WorldWideScience

Sample records for short-term prediction research

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

    Science.gov (United States)

    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.

  2. Implementation of short-term prediction

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L; Joensen, A; Giebel, G [and others

    1999-03-01

    This paper will giver a general overview of the results from a EU JOULE funded project (`Implementing short-term prediction at utilities`, JOR3-CT95-0008). Reference will be given to specialised papers where applicable. The goal of the project was to implement wind farm power output prediction systems in operational environments at a number of utilities in Europe. Two models were developed, one by Risoe and one by the Technical University of Denmark (DTU). Both prediction models used HIRLAM predictions from the Danish Meteorological Institute (DMI). (au) EFP-94; EU-JOULE. 11 refs.

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

    Science.gov (United States)

    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

  4. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

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

    Science.gov (United States)

    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.

  6. Scalable data-driven short-term traffic prediction

    NARCIS (Netherlands)

    Friso, K.; Wismans, L. J.J.; Tijink, M. B.

    2017-01-01

    Short-term traffic prediction has a lot of potential for traffic management. However, most research has traditionally focused on either traffic models-which do not scale very well to large networks, computationally-or on data-driven methods for freeways, leaving out urban arterials completely. Urban

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

    Science.gov (United States)

    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.

  8. Short-term wind power prediction

    DEFF Research Database (Denmark)

    Joensen, Alfred K.

    2003-01-01

    , and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity...

  9. Short-term predictions in forex trading

    Science.gov (United States)

    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.

  10. Statistical short-term earthquake prediction.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  15. VAN method of short-term earthquake prediction shows promise

    Science.gov (United States)

    Uyeda, Seiya

    Although optimism prevailed in the 1970s, the present consensus on earthquake prediction appears to be quite pessimistic. However, short-term prediction based on geoelectric potential monitoring has stood the test of time in Greece for more than a decade [VarotsosandKulhanek, 1993] Lighthill, 1996]. The method used is called the VAN method.The geoelectric potential changes constantly due to causes such as magnetotelluric effects, lightning, rainfall, leakage from manmade sources, and electrochemical instabilities of electrodes. All of this noise must be eliminated before preseismic signals are identified, if they exist at all. The VAN group apparently accomplished this task for the first time. They installed multiple short (100-200m) dipoles with different lengths in both north-south and east-west directions and long (1-10 km) dipoles in appropriate orientations at their stations (one of their mega-stations, Ioannina, for example, now has 137 dipoles in operation) and found that practically all of the noise could be eliminated by applying a set of criteria to the data.

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

    Science.gov (United States)

    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).

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

    Science.gov (United States)

    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

  18. An Artificial Neural Network Based Short-term Dynamic Prediction of Algae Bloom

    Directory of Open Access Journals (Sweden)

    Yao Junyang

    2014-06-01

    Full Text Available This paper proposes a method of short-term prediction of algae bloom based on artificial neural network. Firstly, principal component analysis is applied to water environmental factors in algae bloom raceway ponds to get main factors that influence the formation of algae blooms. Then, a model of short-term dynamic prediction based on neural network is built with the current chlorophyll_a values as input and the chlorophyll_a values in the next moment as output to realize short-term dynamic prediction of algae bloom. Simulation results show that the model can realize short-term prediction of algae bloom effectively.

  19. Predicting short term mood developments among depressed patients using adherence and ecological momentary assessment data

    Directory of Open Access Journals (Sweden)

    Adam Mikus

    2018-06-01

    , but from this research we can conclude that sophisticated machine learning algorithms/setups can result in accurate performance. For future work, we want to use more data from the mobile phone to improve predictive performance of short term mood. Keywords: Depression, Machine learning, Short term mood, Prediction

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

    Science.gov (United States)

    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

    2015-08-07

    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. 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 (PPeruvian 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. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

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

    Science.gov (United States)

    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 (PPeruvian 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

  2. Predicting Short-Term Subway Ridership and Prioritizing Its Influential Factors Using Gradient Boosting Decision Trees

    Directory of Open Access Journals (Sweden)

    Chuan Ding

    2016-10-01

    Full Text Available Understanding the relationship between short-term subway ridership and its influential factors is crucial to improving the accuracy of short-term subway ridership prediction. Although there has been a growing body of studies on short-term ridership prediction approaches, limited effort is made to investigate the short-term subway ridership prediction considering bus transfer activities and temporal features. To fill this gap, a relatively recent data mining approach called gradient boosting decision trees (GBDT is applied to short-term subway ridership prediction and used to capture the associations with the independent variables. Taking three subway stations in Beijing as the cases, the short-term subway ridership and alighting passengers from its adjacent bus stops are obtained based on transit smart card data. To optimize the model performance with different combinations of regularization parameters, a series of GBDT models are built with various learning rates and tree complexities by fitting a maximum of trees. The optimal model performance confirms that the gradient boosting approach can incorporate different types of predictors, fit complex nonlinear relationships, and automatically handle the multicollinearity effect with high accuracy. In contrast to other machine learning methods—or “black-box” procedures—the GBDT model can identify and rank the relative influences of bus transfer activities and temporal features on short-term subway ridership. These findings suggest that the GBDT model has considerable advantages in improving short-term subway ridership prediction in a multimodal public transportation system.

  3. Short-term prediction of local wind conditions

    DEFF Research Database (Denmark)

    Landberg, L.

    2001-01-01

    This paper will describe a system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual...

  4. Error analysis of short term wind power prediction models

    International Nuclear Information System (INIS)

    De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco

    2011-01-01

    The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

  5. Error analysis of short term wind power prediction models

    Energy Technology Data Exchange (ETDEWEB)

    De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)

    2011-04-15

    The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

  6. Artificial intelligence to predict short-term wind speed

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, Tiago; Soares, Joao; Ramos, Sergio; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - ISEP

    2012-07-01

    The use of renewable energy is increasing exponentially in many countries due to the introduction of new energy and environmental policies. Thus, the focus on energy and on the environment makes the efficient integration of renewable energy into the electric power system extremely important. Several European countries have been seeing a high penetration of wind power, representing, gradually, a significant penetration on electricity generation. The introduction of wind power in the network power system causes new challenges for the power system operator due to the variability and uncertainty in weather conditions and, consequently, in the wind power generation. As result, the scheduling dispatch has a significantly portion of uncertainty. In order to deal with the uncertainty in wind power and, with that, introduce improvements in the power system operator efficiency, the wind power forecasting may reveal as a useful tool. This paper proposes a data-mining-based methodology to forecast wind speed. This method is based on the use of data mining techniques applied to a real database of historical wind data. The paper includes a case study based on a real database regarding the last three years to predict wind speed at 5 minute intervals. (orig.)

  7. Short-term Prediction of Coronary Heart Disease Mortality in the Czech Republic Based on Data from 1968-2014.

    Czech Academy of Sciences Publication Activity Database

    Reissigová, Jindra; Zvolský, M.

    2018-01-01

    Roč. 26, č. 1 (2018), s. 10-15 ISSN 1210-7778 Institutional support: RVO:67985807 Keywords : mortality * coronary heart diseases * short-term prediction * long-term prediction * national health registries Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Applied mathematics Impact factor: 0.682, year: 2016 https://cejph.szu.cz/artkey/cjp-201801-0002_short-term-prediction-of-coronary- heart -disease-mortality-in-the-czech-republic-based-on-data-from-1968-2014.php

  8. A review on the young history of the wind power short-term prediction

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Alexandre; Navarro, Jorge [Wind Energy, Division of Renewable Energies, Department of Energy, CIEMAT, Av. Complutense, 22, Ed. 42, 28044 Madrid (Spain); Crespo, Antonio [Laboratorio de Mecanica de Fluidos, Departmento de Ingenieria Energetica y Fluidomecanica, ETSII, Universidad Politecnica de Madrid, C/Jose Gutierrez Abascal, 2-28006 Madrid (Spain); Lizcano, Gil [Oxford University Centre for the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY (United Kingdom); Madsen, Henrik [Informatics and Mathematical Modelling - IMM, Technical University of Denmark, Richard Petersens Plads, Building 321, Office 019, 2800 Kgs. Lyngby (Denmark); Feitosa, Everaldo [Brazilian Wind Energy Centre - CBEE, Centro de Tecnologia e Geociencias, UFPE-50.740-530 Recife, PE (Brazil)

    2008-08-15

    This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art on models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly the same in order to compare two models (this fact makes it almost impossible to carry out a quantitative comparison between a huge number of models and methods). In place of a quantitative description, a qualitative approach is preferred for this review, remarking the contribution (and innovative aspect) of each model. On the basis of the review, some topics for future research are pointed out. (author)

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

    Science.gov (United States)

    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.

  10. An adaptive short-term prediction scheme for wind energy storage management

    International Nuclear Information System (INIS)

    Blonbou, Ruddy; Monjoly, Stephanie; Dorville, Jean-Francois

    2011-01-01

    Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.

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

    Science.gov (United States)

    Jones, Gary; Macken, Bill

    2018-02-01

    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.

  12. A review on the young history of the wind power short-term prediction

    DEFF Research Database (Denmark)

    Costa, A.; Crespo, A.; Navarro, J.

    2008-01-01

    This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art oil models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought...... on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly...

  13. Short Term Prediction of PM10 Concentrations Using Seasonal Time Series Analysis

    Directory of Open Access Journals (Sweden)

    Hamid Hazrul Abdul

    2016-01-01

    Full Text Available Air pollution modelling is one of an important tool that usually used to make short term and long term prediction. Since air pollution gives a big impact especially to human health, prediction of air pollutants concentration is needed to help the local authorities to give an early warning to people who are in risk of acute and chronic health effects from air pollution. Finding the best time series model would allow prediction to be made accurately. This research was carried out to find the best time series model to predict the PM10 concentrations in Nilai, Negeri Sembilan, Malaysia. By considering two seasons which is wet season (north east monsoon and dry season (south west monsoon, seasonal autoregressive integrated moving average model were used to find the most suitable model to predict the PM10 concentrations in Nilai, Negeri Sembilan by using three error measures. Based on AIC statistics, results show that ARIMA (1, 1, 1 × (1, 0, 012 is the most suitable model to predict PM10 concentrations in Nilai, Negeri Sembilan.

  14. Motion Simulation Research Related Short Term Training Attachment to TARDEC

    Science.gov (United States)

    2013-04-01

    had to ensure that they could show the value of this advanced technology to its clients, rather than the clients perceiving it as an experimental...Surroundings Image Generation Controller Software SCRAM Net Comms to Sim Terra Vista Detailed terrain modelling VR Forces Simulation Scenario...Kelvin Oie, who is the neuroscience manager. The overlap between the respective organisations’ research goals was realised and benefits of

  15. Short-term wind power prediction based on LSSVM–GSA model

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong

    2015-01-01

    Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction

  16. Application of Grey Model GM(1, 1) to Ultra Short-Term Predictions of Universal Time

    Science.gov (United States)

    Lei, Yu; Guo, Min; Zhao, Danning; Cai, Hongbing; Hu, Dandan

    2016-03-01

    A mathematical model known as one-order one-variable grey differential equation model GM(1, 1) has been herein employed successfully for the ultra short-term (advantage is that the developed method is easy to use. All these reveal a great potential of the GM(1, 1) model for UT1-UTC predictions.

  17. Analysts forecast error : A robust prediction model and its short term trading

    NARCIS (Netherlands)

    Boudt, Kris; de Goeij, Peter; Thewissen, James; Van Campenhout, Geert

    We examine the profitability of implementing a short term trading strategy based on predicting the error in analysts' earnings per share forecasts using publicly available information. Since large earnings surprises may lead to extreme values in the forecast error series that disrupt their smooth

  18. Theta coupling between V4 and prefrontal cortex predicts visual short-term memory performance.

    Science.gov (United States)

    Liebe, Stefanie; Hoerzer, Gregor M; Logothetis, Nikos K; Rainer, Gregor

    2012-01-29

    Short-term memory requires communication between multiple brain regions that collectively mediate the encoding and maintenance of sensory information. It has been suggested that oscillatory synchronization underlies intercortical communication. Yet, whether and how distant cortical areas cooperate during visual memory remains elusive. We examined neural interactions between visual area V4 and the lateral prefrontal cortex using simultaneous local field potential (LFP) recordings and single-unit activity (SUA) in monkeys performing a visual short-term memory task. During the memory period, we observed enhanced between-area phase synchronization in theta frequencies (3-9 Hz) of LFPs together with elevated phase locking of SUA to theta oscillations across regions. In addition, we found that the strength of intercortical locking was predictive of the animals' behavioral performance. This suggests that theta-band synchronization coordinates action potential communication between V4 and prefrontal cortex that may contribute to the maintenance of visual short-term memories.

  19. Short-Term Power Load Point Prediction Based on the Sharp Degree and Chaotic RBF Neural Network

    Directory of Open Access Journals (Sweden)

    Dongxiao Niu

    2015-01-01

    Full Text Available In order to realize the predicting and positioning of short-term load inflection point, this paper made reference to related research in the field of computer image recognition. It got a load sharp degree sequence by the transformation of the original load sequence based on the algorithm of sharp degree. Then this paper designed a forecasting model based on the chaos theory and RBF neural network. It predicted the load sharp degree sequence based on the forecasting model to realize the positioning of short-term load inflection point. Finally, in the empirical example analysis, this paper predicted the daily load point of a region using the actual load data of the certain region to verify the effectiveness and applicability of this method. Prediction results showed that most of the test sample load points could be accurately predicted.

  20. Development of a short-term model to predict natural gas demand, March 1989

    International Nuclear Information System (INIS)

    Lihn, M.L.

    1989-03-01

    Project management decisions for the Gas Research Institute (GRI) R and D program require an appreciation of the short-term outlook for gas consumption. This paper provides a detailed discussion of the methodology used to develop short-term models for the residential, commercial, industrial, and electric utility sectors. The relative success of the models in projecting gas demand, compared with actual gas demand, is reviewed for each major gas-consuming sector. The comparison of actual to projected gas demand has pointed out several problems with the model, and possible solutions to these problems are discussed

  1. Standardizing the performance evaluation of short-term wind prediction models

    DEFF Research Database (Denmark)

    Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

    2005-01-01

    Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

  2. Withdrawal-Related Changes in Delay Discounting Predict Short-Term Smoking Abstinence.

    Science.gov (United States)

    Miglin, Rickie; Kable, Joseph W; Bowers, Maureen E; Ashare, Rebecca L

    2017-06-01

    Impulsive decision making is associated with smoking behavior and reflects preferences for smaller, immediate rewards and intolerance of temporal delays. Nicotine withdrawal may alter impulsive decision making and time perception. However, little is known about whether withdrawal-related changes in decision making and time perception predict smoking relapse. Forty-five smokers (14 female) completed two laboratory sessions, one following 24-hour abstinence and one smoking-as-usual (order counterbalanced; biochemically verified abstinence). During each visit, participants completed measures of time perception, decision making (ie, discount rates), craving, and withdrawal. Following the second laboratory session, subjects underwent a well-validated model of short-term abstinence (quit week) with small monetary incentives for each day of biochemically confirmed abstinence. Smokers significantly overestimated time during abstinence, compared to smoking-as-usual (p = .021), but there were no abstinence effects on discount rates (p = .6). During the quit week, subjects were abstinent for 3.5 days (SD = 2.15) and smoked a total of 12.9 cigarettes (SD = 15.8). Importantly, higher discount rates (ie, preferences for immediate rewards) during abstinence (abstinence minus smoking difference score) predicted greater number of days abstinent (p = .01) and fewer cigarettes smoked during the quit week (p = .02). Withdrawal-related change in time reproduction did not predict relapse (p = .2). These data suggest that individuals who have a greater preference for immediate rewards during abstinence (vs. smoking-as-usual) may be more successful at maintaining short-term abstinence when provided with frequent (eg, daily) versus less frequent incentive schedules (eg, 1 month). Abstinence-induced changes in decision making may be important for identifying smokers who may benefit from interventions that incentivize abstinence such as contingency management (CM). The present results

  3. Short-term PV/T module temperature prediction based on PCA-RBF neural network

    Science.gov (United States)

    Li, Jiyong; Zhao, Zhendong; Li, Yisheng; Xiao, Jing; Tang, Yunfeng

    2018-02-01

    Aiming at the non-linearity and large inertia of temperature control in PV/T system, short-term temperature prediction of PV/T module is proposed, to make the PV/T system controller run forward according to the short-term forecasting situation to optimize control effect. Based on the analysis of the correlation between PV/T module temperature and meteorological factors, and the temperature of adjacent time series, the principal component analysis (PCA) method is used to pre-process the original input sample data. Combined with the RBF neural network theory, the simulation results show that the PCA method makes the prediction accuracy of the network model higher and the generalization performance stronger than that of the RBF neural network without the main component extraction.

  4. Predicting short-term weight loss using four leading health behavior change theories

    Directory of Open Access Journals (Sweden)

    Barata José T

    2007-04-01

    Full Text Available Abstract Background This study was conceived to analyze how exercise and weight management psychosocial variables, derived from several health behavior change theories, predict weight change in a short-term intervention. The theories under analysis were the Social Cognitive Theory, the Transtheoretical Model, the Theory of Planned Behavior, and Self-Determination Theory. Methods Subjects were 142 overweight and obese women (BMI = 30.2 ± 3.7 kg/m2; age = 38.3 ± 5.8y, participating in a 16-week University-based weight control program. Body weight and a comprehensive psychometric battery were assessed at baseline and at program's end. Results Weight decreased significantly (-3.6 ± 3.4%, p Conclusion The present models were able to predict 20–30% of variance in short-term weight loss and changes in weight management self-efficacy accounted for a large share of the predictive power. As expected from previous studies, exercise variables were only moderately associated with short-term outcomes; they are expected to play a larger explanatory role in longer-term results.

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

    Directory of Open Access Journals (Sweden)

    Make BJ

    2015-01-01

    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 ß2-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. Keywords: chronic obstructive pulmonary disease, exacerbation, model, predictor, inhaled corticosteroids, bronchodilators 

  6. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    International Nuclear Information System (INIS)

    Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

    2011-01-01

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

  7. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

    2011-01-15

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

  8. Short-Term Wind Speed Prediction Using EEMD-LSSVM Model

    Directory of Open Access Journals (Sweden)

    Aiqing Kang

    2017-01-01

    Full Text Available Hybrid Ensemble Empirical Mode Decomposition (EEMD and Least Square Support Vector Machine (LSSVM is proposed to improve short-term wind speed forecasting precision. The EEMD is firstly utilized to decompose the original wind speed time series into a set of subseries. Then the LSSVM models are established to forecast these subseries. Partial autocorrelation function is adopted to analyze the inner relationships between the historical wind speed series in order to determine input variables of LSSVM models for prediction of every subseries. Finally, the superposition principle is employed to sum the predicted values of every subseries as the final wind speed prediction. The performance of hybrid model is evaluated based on six metrics. Compared with LSSVM, Back Propagation Neural Networks (BP, Auto-Regressive Integrated Moving Average (ARIMA, combination of Empirical Mode Decomposition (EMD with LSSVM, and hybrid EEMD with ARIMA models, the wind speed forecasting results show that the proposed hybrid model outperforms these models in terms of six metrics. Furthermore, the scatter diagrams of predicted versus actual wind speed and histograms of prediction errors are presented to verify the superiority of the hybrid model in short-term wind speed prediction.

  9. Neonatal Pulmonary MRI of Bronchopulmonary Dysplasia Predicts Short-term Clinical Outcomes.

    Science.gov (United States)

    Higano, Nara S; Spielberg, David R; Fleck, Robert J; Schapiro, Andrew H; Walkup, Laura L; Hahn, Andrew D; Tkach, Jean A; Kingma, Paul S; Merhar, Stephanie L; Fain, Sean B; Woods, Jason C

    2018-05-23

    Bronchopulmonary dysplasia (BPD) is a serious neonatal pulmonary condition associated with premature birth, but the underlying parenchymal disease and trajectory are poorly characterized. The current NICHD/NHLBI definition of BPD severity is based on degree of prematurity and extent of oxygen requirement. However, no clear link exists between initial diagnosis and clinical outcomes. We hypothesized that magnetic resonance imaging (MRI) of structural parenchymal abnormalities will correlate with NICHD-defined BPD disease severity and predict short-term respiratory outcomes. Forty-two neonates (20 severe BPD, 6 moderate, 7 mild, 9 non-BPD controls; 40±3 weeks post-menstrual age) underwent quiet-breathing structural pulmonary MRI (ultrashort echo-time and gradient echo) in a NICU-sited, neonatal-sized 1.5T scanner, without sedation or respiratory support unless already clinically prescribed. Disease severity was scored independently by two radiologists. Mean scores were compared to clinical severity and short-term respiratory outcomes. Outcomes were predicted using univariate and multivariable models including clinical data and scores. MRI scores significantly correlated with severities and predicted respiratory support at NICU discharge (P<0.0001). In multivariable models, MRI scores were by far the strongest predictor of respiratory support duration over clinical data, including birth weight and gestational age. Notably, NICHD severity level was not predictive of discharge support. Quiet-breathing neonatal pulmonary MRI can independently assess structural abnormalities of BPD, describe disease severity, and predict short-term outcomes more accurately than any individual standard clinical measure. Importantly, this non-ionizing technique can be implemented to phenotype disease and has potential to serially assess efficacy of individualized therapies.

  10. Hyperdense basilar artery sign diagnoses acute posterior circulation stroke and predicts short-term outcome

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Xiaoping [Affiliated Hospital of China Medical University at Shenyang, Department of Neurology, Shengjing Hospital, Shenyang (China); Guo, Yang [Shengjing Hospital, Department of Neurology, Shenyang (China)

    2010-12-15

    It is well established that the hyperdense middle cerebral artery sign is a specific marker for early ischemia in anterior circulation. However, little is known about the hyperdense basilar artery sign (HDBA) in posterior circulation. Our aim was to determine whether the HDBA sign has utility in early diagnosis of acute posterior circulation stroke and prediction of short-term outcome. Three-blinded readers examined unenhanced computed tomography scans for the HDBA sign, and materials were classified into two groups according to this sign. Vascular risk factors, admission and discharge National Institute of Health Stroke Scale (NIHSS) scores, short-term outcome, and radiological findings between the two groups were compared. One hundred and twenty-six cases of acute posterior circulation stroke (PCS) were included in the study. No statistically significant differences were found in risk factors of ischemic stroke, except atrial fibrillation (P = 0.025). Admission and discharge NIHSS scores for the positive HDBA group were significantly higher than scores for the negative HDBA group (P = 0.001, 0.002, respectively). The infarction territory for the positive HDBA group was mainly multi-region in nature (51.6%, P < 0.001), while the negative HDBA group showed mainly middle territory infarction. Significant independent predictors of short-term outcome included the HDBA sign (P < 0.001) and admission NIHSS scores (P < 0.001). Approximately half of the HDBA patients showed multi-region infarction and a serious neurological symptom. Based on our results, this sign might not only be helpful in early diagnosis of acute PCS but also be able to correlate with a poor short-term outcome. (orig.)

  11. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

  12. Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.

    Science.gov (United States)

    Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

    2017-07-15

    Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k -mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k -mer co-occurrence information with recent advances in deep learning. We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k -mer embedding. We first split DNA sequences into k -mers and pre-train k -mer embedding vectors based on the co-occurrence matrix of k -mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k -mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm . tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn. Supplementary materials are available at

  13. Predicting the short-term risk of diabetes in HIV-positive patients

    DEFF Research Database (Denmark)

    Petoumenos, Kathy; Worm, Signe W; Fontas, Eric

    2012-01-01

    HIV-positive patients receiving combination antiretroviral therapy (cART) frequently experience metabolic complications such as dyslipidemia and insulin resistance, as well as lipodystrophy, increasing the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). Rates of DM and other...... glucose-associated disorders among HIV-positive patients have been reported to range between 2 and 14%, and in an ageing HIV-positive population, the prevalence of DM is expected to continue to increase. This study aims to develop a model to predict the short-term (six-month) risk of DM in HIV...

  14. Predictive Validity of the Columbia-Suicide Severity Rating Scale for Short-Term Suicidal Behavior

    DEFF Research Database (Denmark)

    Conway, Paul Maurice; Erlangsen, Annette; Teasdale, Thomas William

    2017-01-01

    adolescents (90.6% females) who participated at follow-up (85.9%) out of the 99 (49.7%) baseline respondents. All adolescents were recruited from a specialized suicide-prevention clinic in Denmark. Through multivariate logistic regression analyses, we examined whether baseline suicidal behavior predicted......Using the Columbia-Suicide Severity Rating Scale (C-SSRS), we examined the predictive and incremental predictive validity of past-month suicidal behavior and ideation for short-term suicidal behavior among adolescents at high risk of suicide. The study was conducted in 2014 on a sample of 85...... subsequent suicidal behavior (actual attempts and suicidal behavior of any type, including preparatory acts, aborted, interrupted and actual attempts; mean follow-up of 80.8 days, SD = 52.4). Furthermore, we examined whether suicidal ideation severity and intensity incrementally predicted suicidal behavior...

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

    OpenAIRE

    Jones, Gary; Macken, Bill

    2017-01-01

    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...

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

    Science.gov (United States)

    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. Copyright © 2013 Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2017-12-01

    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 PM 2.5 (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.

  18. Serial-order short-term memory predicts vocabulary development: evidence from a longitudinal study.

    Science.gov (United States)

    Leclercq, Anne-Lise; Majerus, Steve

    2010-03-01

    Serial-order short-term memory (STM), as opposed to item STM, has been shown to be very consistently associated with lexical learning abilities in cross-sectional study designs. This study investigated longitudinal predictions between serial-order STM and vocabulary development. Tasks maximizing the temporary retention of either serial-order or item information were administered to kindergarten children aged 4 and 5. At age 4, age 5, and from age 4 to age 5, serial-order STM capacities, but not item STM capacities, were specifically associated with vocabulary development. Moreover, the increase of serial-order STM capacity from age 4 to age 5 predicted the increase of vocabulary knowledge over the same time period. These results support a theoretical position that assumes an important role for serial-order STM capacities in vocabulary acquisition.

  19. Predicting the short-term risk of diabetes in HIV-positive patients

    DEFF Research Database (Denmark)

    Petoumenos, Kathy; Worm, Signe Westring; Fontas, Eric

    2012-01-01

    Introduction: HIV-positive patients receiving combination antiretroviral therapy (cART) frequently experience metabolic complications such as dyslipidemia and insulin resistance, as well as lipodystrophy, increasing the risk of cardiovascular disease (CVD) and diabetes mellitus (DM). Rates of DM ......). Factors predictive of DM included higher glucose, body mass index (BMI) and triglyceride levels, and older age. Among HIV-related factors, recent CD4 counts of...... and other glucose-associated disorders among HIV-positive patients have been reported to range between 2 and 14%, and in an ageing HIV-positive population, the prevalence of DM is expected to continue to increase. This study aims to develop a model to predict the short-term (six-month) risk of DM in HIV...

  20. Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

    Energy Technology Data Exchange (ETDEWEB)

    Melin, Alexander M. [ORNL; Olama, Mohammed M. [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M. [ORNL; Zhang, Yichen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science

    2017-09-01

    The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed to estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.

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

    Science.gov (United States)

    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. Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach

    Directory of Open Access Journals (Sweden)

    Rui Xue

    2015-01-01

    Full Text Available Although bus passenger demand prediction has attracted increased attention during recent years, limited research has been conducted in the context of short-term passenger demand forecasting. This paper proposes an interactive multiple model (IMM filter algorithm-based model to predict short-term passenger demand. After aggregated in 15 min interval, passenger demand data collected from a busy bus route over four months were used to generate time series. Considering that passenger demand exhibits various characteristics in different time scales, three time series were developed, named weekly, daily, and 15 min time series. After the correlation, periodicity, and stationarity analyses, time series models were constructed. Particularly, the heteroscedasticity of time series was explored to achieve better prediction performance. Finally, IMM filter algorithm was applied to combine individual forecasting models with dynamically predicted passenger demand for next interval. Different error indices were adopted for the analyses of individual and hybrid models. The performance comparison indicates that hybrid model forecasts are superior to individual ones in accuracy. Findings of this study are of theoretical and practical significance in bus scheduling.

  3. Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

    Directory of Open Access Journals (Sweden)

    Haimin Yang

    2017-01-01

    Full Text Available Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam, for long short-term memory (LSTM to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

  4. Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

    Science.gov (United States)

    Yang, Haimin; Pan, Zhisong; Tao, Qing

    2017-01-01

    Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

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

    International Nuclear Information System (INIS)

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

    2017-01-01

    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 PM 2.5 (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%). - Highlights: • Regional air pollutant concentration shows an obvious spatiotemporal correlation. • Our prediction model presents superior performance. • Climate data and metadata can significantly

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

    Science.gov (United States)

    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.

  7. Prediction of Sea Surface Temperature Using Long Short-Term Memory

    Science.gov (United States)

    Zhang, Qin; Wang, Hui; Dong, Junyu; Zhong, Guoqiang; Sun, Xin

    2017-10-01

    This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one month daily prediction. We formulate the SST prediction problem as a time series regression problem. LSTM is a special kind of recurrent neural network, which introduces gate mechanism into vanilla RNN to prevent the vanished or exploding gradient problem. It has strong ability to model the temporal relationship of time series data and can handle the long-term dependency problem well. The proposed network architecture is composed of two kinds of layers: LSTM layer and full-connected dense layer. LSTM layer is utilized to model the time series relationship. Full-connected layer is utilized to map the output of LSTM layer to a final prediction. We explore the optimal setting of this architecture by experiments and report the accuracy of coastal seas of China to confirm the effectiveness of the proposed method. In addition, we also show its online updated characteristics.

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

    Science.gov (United States)

    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.

  9. Multi-step prediction for influenza outbreak by an adjusted long short-term memory.

    Science.gov (United States)

    Zhang, J; Nawata, K

    2018-05-01

    Influenza results in approximately 3-5 million annual cases of severe illness and 250 000-500 000 deaths. We urgently need an accurate multi-step-ahead time-series forecasting model to help hospitals to perform dynamical assignments of beds to influenza patients for the annually varied influenza season, and aid pharmaceutical companies to formulate a flexible plan of manufacturing vaccine for the yearly different influenza vaccine. In this study, we utilised four different multi-step prediction algorithms in the long short-term memory (LSTM). The result showed that implementing multiple single-output prediction in a six-layer LSTM structure achieved the best accuracy. The mean absolute percentage errors from two- to 13-step-ahead prediction for the US influenza-like illness rates were all LSTM has been applied and refined to perform multi-step-ahead prediction for influenza outbreaks. Hopefully, this modelling methodology can be applied in other countries and therefore help prevent and control influenza worldwide.

  10. Report of short term research group on environment safety in nuclear fuel cycle, 1983

    International Nuclear Information System (INIS)

    1984-01-01

    The research group on environment safety in nuclear fuel cycle was organized in fiscal 1979 as the research group in the range of the common utilization of Yayoi, and this is the third year since it developed into the short term research group in the Nuclear Engineering Research Laboratory. The results obtained so far were summarized in three reports, UTNL-R110, 134 and 147. In this fiscal year, ''The chemistry of reprocessing'' is the subtheme, and this short term research is to be carried out. The meeting is held on March 23 and 24, 1984, in this Laboratory, and the following reports are presented. The conference on institutional stability and the disposal of nuclear and chemically toxic wastes held at MIT, the social scientific analysis of nuclear power development, the present status of reprocessing research in foreign countries, the problems based on the operation experience of actual plants, the chemistry of fuel dissolution, the chemistry of solvent extraction, reprocessing offgas treatment and problems, the chemistry of fixing Kr and I in zeolite, waste treatment in the Tokai Reprocessing Plant of Power Reactor and Nuclear Fuel Development Corp., the chemistry of actinoids, denitration process and the chemistry of MOX production, and future reprocessing research. (Kako, I.)

  11. Sensitivity Analysis of Wavelet Neural Network Model for Short-Term Traffic Volume Prediction

    Directory of Open Access Journals (Sweden)

    Jinxing Shen

    2013-01-01

    Full Text Available In order to achieve a more accurate and robust traffic volume prediction model, the sensitivity of wavelet neural network model (WNNM is analyzed in this study. Based on real loop detector data which is provided by traffic police detachment of Maanshan, WNNM is discussed with different numbers of input neurons, different number of hidden neurons, and traffic volume for different time intervals. The test results show that the performance of WNNM depends heavily on network parameters and time interval of traffic volume. In addition, the WNNM with 4 input neurons and 6 hidden neurons is the optimal predictor with more accuracy, stability, and adaptability. At the same time, a much better prediction record will be achieved with the time interval of traffic volume are 15 minutes. In addition, the optimized WNNM is compared with the widely used back-propagation neural network (BPNN. The comparison results indicated that WNNM produce much lower values of MAE, MAPE, and VAPE than BPNN, which proves that WNNM performs better on short-term traffic volume prediction.

  12. A Gaussian process regression based hybrid approach for short-term wind speed prediction

    International Nuclear Information System (INIS)

    Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian

    2016-01-01

    Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.

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

    Science.gov (United States)

    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. Copyright © 2011. Published by Elsevier Ltd.

  14. Dynamical prediction and pattern mapping in short-term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Aguirre, Luis Antonio; Rodrigues, Daniela D.; Lima, Silvio T. [Departamento de Engenharia Eletronica, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil); Martinez, Carlos Barreira [Departamento de Engenharia Hidraulica e Recursos Hidricos, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil)

    2008-01-15

    This work will not put forward yet another scheme for short-term load forecasting but rather will provide evidences that may improve our understanding about fundamental issues which underlay load forecasting problems. In particular, load forecasting will be decomposed into two main problems, namely dynamical prediction and pattern mapping. It is argued that whereas the latter is essentially static and becomes nonlinear when weekly features in the data are taken into account, the former might not be deterministic at all. In such cases there is no determinism (serial correlations) in the data apart from the average cycle and the best a model can do is to perform pattern mapping. Moreover, when there is determinism in addition to the average cycle, the underlying dynamics are sometimes linear, in which case there is no need to resort to nonlinear models to perform dynamical prediction. Such conclusions were confirmed using real load data and surrogate data analysis. In a sense, the paper details and organizes some general beliefs found in the literature on load forecasting. This sheds some light on real model-building and forecasting problems and helps understand some apparently conflicting results reported in the literature. (author)

  15. SHORT-TERM SOLAR FLARE LEVEL PREDICTION USING A BAYESIAN NETWORK APPROACH

    International Nuclear Information System (INIS)

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

    2010-01-01

    A Bayesian network approach for short-term solar flare level prediction has been proposed based on three sequences of photospheric magnetic field parameters extracted from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms. The magnetic measures, the maximum horizontal gradient, the length of neutral line, and the number of singular points do not have determinate relationships with solar flares, so the solar flare level prediction is considered as an uncertainty reasoning process modeled by the Bayesian network. The qualitative network structure which describes conditional independent relationships among magnetic field parameters and the quantitative conditional probability tables which determine the probabilistic values for each variable are learned from the data set. Seven sequential features-the maximum, the mean, the root mean square, the standard deviation, the shape factor, the crest factor, and the pulse factor-are extracted to reduce the dimensions of the raw sequences. Two Bayesian network models are built using raw sequential data (BN R ) and feature extracted data (BN F ), respectively. The explanations of these models are consistent with physical analyses of experts. The performances of the BN R and the BN F appear comparable with other methods. More importantly, the comprehensibility of the Bayesian network models is better than other methods.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  18. Effect of short-term research training programs on medical students' attitudes toward aging.

    Science.gov (United States)

    Jeste, Dilip V; Avanzino, Julie; Depp, Colin A; Gawronska, Maja; Tu, Xin; Sewell, Daniel D; Huege, Steven F

    2018-01-01

    Strategies to build a larger workforce of physicians dedicated to research on aging are needed. One method to address this shortage of physician scientists in geriatrics is short-term training in aging research for early-stage medical students. The authors examined the effects of two summer research training programs, funded by the National Institutes of Health, on medical students' attitudes toward aging, using the Carolina Opinions on Care of Older Adults (COCOA). The programs combined mentored research, didactics, and some clinical exposure. In a sample of 134 participants, COCOA scores improved significantly after completion of the research training program. There was a significant interaction of gender, such that female students had higher baseline scores than males, but this gender difference in COCOA scores was attenuated following the program. Four of the six COCOA subscales showed significant improvement from baseline: early interest in geriatrics, empathy/compassion, attitudes toward geriatrics careers, and ageism.

  19. Relative performance of different numerical weather prediction models for short term predition of wind wnergy

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G; Landberg, L [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Moennich, K; Waldl, H P [Carl con Ossietzky Univ., Faculty of Physics, Dept. of Energy and Semiconductor, Oldenburg (Germany)

    1999-03-01

    In several approaches presented in other papers in this conference, short term forecasting of wind power for a time horizon covering the next two days is done on the basis of Numerical Weather Prediction (NWP) models. This paper explores the relative merits of HIRLAM, which is the model used by the Danish Meteorological Institute, the Deutschlandmodell from the German Weather Service and the Nested Grid Model used in the US. The performance comparison will be mainly done for a site in Germany which is in the forecasting area of both the Deutschlandmodell and HIRLAM. In addition, a comparison of measured data with the forecasts made for one site in Iowa will be included, which allows conclusions on the merits of all three models. Differences in the relative performances could be due to a better tailoring of one model to its country, or to a tighter grid, or could be a function of the distance between the grid points and the measuring site. Also the amount, in which the performance can be enhanced by the use of model output statistics (topic of other papers in this conference) could give insights into the performance of the models. (au)

  20. V4 activity predicts the strength of visual short-term memory representations.

    Science.gov (United States)

    Sligte, Ilja G; Scholte, H Steven; Lamme, Victor A F

    2009-06-10

    Recent studies have shown the existence of a form of visual memory that lies intermediate of iconic memory and visual short-term memory (VSTM), in terms of both capacity (up to 15 items) and the duration of the memory trace (up to 4 s). Because new visual objects readily overwrite this intermediate visual store, we believe that it reflects a weak form of VSTM with high capacity that exists alongside a strong but capacity-limited form of VSTM. In the present study, we isolated brain activity related to weak and strong VSTM representations using functional magnetic resonance imaging. We found that activity in visual cortical area V4 predicted the strength of VSTM representations; activity was low when there was no VSTM, medium when there was a weak VSTM representation regardless of whether this weak representation was available for report or not, and high when there was a strong VSTM representation. Altogether, this study suggests that the high capacity yet weak VSTM store is represented in visual parts of the brain. Allegedly, only some of these VSTM traces are amplified by parietal and frontal regions and as a consequence reside in traditional or strong VSTM. The additional weak VSTM representations remain available for conscious access and report when attention is redirected to them yet are overwritten as soon as new visual stimuli hit the eyes.

  1. The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management

    Directory of Open Access Journals (Sweden)

    César Hernández-Hernández

    2017-06-01

    Full Text Available Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation.

  2. Prediction of short-term and long-term VOC emissions from SBR bitumen-backed carpet under different temperatures

    NARCIS (Netherlands)

    Yang, X.; Chen, Q.; Bluyssen, P.M.

    1998-01-01

    This paper presents two models for volatile organic compound (VOC) emissions from carpet. One is a numerical model using the computational fluid dynamics (CFD) tech-nique for short-term predictions, the other an analytical model for long-term predictions. The numerical model can (1) deal with

  3. Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, Ian B.; Arendt, Dustin L.; Bell, Eric B.; Volkova, Svitlana

    2017-05-17

    Language in social media is extremely dynamic: new words emerge, trend and disappear, while the meaning of existing words can fluctuate over time. This work addresses several important tasks of visualizing and predicting short term text representation shift, i.e. the change in a word’s contextual semantics. We study the relationship between short-term concept drift and representation shift on a large social media corpus – VKontakte collected during the Russia-Ukraine crisis in 2014 – 2015. We visualize short-term representation shift for example keywords and build predictive models to forecast short-term shifts in meaning from previous meaning as well as from concept drift. We show that short-term representation shift can be accurately predicted up to several weeks in advance and that visualization provides insight into meaning change. Our approach can be used to explore and characterize specific aspects of the streaming corpus during crisis events and potentially improve other downstream classification tasks including real-time event forecasting in social media.

  4. Applicability of short-term accelerated biofouling studies to predict long-term biofouling accumulation in reverse osmosis membrane systems

    KAUST Repository

    Sanawar, Huma

    2018-02-02

    Biofouling studies addressing biofouling control are mostly executed in short-term studies. It is unclear whether data collected from these experiments are representative for long-term biofouling as occurring in full-scale membrane systems. This study investigated whether short-term biofouling studies accelerated by biodegradable nutrient dosage to feed water were predictive for long-term biofouling development without nutrient dosage. Since the presence of a feed spacer has an strong effect on the degree of biofouling, this study employed six geometrically different feed spacers. Membrane fouling simulators (MFSs) were operated with the same (i) membrane, (ii) feed flow and (iii) feed water, but with feed spacers varying in geometry. For the short-term experiment, biofilm formation was enhanced by nutrient dosage to the MFS feed water, whereas no nutrient dosage was applied in the long-term experiment. Pressure drop development was monitored to characterize the extent of biofouling, while the accumulated viable biomass content at the end of the experimental run was quantified by adenosine triphosphate (ATP) measurements. Impact of feed spacer geometry on biofouling was compared for the short-term and long-term biofouling study. The results of the study revealed that the feed spacers exhibited the same biofouling behavior for (i) the short-term (9-d) study with nutrient dosage and (ii) the long-term (96-d) study without nutrient dosage. For the six different feed spacers, the accumulated viable biomass content (pg ATP.cm) was roughly the same, but the biofouling impact in terms of pressure drop increase in time was significantly different. The biofouling impact ranking of the six feed spacers was the same for the short-term and long-term biofouling studies. Therefore, it can be concluded that short-term accelerated biofouling studies in MFSs are a representative and suitable approach for the prediction of biofouling in membrane filtration systems after long

  5. Short-term changes in arterial inflammation predict long-term changes in atherosclerosis progression

    Energy Technology Data Exchange (ETDEWEB)

    Joseph, Philip [Massachusetts General Hospital and Harvard Medical School, Cardiology Division and Cardiac MR PET CT Program, Boston, MA (United States); McMaster University, Population Health Research Institute, Department of Medicine, and Department of Radiology, Hamilton, ON (Canada); Ishai, Amorina; Tawakol, Ahmed [Massachusetts General Hospital and Harvard Medical School, Cardiology Division and Cardiac MR PET CT Program, Boston, MA (United States); Mani, Venkatesh [Icahn School of Medicine at Mount Sinai School of Medicine, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States); Kallend, David [The Medicines Company, Parsippany, NJ (United States); Rudd, James H.F. [University of Cambridge, Division of Cardiovascular Medicine, Cambridge (United Kingdom); Fayad, Zahi A. [Icahn School of Medicine at Mount Sinai School of Medicine, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States); Icahn School of Medicine at Mount Sinai School of Medicine, Hess CSM Building Floor TMII, Rm S1-104, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States)

    2017-01-15

    It remains unclear whether changes in arterial wall inflammation are associated with subsequent changes in the rate of structural progression of atherosclerosis. In this sub-study of the dal-PLAQUE clinical trial, multi-modal imaging was performed using 18-fludeoxyglucose (FDG) positron emission tomography (PET, at 0 and 6 months) and magnetic resonance imaging (MRI, at 0 and 24 months). The primary objective was to determine whether increasing FDG uptake at 6 months predicted atherosclerosis progression on MRI at 2 years. Arterial inflammation was measured by the carotid FDG target-to-background ratio (TBR), and atherosclerotic plaque progression was defined as the percentage change in carotid mean wall area (MWA) and mean wall thickness (MWT) on MRI between baseline and 24 months. A total of 42 participants were included in this sub-study. The mean age of the population was 62.5 years, and 12 (28.6 %) were women. In participants with (vs. without) any increase in arterial inflammation over 6 months, the long-term changes in both MWT (% change MWT: 17.49 % vs. 1.74 %, p = 0.038) and MWA (% change MWA: 25.50 % vs. 3.59 %, p = 0.027) were significantly greater. Results remained significant after adjusting for clinical and biochemical covariates. Individuals with no increase in arterial inflammation over 6 months had no significant structural progression of atherosclerosis over 24 months as measured by MWT (p = 0.616) or MWA (p = 0.373). Short-term changes in arterial inflammation are associated with long-term structural atherosclerosis progression. These data support the concept that therapies that reduce arterial inflammation may attenuate or halt progression of atherosclerosis. (orig.)

  6. Feasibility study of short-term earthquake prediction using ionospheric anomalies immediately before large earthquakes

    Science.gov (United States)

    Heki, K.; He, L.

    2017-12-01

    We showed that positive and negative electron density anomalies emerge above the fault immediately before they rupture, 40/20/10 minutes before Mw9/8/7 earthquakes (Heki, 2011 GRL; Heki and Enomoto, 2013 JGR; He and Heki 2017 JGR). These signals are stronger for earthquake with larger Mw and under higher background vertical TEC (total electron conetent) (Heki and Enomoto, 2015 JGR). The epicenter, the positive and the negative anomalies align along the local geomagnetic field (He and Heki, 2016 GRL), suggesting electric fields within ionosphere are responsible for making the anomalies (Kuo et al., 2014 JGR; Kelley et al., 2017 JGR). Here we suppose the next Nankai Trough earthquake that may occur within a few tens of years in Southwest Japan, and will discuss if we can recognize its preseismic signatures in TEC by real-time observations with GNSS.During high geomagnetic activities, large-scale traveling ionospheric disturbances (LSTID) often propagate from auroral ovals toward mid-latitude regions, and leave similar signatures to preseismic anomalies. This is a main obstacle to use preseismic TEC changes for practical short-term earthquake prediction. In this presentation, we show that the same anomalies appeared 40 minutes before the mainshock above northern Australia, the geomagnetically conjugate point of the 2011 Tohoku-oki earthquake epicenter. This not only demonstrates that electric fields play a role in making the preseismic TEC anomalies, but also offers a possibility to discriminate preseismic anomalies from those caused by LSTID. By monitoring TEC in the conjugate areas in the two hemisphere, we can recognize anomalies with simultaneous onset as those caused by within-ionosphere electric fields (e.g. preseismic anomalies, night-time MSTID) and anomalies without simultaneous onset as gravity-wave origin disturbances (e.g. LSTID, daytime MSTID).

