WorldWideScience

Sample records for modeling short-term processes

  1. Models of Short-Term Synaptic Plasticity.

    Science.gov (United States)

    Barroso-Flores, Janet; Herrera-Valdez, Marco A; Galarraga, Elvira; Bargas, José

    2017-01-01

    We focus on dynamical descriptions of short-term synaptic plasticity. Instead of focusing on the molecular machinery that has been reviewed recently by several authors, we concentrate on the dynamics and functional significance of synaptic plasticity, and review some mathematical models that reproduce different properties of the dynamics of short term synaptic plasticity that have been observed experimentally. The complexity and shortcomings of these models point to the need of simple, yet physiologically meaningful models. We propose a simplified model to be tested in synapses displaying different types of short-term plasticity.

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

    NARCIS (Netherlands)

    Cheong, S.A.; Tan, T.L.; Chen, C.-C.; Chang, W.-L.; Liu, Z.; Chew, L.Y.; Sloot, P.M.A.; Johnson, N.F.

    2014-01-01

    Predicting how large an earthquake can be, where and when it will strike remains an elusive goal in spite of the ever-increasing volume of data collected by earth scientists. In this paper, we introduce a universal model of fusion-fission processes that can be used to predict earthquakes starting

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

    Science.gov (United States)

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

    2014-01-01

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

  4. 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

  5. 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

  6. Short-Term Memory and Its Biophysical Model

    Science.gov (United States)

    Wang, Wei; Zhang, Kai; Tang, Xiao-wei

    1996-12-01

    The capacity of short-term memory has been studied using an integrate-and-fire neuronal network model. It is found that the storage of events depend on the manner of the correlation between the events, and the capacity is dominated by the value of after-depolarization potential. There is a monotonic increasing relationship between the value of after-depolarization potential and the memory numbers. The biophysics relevance of the network model is discussed and different kinds of the information processes are studied too.

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

    Science.gov (United States)

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

    2015-07-01

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

  8. Short-Termed Integrated Forecasting System: 1993 Model documentation report

    Energy Technology Data Exchange (ETDEWEB)

    1993-05-01

    The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the US Energy Department (DOE) developed the STIFS model to generate short-term (up to 8 quarters), monthly forecasts of US supplies, demands, imports exports, stocks, and prices of various forms of energy. The models that constitute STIFS generate forecasts for a wide range of possible scenarios, including the following ones done routinely on a quarterly basis: A base (mid) world oil price and medium economic growth. A low world oil price and high economic growth. A high world oil price and low economic growth. This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.

  9. Short-term integrated forecasting system : 1993 model documentation report

    Science.gov (United States)

    1993-12-01

    The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the U.S. Energy Department (DOE) developed the STIFS model to generate shor...

  10. 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

  11. Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

    OpenAIRE

    Marin Cerjan; Marin Matijaš; Marko Delimar

    2014-01-01

    Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing of data and a multi-layer (MLP) neural network for forecasting electricity price and price spike det...

  12. Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

    Directory of Open Access Journals (Sweden)

    Marin Cerjan

    2014-05-01

    Full Text Available Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing of data and a multi-layer (MLP neural network for forecasting electricity price and price spike detection. Based on statistical analysis, days are arranged into several categories. Similar days are examined by correlation significance of the historical data. Factors impacting the electricity price forecasting, including historical price factors, load factors and wind production factors are discussed. A price spike index (CWI is defined for spike detection and forecasting. Using proposed approach we created several forecasting models of diverse model complexity. The method is validated using the European Energy Exchange (EEX electricity price data records. Finally, results are discussed with respect to price volatility, with emphasis on the price forecasting accuracy.

  13. A Simple Hybrid Model for Short-Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Suseelatha Annamareddi

    2013-01-01

    Full Text Available The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.

  14. Short-Term Wind Speed Forecasting Using the Data Processing Approach and the Support Vector Machine Model Optimized by the Improved Cuckoo Search Parameter Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Chen Wang

    2016-01-01

    Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.

  15. 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

  16. The IEA Model of 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 Working Paper is intended for readers who wish to explore the MOSES methodology in depth; there is also a brochure which provides an overview of the analysis and results.

