused the population of the capital Port-au-Prince to decrease by an estimated 23%. Both the travel distances and size of people’s movement trajectories grew after the earthquake. These findings, in combination with the disorder that was present after the disaster, suggest that people’s movements would have become less predictable. Instead, the predictability of people’s trajectories remained high and even increased slightly during the three-month period after the earthquake. Moreover, the destinations of people who left the capital during the first three weeks after the earthquake was highly correlated with their mobility patterns during normal times, and specifically with the locations in which people had significant social bonds. For the people who left Port-au-Prince, the duration of their stay outside the city, as well as the time for their return, all followed a skewed, fat-tailed distribution. The findings suggest that population movements during disasters may be significantly more predictable than previously thought. PMID:22711804

  9. Predictability of population displacement after the 2010 Haiti earthquake.

    PubMed

    Lu, Xin; Bengtsson, Linus; Holme, Petter

    2012-07-17

    Most severe disasters cause large population movements. These movements make it difficult for relief organizations to efficiently reach people in need. Understanding and predicting the locations of affected people during disasters is key to effective humanitarian relief operations and to long-term societal reconstruction. We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, to 341 d after the devastating Haiti earthquake of January 12, 2010. Nineteen days after the earthquake, population movements had caused the population of the capital Port-au-Prince to decrease by an estimated 23%. Both the travel distances and size of people's movement trajectories grew after the earthquake. These findings, in combination with the disorder that was present after the disaster, suggest that people's movements would have become less predictable. Instead, the predictability of people's trajectories remained high and even increased slightly during the three-month period after the earthquake. Moreover, the destinations of people who left the capital during the first three weeks after the earthquake was highly correlated with their mobility patterns during normal times, and specifically with the locations in which people had significant social bonds. For the people who left Port-au-Prince, the duration of their stay outside the city, as well as the time for their return, all followed a skewed, fat-tailed distribution. The findings suggest that population movements during disasters may be significantly more predictable than previously thought.

  10. Earthquake prediction: Criterion for a tilt anomaly

    SciTech Connect

    Buckley, C.P.; Kohlenberger, C.W.

    1980-07-10

    A current approach to the problem of defining and detecting anomalous tilt behavior is presented. To establish what is considered to be normal tilt behavior, we isolate systematic signals such as hydrologic, thermal, tidal, cultural, and equipment-related effects from the tilt data. The kinds of tilt signals which remain after rejection of the systematic signals are designated by ourselves as residual tilt. Residual tilt consists of asystematic random noise and anomalous tilts. To affirm or deny the contention that an anomalous tilt is present in the data requires the formulation of a statistically valid judgment criteria. Our approach adopts the hypothesis that the random walk model is not significantly different from the residual tilt and allows the application of standard statistical tests to the problem of detecting anomalous varia ions in random noise. In our study of the data analyzed so far, we find that the boundary for detectability is inverse frequency dependent, and this limits the way in which anomalies can be treated. The fact that the magnitude of the anomaly decreases as the tilt data span increases suggests that further criterion development is necessary and tends to imply that longer anomalies will not be detected unless there is a correspondingly larger amplitude. From our studies of three earthquake-association anomalies this does not appear to be the case.

  11. Metropolitan French: Familiarization & Short-Term Training.

    ERIC Educational Resources Information Center

    Iszkowski, Marie-Charlotte

    The U.S. Department of State's Foreign Service Institute French Familiarization and Short-Term (FAST) course for personnel working and living in France consists of 10 weeks of French language instruction combined with practical and cultural information. An introductory section outlines FAST course objectives and sample teaching techniques in…

  12. Intercultural Learning on Short-Term Sojourns

    ERIC Educational Resources Information Center

    Jackson, Jane

    2009-01-01

    This paper presents an ethnographic case study of advanced second language (L2) students from Hong Kong who took part in a short-term sojourn in England after 14 weeks of preparation. While abroad, they lived with a host family, took literary/cultural studies courses, visited cultural sites, participated in debriefing sessions, and conducted…

  13. Spanish: Familiarization and Short-Term Training.

    ERIC Educational Resources Information Center

    Arbelaez, Vicente; And Others

    The State Department's Foreign Service Institute short-term, intensive course in Spanish language and culture for government employees going to work in Spanish-speaking countries contains an introductory section and 38 lessons and 10 related audio cassettes intended as the basis for a ten-week program with an instructor. The lessons cover these…

  14. Short-Term Play Therapy for Children.

    ERIC Educational Resources Information Center

    Kaduson, Heidi Gerard, Ed.; Schaefer, Charles E., Ed.

    Play therapy offers a powerful means of helping children resolve a wide range of psychological difficulties, and many play approaches are ideally suited to short-term work. This book brings together leading play therapists to share their expertise on facilitating children's healing in a shorter time frame. The book provides knowledge and skills…

  15. Spanish: Familiarization and Short-Term Training.

    ERIC Educational Resources Information Center

    Arbelaez, Vicente; And Others

    The State Department's Foreign Service Institute short-term, intensive course in Spanish language and culture for government employees going to work in Spanish-speaking countries contains an introductory section and 38 lessons and 10 related audio cassettes intended as the basis for a ten-week program with an instructor. The lessons cover these…

  16. Metropolitan French: Familiarization & Short-Term Training.

    ERIC Educational Resources Information Center

    Iszkowski, Marie-Charlotte

    The U.S. Dep