  7. Short-term changes in arterial inflammation predict long-term changes in atherosclerosis progression

    International Nuclear Information System (INIS)

    Joseph, Philip; Ishai, Amorina; Tawakol, Ahmed; Mani, Venkatesh; Kallend, David; Rudd, James H.F.; Fayad, Zahi A.

    2017-01-01

    It remains unclear whether changes in arterial wall inflammation are associated with subsequent changes in the rate of structural progression of atherosclerosis. In this sub-study of the dal-PLAQUE clinical trial, multi-modal imaging was performed using 18-fludeoxyglucose (FDG) positron emission tomography (PET, at 0 and 6 months) and magnetic resonance imaging (MRI, at 0 and 24 months). The primary objective was to determine whether increasing FDG uptake at 6 months predicted atherosclerosis progression on MRI at 2 years. Arterial inflammation was measured by the carotid FDG target-to-background ratio (TBR), and atherosclerotic plaque progression was defined as the percentage change in carotid mean wall area (MWA) and mean wall thickness (MWT) on MRI between baseline and 24 months. A total of 42 participants were included in this sub-study. The mean age of the population was 62.5 years, and 12 (28.6 %) were women. In participants with (vs. without) any increase in arterial inflammation over 6 months, the long-term changes in both MWT (% change MWT: 17.49 % vs. 1.74 %, p = 0.038) and MWA (% change MWA: 25.50 % vs. 3.59 %, p = 0.027) were significantly greater. Results remained significant after adjusting for clinical and biochemical covariates. Individuals with no increase in arterial inflammation over 6 months had no significant structural progression of atherosclerosis over 24 months as measured by MWT (p = 0.616) or MWA (p = 0.373). Short-term changes in arterial inflammation are associated with long-term structural atherosclerosis progression. These data support the concept that therapies that reduce arterial inflammation may attenuate or halt progression of atherosclerosis. (orig.)

  8. The state-of-the-art in short-term prediction of wind power. A literature overview

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Brownsword, R.; Kariniotakis, G.

    2003-08-01

    Based on an appropriate questionnaire (WP1.1) and some other works already in progress, this report details the state-of-the-art in short term prediction of wind power, mostly summarising nearly all existing literature on the topic. (au)

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

    Science.gov (United States)

    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…

  10. Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach

    International Nuclear Information System (INIS)

    Chen, Kuilin; Yu, Jie

    2014-01-01

    Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations

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

    Science.gov (United States)

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

    Science.gov (United States)

    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…

  13. Predicting Employment Outcomes for Consumers in Community College Short-Term Training Programs

    Science.gov (United States)

    Flannery, K. Brigid; Benz, Michael R.; Yovanoff, Paul; Kato, Mary McGrath; Lindstrom, Lauren

    2011-01-01

    Postsecondary education has been linked to improved access to employment opportunities for individuals with and without disabilities. The purpose of this study was to determine factors associated with increased employment outcomes for Vocational Rehabilitation consumers enrolled in community college short term occupational skill training programs.…

  14. V4 activity predicts the strength of visual short-term memory representations

    NARCIS (Netherlands)

    Sligte, I.G.; Scholte, H.S.; Lamme, V.A.F.

    2009-01-01

    Recent studies have shown the existence of a form of visual memory that lies intermediate of iconic memory and visual short-term memory (VSTM), in terms of both capacity (up to 15 items) and the duration of the memory trace (up to 4 s). Because new visual objects readily overwrite this intermediate

  15. Improving short-term air quality predictions over the U.S. using chemical data assimilation

    Science.gov (United States)

    Kumar, R.; Delle Monache, L.; Alessandrini, S.; Saide, P.; Lin, H. C.; Liu, Z.; Pfister, G.; Edwards, D. P.; Baker, B.; Tang, Y.; Lee, P.; Djalalova, I.; Wilczak, J. M.

    2017-12-01

    State and local air quality forecasters across the United States use air quality forecasts from the National Air Quality Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) as one of the key tools to protect the public from adverse air pollution related health effects by dispensing timely information about air pollution episodes. This project funded by the National Aeronautics and Space Administration (NASA) aims to enhance the decision-making process by improving the accuracy of NAQFC short-term predictions of ground-level particulate matter of less than 2.5 µm in diameter (PM2.5) by exploiting NASA Earth Science Data with chemical data assimilation. The NAQFC is based on the Community Multiscale Air Quality (CMAQ) model. To improve the initialization of PM2.5 in CMAQ, we developed a new capability in the community Gridpoint Statistical Interpolation (GSI) system to assimilate Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals in CMAQ. Specifically, we developed new capabilities within GSI to read/write CMAQ data, a forward operator that calculates AOD at 550 nm from CMAQ aerosol chemical composition and an adjoint of the forward operator that translates the changes in AOD to aerosol chemical composition. A generalized background error covariance program called "GEN_BE" has been extended to calculate background error covariance using CMAQ output. The background error variances are generated using a combination of both emissions and meteorological perturbations to better capture sources of uncertainties in PM2.5 simulations. The newly developed CMAQ-GSI system is used to perform daily 24-h PM2.5 forecasts with and without data assimilation from 15 July to 14 August 2014, and the resulting forecasts are compared against AirNOW PM2.5 measurements at 550 stations across the U. S. We find that the assimilation of MODIS AOD retrievals improves initialization of the CMAQ model

  16. SHORT-TERM AND LONG-TERM WATER LEVEL PREDICTION AT ONE RIVER MEASUREMENT LOCATION

    Directory of Open Access Journals (Sweden)

    Rudolf Scitovski

    2012-12-01

    Full Text Available Global hydrological cycles mainly depend on climate changes whose occurrence is predominantly triggered by solar and terrestrial influence, and the knowledge of the high water regime is widely applied in hydrology. Regular monitoring and studying of river water level behavior is important from several perspectives. On the basis of the given data, by using modifications of general approaches known from literature, especially from investigation in hydrology, the problem of long- and short-term water level forecast at one river measurement location is considered in the paper. Long-term forecasting is considered as the problem of investigating the periodicity of water level behavior by using linear-trigonometric regression and short-term forecasting is based on the modification of the nearest neighbor method. The proposed methods are tested on data referring to the Drava River level by Donji Miholjac, Croatia, in the period between the beginning of 1900 and the end of 2012.

  17. Benefits for wind energy in electricity markets from using short term wind power prediction tools: a simulation study

    International Nuclear Information System (INIS)

    Usaola, J.; Ravelo, O.; Gonzalez, G.; Soto, F.; Davila, M.C.; Diaz-Guerra, B.

    2004-01-01

    One of the characteristics of wind energy, from the grid point of view, is its non-dispatchability, i.e. generation cannot be ordered, hence integration in electrical networks may be difficult. Short-term wind power prediction-tools could make this integration easier, either by their use by the grid System Operator, or by promoting the participation of wind farms in the electricity markets and using prediction tools to make their bids in the market. In this paper, the importance of a short-term wind power-prediction tool for the participation of wind energy systems in electricity markets is studied. Simulations, according to the current Spanish market rules, have been performed to the production of different wind farms, with different degrees of accuracy in the prediction tool. It may be concluded that income from participation in electricity markets is increased using a short-term wind power prediction-tool of average accuracy. This both marginally increases income and also reduces the impact on system operation with the improved forecasts. (author)

  18. Research on Cascade Reservoirs’ Short-Term Optimal Operation under the Effect of Reverse Regulation

    Directory of Open Access Journals (Sweden)

    Changming Ji

    2018-06-01

    Full Text Available Currently research on joint operation of a large reservoir and its re-regulating reservoir focuses on either water quantity regulation or water head regulation. The accuracy of relevant models is in need of improvement if the influence of factors such as water flow hysteresis and the aftereffect of tail water level variation are taken into consideration. In this paper, given the actual production of Pankou-Xiaoxuan cascade hydropower stations that combines two operation modes (‘electricity to water’ and ‘water to electricity’, a coupling model of their short-term optimal operation is developed, which considers Xiaoxuan reservoir’s regulating effect on Pankou reservoir’s outflow volume and water head. Factors such as water flow hysteresis and the aftereffect of tail water level variation are also considered to enhance the model’s accuracy. The Backward Propagation (BP neural network is employed for precise calculation of the downstream reservoir’s inflow and the upstream reservoir’s tail water level. Besides, we put forth Accompanying Progressive Optimality Algorithm (APOA to solve the coupling model with aftereffect. An example is given to verify the scientificity of the proposed model and the advantages of APOA. Through analysis of the model calculation results, the optimal operation rules of the cascade reservoirs are obtained in terms of water quantity regulation and water head regulation, which can provide scientific reference for cascade reservoirs’ optimal operation.

  19. Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network

    OpenAIRE

    Stewart, Ian; Arendt, Dustin; Bell, Eric; Volkova, Svitlana

    2017-01-01

    Language in social media is extremely dynamic: new words emerge, trend and disappear, while the meaning of existing words can fluctuate over time. Such dynamics are especially notable during a period of crisis. This work addresses several important tasks of measuring, visualizing and predicting short term text representation shift, i.e. the change in a word's contextual semantics, and contrasting such shift with surface level word dynamics, or concept drift, observed in social media streams. ...

  20. Humidifier disinfectant-associated lung injury in adults: Prognostic factors in predicting short-term outcome

    International Nuclear Information System (INIS)

    Koo, Hyun Jung; Do, Kyung-Hyun; Chae, Eun Jin; Kim, Hwa Jung; Song, Joon Seon; Jang, Se Jin; Hong, Sang-Bum; Huh, Jin Won; Lee, En; Hong, Soo-Jong

    2017-01-01

    To identify clinical and radiologic findings that affect disease severity and short-term prognosis of humidifier disinfectant-associated lung injury in adults and to compare computed tomography (CT) findings between the patients with and without death or lung transplantation. Fifty-nine adults (mean age, 34 years; M/F = 12:47) were enrolled in this retrospective study. Medical records and prospective surveillance data were used to assess clinical and radiological factors associated with a poor clinical outcome. Multivariate generalized estimating equation models were used to analyse serial CT findings. Overall cumulative major events including lung transplantation and mortality were assessed using the Kaplan-Meier method. Almost half needed ICU admission (47.5 %) and 17 died (28.8 %). Young age, peripartum and low O_2 saturation were factors associated with ICU admission. On initial chest radiographs, consolidation (P < 0.001) and ground-glass opacity (P = 0.01) were significantly noted in patients who required ICU admission. CT findings including consolidation (odds ratio (OR), 1.02), pneumomediastinum (OR, 1.66) and pulmonary interstitial emphysema (OR, 1.61) were the risk factors for lung transplantation and mortality. Clinical and radiologic findings are related to the risks of lung transplantation and mortality of humidifier disinfectant-associated lung injury. Consolidation, pneumomediastinum and pulmonary interstitial emphysema were short-term prognostic CT findings. (orig.)

  1. Humidifier disinfectant-associated lung injury in adults: Prognostic factors in predicting short-term outcome

    Energy Technology Data Exchange (ETDEWEB)

    Koo, Hyun Jung; Do, Kyung-Hyun; Chae, Eun Jin [University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Asan Medical Center, Songpa-gu, Seoul (Korea, Republic of); Kim, Hwa Jung [University of Ulsan College of Medicine, Cancer Center, Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, Seoul (Korea, Republic of); Song, Joon Seon; Jang, Se Jin [University of Ulsan College of Medicine, Department of Pathology, Asan Medical Center, Seoul (Korea, Republic of); Hong, Sang-Bum; Huh, Jin Won [University of Ulsan College of Medicine, Department of Pulmonary and Critical Care Medicine, Asan Medical Center, Seoul (Korea, Republic of); Lee, En [Inje University Haundae Paik Hospital, Department of Pediatrics, Busan (Korea, Republic of); Hong, Soo-Jong [University of Ulsan College of Medicine, Department of Pediatrics, Childhood Asthma and Atopy Center, Environmental Health Center, Asan Medical Center, Seoul (Korea, Republic of)

    2017-01-15

    To identify clinical and radiologic findings that affect disease severity and short-term prognosis of humidifier disinfectant-associated lung injury in adults and to compare computed tomography (CT) findings between the patients with and without death or lung transplantation. Fifty-nine adults (mean age, 34 years; M/F = 12:47) were enrolled in this retrospective study. Medical records and prospective surveillance data were used to assess clinical and radiological factors associated with a poor clinical outcome. Multivariate generalized estimating equation models were used to analyse serial CT findings. Overall cumulative major events including lung transplantation and mortality were assessed using the Kaplan-Meier method. Almost half needed ICU admission (47.5 %) and 17 died (28.8 %). Young age, peripartum and low O{sub 2} saturation were factors associated with ICU admission. On initial chest radiographs, consolidation (P < 0.001) and ground-glass opacity (P = 0.01) were significantly noted in patients who required ICU admission. CT findings including consolidation (odds ratio (OR), 1.02), pneumomediastinum (OR, 1.66) and pulmonary interstitial emphysema (OR, 1.61) were the risk factors for lung transplantation and mortality. Clinical and radiologic findings are related to the risks of lung transplantation and mortality of humidifier disinfectant-associated lung injury. Consolidation, pneumomediastinum and pulmonary interstitial emphysema were short-term prognostic CT findings. (orig.)

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  4. The value of perfusion CT in predicting the short-term response to synchronous radiochemotherapy for cervical squamous cancer

    International Nuclear Information System (INIS)

    Li, Xiang Sheng; Fan, Hong Xia; Zhu, Hong Xian; Song, Yun Long; Zhou, Chun Wu

    2012-01-01

    To determine the value of the perfusion parameters in predicting short-term tumour response to synchronous radiochemotherapy for cervical squamous carcinoma. Ninety-three patients with cervical squamous carcinoma later than stage IIB were included in this study. Perfusion CT was performed for all these patients who subsequently received the same synchronous radiochemotherapy. The patients were divided into responders and non-responders according to short-term response to treatment. Baseline perfusion parameters of the two groups were compared. The perfusion parameters that might affect treatment effect were analysed by using a multivariate multi-regression analysis. The responders group had higher baseline permeability-surface area product (PS) and blood volume (BV) values than the non-responders group (P 0.05). At multivariate multi-regression analysis, BV, PS and tumour size were significant factors in the prediction of treatment effect. Small tumours usually had high PS and BV values, and thus had a good treatment response. Perfusion CT can provide some helpful information for the prediction of the short-term effect. Synchronous radiochemotherapy may be more effective in cervical squamous carcinoma with higher baseline PS and BV. (orig.)

  5. Short-term outcomes of a program developed to inculcate research essentials in undergraduate medical students

    Directory of Open Access Journals (Sweden)

    V Devi

    2015-01-01

    Full Text Available Background: Participation in research during undergraduate studies may increase students′ interest in research and inculcate research essentials in them. Aims: The purpose of this study was to evaluate the effectiveness of the mentored student project (MSP program. Settings and Design: In the MSP program, students in groups (n = 3 to 5 undertook a research project, wrote a scholarly report, and presented the work as a poster presentation with the help of a faculty mentor. To begin with, the logic model of the program was developed to identify short-term outcomes of the program on students, mentors, and the institution. A quasi-experimental design was used to measure the outcomes. Materials and Methods: A mixed method evaluation was done using a newly-developed questionnaire to assess the impact of the MSP on students′ attitude, a multiple-choice question (MCQs test to find out the impact on students′ knowledge and grading of students′ project reports and posters along with a survey to check the impact on skills. Students′ satisfaction regarding the program and mentors′ perceptions were collected using questionnaires. Evidence for validity was collected for all the instruments used for the evaluation. Statistical Analysis: Non-parametric tests were used to analyze data. Based on the scores, project reports and posters were graded into A (>70% marks, B (60-69% marks, and C (<59% marks categories. The number of MSPs that resulted in publications, conference presentation and departmental collaborations were taken as impact on the institution. Results: Students′ response rate was 91.5%. The students′ attitudes regarding research changed positively (P = 0.036 and score in the MCQ test improved (P < 0.001 after undertaking MSP. Majority of project reports and posters were of grade A category. The majority of the items related to skills gained and satisfaction had a median score of 4. The MSPs resulted in inter-departmental and inter

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

    Science.gov (United States)

    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. 

  7. Short-term predictability of crude oil markets: A detrended fluctuation analysis approach

    International Nuclear Information System (INIS)

    Alvarez-Ramirez, Jose; Alvarez, Jesus; Rodriguez, Eduardo

    2008-01-01

    This paper analyzes the auto-correlations of international crude oil prices on the basis of the estimation of the Hurst exponent dynamics for returns over the period from 1987 to 2007. In doing so, a model-free statistical approach - detrended fluctuation analysis - that reduces the effects of non-stationary market trends and focuses on the intrinsic auto-correlation structure of market fluctuations over different time horizons, is used. Tests for time variations of the Hurst exponent indicate that over long horizons the crude oil market is consistent with the efficient market hypothesis. However, meaningful auto-correlations cannot be excluded for time horizons smaller than one month where the Hurst exponent manifests cyclic, non-periodic dynamics. This means that the market exhibits a time-varying short-term inefficient behavior that becomes efficient in the long term. The proposed methodology and its findings are put in perspective with previous studies and results. (author)

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

    Science.gov (United States)

    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 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.

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

    Science.gov (United States)

    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

  10. Prediction of tritium behavior in rice plant after a short-term exposure of HTO

    International Nuclear Information System (INIS)

    Yook, Dae Sik; Lee, Kun Jai; Choi, Heui Joo; Lee, Chang Min

    2001-01-01

    In many Asian countries including Korea, rice is a very important food crop. Its grain is consumed by humans and its straw is used to feed animals. Because four CANDU reactors are in operation in Korea, relatively large amounts of tritium are released into the environment and the dose by these tritium in the rice plant must be estimated. Since 1997, KAERI (Korea Atomic Energy Research Institute) has carried out experimental studies to obtain domestic data on various parameters related to the direct tritium contamination of plant. But the analysis of the tritium behavior in the rice plant has been insufficient. In this study, the behavior of the tritium in the rice plant is predicted and compared with the measurement performed at KAERI. Using the conceptual model of the soil-plant-atmosphere tritiated water transport system which was suggested by Charles E. Murphy, transient tritium concentrations in soil and leaves were predicted. If the effect of tritium concentration in the soil is taken into account, the tritium concentration in leaves can be described by a double exponential model, however if the tritium concentration in the soil is disregarded, the tritium concentration in leaves can be described by a single exponential term like other relevant models e.g. UFOTRI or STAR-H3 model. The results can be used to predict the tritium concentration in the rice plant near the plant site and to estimate the ingestion dose after the release of tritium to the environment

  11. Vegetation cover, tidal amplitude and land area predict short-term marsh vulnerability in Coastal Louisiana

    Science.gov (United States)

    Schoolmaster, Donald; Stagg, Camille L.; Sharp, Leigh Anne; McGinnis, Tommy S.; Wood, Bernard; Piazza, Sarai

    2018-01-01

    , vegetation cover in prior year was the best single predictor of subsequent loss in most sites followed by changes in percent land and tidal amplitude. The model’s predicted land loss rates correlated well with land loss rates derived from satellite data, although agreement was spatially variable. These results indicate 1) monitoring the loss of small scale vegetation plots can inform patterns of land loss at larger scales 2) the drivers of land loss vary spatially across coastal Louisiana, and 3) relatively simple models have potential as highly informative tools for bioassessment, directing future research, and management planning.

  12. Comparison of Two Predictive Models for Short-Term Mortality in Patients after Severe Traumatic Brain Injury.

    Science.gov (United States)

    Kesmarky, Klara; Delhumeau, Cecile; Zenobi, Marie; Walder, Bernhard

    2017-07-15

    The Glasgow Coma Scale (GCS) and the Abbreviated Injury Score of the head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim of this study was to compare the prognostic performance of an alternative predictive model including motor GCS, pupillary reactivity, age, HAIS, and presence of multi-trauma for short-term mortality with a reference predictive model including motor GCS, pupil reaction, and age (IMPACT core model). A secondary analysis of a prospective epidemiological cohort study in Switzerland including patients after severe TBI (HAIS >3) with the outcome death at 14 days was performed. Performance of prediction, accuracy of discrimination (area under the receiver operating characteristic curve [AUROC]), calibration, and validity of the two predictive models were investigated. The cohort included 808 patients (median age, 56; interquartile range, 33-71), median GCS at hospital admission 3 (3-14), abnormal pupil reaction 29%, with a death rate of 29.7% at 14 days. The alternative predictive model had a higher accuracy of discrimination to predict death at 14 days than the reference predictive model (AUROC 0.852, 95% confidence interval [CI] 0.824-0.880 vs. AUROC 0.826, 95% CI 0.795-0.857; p predictive model had an equivalent calibration, compared with the reference predictive model Hosmer-Lemeshow p values (Chi2 8.52, Hosmer-Lemeshow p = 0.345 vs. Chi2 8.66, Hosmer-Lemeshow p = 0.372). The optimism-corrected value of AUROC for the alternative predictive model was 0.845. After severe TBI, a higher performance of prediction for short-term mortality was observed with the alternative predictive model, compared with the reference predictive model.

  13. Individual differences in rate of encoding predict estimates of visual short-term memory capacity (K).

    Science.gov (United States)

    Jannati, Ali; McDonald, John J; Di Lollo, Vincent

    2015-06-01

    The capacity of visual short-term memory (VSTM) is commonly estimated by K scores obtained with a change-detection task. Contrary to common belief, K may be influenced not only by capacity but also by the rate at which stimuli are encoded into VSTM. Experiment 1 showed that, contrary to earlier conclusions, estimates of VSTM capacity obtained with a change-detection task are constrained by temporal limitations. In Experiment 2, we used change-detection and backward-masking tasks to obtain separate within-subject estimates of K and of rate of encoding, respectively. A median split based on rate of encoding revealed significantly higher K estimates for fast encoders. Moreover, a significant correlation was found between K and the estimated rate of encoding. The present findings raise the prospect that the reported relationships between K and such cognitive concepts as fluid intelligence may be mediated not only by VSTM capacity but also by rate of encoding. (c) 2015 APA, all rights reserved).

  14. Road Short-Term Travel Time Prediction Method Based on Flow Spatial Distribution and the Relations

    Directory of Open Access Journals (Sweden)

    Mingjun Deng

    2016-01-01

    Full Text Available There are many short-term road travel time forecasting studies based on time series, but indeed, road travel time not only relies on the historical travel time series, but also depends on the road and its adjacent sections history flow. However, few studies have considered that. This paper is based on the correlation of flow spatial distribution and the road travel time series, applying nearest neighbor and nonparametric regression method to build a forecasting model. In aspect of spatial nearest neighbor search, three different space distances are defined. In addition, two forecasting functions are introduced: one combines the forecasting value by mean weight and the other uses the reciprocal of nearest neighbors distance as combined weight. Three different distances are applied in nearest neighbor search, which apply to the two forecasting functions. For travel time series, the nearest neighbor and nonparametric regression are applied too. Then minimizing forecast error variance is utilized as an objective to establish the combination model. The empirical results show that the combination model can improve the forecast performance obviously. Besides, the experimental results of the evaluation for the computational complexity show that the proposed method can satisfy the real-time requirement.

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

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    Full Text Available 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.

  16. On the short-term predictability of fully digital chaotic oscillators for pseudo-random number generation

    KAUST Repository

    Radwan, Ahmed Gomaa

    2014-06-18

    This paper presents a digital implementation of a 3rd order chaotic system using the Euler approximation. Short-term predictability is studied in relation to system precision, Euler step size and attractor size and optimal parameters for maximum performance are derived. Defective bits from the native chaotic output are neglected and the remaining pass the NIST SP. 800-22 tests without post-processing. The resulting optimized pseudorandom number generator has throughput up to 17.60 Gbits/s for a 64-bit design experimentally verified on a Xilinx Virtex 4 FPGA with logic utilization less than 1.85%.

  17. On the short-term predictability of fully digital chaotic oscillators for pseudo-random number generation

    KAUST Repository

    Radwan, Ahmed Gomaa; Mansingka, Abhinav S.; Salama, Khaled N.; Zidan, Mohammed A.

    2014-01-01

    This paper presents a digital implementation of a 3rd order chaotic system using the Euler approximation. Short-term predictability is studied in relation to system precision, Euler step size and attractor size and optimal parameters for maximum performance are derived. Defective bits from the native chaotic output are neglected and the remaining pass the NIST SP. 800-22 tests without post-processing. The resulting optimized pseudorandom number generator has throughput up to 17.60 Gbits/s for a 64-bit design experimentally verified on a Xilinx Virtex 4 FPGA with logic utilization less than 1.85%.

  18. Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

    Science.gov (United States)

    Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

    2016-09-01

    We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

  19. Short-term prediction method of wind speed series based on fractal interpolation

    International Nuclear Information System (INIS)

    Xiu, Chunbo; Wang, Tiantian; Tian, Meng; Li, Yanqing; Cheng, Yi

    2014-01-01

    Highlights: • An improved fractal interpolation prediction method is proposed. • The chaos optimization algorithm is used to obtain the iterated function system. • The fractal extrapolate interpolation prediction of wind speed series is performed. - Abstract: In order to improve the prediction performance of the wind speed series, the rescaled range analysis is used to analyze the fractal characteristics of the wind speed series. An improved fractal interpolation prediction method is proposed to predict the wind speed series whose Hurst exponents are close to 1. An optimization function which is composed of the interpolation error and the constraint items of the vertical scaling factors in the fractal interpolation iterated function system is designed. The chaos optimization algorithm is used to optimize the function to resolve the optimal vertical scaling factors. According to the self-similarity characteristic and the scale invariance, the fractal extrapolate interpolation prediction can be performed by extending the fractal characteristic from internal interval to external interval. Simulation results show that the fractal interpolation prediction method can get better prediction result than others for the wind speed series with the fractal characteristic, and the prediction performance of the proposed method can be improved further because the fractal characteristic of its iterated function system is similar to that of the predicted wind speed series

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

    Science.gov (United States)

    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.

  1. Overgeneral memory predicts stability of short-term outcome of electroconvulsive therapy for depression.

    Science.gov (United States)

    Raes, Filip; Sienaert, Pascal; Demyttenaere, Koen; Peuskens, Joseph; Williams, J Mark G; Hermans, Dirk

    2008-03-01

    To investigate the predictive value of overgeneral memory (OGM) for outcome of electroconvulsive therapy (ECT) for depression. The Autobiographical Memory Test was used to measure OGM in 25 patients with depression before ECT. The Hamilton Rating Scale for Depression (HRSD) was administered weekly to 1 week posttreatment. Overgeneral memory did not predict HRSD scores from the last ECT treatment, but did predict HRSD change scores from the last treatment to 1-week follow-up: patients high in OGM experienced a relatively greater increase in HRSD scores after the last treatment. Results further extend the status of OGM as a predictor of an unfavorable course of depression to a previously unstudied ECT population.

  2. Short Term Prediction of Freeway Exiting Volume Based on SVM and KNN

    Directory of Open Access Journals (Sweden)

    Xiang Wang

    2015-09-01

    The model results indicate that the proposed algorithm is feasible and accurate. The Mean Absolute Percentage Error is under 10%. When comparing with the results of single KNN or SVM method, the results show that the combination of KNN and SVM can improve the reliability of the prediction significantly. The proposed method can be implemented in the on-line application of exiting volume prediction, which is able to consider different vehicle types.

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

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas

    2012-01-01

    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 forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

  4. Comparison of short-term rainfall forecasts for modelbased flow prediction in urban drainage systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Ahm, Malte; Nielsen, Jesper Ellerbek

    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...... performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times....

  5. A new approach to very short term wind speed prediction using k-nearest neighbor classification

    International Nuclear Information System (INIS)

    Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

    2013-01-01

    Highlights: ► Wind speed parameter was predicted in an n-tupled inputs using k-NN classification. ► The effects of input parameters, nearest neighbors and distance metrics were analyzed. ► Many useful and reasonable inferences were uncovered using the developed model. - Abstract: Wind energy is an inexhaustible energy source and wind power production has been growing rapidly in recent years. However, wind power has a non-schedulable nature due to wind speed variations. Hence, wind speed prediction is an indispensable requirement for power system operators. This paper predicts wind speed parameter in an n-tupled inputs using k-nearest neighbor (k-NN) classification and analyzes the effects of input parameters, nearest neighbors and distance metrics on wind speed prediction. The k-NN classification model was developed using the object oriented programming techniques and includes Manhattan and Minkowski distance metrics except from Euclidean distance metric on the contrary of literature. The k-NN classification model which uses wind direction, air temperature, atmospheric pressure and relative humidity parameters in a 4-tupled space achieved the best wind speed prediction for k = 5 in the Manhattan distance metric. Differently, the k-NN classification model which uses wind direction, air temperature and atmospheric pressure parameters in a 3-tupled inputs gave the worst wind speed prediction for k = 1 in the Minkowski distance metric

  6. Association of learning styles with research self-efficacy: study of short-term research training program for medical students.

    Science.gov (United States)

    Dumbauld, Jill; Black, Michelle; Depp, Colin A; Daly, Rebecca; Curran, Maureen A; Winegarden, Babbi; Jeste, Dilip V

    2014-12-01

    With a growing need for developing future physician scientists, identifying characteristics of medical students who are likely to benefit from research training programs is important. This study assessed if specific learning styles of medical students, participating in federally funded short-term research training programs, were associated with research self-efficacy, a potential predictor of research career success. Seventy-five first-year medical students from 28 medical schools, selected to participate in two competitive NIH-supported summer programs for research training in aging, completed rating scales to evaluate learning styles at baseline, and research self-efficacy before and after training. We examined associations of individual learning styles (visual-verbal, sequential-global, sensing-intuitive, and active-reflective) with students' gender, ranking of medical school, and research self-efficacy. Research self-efficacy improved significantly following the training programs. Students with a verbal learning style reported significantly greater research self-efficacy at baseline, while visual, sequential, and intuitive learners demonstrated significantly greater increases in research self-efficacy from baseline to posttraining. No significant relationships were found between learning styles and students' gender or ranking of their medical school. Assessments of learning styles may provide useful information to guide future training endeavors aimed at developing the next generation of physician-scientists. © 2014 Wiley Periodicals, Inc.

  7. Analysts’ forecast error: A robust prediction model and its short term trading profitability

    NARCIS (Netherlands)

    Boudt, K.M.R.; de Goei, P.; Thewissen, J.; van Campenhout, G.

    2015-01-01

    This paper contributes to the empirical evidence on the investment horizon salient to trading based on predicting the error in analysts' earnings forecasts. An econometric framework is proposed that accommodates the stylized fact of extreme values in the forecast error series. We find that between

  8. Overview, comparative assessment and recommendations of forecasting models for short-term water demand prediction

    CSIR Research Space (South Africa)

    Anele, AO

    2017-11-01

    Full Text Available -term water demand (STWD) forecasts. In view of this, an overview of forecasting methods for STWD prediction is presented. Based on that, a comparative assessment of the performance of alternative forecasting models from the different methods is studied. Times...

  9. Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction

    Directory of Open Access Journals (Sweden)

    Changbin Hu

    2015-02-01

    Full Text Available According to the topological structure of wind-storage-load complementation microgrids, this paper proposes a method for energy coordinative optimization which focuses on improvement of the economic benefits of microgrids in the prediction framework. First of all, the external characteristic mathematical model of distributed generation (DG units including wind turbines and storage batteries are established according to the requirements of the actual constraints. Meanwhile, using the minimum consumption costs from the external grid as the objective function, a grey prediction model with residual modification is introduced to output the predictive wind turbine power and load at specific periods. Second, based on the basic framework of receding horizon optimization, an intelligent genetic algorithm (GA is applied to figure out the optimum solution in the predictive horizon for the complex non-linear coordination control model of microgrids. The optimum results of the GA are compared with the receding solution of mixed integer linear programming (MILP. The obtained results show that the method is a viable approach for energy coordinative optimization of microgrid systems for energy flow and reasonable schedule. The effectiveness and feasibility of the proposed method is verified by examples.

  10. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models

    Directory of Open Access Journals (Sweden)

    B. M. Brentan

    2017-01-01

    Full Text Available Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA and machine learning powerful algorithms such as Self-Organizing Maps (SOMs and Random Forest (RF. We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.

  11. Short-Term changes on MRI predict long-Term changes on radiography in rheumatoid arthritis

    DEFF Research Database (Denmark)

    Peterfy, Charles; Strand, Vibeke; Tian, Lu

    2017-01-01

    Objective In rheumatoid arthritis (RA), MRI provides earlier detection of structural damage than radiography (X-ray) and more sensitive detection of intra-Articular inflammation than clinical examination. This analysis was designed to evaluate the ability of early MRI findings to predict subsequent...

  12. Short-term prediction of windfarm power output - from theory to practice

    International Nuclear Information System (INIS)

    Landberg, L.

    1998-01-01

    From the very complicated and evolved theories of boundary-layer meteorology encompassing the equations of turbulence and mean flow, a model has been derived to predict the power output from wind farms. For practical dispatching purposes the predictions must reach as far into the future as 36 hours. The model has been put into an operation frame-work where the predictions for a number of wind farms scattered all over Europe are available on-line on the World Wide Web. The system is very versatile and new wind farms can be included within a few days. The system is made up of predictions from the Danish Meteorological Institute HIRLAM model which are refined using the WASP model from Risoe National Laboratory. The paper will describe this operation set-up, give examples of the performance of the model of wind farms in the UK, Denmark, Greece and the US. An analysis of the error for a one-year period will also be presented. Finally, possible improvements will be discussed. These include Kalman filtering and other statistical methods. (Author)

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

    Science.gov (United States)

    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.

  14. Very short-term rainfall forecasting by effectively using the ensemble outputs of numerical weather prediction models

    Science.gov (United States)

    Wu, Ming-Chang; Lin, Gwo-Fong; Feng, Lei; Hwang, Gong-Do

    2017-04-01

    In Taiwan, heavy rainfall brought by typhoons often causes serious disasters and leads to loss of life and property. In order to reduce the impact of these disasters, accurate rainfall forecasts are always important for civil protection authorities to prepare proper measures in advance. In this study, a methodology is proposed for providing very short-term (1- to 6-h ahead) rainfall forecasts in a basin-scale area. The proposed methodology is developed based on the use of analogy reasoning approach to effectively integrate the ensemble precipitation forecasts from a numerical weather prediction system in Taiwan. To demonstrate the potential of the proposed methodology, an application to a basin-scale area (the Choshui River basin located in west-central Taiwan) during five typhoons is conducted. The results indicate that the proposed methodology yields more accurate hourly rainfall forecasts, especially the forecasts with a lead time of 1 to 3 hours. On average, improvement of the Nash-Sutcliffe efficiency coefficient is about 14% due to the effective use of the ensemble forecasts through the proposed methodology. The proposed methodology is expected to be useful for providing accurate very short-term rainfall forecasts during typhoons.

  15. Improved Short-Term Load Forecasting Based on Two-Stage Predictions with Artificial Neural Networks in a Microgrid Environment

    Directory of Open Access Journals (Sweden)

    Jaime Lloret

    2013-08-01

    Full Text Available Short-Term Load Forecasting plays a significant role in energy generation planning, and is specially gaining momentum in the emerging Smart Grids environment, which usually presents highly disaggregated scenarios where detailed real-time information is available thanks to Communications and Information Technologies, as it happens for example in the case of microgrids. This paper presents a two stage prediction model based on an Artificial Neural Network in order to allow Short-Term Load Forecasting of the following day in microgrid environment, which first estimates peak and valley values of the demand curve of the day to be forecasted. Those, together with other variables, will make the second stage, forecast of the entire demand curve, more precise than a direct, single-stage forecast. The whole architecture of the model will be presented and the results compared with recent work on the same set of data, and on the same location, obtaining a Mean Absolute Percentage Error of 1.62% against the original 2.47% of the single stage model.

  16. Time-Series Prediction: Application to the Short-Term Electric Energy Demand

    OpenAIRE

    Troncoso Lora, Alicia; Riquelme Santos, Jesús Manuel; Riquelme Santos, José Cristóbal; Gómez Expósito, Antonio; Martínez Ramos, José Luis

    2003-01-01

    This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to the 24-hour load forecasting problem. Also, based on recorded data, an alternative model is developed by means of a conventional dynamic regression technique, where the parameters are estimated by solving a least squares problem. Finally, results obtained from the application of both techniques to the Spanish transmission system are compared in terms of maximum, average and ...

  17. Short term prediction of the horizontal wind vector within a wake vortex warning system

    Energy Technology Data Exchange (ETDEWEB)

    Frech, M.; Holzaepfel, F.; Gerz, T. [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Wessling (Germany). Inst. fuer Physik der Atmosphaere; Konopka, J. [Deutsche Flugsicherung (DFS) GmbH, Langen (Germany)

    2000-07-14

    A wake vortex warning system (WVWS) has been developed for Frankfurt airport. This airport has two parallel runways which are separated by 518 m, a distance too short to operate them independently because wake vortices may be advected to the adjacent runway. The objective of the WVWS is to enable operation with reduced separation between two aircraft approaching the parallel runways at appropriate wind conditions. The WVWS applies a statistical persistence model to predict the crosswind within a 20 minute period. One of the main problems identified in the old WVWS are discontinuities between successive forecasts. These forecast breakdowns were not acceptable to airtraffic controllers. At least part of the problem was related to the fact that the forecast was solely based on the prediction of crosswind. A new method is developed on the basis of 523 days of sonic anemometer measurements at Frankfurt airport. It is demonstrated that the prediction of the horizontal wind vector avoids these difficulties and significantly improves the system's performance. (orig.)

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

    Directory of Open Access Journals (Sweden)

    F. Anctil

    2009-11-01

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

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

  19. Foreshock sequences and short-term earthquake predictability on East Pacific Rise transform faults.

    Science.gov (United States)

    McGuire, Jeffrey J; Boettcher, Margaret S; Jordan, Thomas H

    2005-03-24

    East Pacific Rise transform faults are characterized by high slip rates (more than ten centimetres a year), predominantly aseismic slip and maximum earthquake magnitudes of about 6.5. Using recordings from a hydroacoustic array deployed by the National Oceanic and Atmospheric Administration, we show here that East Pacific Rise transform faults also have a low number of aftershocks and high foreshock rates compared to continental strike-slip faults. The high ratio of foreshocks to aftershocks implies that such transform-fault seismicity cannot be explained by seismic triggering models in which there is no fundamental distinction between foreshocks, mainshocks and aftershocks. The foreshock sequences on East Pacific Rise transform faults can be used to predict (retrospectively) earthquakes of magnitude 5.4 or greater, in narrow spatial and temporal windows and with a high probability gain. The predictability of such transform earthquakes is consistent with a model in which slow slip transients trigger earthquakes, enrich their low-frequency radiation and accommodate much of the aseismic plate motion.

  20. Working Memory Deficits Predict Short-term Smoking Resumption Following Brief Abstinence*

    Science.gov (United States)

    Patterson, Freda; Jepson, Christopher; Loughead, James; Perkins, Kenneth; Strasser, Andrew A.; Siegel, Steven; Frey, Joseph; Gur, Ruben; Lerman, Caryn

    2009-01-01

    As many as one-half of smokers relapse in the first week following a quit attempt, and subjective reports of cognitive deficits in early abstinence are associated with increased relapse risk. This study examined whether objective cognitive performance after three days of abstinence predicts smoking resumption in a 7-day simulated quit attempt. Sixty-seven treatment-seeking smokers received either varenicline or placebo (randomized double-blind) for 21 days. Following medication run-up (days 1-10), there was a 3-day mandatory (biochemically confirmed) abstinence period (days 11-13) during which working memory (Letter-N-Back Task) and sustained attention (Continuous Performance Task) were assessed (day 13). Participants were then exposed to a scheduled smoking lapse and instructed to try to remain abstinent for the next 7 days (days 15-21). Poorer cognitive performance (slower correct reaction time on Letter-N-Back task) during abstinence predicted more rapid smoking resumption among those receiving placebo (p=.038) but not among those receiving varenicline. These data lend further support for the growing recognition that cognitive deficits involving working memory are a core symptom of nicotine withdrawal and a potential target for the development of pharmacological and behavioral treatments. PMID:19733449

  1. Predicting short term (1 week to 6 months) fuel prices using EIA data

    International Nuclear Information System (INIS)

    Felts, M.C.

    1992-01-01

    Events in the oil market from August 1990 to February 1991 provide an excellent case study for understanding the relationship of oil inventories, product inventories, refinery utilization rates and the prices of crude oil and products. This paper presents a basic overview of how the system works and demonstrates how anyone can predict what will happen next using EIA weekly data. The system of analysis require only that one think logically about the factors involved. The system never fails because it is based on certain conditions which do not change, such as the limited capacity of refineries, storage and transportation facilities. As one becomes familiar with the general theory behind this type of analysis, it is possible to accurately predict the behavior of gasoline and diesel prices in separate areas of the US. Because the US is the primary user of crude oil, conditions in the US refining market also significantly influence the price of crude oil. These price fluctuations can also be anticipated by watching the EIA data

  2. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

    International Nuclear Information System (INIS)

    Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

    2017-01-01

    Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

  3. Short Term Prediction of Highway Travel Time using GUHA Data Mining Method

    Czech Academy of Sciences Publication Activity Database

    Coufal, David; Turunen, E.

    2004-01-01

    Roč. 14, - (2004), s. 221-231 ISSN 1210-0552 R&D Projects: GA MŠk OC 274.001 Grant - others:COST(XE) Action 274 TARSKI Institutional research plan: CEZ:AV0Z1030915 Keywords : data mining * many-valued logic Subject RIV: BA - General Mathematics

  4. Fasting ghrelin does not predict food intake after short-term energy restriction

    NARCIS (Netherlands)

    Blom, W.A.M.; Mars, M.; Hendriks, H.F.J.; Groot, de C.P.G.M.; Stafleu, A.; Kok, F.J.; Graaf, de C.

    2006-01-01

    Objective: To study the role of ghrelin as a hunger signal during energy restriction and to test the hypothesis that changes in fasting leptin concentrations during energy restriction are associated with changes in fasting ghrelin concentrations. Research Methods and Procedures: Thirty-five healthy,

  5. Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Chi-Man Vong

    2012-01-01

    Full Text Available Forecasting of air pollution is a popular and important topic in recent years due to the health impact caused by air pollution. It is necessary to build an early warning system, which provides forecast and also alerts health alarm to local inhabitants by medical practitioners and the local government. Meteorological and pollutions data collected daily at monitoring stations of Macau can be used in this study to build a forecasting system. Support vector machines (SVMs, a novel type of machine learning technique based on statistical learning theory, can be used for regression and time series prediction. SVM is capable of good generalization while the performance of the SVM model is often hinged on the appropriate choice of the kernel.

  6. An Optimized Prediction Intervals Approach for Short Term PV Power Forecasting

    Directory of Open Access Journals (Sweden)

    Qiang Ni

    2017-10-01

    Full Text Available High quality photovoltaic (PV power prediction intervals (PIs are essential to power system operation and planning. To improve the reliability and sharpness of PIs, in this paper, a new method is proposed, which involves the model uncertainties and noise uncertainties, and PIs are constructed with a two-step formulation. In the first step, the variance of model uncertainties is obtained by using extreme learning machine to make deterministic forecasts of PV power. In the second stage, innovative PI-based cost function is developed to optimize the parameters of ELM and noise uncertainties are quantization in terms of variance. The performance of the proposed approach is examined by using the PV power and meteorological data measured from 1kW rooftop DC micro-grid system. The validity of the proposed method is verified by comparing the experimental analysis with other benchmarking methods, and the results exhibit a superior performance.

  7. HPA AXIS RESPONSE TO STRESS PREDICTS SHORT-TERM SNACK INTAKE IN OBESE WOMEN

    OpenAIRE

    Appelhans, Bradley M.; Pagoto, Sherry L.; Peters, Erica N.; Spring, Bonnie J.

    2009-01-01

    Prior research has linked heightened cortisol reactivity to stress with increased food consumption. This pilot study tested corollaries of the hypothesis that cortisol stress reactivity promotes obesity. Thirty-four lean and obese women completed an acute stress task and a non-stressful control task in counterbalanced order. Contrary to expectations, higher post-stress cortisol was associated with decreased post-stress snack intake in obese women but was unrelated to snack intake in lean wome...

  8. A Neuro-genetic Based Short-term Forecasting Framework for Network Intrusion Prediction System

    Institute of Scientific and Technical Information of China (English)

    Siva S. Sivatha Sindhu; S. Geetha; M. Marikannan; A. Kannan

    2009-01-01

    Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by "authorized" users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system (IDS) is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference (KDD 2009) intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS (NGIDS) involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this

  9. A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

    Science.gov (United States)

    Tsiouris, Κostas Μ; Pezoulas, Vasileios C; Zervakis, Michalis; Konitsiotis, Spiros; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I

    2018-05-17

    The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic seizure prediction using EEG signals, expanding the use of deep learning algorithms with convolutional neural networks (CNN). A pre-analysis is initially performed to find the optimal architecture of the LSTM network by testing several modules and layers of memory units. Based on these results, a two-layer LSTM network is selected to evaluate seizure prediction performance using four different lengths of preictal windows, ranging from 15 min to 2 h. The LSTM model exploits a wide range of features extracted prior to classification, including time and frequency domain features, between EEG channels cross-correlation and graph theoretic features. The evaluation is performed using long-term EEG recordings from the open CHB-MIT Scalp EEG database, suggest that the proposed methodology is able to predict all 185 seizures, providing high rates of seizure prediction sensitivity and low false prediction rates (FPR) of 0.11-0.02 false alarms per hour, depending on the duration of the preictal window. The proposed LSTM-based methodology delivers a significant increase in seizure prediction performance compared to both traditional machine learning techniques and convolutional neural networks that have been previously evaluated in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  12. Assessment and prediction of short term hospital admissions: the case of Athens, Greece

    Science.gov (United States)

    Kassomenos, P.; Papaloukas, C.; Petrakis, M.; Karakitsios, S.