  17. A Latent Variable Analysis of Working Memory Capacity, Short-Term Memory Capacity, Processing Speed, and General Fluid Intelligence.

    Science.gov (United States)

    Conway, Andrew R. A.; Cowan, Nelsin; Bunting, Michael F.; Therriault, David J.; Minkoff, Scott R. B.

    2002-01-01

    Studied the interrelationships among general fluid intelligence, short-term memory capacity, working memory capacity, and processing speed in 120 young adults and used structural equation modeling to determine the best predictor of general fluid intelligence. Results suggest that working memory capacity, but not short-term memory capacity or…

  18. Two empirical models for short-term forecast of Kp

    Science.gov (United States)

    Luo, B.; Liu, S.; Gong, J.

    2017-03-01

    In this paper, two empirical models are developed for short-term forecast of the Kp index, taking advantage of solar wind-magnetosphere coupling functions proposed by the research community. Both models are based on the data for years 1995 to 2004. Model 1 mainly uses solar wind parameters as the inputs, while model 2 also utilizes the previous measured Kp value. Finally, model 1 predicts Kp with a linear correlation coefficient (r) of 0.91, a prediction efficiency (PE) of 0.81, and a root-mean-square (RMS) error of 0.59. Model 2 gives an r of 0.92, a PE of 0.84, and an RMS error of 0.57. The two models are validated through out-of-sample test for years 2005 to 2013, which also yields high forecast accuracy. Unlike in the other models reported in the literature, we are taking the response time of the magnetosphere to external solar wind at the Earth explicitly in the modeling. Statistically, the time delay in the models turns out to be about 30 min. By introducing this term, both the accuracy and lead time of the model forecast are improved. Through verification and validation, the models can be used in operational geomagnetic storm warnings with reliable performance.

  19. [Model of short-term psychological intervention in psychosomatic gynaecology].

    Science.gov (United States)

    Zutter, A-M; Bianchi-Demicheli, F

    2004-02-01

    This article proposes a rapid psychological intervention model in psychosomatic gynaecology. The work draws from the method developed by Dr H. Davanloo (Intensive Short Term Dynamic Psychotherapy). First it consists in identifying and clarifying the defence mechanisms, second in exercising pressure on them. This pressure causes an increase in anxiety, an intensification of the defence mechanisms and the development of an intrapsychic crisis that induces emotions and painful feelings linked to past traumata. This activation of the unconscious can activate somatic symptoms (pain, unconscious movements, tics, muscular tensions) that highlight the link between the physical and psychic aspects. This work allows a rapid access to the painful emotions that turn to symptom. It indicates the therapeutic intervention zones and levels. It allows translating psychic reality in a simple, fast and efficient way. It brings heightened consciousness and comprehension for the therapist and the patient.

  20. Short-term memory as a working memory control process

    OpenAIRE

    Davelaar, Eddy J.

    2013-01-01

    Aben et al. (2012) take issue with the unthoughtful use of the terms “working memory” (WM) and “short-term memory” (STM) in the cognitive and neuroscientific literature. Whereas I agree that neuroscientists using the term WM to refer to sustained neural activation and cognitive psychologists using the terms interchangeably reflects that the field has lost control over its own dictionary, the recommendations to develop more tasks does not seem to get to the heart of the matter. Here, I argue i...

  1. 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

  2. Statistical mechanics of neocortical interactions: Constraints on 40-Hz models of short-term memory

    Science.gov (United States)

    Ingber, Lester

    1995-10-01

    Calculations presented in L. Ingber and P.L. Nunez, Phys. Rev. E 51, 5074 (1995) detailed the evolution of short-term memory in the neocortex, supporting the empirical 7+/-2 rule of constraints on the capacity of neocortical processing. These results are given further support when other recent models of 40-Hz subcycles of low-frequency oscillations are considered.

  3. Resolving the impact of short-term variations in physical processes impacting on the spawning environment of eastern Baltic cod : application of a 3-D hydrodynamic model

    DEFF Research Database (Denmark)

    Hinrichsen, H.H.; St. John, Michael; Lehmann, A.