    The contribution of air pollution on hospital admissions due to respiratory and heart diseases is a major issue in the health-environmental perspective. In the present study, an attempt was made to run down the relationships between air pollution levels and meteorological indexes, and corresponding hospital admissions in Athens, Greece. The available data referred to a period of eight years (1992-2000) including the daily number of hospital admissions due to respiratory and heart diseases, hourly mean concentrations of CO, NO 2, SO 2, O 3 and particulates in several monitoring stations, as well as, meteorological data (temperature, relative humidity, wind speed/direction). The relations among the above data were studied through widely used statistical techniques (multivariate stepwise analyses) and Artificial Neural Networks (ANNs). Both techniques revealed that elevated particulate concentrations are the dominant parameter related to hospital admissions (an increase of 10 μg m -3 leads to an increase of 10.2% in the number of admissions), followed by O 3 and the rest of the pollutants (CO, NO 2 and SO 2). Meteorological parameters also play a decisive role in the formation of air pollutant levels affecting public health. Consequently, increased/decreased daily hospital admissions are related to specific types of meteorological conditions that favor/do not favor the accumulation of pollutants in an urban complex. In general, the role of meteorological factors seems to be underestimated by stepwise analyses, while ANNs attribute to them a more important role. Comparison of the two models revealed that ANN adaptation in complicate environmental issues presents improved modeling results compared to a regression technique. Furthermore, the ANN technique provides a reliable model for the prediction of the daily hospital admissions based on air quality data and meteorological indices, undoubtedly useful for regulatory purposes.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  15. SHORT-TERM PRECIPITATION OCCURRENCE PREDICTION FOR STRONG CONVECTIVE WEATHER USING FY2-G SATELLITE DATA: A CASE STUDY OF SHENZHEN,SOUTH CHINA

    Directory of Open Access Journals (Sweden)

    K. Chen

    2016-06-01

    Full Text Available 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.

  16. Aberrant GSTP1 promoter methylation predicts short-term prognosis in acute-on-chronic hepatitis B liver failure.

    Science.gov (United States)

    Gao, S; Sun, F-K; Fan, Y-C; Shi, C-H; Zhang, Z-H; Wang, L-Y; Wang, K

    2015-08-01

    Glutathione-S-transferase P1 (GSTP1) methylation has been demonstrated to be associated with oxidative stress induced liver damage in acute-on-chronic hepatitis B liver failure (ACHBLF). To evaluate the methylation level of GSTP1 promoter in acute-on-chronic hepatitis B liver failure and determine its predictive value for prognosis. One hundred and five patients with acute-on-chronic hepatitis B liver failure, 86 with chronic hepatitis B (CHB) and 30 healthy controls (HC) were retrospectively enrolled. GSTP1 methylation level in peripheral mononuclear cells (PBMC) was detected by MethyLight. Clinical and laboratory parameters were obtained. GSTP1 methylation levels were significantly higher in patients with acute-on-chronic hepatitis B liver failure (median 16.84%, interquartile range 1.83-59.05%) than those with CHB (median 1.25%, interquartile range 0.48-2.47%; P chronic hepatitis B liver failure group, nonsurvivors showed significantly higher GSTP1 methylation levels (P chronic hepatitis B liver failure, GSTP1 methylation showed significantly better predictive value than MELD score [area under the receiver operating characteristic curve (AUC) 0.89 vs. 0.72, P chronic hepatitis B liver failure and shows high predictive value for short-term mortality. It might serve as a potential prognostic marker for acute-on-chronic hepatitis B liver failure. © 2015 John Wiley & Sons Ltd.

  17. Value of five-stage prognostic system in predicting short-term outcome of patients with liver cirrhosis

    Directory of Open Access Journals (Sweden)

    TIAN Yan

    2015-03-01

    Full Text Available ObjectiveTo evaluate the clinical value of five-stage prognostic system in predicting the short-term outcome of patients with liver cirrhosis, and to compare it with the Child-Turcotte-Pugh (CTP and Model of End-Stage Liver Disease (MELD scores. MethodsTwo hundred and one hospitalized patients with liver cirrhosis in the Department of Gastroenterology in the First Affiliated Hospital of Anhui Medical University from January 2011 to January 2014 were enrolled in the study and followed up for at least six months. Patients were classified accorded to the five-stage prognostic system, and the mortality rate in each stage was measured. The receiver operating characteristic (ROC curve and the area under the ROC curve (AUC were used to assess the accuracy of the five-stage prognostic system in predicting the short-term death risk of cirrhotic patients, which was then compared with the CTP and MELD scores. Categorical data were analyzed by chi-square test. Comparison of AUC was made by normal distribution Z test. Spearman′s correlation analysis was used to investigate the correlation of the five-stage prognostic system with the CTP and MELD scores. ResultsThe study used the admission time as the starting point and the death of patients or study termination time as the endpoint. Among the 201 patients, 50 (24.9% died within six months. Based on the five-stage prognostic system, the mortality rates for stages 1 to 5 were 0(0/11, 0(0/18, 4.2%(2/48, 16.3% (7/43, and 50.6%(41/81, respectively. In patients with decompensated cirrhosis (stages 3, 4, and 5, the mortality increased with stage, and the differences in mortality between patients in stages 3 and 4, 3 and 5, and 4 and 5 were all significant (χ2=3.89, 35.33, and 13.96, respectively; P=0.049, 0.000, and 0.049, respectively. The AUC for the five-stage prognostic system, five-stage prognostic system combined with CTP and MELD score, and CTP score were 0820, 0.915, 0.888, and 0

  18. Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk

    Science.gov (United States)

    Li, Yane; Fan, Ming; Cheng, Hu; Zhang, Peng; Zheng, Bin; Li, Lihua

    2018-01-01

    This study aims to develop and test a new imaging marker-based short-term breast cancer risk prediction model. An age-matched dataset of 566 screening mammography cases was used. All ‘prior’ images acquired in the two screening series were negative, while in the ‘current’ screening images, 283 cases were positive for cancer and 283 cases remained negative. For each case, two bilateral cranio-caudal view mammograms acquired from the ‘prior’ negative screenings were selected and processed by a computer-aided image processing scheme, which segmented the entire breast area into nine strip-based local regions, extracted the element regions using difference of Gaussian filters, and computed both global- and local-based bilateral asymmetrical image features. An initial feature pool included 190 features related to the spatial distribution and structural similarity of grayscale values, as well as of the magnitude and phase responses of multidirectional Gabor filters. Next, a short-term breast cancer risk prediction model based on a generalized linear model was built using an embedded stepwise regression analysis method to select features and a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) values significantly increased from 0.5863  ±  0.0237 to 0.6870  ±  0.0220 when the model trained by the image features extracted from the global regions and by the features extracted from both the global and the matched local regions (p  =  0.0001). The odds ratio values monotonically increased from 1.00-8.11 with a significantly increasing trend in slope (p  =  0.0028) as the model-generated risk score increased. In addition, the AUC values were 0.6555  ±  0.0437, 0.6958  ±  0.0290, and 0.7054  ±  0.0529 for the three age groups of 37

  19. Malnutrition: a highly predictive risk factor of short-term mortality in elderly presenting to the emergency department.

    Science.gov (United States)

    Gentile, S; Lacroix, O; Durand, A C; Cretel, E; Alazia, M; Sambuc, R; Bonin-Guillaume, S

    2013-04-01

    To identify independent risk factors of mortality among elderly patients in the 3 months after their visit (T3) to an emergency department (ED). Prospective cohort study. University hospital ED in an urban setting in France. One hundred seventy-three patients aged 75 and older were admitted to the ED over two weeks (18.7% of the 924 ED visits). Of these, 164 patients (94.8%) were included in our study, and 157 (95.7%) of them were followed three months after their ED visit. During the inclusion period (T0), a standardized questionnaire was used to collect data on socio-demographic and environmental characteristics, ED visit circumstances, medical conditions and geriatric assessment including functional and nutritional status. Three months after the ED visits (T3), patients or their caregivers were interviewed to collect data on vital status, and ED return or hospitalization. Among the 157 patients followed at T3, 14.6% had died, 19.9% had repeated ED visits, and 63.1% had been hospitalized. The two independent predictive factors for mortality within the 3 months after ED visit were: malnutrition screened by the Mini Nutritional Assessment short-form (MNA-SF) (OR=20.2; 95% CI: 5.74-71.35; pMalnutrition is the strongest independent risk factor predicting short-term mortality in elderly patients visiting the ED, and it was easily detected by MNA-SF and supported from the ED visit.

  20. Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk

    Science.gov (United States)

    Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Patel, Bhavika; Heidari, Morteza; Liu, Hong; Zheng, Bin

    2018-05-01

    This study aims to investigate the feasibility of identifying a new quantitative imaging marker based on false-positives generated by a computer-aided detection (CAD) scheme to help predict short-term breast cancer risk. An image dataset including four view mammograms acquired from 1044 women was retrospectively assembled. All mammograms were originally interpreted as negative by radiologists. In the next subsequent mammography screening, 402 women were diagnosed with breast cancer and 642 remained negative. An existing CAD scheme was applied ‘as is’ to process each image. From CAD-generated results, four detection features including the total number of (1) initial detection seeds and (2) the final detected false-positive regions, (3) average and (4) sum of detection scores, were computed from each image. Then, by combining the features computed from two bilateral images of left and right breasts from either craniocaudal or mediolateral oblique view, two logistic regression models were trained and tested using a leave-one-case-out cross-validation method to predict the likelihood of each testing case being positive in the next subsequent screening. The new prediction model yielded the maximum prediction accuracy with an area under a ROC curve of AUC  =  0.65  ±  0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of (2.95, 6.83). The results also showed an increasing trend in the adjusted odds ratio and risk prediction scores (p  breast cancer risk.

  1. Current, Short Term, Future and Star Wars Research Projects for Ornamental Crops

    Science.gov (United States)

    The USDA-ARS Greenhouse Production Research Group is involved in fundamental and developmental plant research aimed at developing tools for early stress detection and efficient agrochemical utilization for protected horticulture crops. The group conducts basic plant biology research with the goal o...

  2. A Modified LS+AR Model to Improve the Accuracy of the Short-term Polar Motion Prediction

    Science.gov (United States)

    Wang, Z. W.; Wang, Q. X.; Ding, Y. Q.; Zhang, J. J.; Liu, S. S.

    2017-03-01

    There are two problems of the LS (Least Squares)+AR (AutoRegressive) model in polar motion forecast: the inner residual value of LS fitting is reasonable, but the residual value of LS extrapolation is poor; and the LS fitting residual sequence is non-linear. It is unsuitable to establish an AR model for the residual sequence to be forecasted, based on the residual sequence before forecast epoch. In this paper, we make solution to those two problems with two steps. First, restrictions are added to the two endpoints of LS fitting data to fix them on the LS fitting curve. Therefore, the fitting values next to the two endpoints are very close to the observation values. Secondly, we select the interpolation residual sequence of an inward LS fitting curve, which has a similar variation trend as the LS extrapolation residual sequence, as the modeling object of AR for the residual forecast. Calculation examples show that this solution can effectively improve the short-term polar motion prediction accuracy by the LS+AR model. In addition, the comparison results of the forecast models of RLS (Robustified Least Squares)+AR, RLS+ARIMA (AutoRegressive Integrated Moving Average), and LS+ANN (Artificial Neural Network) confirm the feasibility and effectiveness of the solution for the polar motion forecast. The results, especially for the polar motion forecast in the 1-10 days, show that the forecast accuracy of the proposed model can reach the world level.

  3. Predicting short-term mortality and long-term survival for hospitalized US patients with alcoholic hepatitis.

    Science.gov (United States)

    Cuthbert, Jennifer A; Arslanlar, Sami; Yepuri, Jay; Montrose, Marc; Ahn, Chul W; Shah, Jessica P

    2014-07-01

    No study has evaluated current scoring systems for their accuracy in predicting short and long-term outcome of alcoholic hepatitis in a US population. We reviewed electronic records for patients with alcoholic liver disease (ALD) admitted to Parkland Memorial Hospital between January 2002 and August 2005. Data and outcomes for 148 of 1,761 admissions meeting pre-defined criteria were collected. The discriminant function (DF) was revised (INRdf) to account for changes in prothrombin time reagents that could potentially affect identification of risk using the previous DF threshold of >32. Admission and theoretical peak scores were calculated by use of the Model for End-stage Liver Disease (MELD). Analysis models compared five different scoring systems. INRdf was closely correlated with the old DF (r (2) = 0.95). Multivariate analysis of the data showed that survival for 28 days was significantly associated with a scoring system using a combination of age, bilirubin, coagulation status, and creatinine (p short-term mortality (p 50 % mortality at four weeks and >80 % mortality at six months without specific treatment.

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

    Science.gov (United States)

    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.

  5. A New Empirical Model for Short-Term Forecasting of the Broadband Penetration: A Short Research in Greece

    Directory of Open Access Journals (Sweden)

    Salpasaranis Konstantinos

    2011-01-01

    Full Text Available The objective of this paper is to present a short research about the overall broadband penetration in Greece. In this research, a new empirical deterministic model is proposed for the short-term forecast of the cumulative broadband adoption. The fitting performance of the model is compared with some widely used diffusion models for the cumulative adoption of new telecommunication products, namely, Logistic, Gompertz, Flexible Logistic (FLOG, Box-Cox, Richards, and Bass models. The fitting process is done with broadband penetration official data for Greece. In conclusion, comparing these models with the empirical model, it could be argued that the latter yields well enough statistics indicators for fitting and forecasting performance. It also stresses the need for further research and performance analysis of the model in other more mature broadband markets.

  6. Artificial intelligence in short term electric load forecasting: a state-of-the-art survey for the researcher

    Energy Technology Data Exchange (ETDEWEB)

    Metaxiotis, K.; Kagiannas, A.; Askounis, D.; Psarras, J. [National Technical University of Athens, Zografou (Turkey). Dept. of Electrical and Computer Engineering

    2003-06-01

    Intelligent solutions, based on artificial intelligence (AI) technologies, to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. AI-based systems are being developed and deployed worldwide in myriad applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. This paper provides an overview for the researcher of AI technologies, as well as their current use in the field of short term electric load forecasting (STELF). The history of AI in STELF is outlined, leading to a discussion of the various approaches as well as the current research directions. The paper concludes by sharing thoughts and estimations on AI future prospects in this area. This review reveals that although still regarded as a novel methodology, AI technologies are shown to have matured to the point of offering real practical benefits in many of their applications. (Author)

  7. A Distributed Web-based Solution for Ionospheric Model Real-time Management, Monitoring, and Short-term Prediction

    Science.gov (United States)

    Kulchitsky, A.; Maurits, S.; Watkins, B.

    2006-12-01

    provide inputs for the next ionospheic model time step and then stored in a MySQL database as the first part of the time-specific record. The RMM then performs synchronization of the input times with the current model time, prepares a decision on initialization for the next model time step, and monitors its execution. Then, as soon as the model completes computations for the next time step, RMM visualizes the current model output into various short-term (about 1-2 hours) forecasting products and compares prior results with available ionospheric measurements. The RMM places prepared images into the MySQL database, which can be located on a different computer node, and then proceeds to the next time interval continuing the time-loop. The upper-level interface of this real-time system is the a PHP-based Web site (http://www.arsc.edu/SpaceWeather/new). This site provides general information about the Earth polar and adjacent mid-latitude ionosphere, allows for monitoring of the current developments and short-term forecasts, and facilitates access to the comparisons archive stored in the database.

  8. Short-Term Prognosis of Transient Ischemic Attack and Predictive Value of the ABCD2 Score in Hong Kong Chinese

    Directory of Open Access Journals (Sweden)

    Lai Hong Simon Chiu

    2014-03-01

    Full Text Available Background: Literature on prognosis of transient ischemic attack (TIA in Chinese is scarce. The short-term prognosis of TIA and the predictive value of the ABCD2 score in Hong Kong Chinese patients attending the emergency department (ED were studied to provide reference for TIA patient management in our ED. Methods: A cohort of TIA patients admitted through the ED to 13 acute public hospitals in 2006 was recruited through the centralized electronic database by the Hong Kong Hospital Authority (HA. All inpatients were e-coded by the HA according to the International Classification of Diseases, Ninth Revision (ICD9. Electronic records and hard copies were studied up to 90 days after a TIA. The stroke risk of a separate TIA cohort diagnosed by the ED was compared. Results: In the 1,000 recruited patients, the stroke risk after a TIA at days 2, 7, 30, and 90 was 0.2, 1.4, 2.9, and 4.4%, respectively. Antiplatelet agents were prescribed in 89%, warfarin in 6.9%, statin in 28.6%, antihypertensives in 39.3%, and antidiabetics in 11.9% of patients after hospitalization. Before the index TIA, the prescribed medications were 27.6, 3.7, 11.3, 27.1, and 9.7%, respectively. The accuracy of the ABCD2 score in predicting stroke risk was 0.607 at 7 days, 0.607 at 30 days, and 0.574 at 90 days. At 30 days, the p for trend across ABCD2 score levels was 0.038 (OR for every score point = 1.36, p = 0.040. Diabetes mellitus, previous stroke and carotid bruit were associated with stroke within 90 days (p = 0.038, 0.045, 0.030, respectively. A total of 45.4% of CTs of the brain showed lacunar infarcts or small vessel disease. There was an increased stroke risk at 90 days in patients with old or new infarcts on CT or MRI. Patients with carotid stenosis ≥70% had an increased stroke risk within 30 (OR = 6.335, p = 0.013 and 90 days (OR = 3.623, p = 0.050. Stroke risks at days 2, 7, 30, and 90 in the 289 TIA patients diagnosed by the ED were 0.35, 2.4, 5.2, and 6

  9. Assessment of Short Term Flood Operation Strategies Using Numerical Weather Prediction Data in YUVACΙK DAM Reservoir, Turkey

    Science.gov (United States)

    Uysal, G.; Yavuz, O.; Sensoy, A.; Sorman, A.; Akgun, T.; Gezgin, T.

    2011-12-01

    first step, a hydrological model with an embedded snow module is used to establish a rainfall-runoff relationship to calculate the inflow into the dam reservoir. The basin is divided into four sub-basins, along with the three elevation zones for each subbasin. Hydro-meteorological data are collected via 11 automated stations in and around the basin and a semi-distributed rainfall-runoff model, HEC-HMS, is calibrated for sub-basins. Then, HEC-ResSim is used to create simulation alternatives of reservoir system according to user defined guide curves and rules based on internal and/or external variables. The decision support modeling scenarios are tested with Numerical Weather Prediction Mesoscale Model 5 (MM5) daily total precipitation and daily average temperature data. Predicted precipitation and temperature data are compared with ground observations to examine the consistency. Predicted inflows computed by HEC-HMS are used as main forcing inputs into HEC-ResSim for the short term operation of reservoir during the flood events.

  10. Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas

    Science.gov (United States)

    Zhang, Jianfeng; Zhu, Yan; Zhang, Xiaoping; Ye, Ming; Yang, Jinzhong

    2018-06-01

    Predicting water table depth over the long-term in agricultural areas presents great challenges because these areas have complex and heterogeneous hydrogeological characteristics, boundary conditions, and human activities; also, nonlinear interactions occur among these factors. Therefore, a new time series model based on Long Short-Term Memory (LSTM), was developed in this study as an alternative to computationally expensive physical models. The proposed model is composed of an LSTM layer with another fully connected layer on top of it, with a dropout method applied in the first LSTM layer. In this study, the proposed model was applied and evaluated in five sub-areas of Hetao Irrigation District in arid northwestern China using data of 14 years (2000-2013). The proposed model uses monthly water diversion, evaporation, precipitation, temperature, and time as input data to predict water table depth. A simple but effective standardization method was employed to pre-process data to ensure data on the same scale. 14 years of data are separated into two sets: training set (2000-2011) and validation set (2012-2013) in the experiment. As expected, the proposed model achieves higher R2 scores (0.789-0.952) in water table depth prediction, when compared with the results of traditional feed-forward neural network (FFNN), which only reaches relatively low R2 scores (0.004-0.495), proving that the proposed model can preserve and learn previous information well. Furthermore, the validity of the dropout method and the proposed model's architecture are discussed. Through experimentation, the results show that the dropout method can prevent overfitting significantly. In addition, comparisons between the R2 scores of the proposed model and Double-LSTM model (R2 scores range from 0.170 to 0.864), further prove that the proposed model's architecture is reasonable and can contribute to a strong learning ability on time series data. Thus, one can conclude that the proposed model can

  11. Short-term traffic flow prediction model using particle swarm optimization–based combined kernel function-least squares support vector machine combined with chaos theory

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    2016-08-01

    Full Text Available Short-term traffic flow prediction is an important part of intelligent transportation systems research and applications. For further improving the accuracy of short-time traffic flow prediction, a novel hybrid prediction model (multivariate phase space reconstruction–combined kernel function-least squares support vector machine based on multivariate phase space reconstruction and combined kernel function-least squares support vector machine is proposed. The C-C method is used to determine the optimal time delay and the optimal embedding dimension of traffic variables’ (flow, speed, and occupancy time series for phase space reconstruction. The G-P method is selected to calculate the correlation dimension of attractor which is an important index for judging chaotic characteristics of the traffic variables’ series. The optimal input form of combined kernel function-least squares support vector machine model is determined by multivariate phase space reconstruction, and the model’s parameters are optimized by particle swarm optimization algorithm. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. The experimental results suggest that the new proposed model yields better predictions compared with similar models (combined kernel function-least squares support vector machine, multivariate phase space reconstruction–generalized kernel function-least squares support vector machine, and phase space reconstruction–combined kernel function-least squares support vector machine, which indicates that the new proposed model exhibits stronger prediction ability and robustness.

  12. Effectiveness of short-term numerical weather prediction in predicting growing degree days and meteorological conditions for apple scab appearance

    Czech Academy of Sciences Publication Activity Database

    Lalic, B.; Francia, M.; Eitzinger, Josef; Podrascanin, Z.; Arsenic, I.

    2016-01-01

    Roč. 23, č. 1 (2016), s. 50-56 ISSN 1350-4827 Institutional support: RVO:86652079 Keywords : venturia-inaequalis * temperature * equation * schemes * model * numerical weather prediction * disease prediction * verification * apple scab * growing degree days Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 1.411, year: 2016

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

    Science.gov (United States)

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

    NARCIS (Netherlands)

    Geerts, E; Bouhuys, N

    1998-01-01

    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

  15. Combining weather radar nowcasts and numerical weather prediction models to estimate short-term quantitative precipitation and uncertainty

    DEFF Research Database (Denmark)

    Jensen, David Getreuer

    The topic of this Ph.D. thesis is short term forecasting of precipitation for up to 6 hours called nowcasts. The focus is on improving the precision of deterministic nowcasts, assimilation of radar extrapolation model (REM) data into Danish Meteorological Institutes (DMI) HIRLAM numerical weather...

  16. Validation of prognostic scores to predict short-term mortality in patients with acute-on-chronic liver failure.

    Science.gov (United States)

    Song, Do Seon; Kim, Tae Yeob; Kim, Dong Joon; Kim, Hee Yeon; Sinn, Dong Hyun; Yoon, Eileen L; Kim, Chang Wook; Jung, Young Kul; Suk, Ki Tae; Lee, Sang Soo; Lee, Chang Hyeong; Kim, Tae Hun; Choe, Won Hyeok; Yim, Hyung Joon; Kim, Sung Eun; Baik, Soon Koo; Jang, Jae Young; Kim, Hyoung Su; Kim, Sang Gyune; Yang, Jin Mo; Sohn, Joo Hyun; Choi, Eun Hee; Cho, Hyun Chin; Jeong, Soung Won; Kim, Moon Young

    2018-04-01

    The aim of this study was to validate the chronic liver failure-sequential organ failure assessment score (CLIF-SOFAs), CLIF consortium organ failure score (CLIF-C OFs), CLIF-C acute-on-chronic liver failure score (CLIF-C ACLFs), and CLIF-C acute decompensation score in Korean chronic liver disease patients with acute deterioration. Acute-on-chronic liver failure was defined by either the Asian Pacific Association for the study of the Liver ACLF Research Consortium (AARC) or CLIF-C criteria. The diagnostic performances for short-term mortality were compared by the area under the receiver operating characteristic curve. Among a total of 1470 patients, 252 patients were diagnosed with ACLF according to the CLIF-C (197 patients) or AARC definition (95 patients). As the ACLF grades increased, the survival rates became significantly lower. The areas under the receiver operating characteristic of the CLIF-SOFAs, CLIF-C OFs, and CLIF-C ACLFs were significantly higher than those of the Child-Pugh, model for end-stage liver disease, and model for end-stage liver disease-Na scores in ACLF patients according to the CLIF-C definition (all P < 0.05), but there were no significant differences in patients without ACLF or in patients with ACLF according to the AARC definition. The CLIF-SOFAs, CLIF-C OFs, and CLIF-C ACLFs had higher specificities with a fixed sensitivity than liver specific scores in ACLF patients according to the CLIF-C definition, but not in ACLF patients according to the AARC definition. The CLIF-SOFAs, CLIF-C OFs, and CLIF-C ACLFs are useful scoring systems that provide accurate information on prognosis in patients with ACLF according to the CLIF-C definition, but not the AARC definition. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  19. The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness, and Verbal Short-Term Memory in Reading Skills: A Review

    Science.gov (United States)

    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…

  20. An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction

    International Nuclear Information System (INIS)

    Zheng, Xiujuan; Fang, Huajing

    2015-01-01

    The gradual decreasing capacity of lithium-ion batteries can serve as a health indicator for tracking the degradation of lithium-ion batteries. It is important to predict the capacity of a lithium-ion battery for future cycles to assess its health condition and remaining useful life (RUL). In this paper, a novel method is developed using unscented Kalman filter (UKF) with relevance vector regression (RVR) and applied to RUL and short-term capacity prediction of batteries. A RVR model is employed as a nonlinear time-series prediction model to predict the UKF future residuals which otherwise remain zero during the prediction period. Taking the prediction step into account, the predictive value through the RVR method and the latest real residual value constitute the future evolution of the residuals with a time-varying weighting scheme. Next, the future residuals are utilized by UKF to recursively estimate the battery parameters for predicting RUL and short-term capacity. Finally, the performance of the proposed method is validated and compared to other predictors with the experimental data. According to the experimental and analysis results, the proposed approach has high reliability and prediction accuracy, which can be applied to battery monitoring and prognostics, as well as generalized to other prognostic applications. - Highlights: • An integrated method is proposed for RUL prediction as well as short-term capacity prediction. • Relevance vector regression model is employed as a nonlinear time-series prediction model. • Unscented Kalman filter is used to recursively update the states for battery model parameters during the prediction. • A time-varying weighting scheme is utilized to improve the accuracy of the RUL prediction. • The proposed method demonstrates high reliability and prediction accuracy.

  1. The use of standardised short-term and working memory tests in aphasia research: a systematic review.

    Science.gov (United States)

    Murray, Laura; Salis, Christos; Martin, Nadine; Dralle, Jenny

    2018-04-01

    Impairments of short-term and working memory (STM, WM), both verbal and non-verbal, are ubiquitous in aphasia. Increasing interest in assessing STM and WM in aphasia research and clinical practice as well as a growing evidence base of STM/WM treatments for aphasia warrant an understanding of the range of standardised STM/WM measures that have been utilised in aphasia. To date, however, no previous systematic review has focused on aphasia. Accordingly, the goals of this systematic review were: (1) to identify standardised tests of STM and WM utilised in the aphasia literature, (2) to evaluate critically the psychometric strength of these tests, and (3) to appraise critically the quality of the investigations utilising these tests. Results revealed that a very limited number of standardised tests, in the verbal and non-verbal domains, had robust psychometric properties. Standardisation samples to elicit normative data were often small, and most measures exhibited poor validity and reliability properties. Studies using these tests inconsistently documented demographic and aphasia variables essential to interpreting STM/WM test outcomes. In light of these findings, recommendations are provided to foster, in the future, consistency across aphasia studies and confidence in STM/WM tests as assessment and treatment outcome measures.

  2. Radiomic features from the peritumoral brain parenchyma on treatment-naive multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings

    Energy Technology Data Exchange (ETDEWEB)

    Prasanna, Prateek; Patel, Jay; Madabhushi, Anant; Tiwari, Pallavi [Case Western Reserve University, Department of Biomedical Engineering, Cleveland, OH (United States); Partovi, Sasan [University Hospitals Case Medical Center, Case Western Reserve School of Medicine, Cleveland, OH (United States)

    2017-10-15

    Despite 90 % of glioblastoma (GBM) recurrences occurring in the peritumoral brain zone (PBZ), its contribution in patient survival is poorly understood. The current study leverages computerized texture (i.e. radiomic) analysis to evaluate the efficacy of PBZ features from pre-operative MRI in predicting long- (>18 months) versus short-term (<7 months) survival in GBM. Sixty-five patient examinations (29 short-term, 36 long-term) with gadolinium-contrast T{sub 1w}, FLAIR and T{sub 2w} sequences from the Cancer Imaging Archive were employed. An expert manually segmented each study as: enhancing lesion, PBZ and tumour necrosis. 402 radiomic features (capturing co-occurrence, grey-level dependence and directional gradients) were obtained for each region. Evaluation was performed using threefold cross-validation, such that a subset of studies was used to select the most predictive features, and the remaining subset was used to evaluate their efficacy in predicting survival. A subset of ten radiomic 'peritumoral' MRI features, suggestive of intensity heterogeneity and textural patterns, was found to be predictive of survival (p = 1.47 x 10{sup -5}) as compared to features from enhancing tumour, necrotic regions and known clinical factors. Our preliminary analysis suggests that radiomic features from the PBZ on routine pre-operative MRI may be predictive of long- versus short-term survival in GBM. (orig.)

  3. Short-term prediction of threatening and violent behaviour in an Acute Psychiatric Intensive Care Unit based on patient and environment characteristics

    Directory of Open Access Journals (Sweden)

    Morken Gunnar

    2011-03-01

    Full Text Available Abstract Background The aims of the present study were to investigate clinically relevant patient and environment-related predictive factors for threats and violent incidents the first three days in a PICU population based on evaluations done at admittance. Methods In 2000 and 2001 all 118 consecutive patients were assessed at admittance to a Psychiatric Intensive Care Unit (PICU. Patient-related conditions as actuarial data from present admission, global clinical evaluations by physician at admittance and clinical nurses first day, a single rating with an observer rated scale scoring behaviours that predict short-term violence in psychiatric inpatients (The Brøset Violence Checklist (BVC at admittance, and environment-related conditions as use of segregation or not were related to the outcome measure Staff Observation Aggression Scale-Revised (SOAS-R. A multiple logistic regression analysis with SOAS-R as outcome variable was performed. Results The global clinical evaluations and the BVC were effective and more suitable than actuarial data in predicting short-term aggression. The use of segregation reduced the number of SOAS-R incidents. Conclusions In a naturalistic group of patients in a PICU segregation of patients lowers the number of aggressive and threatening incidents. Prediction should be based on clinical global judgment, and instruments designed to predict short-term aggression in psychiatric inpatients. Trial registrations NCT00184119/NCT00184132

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

    Science.gov (United States)

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

    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.

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

    Science.gov (United States)

    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.

  6. Short-term Automated Quantification of Radiologic Changes in the Characterization of Idiopathic Pulmonary Fibrosis Versus Nonspecific Interstitial Pneumonia and Prediction of Long-term Survival.

    Science.gov (United States)

    De Giacomi, Federica; Raghunath, Sushravya; Karwoski, Ronald; Bartholmai, Brian J; Moua, Teng

    2018-03-01

    Fibrotic interstitial lung diseases presenting with nonspecific and overlapping radiologic findings may be difficult to diagnose without surgical biopsy. We hypothesized that baseline quantifiable radiologic features and their short-term interval change may be predictive of underlying histologic diagnosis as well as long-term survival in idiopathic pulmonary fibrosis (IPF) presenting without honeycombing versus nonspecific interstitial pneumonia (NSIP). Forty biopsy-confirmed IPF and 20 biopsy-confirmed NSIP patients with available high-resolution chest computed tomography 4 to 24 months apart were studied. CALIPER software was used for the automated characterization and quantification of radiologic findings. IPF subjects were older (66 vs. 48; P<0.0001) with lower diffusion capacity for carbon monoxide and higher volumes of baseline reticulation (193 vs. 83 mL; P<0.0001). Over the interval period, compared with NSIP, IPF patients experienced greater functional decline (forced vital capacity, -6.3% vs. -1.7%; P=0.02) and radiologic progression, as noted by greater increase in reticulation volume (24 vs. 1.74 mL; P=0.048), and decrease in normal (-220 vs. -37.7 mL; P=0.045) and total lung volumes (-198 vs. 58.1 mL; P=0.03). Older age, male gender, higher reticulation volumes at baseline, and greater interval decrease in normal lung volumes were predictive of IPF. Both baseline and short-term changes in quantitative radiologic findings were predictive of mortality. Baseline quantitative radiologic findings and assessment of short-term disease progression may help characterize underlying IPF versus NSIP in those with difficult to differentiate clinicoradiologic presentations. Our study supports the possible utility of assessing serial quantifiable high-resolution chest computed tomographic findings for disease differentiation in these 2 entities.

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

    Directory of Open Access Journals (Sweden)

    Dres M

    2017-03-01

    Full Text Available Martin Dres,1,2 Pierre Hausfater,3,4 Frantz Foissac,5,6 Maguy Bernard,7 Luc-Marie Joly,8 Mustapha Sebbane,9 Anne-Laure Philippon,3,4 Cédric Gil-Jardiné,10 Jeannot Schmidt,11 Maxime Maignan,12 Jean-Marc Treluyer,13 Nicolas Roche14,15 On behalf of the UTAPE Study Investigators and Scientific Committee 1Pulmonary and Critical Care Department, Pitié-Salpêtrière Hospital, AP-HP, 2UMRS1158: Clinical and Experimental Respiratory Neurophysiology, Paris 6 University, 3Emergency Department, Hôpital Pitié-Salpêtrière, AP-HP, 4Sorbonne Universités UPMC Univ-Paris06, GRC-14 BIOSFAST, 5Clinical Research Department, Necker Cochin Hospital, AP-HP, 6EA 7323, Sorbonne Paris-Cité, 7Biochemistry Department, Pitié-Salpêtrière Hospital, AP-HP, Paris, 8Emergency Department, Charles Nicolle Hospital, Rouen, 9Department of Emergency Medicine, Lapeyronie Hospital, Montpellier, 10Emergency Department, Pellegrin Hospital, Bordeaux, 11Emergency Department, Gabriel Montpied Hospital, Clermont-Ferrand, 12Emergency Department, Grenoble University Hospital, Grenoble, 13Clinical Research Department, Paris Descartes University, Hôpital Cochin, AP-HP, 14Pulmonary Department, Cochin Hospital, AP-HP, 15Paris Descartes University, Paris, France 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

  8. Predictive Validity of the Columbia-Suicide Severity Rating Scale for Short-Term Suicidal Behavior: A Danish Study of Adolescents at a High Risk of Suicide.

    Science.gov (United States)

    Conway, Paul Maurice; Erlangsen, Annette; Teasdale, Thomas William; Jakobsen, Ida Skytte; Larsen, Kim Juul

    2017-07-03

    Using the Columbia-Suicide Severity Rating Scale (C-SSRS), we examined the predictive and incremental predictive validity of past-month suicidal behavior and ideation for short-term suicidal behavior among adolescents at high risk of suicide. The study was conducted in 2014 on a sample of 85 adolescents (90.6% females) who participated at follow-up (85.9%) out of the 99 (49.7%) baseline respondents. All adolescents were recruited from a specialized suicide-prevention clinic in Denmark. Through multivariate logistic regression analyses, we examined whether baseline suicidal behavior predicted subsequent suicidal behavior (actual attempts and suicidal behavior of any type, including preparatory acts, aborted, interrupted and actual attempts; mean follow-up of 80.8 days, SD = 52.4). Furthermore, we examined whether suicidal ideation severity and intensity incrementally predicted suicidal behavior at follow-up over and above suicidal behavior at baseline. Actual suicide attempts at baseline strongly predicted suicide attempts at follow-up. Baseline suicidal ideation severity and intensity did not significantly predict future actual attempts over and above baseline attempts. The suicidal ideation intensity items deterrents and duration were significant predictors of subsequent actual attempts after adjustment for baseline suicide attempts and suicidal behavior of any type, respectively. Suicidal ideation severity and intensity, and the intensity items frequency, duration and deterrents, all significantly predicted any type of suicidal behavior at follow-up, also after adjusting for baseline suicidal behavior. The present study points to an incremental predictive validity of the C-SSRS suicidal ideation scales for short-term suicidal behavior of any type among high-risk adolescents.

  9. The value of short-term pain relief in predicting the long-term outcome of 'indirect' cervical epidural steroid injections.

    Science.gov (United States)

    Joswig, Holger; Neff, Armin; Ruppert, Christina; Hildebrandt, Gerhard; Stienen, Martin Nikolaus

    2018-05-01

    The predictive value of short-term arm pain relief after 'indirect' cervical epidural steroid injection (ESI) for the 1-month treatment response has been previously demonstrated. It remained to be answered whether the long-term response could be estimated by the early post-interventional pain course as well. Prospective observational study, following a cohort of n = 45 patients for a period of 24 months after 'indirect' ESI for radiculopathy secondary to a single-level cervical disk herniation (CDH). Arm and neck pain on the visual analog scale (VAS), health-related quality of life with the Short Form-12 (SF-12), and functional outcome with the Neck Pain and Disability (NPAD) Scale were assessed. Any additional invasive treatment after a single injection (second injection or surgery) defined treatment outcome as 'non-response'. At 24 months, n = 30 (66.7%) patients were responders and n = 15 (33.3%) were non-responders. Non-responders exited the follow-up at 1 month (n = 10), at 3 months (n = 4), and at 6 months (n = 1). No patients were injected again or operated on between the 6- and 24-month follow-up. Patients with favorable treatment response at 24 months had significantly lower VAS arm pain (p  50% short term pain reduction was not a reliable predictor of the 24-month responder status. SF-12 and NPAD scores were better among treatment responders in the long term. Patients who require a second injection or surgery after 'indirect' cervical ESI for a symptomatic CDH do so within the first 6 months. Short-term pain relief cannot reliably predict the long-term outcome.

  10. Gender differences in the predictive role of self-rated health on short-term risk of mortality among older adults

    Directory of Open Access Journals (Sweden)

    Shervin Assari

    2016-09-01

    Full Text Available 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

  11. Short-term memory

    Science.gov (United States)

    Toulouse, G.

    This is a rather bold attempt to bridge the gap between neuron structure and psychological data. We try to answer the question: Is there a relation between the neuronal connectivity in the human cortex (around 5,000) and the short-term memory capacity (7±2)? Our starting point is the Hopfield model (Hopfield 1982), presented in this volume by D.J. Amit.

  12. Increased short-term variability of repolarization predicts d-sotalol-induced torsades de pointes in dogs

    DEFF Research Database (Denmark)

    Thomsen, Morten Bækgaard; Verduyn, S Cora; Stengl, Milan

    2004-01-01

    Identification of patients at risk for drug-induced torsades de pointes arrhythmia (TdP) is difficult. Increased temporal lability of repolarization has been suggested as being valuable to predict proarrhythmia. The predictive value of different repolarization parameters, including beat...

  13. 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.

    Science.gov (United States)

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

    2016-02-01

    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 PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P 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.

  14. The Sources of Life Chances: Does Education, Class Category, Occupation, or Short-Term Earnings Predict 20-Year Long-Term Earnings?

    Directory of Open Access Journals (Sweden)

    ChangHwan Kim

    2018-03-01

    Full Text Available In sociological studies of economic stratification and intergenerational mobility, occupation has long been presumed to reflect lifetime earnings better than do short-term earnings. However, few studies have actually tested this critical assumption. In this study, we investigate the cross-sectional determinants of 20-year accumulated earnings using data that match respondents in the Survey of Income and Program Participation to their longitudinal earnings records based on administrative tax information from 1990 to 2009. Fit statistics of regression models are estimated to assess the predictive power of various proxy variables, including occupation, education, and short-term earnings, on cumulative earnings over the 20-year time period. Contrary to the popular assumption in sociology, our results find that cross-sectional earnings have greater predictive power on long-term earnings than occupation-based class classifications, including three-digit detailed occupations for both men and women. The model based on educational attainment, including field of study, has slightly better fit than models based on one-digit occupation or the Erikson, Goldthorpe, and Portocarero class scheme. We discuss the theoretical implications of these findings for the sociology of stratification and intergenerational mobility.

  15. Short-term and long-term thermal prediction of a walking beam furnace using neuro-fuzzy techniques

    Directory of Open Access Journals (Sweden)

    Banadaki Hamed Dehghan

    2015-01-01

    Full Text Available The walking beam furnace (WBF is one of the most prominent process plants often met in an alloy steel production factory and characterized by high non-linearity, strong coupling, time delay, large time-constant and time variation in its parameter set and structure. From another viewpoint, the WBF is a distributed-parameter process in which the distribution of temperature is not uniform. Hence, this process plant has complicated non-linear dynamic equations that have not worked out yet. In this paper, we propose one-step non-linear predictive model for a real WBF using non-linear black-box sub-system identification based on locally linear neuro-fuzzy (LLNF model. Furthermore, a multi-step predictive model with a precise long prediction horizon (i.e., ninety seconds ahead, developed with application of the sequential one-step predictive models, is also presented for the first time. The locally linear model tree (LOLIMOT which is a progressive tree-based algorithm trains these models. Comparing the performance of the one-step LLNF predictive models with their associated models obtained through least squares error (LSE solution proves that all operating zones of the WBF are of non-linear sub-systems. The recorded data from Iran Alloy Steel factory is utilized for identification and evaluation of the proposed neuro-fuzzy predictive models of the WBF process.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    L. de Montera

    2008-08-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  1. A prediction model of short-term ionospheric foF2 based on AdaBoost

    Science.gov (United States)

    Zhao, Xiukuan; Ning, Baiqi; Liu, Libo; Song, Gangbing

    2014-02-01

    In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer (foF2) one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years' foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years' data were used as a training dataset and the second eleven years' data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.

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

    DEFF Research Database (Denmark)

    Schievink, Bauke; de Zeeuw, Dick; Smink, Paul A

    2016-01-01

    from the RADAR/JAPAN study to predict the effect of atrasentan on renal and heart failure outcomes. METHODS: 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......BACKGROUND: 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. DESIGN: We used the PRE score on data...

  3. Study of s-component of the solar radio emission and short-term quantitative prediction of powerful solar flares

    International Nuclear Information System (INIS)

    Guseynov, Sh; Gakhramanov, I.G.

    2012-01-01

    Full text : All living and non-living things on Earth is dependent on the processes occurring in the Sun. Therefore the study of the Sun with the aim to predict powerful solar flares is of great scientific and practical importance. It is known that the main drawback of modern forecasting of solar flares and the low reliability of forecasts is the lack of use of the physical concepts of the mechanism of flares

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

    Science.gov (United States)

    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.

  5. A prediction model of short-term ionospheric foF2 Based on AdaBoost

    Science.gov (United States)

    Zhao, Xiukuan; Liu, Libo; Ning, Baiqi

    Accurate specifications of spatial and temporal variations of the ionosphere during geomagnetic quiet and disturbed conditions are critical for applications, such as HF communications, satellite positioning and navigation, power grids, pipelines, etc. Therefore, developing empirical models to forecast the ionospheric perturbations is of high priority in real applications. The critical frequency of the F2 layer, foF2, is an important ionospheric parameter, especially for radio wave propagation applications. In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years’ foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years’ data were used as a training dataset and the second eleven years’ data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.

  6. Short-term predictive capacity of two different triage systems in patients with acute heart failure: TRICA-EAHFE study.

    Science.gov (United States)

    Miró, Òscar; Tost, Josep; Herrero, Pablo; Jacob, Javier; Martín-Sánchez, Francisco Javier; Gil, Víctor; Fernández-Pérez, Cristina; Escoda, Rosa; Llorens, Pere

    2016-12-01

    To evaluate whether prioritization of patients with acute heart failure (AHF) in the Andorran Triage Model/Spanish Triage System (MAT/SET) and the Manchester Triage System (MTS) also allows the identification of different profiles of outcome and prognosis and determine whether either system has a better predictive capacity of outcomes. Patients with AHF included in the Spanish EAHFE registry from hospitals using the MAT/SET or MTS were selected and divided according to the triage system used. Outcome variables included hospital admission, length of stay, death during admission, 3, 7, and 30-day all-cause mortality, and emergency department (ED) reconsultation at 30 days. The results were compared according to the level of priority and the triage system used. We included 3837 patients (MAT/SET=2474; MTS=1363) classified as follows: 4.0% level 1; 34.7% level 2; 55.1% level 3; and 6.3% levels 4-5. Both systems associated greater priority with higher rates of admission and mortality; the MTS associated greater priority with greater ED reconsultation and the MAT/SET found greater priority to be associated with less ED reconsultation. The discriminative capacity of the two scales for adverse outcomes was statistically significant, albeit poor, for almost all the outcome events and it was of scarce clinical relevance (Area under the curve of the receiver operating characteristic between 0.458 and 0.661). The prediction of the outcome of patients with AHF determined with the MAT/SET or MTS showed scarce differences between the two systems, and their discriminative capacity does not seem to be clinically relevant.

  7. Global Integration of the Hot-State Brain Network of Appetite Predicts Short Term Weight Loss in Older Adult

    Directory of Open Access Journals (Sweden)

    Brielle M Paolini

    2015-05-01

    Full Text Available 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, amygdala and the parahippocampal gyrus were highly integrated as evidenced by the results of a principal component analysis. 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

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

    Directory of Open Access Journals (Sweden)

    Yu Liu

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  10. Predicting Short-Term Electricity Demand by Combining the Advantages of ARMA and XGBoost in Fog Computing Environment

    Directory of Open Access Journals (Sweden)

    Chuanbin Li

    2018-01-01

    Full Text Available With the rapid development of IoT, the disadvantages of Cloud framework have been exposed, such as high latency, network congestion, and low reliability. Therefore, the Fog Computing framework has emerged, with an extended Fog Layer between the Cloud and terminals. In order to address the real-time prediction on electricity demand, we propose an approach based on XGBoost and ARMA in Fog Computing environment. By taking the advantages of Fog Computing framework, we first propose a prototype-based clustering algorithm to divide enterprise users into several categories based on their total electricity consumption; we then propose a model selection approach by analyzing users’ historical records of electricity consumption and identifying the most important features. Generally speaking, if the historical records pass the test of stationarity and white noise, ARMA is used to model the user’s electricity consumption in time sequence; otherwise, if the historical records do not pass the test, and some discrete features are the most important, such as weather and whether it is weekend, XGBoost will be used. The experiment results show that our proposed approach by combining the advantage of ARMA and XGBoost is more accurate than the classical models.

  11. {sup 18}F-alfatide PET/CT may predict short-term outcome of concurrent chemoradiotherapy in patients with advanced non-small cell lung cancer

    Energy Technology Data Exchange (ETDEWEB)

    Luan, Xiaohui [Shandong Cancer Hospital affiliated to Shandong University, Department of Radiation Oncology, Jinan, Shandong (China); University of Jinan-Shandong Academy of Medical Sciences, School of Medicine and Life Sciences, Jinan (China); Huang, Yong; Sun, Xiaorong; Ma, Li; Teng, Xuepeng; Lu, Hong [Shandong Cancer Hospital affiliated to Shandong University, Department of Radiology, Jinan, Shandong (China); Gao, Song [Jining Infectious Diseases Hospital, Department of Oncology, Jining, Shandong (China); Wang, Suzhen; Yu, Jinming; Yuan, Shuanghu [Shandong Cancer Hospital affiliated to Shandong University, Department of Radiation Oncology, Jinan, Shandong (China)

    2016-12-15

    The study aims to investigate the role of {sup 18}F-alfatide positron emission tomography/computed tomography (PET/CT) in predicting the short-term outcome of concurrent chemoradiotherapy (CCRT) in patients with advanced non-small cell lung cancer (NSCLC). Eighteen patients with advanced NSCLC had undergone {sup 18}F-alfatide PET/CT scans before CCRT and PET/CT parameters including maximum and mean standard uptake values (SUV{sub max}/SUV{sub mean}), peak standard uptake values (SUV{sub peak}) and tumor volume (TV{sub PET} and TV{sub CT}) were obtained. The SUV{sub max} of tumor and normal tissues (lung, blood pool and muscle) were measured, and their ratios were denoted as T/NT (T/NT{sub lung}, T/NT{sub blood} and T/NT{sub muscle}). Statistical methods included the Two-example t test, Wilcoxon rank-sum test, Receiver-operating characteristic (ROC) curve analysis and logistic regression analyses. We found that SUV{sub max}, SUV{sub peak}, T/NT{sub lung}, T/NT{sub blood} and T/NT{sub muscle} were higher in non-responders than in responders (P = 0.0024, P = 0.016, P < 0.001, P = 0.003, P = 0.004). According to ROC curve analysis, the thresholds of SUV{sub max}, SUV{sub peak}, T/NT{sub lung}, T/NT{sub blood} and T/NT{sub muscle} were 5.65, 4.46, 7.11, 5.41, and 11.75, respectively. The five parameters had high sensitivity, specificity and accuracy in distinguishing non-responders and responders. Multivariate logistic regression analyses showed that T/NT{sub lung} was an independent predictor of the short-term outcome of CCRT in patients with advanced NSCLC (P = 0.032). {sup 18}F-alfatide PET/CT may be useful in predicting the short-term outcome of CCRT in patients with advanced NSCLC. (orig.)

  12. Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods

    International Nuclear Information System (INIS)

    Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli

    2016-01-01

    Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid

  13. 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.

    Science.gov (United States)

    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.

  14. Acute pulmonary embolism: prediction of cor pulmonale and short-term patient survival from assessment of cardiac dimensions in routine multidetector-row CT

    International Nuclear Information System (INIS)

    Engeike, C.; Rummeny, E.; Marten, K.

    2006-01-01

    Purpose: evaluation of the prognostic value of morphological cardiac parameters in patients with suspected and incidental acute pulmonary embolism (PE) using multidetector-row chest CT (MSCT). Materials and methods: 2335 consecutive MSCT scans were evaluated for the presence of PE. The arterial enhancement and analysability of pulmonary arteries and the heart were assessed as parameters of the scan quality. The diastolic right and left ventricular short axes (RV D , LV D ) and the interventricular septal deviation (ISD) were measured in all PE-positive patients and the echocardiography reports were reviewed. The clinical data assessment included cardio-respiratory and other co-morbidities, systemic anticoagulant therapy (ACT), and the 30-day outcome. Predictors of acute cor pulmonale and the short-term outcome were calculated by univariate and multivariate logistic regressions including odds ratios (OR) and ROC analyses using positive (PPV) and negative predictive values (NPV). Results: 90 patients with acute PE were included (36 with clinically suspected PE, 54 with incidental PE). 26 patients had cardio-respiratory co-morbidities. Four patients underwent systemic thrombolysis, 43 underwent anticoagulation in therapeutic doses, 19 underwent anticoagulation in prophylactic doses, and 24 patients did not undergo ACT. 15 of 41 patients had echocardiographic evidence of acute cor pulmonale. 8 patients died within 30 days. The RV D was the best independent predictor of acute cor pulmonale (p = 0,002, OR = 9.16, PPV = 0.68, NPV=1 at 4.49 cm cut off) and short-term outcome (p= 0,0005, OR = 2.82, PPV = 0.23, NPV = 0.98 at 4.75 cm cut off). The RV D /LV D ratio had a PPV of 0.85 for cor pulmonale. (orig.)

  15. Clinical research on radioiodine addition of low-doses of lithium carbonate in short-term treatment of Graves hyperthyroidism

    International Nuclear Information System (INIS)

    Zha Jinshun; Jiang Yan; Xu Yuan; Lin Qinxiu; Huang Chunling; Jiang Tingyin

    2014-01-01

    after therapy (t fT3 =5.23, t fT4 =10.14 in group Ⅰ, t fT3 =5.12, t fT4 =9.98 in group Ⅱ, all P<0.01), then decreased gradually to the normal ranges. The fT 3 and fT 4 values in group Ⅱ were much lower than those in group Ⅰ (t fT3 =8.22, t fT4 =19.18, all P<0.01) 30 days after therapy, no significance were found in other time periods. Cure rate of hyperthyroidism was achieved in 36 of the 50 patients (72%) in group Ⅰ and in 38 of the 50 patients (76%) in group Ⅱ without significant difference. There were no significant differences in curative effect of the two groups (χ 2 =0.21, P>0.05). Conclusion: For patients withdrawing of ATD and those with short effective half-time, as well as those intolerant or invalid, the short term addition of lithium to 131 I allows for a better control of thyrotoxia and the completeness of treatment. But there have not been observed that lithium carbonate plus 131 I can improve the long term cure rate of Graves hyperthyroidism. (authors)

  16. The attention-weighted sample-size model of visual short-term memory: Attention capture predicts resource allocation and memory load.

    Science.gov (United States)

    Smith, Philip L; Lilburn, Simon D; Corbett, Elaine A; Sewell, David K; Kyllingsbæk, Søren

    2016-09-01

    We investigated the capacity of visual short-term memory (VSTM) in a phase discrimination task that required judgments about the configural relations between pairs of black and white features. Sewell et al. (2014) previously showed that VSTM capacity in an orientation discrimination task was well described by a sample-size model, which views VSTM as a resource comprised of a finite number of noisy stimulus samples. The model predicts the invariance of [Formula: see text] , the sum of squared sensitivities across items, for displays of different sizes. For phase discrimination, the set-size effect significantly exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items in the display captures attention and receives a disproportionate share of resources. The choice probabilities and response time distributions from the task were well described by a diffusion decision model in which the drift rates embodied the assumptions of the attention-weighted sample-size model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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.

  18. An empirical assessment of the short-term impacts of a reading of Deborah Zoe Laufer's drama Informed Consent on attitudes and intentions to participate in genetic research.

    Science.gov (United States)

    Rothwell, Erin; Botkin, Jeffrey R; Cheek-O'Donnell, Sydney; Wong, Bob; Case, Gretchen A; Johnson, Erin; Matheson, Trent; Wilson, Alena; Robinson, Nicole R; Rawlings, Jared; Horejsi, Brooke; Lopez, Ana Maria; Byington, Carrie L

    2018-01-01

    This study assessed the short-term impact of the play "Informed Consent" by Deborah Zoe Laufer (a fictionalized look at the controversy over specimens collected from the Havasupai Tribe for diabetes research in 1989) on perceptions of trust, willingness to donate biospecimens, and attitudes toward harm and privacy among the medical and undergraduate students, faculty, and the public in the Intermountain West. Surveys were administered before and after a staged reading of the play by professional actors. Survey items included the short form Trust in Medical Researchers, and single-item questions about group identity, ethics of genetic testing in children, and willingness to donate biospecimens. In addition, respondents were given the option to answer open-ended questions through e-mail. Out of the 481 who attended the play, 421 completed both the pre and post surveys, and 166 participants completed open-ended questions online approximately 1 week after the play. Across all participants, there were significant declines for trust in medical researchers and for the survey item "is it ethical for investigators to test children for adult onset diseases" (p < .001 for both) following the play. There was a significant increase in agreement to improve group identity protections (p < .001) and there were no differences on willingness to donate biospecimens to research (p = .777). Qualitative data provided extensive contextual data supporting these perspectives. This is one of the first studies to document short-term impacts of a theatrical performance on both attitudes and behavioral intentions toward research ethics and clinical research participation. Future research should continue to explore the impact of theatrical performances among public and investigators on the ethical issues and complexities in clinical research.

  19. A Measure of Proficiency or Short-Term Memory? Validation of an Elicited Imitation Test for SLA Research

    Science.gov (United States)

    Kim, Youjin; Tracy-Ventura, Nicole; Jung, Yeonjoo

    2016-01-01

    Elicited imitation requires listeners to listen and repeat sentences as accurately as possible. In second language acquisition (SLA) research it has been used for a variety of purposes. Recently, versions of the same elicited imitation test (EIT) have been created in 6 languages with the purpose of measuring second language proficiency (Ortega…

  20. Displacement prediction of Baijiabao landslide based on empirical mode decomposition and long short-term memory neural network in Three Gorges area, China

    Science.gov (United States)

    Xu, Shiluo; Niu, Ruiqing

    2018-02-01

    Every year, landslides pose huge threats to thousands of people in China, especially those in the Three Gorges area. It is thus necessary to establish an early warning system to help prevent property damage and save peoples' lives. Most of the landslide displacement prediction models that have been proposed are static models. However, landslides are dynamic systems. In this paper, the total accumulative displacement of the Baijiabao landslide is divided into trend and periodic components using empirical mode decomposition. The trend component is predicted using an S-curve estimation, and the total periodic component is predicted using a long short-term memory neural network (LSTM). LSTM is a dynamic model that can remember historical information and apply it to the current output. Six triggering factors are chosen to predict the periodic term using the Pearson cross-correlation coefficient and mutual information. These factors include the cumulative precipitation during the previous month, the cumulative precipitation during a two-month period, the reservoir level during the current month, the change in the reservoir level during the previous month, the cumulative increment of the reservoir level during the current month, and the cumulative displacement during the previous month. When using one-step-ahead prediction, LSTM yields a root mean squared error (RMSE) value of 6.112 mm, while the support vector machine for regression (SVR) and the back-propagation neural network (BP) yield values of 10.686 mm and 8.237 mm, respectively. Meanwhile, the Elman network (Elman) yields an RMSE value of 6.579 mm. In addition, when using multi-step-ahead prediction, LSTM obtains an RMSE value of 8.648 mm, while SVR, BP and the Elman network obtains RSME values of 13.418 mm, 13.014 mm, and 13.370 mm. The predicted results indicate that, to some extent, the dynamic model (LSTM) achieves results that are more accurate than those of the static models (i.e., SVR and BP). LSTM even

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

    International Nuclear Information System (INIS)

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

    2002-01-01

    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

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

    Science.gov (United States)

    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.

  3. Metallic ureteral stents in malignant ureteral obstruction: short-term results and radiological features predicting stent failure in patients with non-urological malignancies.

    Science.gov (United States)

    Chow, Po-Ming; Hsu, Jui-Shan; Wang, Shuo-Meng; Yu, Hong-Jheng; Pu, Yeong-Shiau; Liu, Kao-Lang

    2014-06-01

    To provide short-term result of the metallic ureteral stent in patients with malignant ureteral obstruction and identify radiological findings predicting stent failure. The records of all patients with non-urological malignant diseases who have received metallic ureteral stents from July 2009 to March 2012 for ureteral obstruction were reviewed. Stent failure was detected by clinical symptoms and imaging studies. Survival analysis was used to estimate patency rates and factors predicting stent failure. A total of 74 patients with 130 attempts of stent insertion were included. A total of 113 (86.9 %) stents were inserted successfully and 103 (91.2 %) achieved primary patency. After excluding cases without sufficient imaging data, 94 stents were included in the survival analysis. The median functional duration of the 94 stents was 6.2 months (range 3-476 days). Obstruction in abdominal ureter (p = 0.0279) and lymphatic metastasis around ureter (p = 0.0398) were risk factors for stent failure. The median functional durations of the stents for abdominal and pelvic obstructions were 4.5 months (range 3-263 days) and 6.5 months (range 4-476 days), respectively. The median durations of the stents with and without lymphatic metastasis were 5.3 months (range 4-398 days) and 7.8 months (range 31-476 days), respectively. Metallic ureteral stents are effective and safe in relieving ureteral obstructions resulting from non-urological malignancies, and abdominal ureteral obstruction and lymphatic metastasis around ureter were associated with shorter functional duration.

  4. Expert consensus document: Mind the gaps—advancing research into short-term and long-term neuropsychological outcomes of youth sports-related concussions.

    Science.gov (United States)

    Carman, Aaron J; Ferguson, Rennie; Cantu, Robert; Comstock, R Dawn; Dacks, Penny A; DeKosky, Steven T; Gandy, Sam; Gilbert, James; Gilliland, Chad; Gioia, Gerard; Giza, Christopher; Greicius, Michael; Hainline, Brian; Hayes, Ronald L; Hendrix, James; Jordan, Barry; Kovach, James; Lane, Rachel F; Mannix, Rebekah; Murray, Thomas; Seifert, Tad; Shineman, Diana W; Warren, Eric; Wilde, Elisabeth; Willard, Huntington; Fillit, Howard M

    2015-04-01

    Sports-related concussions and repetitive subconcussive exposure are increasingly recognized as potential dangers to paediatric populations, but much remains unknown about the short-term and long-term consequences of these events, including potential cognitive impairment and risk of later-life dementia. This Expert Consensus Document is the result of a 1-day meeting convened by Safe Kids Worldwide, the Alzheimer's Drug Discovery Foundation, and the Andrews Institute for Orthopaedics and Sports Medicine. The goal is to highlight knowledge gaps and areas of critically needed research in the areas of concussion science, dementia, genetics, diagnostic and prognostic biomarkers, neuroimaging, sports injury surveillance, and information sharing. For each of these areas, we propose clear and achievable paths to improve the understanding, treatment and prevention of youth sports-related concussions.

  5. In Search of Decay in Verbal Short-Term Memory

    Science.gov (United States)

    Berman, Marc G.; Jonides, John; Lewis, Richard L.

    2009-01-01

    Is forgetting in the short term due to decay with the mere passage of time, interference from other memoranda, or both? Past research on short-term memory has revealed some evidence for decay and a plethora of evidence showing that short-term memory is worsened by interference. However, none of these studies has directly contrasted decay and…

  6. Efficacy of a tool to predict short-term mortality in older people presenting at emergency departments: Protocol for a multi-centre cohort study.

    Science.gov (United States)

    Cardona, Magnolia; Lewis, Ebony T; Turner, Robin M; Alkhouri, Hatem; Asha, Stephen; Mackenzie, John; Perkins, Margaret; Suri, Sam; Holdgate, Anna; Winoto, Luis; Chang, Chan-Wei; Gallego-Luxan, Blanca; McCarthy, Sally; Kristensen, Mette R; O'Sullivan, Michael; Skjøt-Arkil, Helene; Ekmann, Anette A; Nygaard, Hanne H; Jensen, Jonas J; Jensen, Rune O; Pedersen, Jonas L; Breen, Dorothy; Petersen, John A; Jensen, Birgitte N; Mogensen, Christian Backer; Hillman, Ken; Brabrand, Mikkel

    Prognostic uncertainty inhibits clinicians from initiating timely end-of-life discussions and advance care planning. This study evaluates the efficacy of the CriSTAL (Criteria for Screening and Triaging to Appropriate aLternative care) checklist in emergency departments. Prospective cohort study of patients aged ≥65 years with any diagnosis admitted via emergency departments in ten hospitals in Australia, Denmark and Ireland. Electronic and paper clinical records will be used to extract risk factors such as nursing home residency, physiological deterioration warranting a rapid response call, personal history of active chronic disease, history of hospitalisations or intensive care unit admission in the past year, evidence of proteinuria or ECG abnormalities, and evidence of frailty to be concurrently measured with Fried Score and Clinical Frailty Scale. Patients or their informal caregivers will be contacted by telephone around three months after initial assessment to ascertain survival, self-reported health, post-discharge frailty and health service utilisation since discharge. Logistic regression and bootstrapping techniques and AUROC curves will be used to test the predictive accuracy of CriSTAL for death within 90 days of admission and in-hospital death. The CriSTAL checklist is an objective and practical tool for use in emergency departments among older patients to determine individual probability of death in the short-term. Its validation in this cohort is expected to reduce clinicians' prognostic uncertainty on the time to patients' death and encourage timely end-of-life conversations to support clinical decisions with older frail patients and their families about their imminent or future care choices. Copyright © 2018 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    Michael, G; Dempster, J; Kane, K A; Coker, S J

    2007-12-01

    Torsade de pointes (TdP) can be induced by a reduction in cardiac repolarizing capacity. The aim of this study was to assess whether IKs blockade or enhancement of INa could potentiate TdP induced by IKr blockade and to investigate whether short-term variability (STV) or triangulation of action potentials preceded TdP. Experiments were performed in open-chest, pentobarbital-anaesthetized, alpha 1-adrenoceptor-stimulated, male New Zealand White rabbits, which received three consecutive i.v. infusions of either the IKr blocker E-4031 (1, 3 and 10 nmol kg(-1) min(-1)), the IKs 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 INa 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. 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. Giving modulators of ion channels in combination substantially increased TdP but, in this model, neither STV nor triangulation of action potentials could predict TdP.

  9. An Exemplar-Familiarity Model Predicts Short-Term and Long-Term Probe Recognition across Diverse Forms of Memory Search

    Science.gov (United States)

    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…

  10. 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.

    Science.gov (United States)

    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 ...

  11. Development of Short-term Molecular Thresholds to Predict Long-term Mouse Liver Tumor Outcomes: Phthalate Case StudyTo be

    Science.gov (United States)

    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...

  12. Discussion of “Prediction intervals for short-term wind farm generation forecasts” and “Combined nonparametric prediction intervals for wind power generation”

    DEFF Research Database (Denmark)

    Pinson, Pierre; Tastu, Julija

    2014-01-01

    A new score for the evaluation of interval forecasts, the so-called coverage width-based criterion (CWC), was proposed and utilized.. This score has been used for the tuning (in-sample) and genuine evaluation (out-ofsample) of prediction intervals for various applications, e.g., electric load [1......], electricity prices [2], general purpose prediction [3], and wind power generation [4], [5]. Indeed, two papers by the same authors appearing in the IEEE Transactions On Sustainable Energy employ that score and use it to conclude on the comparative quality of alternative approaches to interval forecasting...

  13. A Short Term Analogue Memory

    DEFF Research Database (Denmark)

    Shah, Peter Jivan

    1992-01-01

    A short term analogue memory is described. It is based on a well-known sample-hold topology in which leakage currents have been minimized partly by circuit design and partly by layout techniques. Measurements on a test chip implemented in a standard 2.4 micron analogue CMOS process show a droop...

  14. An exemplar-familiarity model predicts short-term and long-term probe recognition across diverse forms of memory search.

    Science.gov (United States)

    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.

  15. Pediatric polytrauma : Short-term and long-term outcomes

    NARCIS (Netherlands)

    vanderSluis, CK; Kingma, J; Eisma, WH; tenDuis, HJ

    Objective: To assess the short-term and long-term outcomes of pediatric polytrauma patients and to analyze the extent to which short-term outcomes can predict long-term outcomes. Materials and Methods: Ail pediatric polytrauma patients (Injury Severity Score of greater than or equal to 16, less than

  16. Short-Term Memory and Aphasia: From Theory to Treatment.

    Science.gov (United States)

    Minkina, Irene; Rosenberg, Samantha; Kalinyak-Fliszar, Michelene; Martin, Nadine

    2017-02-01

    This article reviews existing research on the interactions between verbal short-term memory and language processing impairments in aphasia. Theoretical models of short-term memory are reviewed, starting with a model assuming a separation between short-term memory and language, and progressing to models that view verbal short-term memory as a cognitive requirement of language processing. The review highlights a verbal short-term memory model derived from an interactive activation model of word retrieval. This model holds that verbal short-term memory encompasses the temporary activation of linguistic knowledge (e.g., semantic, lexical, and phonological features) during language production and comprehension tasks. Empirical evidence supporting this model, which views short-term memory in the context of the processes it subserves, is outlined. Studies that use a classic measure of verbal short-term memory (i.e., number of words/digits correctly recalled in immediate serial recall) as well as those that use more intricate measures (e.g., serial position effects in immediate serial recall) are discussed. Treatment research that uses verbal short-term memory tasks in an attempt to improve language processing is then summarized, with a particular focus on word retrieval. A discussion of the limitations of current research and possible future directions concludes the review. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  17. Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study).

    Science.gov (United States)

    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 model. The AUC statistic quantified the ROC curve's capacity to classify participants likely to lose 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.

  18. Short-term Memory of Deep RNN

    OpenAIRE

    Gallicchio, Claudio

    2018-01-01

    The extension of deep learning towards temporal data processing is gaining an increasing research interest. In this paper we investigate the properties of state dynamics developed in successive levels of deep recurrent neural networks (RNNs) in terms of short-term memory abilities. Our results reveal interesting insights that shed light on the nature of layering as a factor of RNN design. Noticeably, higher layers in a hierarchically organized RNN architecture results to be inherently biased ...

  19. Predictable 'meta-mechanisms' emerge from feedbacks between transpiration and plant growth and cannot be simply deduced from short-term mechanisms.

    Science.gov (United States)

    Tardieu, François; Parent, Boris

    2017-06-01

    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. © 2016 John Wiley & Sons Ltd.

  20. 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

    Science.gov (United States)

    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

  1. Short-Term Research Experiences with Teachers in Earth and Planetary Sciences and a Model for Integrating Research into Classroom Inquiry

    Science.gov (United States)

    Morgan, P.; Bloom, J. W.

    2006-12-01

    For the past three summers, we have worked with in-service teachers on image processing, planetary geology, and earthquake and volcano content modules using inquiry methods that ended with mini-research experiences. Although almost all were science teachers, very few could give a reasonable definition of science at the start of the modules, and very few had a basic grasp of the processes of scientific research and could not include substantive scientific inquiry into their lessons. To build research understanding and confidence, an instructor-student interaction model was used in the modules. Studies have shown that children who participate in classrooms as learning and inquiry communities develop more complex understandings. The same patterns of complex understandings have resulted in similarly structured professional communities of teachers. The model is based on professional communities, emphasizing from the beginning that inquiry is a form of research. Although the actual "research" component of the modules was short, the teachers were identified as professionals and researchers from the start. Research/inquiry participation is therefore an excellent example by which to allow their teachers to learn. Initially the teachers were very reluctant to pose questions. As they were encouraged to share, collaborate, and support each other, the role of the instructor became less of a leader and more of a facilitator, and the confidence of the teachers as professionals and researchers grew. One teacher even remarked, "This is how we should be teaching our kids!' Towards the end of the modules the teachers were ready for their mini- research projects and collaborated in teams of 2-4. They selected their own research topics, but were guided toward research questions that required data collection (from existing studies), some data manipulation, interpretation, and drawing conclusions with respect to the original question. The teachers were enthusiastic about all of their

  2. Short-term effects of air pollution, markers of endothelial activation, and coagulation to predict major adverse cardiovascular events in patients with acute coronary syndrome: insights from AIRACOS study.

    Science.gov (United States)

    Dominguez-Rodriguez, Alberto; Abreu-Gonzalez, Pedro; Rodríguez, Sergio; Avanzas, Pablo; Juarez-Prera, Ruben A

    2017-07-01

    The aim of this study was to determine whether markers of inflammation and coagulation are associated with short-term particulate matter exposure and predict major adverse cardiovascular events at 360 d in patients with acute coronary syndrome (ACS). We included 307 consecutive patients, and assessed the average concentrations of data on atmospheric pollution in ambient air and meteorological variables from 1 d up to 7 d prior to admission. In patients with ACS, the markers of endothelial activation and coagulation, but not black carbon exposure, are associated with major adverse cardiovascular events at one-year follow-up.

  3. A comparison between the ECMWF and COSMO Ensemble Prediction Systems applied to short-term wind power forecasting on real data

    DEFF Research Database (Denmark)

    Alessandrini, S.; Sperati, S.; Pinson, Pierre

    2013-01-01

    together with a single forecast power value for each future time horizon. A comparison between two different ensemble forecasting models, ECMWF EPS (Ensemble Prediction System in use at the European Centre for Medium-Range Weather Forecasts) and COSMO-LEPS (Limited-area Ensemble Prediction System developed...... ahead forecast horizon. A statistical calibration of the ensemble wind speed members based on the use of past wind speed measurements is explained. The two models are compared using common verification indices and diagrams. The higher horizontal resolution model (COSMO-LEPS) shows slightly better...

  4. 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

    Science.gov (United States)

    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...

  5. Onboard Short Term Plan Viewer

    Science.gov (United States)

    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.

  6. Research and Application of a Novel Hybrid Model Based on Data Selection and Artificial Intelligence Algorithm for Short Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Wendong Yang

    2017-01-01

    Full Text Available Machine learning plays a vital role in several modern economic and industrial fields, and selecting an optimized machine learning method to improve time series’ forecasting accuracy is challenging. Advanced machine learning methods, e.g., the support vector regression (SVR model, are widely employed in forecasting fields, but the individual SVR pays no attention to the significance of data selection, signal processing and optimization, which cannot always satisfy the requirements of time series forecasting. By preprocessing and analyzing the original time series, in this paper, a hybrid SVR model is developed, considering periodicity, trend and randomness, and combined with data selection, signal processing and an optimization algorithm for short-term load forecasting. Case studies of electricity power data from New South Wales and Singapore are regarded as exemplifications to estimate the performance of the developed novel model. The experimental results demonstrate that the proposed hybrid method is not only robust but also capable of achieving significant improvement compared with the traditional single models and can be an effective and efficient tool for power load forecasting.

  7. Cross-cultural comparison of long-term care in the United States and Finland: Research done through a short-term study-abroad experience.

    Science.gov (United States)

    Kruger, Tina M; Gilland, Sarah; Frank, Jacquelyn B; Murphy, Bridget C; English, Courtney; Meade, Jana; Morrow, Kaylee; Rush, Evan

    2017-01-01

    In May 2014, a short-term study-abroad experience was conducted in Finland through a course offered at Indiana State University (ISU). Students and faculty from ISU and Eastern Illinois University participated in the experience, which was created to facilitate a cross-cultural comparison of long-term-care settings in the United States and Finland. With its outstanding system of caring for the health and social needs of its aging populace, Finland is a logical model to examine when considering ways to improve the quality of life for older adults who require care in the United States . Those participating in the course visited a series of long-term-care facilities in the region surrounding Terre Haute, Indiana, then travelled to Lappeenranta, Finland to visit parallel sites. Through limited-participation observation and semistructured interviews, similarities and differences in experiences, educations, and policies affecting long-term care workers in the United States and Finland were identified and are described here.

  8. A comparison of the recording of comorbidity in primary and secondary care by using the Charlson Index to predict short-term and long-term survival in a routine linked data cohort.

    Science.gov (United States)

    Crooks, C J; West, J; Card, T R

    2015-06-05

    Hospital admission records provide snapshots of clinical histories for a subset of the population admitted to hospital. In contrast, primary care records provide continuous clinical histories for complete populations, but might lack detail about inpatient stays. Therefore, combining primary and secondary care records should improve the ability of comorbidity scores to predict survival in population-based studies, and provide better adjustment for case-mix differences when assessing mortality outcomes. Cohort study. English primary and secondary care 1 January 2005 to 1 January 2010. All patients 20 years and older registered to a primary care practice contributing to the linked Clinical Practice Research Datalink from England. The performance of the Charlson index with mortality was compared when derived from either primary or secondary care data or both. This was assessed in relation to short-term and long-term survival, age, consultation rate, and specific acute and chronic diseases. 657,264 people were followed up from 1 January 2005. Although primary care recorded more comorbidity than secondary care, the resulting C statistics for the Charlson index remained similar: 0.86 and 0.87, respectively. Higher consultation rates and restricted age bands reduced the performance of the Charlson index, but the index's excellent performance persisted over longer follow-up; the C statistic was 0.87 over 1 year, and 0.85 over all 5 years of follow-up. The Charlson index derived from secondary care comorbidity had a greater effect than primary care comorbidity in reducing the association of upper gastrointestinal bleeding with mortality. However, they had a similar effect in reducing the association of diabetes with mortality. These findings support the use of the Charlson index from linked data and show that secondary care comorbidity coding performed at least as well as that derived from primary care in predicting survival. Published by the BMJ Publishing Group Limited

  9. Short-Term Memory in Habituation and Dishabituation

    Science.gov (United States)

    Whitlow, Jesse William, Jr.

    1975-01-01

    The present research evaluated the refractorylike response decrement, as found in habituation of auditory evoked peripheral vasoconstriction in rabbits, to determine whether or not it represents a short-term habituation process distinct from effector fatigue or sensory adaptation. (Editor)

  10. Aspects if stochastic models for short-term hydropower scheduling and bidding

    Energy Technology Data Exchange (ETDEWEB)

    Belsnes, Michael Martin [Sintef Energy, Trondheim (Norway); Follestad, Turid [Sintef Energy, Trondheim (Norway); Wolfgang, Ove [Sintef Energy, Trondheim (Norway); Fosso, Olav B. [Dep. of electric power engineering NTNU, Trondheim (Norway)

    2012-07-01

    This report discusses challenges met when turning from deterministic to stochastic decision support models for short-term hydropower scheduling and bidding. The report describes characteristics of the short-term scheduling and bidding problem, different market and bidding strategies, and how a stochastic optimization model can be formulated. A review of approaches for stochastic short-term modelling and stochastic modelling for the input variables inflow and market prices is given. The report discusses methods for approximating the predictive distribution of uncertain variables by scenario trees. Benefits of using a stochastic over a deterministic model are illustrated by a case study, where increased profit is obtained to a varying degree depending on the reservoir filling and price structure. Finally, an approach for assessing the effect of using a size restricted scenario tree to approximate the predictive distribution for stochastic input variables is described. The report is a summary of the findings of Work package 1 of the research project #Left Double Quotation Mark#Optimal short-term scheduling of wind and hydro resources#Right Double Quotation Mark#. The project aims at developing a prototype for an operational stochastic short-term scheduling model. Based on the investigations summarized in the report, it is concluded that using a deterministic equivalent formulation of the stochastic optimization problem is convenient and sufficient for obtaining a working prototype. (author)

  11. Extrapolation of short term observations to time periods relevant to the isolation of long lived radioactive waste. Results of a co-ordinated research project 1995-2000

    International Nuclear Information System (INIS)

    2000-09-01

    This report addresses safety analysis of the whole repository life-cycle that may require long term performance assessment of its components and evaluation of potential impacts of the facility on the environment. Generic consideration of procedures for the development of predictive tools are completed by detailed characterization of selected principles and methods that were applied and presented within the co-ordinated research project (CRP). The project focused on different approaches to extrapolation, considering radionuclide migration/sorption, physical, geochemical and geotechnical characteristics of engineered barriers, irradiated rock and backfill performance, and on corrosion of metallic and vitreous materials. This document contains a comprehensive discussion of the overall problem and the practical results of the individual projects preformed within the CRP. Each of the papers on the individual projects has been indexed separately

  12. Risky decision-making predicts short-term outcome of community but not residential treatment for opiate addiction. Implications for case management.

    Science.gov (United States)

    Passetti, F; Clark, L; Davis, P; Mehta, M A; White, S; Checinski, K; King, M; Abou-Saleh, M

    2011-10-01

    Opiate addiction is associated with decision-making deficits and we previously showed that the extent of these impairments predicts aspects of treatment outcome. Here we aimed to establish whether measures of decision-making performance might be used to inform placement matching. Two groups of opiate dependent individuals, one receiving treatment in a community setting (n=48) and one in a residential setting (n=32) were administered computerised tests of decision-making, impulsivity and planning shortly after the beginning of treatment, to be followed up three months into each programme. In the community sample, performance on the decision-making tasks at initial assessment predicted abstinence from illicit drugs at follow-up. In contrast, in the residential sample there was no relationship between decision-making and clinical outcome. Intact decision-making processes appear to be necessary for upholding a resolve to avoid taking drugs in a community setting, but the importance of these mechanisms may be attenuated in a residential treatment setting. The results support the placement matching hypothesis, suggesting that individuals with more prominent decision-making deficits may particularly benefit from treatment in a residential setting and from the inclusion of aspects of cognitive rehabilitation in their treatment programme. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  13. 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.

    Science.gov (United States)

    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.

  14. Evaluation of Short Term Memory Span Function In Children

    Directory of Open Access Journals (Sweden)

    Barış ERGÜL

    2016-12-01

    Full Text Available Although details of the information encoded in the short-term memory where it is stored temporarily be recorded in the working memory in the next stage. Repeating the information mentally makes it remain in memory for a long time. Studies investigating the relationship between short-term memory and reading skills that are carried out to examine the relationship between short-term memory processes and reading comprehension. In this study information coming to short-term memory and the factors affecting operation of short term memory are investigated with regression model. The aim of the research is to examine the factors (age, IQ and reading skills that are expected the have an effect on short-term memory in children through regression analysis. One of the assumptions of regression analysis is to examine which has constant variance and normal distribution of the error term. In this study, because the error term is not normally distributed, robust regression techniques were applied. Also, for each technique; coefficient of determination is determined. According to the findings, the increase in age, IQ and reading skills caused the increase in short term memory in children. After applying robust regression techniques, the Winsorized Least Squares (WLS technique gives the highest coefficient of determination.

  15. 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

    DEFF Research Database (Denmark)

    Stræde, Mia; Brabrand, Mikkel

    2014-01-01

    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.......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....

  16. High-resolution energetic particle measurements at 6.6R/sub E/ 3. Low-energy electron anisotropies and short-term substorm predictions

    International Nuclear Information System (INIS)

    Baker, D.N.; Higbie, P.R.; Hones, E.W. Jr.; Belian, R.D.

    1978-01-01

    Multiple detectors giving nearly complete 4π coverage of particle pitch angle distributions have provided high resolution measurements (in energy and time) of 30- to 300-keV electrons. Data from a spacecraft (1976-059A) in geostationary orbit show a remarkably consistent sequence of variations of the electron anisotropy before and during magnetospheric substorms. For periods typically 1--2 hours prior to the onset of substorms, electron distributions, peaked along the direction of the local magnetic field, are observed in the premidnight sector. These cigarlike anisotropies are accompanied by a local taillike magnetic field which may develop further during the event. At substorm onset an abrupt transition usually occurs from the cigar-shaped distributions to pancake-shaped distributions. This anisotropy sequence may be due to the buildup and subsequent release of stresses in the magnetotail; the cigar phase may also be due to associated processes at the dayside magnetopause causing a loss of 90 0 pitch angle particles. The present observations, based on approx.100 events, appear to provide a predictive tool for assessing the probability of occurrence of a substorm

  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.

    Science.gov (United States)

    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 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. Atmospheric emissions of Cu and Zn from coal combustion in China: Spatio-temporal distribution, human health effects, and short-term prediction.

    Science.gov (United States)

    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.

  19. Re-evaluation of lung to thorax transverse area ratio immediately before birth in predicting postnatal short-term outcomes of fetuses with isolated left-sided congenital diaphragmatic hernia: A single center analysis.

    Science.gov (United States)

    Kido, Saki; Hidaka, Nobuhiro; Sato, Yuka; Fujita, Yasuyuki; Miyoshi, Kina; Nagata, Kouji; Taguchi, Tomoaki; Kato, Kiyoko

    2018-05-01

    We aimed to investigate whether the lung-to-thorax transverse area ratio (LTR) immediately before birth is of diagnostic value for the prediction of postnatal short-term outcomes in cases of isolated left-sided congenital diaphragmatic hernia (CDH). We retrospectively reviewed the cases of fetal isolated left-sided CDH managed at our institution between April 2008 and July 2016. We divided the patients into two groups based on LTR immediately before birth, using a cut-off value of 0.08. We compared the proportions of subjects within the two groups who survived until discharge using Fisher's exact test. Further, using Spearman's rank correlation, we assessed whether LTR was correlated with length of stay, duration of mechanical ventilation, and supplemental oxygen. Twenty-nine subjects were included (five with LTR < 0.08, and 24 with LTR ≥ 0.08). The proportion of subjects surviving until discharge was 40% (2/5) for patients with LTR < 0.08, as compared with 96% (23/24) for those with LTR ≥ 0.08. LTR measured immediately before birth was negatively correlated with the postnatal length of stay (Spearman's rank correlation coefficient, rs = -0.486), and the duration of supplemental oxygen (rs = -0.537). Further, the duration of mechanical ventilation was longer in patients with a lower LTR value. LTR immediately before birth is useful for the prediction of postnatal short-term outcomes in fetuses with isolated left-sided CDH. In particular, patients with prenatal LTR value less than 0.08 are at increased risk of postnatal death. © 2017 Japanese Teratology Society.

  20. Short-term stress, but not mucosal healing nor depression was predictive for the risk of relapse in patients with ulcerative colitis: a prospective 12-month follow-up study.

    Science.gov (United States)

    Langhorst, Jost; Hofstetter, Anna; Wolfe, Fred; Häuser, Winfried

    2013-10-01

    Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease. Psychological factors such as depression and stress are under debate to contribute to the risk of relapse. The impact of mucosal healing to reduce the risk of relapse had not been studied prospectively. The aim of this study was to identify whether depression and stress increase and mucosal healing reduces the risk of clinical relapse in patients with UC in clinical remission. Patients in clinical remission were followed prospectively for 1 year, or less if they relapsed. Endoscopy and histology score and long-term perceived stress (Perceived Stress Questionnaire) were measured at baseline. Mucosal healing was defined by a Mayo Endoscopy score of 0-1. Depression (Hospital Anxiety and Depression Scale) and acute perceived stress (Cohen Perceived Stress Scale) were measured at baseline and after 1, 3, 6, 9, and 12 months. A time-dependent multivariate Cox regression model determined the predictors of time to relapse. Seventy-five patients were included into final analysis, of which 28 (37.3%) relapsed. Short-term stress at the last visit before relapse (hazard ratio [HR] = 1.05, 95% confidence interval [CI] = 1.01-1.10) and male gender (HR = 2.38, 95% CI = 1.01-5.61), but not baseline mucosal healing (HR = 0.86, 95% CI = 0.35-2.11), baseline long-term stress (HR = 0.20, 95% CI = 0.01-3.31), and depression at the last visit before relapse (HR = 1.08, 95% CI = 0.95-1.22) were predictive for a relapse. Short-term stress but not depression nor mucosal healing was predictive for the risk of relapse in patients with UC in clinical remission. Larger multicentre studies are necessary to confirm our findings.

  1. Narcissism and the Strategic Pursuit of Short-Term Mating

    DEFF Research Database (Denmark)

    Schmitt, David P.; Alcalay, Lidia; Allik, Jüri

    2017-01-01

    Previous studies have documented links between sub-clinical narcissism and the active pursuit of short-term mating strategies (e.g., unrestricted sociosexuality, marital infidelity, mate poaching). Nearly all of these investigations have relied solely on samples from Western cultures. In the curr...... limitations of these cross-culturally universal findings and presents suggestions for future research into revealing the precise psychological features of narcissism that facilitate the strategic pursuit of short-term mating....

  2. Economics of solar energy: Short term costing

    Science.gov (United States)

    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.

  3. Short-term memory in Down syndrome: applying the working memory model.

    Science.gov (United States)

    Jarrold, C; Baddeley, A D

    2001-10-01

    This paper is divided into three sections. The first reviews the evidence for a verbal short-term memory deficit in Down syndrome. Existing research suggests that short-term memory for verbal information tends to be impaired in Down syndrome, in contrast to short-term memory for visual and spatial material. In addition, problems of hearing or speech do not appear to be a major cause of difficulties on tests of verbal short-term memory. This suggests that Down syndrome is associated with a specific memory problem, which we link to a potential deficit in the functioning of the 'phonological loop' of Baddeley's (1986) model of working memory. The second section considers the implications of a phonological loop problem. Because a reasonable amount is known about the normal functioning of the phonological loop, and of its role in language acquisition in typical development, we can make firm predictions as to the likely nature of the short-term memory problem in Down syndrome, and its consequences for language learning. However, we note that the existing evidence from studies with individuals with Down syndrome does not fit well with these predictions. This leads to the third section of the paper, in which we consider key questions to be addressed in future research. We suggest that there are two questions to be answered, which follow directly from the contradictory results outlined in the previous section. These are 'What is the precise nature of the verbal short-term memory deficit in Down syndrome', and 'What are the consequences of this deficit for learning'. We discuss ways in which these questions might be addressed in future work.

  4. Short-term incentive schemes for hospital managers

    Directory of Open Access Journals (Sweden)

    Lucas Malambe

    2013-10-01

    Full Text Available Orientation: Short-term incentives, considered to be an extrinsic motivation, are commonly used to motivate performance. This study explored hospital managers’ perceptions of short term incentives in maximising performance and retention. Research purpose: The study explored the experiences, views and perceptions of private hospital managers in South Africa regarding the use of short-term incentives to maximise performance and retention, as well as the applicability of the findings to public hospitals. Motivation for the study: Whilst there is an established link between performance reward schemes and organisational performance, there is little understanding of the effects of short term incentives on the performance and retention of hospital managers within the South African context. Research design, approach, and method: The study used a qualitative research design: interviews were conducted with a purposive sample of 19 hospital managers, and a thematic content analysis was performed. Main findings: Short-term incentives may not be the primary motivator for hospital managers, but they do play a critical role in sustaining motivation. Participants indicated that these schemes could also be applicable to public hospitals. Practical/managerial implications: Hospital managers are inclined to be more motivated by intrinsic than extrinsic factors. However, hospital managers (as middle managers also seem to be motivated by short-term incentives. A combination of intrinsic and extrinsic motivators should thus be used to maximise performance and retention. Contribution/value-add: Whilst the study sought to explore hospital managers’ perceptions of short-term incentives, it also found that an adequate balance between internal and external motivators is key to implementing an effective short-term incentive scheme.

  5. GOES-R Proving Ground Activities at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

    Science.gov (United States)

    Molthan, Andrew

    2011-01-01

    SPoRT is actively involved in GOES-R Proving Ground activities in a number of ways: (1) Applying the paradigm of product development, user training, and interaction to foster interaction with end users at NOAA forecast offices national centers. (2) Providing unique capabilities in collaboration with other GOES-R Proving Ground partners (a) Hybrid GOES-MODIS imagery (b) Pseudo-GLM via regional lightning mapping arrays (c) Developing new RGB imagery from EUMETSAT guidelines

  6. The Demonstration of Short-Term Consolidation.

    Science.gov (United States)

    Jolicoeur, Pierre; Dell'Acqua, Roberto

    1998-01-01

    Results of seven experiments involving 112 college students or staff using a dual-task approach provide evidence that encoding information into short-term memory involves a distinct process termed short-term consolidation (STC). Results suggest that STC has limited capacity and that it requires central processing mechanisms. (SLD)

  7. Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

    Science.gov (United States)

    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…

  8. Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting

    Directory of Open Access Journals (Sweden)

    Federico Divina

    2018-04-01

    Full Text Available The ability to predict short-term electric energy demand would provide several benefits, both at the economic and environmental level. For example, it would allow for an efficient use of resources in order to face the actual demand, reducing the costs associated to the production as well as the emission of CO 2 . To this aim, in this paper we propose a strategy based on ensemble learning in order to tackle the short-term load forecasting problem. In particular, our approach is based on a stacking ensemble learning scheme, where the predictions produced by three base learning methods are used by a top level method in order to produce final predictions. We tested the proposed scheme on a dataset reporting the energy consumption in Spain over more than nine years. The obtained experimental results show that an approach for short-term electricity consumption forecasting based on ensemble learning can help in combining predictions produced by weaker learning methods in order to obtain superior results. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that using an ensemble scheme can achieve very accurate predictions, and thus that it is a suitable approach for addressing the short-term load forecasting problem.