    2002-01-01

    cod. Recent research has identified the importance of inflows of saline and oxygenated North Sea water into the Baltic Sea for the recruitment of Baltic cod. However, other processes have been suggested to modify this reproduction volume including variations in timing and volume of terrestrial runoff......, variability of the solubility of oxygen due to variations in sea surface temperature as well as the influence of variations in wind stress. In order to examine the latter three mechanisms, we have performed simulations utilizing the Kiel Baltic Sea model for a period of a weak to moderate inflow of North Sea...... compared to runs with modified meteorological forcing conditions and river runoff. From these simulations, it is apparent that processes other than major Baltic inflows have the potential to alter the reproduction volume of Baltic cod. Low near-surface air temperatures in the North Sea, the Skagerrak...

  4. Using a Large-scale Neural Model of Cortical Object Processing to Investigate the Neural Substrate for Managing Multiple Items in Short-term Memory.

    Science.gov (United States)

    Liu, Qin; Ulloa, Antonio; Horwitz, Barry

    2017-11-01

    Many cognitive and computational models have been proposed to help understand working memory. In this article, we present a simulation study of cortical processing of visual objects during several working memory tasks using an extended version of a previously constructed large-scale neural model [Tagamets, M. A., & Horwitz, B. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral Cortex, 8, 310-320, 1998]. The original model consisted of arrays of Wilson-Cowan type of neuronal populations representing primary and secondary visual cortices, inferotemporal (IT) cortex, and pFC. We added a module representing entorhinal cortex, which functions as a gating module. We successfully implemented multiple working memory tasks using the same model and produced neuronal patterns in visual cortex, IT cortex, and pFC that match experimental findings. These working memory tasks can include distractor stimuli or can require that multiple items be retained in mind during a delay period (Sternberg's task). Besides electrophysiology data and behavioral data, we also generated fMRI BOLD time series from our simulation. Our results support the involvement of IT cortex in working memory maintenance and suggest the cortical architecture underlying the neural mechanisms mediating particular working memory tasks. Furthermore, we noticed that, during simulations of memorizing a list of objects, the first and last items in the sequence were recalled best, which may implicate the neural mechanism behind this important psychological effect (i.e., the primacy and recency effect).

  5. Short-term Memory as a Processing Shift

    Science.gov (United States)

    Lewis-Smith, Marion Quinn

    1975-01-01

    The series of experiments described here examined the predictions for free recall from sequential models and the shift formulation, focusing on the roles of short- and long-term memory in the primacy/recency shift and on the effects of expectancies on short- and long-term memory. (Author/RK)

  6. Tracking the Short Term Planning (STP) Development Process

    Science.gov (United States)

    Price, Melanie; Moore, Alexander

    2010-01-01

    Part of the National Aeronautics and Space Administration?s mission is to pioneer the future in space exploration, scientific discovery and aeronautics research is enhanced by discovering new scientific tools to improve life on earth. Sequentially, to successfully explore the unknown, there has to be a planning process that organizes certain events in the right priority. Therefore, the planning support team has to continually improve their processes so the ISS Mission Operations can operate smoothly and effectively. The planning support team consists of people in the Long Range Planning area that develop timelines that includes International Partner?s Preliminary STP inputs all the way through to publishing of the Final STP. Planning is a crucial part of the NASA community when it comes to planning the astronaut?s daily schedule in great detail. The STP Process is in need of improvement, because of the various tasks that are required to be broken down in order to get the overall objective of developing a Final STP done correctly. Then a new project came along in order to store various data in a more efficient database. "The SharePoint site is a Web site that provides a central storage and collaboration space for documents, information, and ideas."

  7. A processing architecture for associative short-term memory in electronic noses

    Science.gov (United States)

    Pioggia, G.; Ferro, M.; Di Francesco, F.; DeRossi, D.