  9. Predicting short-term mortality in advanced decompensated heart failure - role of the updated acute decompensated heart failure/N-terminal pro-B-type natriuretic Peptide risk score.

    Science.gov (United States)

    Scrutinio, Domenico; Ammirati, Enrico; Passantino, Andrea; Guida, Pietro; D'Angelo, Luciana; Oliva, Fabrizio; Ciccone, Marco Matteo; Iacoviello, Massimo; Dentamaro, Ilaria; Santoro, Daniela; Lagioia, Rocco; Sarzi Braga, Simona; Guzzetti, Daniela; Frigerio, Maria

    2015-01-01

    The first few months after admission are the most vulnerable period in patients with acute decompensated heart failure (ADHF). We assessed the association of the updated ADHF/N-terminal pro-B-type natriuretic peptide (NT-proBNP) risk score with 90-day and in-hospital mortality in 701 patients admitted with advanced ADHF, defined as severe symptoms of worsening HF, severely depressed left ventricular ejection fraction, and the need for i.v. diuretic and/or inotropic drugs. A total of 15.7% of the patients died within 90 days of admission and 5.2% underwent ventricular assist device (VAD) implantation or urgent heart transplantation (UHT). The C-statistic of the ADHF/NT-proBNP risk score for 90-day mortality was 0.810 (95% CI: 0.769-0.852). Predicted and observed mortality rates were in close agreement. When the composite outcome of death/VAD/UHT at 90 days was considered, the C-statistic decreased to 0.741. During hospitalization, 7.6% of the patients died. The C-statistic for in-hospital mortality was 0.815 (95% CI: 0.761-0.868) and Hosmer-Lemeshow χ(2)=3.71 (P=0.716). The updated ADHF/NT-proBNP risk score outperformed the Acute Decompensated Heart Failure National Registry, the Organized Program to Initiate Lifesaving Treatment in Patients Hospitalized for Heart Failure, and the American Heart Association Get with the Guidelines Program predictive models. Updated ADHF/NT-proBNP risk score is a valuable tool for predicting short-term mortality in severe ADHF, outperforming existing inpatient predictive models.

  10. Short term memory in echo state networks

    OpenAIRE

    Jaeger, H.

    2001-01-01

    The report investigates the short-term memory capacity of echo state recurrent neural networks. A quantitative measure MC of short-term memory capacity is introduced. The main result is that MC 5 N for networks with linear Output units and i.i.d. input, where N is network size. Conditions under which these maximal memory capacities are realized are described. Several theoretical and practical examples demonstrate how the short-term memory capacities of echo state networks can be exploited for...

  11. Expanding research capabilities with sea ice climate records for analysis of long-term climate change and short-term variability

    Science.gov (United States)

    Scott, D. J.; Meier, W. N.

    2008-12-01

    Recent sea ice analysis is leading to predictions of a sea ice-free summertime in the Arctic within 20 years, or even sooner. Sea ice topics, such as concentration, extent, motion, and age, are predominately studied using satellite data. At the National Snow and Ice Data Center (NSIDC), passive microwave sea ice data sets provide timely assessments of seasonal-scale variability as well as consistent long-term climate data records. Such data sets are crucial to understanding changes and assessing their impacts. Noticeable impacts of changing sea ice conditions on native cultures and wildlife in the Arctic region are now being documented. With continued deterioration in Arctic sea ice, global economic impacts will be seen as new shipping routes open. NSIDC is at the forefront of making climate data records available to address the changes in sea ice and its global impacts. By focusing on integrated data sets, NSIDC leads the way by broadening the studies of sea ice beyond the traditional cryospheric community.

  12. Working memory training improves visual short-term memory capacity.

    Science.gov (United States)

    Schwarb, Hillary; Nail, Jayde; Schumacher, Eric H

    2016-01-01

    Since antiquity, philosophers, theologians, and scientists have been interested in human memory. However, researchers today are still working to understand the capabilities, boundaries, and architecture. While the storage capabilities of long-term memory are seemingly unlimited (Bahrick, J Exp Psychol 113:1-2, 1984), working memory, or the ability to maintain and manipulate information held in memory, seems to have stringent capacity limits (e.g., Cowan, Behav Brain Sci 24:87-185, 2001). Individual differences, however, do exist and these differences can often predict performance on a wide variety of tasks (cf. Engle What is working-memory capacity? 297-314, 2001). Recently, researchers have promoted the enticing possibility that simple behavioral training can expand the limits of working memory which indeed may also lead to improvements on other cognitive processes as well (cf. Morrison and Chein, Psychol Bull Rev 18:46-60 2011). However, initial investigations across a wide variety of cognitive functions have produced mixed results regarding the transferability of training-related improvements. Across two experiments, the present research focuses on the benefit of working memory training on visual short-term memory capacity-a cognitive process that has received little attention in the training literature. Data reveal training-related improvement of global measures of visual short-term memory as well as of measures of the independent sub-processes that contribute to capacity (Awh et al., Psychol Sci 18(7):622-628, 2007). These results suggest that the ability to inhibit irrelevant information within and between trials is enhanced via n-back training allowing for selective improvement on untrained tasks. Additionally, we highlight a potential limitation of the standard adaptive training procedure and propose a modified design to ensure variability in the training environment.

  13. Brain oscillatory substrates of visual short-term memory capacity.

    Science.gov (United States)

    Sauseng, Paul; Klimesch, Wolfgang; Heise, Kirstin F; Gruber, Walter R; Holz, Elisa; Karim, Ahmed A; Glennon, Mark; Gerloff, Christian; Birbaumer, Niels; Hummel, Friedhelm C

    2009-11-17

    The amount of information that can be stored in visual short-term memory is strictly limited to about four items. Therefore, memory capacity relies not only on the successful retention of relevant information but also on efficient suppression of distracting information, visual attention, and executive functions. However, completely separable neural signatures for these memory capacity-limiting factors remain to be identified. Because of its functional diversity, oscillatory brain activity may offer a utile solution. In the present study, we show that capacity-determining mechanisms, namely retention of relevant information and suppression of distracting information, are based on neural substrates independent of each other: the successful maintenance of relevant material in short-term memory is associated with cross-frequency phase synchronization between theta (rhythmical neural activity around 5 Hz) and gamma (> 50 Hz) oscillations at posterior parietal recording sites. On the other hand, electroencephalographic alpha activity (around 10 Hz) predicts memory capacity based on efficient suppression of irrelevant information in short-term memory. Moreover, repetitive transcranial magnetic stimulation at alpha frequency can modulate short-term memory capacity by influencing the ability to suppress distracting information. Taken together, the current study provides evidence for a double dissociation of brain oscillatory correlates of visual short-term memory capacity.

  14. LANGUAGE REPETITION AND SHORT-TERM MEMORY: AN INTEGRATIVE FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Steve eMajerus

    2013-07-01

    Full Text Available Short-term maintenance of verbal information is a core factor of language repetition, especially when reproducing multiple or unfamiliar stimuli. Many models of language processing locate the verbal short-term maintenance function in the left posterior superior temporo-parietal area and its connections with the inferior frontal gyrus. However, research in the field of short-term memory has implicated bilateral fronto-parietal networks, involved in attention and serial order processing, as being critical for the maintenance and reproduction of verbal sequences. We present here an integrative framework aimed at bridging research in the language processing and short-term memory fields. This framework considers verbal short-term maintenance as an emergent function resulting from synchronized and integrated activation in dorsal and ventral language processing networks as well as fronto-parietal attention and serial order processing networks. To-be-maintained item representations are temporarily activated in the dorsal and ventral language processing networks, novel phoneme and word serial order information is proposed to be maintained via a right fronto-parietal serial order processing network, and activation in these different networks is proposed to be coordinated and maintained via a left fronto-parietal attention processing network. This framework provides new perspectives for our understanding of information maintenance at the nonword-, word- and sentence-level as well as of verbal maintenance deficits in case of brain injury.

  15. Language repetition and short-term memory: an integrative framework.

    Science.gov (United States)

    Majerus, Steve

    2013-01-01

    Short-term maintenance of verbal information is a core factor of language repetition, especially when reproducing multiple or unfamiliar stimuli. Many models of language processing locate the verbal short-term maintenance function in the left posterior superior temporo-parietal area and its connections with the inferior frontal gyrus. However, research in the field of short-term memory has implicated bilateral fronto-parietal networks, involved in attention and serial order processing, as being critical for the maintenance and reproduction of verbal sequences. We present here an integrative framework aimed at bridging research in the language processing and short-term memory fields. This framework considers verbal short-term maintenance as an emergent function resulting from synchronized and integrated activation in dorsal and ventral language processing networks as well as fronto-parietal attention and serial order processing networks. To-be-maintained item representations are temporarily activated in the dorsal and ventral language processing networks, novel phoneme and word serial order information is proposed to be maintained via a right fronto-parietal serial order processing network, and activation in these different networks is proposed to be coordinated and maintained via a left fronto-parietal attention processing network. This framework provides new perspectives for our understanding of information maintenance at the non-word-, word- and sentence-level as well as of verbal maintenance deficits in case of brain injury.

  16. Mapping the isotopic signature of methane in South-Eastern Spain: complementing biogeochemical long-term research with short term observations

    Science.gov (United States)

    Àgueda, Alba; Morguí, Josep Anton; Vazquez Garcia, Eusebi; Curcoll, Roger; Lowry, David; Fisher, Rebecca E.; Nisbet, Euan G.

    2016-04-01

    will be helpful in the validation of transport models. *Corresponding author: Josep Anton Morguí - josep-anton.morgui@ic3.cat "The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) in the InGOS project under grant agreement n° 284274''

  17. [An intergenerational health promotion program involving older adults in urban areas. "Research of Productivity by Intergenerational Sympathy (REPRINTS)": first-year experience and short-term effects].

    Science.gov (United States)

    Fujiwara, Yoshinori; Nishi, Mariko; Watanabe, Naoki; Lee, Sangyoon; Inoue, Kazuko; Yoshida, Hiroto; Sakuma, Naoko; Kureta, Youichi; Ishii, Kenji; Uchida, Hayato; Kakuno, Fumihiko; Shinkai, Shoji

    2006-09-01

    We have launched a new intervention study, called "Research of Productivity by Intergenerational Sympathy (REPRINTS)" in which senior volunteers engage in reading picture books to children. The "REPRINTS" program consistently involves social roles and intellectual activity, two higher-level functional capacities. This study reported findings and problems experienced through "REPRINTS" during the first year, ascertained potential effectiveness of social activity, and proposed methods for continued activity. Basic concepts of "REPRINTS"program include "contribution to society", "life-long learning", and "group activity." Sixty seven volunteers and 74 controls, all aged 60 years and over living in three areas, ie., Chuo-ku, central Tokyo, Kawasaki city, suburb of Tokyo and Nagahama city, a local city, participated in a baseline health check-up in June, 2004. After completion of 3-month training seminars (once a week, 2 hr per session), volunteers visited public elementary schools and kindergartens in groups of 6-10 persons for 6 months. They were assessed again by follow-up health check-up in March, 2005. At baseline, the proportion of those who had no grand children (41.8% vs. 20.3%, P= 0.006), average school years (13.4 +/- 2.5 vs. 12.3 +/- 2.5 years, P= 0.008), having any experience of volunteer activities (79.1% vs. 52.7%, P=0.001), and an usual walking speed (86.7 +/- 12.3 vs. 81.3 +/- 12.9 m/min, P=0.012) were significantly higher in volunteers than in controls. There was no significant difference in other baseline characteristics between the two groups. At follow-up, social network scores for 56 volunteers were significantly improved: frequency of contact with grandchildren and others around neighborhood and size of circles of friends and acquaintances were increased, as compared to controls. Social support scores for the volunteers significantly decreased in the receiving aspect, while increased in the giving aspect. In addition, consciousness of loving

  18. Fast Weight Long Short-Term Memory

    OpenAIRE

    Keller, T. Anderson; Sridhar, Sharath Nittur; Wang, Xin

    2018-01-01

    Associative memory using fast weights is a short-term memory mechanism that substantially improves the memory capacity and time scale of recurrent neural networks (RNNs). As recent studies introduced fast weights only to regular RNNs, it is unknown whether fast weight memory is beneficial to gated RNNs. In this work, we report a significant synergy between long short-term memory (LSTM) networks and fast weight associative memories. We show that this combination, in learning associative retrie...

  19. Fuzzy approach for short term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Chenthur Pandian, S.; Duraiswamy, K.; Kanagaraj, N. [Electrical and Electronics Engg., K.S. Rangasamy College of Technology, Tiruchengode 637209, Tamil Nadu (India); Christober Asir Rajan, C. [Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Pondicherry (India)

    2006-04-15

    The main objective of short term load forecasting (STLF) is to provide load predictions for generation scheduling, economic load dispatch and security assessment at any time. The STLF is needed to supply necessary information for the system management of day-to-day operations and unit commitment. In this paper, the 'time' and 'temperature' of the day are taken as inputs for the fuzzy logic controller and the 'forecasted load' is the output. The input variable 'time' has been divided into eight triangular membership functions. The membership functions are Mid Night, Dawn, Morning, Fore Noon, After Noon, Evening, Dusk and Night. Another input variable 'temperature' has been divided into four triangular membership functions. They are Below Normal, Normal, Above Normal and High. The 'forecasted load' as output has been divided into eight triangular membership functions. They are Very Low, Low, Sub Normal, Moderate Normal, Normal, Above Normal, High and Very High. Case studies have been carried out for the Neyveli Thermal Power Station Unit-II (NTPS-II) in India. The fuzzy forecasted load values are compared with the conventional forecasted values. The forecasted load closely matches the actual one within +/-3%. (author)

  20. Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility.

    Science.gov (United States)

    Heffernan, Rhys; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

    2017-09-15

    The accuracy of predicting protein local and global structural properties such as secondary structure and solvent accessible surface area has been stagnant for many years because of the challenge of accounting for non-local interactions between amino acid residues that are close in three-dimensional structural space but far from each other in their sequence positions. All existing machine-learning techniques relied on a sliding window of 10-20 amino acid residues to capture some 'short to intermediate' non-local interactions. Here, we employed Long Short-Term Memory (LSTM) Bidirectional Recurrent Neural Networks (BRNNs) which are capable of capturing long range interactions without using a window. We showed that the application of LSTM-BRNN to the prediction of protein structural properties makes the most significant improvement for residues with the most long-range contacts (|i-j| >19) over a previous window-based, deep-learning method SPIDER2. Capturing long-range interactions allows the accuracy of three-state secondary structure prediction to reach 84% and the correlation coefficient between predicted and actual solvent accessible surface areas to reach 0.80, plus a reduction of 5%, 10%, 5% and 10% in the mean absolute error for backbone ϕ , ψ , θ and τ angles, respectively, from SPIDER2. More significantly, 27% of 182724 40-residue models directly constructed from predicted C α atom-based θ and τ have similar structures to their corresponding native structures (6Å RMSD or less), which is 3% better than models built by ϕ and ψ angles. We expect the method to be useful for assisting protein structure and function prediction. The method is available as a SPIDER3 server and standalone package at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au or yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email

  1. An investigation of whether factors associated with short-term attrition change or persist over ten years: data from the Medical Research Council Cognitive Function and Ageing Study (MRC CFAS

    Directory of Open Access Journals (Sweden)

    Chatfield Mark

    2006-07-01

    Full Text Available Abstract Background Factors associated with the loss of participants in long-term longitudinal studies of ageing, due to refusal or moves, have been discussed less than those with short term follow-up. Methods In a population-based study of cognition and ageing (the Medical Research Council Cognitive Function and Ageing Study (MRC CFAS, factors associated with dropout due to refusal and moving in the first follow-up period (over two years are compared with factors associated with dropout over ten years. Participants at 10-year follow-up are compared with their age-standardised baseline contemporaries. Results Some consistent trends are found over the longer term. Refusers tended to have poorer cognition, less years of education, not have a family history of dementia and be women. Characteristics of people who moved differed between waves, but the oldest and people in worse health moved more. When surviving and responding individuals at ten years are compared with those of the same age at baseline many differences are found. Individuals of lower social class, education, cognitive ability, in residential care, with sight/hearing problems and poor/fair self-reported health are less likely to be seen after 10 years of follow-up. Individuals report more health problems when they participate in multiple interviews. Conclusion The characteristics of refusers in the longer term are similar to those refusing to participate over the shorter term. Long-term follow-up studies will under represent the disadvantaged and disabled but represent full health status of participating individuals better. There are advantages and disadvantages to both short-term and long-term follow-up.

  2. The pedagogy of Short-Term Study-Abroad Programs

    Directory of Open Access Journals (Sweden)

    Jude Gonsalvez

    2013-10-01

    Full Text Available This paper focuses on establishing guidelines on the pedagogy of short term study abroad programs. This study follows 33 students who participated in a short-term study-abroad program to India with the researcher from 2006 through 2011. The study relies heavily on the student reflections and expressions as they experienced them. It is qualitative in nature. Focus groups were the main method of data collection, where participants were invited to reflect, express, and share their experiences with one another. This provided an opportunity for the participants to come together, relive their experiences, and help provide information as to how and what type of an influence this short-term study-abroad program provided.

  3. Short-term memory across eye blinks.

    Science.gov (United States)

    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.

  4. Combination of Mean Platelet Volume/Platelet Count Ratio and the APACHE II Score Better Predicts the Short-Term Outcome in Patients with Acute Kidney Injury Receiving Continuous Renal Replacement Therapy.

    Science.gov (United States)

    Li, Junhui; Li, Yingchuan; Sheng, Xiaohua; Wang, Feng; Cheng, Dongsheng; Jian, Guihua; Li, Yongguang; Feng, Liang; Wang, Niansong

    2018-03-29

    Both the Acute physiology and Chronic Health Evaluation (APACHE II) score and mean platelet volume/platelet count Ratio (MPR) can independently predict adverse outcomes in critically ill patients. This study was aimed to investigate whether the combination of them could have a better performance in predicting prognosis of patients with acute kidney injury (AKI) who received continuous renal replacement therapy (CRRT). Two hundred twenty-three patients with AKI who underwent CRRT between January 2009 and December 2014 in a Chinese university hospital were enrolled. They were divided into survivals group and non-survivals group based on the situation at discharge. Receiver Operating Characteristic (ROC) curve was used for MPR and APACHE II score, and to determine the optimal cut-off value of MPR for in-hospital mortality. Factors associated with mortality were identified by univariate and multivariate logistic regression analysis. The mean age of the patients was 61.4 years, and the overall in-hospital mortality was 48.4%. Acute cardiorenal syndrome (ACRS) was the most common cause of AKI. The optimal cut-off value of MPR for mortality was 0.099 with an area under the ROC curve (AUC) of 0.636. The AUC increased to 0.851 with the addition of the APACHE II score. The mortality of patients with of MPR > 0.099 was 56.4%, which was significantly higher than that of the control group with of ≤ 0.099 (39.6%, P= 0.012). Logistic regression analysis showed that average number of organ failure (OR = 2.372), APACHE II score (OR = 1.187), age (OR = 1.028) and vasopressors administration (OR = 38.130) were significantly associated with poor prognosis. Severity of illness was significantly associated with prognosis of patients with AKI. The combination of MPR and APACHE II score may be helpful in predicting the short-term outcome of AKI. © 2018 The Author(s). Published by S. Karger AG, Basel.

  5. 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.

    Science.gov (United States)

    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 69°, total tenderness score 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.

  6. Combination of Mean Platelet Volume/Platelet Count Ratio and the APACHE II Score Better Predicts the Short-Term Outcome in Patients with Acute Kidney Injury Receiving Continuous Renal Replacement Therapy

    Directory of Open Access Journals (Sweden)

    Junhui Li

    2018-03-01

    Full Text Available Background/Aims: Both the Acute physiology and Chronic Health Evaluation (APACHE II score and mean platelet volume/platelet count Ratio (MPR can independently predict adverse outcomes in critically ill patients. This study was aimed to investigate whether the combination of them could have a better performance in predicting prognosis of patients with acute kidney injury (AKI who received continuous renal replacement therapy (CRRT. Methods: Two hundred twenty-three patients with AKI who underwent CRRT between January 2009 and December 2014 in a Chinese university hospital were enrolled. They were divided into survivals group and non-survivals group based on the situation at discharge. Receiver Operating Characteristic (ROC curve was used for MPR and APACHE II score, and to determine the optimal cut-off value of MPR for in-hospital mortality. Factors associated with mortality were identified by univariate and multivariate logistic regression analysis. Results: The mean age of the patients was 61.4 years, and the overall in-hospital mortality was 48.4%. Acute cardiorenal syndrome (ACRS was the most common cause of AKI. The optimal cut-off value of MPR for mortality was 0.099 with an area under the ROC curve (AUC of 0.636. The AUC increased to 0.851 with the addition of the APACHE II score. The mortality of patients with of MPR > 0.099 was 56.4%, which was significantly higher than that of the control group with of ≤ 0.099 (39.6%, P= 0.012. Logistic regression analysis showed that average number of organ failure (OR = 2.372, APACHE II score (OR = 1.187, age (OR = 1.028 and vasopressors administration (OR = 38.130 were significantly associated with poor prognosis. Conclusion: Severity of illness was significantly associated with prognosis of patients with AKI. The combination of MPR and APACHE II score may be helpful in predicting the short-term outcome of AKI.

  7. Dynamic visual noise reduces confidence in short-term memory for visual information.

    Science.gov (United States)

    Kemps, Eva; Andrade, Jackie

    2012-05-01

    Previous research has shown effects of the visual interference technique, dynamic visual noise (DVN), on visual imagery, but not on visual short-term memory, unless retention of precise visual detail is required. This study tested the prediction that DVN does also affect retention of gross visual information, specifically by reducing confidence. Participants performed a matrix pattern memory task with three retention interval interference conditions (DVN, static visual noise and no interference control) that varied from trial to trial. At recall, participants indicated whether or not they were sure of their responses. As in previous research, DVN did not impair recall accuracy or latency on the task, but it did reduce recall confidence relative to static visual noise and no interference. We conclude that DVN does distort visual representations in short-term memory, but standard coarse-grained recall measures are insensitive to these distortions.

  8. Qualitative similarities in the visual short-term memory of pigeons and people

    OpenAIRE

    Gibson, Brett; Wasserman, Edward; Luck, Steven J.

    2011-01-01

    Visual short-term memory plays a key role in guiding behavior, and individual differences in visual short-term memory capacity are strongly predictive of higher cognitive abilities. To provide a broader evolutionary context for understanding this memory system, we directly compared the behavior of pigeons and humans on a change detection task. Although pigeons had a lower storage capacity and a higher lapse rate than humans, both species stored multiple items in short-term memory and conforme...

  9. Improving creativity performance by short-term meditation

    Science.gov (United States)

    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

  10. Grey-identification model based wind power generation short-term prediction%基于灰色-辨识模型的风电功率短期预测

    Institute of Scientific and Technical Information of China (English)

    2013-01-01

      为了准确预测风电机组的输出功率,针对实际风场,给出一种基于灰色 GM(1,1)模型和辨识模型的风电功率预测建模方法,采用残差修正的方法对风速进行预测,得出准确的风速预测序列。同时为了提高风电功率预测的精度,引入 FIR-MA迭代辨识模型,从分段函数的角度对风电场实际风速-风电功率曲线进行拟合,取得合适的 FIR-MA 模型。利用该模型对额定容量为850 kW 的风电机组进行建模,采用平均绝对误差和均方根误差,以及单点误差作为评价指标,与风电场的实测数据进行比较分析。仿真结果表明,基于灰色-辨识模型的风电机组输出功率预测方法是有效和实用的,该模型能够很好地预测风电机组的实时输出功率,从而提高风电场输出功率预测的精确性。%To predict the output power of wind turbine accurately, based on the GM (1, 1) model and the identification method, a wind power generation short-term prediction method is presented for the real wind farm. The revision of residual error is applied to forecast the wind speed and get the accurate predicted wind speed series. Then, in order to increase the prediction precision of wind power, the FIR-MA iterative identification model is adopted to fit the real relationship between sequential wind speed and wind power and get the proper FIR-MA model. By modeling the wind turbine whose rated capacity is 850 kW, this paper compares the predicted wind generation power with the observed data using mean absolute percentage error, root mean square error and single point error as its evaluation indexes. The simulation shows the effectiveness and the practical applicability of the presented method, which can predict the real time generation power of wind turbineness and raise the accuracy of the wind power prediction. Finally, the simulation using the actual data from wind farm in China proves the efficiency of the

  11. An information capacity limitation of visual short-term memory.

    Science.gov (United States)

    Sewell, David K; Lilburn, Simon D; Smith, Philip L

    2014-12-01

    Research suggests that visual short-term memory (VSTM) has both an item capacity, of around 4 items, and an information capacity. We characterize the information capacity limits of VSTM using a task in which observers discriminated the orientation of a single probed item in displays consisting of 1, 2, 3, or 4 orthogonally oriented Gabor patch stimuli that were presented in noise for 50 ms, 100 ms, 150 ms, or 200 ms. The observed capacity limitations are well described by a sample-size model, which predicts invariance of ∑(i)(d'(i))² for displays of different sizes and linearity of (d'(i))² for displays of different durations. Performance was the same for simultaneous and sequentially presented displays, which implicates VSTM as the locus of the observed invariance and rules out explanations that ascribe it to divided attention or stimulus encoding. The invariance of ∑(i)(d'(i))² is predicted by the competitive interaction theory of Smith and Sewell (2013), which attributes it to the normalization of VSTM traces strengths arising from competition among stimuli entering VSTM. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  12. Visual Short-Term Memory Complexity

    DEFF Research Database (Denmark)

    Sørensen, Thomas Alrik

    Several recent studies have explored the nature and limits of visual short-term memory (VSTM) (e.g. Luck & Vogel, 1997). A general VSTM capacity limit of about 3 to 4 letters has been found, thus confirming results from earlier studies (e.g. Cattell, 1885; Sperling, 1960). However, Alvarez...

  13. Short-term forecasting model for aggregated regional hydropower generation

    International Nuclear Information System (INIS)

    Monteiro, Claudio; Ramirez-Rosado, Ignacio J.; Fernandez-Jimenez, L. Alfredo

    2014-01-01

    Highlights: • Original short-term forecasting model for the hourly hydropower generation. • The use of NWP forecasts allows horizons of several days. • New variable to represent the capacity level for generating hydroelectric energy. • The proposed model significantly outperforms the persistence model. - Abstract: This paper presents an original short-term forecasting model of the hourly electric power production for aggregated regional hydropower generation. The inputs of the model are previously recorded values of the aggregated hourly production of hydropower plants and hourly water precipitation forecasts using Numerical Weather Prediction tools, as well as other hourly data (load demand and wind generation). This model is composed of three modules: the first one gives the prediction of the “monthly” hourly power production of the hydropower plants; the second module gives the prediction of hourly power deviation values, which are added to that obtained by the first module to achieve the final forecast of the hourly hydropower generation; the third module allows a periodic adjustment of the prediction of the first module to improve its BIAS error. The model has been applied successfully to the real-life case study of the short-term forecasting of the aggregated hydropower generation in Spain and Portugal (Iberian Peninsula Power System), achieving satisfactory results for the next-day forecasts. The model can be valuable for agents involved in electricity markets and useful for power system operations

  14. Decay uncovered in nonverbal short-term memory.

    Science.gov (United States)

    Mercer, Tom; McKeown, Denis

    2014-02-01

    Decay theory posits that memory traces gradually fade away over the passage of time unless they are actively rehearsed. Much recent work exploring verbal short-term memory has challenged this theory, but there does appear to be evidence for trace decay in nonverbal auditory short-term memory. Numerous discrimination studies have reported a performance decline as the interval separating two tones is increased, consistent with a decay process. However, most of this tone comparison research can be explained in other ways, without reference to decay, and these alternative accounts were tested in the present study. In Experiment 1, signals were employed toward the end of extended retention intervals to ensure that listeners were alert to the presence and frequency content of the memoranda. In Experiment 2, a mask stimulus was employed in an attempt to distinguish between a highly detailed sensory trace and a longer-lasting short-term memory, and the distinctiveness of the stimuli was varied. Despite these precautions, slow-acting trace decay was observed. It therefore appears that the mere passage of time can lead to forgetting in some forms of short-term memory.

  15. Relationship between short-term sexual strategies and sexual jealousy.

    Science.gov (United States)

    Mathes, Eugene W

    2005-02-01

    In a classic study, Buss, Larson, Westen, and Semmelroth reported that men were more distressed by the thought of a partner's sexual infidelity (sexual jealousy) and women were more distressed by the thought of a partner's emotional infidelity (emotional jealousy). Initially, Buss and his associates explained these results by suggesting that men are concerned about uncertainty of paternity, that is, the possibility of raising another man's child while believing the child is their own. However, later they explained the results in terms of men's preference for short-term sexual strategies. The purpose of this research was to test the explanation of short-term sexual strategies. Men and women subjects were instructed to imagine themselves in a relationship which was either short-term (primarily sexual) or long-term (involving commitment) and then respond to Buss's jealousy items. It was hypothesized that, when both men and women imagined a short-term relationship, they would be more threatened by a partner's sexual infidelity, and, when they imagined a long-term relationship, they would be more threatened by a partner's emotional infidelity. Support was found for this hypothesis.

  16. Association between Early Attention-Deficit/Hyperactivity Symptoms and Current Verbal and Visuo-Spatial Short-Term Memory

    Science.gov (United States)

    Gau, Susan Shur-Fen; Chiang, Huey-Ling

    2013-01-01

    Deficits in short-term memory are common in adolescents with attention-deficit/hyperactivity disorder (ADHD), but their current ADHD symptoms cannot well predict their short-term performance. Taking a developmental perspective, we wanted to clarify the association between ADHD symptoms at early childhood and short-term memory in late childhood and…

  17. DYNAMICS OF THE ANXIETY DISORDERS IN THE COURSE OF SHORT-TERM PSYCHOTHERAPY

    Directory of Open Access Journals (Sweden)

    T.N. Hmylova

    2008-06-01

    Full Text Available The tendency of psychotherapy modern concepts referring to the short-term forms having been taken into account, we carried out the research aimed at the study of short-term form personality-oriented psychotherapy effect on the anxiety disorder dynamics. 103 patients with neurotic disorders were examined in the neurosis and psychotherapy department of the Bekhterev Psychoneurological Research Institute. The findings revealed the situational and personal anxiety level to be objectively decreased in the short-term group psychotherapy course. The short-term group psychotherapy was proved to bean effective method in anxiety disorders treatment considering indications and limitations.

  18. How Emotional Pictures Influence Visuospatial Binding in Short-Term Memory in Ageing and Alzheimer's Disease?

    Science.gov (United States)

    Borg, Celine; Leroy, Nicolas; Favre, Emilie; Laurent, Bernard; Thomas-Anterion, Catherine

    2011-01-01

    The present study examines the prediction that emotion can facilitate short-term memory. Nevertheless, emotion also recruits attention to process information, thereby disrupting short-term memory when tasks involve high attentional resources. In this way, we aimed to determine whether there is a differential influence of emotional information on…

  19. Short-term LNG-markets

    International Nuclear Information System (INIS)

    Eldegard, Tom; Lund, Arne-Christian; Miltersen, Kristian; Rud, Linda

    2005-01-01

    The global Liquefied Natural Gas (LNG) industry has experienced substantial growth in the past decades. In the traditional trade patterns of LNG the product has typically been handled within a dedicated chain of plants and vessels fully committed by long term contracts or common ownership, providing risk sharing of large investments in a non-liquid market. Increasing gas prices and substantial cost reductions in all parts of the LNG chain have made LNG projects viable even if only part of the capacity is secured by long-term contracts, opening for more flexible trade of the remainder. Increasing gas demand, especially in power generation, combined with cost reductions in the cost of LNG terminals, open new markets for LNG. For the LNG supplier, the flexibility of shifting volumes between regions represents an additional value. International trade in LNG has been increasing, now accounting for more than one fifth of the world's cross-border gas trade. Despite traditional vertical chain bonds, increased flexibility has contributed in fact to an increasing LNG spot trade, representing 8% of global trade in 2002. The focus of this paper is on the development of global short-term LNG markets, and their role with respect to efficiency and security of supply in European gas markets. Arbitrage opportunities arising from price differences between regional markets (such as North America versus Europe) are important impetuses for flexible short-term trade. However, the short-term LNG trade may suffer from problems related to market access, e.g. limited access to terminals and regulatory issues, as well as rigidities connected to vertical binding within the LNG chain. Important issues related to the role of short-term LNG-trade in the European gas market are: Competition, flexibility in meeting peak demand, security of supply and consequences of differences in pricing policies (oil-linked prices in Europe and spot market prices in North America). (Author)

  20. A short-term neural network memory

    Energy Technology Data Exchange (ETDEWEB)

    Morris, R.J.T.; Wong, W.S.

    1988-12-01

    Neural network memories with storage prescriptions based on Hebb's rule are known to collapse as more words are stored. By requiring that the most recently stored word be remembered precisely, a new simple short-term neutral network memory is obtained and its steady state capacity analyzed and simulated. Comparisons are drawn with Hopfield's method, the delta method of Widrow and Hoff, and the revised marginalist model of Mezard, Nadal, and Toulouse.

  1. Short-term ensemble radar rainfall forecasts for hydrological applications

    Science.gov (United States)

    Codo de Oliveira, M.; Rico-Ramirez, M. A.

    2016-12-01

    Flooding is a very common natural disaster around the world, putting local population and economy at risk. Forecasting floods several hours ahead and issuing warnings are of main importance to permit proper response in emergency situations. However, it is important to know the uncertainties related to the rainfall forecasting in order to produce more reliable forecasts. Nowcasting models (short-term rainfall forecasts) are able to produce high spatial and temporal resolution predictions that are useful in hydrological applications. Nonetheless, they are subject to uncertainties mainly due to the nowcasting model used, errors in radar rainfall estimation, temporal development of the velocity field and to the fact that precipitation processes such as growth and decay are not taken into account. In this study an ensemble generation scheme using rain gauge data as a reference to estimate radars errors is used to produce forecasts with up to 3h lead-time. The ensembles try to assess in a realistic way the residual uncertainties that remain even after correction algorithms are applied in the radar data. The ensembles produced are compered to a stochastic ensemble generator. Furthermore, the rainfall forecast output was used as an input in a hydrodynamic sewer network model and also in hydrological model for catchments of different sizes in north England. A comparative analysis was carried of how was carried out to assess how the radar uncertainties propagate into these models. The first named author is grateful to CAPES - Ciencia sem Fronteiras for funding this PhD research.

  2. Auditory short-term memory behaves like visual short-term memory.

    Directory of Open Access Journals (Sweden)

    Kristina M Visscher

    2007-03-01

    Full Text Available Are the information processing steps that support short-term sensory memory common to all the senses? Systematic, psychophysical comparison requires identical experimental paradigms and comparable stimuli, which can be challenging to obtain across modalities. Participants performed a recognition memory task with auditory and visual stimuli that were comparable in complexity and in their neural representations at early stages of cortical processing. The visual stimuli were static and moving Gaussian-windowed, oriented, sinusoidal gratings (Gabor patches; the auditory stimuli were broadband sounds whose frequency content varied sinusoidally over time (moving ripples. Parallel effects on recognition memory were seen for number of items to be remembered, retention interval, and serial position. Further, regardless of modality, predicting an item's recognizability requires taking account of (1 the probe's similarity to the remembered list items (summed similarity, and (2 the similarity between the items in memory (inter-item homogeneity. A model incorporating both these factors gives a good fit to recognition memory data for auditory as well as visual stimuli. In addition, we present the first demonstration of the orthogonality of summed similarity and inter-item homogeneity effects. These data imply that auditory and visual representations undergo very similar transformations while they are encoded and retrieved from memory.

  3. Auditory short-term memory behaves like visual short-term memory.

    Science.gov (United States)

    Visscher, Kristina M; Kaplan, Elina; Kahana, Michael J; Sekuler, Robert

    2007-03-01

    Are the information processing steps that support short-term sensory memory common to all the senses? Systematic, psychophysical comparison requires identical experimental paradigms and comparable stimuli, which can be challenging to obtain across modalities. Participants performed a recognition memory task with auditory and visual stimuli that were comparable in complexity and in their neural representations at early stages of cortical processing. The visual stimuli were static and moving Gaussian-windowed, oriented, sinusoidal gratings (Gabor patches); the auditory stimuli were broadband sounds whose frequency content varied sinusoidally over time (moving ripples). Parallel effects on recognition memory were seen for number of items to be remembered, retention interval, and serial position. Further, regardless of modality, predicting an item's recognizability requires taking account of (1) the probe's similarity to the remembered list items (summed similarity), and (2) the similarity between the items in memory (inter-item homogeneity). A model incorporating both these factors gives a good fit to recognition memory data for auditory as well as visual stimuli. In addition, we present the first demonstration of the orthogonality of summed similarity and inter-item homogeneity effects. These data imply that auditory and visual representations undergo very similar transformations while they are encoded and retrieved from memory.

  4. Determinants of Short-Term Export Performance in Pakistan

    OpenAIRE

    Subhani, Muhammad Imtiaz; Osman, Ms.Amber; Habib, Sukaina

    2010-01-01

    This research investigates the interdependency between independent (Increase of pricing strategy adaptation, Increase of export intensity, Firm's commitment to exporting, Export market development, Export market competition, Past Pricing Strategy Adaptation, Past Export Performance Satisfaction, Past Export Intensity, Export market distance) and dependent variables (i.e. Expected Short-Term Export Performance improvement) of export performance. The framework is tested via a survey through que...

  5. Impact of Obstructive Sleep Apnea on the Levels of Placental Growth Factor (PlGF and Their Value for Predicting Short-Term Adverse Outcomes in Patients with Acute Coronary Syndrome.

    Directory of Open Access Journals (Sweden)

    Antonia Barcelo

    Full Text Available Placental growth factor (PlGF induces angiogenesis and promotes tissue repair, and plasma PlGF levels change markedly during acute myocardial infarction (AMI. Currently, the impact of obstructive sleep apnea (OSA in patients with AMI is a subject of debate. Our objective was to evaluate the relationships between PlGF levels and both the severity of acute coronary syndrome (ACS and short-term outcomes after ACS in patients with and without OSA.A total of 538 consecutive patients (312 OSA patients and 226 controls admitted for ACS were included in this study. All patients underwent polygraphy in the first 72 hours after hospital admission. The severity of disease and short-term prognoses were evaluated during the hospitalization period. Plasma PlGF levels were measured using an electrochemiluminescence immunoassay.Patients with OSA were significantly older and more frequently hypertensive and had higher BMIs than those without OSA. After adjusting for age, smoking status, BMI and hypertension, PlGF levels were significantly elevated in patients with OSA compared with patients without OSA (19.9 pg/mL, interquartile range: 16.6-24.5 pg/mL; 18.5 pg/mL, interquartile range: 14.7-22.7 pg/mL; p1, even after adjustment.The results of this study show that in patients with ACS, elevated plasma levels of PlGF are associated with the presence of OSA and with adverse outcomes during short-term follow-up.ClinicalTrials.gov NCT01335087.

  6. Short-term Forecasting Tools for Agricultural Nutrient Management.

    Science.gov (United States)

    Easton, Zachary M; Kleinman, Peter J A; Buda, Anthony R; Goering, Dustin; Emberston, Nichole; Reed, Seann; Drohan, Patrick J; Walter, M Todd; Guinan, Pat; Lory, John A; Sommerlot, Andrew R; Sharpley, Andrew

    2017-11-01

    The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  7. A neuromorphic circuit mimicking biological short-term memory.

    Science.gov (United States)

    Barzegarjalali, Saeid; Parker, Alice C

    2016-08-01

    Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).

  8. Is visual short-term memory depthful?

    Science.gov (United States)

    Reeves, Adam; Lei, Quan

    2014-03-01

    Does visual short-term memory (VSTM) depend on depth, as it might be if information was stored in more than one depth layer? Depth is critical in natural viewing and might be expected to affect retention, but whether this is so is currently unknown. Cued partial reports of letter arrays (Sperling, 1960) were measured up to 700 ms after display termination. Adding stereoscopic depth hardly affected VSTM capacity or decay inferred from total errors. The pattern of transposition errors (letters reported from an uncued row) was almost independent of depth and cue delay. We conclude that VSTM is effectively two-dimensional. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Reinsurance by short-term reinsurers in South Africa

    Directory of Open Access Journals (Sweden)

    Fernhout, C. L. R.

    2016-02-01

    Full Text Available The short-term reinsurance process usually involves three parties, namely the insurer, the reinsurer and the original policyholder, as the insurer cedes a part of the covered risk of the policyholder to the reinsurer. This research however addresses the perceptions of reinsurers regarding their reinsurance activities, where the reinsurer sells reinsurance to other insurance entities (viz. insurers and reinsurers, as well as buys reinsurance from other insurance entities. The crux of short-term reinsurance is therefore mutually loss sharing between the various insurance entities. The objective of this research focuses on the improvement of financial decision-making regarding the reinsurance operations of the reinsurers. To achieve this objective a literature study was undertaken to provide adequate background to compile a questionnaire for the empirical survey. The primary study embodies the perceptions of the South African short-term reinsurers regarding the following aspects: the various reasons why reinsurance occurs; the contracts / methods of reinsurance; the bases / forms of reinsurance; and the factors which determine the retention levels of a reinsurer. South Africa is classified as a developing economy, is a member of the BRICS countries and has an emerging market economy. The empirical results should therefore also be valuable to other countries which are classified similarly

  10. Short term depression unmasks the ghost frequency.

    Directory of Open Access Journals (Sweden)

    Tjeerd V Olde Scheper

    Full Text Available Short Term Plasticity (STP has been shown to exist extensively in synapses throughout the brain. Its function is more or less clear in the sense that it alters the probability of synaptic transmission at short time scales. However, it is still unclear what effect STP has on the dynamics of neural networks. We show, using a novel dynamic STP model, that Short Term Depression (STD can affect the phase of frequency coded input such that small networks can perform temporal signal summation and determination with high accuracy. We show that this property of STD can readily solve the problem of the ghost frequency, the perceived pitch of a harmonic complex in absence of the base frequency. Additionally, we demonstrate that this property can explain dynamics in larger networks. By means of two models, one of chopper neurons in the Ventral Cochlear Nucleus and one of a cortical microcircuit with inhibitory Martinotti neurons, it is shown that the dynamics in these microcircuits can reliably be reproduced using STP. Our model of STP gives important insights into the potential roles of STP in self-regulation of cortical activity and long-range afferent input in neuronal microcircuits.

  11. Short-term energy outlook, July 1998

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-07-01

    The Energy Information Administration (EIA) prepares The Short-Term Energy Outlook (energy supply, demand, and price projections) monthly for distribution on the internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. In addition, printed versions of the report are available to subscribers in January, April, July and October. The forecast period for this issue of the Outlook extends from July 1998 through December 1999. Values for second quarter of 1998 data, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the July 1998 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. 28 figs., 19 tabs.

  12. Short-term energy outlook, January 1999

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-01-01

    The Energy Information Administration (EIA) prepares the Short-Term Energy Outlook (energy supply, demand, and price projections) monthly. The forecast period for this issue of the Outlook extends from January 1999 through December 2000. Data values for the fourth quarter 1998, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the January 1999 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 28 figs., 19 tabs.

  13. Measuring Short-term Energy Security

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-07-01

    Ensuring energy security has been at the centre of the IEA mission since its inception, following the oil crises of the early 1970s. While the security of oil supplies remains important, contemporary energy security policies must address all energy sources and cover a comprehensive range of natural, economic and political risks that affect energy sources, infrastructures and services. In response to this challenge, the IEA is currently developing a Model Of Short-term Energy Security (MOSES) to evaluate the energy security risks and resilience capacities of its member countries. The current version of MOSES covers short-term security of supply for primary energy sources and secondary fuels among IEA countries. It also lays the foundation for analysis of vulnerabilities of electricity and end-use energy sectors. MOSES contains a novel approach to analysing energy security, which can be used to identify energy security priorities, as a starting point for national energy security assessments and to track the evolution of a country's energy security profile. By grouping together countries with similar 'energy security profiles', MOSES depicts the energy security landscape of IEA countries. By extending the MOSES methodology to electricity security and energy services in the future, the IEA aims to develop a comprehensive policy-relevant perspective on global energy security. This Brochure provides and overview of the analysis and results. Readers interested in an in-depth discussion of methodology are referred to the MOSES Working Paper.

  14. Qualitative similarities in the visual short-term memory of pigeons and people.

    Science.gov (United States)

    Gibson, Brett; Wasserman, Edward; Luck, Steven J

    2011-10-01

    Visual short-term memory plays a key role in guiding behavior, and individual differences in visual short-term memory capacity are strongly predictive of higher cognitive abilities. To provide a broader evolutionary context for understanding this memory system, we directly compared the behavior of pigeons and humans on a change detection task. Although pigeons had a lower storage capacity and a higher lapse rate than humans, both species stored multiple items in short-term memory and conformed to the same basic performance model. Thus, despite their very different evolutionary histories and neural architectures, pigeons and humans have functionally similar visual short-term memory systems, suggesting that the functional properties of visual short-term memory are subject to similar selective pressures across these distant species.

  15. Short Term Airing by Natural Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per; Perino, M.

    2010-01-01

    The need to improve the energy efficiency of buildings requires new and more efficient ventilation systems. It has been demonstrated that innovative operating concepts that make use of natural ventilation seem to be more appreciated by occupants. Among the available ventilation strategies...... that are currently available, buoyancy driven, single-sided natural ventilation has proved to be very effective and can provide high air change rates for temperature and Indoor Air Quality (IAQ) control. However, to promote a wider distribution of these systems an improvement in the knowledge of their working...... airflow rate, ventilation efficiency, thermal comfort and dynamic temperature conditions. A suitable laboratory test rig was developed to perform extensive experimental analyses of the phenomenon under controlled and repeatable conditions. The results showed that short-term window airing is very effective...

  16. Short-term forecasting of internal migration.

    Science.gov (United States)

    Frees, E W

    1993-11-01

    A new methodological approach to the forecasting of short-term trends in internal migration in the United States is introduced. "Panel-data (or longitudinal-data) models are used to represent the relationship between destination-specific out-migration and several explanatory variables. The introduction of this methodology into the migration literature is possible because of some new and improved databases developed by the U.S. Bureau of the Census.... Data from the Bureau of Economic Analysis are used to investigate the incorporation of exogenous factors as variables in the model." The exogenous factors considered include employment and unemployment, income, population size of state, and distance between states. The author concludes that "when one...includes additional parameters that are estimable in longitudinal-data models, it turns out that there is little additional information in the exogenous factors that is useful for forecasting." excerpt

  17. Short-term plasticity in auditory cognition.

    Science.gov (United States)

    Jääskeläinen, Iiro P; Ahveninen, Jyrki; Belliveau, John W; Raij, Tommi; Sams, Mikko

    2007-12-01

    Converging lines of evidence suggest that auditory system short-term plasticity can enable several perceptual and cognitive functions that have been previously considered as relatively distinct phenomena. Here we review recent findings suggesting that auditory stimulation, auditory selective attention and cross-modal effects of visual stimulation each cause transient excitatory and (surround) inhibitory modulations in the auditory cortex. These modulations might adaptively tune hierarchically organized sound feature maps of the auditory cortex (e.g. tonotopy), thus filtering relevant sounds during rapidly changing environmental and task demands. This could support auditory sensory memory, pre-attentive detection of sound novelty, enhanced perception during selective attention, influence of visual processing on auditory perception and longer-term plastic changes associated with perceptual learning.

  18. A fuzzy inference model for short-term load forecasting

    International Nuclear Information System (INIS)

    Mamlook, Rustum; Badran, Omar; Abdulhadi, Emad

    2009-01-01

    This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling and unit commitment decisions, and therefore precise load forecasting plays an important role in reducing the generation cost and the spinning reserve capacity. Short-term electricity demand forecasting (i.e., the prediction of hourly loads (demand)) is one of the most important tools by which an electric utility/company plans, dispatches the loading of generating units in order to meet system demand. The accuracy of the dispatching system, which is derived from the accuracy of the forecasting algorithm used, will determine the economics of the operation of the power system. The inaccuracy or large error in the forecast simply means that load matching is not optimized and consequently the generation and transmission systems are not being operated in an efficient manner. In the present study, a proposed methodology has been introduced to decrease the forecasted error and the processing time by using fuzzy logic controller on an hourly base. Therefore, it predicts the effect of different conditional parameters (i.e., weather, time, historical data, and random disturbances) on load forecasting in terms of fuzzy sets during the generation process. These parameters are chosen with respect to their priority and importance. The forecasted values obtained by fuzzy method were compared with the conventionally forecasted ones. The results showed that the STLF of the fuzzy implementation have more accuracy and better outcomes

  19. Evaluation of Short Term Memory Span Function In Children

    OpenAIRE

    Barış ERGÜL; Arzu ALTIN YAVUZ; Ebru GÜNDOĞAN AŞIK

    2016-01-01

    Although details of the information encoded in the short-term memory where it is stored temporarily be recorded in the working memory in the next stage. Repeating the information mentally makes it remain in memory for a long time. Studies investigating the relationship between short-term memory and reading skills that are carried out to examine the relationship between short-term memory processes and reading comprehension. In this study information coming to short-term memory and the factors ...

  20. Hybrid ARIMAX quantile regression method for forecasting short term electricity consumption in east java

    Science.gov (United States)

    Prastuti, M.; Suhartono; Salehah, NA

    2018-04-01

    The need for energy supply, especially for electricity in Indonesia has been increasing in the last past years. Furthermore, the high electricity usage by people at different times leads to the occurrence of heteroscedasticity issue. Estimate the electricity supply that could fulfilled the community’s need is very important, but the heteroscedasticity issue often made electricity forecasting hard to be done. An accurate forecast of electricity consumptions is one of the key challenges for energy provider to make better resources and service planning and also take control actions in order to balance the electricity supply and demand for community. In this paper, hybrid ARIMAX Quantile Regression (ARIMAX-QR) approach was proposed to predict the short-term electricity consumption in East Java. This method will also be compared to time series regression using RMSE, MAPE, and MdAPE criteria. The data used in this research was the electricity consumption per half-an-hour data during the period of September 2015 to April 2016. The results show that the proposed approach can be a competitive alternative to forecast short-term electricity in East Java. ARIMAX-QR using lag values and dummy variables as predictors yield more accurate prediction in both in-sample and out-sample data. Moreover, both time series regression and ARIMAX-QR methods with addition of lag values as predictor could capture accurately the patterns in the data. Hence, it produces better predictions compared to the models that not use additional lag variables.

  1. Short-term memory, executive control, and children's route learning

    OpenAIRE

    Purser, H. R.; Farran, E. K.; Courbois, Y.; Lemahieu, A.; Mellier, D.; Sockeel, P.; Blades, M.

    2012-01-01

    The aim of this study was to investigate route-learning ability in 67 children aged 5 to 11years and to relate route-learning performance to the components of Baddeley's model of working memory. Children carried out tasks that included measures of verbal and visuospatial short-term memory and executive control and also measures of verbal and visuospatial long-term memory; the route-learning task was conducted using a maze in a virtual environment. In contrast to previous research, correlation...

  2. Short-Term Saved Leave Scheme

    CERN Multimedia

    2007-01-01

    As announced at the meeting of the Standing Concertation Committee (SCC) on 26 June 2007 and in http://Bulletin No. 28/2007, the existing Saved Leave Scheme will be discontinued as of 31 December 2007. Staff participating in the Scheme will shortly receive a contract amendment stipulating the end of financial contributions compensated by save leave. Leave already accumulated on saved leave accounts can continue to be taken in accordance with the rules applicable to the current scheme. A new system of saved leave will enter into force on 1 January 2008 and will be the subject of a new implementation procedure entitled "Short-term saved leave scheme" dated 1 January 2008. At its meeting on 4 December 2007, the SCC agreed to recommend the Director-General to approve this procedure, which can be consulted on the HR Department’s website at the following address: https://cern.ch/hr-services/services-Ben/sls_shortterm.asp All staff wishing to participate in the new scheme a...

  3. Short-Term Saved Leave Scheme

    CERN Multimedia

    HR Department

    2007-01-01

    As announced at the meeting of the Standing Concertation Committee (SCC) on 26 June 2007 and in http://Bulletin No. 28/2007, the existing Saved Leave Scheme will be discontinued as of 31 December 2007. Staff participating in the Scheme will shortly receive a contract amendment stipulating the end of financial contributions compensated by save leave. Leave already accumulated on saved leave accounts can continue to be taken in accordance with the rules applicable to the current scheme. A new system of saved leave will enter into force on 1 January 2008 and will be the subject of a new im-plementation procedure entitled "Short-term saved leave scheme" dated 1 January 2008. At its meeting on 4 December 2007, the SCC agreed to recommend the Director-General to approve this procedure, which can be consulted on the HR Department’s website at the following address: https://cern.ch/hr-services/services-Ben/sls_shortterm.asp All staff wishing to participate in the new scheme ...

  4. Short-term energy outlook, April 1999

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-04-01

    The forecast period for this issue of the Outlook extends from April 1999 through December 2000. Data values for the first quarter 1999, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the April 1999 version of the Short-Term Integrated forecasting system (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 25 figs., 19 tabs.

  5. Continuity of Landsat observations: Short term considerations

    Science.gov (United States)

    Wulder, Michael A.; White, Joanne C.; Masek, Jeffery G.; Dwyer, John L.; Roy, David P.

    2011-01-01

    As of writing in mid-2010, both Landsat-5 and -7 continue to function, with sufficient fuel to enable data collection until the launch of the Landsat Data Continuity Mission (LDCM) scheduled for December of 2012. Failure of one or both of Landsat-5 or -7 may result in a lack of Landsat data for a period of time until the 2012 launch. Although the potential risk of a component failure increases the longer the sensor's design life is exceeded, the possible gap in Landsat data acquisition is reduced with each passing day and the risk of Landsat imagery being unavailable diminishes for all except a handful of applications that are particularly data demanding. Advances in Landsat data compositing and fusion are providing opportunities to address issues associated with Landsat-7 SLC-off imagery and to mitigate a potential acquisition gap through the integration of imagery from different sensors. The latter will likely also provide short-term, regional solutions to application-specific needs for the continuity of Landsat-like observations. Our goal in this communication is not to minimize the community's concerns regarding a gap in Landsat observations, but rather to clarify how the current situation has evolved and provide an up-to-date understanding of the circumstances, implications, and mitigation options related to a potential gap in the Landsat data record.

  6. Short-term natural gas consumption forecasting

    International Nuclear Information System (INIS)

    Potocnik, P.; Govekar, E.; Grabec, I.

    2007-01-01

    Energy forecasting requirements for Slovenia's natural gas market were investigated along with the cycles of natural gas consumption. This paper presented a short-term natural gas forecasting approach where the daily, weekly and yearly gas consumption were analyzed and the information obtained was incorporated into the forecasting model for hourly forecasting for the next day. The natural gas market depends on forecasting in order to optimize the leasing of storage capacities. As such, natural gas distribution companies have an economic incentive to accurately forecast their future gas consumption. The authors proposed a forecasting model with the following properties: two submodels for the winter and summer seasons; input variables including past consumption data, weather data, weather forecasts and basic cycle indexes; and, a hierarchical forecasting structure in which a daily model was used as the basis, with the hourly forecast obtained by modeling the relative daily profile. This proposed method was illustrated by a forecasting example for Slovenia's natural gas market. 11 refs., 11 figs

  7. Why do short term workers have high mortality?

    DEFF Research Database (Denmark)

    Kolstad, Henrik; Olsen, Jørn

    1999-01-01

    or violence, the rate ratios for short term employment were 2.30 (95% Cl 1.74-3.06) and 1.86 (95% Cl 1.35-2.56), respectively. An unhealthy lifestyle may also be a determinant of short term employment. While it is possible in principle to adjust for lifestyle factors if proper data are collected, the health......Increased mortality is often reported among workers in short term employment. This may indicate either a health-related selection process or the presence of different lifestyle or social conditions among short term workers. The authors studied these two aspects of short term employment among 16...

  8. Social Welfare and the Psychology of Food Sharing: Short-Term Hunger Increases Support for Social Welfare

    DEFF Research Database (Denmark)

    Petersen, Michael Bang; Aarøe, Lene; Jensen, Niels Holm

    2014-01-01

    Do politically irrelevant events influence important policy opinions? Previous research on social welfare attitudes has emphasized the role of political factors such as economic self-interest and ideology. Here, we demonstrate that attitudes to social welfare are also influenced by short-term flu......—we consistently find that hungry individuals act in a greedier manner but describe themselves as more cooperative and express greater support for social welfare.......Do politically irrelevant events influence important policy opinions? Previous research on social welfare attitudes has emphasized the role of political factors such as economic self-interest and ideology. Here, we demonstrate that attitudes to social welfare are also influenced by short......-term fluctuations in hunger. Using theories in evolutionary psychology, we predict that hungry individuals will be greedier and take more resources from others while also attempting to induce others to share by signaling cooperative intentions and expressing support for sharing, including evolutionarily novel forms...

  9. Short term benefits for laparoscopic colorectal resection.

    Science.gov (United States)

    Schwenk, W; Haase, O; Neudecker, J; Müller, J M

    2005-07-20

    Colorectal resections are common surgical procedures all over the world. Laparoscopic colorectal surgery is technically feasible in a considerable amount of patients under elective conditions. Several short-term benefits of the laparoscopic approach to colorectal resection (less pain, less morbidity, improved reconvalescence and better quality of life) have been proposed. This review compares laparoscopic and conventional colorectal resection with regards to possible benefits of the laparoscopic method in the short-term postoperative period (up to 3 months post surgery). We searched MEDLINE, EMBASE, CancerLit, and the Cochrane Central Register of Controlled Trials for the years 1991 to 2004. We also handsearched the following journals from 1991 to 2004: British Journal of Surgery, Archives of Surgery, Annals of Surgery, Surgery, World Journal of Surgery, Disease of Colon and Rectum, Surgical Endoscopy, International Journal of Colorectal Disease, Langenbeck's Archives of Surgery, Der Chirurg, Zentralblatt für Chirurgie, Aktuelle Chirurgie/Viszeralchirurgie. Handsearch of abstracts from the following society meetings from 1991 to 2004: American College of Surgeons, American Society of Colorectal Surgeons, Royal Society of Surgeons, British Assocation of Coloproctology, Surgical Association of Endoscopic Surgeons, European Association of Endoscopic Surgeons, Asian Society of Endoscopic Surgeons. All randomised-controlled trial were included regardless of the language of publication. No- or pseudorandomised trials as well as studies that followed patient's preferences towards one of the two interventions were excluded, but listed separately. RCT presented as only an abstract were excluded. Results were extracted from papers by three observers independently on a predefined data sheet. Disagreements were solved by discussion. 'REVMAN 4.2' was used for statistical analysis. Mean differences (95% confidence intervals) were used for analysing continuous variables. If

  10. Order recall in verbal short-term memory: The role of semantic networks.

    Science.gov (United States)

    Poirier, Marie; Saint-Aubin, Jean; Mair, Ali; Tehan, Gerry; Tolan, Anne

    2015-04-01

    In their recent article, Acheson, MacDonald, and Postle (Journal of Experimental Psychology: Learning, Memory, and Cognition 37:44-59, 2011) made an important but controversial suggestion: They hypothesized that (a) semantic information has an effect on order information in short-term memory (STM) and (b) order recall in STM is based on the level of activation of items within the relevant lexico-semantic long-term memory (LTM) network. However, verbal STM research has typically led to the conclusion that factors such as semantic category have a large effect on the number of correctly recalled items, but little or no impact on order recall (Poirier & Saint-Aubin, Quarterly Journal of Experimental Psychology 48A:384-404, 1995; Saint-Aubin, Ouellette, & Poirier, Psychonomic Bulletin & Review 12:171-177, 2005; Tse, Memory 17:874-891, 2009). Moreover, most formal models of short-term order memory currently suggest a separate mechanism for order coding-that is, one that is separate from item representation and not associated with LTM lexico-semantic networks. Both of the experiments reported here tested the predictions that we derived from Acheson et al. The findings show that, as predicted, manipulations aiming to affect the activation of item representations significantly impacted order memory.

  11. Short-term contracts: Descending the career ladder

    Science.gov (United States)

    Griffin, Elizabeth

    2002-12-01

    Elizabeth Griffin brings a personal insight to the hurdles that women seeking a scientific career face, arguing that the only gender differences are those of attitude, tradition and style. The policy of employing some but not all academic researchers through short-term contracts is highly divisive, in that it creates a two-tier system not only of opportunities and expectations but also of personal worth and value. Far more women than men are trapped in these career cul-de-sacs, and a seriously large fraction is unable to stay in research until retirement. It is the employment policy that is at fault, not the potential of the researchers or the quality of their research.

  12. Hydroxychloroquine retinopathy after short-term therapy.

    Science.gov (United States)

    Phillips, Brandon N; Chun, Dal W

    2014-01-01

    To report an unusual case of hydroxychloroquine toxicity after short-term therapy. Observational case report. A 56-year-old woman presented to the Ophthalmology Clinic at Walter Reed Army Medical Center (WRAMC) with a 6-month history of gradually decreasing vision in both eyes. The patient had been taking hydroxychloroquine for the preceding 48 months for the treatment of rheumatoid arthritis. Examination of the posterior segment revealed bilateral "bull's eye" macular lesions. Fundus autofluorescence revealed hyperfluorescence of well-defined bull's eye lesions in both eyes. Optical coherence tomography revealed corresponding parafoveal atrophy with a loss of the retinal inner segment/outer segment junction. Humphrey visual field 10-2 white showed significant central and paracentral defects with a generalized depression. The patient was on a standard dose of 400 mg daily, which was above her ideal dose. The patient had no history of kidney or liver dysfunction. There were no known risk factors but there were several possible confounding factors. The patient was started on high-dose nabumetone, a nonsteroidal antiinflammatory drug, at the same time she was started on hydroxychloroquine. She also reported taking occasional ibuprofen. Retinal toxicity from chloroquine has been recognized for decades with later reports showing retinopathy from long-term hydroxychloroquine (Plaquenil) use for the treatment of antiinflammatory diseases. Hydroxychloroquine is now widely used and retinal toxicity is relatively uncommon. However, it can cause serious vision loss and is usually irreversible. The risk of hydroxychloroquine toxicity rises to nearly 1% with a total cumulative dose of 1,000 g, which is ∼5 years to 7 years of normal use. Toxicity is rare under this dose. For this reason, the American Academy of Ophthalmology has revised its recommendations such that annual screenings begin 5 years after therapy with hydroxychloroquine has begun unless there are known risk

  13. Short-term Power Load Forecasting Based on Balanced KNN

    Science.gov (United States)

    Lv, Xianlong; Cheng, Xingong; YanShuang; Tang, Yan-mei

    2018-03-01

    To improve the accuracy of load forecasting, a short-term load forecasting model based on balanced KNN algorithm is proposed; According to the load characteristics, the historical data of massive power load are divided into scenes by the K-means algorithm; In view of unbalanced load scenes, the balanced KNN algorithm is proposed to classify the scene accurately; The local weighted linear regression algorithm is used to fitting and predict the load; Adopting the Apache Hadoop programming framework of cloud computing, the proposed algorithm model is parallelized and improved to enhance its ability of dealing with massive and high-dimension data. The analysis of the household electricity consumption data for a residential district is done by 23-nodes cloud computing cluster, and experimental results show that the load forecasting accuracy and execution time by the proposed model are the better than those of traditional forecasting algorithm.

  14. Attention restores discrete items to visual short-term memory.

    Science.gov (United States)

    Murray, Alexandra M; Nobre, Anna C; Clark, Ian A; Cravo, André M; Stokes, Mark G

    2013-04-01

    When a memory is forgotten, is it lost forever? Our study shows that selective attention can restore forgotten items to visual short-term memory (VSTM). In our two experiments, all stimuli presented in a memory array were designed to be equally task relevant during encoding. During the retention interval, however, participants were sometimes given a cue predicting which of the memory items would be probed at the end of the delay. This shift in task relevance improved recall for that item. We found that this type of cuing improved recall for items that otherwise would have been irretrievable, providing critical evidence that attention can restore forgotten information to VSTM. Psychophysical modeling of memory performance has confirmed that restoration of information in VSTM increases the probability that the cued item is available for recall but does not improve the representational quality of the memory. We further suggest that attention can restore discrete items to VSTM.

  15. The Role of Short-term Consolidation in Memory Persistence

    OpenAIRE

    Timothy J. Ricker

    2015-01-01

    Short-term memory, often described as working memory, is one of the most fundamental information processing systems of the human brain. Short-term memory function is necessary for language, spatial navigation, problem solving, and many other daily activities. Given its importance to cognitive function, understanding the architecture of short-term memory is of crucial importance to understanding human behavior. Recent work from several laboratories investigating the entry of information into s...

  16. The left superior temporal gyrus is a shared substrate for auditory short-term memory and speech comprehension: evidence from 210 patients with stroke

    OpenAIRE

    Leff, Alexander P.; Schofield, Thomas M.; Crinion, Jennifer T.; Seghier, Mohamed L.; Grogan, Alice; Green, David W.; Price, Cathy J.

    2009-01-01

    Competing theories of short-term memory function make specific predictions about the functional anatomy of auditory short-term memory and its role in language comprehension. We analysed high-resolution structural magnetic resonance images from 210 stroke patients and employed a novel voxel based analysis to test the relationship between auditory short-term memory and speech comprehension. Using digit span as an index of auditory short-term memory capacity we found that the structural integrit...

  17. Remembering over the short-term: the case against the standard model.

    Science.gov (United States)

    Nairne, James S

    2002-01-01

    Psychologists often assume that short-term storage is synonymous with activation, a mnemonic property that keeps information in an immediately accessible form. Permanent knowledge is activated, as a result of on-line cognitive processing, and an activity trace is established "in" short-term (or working) memory. Activation is assumed to decay spontaneously with the passage of time, so a refreshing process-rehearsal-is needed to maintain availability. Most of the phenomena of immediate retention, such as capacity limitations and word length effects, are assumed to arise from trade-offs between rehearsal and decay. This "standard model" of how we remember over the short-term still enjoys considerable popularity, although recent research questions most of its main assumptions. In this chapter I review the recent research and identify the empirical and conceptual problems that plague traditional conceptions of short-term memory. Increasingly, researchers are recognizing that short-term retention is cue driven, much like long-term memory, and that neither rehearsal nor decay is likely to explain the particulars of short-term forgetting.

  18. The Mind and Brain of Short-Term Memory

    OpenAIRE

    Jonides, John; Lewis, Richard L.; Nee, Derek Evan; Lustig, Cindy A.; Berman, Marc G.; Moore, Katherine Sledge

    2008-01-01

    The past 10 years have brought near-revolutionary changes in psychological theories about short-term memory, with similarly great advances in the neurosciences. Here, we critically examine the major psychological theories (the “mind”) of short-term memory and how they relate to evidence about underlying brain mechanisms. We focus on three features that must be addressed by any satisfactory theory of short-term memory. First, we examine the evidence for the architecture of short-term memory, w...

  19. A novel TRNSYS type for short-term borehole heat exchanger simulation: B2G model

    International Nuclear Information System (INIS)

    De Rosa, Mattia; Ruiz-Calvo, Félix; Corberán, José M.; Montagud, Carla; Tagliafico, Luca A.

    2015-01-01

    Highlights: • A novel dynamic borehole heat exchanger model is presented. • Theoretical approach for model parameters calculation is described. • The short-term model is validated against experimental data of a real GSHP. • Strong dynamic conditions due to the ON–OFF regulation are investigated. - Abstract: Models of ground source heat pump (GSHP) systems are used as an aid for the correct design and optimization of the system. For this purpose, it is necessary to develop models which correctly reproduce the dynamic thermal behavior of each component in a short-term basis. Since the borehole heat exchanger (BHE) is one of the main components, special attention should be paid to ensuring a good accuracy on the prediction of the short-term response of the boreholes. The BHE models found in literature which are suitable for short-term simulations usually present high computational costs. In this work, a novel TRNSYS type implementing a borehole-to-ground (B2G) model, developed for modeling the short-term dynamic performance of a BHE with low computational cost, is presented. The model has been validated against experimental data from a GSHP system located at Universitat Politècnica de València, Spain. Validation results show the ability of the model to reproduce the short-term behavior of the borehole, both for a step-test and under normal operating conditions

  20. Short-term solar irradiation forecasting based on Dynamic Harmonic Regression

    International Nuclear Information System (INIS)

    Trapero, Juan R.; Kourentzes, Nikolaos; Martin, A.

    2015-01-01

    Solar power generation is a crucial research area for countries that have high dependency on fossil energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate the electricity generated by solar energy into the grid, solar irradiation must be reasonably well forecasted, where deviations of the forecasted value from the actual measured value involve significant costs. The present paper proposes a univariate Dynamic Harmonic Regression model set up in a State Space framework for short-term (1–24 h) solar irradiation forecasting. Time series hourly aggregated as the Global Horizontal Irradiation and the Direct Normal Irradiation will be used to illustrate the proposed approach. This method provides a fast automatic identification and estimation procedure based on the frequency domain. Furthermore, the recursive algorithms applied offer adaptive predictions. The good forecasting performance is illustrated with solar irradiance measurements collected from ground-based weather stations located in Spain. The results show that the Dynamic Harmonic Regression achieves the lowest relative Root Mean Squared Error; about 30% and 47% for the Global and Direct irradiation components, respectively, for a forecast horizon of 24 h ahead. - Highlights: • Solar irradiation forecasts at short-term are required to operate solar power plants. • This paper assesses the Dynamic Harmonic Regression to forecast solar irradiation. • Models are evaluated using hourly GHI and DNI data collected in Spain. • The results show that forecasting accuracy is improved by using the model proposed

  1. Short-Term Load Forecasting Model Based on Quantum Elman Neural Networks

    Directory of Open Access Journals (Sweden)

    Zhisheng Zhang

    2016-01-01

    Full Text Available Short-term load forecasting model based on quantum Elman neural networks was constructed in this paper. The quantum computation and Elman feedback mechanism were integrated into quantum Elman neural networks. Quantum computation can effectively improve the approximation capability and the information processing ability of the neural networks. Quantum Elman neural networks have not only the feedforward connection but also the feedback connection. The feedback connection between the hidden nodes and the context nodes belongs to the state feedback in the internal system, which has formed specific dynamic memory performance. Phase space reconstruction theory is the theoretical basis of constructing the forecasting model. The training samples are formed by means of K-nearest neighbor approach. Through the example simulation, the testing results show that the model based on quantum Elman neural networks is better than the model based on the quantum feedforward neural network, the model based on the conventional Elman neural network, and the model based on the conventional feedforward neural network. So the proposed model can effectively improve the prediction accuracy. The research in the paper makes a theoretical foundation for the practical engineering application of the short-term load forecasting model based on quantum Elman neural networks.

  2. Prospective testing of Coulomb short-term earthquake forecasts

    Science.gov (United States)

    Jackson, D. D.; Kagan, Y. Y.; Schorlemmer, D.; Zechar, J. D.; Wang, Q.; Wong, K.

    2009-12-01

    Earthquake induced Coulomb stresses, whether static or dynamic, suddenly change the probability of future earthquakes. Models to estimate stress and the resulting seismicity changes could help to illuminate earthquake physics and guide appropriate precautionary response. But do these models have improved forecasting power compared to empirical statistical models? The best answer lies in prospective testing in which a fully specified model, with no subsequent parameter adjustments, is evaluated against future earthquakes. The Center of Study of Earthquake Predictability (CSEP) facilitates such prospective testing of earthquake forecasts, including several short term forecasts. Formulating Coulomb stress models for formal testing involves several practical problems, mostly shared with other short-term models. First, earthquake probabilities must be calculated after each “perpetrator” earthquake but before the triggered earthquakes, or “victims”. The time interval between a perpetrator and its victims may be very short, as characterized by the Omori law for aftershocks. CSEP evaluates short term models daily, and allows daily updates of the models. However, lots can happen in a day. An alternative is to test and update models on the occurrence of each earthquake over a certain magnitude. To make such updates rapidly enough and to qualify as prospective, earthquake focal mechanisms, slip distributions, stress patterns, and earthquake probabilities would have to be made by computer without human intervention. This scheme would be more appropriate for evaluating scientific ideas, but it may be less useful for practical applications than daily updates. Second, triggered earthquakes are imperfectly recorded following larger events because their seismic waves are buried in the coda of the earlier event. To solve this problem, testing methods need to allow for “censoring” of early aftershock data, and a quantitative model for detection threshold as a function of

  3. Short-term and long-term deflection of reinforced hollow core ...

    African Journals Online (AJOL)

    This paper presents a study on different methods of analysis that are currently used by design codes to predict the short-term and long-term deflection of reinforced concrete slab systems and compares the predicted deflections with measured deflections. The experimental work to measure deflections involved the testing of ...

  4. Short-Term Memory as an Additional Predictor of School Achievement for Immigrant Children?

    Science.gov (United States)

    te Nijenhuis, Jan; Resing, Wilma; Tolboom, Elsbeth; Bleichrodt, Nico

    2004-01-01

    The predictive validity and utility of assessment procedures can be increased by adding predictors to the prediction supplied by general ability tests. Of Jensen's early work comes the suggestion of focusing on the cognitive ability short-term memory (STM), especially for low-"g" Black children. Meta-analysis convincingly shows high…

  5. CGH Short Term Scientist Exchange Program (STSEP)

    Science.gov (United States)

    STSEP promotes collaborative research between established U.S. and foreign scientists from low, middle, and upper-middle income countries (LMICs) by supporting, in part, exchange visits of cancer researchers between U.S. and foreign laboratories.

  6. Online Short-term Solar Power Forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    2011-01-01

    This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours.......This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours....

  7. Visual short-term memory for sequential arrays.

    Science.gov (United States)

    Kumar, Arjun; Jiang, Yuhong

    2005-04-01

    The capacity of visual short-term memory (VSTM) for a single visual display has been investigated in past research, but VSTM for multiple sequential arrays has been explored only recently. In this study, we investigate the capacity of VSTM across two sequential arrays separated by a variable stimulus onset asynchrony (SOA). VSTM for spatial locations (Experiment 1), colors (Experiments 2-4), orientations (Experiments 3 and 4), and conjunction of color and orientation (Experiment 4) were tested, with the SOA across the two sequential arrays varying from 100 to 1,500 msec. We find that VSTM for the trailing array is much better than VSTM for the leading array, but when averaged across the two arrays VSTM has a constant capacity independent of the SOA. We suggest that multiple displays compete for retention in VSTM and that separating information into two temporally discrete groups does not enhance the overall capacity of VSTM.

  8. Short-term memories with a stochastic perturbation

    International Nuclear Information System (INIS)

    Pontes, Jose C.A. de; Batista, Antonio M.; Viana, Ricardo L.; Lopes, Sergio R.

    2005-01-01

    We investigate short-term memories in linear and weakly nonlinear coupled map lattices with a periodic external input. We use locally coupled maps to present numerical results about short-term memory formation adding a stochastic perturbation in the maps and in the external input

  9. Short-term energy outlook, annual supplement 1994

    International Nuclear Information System (INIS)

    1994-08-01

    The Short-Term Energy Outlook Annual Supplement (Supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts

  10. Comparison of Sugammadex and Neostigmine in Short Term Surgery

    Directory of Open Access Journals (Sweden)

    Fatih Koc

    2014-03-01

    Full Text Available Aim: This study compared the efficacy and cost effectivines of sugammadex and neostigmine for reversal of neuromuscular blockade induced by rocuronium for short term elective surgery. Material and Method: After written informed consent, 33 patients aged 18%u201365, ASA I-III, who were undergoing short term surgery (

  11. Short-Term Group Treatment for Adult Children of Alcoholics.

    Science.gov (United States)

    Cooper, Alvin; McCormack, WIlliam A.

    1992-01-01

    Adult children of alcoholics (n=24) were tested on measures of loneliness, anxiety, hostility, depression, and interpersonal dependency before and after participation in short-term group therapy. Highly significant test score changes supported effectiveness of individual therapy in short-term groups. (Author/NB)

  12. Short-term energy outlook annual supplement, 1993

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-08-06

    The Short-Term Energy Outlook Annual Supplement (supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts.

  13. Short-Term Robustness of Production Management Systems : New Methodology

    NARCIS (Netherlands)

    Kleijnen, J.P.C.; Gaury, E.G.A.

    2000-01-01

    This paper investigates the short-term robustness of production planning and control systems. This robustness is defined here as the systems ability to maintain short-term service probabilities (i.e., the probability that the fill rate remains within a prespecified range), in a variety of

  14. Short-Term Reciprocity in Late Parent-Child Relationships

    Science.gov (United States)

    Leopold, Thomas; Raab, Marcel

    2011-01-01

    Long-term concepts of parent-child reciprocity assume that the amount of support given and received is only balanced in a generalized fashion over the life course. We argue that reciprocity in parent-child relationships also operates in the short term. Our analysis of short-term reciprocity focuses on concurrent exchange in its main upward and…

  15. Online short-term solar power forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    2009-01-01

    This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 hours. The data used is fifteen......-minute observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques....... Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to two hours...

  16. Comparison of two new short-term wind-power forecasting systems

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez-Rosado, Ignacio J. [Department of Electrical Engineering, University of Zaragoza, Zaragoza (Spain); Fernandez-Jimenez, L. Alfredo [Department of Electrical Engineering, University of La Rioja, Logrono (Spain); Monteiro, Claudio; Sousa, Joao; Bessa, Ricardo [FEUP, Fac. Engenharia Univ. Porto (Portugal)]|[INESC - Instituto de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

    2009-07-15

    This paper presents a comparison of two new advanced statistical short-term wind-power forecasting systems developed by two independent research teams. The input variables used in both systems were the same: forecasted meteorological variable values obtained from a numerical weather prediction model; and electric power-generation registers from the SCADA system of the wind farm. Both systems are described in detail and the forecasting results compared, revealing great similarities, although the proposed structures of the two systems are different. The forecast horizon for both systems is 72 h, allowing the use of the forecasted values in electric market operations, as diary and intra-diary power generation bid offers, and in wind-farm maintenance planning. (author)

  17. Are narcissists sexy? Zeroing in on the effect of narcissism on short-term mate appeal.

    Science.gov (United States)

    Dufner, Michael; Rauthmann, John F; Czarna, Anna Z; Denissen, Jaap J A

    2013-07-01

    This research was aimed to provide a comprehensive test of the classic notion that narcissistic individuals are appealing as short-term romantic or sexual partners. In three studies, we tested the hypotheses that narcissism exerts a positive effect on an individual's mate appeal and that this effect is mediated by high physical attractiveness and high social boldness. We implemented a multimethod approach and used ratings of opposite sex persons (Study 1), ratings of friends (Study 2), and records of courtship outcomes in naturalistic interactions (Study 3) as indicators of mate appeal. In all cases, narcissism had a positive effect on mate appeal, which was mainly due to the agentic self-enhancement aspects of narcissism (rather than narcissists' lacking communion). As predicted, physical attractiveness and social boldness mediated the positive effect of narcissism on mate appeal. Findings further indicated that narcissism was more strongly linked to mate appeal than to friend appeal.

  18. Quality of rearing practices as predictor of short-term outcome in adolescent anorexia nervosa.

    Science.gov (United States)

    Castro, J; Toro, J; Cruz, M

    2000-01-01

    Studies of family relationships in anorexia nervosa have produced conflicting results. Some authors claim that family factors are related to short-term outcomes. Perceived rearing practices, as measured by the EMBU (Egna Minnen Betraffande Uppfostran: 'My memories of Upbringing') were examined in a sample (N = 158) of adolescents with anorexia nervosa and compared with the perceptions of adolescents (N = 159) from the general population. A further comparison was made between the groups of patients with good and bad short-term outcomes. Logistic regression analysis was performed to evaluate the predictive value of different variables on short-term outcome. Overall, small differences were observed in the perceptions of rearing practices as expressed by the controls and the anorexic patients. Patients with bad short-term outcome perceived more rejection and control-overprotection from both parents than those with good outcome. In the logistic regression analysis only Rejection from father and the EAT (Eating Attitudes Test) total score gave independent prediction of treatment response. Taken as a whole, these results do not support the idea of altered rearing practices in anorexic patients, at least in young patients with a short evolution of the disease. Perceived rearing practices, especially 'rejection', appear to have an appreciable effect on the short-term outcome.

  19. Short-term Variability of Vitamin D-Related Biomarkers.

    Science.gov (United States)

    Lutsey, Pamela L; Parrinello, Christina M; Misialek, Jeffrey R; Hoofnagle, Andy N; Henderson, Clark M; Laha, Thomas J; Michos, Erin D; Eckfeldt, John H; Selvin, Elizabeth

    2016-12-01

    Quantifying the variability of biomarkers is important, as high within-person variability can lead to misclassification of individuals. Short-term variability of important markers of vitamin D metabolism is relatively unknown. A repeatability study was conducted in 160 Atherosclerosis Risk in Communities study participants (60% female, 28% black, mean age 76 years). Fasting serum was drawn at 2 time points, a median of 6 (range 3-13) weeks apart. Vitamin D binding protein (VDBP) and 25-hydroxyvitamin D [25(OH)D] were measured by LC-MS, fibroblast growth factor (FGF23) and parathyroid hormone (PTH) by enzyme-linked immunoassay, and calcium and phosphorus by Roche Cobas 6000. Free and bioavailable 25(OH)D were calculated. We calculated the within-person CV (CV W ), intraclass correlation coefficient (ICC), Spearman rank correlation coefficient (r), and percent reclassified. The CV W was lowest for calcium (2.0%), albumin (3.6%), 25(OH)D (6.9%), VDBP (7.0%) and phosphorus (7.6%); intermediate for free 25(OH)D (9.0%) and bioavailable 25(OH)D (9.9%); and highest for PTH (16.7%) and FGF23 (17.8%). Reclassification was highest for PTH, VDBP, and phosphorus (all 7.5%). The ICC and r were highest (≥0.80) for 25(OH)D, free 25(OH)D, bioavailable 25(OH)D and PTH, but somewhat lower (approximately 0.60-0.75) for the other biomarkers. Six-week short-term variability, as assessed by CV W , was quite low for VDBP, calcium and phosphorus, but fairly high for FGF23 and PTH. As such, multiple measurements of FGF23 and PTH may be needed to minimize misclassification. These results provide insight into the extent of potential misclassification of vitamin D markers in research and clinical settings. © 2016 American Association for Clinical Chemistry.

  20. Short-Term Solar Collector Power Forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Perers, Bengt

    2011-01-01

    This paper describes a new approach to online forecasting of power output from solar thermal collectors. The method is suited for online forecasting in many applications and in this paper it is applied to predict hourly values of power from a standard single glazed large area flat plate collector...... enabling tracking of changes in the system and in the surrounding conditions, such as decreasing performance due to wear and dirt, and seasonal changes such as leaves on trees. This furthermore facilitates remote monitoring and check of the system....

  1. Verbal Short-Term Memory Span in Speech-Disordered Children: Implications for Articulatory Coding in Short-Term Memory.

    Science.gov (United States)

    Raine, Adrian; And Others

    1991-01-01

    Children with speech disorders had lower short-term memory capacity and smaller word length effect than control children. Children with speech disorders also had reduced speech-motor activity during rehearsal. Results suggest that speech rate may be a causal determinant of verbal short-term memory capacity. (BC)

  2. EVALUATING SHORT-TERM CLIMATE VARIABILITY IN THE LATE HOLOCENE OF THE NORTHERN GREAT PLAINS

    Energy Technology Data Exchange (ETDEWEB)

    Joseph H. Hartman

    1999-09-01

    Great Plains, northern hemisphere, and elsewhere. Finally these data can be integrated into a history of climate change and predictive climate models. This is not a small undertaking. The goals of researchers and the methods used vary considerably. The primary task of this project was literature research to (1) evaluate existing methodologies used in geologic climate change studies and evidence for short-term cycles produced by these methodologies and (2) evaluate late Holocene climate patterns and their interpretations.

  3. Audit of long-term and short-term liabilities

    Directory of Open Access Journals (Sweden)

    Korinko M.D.

    2017-03-01

    Full Text Available The article determines the importance of long-term and short-term liabilities for the management of financial and material resources of an enterprise. It reviews the aim, objects and information generators for realization of audit of short-term and long-term obligations. The organizing and methodical providing of audit of long-term and short-term liabilities of an enterprise are generalized. The authors distinguish the stages of realization of audit of long-term and short-term liabilities, the aim of audit on each of the presented stages, and recommend methodical techniques. It is fixed that it is necessary to conduct the estimation of the systems of internal control and record-keeping of an enterprise by implementation of public accountant procedures for determination of volume and maintenance of selection realization. After estimating the indicated systems, a public accountant determines the methodology for realization of public accountant verification of long-term and short-term liabilities. The analytical procedures that public accountants are expedient to use for realization of audit of short-term and long-term obligations are determined. The authors suggest the classification of the educed defects on the results of the conducted public accountant verification of short-term and long-term obligations.

  4. Self-reported immature defense style as a predictor of outcome in short-term and long-term psychotherapy.

    Science.gov (United States)

    Laaksonen, Maarit A; Sirkiä, Carlos; Knekt, Paul; Lindfors, Olavi

    2014-07-01

    Identification of pretreatment patient characteristics predictive of psychotherapy outcome could help to guide treatment choices. This study evaluates patients' initial level of immature defense style as a predictor of the outcome of short-term versus long-term psychotherapy. In the Helsinki Psychotherapy Study, 326 adult outpatients with mood or anxiety disorder were randomized to individual short-term (psychodynamic or solution-focused) or long-term (psychodynamic) psychotherapy. Their defense style was assessed at baseline using the 88-item Defense Style Questionnaire and classified as low or high around the median value of the respective score. Both specific (Beck Depression Inventory [BDI], Hamilton Depression Rating Scale [HDRS], Symptom Check List Anxiety Scale [SCL-90-Anx], Hamilton Anxiety Rating Scale [HARS]) and global (Symptom Check List Global Severity Index [SCL-90-GSI], Global Assessment of Functioning Scale [GAF]) psychiatric symptoms were measured at baseline and 3-7 times during a 3-year follow-up. Patients with high use of immature defense style experienced greater symptom reduction in long-term than in short-term psychotherapy by the end of the 3-year follow-up (50% vs. 34%). Patients with low use of immature defense style experienced faster symptom reduction in short-term than in long-term psychotherapy during the first year of follow-up (34% vs. 19%). Knowledge of patients' initial level of immature defense style may potentially be utilized in tailoring treatments. Further research on defense styles as outcome predictors in psychotherapies of different types is needed.

  5. Short term load forecasting using neuro-fuzzy networks

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, M.; Hassan, A. [South Dakota School of Mines and Technology, Rapid City, SD (United States); Martinez, D. [Black Hills Power and Light, Rapid City, SD (United States)

    2005-07-01

    Details of a neuro-fuzzy network-based short term load forecasting system for power utilities were presented. The fuzzy logic controller was used to fuzzify inputs representing historical temperature and load curves. The fuzzified inputs were then used to develop the fuzzy rules matrix. Output membership function values were determined by evaluating the fuzzified inputs with the fuzzy rules. Output membership function values were used as inputs for the neural network portion of the system. The training process used a back propagation gradient descent algorithm to adjust the weight values of the neural network in order to reduce the error between the neural network output and the desired output. The neural network was then used to predict future load values. Sample data were taken from a local power company's daily load curve to validate the system. A 10 per cent forecast error was introduced in the temperature values to determine the effect on load prediction. Results of the study suggest that the combined use of fuzzy logic and neural networks provide greater accuracy than studies where either approach is used alone. 6 refs., 6 figs.

  6. Short-term load forecasting of power system

    Science.gov (United States)

    Xu, Xiaobin

    2017-05-01

    In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

  7. Phonological short-term memory impairment and the word length effect in children with intellectual disabilities.

    Science.gov (United States)

    Poloczek, Sebastian; Büttner, Gerhard; Hasselhorn, Marcus

    2014-02-01

    There is mounting evidence that children and adolescents with intellectual disabilities (ID) of nonspecific aetiology perform poorer on phonological short-term memory tasks than children matched for mental age indicating a structural deficit in a process contributing to short-term recall of verbal material. One explanation is that children with ID of nonspecific aetiology do not activate subvocal rehearsal to refresh degrading memory traces. However, existing research concerning this explanation is inconclusive since studies focussing on the word length effect (WLE) as indicator of rehearsal have revealed inconsistent results for samples with ID and because in several existing studies, it is unclear whether the WLE was caused by rehearsal or merely appeared during output of the responses. We assumed that in children with ID only output delays produce a small WLE while in typically developing 6- to 8-year-olds rehearsal and output contribute to the WLE. From this assumption we derived several predictions that were tested in an experiment including 34 children with mild or borderline ID and 34 typically developing children matched for mental age (MA). As predicted, results revealed a small but significant WLE for children with ID that was significantly smaller than the WLE in the control group. Additionally, for children with ID, a WLE was not found for the first word of each trial but the effect emerged only in later serial positions. The findings corroborate the notion that in children with ID subvocal rehearsal does not develop in line with their mental age and provide a potential explanation for the inconsistent results on the WLE in children with ID. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yannan; Hou, Zhangshuan; Meng, Da; Samaan, Nader A.; Makarov, Yuri V.; Huang, Zhenyu

    2016-07-17

    In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

  9. Characterizing short-term stability for Boolean networks over any distribution of transfer functions

    International Nuclear Information System (INIS)

    Seshadhri, C.; Smith, Andrew M.; Vorobeychik, Yevgeniy; Mayo, Jackson R.; Armstrong, Robert C.

    2016-01-01

    Here we present a characterization of short-term stability of random Boolean networks under arbitrary distributions of transfer functions. Given any distribution of transfer functions for a random Boolean network, we present a formula that decides whether short-term chaos (damage spreading) will happen. We provide a formal proof for this formula, and empirically show that its predictions are accurate. Previous work only works for special cases of balanced families. Finally, it has been observed that these characterizations fail for unbalanced families, yet such families are widespread in real biological networks.

  10. Short-Term Forecasting of Electric Energy Generation for a Photovoltaic System

    Directory of Open Access Journals (Sweden)

    Dinh V.T.

    2018-01-01

    Full Text Available This article presents a short-term forecast of electric energy output of a photovoltaic (PV system towards Tomsk city, Russia climate variations (module temperature and solar irradiance. The system is located at Institute of Non-destructive Testing, Tomsk Polytechnic University. The obtained results show good agreement between actual data and prediction values.