    2006-11-01

    Electronic nose (e-nose) architectures usually consist of several modules that process various tasks such as control, data acquisition, data filtering, feature selection and pattern analysis. Heterogeneous techniques derived from chemometrics, neural networks, and fuzzy rules used to implement such tasks may lead to issues concerning module interconnection and cooperation. Moreover, a new learning phase is mandatory once new measurements have been added to the dataset, thus causing changes in the previously derived model. Consequently, if a loss in the previous learning occurs (catastrophic interference), real-time applications of e-noses are limited. To overcome these problems this paper presents an architecture for dynamic and efficient management of multi-transducer data processing techniques and for saving an associative short-term memory of the previously learned model. The architecture implements an artificial model of a hippocampus-based working memory, enabling the system to be ready for real-time applications. Starting from the base models available in the architecture core, dedicated models for neurons, maps and connections were tailored to an artificial olfactory system devoted to analysing olive oil. In order to verify the ability of the processing architecture in associative and short-term memory, a paired-associate learning test was applied. The avoidance of catastrophic interference was observed.

  8. Resolving the impact of short-term variations in physical processes impacting on the spawning environment of eastern Baltic cod : application of a 3-D hydrodynamic model

    DEFF Research Database (Denmark)

    Hinrichsen, H.H.; St. John, Michael; Lehmann, A.

    2002-01-01

    Variations in oxygen conditions below the permanent halocline influence the ecosystem of the Baltic Sea through a number of mechanisms. In this study, we examine the effects of physical forcing on variations in the volume of deep oxygenated water suitable for reproductive success of central Baltic......, variability of the solubility of oxygen due to variations in sea surface temperature as well as the influence of variations in wind stress. In order to examine the latter three mechanisms, we have performed simulations utilizing the Kiel Baltic Sea model for a period of a weak to moderate inflow of North Sea...... water into the Baltic, modifying wind stress, freshwater runoff and thermal inputs. The model is started from three-dimensional fields of temperature, salinity and oxygen obtained from a previous model run and forced by realistic atmospheric conditions. Results of this realistic reference run were...

  9. Enhanced stability of car-following model upon incorporation of short-term driving memory

    Science.gov (United States)

    Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

    2017-06-01

    Based on the full velocity difference model, a new car-following model is developed to investigate the effect of short-term driving memory on traffic flow in this paper. Short-term driving memory is introduced as the influence factor of driver's anticipation behavior. The stability condition of the newly developed model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Via numerical method, evolution of a small perturbation is investigated firstly. The results show that the improvement of this new car-following model over the previous ones lies in the fact that the new model can improve the traffic stability. Starting and breaking processes of vehicles in the signalized intersection are also investigated. The numerical simulations illustrate that the new model can successfully describe the driver's anticipation behavior, and that the efficiency and safety of the vehicles passing through the signalized intersection are improved by considering short-term driving memory.

  10. A Gaussian Processes Technique for Short-term Load Forecasting with Considerations of Uncertainty

    Science.gov (United States)

    Ohmi, Masataro; Mori, Hiroyuki

    In this paper, an efficient method is proposed to deal with short-term load forecasting with the Gaussian Processes. Short-term load forecasting plays a key role to smooth power system operation such as economic load dispatching, unit commitment, etc. Recently, the deregulated and competitive power market increases the degree of uncertainty. As a result, it is more important to obtain better prediction results to save the cost. One of the most important aspects is that power system operator needs the upper and lower bounds of the predicted load to deal with the uncertainty while they require more accurate predicted values. The proposed method is based on the Bayes model in which output is expressed in a distribution rather than a point. To realize the model efficiently, this paper proposes the Gaussian Processes that consists of the Bayes linear model and kernel machine to obtain the distribution of the predicted value. The proposed method is successively applied to real data of daily maximum load forecasting.

  11. 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)

  12. 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.…

  13. 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.

  14. 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

  15. Modelling the short term herding behaviour of stock markets

    International Nuclear Information System (INIS)

    Shapira, Yoash; Berman, Yonatan; Ben-Jacob, Eshel

    2014-01-01

    Modelling the behaviour of stock markets has been of major interest in the past century. The market can be treated as a network of many investors reacting in accordance to their group behaviour, as manifested by the index and effected by the flow of external information into the system. Here we devise a model that encapsulates the behaviour of stock markets. The model consists of two terms, demonstrating quantitatively the effect of the individual tendency to follow the group and the effect of the individual reaction to the available information. Using the above factors we were able to explain several key features of the stock market: the high correlations between the individual stocks and the index; the Epps effect; the high fluctuating nature of the market, which is similar to real market behaviour. Furthermore, intricate long term phenomena are also described by this model, such as bursts of synchronized average correlation and the dominance of the index as demonstrated through partial correlation. (paper)

  16. One minute of grief: emotional processing in short-term dynamic psychotherapy for adjustment disorder.

    Science.gov (United States)

    Kramer, Ueli; Pascual-Leone, Antonio; Despland, Jean-Nicolas; de Roten, Yves

    2015-02-01

    Depth of emotional processing has shown to be related to outcome across approaches to psychotherapy. Moreover, a specific emotional sequence has been postulated and tested in several studies on experiential psychotherapy (Pascual-Leone & Greenberg, 2007). This process-outcome study aims at reproducing the sequential model of emotional processing in psychodynamic psychotherapy for adjustment disorder and linking these variables with ultimate therapeutic outcome. In this study, 32 patients underwent short-term dynamic psychotherapy. On the basis of reliable clinical change statistics, a subgroup (n = 16) presented with good outcome and another subgroup (n = 16) had a poor outcome in the end of treatment. The strongest alliance session of each case was rated using the observer-rated system Classification of Affective Meaning States. Reliability coefficients for the measure were excellent (κ = .82). Using 1 min as the fine-grained unit of analysis, results showed that the experience of fundamentally adaptive grief was more common in the in-session process of patients with good outcome, compared with those with poor outcomes (χ2 = 6.56, p = .01, d = 1.23). This variable alone predicted 19% of the change in depressive symptoms as measured by the Beck Depression Inventory at the end of treatment. Moreover, sequences of the original model were supported and related to outcome. These results are discussed within the framework of the sequential model of emotional processing and its possible relevance for psychodynamic psychotherapy. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  17. Short-Term Memory Limitations in Children: Capacity or Processing Deficits?

    Science.gov (United States)

    Chi, Michelene T. H.

    1976-01-01

    Evaluates the assertion that short-term memory (STM) capacity increases with age and concludes that the STM capacity limitation in children is due to the deficits in the processing strategies and speeds, which presumably improve with age through cumulative learning. (JM) Available from: Memory and Cognition, Psychonomic Society, 1018 West 34…

  18. The Cultural Adaptation Process during a Short-Term Study Abroad Experience in Swaziland

    Science.gov (United States)

    Conner, Nathan W.; Roberts, T. Grady

    2015-01-01

    Globalization continuously shapes our world and influences post-secondary education. This study explored the cultural adaptation process of participants during a short-term study abroad program. Participants experienced stages which included initial feelings, cultural uncertainty, cultural barriers, cultural negativity, academic and career growth,…

  19. 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.

  20. Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model

    OpenAIRE

    Haixiang Zang; Lei Fan; Mian Guo; Zhinong Wei; Guoqiang Sun; Li Zhang

    2016-01-01

    Accurate short-term wind power forecasting is important for improving the security and economic success of power grids. Existing wind power forecasting methods are mostly types of deterministic point forecasting. Deterministic point forecasting is vulnerable to forecasting errors and cannot effectively deal with the random nature of wind power. In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EE...

  1. EDM - A model for optimising the short-term power operation of a complex hydroelectric network

    International Nuclear Information System (INIS)

    Tremblay, M.; Guillaud, C.

    1996-01-01

    In order to optimize the short-term power operation of a complex hydroelectric network, a new model called EDM was added to PROSPER, a water management analysis system developed by SNC-Lavalin. PROSPER is now divided into three parts: an optimization model (DDDP), a simulation model (ESOLIN), and an economic dispatch model (EDM) for the short-term operation. The operation of the KSEB hydroelectric system (located in southern India) with PROSPER was described. The long-term analysis with monthly time steps is assisted by the DDDP, and the daily analysis with hourly or half-hourly time steps is performed with the EDM model. 3 figs

  2. Short-term load forecast using trend information and process reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Santos, P.J.; Pires, A.J.; Martins, J.F. [Instituto Politecnico de Setubal (Portugal). Dept. of Electrical Engineering; Martins, A.G. [University of Coimbra (Portugal). Dept. of Electrical Engineering; Mendes, R.V. [Instituto Superior Tecnico, Lisboa (Portugal). Laboratorio de Mecatronica