  11. Modelling the short-term response of the Greenland ice-sheet to global warming

    NARCIS (Netherlands)

    Wal, R.S.W. van de; Oerlemans, J.

    1997-01-01

    A two-dimensional vertically integrated ice flow model has been developed to test the importance of various processes and concepts used for the prediction of the contribution of the Greenland ice-sheet to sea-level rise over the next 350 y (short-term response). The mass balance is modelled by the

  12. Short-term effects of simultaneous cardiovascular workout and ...

    African Journals Online (AJOL)

    PMD), has become a growing public health concern, as it may potentially result in the development of hearing difficulties. Objectives: The aim of the study was to determine the differential impact and short-term effects of simultaneous ...

  13. Short-term treatment outcomes of children starting antiretroviral ...

    African Journals Online (AJOL)

    Short-term treatment outcomes of children starting antiretroviral therapy in the intensive care unit, general medical wards and outpatient HIV clinics at Red Cross War Memorial Children's Hospital, Cape Town, South Africa: A retrospective cohort study.

  14. Short-term outcome of patients with closed comminuted femoral ...

    African Journals Online (AJOL)

    Short-term outcome of patients with closed comminuted femoral shaft fracture treated with locking intramedullary sign nail at Muhimbili Orthopaedic Institute in Tanzania. Billy T. Haonga, Felix S. Mrita, Edmundo E. Ndalama, Jackline E. Makupa ...

  15. Short term variations in particulate matter in Mahi river estuary

    Digital Repository Service at National Institute of Oceanography (India)

    Bhosle, N.B.; Rokade, M.A.; Zingde, M.D.

    The particulate matter (PM) collected from Mahi River Estuary was analysed for organic carbon (POC), nitrogen (PON), and chlorophyll a (Chl a). The concentration of PM, POC, PON and Chl a showed short term variations. Average surface concentration...

  16. Short-Term Wind Speed Forecasting for Power System Operations

    KAUST Repository

    Zhu, Xinxin; Genton, Marc G.

    2012-01-01

    some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss

  17. The nature of forgetting from short-term memory

    OpenAIRE

    Muter, Paul

    2001-01-01

    Memory and forgetting are inextricably intertwined. Any account of short-term memory (STM) should address the following question: If three, four, or five chunks are being held in STM, what happens after attention is diverted?

  18. Parent-Offspring Conflict over Short-Term Mating Strategies

    Directory of Open Access Journals (Sweden)

    Spyroulla Georgiou

    2011-12-01

    Full Text Available Individuals engage in short-term mating strategies that enable them to obtain fitness benefits from casual relationships. These benefits, however, count for less and cost more to their parents. On this basis three hypotheses are tested. First, parents and offspring are likely to disagree over short-term mating strategies, with the former considering these as less acceptable than the latter. Second, parents are more likely to disapprove of the short-term mating strategies of their daughters than of their sons. Finally, mothers and fathers are expected to agree on how much they disagree over the short-term mating strategies of their children. Evidence from a sample of 148 Greek-Cypriot families (140 mothers, 105 fathers, 119 daughters, 77 sons provides support for the first two hypotheses and partial support for the third hypothesis. The implications of these findings for understanding family dynamics are further discussed.

  19. Rapid effects of estrogens on short-term memory: Possible mechanisms.

    Science.gov (United States)

    Paletta, Pietro; Sheppard, Paul A S; Matta, Richard; Ervin, Kelsy S J; Choleris, Elena

    2018-06-01

    Estrogens affect learning and memory through rapid and delayed mechanisms. Here we review studies on rapid effects on short-term memory. Estradiol rapidly improves social and object recognition memory, spatial memory, and social learning when administered systemically. The dorsal hippocampus mediates estrogen rapid facilitation of object, social and spatial short-term memory. The medial amygdala mediates rapid facilitation of social recognition. The three estrogen receptors, α (ERα), β (ERβ) and the G-protein coupled estrogen receptor (GPER) appear to play different roles depending on the task and brain region. Both ERα and GPER agonists rapidly facilitate short-term social and object recognition and spatial memory when administered systemically or into the dorsal hippocampus and facilitate social recognition in the medial amygdala. Conversely, only GPER can facilitate social learning after systemic treatment and an ERβ agonist only rapidly improved short-term spatial memory when given systemically or into the hippocampus, but also facilitates social recognition in the medial amygdala. Investigations into the mechanisms behind estrogens' rapid effects on short term memory showed an involvement of the extracellular signal-regulated kinase (ERK) and the phosphoinositide 3-kinase (PI3K) kinase pathways. Recent evidence also showed that estrogens interact with the neuropeptide oxytocin in rapidly facilitating social recognition. Estrogens can increase the production and/or release of oxytocin and other neurotransmitters, such as dopamine and acetylcholine. Therefore, it is possible that estrogens' rapid effects on short-term memory may occur through the regulation of various neurotransmitters, although more research is need on these interactions as well as the mechanisms of estrogens' actions on short-term memory. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Short-term Consumer Benefits of Dynamic Pricing

    OpenAIRE

    Dupont, Benjamin; De Jonghe, Cedric; Kessels, Kris; Belmans, Ronnie

    2011-01-01

    Consumer benefits of dynamic pricing depend on a variety of factors. Consumer characteristics and climatic circumstances widely differ, which forces a regional comparison. This paper presents a general overview of demand response programs and focuses on the short-term benefits of dynamic pricing for an average Flemish residential consumer. It reaches a methodology to develop a cost reflective dynamic pricing program and to estimate short-term bill savings. Participating in a dynamic pricing p...

  1. Behavioural Models of Motor Control and Short-Term Memory

    OpenAIRE

    Imanaka, Kuniyasu; Funase, Kozo; Yamauchi, Masaki

    1995-01-01

    We examined in this review article the behavioural and conceptual models of motor control and short-term memory which have intensively been investigated since the 1970s. First, we reviewed both the dual-storage model of short-term memory in which movement information is stored and a typical model of motor control which emphasizes the importance of efferent factors. We then examined two models of preselection effects: a cognitive model and a cognitive/ efferent model. Following this we reviewe...

  2. An ethics curriculum for short-term global health trainees

    OpenAIRE

    DeCamp, Matthew; Rodriguez, Joce; Hecht, Shelby; Barry, Michele; Sugarman, Jeremy

    2013-01-01

    Background Interest in short-term global health training and service programs continues to grow, yet they can be associated with a variety of ethical issues for which trainees or others with limited global health experience may not be prepared to address. Therefore, there is a clear need for educational interventions concerning these ethical issues. Methods We developed and evaluated an introductory curriculum, ?Ethical Challenges in Short-term Global Health Training.? The curriculum was deve...

  3. Short-term mechanisms influencing volumetric brain dynamics

    Directory of Open Access Journals (Sweden)

    Nikki Dieleman

    2017-01-01

    Full Text Available With the use of magnetic resonance imaging (MRI and brain analysis tools, it has become possible to measure brain volume changes up to around 0.5%. Besides long-term brain changes caused by atrophy in aging or neurodegenerative disease, short-term mechanisms that influence brain volume may exist. When we focus on short-term changes of the brain, changes may be either physiological or pathological. As such determining the cause of volumetric dynamics of the brain is essential. Additionally for an accurate interpretation of longitudinal brain volume measures by means of neurodegeneration, knowledge about the short-term changes is needed. Therefore, in this review, we discuss the possible mechanisms influencing brain volumes on a short-term basis and set-out a framework of MRI techniques to be used for volumetric changes as well as the used analysis tools. 3D T1-weighted images are the images of choice when it comes to MRI of brain volume. These images are excellent to determine brain volume and can be used together with an analysis tool to determine the degree of volume change. Mechanisms that decrease global brain volume are: fluid restriction, evening MRI measurements, corticosteroids, antipsychotics and short-term effects of pathological processes like Alzheimer's disease, hypertension and Diabetes mellitus type II. Mechanisms increasing the brain volume include fluid intake, morning MRI measurements, surgical revascularization and probably medications like anti-inflammatory drugs and anti-hypertensive medication. Exercise was found to have no effect on brain volume on a short-term basis, which may imply that dehydration caused by exercise differs from dehydration by fluid restriction. In the upcoming years, attention should be directed towards studies investigating physiological short-term changes within the light of long-term pathological changes. Ultimately this may lead to a better understanding of the physiological short-term effects of

  4. Frequency-specific insight into short-term memory capacity

    OpenAIRE

    Feurra, Matteo; Galli, Giulia; Pavone, Enea Francesco; Rossi, Alessandro; Rossi, Simone

    2016-01-01

    We provided novel evidence of a frequency-specific effect by transcranial alternating current stimulation (tACS) of the left posterior parietal cortex on short-term memory, during a digit span task. the effect was prominent with stimulation at beta frequency for young and not for middle-aged adults and correlated with age. Our findings highlighted a short-term memory capacity improvement by tACS application.

  5. Short-term memory for scenes with affective content

    OpenAIRE

    Maljkovic, Vera; Martini, Paolo

    2005-01-01

    The emotional content of visual images can be parameterized along two dimensions: valence (pleasantness) and arousal (intensity of emotion). In this study we ask how these distinct emotional dimensions affect the short-term memory of human observers viewing a rapid stream of images and trying to remember their content. We show that valence and arousal modulate short-term memory as independent factors. Arousal influences dramatically the average speed of data accumulation in memory: Higher aro...

  6. An investigation into the effects of nicotine gum on short-term memory.

    Science.gov (United States)

    Phillips, S; Fox, P

    1998-12-01

    Using a between-subjects 2x2x2 factorial design, 60 smokers and 60 non-smokers (equal number of males and females) performed a short-term memory task requiring delayed free recall of a visually presented supraspan word list. Using a double-blind procedure, half the subjects chewed nicotine gum and the other half chewed placebo gum prior to performing the memory task. Results support previous research findings which show that nicotine significantly improves short-term memory. Sex differences were also investigated, but findings showed no significant differences between male and female subjects. Methodological considerations are discussed and directions for future research are suggested.

  7. Verification of“Trend-Volatility Model”in Short-Term Forecast of Grain Production Potential

    Directory of Open Access Journals (Sweden)

    MI Chang-hong

    2016-02-01

    Full Text Available The "trend-volatility model" in short-term forecasting of grain production potential was verified and discussed systematically by using the grain production data from 1949 to 2014, in 16 typical counties and 6 typical districts, and 31 provinces, of China. The results showed as follows:(1 Size of forecast error reflected the precision of short-term production potential, the main reason of large prediction error was a great amount of high yield farmlands were occupied in developed areas and a great increase of vegetable and fruit planted that made grain yield decreased in a short time;(2 The micro-trend amendment method was a necessary part of "trend-volatility model", which could involve the short-term factors such as meteorological factors, science and technology input, social factors and other effects, while macro-trend prediction could not. Therefore, The micro-trend amendment method could improve the forecast precision.(3 In terms of actual situation in recent years in China, the more developed the areas was, the bigger the volatility of short-term production potential was; For the short-term production potential, the stage of increasing-decreasing-recovering also existed in developed areas;(4 In the terms of forecast precision of short-terms production potential, the scale of national was higher than the scale of province, the scale of province was higher than the scale of district, the scale of district was higher than the scale of county. And it was large differences in precision between different provinces, different districts and different counties respectively, which was concerned to the complementarity of domestic climate and the ability of the farmland resistance to natural disasters.

  8. Short-term memory and dual task performance

    Science.gov (United States)

    Regan, J. E.

    1982-01-01

    Two hypotheses concerning the way in which short-term memory interacts with another task in a dual task situation are considered. It is noted that when two tasks are combined, the activity of controlling and organizing performance on both tasks simultaneously may compete with either task for a resource; this resource may be space in a central mechanism or general processing capacity or it may be some task-specific resource. If a special relationship exists between short-term memory and control, especially if there is an identity relationship between short-term and a central controlling mechanism, then short-term memory performance should show a decrement in a dual task situation. Even if short-term memory does not have any particular identity with a controlling mechanism, but both tasks draw on some common resource or resources, then a tradeoff between the two tasks in allocating resources is possible and could be reflected in performance. The persistent concurrence cost in memory performance in these experiments suggests that short-term memory may have a unique status in the information processing system.

  9. A novel economy reflecting short-term load forecasting approach

    International Nuclear Information System (INIS)

    Lin, Cheng-Ting; Chou, Li-Der

    2013-01-01

    Highlights: ► We combine MA line of TAIEX and SVR to overcome the load demands over-prediction problems caused by the economic downturn. ► The Taiwan island-wide electricity power system was used as the case study. ► Short- to middle-term MA lines of TAIEX are found to be good economic input variables for load forecasting models. - Abstract: The global economic downturn in 2008 and 2009, which was spurred by the bankruptcy of Lehman Brothers, sharply reduced the demand for electricity load. Conventional load-forecasting approaches were unable to respond to sudden changes in the economy, because these approaches do not consider the effect of economic factors. Therefore, the over-prediction problem occurred. To overcome this problem, this paper proposes a novel, economy-reflecting, short-term load forecasting (STLF) approach based on theories of moving average (MA) line of stock index and machine learning. In this approach, the stock indices decision model is designed to reflect fluctuations in the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) series, which is selected as an optimal input variable in support vector regression load forecasting model at an appropriate timing. The Taiwan island-wide hourly electricity load demands from 2008 to 2010 are used as the case study for performance benchmarking. Results show that the proposed approach with a 60-day MA of the TAIEX as economic learning pattern achieves good forecasting performance. It outperforms the conventional approach by 29.16% on average during economic downturn-affected days. Overall, the proposed approach successfully overcomes the over-prediction problems caused by the economic downturn. To the best of our knowledge, this paper is the first attempt to apply MA line theory of stock index on STLF.

  10. Perceptions of short-term medical volunteer work: a qualitative study in Guatemala.

    Science.gov (United States)

    Green, Tyler; Green, Heidi; Scandlyn, Jean; Kestler, Andrew

    2009-02-26

    Each year medical providers from wealthy countries participate in short-term medical volunteer work in resource-poor countries. Various authors have raised concern that such work has the potential to be harmful to recipient communities; however, the social science and medical literature contains little research into the perceptions of short-term medical volunteer work from the perspective of members of recipient communities. This exploratory study examines the perception of short-term medical volunteer work in Guatemala among groups of actors affected by or participating in these programs. The researchers conducted in-depth, semi-structured interviews with 72 individuals, including Guatemalan healthcare providers and health authorities, foreign medical providers, non-medical personnel working on health projects, and Guatemalan parents of children treated by a short-term volunteer group. Detailed notes and summaries of these interviews were uploaded, coded and annotated using Atlas.ti (Scientific Software Development GmbH, Berlin) to identify recurrent themes from the interviews. Informants commonly identified a need for increased access to medical services in Guatemala, and many believed that short-term medical volunteers are in a position to offer improved access to medical care in the communities where they serve. Informants most frequently cited appropriate patient selection and attention to payment systems as the best means to avoid creating dependence on foreign aid. The most frequent suggestion to improve short-term medical volunteer work was coordination with and respect for local Guatemalan healthcare providers and their communities, as insufficient understanding of the country's existing healthcare resources and needs may result in perceived harm to the recipient community. The perceived impact of short-term medical volunteer projects in Guatemala is highly variable and dependent upon the individual project. In this exploratory study, project

  11. Short-Term Forecasts Using NU-WRF for the Winter Olympics 2018

    Science.gov (United States)

    Srikishen, Jayanthi; Case, Jonathan L.; Petersen, Walter A.; Iguchi, Takamichi; Tao, Wei-Kuo; Zavodsky, Bradley T.; Molthan, Andrew

    2017-01-01

    The NASA Unified-Weather Research and Forecasting model (NU-WRF) will be included for testing and evaluation in the forecast demonstration project (FDP) of the International Collaborative Experiment -PyeongChang 2018 Olympic and Paralympic (ICE-POP) Winter Games. An international array of radar and supporting ground based observations together with various forecast and now-cast models will be operational during ICE-POP. In conjunction with personnel from NASA's Goddard Space Flight Center, the NASA Short-term Prediction Research and Transition (SPoRT) Center is developing benchmark simulations for a real-time NU-WRF configuration to run during the FDP. ICE-POP observational datasets will be used to validate model simulations and investigate improved model physics and performance for prediction of snow events during the research phase (RDP) of the project The NU-WRF model simulations will also support NASA Global Precipitation Measurement (GPM) Mission ground-validation physical and direct validation activities in relation to verifying, testing and improving satellite-based snowfall retrieval algorithms over complex terrain.

  12. Familiarity speeds up visual short-term memory consolidation.

    Science.gov (United States)

    Xie, Weizhen; Zhang, Weiwei

    2017-06-01

    Existing long-term memory (LTM) can boost the number of retained representations over a short delay in visual short-term memory (VSTM). However, it is unclear whether and how prior LTM affects the initial process of transforming fragile sensory inputs into durable VSTM representations (i.e., VSTM consolidation). The consolidation speed hypothesis predicts faster consolidation for familiar relative to unfamiliar stimuli. Alternatively, the perceptual boost hypothesis predicts that the advantage in perceptual processing of familiar stimuli should add a constant boost for familiar stimuli during VSTM consolidation. To test these competing hypotheses, the present study examined how the large variance in participants' prior multimedia experience with Pokémon affected VSTM for Pokémon. In Experiment 1, the amount of time allowed for VSTM consolidation was manipulated by presenting consolidation masks at different intervals after the onset of to-be-remembered Pokémon characters. First-generation Pokémon characters that participants were more familiar with were consolidated faster into VSTM as compared with recent-generation Pokémon characters that participants were less familiar with. These effects were absent in participants who were unfamiliar with both generations of Pokémon. Although familiarity also increased the number of retained Pokémon characters when consolidation was uninterrupted but still incomplete due to insufficient encoding time in Experiment 1, this capacity effect was absent in Experiment 2 when consolidation was allowed to complete with sufficient encoding time. Together, these results support the consolidation speed hypothesis over the perceptual boost hypothesis and highlight the importance of assessing experimental effects on both processing and representation aspects of VSTM. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  13. Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects

    Science.gov (United States)

    Pan, Zhiyuan; Liu, Li

    2018-02-01

    In this paper, we extend the GARCH-MIDAS model proposed by Engle et al. (2013) to account for the leverage effect in short-term and long-term volatility components. Our in-sample evidence suggests that both short-term and long-term negative returns can cause higher future volatility than positive returns. Out-of-sample results show that the predictive ability of GARCH-MIDAS is significantly improved after taking the leverage effect into account. The leverage effect for short-term volatility component plays more important role than the leverage effect for long-term volatility component in affecting out-of-sample forecasting performance.

  14. Short term forecasting of petroleum product demand in France

    International Nuclear Information System (INIS)

    Cadren, M.

    1998-01-01

    The analysis of petroleum product demand became a privileged thrust of research following the modifications in terms of structure and level of the petroleum markets since eighties. The greatest importance to econometrics models of Energy demand, joint works about nonstationary data, explained the development of error-correction models and the co-integration. In this context, the short term econometrics modelling of petroleum product demand does not only focus on forecasts but also on the measure of the gain acquired from using error-correction techniques and co-integration. It's filling to take the influence of technical improvement and environment pressures into account in econometrics modelling of petroleum products demand. The first part presents the evolution of Energy Demand in France and more particularly the petroleum product demand since 1986. The objective is to determine the main characteristics of each product, which will help us to analyse and validate the econometrics models. The second part focus on the recent developments in times series modelling. We study the problem of nonstationary data and expose different unit root tests. We examine the main approaches to univariate and multivariate modelling with nonstationary data and distinguish the forecasts of the latter's. The third part is intended to applications; its objective is to illustrate the theoretic developments of the second part with a comparison between the performances of different approaches (approach Box and Jenkins, Johansen approach's and structural approach). The models will be applied to the main French petroleum market. The observed asymmetrical demand behaviour is also considered. (author)

  15. Short term mutagenicity tests and their application to irradiated foods

    International Nuclear Information System (INIS)

    Phillips, B.J.; Elias, P.S.

    1980-01-01

    Although traditional long-term animal tests are likely to continue to be required, these are not only extremely costly but are coming more and more to be recognised as an imprecise and unsatisfactory method of testing the safety of irradiated foods for human consumption. It is therefore clearly advisable to include a selection of quicker and more direct testing methods in any toxicological assessment procedures. The International Project has therefore undertaken a study of the feasibility of using the newer systems for investigation of irradiated foodstuffs. Although some work in this field has already been carried out, some shortcomings in the published work can be identified which justify a more detailed and intensive research programme. As expected, little difficulty has been encountered in testing food by methods involving mammals, but considerable effort has been required to adapt in vitro systems. The use of enzymatic digestion in vitro to provide food samples for testing in mammalian cell cultures has never been attempted before and the procedures developed by the Project represent a positive contribution to methodology in this field. A series of foodstuffs is being tested by a wide spectrum of short-term tests and the first results are now being obtained. (orig./MG) [de

  16. Short-term generation scheduling model of Fujian hydro system

    Energy Technology Data Exchange (ETDEWEB)

    Wang Jinwen [School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)], E-mail: dr.jinwen.wang@gmail.com

    2009-04-15

    The Fujian hydropower system (FHS) is one of the provincial hydropower systems with the most complicated hydraulic topology in China. This paper describes an optimization program that is required by Fujian Electric Power Company Ltd. (FEPCL) to aid the shift engineers in making decisions with the short-term hydropower scheduling such that the generation benefit can be maximal. The problem involves 27 reservoirs and is formulated as a nonlinear and discrete programming. It is a very challenging task to solve such a large-scale problem. In this paper, the Lagrangian multipliers are introduced to decompose the primal problem into a hydro subproblem and many individual plant-based subproblems, which are respectively solved by the improved simplex-like method (SLM) and the dynamic programming (DP). A numerical example is given and the derived solution is very close to the optimal one, with the distance in benefit less than 0.004%. All the data needed for the numerical example are presented in detail for further tests and studies from more experts and researchers.

  17. Short-term generation scheduling model of Fujian hydro system

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jinwen [School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2009-04-15

    The Fujian hydropower system (FHS) is one of the provincial hydropower systems with the most complicated hydraulic topology in China. This paper describes an optimization program that is required by Fujian Electric Power Company Ltd. (FEPCL) to aid the shift engineers in making decisions with the short-term hydropower scheduling such that the generation benefit can be maximal. The problem involves 27 reservoirs and is formulated as a nonlinear and discrete programming. It is a very challenging task to solve such a large-scale problem. In this paper, the Lagrangian multipliers are introduced to decompose the primal problem into a hydro subproblem and many individual plant-based subproblems, which are respectively solved by the improved simplex-like method (SLM) and the dynamic programming (DP). A numerical example is given and the derived solution is very close to the optimal one, with the distance in benefit less than 0.004%. All the data needed for the numerical example are presented in detail for further tests and studies from more experts and researchers. (author)

  18. Holding Multiple Items in Short Term Memory: A Neural Mechanism

    Science.gov (United States)

    Rolls, Edmund T.; Dempere-Marco, Laura; Deco, Gustavo

    2013-01-01

    Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging. PMID:23613789

  19. Impaired short-term memory for pitch in congenital amusia.

    Science.gov (United States)

    Tillmann, Barbara; Lévêque, Yohana; Fornoni, Lesly; Albouy, Philippe; Caclin, Anne

    2016-06-01

    Congenital amusia is a neuro-developmental disorder of music perception and production. The hypothesis is that the musical deficits arise from altered pitch processing, with impairments in pitch discrimination (i.e., pitch change detection, pitch direction discrimination and identification) and short-term memory. The present review article focuses on the deficit of short-term memory for pitch. Overall, the data discussed here suggest impairments at each level of processing in short-term memory tasks; starting with the encoding of the pitch information and the creation of the adequate memory trace, the retention of the pitch traces over time as well as the recollection and comparison of the stored information with newly incoming information. These impairments have been related to altered brain responses in a distributed fronto-temporal network, associated with decreased connectivity between these structures, as well as in abnormalities in the connectivity between the two auditory cortices. In contrast, amusic participants׳ short-term memory abilities for verbal material are preserved. These findings show that short-term memory deficits in congenital amusia are specific to pitch, suggesting a pitch-memory system that is, at least partly, separated from verbal memory. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Circadian modulation of short-term memory in Drosophila.

    Science.gov (United States)

    Lyons, Lisa C; Roman, Gregg

    2009-01-01

    Endogenous biological clocks are widespread regulators of behavior and physiology, allowing for a more efficient allocation of efforts and resources over the course of a day. The extent that different processes are regulated by circadian oscillators, however, is not fully understood. We investigated the role of the circadian clock on short-term associative memory formation using a negatively reinforced olfactory-learning paradigm in Drosophila melanogaster. We found that memory formation was regulated in a circadian manner. The peak performance in short-term memory (STM) occurred during the early subjective night with a twofold performance amplitude after a single pairing of conditioned and unconditioned stimuli. This rhythm in memory is eliminated in both timeless and period mutants and is absent during constant light conditions. Circadian gating of sensory perception does not appear to underlie the rhythm in short-term memory as evidenced by the nonrhythmic shock avoidance and olfactory avoidance behaviors. Moreover, central brain oscillators appear to be responsible for the modulation as cryptochrome mutants, in which the antennal circadian oscillators are nonfunctional, demonstrate robust circadian rhythms in short-term memory. Together these data suggest that central, rather than peripheral, circadian oscillators modulate the formation of short-term associative memory and not the perception of the stimuli.

  1. Holding multiple items in short term memory: a neural mechanism.

    Directory of Open Access Journals (Sweden)

    Edmund T Rolls

    Full Text Available Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging.

  2. Holding multiple items in short term memory: a neural mechanism.

    Science.gov (United States)

    Rolls, Edmund T; Dempere-Marco, Laura; Deco, Gustavo

    2013-01-01

    Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging.

  3. Anomaly Detection for Temporal Data using Long Short-Term Memory (LSTM)

    OpenAIRE

    Singh, Akash

    2017-01-01

    We explore the use of Long short-term memory (LSTM) for anomaly detection in temporal data. Due to the challenges in obtaining labeled anomaly datasets, an unsupervised approach is employed. We train recurrent neural networks (RNNs) with LSTM units to learn the normal time series patterns and predict future values. The resulting prediction errors are modeled to give anomaly scores. We investigate different ways of maintaining LSTM state, and the effect of using a fixed number of time steps on...

  4. Are narcissists sexy? Zeroing in on the effect of narcissism on short-term mate appeal.

    NARCIS (Netherlands)

    Dufner, M.; Rauthmann, J.F.; Czarna, A.Z.; Denissen, J.J.A.

    2013-01-01

    This research was aimed to provide a comprehensive test of the classic notion that narcissistic individuals are appealing as short-term romantic or sexual partners. In three studies, we tested the hypotheses that narcissism exerts a positive effect on an individual’s mate appeal and that this effect

  5. The Development of Visual Short-Term Memory for Multifeature Items during Middle childhood

    Science.gov (United States)

    Riggs, Kevin J.; Simpson, Andrew; Potts, Thomas

    2011-01-01

    Visual short-term memory (VSTM) research suggests that the adult capacity is limited to three or four multifeature object representations. Despite evidence supporting a developmental increase in capacity, it remains unclear what the unit of capacity is in children. The current study employed the change detection paradigm to investigate both the…

  6. Verbal Short-Term Memory Performance in Pupils with Down Syndrome

    Science.gov (United States)

    Abdelhameed, Hala; Porter, Jill

    2010-01-01

    Research has shown that verbal short-term memory span is shorter in individuals with Down syndrome than in typically developing individuals of equivalent mental age, but little attention has been given to variations within or across groups. Differences in the environment and in particular educational experiences may play a part in the relative…

  7. Areas of Left Perisylvian Cortex Mediate Auditory-Verbal Short-Term Memory

    Science.gov (United States)

    Koenigs, Michael; Acheson, Daniel J.; Barbey, Aron K.; Solomon, Jeffrey; Postle, Bradley R.; Grafman, Jordan

    2011-01-01

    A contentious issue in memory research is whether verbal short-term memory (STM) depends on a neural system specifically dedicated to the temporary maintenance of information, or instead relies on the same brain areas subserving the comprehension and production of language. In this study, we examined a large sample of adults with acquired brain…

  8. The Influence of Auditory Short-Term Memory on Behavior Problem Development

    Science.gov (United States)

    Low, Justin; Keith, Timothy

    2015-01-01

    The purpose of this research was to determine the influence of two subcomponents of auditory short-term memory on the developmental trajectories of behavior problems. The sample included 7,058 children from the NLSY79--Children and Young Adult survey between the ages 5 and 14 years. Results suggested that anxious/depressed behavior increases…

  9. Manipulations of attention dissociate fragile visual short-term memory from visual working memory

    NARCIS (Netherlands)

    Vandenbroucke, A.R.E.; Sligte, I.G.; Lamme, V.A.F.

    2011-01-01

    People often rely on information that is no longer in view, but maintained in visual short-term memory (VSTM). Traditionally, VSTM is thought to operate on either a short time-scale with high capacity - iconic memory - or a long time scale with small capacity - visual working memory. Recent research

  10. Creative Activity, Personality, Mental Illness, and Short-Term Mating Success

    Science.gov (United States)

    Beaussart, Melanie L.; Kaufman, Scott Barry; Kaufman, James C.

    2012-01-01

    It has been argued that creativity evolved, at least in part, through sexual selection to attract mates. Recent research lends support to this view and has also demonstrated a link between certain dimensions of schizotypy, creativity, and short-term mating. The current study delves deeper into these relationships by focusing on engagement in…

  11. Short-Term Study Abroad: Culture and the Path of Least Resistance

    Science.gov (United States)

    Lemmons, Kelly

    2015-01-01

    American universities are decreasing the length of study abroad programs in an effort to send more students abroad. Recent publications find that "short-term" programs struggle to increase participants' cultural understanding. However, these research findings fail to offer an explanation as to why shorter programs are falling short. This…

  12. Short-Term Memory for Serial Order: A Recurrent Neural Network Model

    Science.gov (United States)

    Botvinick, Matthew M.; Plaut, David C.

    2006-01-01

    Despite a century of research, the mechanisms underlying short-term or working memory for serial order remain uncertain. Recent theoretical models have converged on a particular account, based on transient associations between independent item and context representations. In the present article, the authors present an alternative model, according…

  13. Phonological Short-Term Memory, Working Memory and Foreign Language Performance in Intensive Language Learning

    Science.gov (United States)

    Kormos, Judit; Safar, Anna

    2008-01-01

    In our research we addressed the question what the relationship is between phonological short-term and working memory capacity and performance in an end-of-year reading, writing, listening, speaking and use of English test. The participants of our study were 121 secondary school students aged 15-16 in the first intensive language training year of…

  14. Dialogue Journals in Short-Term Study Abroad: "Today I Wrote My Mind"

    Science.gov (United States)

    Dressler, Roswita; Tweedie, M. Gregory

    2016-01-01

    Short-term study abroad programs are growing in popularity, and educators and researchers are exploring effective tools to enhance the learning and cultural experiences of students in these programs. Dialogue journals, writing journals in which students respond to instructor prompts and in turn initiate topics for further written discussion, are a…

  15. Splitting Attention across the Two Visual Fields in Visual Short-Term Memory

    Science.gov (United States)

    Delvenne, Jean-Francois; Holt, Jessica L.

    2012-01-01

    Humans have the ability to attentionally select the most relevant visual information from their extrapersonal world and to retain it in a temporary buffer, known as visual short-term memory (VSTM). Research suggests that at least two non-contiguous items can be selected simultaneously when they are distributed across the two visual hemifields. In…

  16. A Meta-Analysis of the Impact of Short-Term Sleep Deprivation on Cognitive Variables

    Science.gov (United States)

    Lim, Julian; Dinges, David F.

    2010-01-01

    A substantial amount of research has been conducted in an effort to understand the impact of short-term (less than 48 hr) total sleep deprivation (SD) on outcomes in various cognitive domains. Despite this wealth of information, there has been disagreement on how these data should be interpreted, arising in part because the relative magnitude of…

  17. Short-term and working memory impairments in aphasia.

    Science.gov (United States)

    Potagas, Constantin; Kasselimis, Dimitrios; Evdokimidis, Ioannis

    2011-08-01

    The aim of the present study is to investigate short-term memory and working memory deficits in aphasics in relation to the severity of their language impairment. Fifty-eight aphasic patients participated in this study. Based on language assessment, an aphasia score was calculated for each patient. Memory was assessed in two modalities, verbal and spatial. Mean scores for all memory tasks were lower than normal. Aphasia score was significantly correlated with performance on all memory tasks. Correlation coefficients for short-term memory and working memory were approximately of the same magnitude. According to our findings, severity of aphasia is related with both verbal and spatial memory deficits. Moreover, while aphasia score correlated with lower scores in both short-term memory and working memory tasks, the lack of substantial difference between corresponding correlation coefficients suggests a possible primary deficit in information retention rather than impairment in working memory. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Model documentation report: Short-Term Hydroelectric Generation Model

    International Nuclear Information System (INIS)

    1993-08-01

    The purpose of this report is to define the objectives of the Short- Term Hydroelectric Generation Model (STHGM), describe its basic approach, and to provide details on the model structure. This report is intended as a reference document for model analysts, users, and the general public. Documentation of the model is in accordance with the Energy Information Administration's (AYE) legal obligation to provide adequate documentation in support of its models (Public Law 94-385, Section 57.b.2). The STHGM performs a short-term (18 to 27- month) forecast of hydroelectric generation in the United States using an autoregressive integrated moving average (UREMIA) time series model with precipitation as an explanatory variable. The model results are used as input for the short-term Energy Outlook

  19. Verbal short-term memory and vocabulary learning in polyglots.

    Science.gov (United States)

    Papagno, C; Vallar, G

    1995-02-01

    Polyglot and non-polyglot Italian subjects were given tests assessing verbal (phonological) and visuo-spatial short-term and long-term memory, general intelligence, and vocabulary knowledge in their native language. Polyglots had a superior level of performance in verbal short-term memory tasks (auditory digit span and nonword repetition) and in a paired-associate learning test, which assessed the subjects' ability to acquire new (Russian) words. By contrast, the two groups had comparable performance levels in tasks assessing general intelligence, visuo-spatial short-term memory and learning, and paired-associate learning of Italian words. These findings, which are in line with neuropsychological and developmental evidence, as well as with data from normal subjects, suggest a close relationship between the capacity of phonological memory and the acquisition of foreign languages.

  20. [Impulsiveness Among Short-Term Prisoners with Antisocial Personality Disorder].

    Science.gov (United States)

    Lang, Fabian U; Otte, Stefanie; Vasic, Nenad; Jäger, Markus; Dudeck, Manuela

    2015-07-01

    The study aimed to investigate the correlation between impulsiveness and the antisocial personality disorder among short-term prisoners. The impulsiveness was diagnosed by the Barratt Impulsiveness Scale (BIS). Short-term prisoners with antisocial personality disorder scored significant higher marks on the BIS total scale than those without any personality disorder. In detail, they scored higher marks on each subscale regarding attentional, motor and nonplanning impulsiveness. Moderate and high effects were calculated. It is to be considered to regard impulsivity as a conceptual component of antisociality. © Georg Thieme Verlag KG Stuttgart · New York.

  1. Short-term memory binding deficits in Alzheimer's disease

    OpenAIRE

    Parra, Mario; Abrahams, S.; Fabi, K.; Logie, R.; Luzzi, S.; Della Sala, Sergio

    2009-01-01

    Alzheimer's disease impairs long term memories for related events (e.g. faces with names) more than for single events (e.g. list of faces or names). Whether or not this associative or ‘binding’ deficit is also found in short-term memory has not yet been explored. In two experiments we investigated binding deficits in verbal short-term memory in Alzheimer's disease. Experiment 1 : 23 patients with Alzheimer's disease and 23 age and education matched healthy elderly were recruited. Participants...

  2. Prosodic Similarity Effects in Short-Term Memory in Developmental Dyslexia.

    Science.gov (United States)

    Goswami, Usha; Barnes, Lisa; Mead, Natasha; Power, Alan James; Leong, Victoria

    2016-11-01

    Children with developmental dyslexia are characterized by phonological difficulties across languages. Classically, this 'phonological deficit' in dyslexia has been investigated with tasks using single-syllable words. Recently, however, several studies have demonstrated difficulties in prosodic awareness in dyslexia. Potential prosodic effects in short-term memory have not yet been investigated. Here we create a new instrument based on three-syllable words that vary in stress patterns, to investigate whether prosodic similarity (the same prosodic pattern of stressed and unstressed syllables) exerts systematic effects on short-term memory. We study participants with dyslexia and age-matched and younger reading-level-matched typically developing controls. We find that all participants, including dyslexic participants, show prosodic similarity effects in short-term memory. All participants exhibited better retention of words that differed in prosodic structure, although participants with dyslexia recalled fewer words accurately overall compared to age-matched controls. Individual differences in prosodic memory were predicted by earlier vocabulary abilities, by earlier sensitivity to syllable stress and by earlier phonological awareness. To our knowledge, this is the first demonstration of prosodic similarity effects in short-term memory. The implications of a prosodic similarity effect for theories of lexical representation and of dyslexia are discussed. © 2016 The Authors. Dyslexia published by John Wiley & Sons Ltd. © 2016 The Authors. Dyslexia published by John Wiley & Sons Ltd.

  3. Auditory-Cortex Short-Term Plasticity Induced by Selective Attention

    Science.gov (United States)

    Jääskeläinen, Iiro P.; Ahveninen, Jyrki

    2014-01-01

    The ability to concentrate on relevant sounds in the acoustic environment is crucial for everyday function and communication. Converging lines of evidence suggests that transient functional changes in auditory-cortex neurons, “short-term plasticity”, might explain this fundamental function. Under conditions of strongly focused attention, enhanced processing of attended sounds can take place at very early latencies (~50 ms from sound onset) in primary auditory cortex and possibly even at earlier latencies in subcortical structures. More robust selective-attention short-term plasticity is manifested as modulation of responses peaking at ~100 ms from sound onset in functionally specialized nonprimary auditory-cortical areas by way of stimulus-specific reshaping of neuronal receptive fields that supports filtering of selectively attended sound features from task-irrelevant ones. Such effects have been shown to take effect in ~seconds following shifting of attentional focus. There are findings suggesting that the reshaping of neuronal receptive fields is even stronger at longer auditory-cortex response latencies (~300 ms from sound onset). These longer-latency short-term plasticity effects seem to build up more gradually, within tens of seconds after shifting the focus of attention. Importantly, some of the auditory-cortical short-term plasticity effects observed during selective attention predict enhancements in behaviorally measured sound discrimination performance. PMID:24551458

  4. Short-term wind power combined forecasting based on error forecast correction

    International Nuclear Information System (INIS)

    Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

    2016-01-01

    Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

  5. Increased performance in the short-term water demand forecasting through the use of a parallel adaptive weighting strategy

    Science.gov (United States)

    Sardinha-Lourenço, A.; Andrade-Campos, A.; Antunes, A.; Oliveira, M. S.

    2018-03-01

    Recent research on water demand short-term forecasting has shown that models using univariate time series based on historical data are useful and can be combined with other prediction methods to reduce errors. The behavior of water demands in drinking water distribution networks focuses on their repetitive nature and, under meteorological conditions and similar consumers, allows the development of a heuristic forecast model that, in turn, combined with other autoregressive models, can provide reliable forecasts. In this study, a parallel adaptive weighting strategy of water consumption forecast for the next 24-48 h, using univariate time series of potable water consumption, is proposed. Two Portuguese potable water distribution networks are used as case studies where the only input data are the consumption of water and the national calendar. For the development of the strategy, the Autoregressive Integrated Moving Average (ARIMA) method and a short-term forecast heuristic algorithm are used. Simulations with the model showed that, when using a parallel adaptive weighting strategy, the prediction error can be reduced by 15.96% and the average error by 9.20%. This reduction is important in the control and management of water supply systems. The proposed methodology can be extended to other forecast methods, especially when it comes to the availability of multiple forecast models.

  6. PENGARUH KEDALAMAN AIR TERHADAP SHORT TERM MEMORY DAN KONSUMSI ENERGI PADA PENYELAM

    Directory of Open Access Journals (Sweden)

    Rini Dharmastiti

    2012-02-01

    Full Text Available Penelitian ini akan melihat pengaruh kedalaman air terhadap short term memory dan konsumsi energi penyelam. Penelitian ini mengambil sampel 10 mahasiswa pria dan 5 wanita. Pengukuran performansi short term memory dilakukan dengan cara setiap obyek diperlihatkan deretan 7 angka acak yang diberikan selama 5 detik dan setelah 15 detik kemudian dilakukan pemanggilan kembali informasi yang baru saja diberikan. Setiap obyek diuji sebangak 30 kali untuk setiap kedalaman (1 m; 2,5 m; dan 4 m. Pengukuran konsumsi energi dilakukan dengan menghitung denyut jantung menggunakan metode palpasi. Hasil penelitian menunjukkan bahwa semakin meningkat kedalaman air, maka performasi short term memory penyelam tersebut semakin menurun.  Penurunan ini berlaku untuk pria dan wanita. Penambahan kedalaman ini juga meningkatkan konsumsi energi baik pada pria maupun wanita. Perbedaan jenis kelamin mempengaruhi performansi short term memory secara signifikan. Pria memiliki performansi rata-rata short term memory sebesar 91,67% pada kedalaman 1 m, 90,67% pada kedalaman 2,5 m, dan 86,33% pada kedalaman 4 m. Sedangkan wanita memiliki performansi rata-rata sebesar 86% pada kedalaman 1 m, 84% pada kedalaman 2,5 m, dan 80,67% pada kedalaman 4 m. Rata-rata konsumsi energi pria adalah 3,19 kkal, 3,34 kkal, dan 3,65 kkal pada kedalaman 1 m; 2,5 m; dan 4 m berturut-turut. Sedangkan rata-rata konsumsi energi wanita adalah 3,81 kkal, 4,07 kkal, dan 4,54 kkal pada kedalaman yang sama dengan pria.     Kata kunci : tekanan, kedalaman air, performansi short term memory, konsumsi energi.       This research is to observe water depth effects on short term memory and energy expenditure of diver. This research objects are 10 male and 5 female students. Short term memory performance measurement held by every object has been shown 7 random numerics (as information for 5 seconds and after 15 seconds later they write down the information on a paper. Every object got 30 tests for every

  7. Implementing a short-term loyalty program : case: Bosch Lawn & Garden and the Ventum short-term loyalty program

    OpenAIRE

    Logvinova, Veronika

    2015-01-01

    In 2015, one of the Bosch Home and Garden divisions, Bosch Lawn and Garden, has made a strategic decision to adopt a points-based short-term loyalty program called Ventum LG in the German supermarkets and petrol stations. It was decided that the base of this program will be completed Ventum PT short-term loyalty program which was managed by another division, Bosch Power Tools, and proved to be successful. This thesis aims to evaluate the worthiness of the Ventum LG loyalty program for Bosch L...

  8. Real-time energy resources scheduling considering short-term and very short-term wind forecast

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

    2012-07-01

    This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

  9. Short-Term Effects of Playing Computer Games on Attention

    Science.gov (United States)

    Tahiroglu, Aysegul Yolga; Celik, Gonca Gul; Avci, Ayse; Seydaoglu, Gulsah; Uzel, Mehtap; Altunbas, Handan

    2010-01-01

    Objective: The main aim of the present study is to investigate the short-term cognitive effects of computer games in children with different psychiatric disorders and normal controls. Method: One hundred one children are recruited for the study (aged between 9 and 12 years). All participants played a motor-racing game on the computer for 1 hour.…

  10. Exogenous Attention Influences Visual Short-Term Memory in Infants

    Science.gov (United States)

    Ross-Sheehy, Shannon; Oakes, Lisa M.; Luck, Steven J.

    2011-01-01

    Two experiments examined the hypothesis that developing visual attentional mechanisms influence infants' Visual Short-Term Memory (VSTM) in the context of multiple items. Five- and 10-month-old infants (N = 76) received a change detection task in which arrays of three differently colored squares appeared and disappeared. On each trial one square…

  11. Retrieval-Induced Inhibition in Short-Term Memory.

    Science.gov (United States)

    Kang, Min-Suk; Choi, Joongrul

    2015-07-01

    We used a visual illusion called motion repulsion as a model system for investigating competition between two mental representations. Subjects were asked to remember two random-dot-motion displays presented in sequence and then to report the motion directions for each. Remembered motion directions were shifted away from the actual motion directions, an effect similar to the motion repulsion observed during perception. More important, the item retrieved second showed greater repulsion than the item retrieved first. This suggests that earlier retrieval exerted greater inhibition on the other item being held in short-term memory. This retrieval-induced motion repulsion could be explained neither by reduced cognitive resources for maintaining short-term memory nor by continued inhibition between short-term memory representations. These results indicate that retrieval of memory representations inhibits other representations in short-term memory. We discuss mechanisms of retrieval-induced inhibition and their implications for the structure of memory. © The Author(s) 2015.

  12. The Precategorical Nature of Visual Short-Term Memory

    Science.gov (United States)

    Quinlan, Philip T.; Cohen, Dale J.