    2005-07-01

    The algorithms for short-term load forecast (STLF), especially within the next-hour horizon, belong to a group of methodologies that aim to render more effective the actions of planning, operating and controlling electric energy systems (EES). In the context of the progressive liberalization of the electricity sector, unbundling of the previous monopolistic structure emphasizes the need for load forecast, particularly at the network level. Methodologies such as artificial neural networks (ANN) have been widely used in next-hour load forecast. Designing an ANN requires the proper choice of input variables, avoiding overfitting and an unnecessarily complex input vector (IV). This may be achieved by trying to reduce the arbitrariness in the choice of endogenous variables. At a first stage, we have applied the mathematical techniques of process-reconstruction to the underlying stochastic process, using coding and block entropies to characterize the measure and memory range. At a second stage, the concept of consumption trend in homologous days of previous weeks has been used. The possibility to include weather-related variables in the IV has also been analysed, the option finally being to establish a model of the non-weather sensitive type. The paper uses a real-life case study. (author)

  3. A long-term/short-term model for daily electricity prices with dynamic volatility

    International Nuclear Information System (INIS)

    In this paper we introduce a new stochastic long-term/short-term model for short-term electricity prices, and apply it to four major European indices, namely to the German, Dutch, UK and Nordic one. We give evidence that all time series contain certain periodic (mostly annual) patterns, and show how to use the wavelet transform, a tool of multiresolution analysis, for filtering purpose. The wavelet transform is also applied to separate the long-term trend from the short-term oscillation in the seasonal-adjusted log-prices. In all time series we find evidence for dynamic volatility, which we incorporate by using a bivariate GARCH model with constant correlation. Eventually we fit various models from the existing literature to the data, and come to the conclusion that our approach performs best. For the error distribution, the Normal Inverse Gaussian distribution shows the best fit. (author)

  4. Individualized Short-Term Core Temperature Prediction in Humans Using Biomathematical Models

    National Research Council Canada - National Science Library

    Gribok, Andrei V; Buller, Mark J; Reifman, Jaques

    2008-01-01

    .... The techniques include a first-principles, physiology-based (SCENARIO) model, a purely data-driven model, and a hybrid model that combines first-principles and data-driven components to provide an early, short-term (20-30 min ahead...

  5. Short-term adaptation to a simple motor task: a physiological process preserved in multiple sclerosis.

    Science.gov (United States)

    Mancini, L; Ciccarelli, O; Manfredonia, F; Thornton, J S; Agosta, F; Barkhof, F; Beckmann, C; De Stefano, N; Enzinger, C; Fazekas, F; Filippi, M; Gass, A; Hirsch, J G; Johansen-Berg, H; Kappos, L; Korteweg, T; Manson, S C; Marino, S; Matthews, P M; Montalban, X; Palace, J; Polman, C; Rocca, M; Ropele, S; Rovira, A; Wegner, C; Friston, K; Thompson, A; Yousry, T

    2009-04-01

    Short-term adaptation indicates the attenuation of the functional MRI (fMRI) response during repeated task execution. It is considered to be a physiological process, but it is unknown whether short-term adaptation changes significantly in patients with brain disorders, such as multiple sclerosis (MS). In order to investigate short-term adaptation during a repeated right-hand tapping task in both controls and in patients with MS, we analyzed the fMRI data collected in a large cohort of controls and MS patients who were recruited into a multi-centre European fMRI study. Four fMRI runs were acquired for each of the 55 controls and 56 MS patients at baseline and 33 controls and 26 MS patients at 1-year follow-up. The externally cued (1 Hz) right hand tapping movement was limited to 3 cm amplitude by using at all sites (7 at baseline and 6 at follow-up) identically manufactured wooden frames. No significant differences in cerebral activation were found between sites. Furthermore, our results showed linear response adaptation (i.e. reduced activation) from run 1 to run 4 (over a 25 minute period) in the primary motor area (contralateral more than ipsilateral), in the supplementary motor area and in the primary sensory cortex, sensory-motor cortex and cerebellum, bilaterally. This linear activation decay was the same in both control and patient groups, did not change between baseline and 1-year follow-up and was not influenced by the modest disease progression observed over 1 year. These findings confirm that the short-term adaptation to a simple motor task is a physiological process which is preserved in MS.

  6. Postscript: More Problems with Botvinick and Plaut's (2006) PDP Model of Short-Term Memory

    Science.gov (United States)

    Bowers, Jeffrey S.; Damian, Markus F.; Davis, Colin J.

    2009-01-01

    Presents a postscript to the current authors' comment on the original article, "Short-term memory for serial order: A recurrent neural network model," by M. M. Botvinick and D. C. Plaut. In their commentary, the current authors demonstrated that Botvinick and Plaut's (2006) model of immediate serial recall catastrophically fails when familiar…

  7. 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…

  8. A model of short term surface deformation of Soufriere Hills Volcano, Montserrat, constrained by GPS geodesy

    Science.gov (United States)

    McPherson, E. E.; Mattioli, G. S.

    2013-05-01

    Soufriere Hills Volcano (SHV), Montserrat, in the Lesser Antilles island arc, became active in 1995, and for nearly two decades, ground breaking geodetic surveys have been conducted using both continuous GPS and campaign GPS sites. Data have been collected and processed using the latest and most advanced geodetic instruments and technique available. The NSF- funded CALIPSO and SEA-CALIPSO projects have allowed for some of the most in depth studies of the ongoing SHV eruptions to date, and many models for surface deformation and magmatic chamber configuration have resulted. Research for this study is constrained to data gathered from the early stages of eruption in 1996 through 2010 from two continuous GPS sites, Hermitage Peak (HERM - located ~1.6 km from the vent) and Montserrat Volcano Observatory 1 (MVO1- located ~7.6 km away from the vent) and have been reprocessed using GIPSY-OASIS II (v. 6.1.2) with final, precise IGS08 orbits, clocks, and earth orientation parameters using an absolute point positioning (APP) strategy. Our study is being conducted to re-examine spatial and temporal changes in surface deformation, constrained by GPS, and to better illuminate the short term (i.e. sub-daily to weekly) deformation signals noted amongst the longer, cyclic deformation signals (i.e. monthly to annually) that have been previously reported and modeled. The reprocessed time-series show lower variance for daily APP solutions over the entire temporal data set; trends in the long-term inflation and deflation patterns are similar to those previously published (e.g. Elsworth et al., 2008; Mattioli et al., 2010; Odbert et al., 2012), but now superimposed, shorter term signals are more clearly visible. New elastic deformation models are being developed and will be presented for these short-term signals.

  9. Expertise prompts initial faster processing followed by increased short-term memory

    DEFF Research Database (Denmark)

    Dall, Jonas Olsen; Watanabe, Katsumi; Sørensen, Thomas Alrik

    2017-01-01

    Attention is a process of prioritising cognitive recourses to task-relevant stimulus. A number of studies have demonstrated various processing limitations in attention; for example, visual short-term memory (VSTM) only retains a limited number of objects (Sperling, 1960). An increasing number...... with varying degrees of expertise in Japanese reading participated: Danish students (novice), Danish students studying Japanese (trained), and Japanese students (expert).The results showed that while expertise enhanced VSTM only for the expert group, replicating our previous study (Dall et al., 2016), it did...

  10. 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

  11. Short-Term Forecasting Models for Photovoltaic Plants: Analytical versus Soft-Computing Techniques

    OpenAIRE

    Monteiro, Claudio; Fernandez-Jimenez, L. Alfredo; Ramirez-Rosado, Ignacio J.; Muñoz-Jimenez, Andres; Lara-Santillan, Pedro M.

    2013-01-01

    We present and compare two short-term statistical forecasting models for hourly average electric power production forecasts of photovoltaic (PV) plants: the analytical PV power forecasting model (APVF) and the multiplayer perceptron PV forecasting model (MPVF). Both models use forecasts from numerical weather prediction (NWP) tools at the location of the PV plant as well as the past recorded values of PV hourly electric power production. The APVF model consists of an original modeling for adj...