    2016-01-01

    We conducted a series of recognition experiments that assessed whether visual short-term memory (VSTM) is sensitive to shared category membership of to-be-remembered (tbr) images of common objects. In Experiment 1 some of the tbr items shared the same basic level category (e.g., hand axe): Such items were no better retained than others. In the…

  13. Pigeon visual short-term memory directly compared to primates.

    Science.gov (United States)

    Wright, Anthony A; Elmore, L Caitlin

    2016-02-01

    Three pigeons were trained to remember arrays of 2-6 colored squares and detect which of two squares had changed color to test their visual short-term memory. Procedures (e.g., stimuli, displays, viewing times, delays) were similar to those used to test monkeys and humans. Following extensive training, pigeons performed slightly better than similarly trained monkeys, but both animal species were considerably less accurate than humans with the same array sizes (2, 4 and 6 items). Pigeons and monkeys showed calculated memory capacities of one item or less, whereas humans showed a memory capacity of 2.5 items. Despite the differences in calculated memory capacities, the pigeons' memory results, like those from monkeys and humans, were all well characterized by an inverse power-law function fit to d' values for the five display sizes. This characterization provides a simple, straightforward summary of the fundamental processing of visual short-term memory (how visual short-term memory declines with memory load) that emphasizes species similarities based upon similar functional relationships. By closely matching pigeon testing parameters to those of monkeys and humans, these similar functional relationships suggest similar underlying processes of visual short-term memory in pigeons, monkeys and humans. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. SHORT-TERM MEMORY IS INDEPENDENT OF BRAIN PROTEIN SYNTHESIS

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Hasker P.; Rosenzweig, Mark R.; Jones, Oliver W.

    1980-09-01

    Male Swiss albino CD-1 mice given a single injection of a cerebral protein synthesis inhibitor, anisomycin (ANI) (1 mg/animal), 20 min prior to single trial passive avoidance training demonstrated impaired retention at tests given 3 hr, 6 hr, 1 day, and 7 days after training. Retention was not significantly different from saline controls when tests were given 0.5 or 1.5 hr after training. Prolonging inhibition of brain protein synthesis by giving either 1 or 2 additional injections of ANI 2 or 2 and 4 hr after training did not prolong short-term retention performance. The temporal development of impaired retention in ANI treated mice could not be accounted for by drug dosage, duration of protein synthesis inhibition, or nonspecific sickness at test. In contrast to the suggestion that protein synthesis inhibition prolongs short-term memory (Quinton, 1978), the results of this experiment indicate that short-term memory is not prolonged by antibiotic drugs that inhibit cerebral protein synthesis. All evidence seems consistent with the hypothesis that short-term memory is protein synthesis independent and that the establishment of long-term memory depends upon protein synthesis during or shortly after training. Evidence for a role of protein synthesis in memory maintenance is discussed.

  15. Short-term robustness of production management systems

    NARCIS (Netherlands)

    Kleijnen, J.P.C.; Gaury, E.G.A.

    1998-01-01

    Short-term performance of a production management system for make-to-stock factories may be quantified through the service rate per shift; long-term performance through the average monthly work in process (WIP). This may yield, for example, that WIP is minimized, while the probability of the service

  16. 22 CFR 62.21 - Short-term scholars.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Short-term scholars. 62.21 Section 62.21 Foreign Relations DEPARTMENT OF STATE PUBLIC DIPLOMACY AND EXCHANGES EXCHANGE VISITOR PROGRAM Specific... programs, confer on common problems and projects, and promote professional relationships and communications...

  17. Short-term energy outlook annual supplement, 1993

    International Nuclear Information System (INIS)

    1993-01-01

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the third quarter of 1993 through the fourth quarter of 1994. Values for the second quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding

  18. Short-term feeding strategies and pork quality

    NARCIS (Netherlands)

    Geesink, G.H.; Buren, van R.G.C.; Savenije, B.; Verstegen, M.W.A.; Ducro, B.J.; Palen, van der J.G.P.; Hemke, G.

    2004-01-01

    Two experiments were done to determine whether short-term supplementation (5 days pre-slaughter) with magnesium acetate, or a combination of magnesium acetate, tryptophan, vitamin E and vitamin C would improve pork quality. In the first experiment the pigs (Pietrain x Yorkshire, n = 96) were fed a

  19. Retention interval affects visual short-term memory encoding.

    Science.gov (United States)

    Bankó, Eva M; Vidnyánszky, Zoltán

    2010-03-01

    Humans can efficiently store fine-detailed facial emotional information in visual short-term memory for several seconds. However, an unresolved question is whether the same neural mechanisms underlie high-fidelity short-term memory for emotional expressions at different retention intervals. Here we show that retention interval affects the neural processes of short-term memory encoding using a delayed facial emotion discrimination task. The early sensory P100 component of the event-related potentials (ERP) was larger in the 1-s interstimulus interval (ISI) condition than in the 6-s ISI condition, whereas the face-specific N170 component was larger in the longer ISI condition. Furthermore, the memory-related late P3b component of the ERP responses was also modulated by retention interval: it was reduced in the 1-s ISI as compared with the 6-s condition. The present findings cannot be explained based on differences in sensory processing demands or overall task difficulty because there was no difference in the stimulus information and subjects' performance between the two different ISI conditions. These results reveal that encoding processes underlying high-precision short-term memory for facial emotional expressions are modulated depending on whether information has to be stored for one or for several seconds.

  20. Managing Transit Ridership with Short-Term Economic Incentives

    Science.gov (United States)

    1982-08-01

    It is the purpose of this booklet to give the reader an overview of the variety, : type, and nature of short-term economic incentive programs that have been : introduced by transit properties over the past few years. 3054k, 55p.

  1. Short-Term Memory, Executive Control, and Children's Route Learning

    Science.gov (United States)

    Purser, Harry R. M.; Farran, Emily K.; Courbois, Yannick; Lemahieu, Axelle; Mellier, Daniel; Sockeel, Pascal; Blades, Mark

    2012-01-01

    The aim of this study was to investigate route-learning ability in 67 children aged 5 to 11 years and to relate route-learning performance to the components of Baddeley's model of working memory. Children carried out tasks that included measures of verbal and visuospatial short-term memory and executive control and also measures of verbal and…

  2. Short-term outcomes following laparoscopic resection for colon cancer.

    LENUS (Irish Health Repository)

    Kavanagh, Dara O

    2011-03-01

    Laparoscopic resection for colon cancer has been proven to have a similar oncological efficacy compared to open resection. Despite this, it is performed by a minority of colorectal surgeons. The aim of our study was to evaluate the short-term clinical, oncological and survival outcomes in all patients undergoing laparoscopic resection for colon cancer.

  3. Labeling, Rehearsal, and Short-Term Memory in Retarded Children

    Science.gov (United States)

    Hagen, John W.; And Others

    1974-01-01

    A short-term memory task was used to explore the effects of verbal labeling and rehearsal on serial-position recall in mildly retarded 9-to 11-year-old children. Results support the view that verbal skills affect recall in mildly retarded children similarly to normal children. (Author/SDH)

  4. Short-Term Energy Outlook: Quarterly projections. Fourth quarter 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-11-05

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the fourth quarter of 1993 through the fourth quarter of 1994. Values for the third quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications.

  5. Short-term mechanisms influencing volumetric brain dynamics

    NARCIS (Netherlands)

    Dieleman, Nikki; Koek, Huiberdina L.; Hendrikse, Jeroen

    2017-01-01

    With the use of magnetic resonance imaging (MRI) and brain analysis tools, it has become possible to measure brain volume changes up to around 0.5%. Besides long-term brain changes caused by atrophy in aging or neurodegenerative disease, short-term mechanisms that influence brain volume may exist.

  6. Short-term variations of radiocarbon during the last century

    International Nuclear Information System (INIS)

    Burchuladze, A.A.; Pagava, S.V.; Jurina, V.; Povinec, P.; Usacev, S.

    1982-01-01

    Radiocarbon variations related to the 11-year solar cycle during the last century are discussed. Previous investigations on short term 14 C variations in tree rings are compared with 14 C measurements in Georgian wine samples. The amplitude of 14 C variations as obtained by various authors ranges from 0.2 to about 1%. (author)

  7. Proactive Interference in Short-Term Recognition and Recall Memory

    Science.gov (United States)

    Dillon, Richard F.; Petrusic, William M.

    1972-01-01

    Purpose of study was to (a) compare the rate of increase of proactive interference over the first few trials under recall and recognition memory test conditions, (2) determine the effects of two types of distractors on short-term recognition, and (3) test memory after proactive interference had reached a stable level under each of three test…

  8. Short-Term Effects of Televised Aggression on Children's Behavior.

    Science.gov (United States)

    Liebert, Robert M.; Baron, Robert A.

    Recently collected data appear to warrant advancing some tentative conslusions concerning the short-term effects of violence in television on children: 1) children are exposed to a substantial amount of violent content on television, and they can remember and learn from such exposure; 2) correlational studies have disclosed a regular association…

  9. Short term clinical outcome of children with rotavirus infection at ...

    African Journals Online (AJOL)

    Background: Rotavirus infection is the single most common cause of acute gastroenteritis in children under five years of age. Rotavirus gastroenteritis has a high morbidity and mortality in children in Kenya. Objectives: To determine the short term clinical outcome for children admitted to Kenyatta National Hospital with ...

  10. Short-term effects of radiation in gliolalstoma spheroids

    DEFF Research Database (Denmark)

    Petterson, Stine Asferg; Jakobsen, Ida Pind; Jensen, Stine Skov

    2016-01-01

    was to investigate the short-term effects of radiation of spheroids containing tumor-initiating stem-like cells. We used a patient-derived glioblastoma stem cell enriched culture (T76) and the standard glioblastoma cell line U87. Primary spheroids were irradiated with doses between 2 and 50 Gy and assessed after two...

  11. Panorama 2012 - Short-term trends in the gas industry

    International Nuclear Information System (INIS)

    Lecarpentier, Armelle

    2011-12-01

    Against the background of an energy market beset by the Fukushima crisis, the Arab spring and economic uncertainty, 2011 saw dynamic growth in demand for natural gas, although developments varied widely from region to region. New trends are emerging in the gas market, and these will have both short-term and longer-term impacts on how the industry develops. (author)

  12. Insulin Resistance Induced by Short term Fructose Feeding may not ...

    African Journals Online (AJOL)

    Fructose feeding causes insulin resistance and invariably Non-Insulin Dependent Diabetes Mellitus (NIDDM) in rats and genetically predisposed humans. The effect of insulin resistance induced by short term fructose feeding on fertility in female rats was investigated using the following parameters: oestrous phase and ...

  13. Histopathologic characteristics and short-term outcomes of ...

    African Journals Online (AJOL)

    Introduction: Colorectal carcinoma (CRC) is generally a disease of persons older than 40 years. Concerning younger patients, controversies still exist regarding features and prognosis of CRC. We performed this study to characterise CRC in young patients (≤40 years) as well as to evaluate short-term outcome in ...

  14. Short-term energy outlook: Quarterly projections, Third quarter 1992

    International Nuclear Information System (INIS)

    1992-08-01

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to 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 forecast period for this issue of the Outlook extends from the third quarter of 1992 through the fourth quarter of 1993. Values for the second quarter of 1992, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding

  15. Panorama 2013 - Short term trends in the gas industry

    International Nuclear Information System (INIS)

    Lecarpentier, Armelle

    2012-10-01

    The outlook for gas industry development in the short term is clouded by uncertainties (impact of the economic slowdown, competition between energies, price fluctuations, etc.). However, as in 2012, many favorable factors in terms of natural gas supply and demand point to sustained and sustainable growth of this energy. (author)

  16. Orienting attention to objects in visual short-term memory

    NARCIS (Netherlands)

    Dell'Acqua, Roberto; Sessa, Paola; Toffanin, Paolo; Luria, Roy; Joliccoeur, Pierre

    We measured electroencephalographic activity during visual search of a target object among objects available to perception or among objects held in visual short-term memory (VSTM). For perceptual search, a single shape was shown first (pre-cue) followed by a search-array and the task was to decide

  17. SHORT-TERM EFFECT OF DIESEL OIL ON PHYTOPLANKTON

    African Journals Online (AJOL)

    PROF. EKWEME

    Short-term effect of Nigerian diesel oil was tested on the phytoplankton species in Great Kwa River ... aquatic environment. Plant life is the basis of all food web in nature and hence constitutes the makes this fundamental contribution by photosynthesis, utilizing radiant energy to .... (2 cells/ml) re-colonized the area. The three ...

  18. Are there multiple visual short-term memory stores?

    NARCIS (Netherlands)

    Sligte, I.G.; Scholte, H.S.; Lamme, V.A.F.

    2008-01-01

    Background: Classic work on visual short-term memory (VSTM) suggests that people store a limited amount of items for subsequent report. However, when human observers are cued to shift attention to one item in VSTM during retention, it seems as if there is a much larger representation, which keeps

  19. Short Term Group Counseling of Visually Impaired People by Telephone.

    Science.gov (United States)

    Jaureguy, Beth M.; Evans, Ron L.

    1983-01-01

    Short term group counseling via the telephone resulted in marked increases in activities of daily living among 12 legally blind veterans. Many subjects' personal coping goals were met as well, and social involvement also increased. No significant changes in levels of depression or agitation were noted. (CL)

  20. High-intensity exercise and recovery during short-term ...

    African Journals Online (AJOL)

    Objective. To determine the effect of short-term creatine supplementation plus a protein-carbohydrate formula on high-intensity exercise performance and recovery. Design. A repeated-measures, experimental study, employing a randomised, double-blind, placebo-controlled, group comparison design was used.

  1. Can Metabolic Factors be used Prognostically for Short.Term ...

    African Journals Online (AJOL)

    to be promising short.term mortality markers in HIV patients apart from established factors like low CD4 counts, co.morbid conditions, and opportunistic infections like M. tuberculosis infection. This study warrants further studies with a larger sample size to establish HDL and triglyceride as markers of disease progression and ...

  2. Neural circuit mechanisms of short-term memory

    Science.gov (United States)

    Goldman, Mark

    Memory over time scales of seconds to tens of seconds is thought to be maintained by neural activity that is triggered by a memorized stimulus and persists long after the stimulus is turned off. This presents a challenge to current models of memory-storing mechanisms, because the typical time scales associated with cellular and synaptic dynamics are two orders of magnitude smaller than this. While such long time scales can easily be achieved by bistable processes that toggle like a flip-flop between a baseline and elevated-activity state, many neuronal systems have been observed experimentally to be capable of maintaining a continuum of stable states. For example, in neural integrator networks involved in the accumulation of evidence for decision making and in motor control, individual neurons have been recorded whose activity reflects the mathematical integral of their inputs; in the absence of input, these neurons sustain activity at a level proportional to the running total of their inputs. This represents an analog form of memory whose dynamics can be conceptualized through an energy landscape with a continuum of lowest-energy states. Such continuous attractor landscapes are structurally non-robust, in seeming violation of the relative robustness of biological memory systems. In this talk, I will present and compare different biologically motivated circuit motifs for the accumulation and storage of signals in short-term memory. Challenges to generating robust memory maintenance will be highlighted and potential mechanisms for ameliorating the sensitivity of memory networks to perturbations will be discussed. Funding for this work was provided by NIH R01 MH065034, NSF IIS-1208218, Simons Foundation 324260, and a UC Davis Ophthalmology Research to Prevent Blindness Grant.

  3. Association between early attention-deficit/hyperactivity symptoms and current verbal and visuo-spatial short-term memory.

    Science.gov (United States)

    Gau, Susan Shur-Fen; Chiang, Huey-Ling

    2013-01-01

    Deficits in short-term memory are common in adolescents with attention-deficit/hyperactivity disorder (ADHD), but their current ADHD symptoms cannot well predict their short-term performance. Taking a developmental perspective, we wanted to clarify the association between ADHD symptoms at early childhood and short-term memory in late childhood and adolescence. The participants included 401 patients with a clinical diagnosis of DSM-IV ADHD, 213 siblings, and 176 unaffected controls aged 8-17 years (mean age, 12.02 ± 2.24). All participants and their mothers were interviewed using the Chinese Kiddie Epidemiologic version of the Schedule for Affective Disorders and Schizophrenia to obtain information about ADHD symptoms and other psychiatric disorders retrospectively, at an earlier age first, then currently. The participants were assessed with the Wechsler Intelligence Scale for Children--3rd edition, including Digit Span, and the Spatial working memory task of the Cambridge Neuropsychological Test Automated Battery. Multi-level regression models were used for data analysis. Although crude analyses revealed that inattention, hyperactivity, and impulsivity symptoms significantly predicted deficits in short-term memory, only inattention symptoms had significant effects (all pshort-term memory at the current assessment. Therefore, our findings suggest that earlier inattention symptoms are associated with impaired verbal and visuo-spatial short-term memory at a later development stage. Impaired short-term memory in adolescence can be detected earlier by screening for the severity of inattention in childhood. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. From probabilistic forecasts to statistical scenarios of short-term wind power production

    DEFF Research Database (Denmark)

    Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

    2009-01-01

    on the development of the forecast uncertainty through forecast series. However, this additional information may be paramount for a large class of time-dependent and multistage decision-making problems, e.g. optimal operation of combined wind-storage systems or multiple-market trading with different gate closures......Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with highly valuable information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform....... This issue is addressed here by describing a method that permits the generation of statistical scenarios of short-term wind generation that accounts for both the interdependence structure of prediction errors and the predictive distributions of wind power production. The method is based on the conversion...

  5. A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

    Science.gov (United States)

    Bao, Wei; Yue, Jun; Rao, Yulei

    2017-01-01

    The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

  6. A deep learning framework for financial time series using stacked autoencoders and long-short term memory

    Science.gov (United States)

    Bao, Wei; Rao, Yulei

    2017-01-01

    The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day’s closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance. PMID:28708865

  7. A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

    Directory of Open Access Journals (Sweden)

    Wei Bao

    Full Text Available The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT, stacked autoencoders (SAEs and long-short term memory (LSTM are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

  8. Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application

    OpenAIRE

    Mingfei Niu; Shaolong Sun; Jie Wu; Yuanlei Zhang

    2015-01-01

    The accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, due to the strong stochastic nature and dynamic uncertainty of wind speed, the forecasting of wind speed data using different patterns is difficult. This paper proposes a novel combination bias c...

  9. Short-term lending: Payday loans as risk factors for anxiety, inflammation and poor health.

    Science.gov (United States)

    Sweet, Elizabeth; Kuzawa, Christopher W; McDade, Thomas W

    2018-08-01

    While research now consistently links consumer financial debt with adverse emotional health outcomes, specific forms of debt and their impact on measures of physical health are underexplored. This gap in knowledge is significant because different forms of loans and debt may have different experiential qualities. In this paper, we focus on a type of unsecured debt - short-term/payday loan borrowing - that has risen dramatically in recent decades in the United States and is characterized by predatory, discriminatory, and poorly regulated lending practices. Using data from a study of debt and health among adults in Boston, MA (n=286), we test whether short-term borrowing is associated with a range of emotional and physical health indicators. We find that short-term loans are associated with higher body mass index, waist circumference, C-reactive protein levels, and self-reported symptoms of physical health, sexual health, and anxiety, after controlling for several socio-demographic covariates. We discuss these findings within the contexts of regulatory shortcomings, psychosocial stress, and racial and economic credit disparities. We suggest that within the broader context of financial debt and health, short-term loans should be considered a specific risk to population health.

  10. Short term and medium term power distribution load forecasting by neural networks

    International Nuclear Information System (INIS)

    Yalcinoz, T.; Eminoglu, U.

    2005-01-01

    Load forecasting is an important subject for power distribution systems and has been studied from different points of view. In general, load forecasts should be performed over a broad spectrum of time intervals, which could be classified into short term, medium term and long term forecasts. Several research groups have proposed various techniques for either short term load forecasting or medium term load forecasting or long term load forecasting. This paper presents a neural network (NN) model for short term peak load forecasting, short term total load forecasting and medium term monthly load forecasting in power distribution systems. The NN is used to learn the relationships among past, current and future temperatures and loads. The neural network was trained to recognize the peak load of the day, total load of the day and monthly electricity consumption. The suitability of the proposed approach is illustrated through an application to real load shapes from the Turkish Electricity Distribution Corporation (TEDAS) in Nigde. The data represents the daily and monthly electricity consumption in Nigde, Turkey

  11. Ordered Short-Term Memory Differs in Signers and Speakers: Implications for Models of Short-Term Memory

    Science.gov (United States)

    Bavelier, Daphne; Newport, Elissa L.; Hall, Matt; Supalla, Ted; Boutla, Mrim

    2008-01-01

    Capacity limits in linguistic short-term memory (STM) are typically measured with forward span tasks in which participants are asked to recall lists of words in the order presented. Using such tasks, native signers of American Sign Language (ASL) exhibit smaller spans than native speakers ([Boutla, M., Supalla, T., Newport, E. L., & Bavelier, D.…

  12. Role of self-efficacy and social support in short-term recovery after total hip replacement: a prospective cohort study.

    Science.gov (United States)

    Brembo, Espen Andreas; Kapstad, Heidi; Van Dulmen, Sandra; Eide, Hilde

    2017-04-11

    Despite the overall success of total hip replacement (THR) in patients with symptomatic osteoarthritis (OA), up to one-quarter of patients report suboptimal recovery. The aim of this study was to determine whether social support and general self-efficacy predict variability in short-term recovery in a Norwegian cohort. We performed secondary analysis of a prospective multicenter study of 223 patients who underwent THR for OA in 2003-2004. The total score of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at 3 months after surgery was used as the recovery variable. We measured self-efficacy using the General Self-Efficacy Scale (GSES) and social support with the Social Provisions Scale (SPS). Preoperative and postoperative scores were compared using Wilcoxon tests. The Mann-Whitney U test compared scores between groups that differed in gender and age. Spearman's rho correlation coefficients were used to evaluate associations between selected predictor variables and the recovery variable. We performed univariate and multiple linear regression analyses to identify independent variables and their ability to predict short-term recovery after THR. The median preoperative WOMAC score was 58.3 before and 23.9 after surgery. The mean absolute change was 31.9 (standard deviation [SD] 17.0) and the mean relative change was 54.8% (SD 26.6). Older age, female gender, higher educational level, number of comorbidities, baseline WOMAC score, self-efficacy, and three of six individual provisions correlated significantly with short-term recovery after THR and predicted the variability in recovery in the univariate regression model. In multiple regression models, baseline WOMAC was the most consistent predictor of short-term recovery: a higher preoperative WOMAC score predicted worse short-term recovery (β = 0.44 [0.29, 0.59]). Higher self-efficacy predicted better recovery (β = -0.44 [-0.87, -0.02]). Reliable alliance was a significant predictor

  13. Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

    OpenAIRE

    Li, Xiangang; Wu, Xihong

    2014-01-01

    Long short-term memory (LSTM) based acoustic modeling methods have recently been shown to give state-of-the-art performance on some speech recognition tasks. To achieve a further performance improvement, in this research, deep extensions on LSTM are investigated considering that deep hierarchical model has turned out to be more efficient than a shallow one. Motivated by previous research on constructing deep recurrent neural networks (RNNs), alternative deep LSTM architectures are proposed an...

  14. Verbal short-term memory in individuals with chromosome 22q11.2 deletion: Specific deficit in serial order retention capacities?

    OpenAIRE

    Majerus, Steve; Van der Linden, Martial; Braissand, V.; Eliez, S.

    2007-01-01

    Many researchers have recently explored the cognitive profile of velocardiofacial syndrome (VCFS), a neurodevelopmental disorder linked to a 22q11.2 deletion. However, verbal short-term memory has not yet been systematically investigated. We explored verbal short-term memory abilities in a group of 11 children and adults presenting with VCFS and two control groups, matched on either CA or vocabulary knowledge, by distinguishing short-term memory for serial order and item information. The VCFS...

  15. Sentence Comprehension in Adolescents with down Syndrome and Typically Developing Children: Role of Sentence Voice, Visual Context, and Auditory-Verbal Short-Term Memory.

    Science.gov (United States)

    Miolo, Giuliana; Chapman, Robins S.; Sindberg, Heidi A.

    2005-01-01

    The authors evaluated the roles of auditory-verbal short-term memory, visual short-term memory, and group membership in predicting language comprehension, as measured by an experimental sentence comprehension task (SCT) and the Test for Auditory Comprehension of Language--Third Edition (TACL-3; E. Carrow-Woolfolk, 1999) in 38 participants: 19 with…

  16. Maternal haemoglobin and short-term neonatal outcome in preterm neonates.

    Directory of Open Access Journals (Sweden)

    Elodie Savajols

    Full Text Available To determine whether there is a significant association between maternal haemoglobin measured before delivery and short-term neonatal outcome in very preterm neonates.We included prospectively all live births occurring from 25 to 32+6 weeks of gestation in a tertiary care centre between January 1(st 2009 and December 31(st 2011. Outborn infants and infants presenting with lethal malformations were excluded. Three hundred and thirty-nine mothers and 409 infants met the inclusion criteria. For each mother-infant pair a prospective record of epidemiologic data was performed and maternal haemoglobin concentration recorded within 24 hours before delivery was retrospectively researched. Maternal haemoglobin was divided into quartiles with the second and the third one regarded as reference as they were composed of normal haemoglobin values. Short-term outcome was defined as poor in case of death during hospital stay and/or grades III/IV intraventricular haemorrhage and/or periventricular leukomalacia and/or necessity of ventriculoperitoneal shunt.The global rate of poor short-term neonatal outcome was 11.4% and was significantly associated with low maternal haemoglobin values. This association remained significant after adjustment for antenatal corticosteroids therapy, gestational age, parity, mechanism of preterm birth, mode of delivery and birth weight (aOR = 2.97 CI 95% [1.36-6.47]. There was no relation between short-term neonatal outcome and high maternal haemoglobin concentration values.We show that low maternal haemoglobin concentration at delivery is an independent risk factor for poor short-term neonatal outcome in very preterm neonates. This study is one of the first to show such an association within the preterm population.

  17. The short-term impacts of Earned Income Tax Credit disbursement on health.

    Science.gov (United States)

    Rehkopf, David H; Strully, Kate W; Dow, William H

    2014-12-01

    There are conflicting findings regarding long- and short-term effects of income on health. Whereas higher average income is associated with better health, there is evidence that health behaviours worsen in the short-term following income receipt.Prior studies revealing such negative short-term effects of income receipt focus on specific subpopulations and examine a limited set of health outcomes. The United States Earned Income Tax Credit (EITC) is an income supplement tied to work, and is the largest poverty reduction programme in the USA. We utilize the fact that EITC recipients typically receive large cash transfers in the months of February,March and April, in order to examine associated changes in health outcomes that can fluctuate on a monthly basis. We examine associations with 30 outcomes in the categories of diet, food security, health behaviours, cardiovascular biomarkers, metabolic biomarkers and infection and immunity among 6925 individuals from the U.S. National Health and Nutrition Survey. Our research design approximates a natural experiment,since whether individuals were sampled during treatment or non-treatment months is independent of social, demographic and health characteristics that do not vary with time. There are both beneficial and detrimental short-term impacts of income receipt.Although there are detrimental impacts on metabolic factors among women, most other impacts are beneficial, including those for food security, smoking and trying to lose weight. The short-term impacts of EITC income receipt are not universally health promoting, but on balance there are more health benefits than detriments.

  18. The suitability of short-term measurements of radon in the built environment

    International Nuclear Information System (INIS)

    Denman, A.R.; Groves-Kirkby, C.J.; Phillips, P.S.; Crockett, R.G.M.; Woolridge, A.C.

    2008-01-01

    Although domestic and workplace radon concentration levels often show marked diurnal/short-term variation, overall health risk is determined by the long-term average level, and many national protocols advocate the use of long exposure periods, usually three months, to assess long-term risk. Simple passive measurement techniques, e.g. track-etch, activated charcoal and electret, can, however, provide reasonably accurate determinations with exposures as short as one week, and there is pressure from users and stake holders for assessments within this time period. We report evaluation of the effectiveness of one-week, one-month and three-month exposures over a period of one year in a designated Radon Affected Area in the United Kingdom (UK). Although short-term exposures did not compromise measurement accuracy, short-term radon variability rendered one-week measurements less reliable in predicting annual average radon levels via the conventional methodology. Analysis permitted estimation of the maximum and minimum short-term measured domestic radon concentrations at which there was 95% probability of the predicted annual average being below or above the UK Action Level of 200 Bq·m -3 respectively. Between these limits, the short-term result is equivocal, requiring repetition, and the 'equivocal range' for one-week measurements is significantly wider than for three-month exposures. In any geographical area, domestic radon concentrations are distributed log normally, with many properties having low average levels; a small number exhibit excessive levels, and this distribution must be considered when defining exposures for a radon measurement programme. In low-radon areas, where 1% of houses might exceed the Action Level, a one-week assessment will find that fewer outcomes are equivocal. For high-radon areas, with 20% or more houses over the Action Level, more than 50% of one-week outcomes will be equivocal, requiring repeats. The results of this work will be presented

  19. Visual dot interaction with short-term memory.

    Science.gov (United States)

    Etindele Sosso, Faustin Armel

    2017-06-01

    Many neurodegenerative diseases have a memory component. Brain structures related to memory are affected by environmental stimuli, and it is difficult to dissociate effects of all behavior of neurons. Here, visual cortex of mice was stimulated with gratings and dot, and an observation of neuronal activity before and after was made. Bandwidth, firing rate and orientation selectivity index were evaluated. A primary communication between primary visual cortex and short-term memory appeared to show an interesting path to train cognitive circuitry and investigate the basics mechanisms of the neuronal learning. The findings also suggested the interplay between primary visual cortex and short-term plasticity. The properties inside a visual target shape the perception and affect the basic encoding. Using visual cortex, it may be possible to train the memory and improve the recovery of people with cognitive disabilities or memory deficit.

  20. Short-term uranium price formation: a methodology

    International Nuclear Information System (INIS)

    Hsieh, L.Y.; de Graffenried, C.L.

    1987-01-01

    One of the major problems in analyzing the short-term uranium market is the lack of a well-defined spot market price. The two primary sources of price data covering the US uranium market are the series published by the US Dept. of Energy (DOE) and by the Nuclear Exchange Corporation (NUEXCO), a private brokerage firm. Because of the differences in both definition and coverage, these two series are not directly comparable. In this study, an econometric model was developed for analyzing the interrelationship between short-term uranium price (NUEXCO exchange value), supply, demand, and future price expectations formed by market participants. The validity of this model has been demonstrated by the fact that all simulation statistics derived are highly significant. Three forecasting scenarios were developed in this study

  1. Short-Term Wind Speed Forecasting for Power System Operations

    KAUST Repository

    Zhu, Xinxin

    2012-04-01

    The emphasis on renewable energy and concerns about the environment have led to large-scale wind energy penetration worldwide. However, there are also significant challenges associated with the use of wind energy due to the intermittent and unstable nature of wind. High-quality short-term wind speed forecasting is critical to reliable and secure power system operations. This article begins with an overview of the current status of worldwide wind power developments and future trends. It then reviews some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented. © 2012 The Authors. International Statistical Review © 2012 International Statistical Institute.

  2. Short-term fasting protects mice against γ ray radiation

    International Nuclear Information System (INIS)

    Zhu Shengnan; Gu Xiuling; Song Lian; Tong Jian; Li Jianxiang

    2012-01-01

    Objective: To investigate the antagonistic effects of short-term fasting against 60 Co γ ray radiation. Methods: After fasting ICR mice were irradiated for 3 min at a dose rate of 2.5 Gy/min and then returned to normal diet. General situation, body weight changes, food consumption and toxic status were observed. WBC, organ index and anti-oxidative ability (ROS, SOD, MDA, T-AOC) were analyzed. Results: After 60 Co γ ray radiation, the mice exhibited severe toxic symptoms before death. The survival rates were 0 for control and 12 h group, 12.5% for 48 h group and 50% for 72 h group respectively. ROS production of 72 h group was reduced compared with 0 h group (P<0.05). Conclusion: Short-term fasting may attenuate radiation induced injuries, evidenced by a significant increase in mice survival rate. (authors)

  3. Short-term synaptic plasticity and heterogeneity in neural systems

    Science.gov (United States)

    Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

    2013-01-01

    We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

  4. The epidemiology of long- and short-term cancer survivors

    DEFF Research Database (Denmark)

    Jarlbæk, Lene; Christensen, Linda; Bruera, Eduardo

    2014-01-01

    Introduction. In this study, we present data from a population-based cohort of incident cancer patients separated in long- and short-term survivors. Our aim was to procure denominators for use in the planning of rehabilitation and palliative care programs. Material and methods. A registry......-linkage cohort study. All cancer patients, diagnosed from 1993 to 2003 from a 470 000 large population, were followed individually from diagnosis to death or until 31 December 2008. Long-term survivors lived five years or more after the time of the cancer diagnosis (TOCD). Short-term survivors died less than...... and sex. Two-year crude cancer survival seems as a clinically relevant cut point for characterizing potential "denominators" for rehabilitation or palliative care programs. From this cohort of incident cancer patients, and using two-year survival as a cut point, it could be estimated that 54% would...

  5. Short-term depression and transient memory in sensory cortex.

    Science.gov (United States)

    Gillary, Grant; Heydt, Rüdiger von der; Niebur, Ernst

    2017-12-01

    Persistent neuronal activity is usually studied in the context of short-term memory localized in central cortical areas. Recent studies show that early sensory areas also can have persistent representations of stimuli which emerge quickly (over tens of milliseconds) and decay slowly (over seconds). Traditional positive feedback models cannot explain sensory persistence for at least two reasons: (i) They show attractor dynamics, with transient perturbations resulting in a quasi-permanent change of system state, whereas sensory systems return to the original state after a transient. (ii) As we show, those positive feedback models which decay to baseline lose their persistence when their recurrent connections are subject to short-term depression, a common property of excitatory connections in early sensory areas. Dual time constant network behavior has also been implemented by nonlinear afferents producing a large transient input followed by much smaller steady state input. We show that such networks require unphysiologically large onset transients to produce the rise and decay observed in sensory areas. Our study explores how memory and persistence can be implemented in another model class, derivative feedback networks. We show that these networks can operate with two vastly different time courses, changing their state quickly when new information is coming in but retaining it for a long time, and that these capabilities are robust to short-term depression. Specifically, derivative feedback networks with short-term depression that acts differentially on positive and negative feedback projections are capable of dynamically changing their time constant, thus allowing fast onset and slow decay of responses without requiring unrealistically large input transients.

  6. Short-term electric load forecasting using computational intelligence methods

    OpenAIRE

    Jurado, Sergio; Peralta, J.; Nebot, Àngela; Mugica, Francisco; Cortez, Paulo

    2013-01-01

    Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, Evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out...

  7. The Development of Rehearsal in Verbal Short-Term Memory

    OpenAIRE

    Jarrold, Christopher; Hall, Debbora

    2013-01-01

    Verbal short-term memory, as indexed by immediate serial recall tasks (in which participants must recall several stimuli in order, immediately after presentation), develops considerably across middle childhood. One explanation for this age-related change is that children's ability to rehearse verbal material increases during this period, and one particularly influential version of this account is that only older children engage in any form of rehearsal. In this article, we critique evidence t...

  8. Auditory short-term memory activation during score reading.

    Science.gov (United States)

    Simoens, Veerle L; Tervaniemi, Mari

    2013-01-01

    Performing music on the basis of reading a score requires reading ahead of what is being played in order to anticipate the necessary actions to produce the notes. Score reading thus not only involves the decoding of a visual score and the comparison to the auditory feedback, but also short-term storage of the musical information due to the delay of the auditory feedback during reading ahead. This study investigates the mechanisms of encoding of musical information in short-term memory during such a complicated procedure. There were three parts in this study. First, professional musicians participated in an electroencephalographic (EEG) experiment to study the slow wave potentials during a time interval of short-term memory storage in a situation that requires cross-modal translation and short-term storage of visual material to be compared with delayed auditory material, as it is the case in music score reading. This delayed visual-to-auditory matching task was compared with delayed visual-visual and auditory-auditory matching tasks in terms of EEG topography and voltage amplitudes. Second, an additional behavioural experiment was performed to determine which type of distractor would be the most interfering with the score reading-like task. Third, the self-reported strategies of the participants were also analyzed. All three parts of this study point towards the same conclusion according to which during music score reading, the musician most likely first translates the visual score into an auditory cue, probably starting around 700 or 1300 ms, ready for storage and delayed comparison with the auditory feedback.

  9. Short-term marginal costs in French agriculture

    OpenAIRE

    Latruffe, Laure; LETORT, Elodie

    2011-01-01

    The paper investigates short-term marginal costs in French agriculture for field cropping, beef cattle, and dairy farms during the period 1995-2006. The multi-input multi-output Symmetric Generalised MacFadden cost function is used, with three variable inputs (crop-specific, animal-specific, energy costs), four outputs and three quasi-fixed inputs. Results indicate that marginal costs are on average lower for crop farms than for livestock samples. However, for crop farms, Common Agricultural ...

  10. Auditory short-term memory in the primate auditory cortex

    OpenAIRE

    Scott, Brian H.; Mishkin, Mortimer

    2015-01-01

    Sounds are fleeting, and assembling the sequence of inputs at the ear into a coherent percept requires auditory memory across various time scales. Auditory short-term memory comprises at least two components: an active ���working memory��� bolstered by rehearsal, and a sensory trace that may be passively retained. Working memory relies on representations recalled from long-term memory, and their rehearsal may require phonological mechanisms unique to humans. The sensory component, passive sho...

  11. Robust Short-Term Memory without Synaptic Learning

    OpenAIRE

    Johnson, Samuel; Marro, J.; Torres, Joaquin J.

    2013-01-01

    Short-term memory in the brain cannot in general be explained the way long-term memory can ??? as a gradual modification of synaptic weights ??? since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining inf...

  12. INCAP - Applying short-term flexibility to control inventories

    OpenAIRE

    Lödding , Hermann; Lohmann , Steffen

    2011-01-01

    Abstract Inventory Based Capacity Control (INCAP) is a very simple method that allows inventory levels to be effectively controlled by using short-term capacity flexibility in make-to-stock settings. Moreover, INCAP can be used for finished goods inventories as well as for semi-finished goods inventories. The basic idea is to define upper and lower inventory limits and to adjust capacities if the inventory level reaches either limit. Should the inventory fall below the lower limit,...

  13. Short-term energy outlook. Quarterly projections, first quarter 1995

    International Nuclear Information System (INIS)

    1995-02-01

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). The forecast period for this issue of the Outlook extends from the first quarter of 1995 through the fourth quarter of 1996. Values for the fourth quarter of 1994, however, are preliminary EIA estimates or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the first quarter 1995 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The cases are produced using the Short-Term Integrated Forecasting System (STIFS). The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. The EIA model is available on computer tape from the National Technical Information Service

  14. Adult neurogenesis supports short-term olfactory memory.

    Science.gov (United States)

    Arenkiel, Benjamin R

    2010-06-01

    Adult neurogenesis has captivated neuroscientists for decades, with hopes that understanding the programs underlying this phenomenon may provide unique insight toward avenues for brain repair. Interestingly, however, despite intense molecular and cellular investigation, the evolutionary roles and biological functions for ongoing neurogenesis have remained elusive. Here I review recent work published in the Journal of Neuroscience that reveals a functional role for continued neurogenesis toward forming short-term olfactory memories.

  15. Cardioprotective Signature of Short-Term Caloric Restriction.

    Directory of Open Access Journals (Sweden)

    Hossein Noyan

    Full Text Available To understand the molecular pathways underlying the cardiac preconditioning effect of short-term caloric restriction (CR.Lifelong CR has been suggested to reduce the incidence of cardiovascular disease through a variety of mechanisms. However, prolonged adherence to a CR life-style is difficult. Here we reveal the pathways that are modulated by short-term CR, which are associated with protection of the mouse heart from ischemia.Male 10-12 wk old C57bl/6 mice were randomly assigned to an ad libitum (AL diet with free access to regular chow, or CR, receiving 30% less food for 7 days (d, prior to myocardial infarction (MI via permanent coronary ligation. At d8, the left ventricles (LV of AL and CR mice were collected for Western blot, mRNA and microRNA (miR analyses to identify cardioprotective gene expression signatures. In separate groups, infarct size, cardiac hemodynamics and protein abundance of caspase 3 was measured at d2 post-MI.This short-term model of CR was associated with cardio-protection, as evidenced by decreased infarct size (18.5±2.4% vs. 26.6±1.7%, N=10/group; P=0.01. mRNA and miR profiles pre-MI (N=5/group identified genes modulated by short-term CR to be associated with circadian clock, oxidative stress, immune function, apoptosis, metabolism, angiogenesis, cytoskeleton and extracellular matrix (ECM. Western blots pre-MI revealed CR-associated increases in phosphorylated Akt and GSK3ß, reduced levels of phosphorylated AMPK and mitochondrial related proteins PGC-1α, cytochrome C and cyclooxygenase (COX IV, with no differences in the levels of phosphorylated eNOS or MAPK (ERK1/2; p38. CR regimen was also associated with reduced protein abundance of cleaved caspase 3 in the infarcted heart and improved cardiac function.

  16. Frequency-specific insight into short-term memory capacity.

    Science.gov (United States)

    Feurra, Matteo; Galli, Giulia; Pavone, Enea Francesco; Rossi, Alessandro; Rossi, Simone

    2016-07-01

    The digit span is one of the most widely used memory tests in clinical and experimental neuropsychology for reliably measuring short-term memory capacity. In the forward version, sequences of digits of increasing length have to be reproduced in the order in which they are presented, whereas in the backward version items must be reproduced in the reversed order. Here, we assessed whether transcranial alternating current stimulation (tACS) increases the memory span for digits of young and midlife adults. Imperceptibly weak electrical currents in the alpha (10 Hz), beta (20 Hz), theta (5 Hz), and gamma (40 Hz) range, as well as a sham stimulation, were delivered over the left posterior parietal cortex, a cortical region thought to sustain maintenance processes in short-term memory through oscillatory brain activity in the beta range. We showed a frequency-specific effect of beta-tACS that robustly increased the forward memory span of young, but not middle-aged, healthy individuals. The effect correlated with age: the younger the subjects, the greater the benefit arising from parietal beta stimulation. Our results provide evidence of a short-term memory capacity improvement in young adults by online frequency-specific tACS application. Copyright © 2016 the American Physiological Society.

  17. Identity modulates short-term memory for facial emotion.

    Science.gov (United States)

    Galster, Murray; Kahana, Michael J; Wilson, Hugh R; Sekuler, Robert

    2009-12-01

    For some time, the relationship between processing of facial expression and facial identity has been in dispute. Using realistic synthetic faces, we reexamined this relationship for both perception and short-term memory. In Experiment 1, subjects tried to identify whether the emotional expression on a probe stimulus face matched the emotional expression on either of two remembered faces that they had just seen. The results showed that identity strongly influenced recognition short-term memory for emotional expression. In Experiment 2, subjects' similarity/dissimilarity judgments were transformed by multidimensional scaling (MDS) into a 2-D description of the faces' perceptual representations. Distances among stimuli in the MDS representation, which showed a strong linkage of emotional expression and facial identity, were good predictors of correct and false recognitions obtained previously in Experiment 1. The convergence of the results from Experiments 1 and 2 suggests that the overall structure and configuration of faces' perceptual representations may parallel their representation in short-term memory and that facial identity modulates the representation of facial emotion, both in perception and in memory. The stimuli from this study may be downloaded from http://cabn.psychonomic-journals.org/content/supplemental.

  18. Short-term indicators. Intensities as a proxy for savings

    Energy Technology Data Exchange (ETDEWEB)

    Boonekamp, P.G.M.; Gerdes, J. [ECN Policy Studies, Petten (Netherlands); Faberi, S. [Institute of Studies for the Integration of Systems ISIS, Rome (Italy)

    2013-12-15

    The ODYSSEE database on energy efficiency indicators (www.odyssee-indicators.org) has been set up to enable the monitoring and evaluation of realised energy efficiency improvements and related energy savings. The database covers the 27 EU countries as well as Norway and Croatia and data are available from 1990 on. This work contributes to the growing need for quantitative monitoring and evaluation of the impacts of energy policies and measures, both at the EU and national level, e.g. due to the Energy Services Directive and the proposed Energy Efficiency Directive. Because the underlying data become available only after some time, the savings figures are not always timely available. This is especially true for the ODEX efficiency indices per sector that rely on a number of indicators. Therefore, there is a need for so-called short-term indicators that become available shortly after the year has passed for which data are needed. The short term indicators do not replace the savings indicators but function as a proxy for the savings in the most recent year. This proxy value is faster available, but will be less accurate than the saving indicators themselves. The short term indicators have to be checked regularly with the ODEX indicators in order to see whether they can function still as a proxy.

  19. Does tonality boost short-term memory in congenital amusia?

    Science.gov (United States)

    Albouy, Philippe; Schulze, Katrin; Caclin, Anne; Tillmann, Barbara

    2013-11-06

    Congenital amusia is a neuro-developmental disorder of music perception and production. Recent findings have demonstrated that this deficit is linked to an impaired short-term memory for tone sequences. As it has been shown before that non-musicians' implicit knowledge of musical regularities can improve short-term memory for tone information, the present study investigated if this type of implicit knowledge could also influence amusics' short-term memory performance. Congenital amusics and their matched controls, who were non-musicians, had to indicate whether sequences of five tones, presented in pairs, were the same or different; half of the pairs respected musical regularities (tonal sequences) and the other half did not (atonal sequences). As previously reported for non-musician participants, the control participants showed better performance (as measured with d') for tonal sequences than for atonal ones. While this improvement was not observed in amusics, both control and amusic participants showed faster response times for tonal sequences than for atonal sequences. These findings suggest that some implicit processing of tonal structures is potentially preserved in congenital amusia. This observation is encouraging as it strengthens the perspective to exploit implicit knowledge to help reducing pitch perception and memory deficits in amusia. © 2013 Elsevier B.V. All rights reserved.

  20. FFT transformed quantitative EEG analysis of short term memory load.

    Science.gov (United States)

    Singh, Yogesh; Singh, Jayvardhan; Sharma, Ratna; Talwar, Anjana

    2015-07-01

    The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.