  12. Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia.

    Science.gov (United States)

    Crabtree, Gregg W; Gogos, Joseph A

    2014-01-01

    Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations.

  13. Persistent short-term memory defects following sleep deprivation in a drosophila model of Parkinson disease.

    Science.gov (United States)

    Seugnet, Laurent; Galvin, James E; Suzuki, Yasuko; Gottschalk, Laura; Shaw, Paul J

    2009-08-01

    Parkinson disease (PD) is the second most common neurodegenerative disorder in the United States. It is associated with motor deficits, sleep disturbances, and cognitive impairment. The pathology associated with PD and the effects of sleep deprivation impinge, in part, upon common molecular pathways suggesting that sleep loss may be particularly deleterious to the degenerating brain. Thus we investigated the long-term consequences of sleep deprivation on shortterm memory using a Drosophila model of Parkinson disease. Transgenic strains of Drosophila melanogaster. Using the GAL4-UAS system, human alpha-synuclein was expressed throughout the nervous system of adult flies. Alpha-synuclein expressing flies (alpha S flies) and the corresponding genetic background controls were sleep deprived for 12 h at age 16 days and allowed to recover undisturbed for at least 3 days. Short-term memory was evaluated using aversive phototaxis suppression. Dopaminergic systems were assessed using mRNA profiling and immunohistochemistry. MEASURMENTS AND RESULTS: When sleep deprived at an intermediate stage of the pathology, alpha S flies showed persistent short-term memory deficits that lasted > or = 3 days. Cognitive deficits were not observed in younger alpha S flies nor in genetic background controls. Long-term impairments were not associated with accelerated loss of dopaminergic neurons. However mRNA expression of the dopamine receptors dDA1 and DAMB were significantly increased in sleep deprived alpha S flies. Blocking D1-like receptors during sleep deprivation prevented persistent shortterm memory deficits. Importantly, feeding flies the polyphenolic compound curcumin blocked long-term learning deficits. These data emphasize the importance of sleep in a degenerating/reorganizing brain and shows that pathological processes induced by sleep deprivation can be dissected at the molecular and cellular level using Drosophila genetics.

  14. Simulation of Mechanical Processes in Gas Storage Caverns for Short-Term Energy Storage

    Science.gov (United States)

    Böttcher, Norbert; Nagel, Thomas; Kolditz, Olaf

    2015-04-01

    In recent years, Germany's energy management has started to be transferred from fossil fuels to renewable and sustainable energy carriers. Renewable energy sources such as solar and wind power are subjected by fluctuations, thus the development and extension of energy storage capacities is a priority in German R&D programs. This work is a part of the ANGUS+ Project, funded by the federal ministry of education and research, which investigates the influence of subsurface energy storage on the underground. The utilization of subsurface salt caverns as a long-term storage reservoir for fossil fuels is a common method, since the construction of caverns in salt rock is inexpensive in comparison to solid rock formations due to solution mining. Another advantage of evaporate as host material is the self-healing behaviour of salt rock, thus the cavity can be assumed to be impermeable. In the framework of short-term energy storage (hours to days), caverns can be used as gas storage reservoirs for natural or artificial fuel gases, such as hydrogen, methane, or compressed air, where the operation pressures inside the caverns will fluctuate more frequently. This work investigates the influence of changing operation pressures at high frequencies on the stability of the host rock of gas storage caverns utilizing numerical models. Therefore, we developed a coupled Thermo-Hydro-Mechanical (THM) model based on the finite element method utilizing the open-source software platform OpenGeoSys. The salt behaviour is described by well-known constitutive material models which are capable of predicting creep, self-healing, and dilatancy processes. Our simulations include the thermodynamic behaviour of gas storage process, temperature development and distribution on the cavern boundary, the deformation of the cavern geometry, and the prediction of the dilatancy zone. Based on the numerical results, optimal operation modes can be found for individual caverns, so the risk of host rock damage

  15. A clustering-based fuzzy wavelet neural network model for short-term load forecasting.

    Science.gov (United States)

    Kodogiannis, Vassilis S; Amina, Mahdi; Petrounias, Ilias

    2013-10-01

    Load forecasting is a critical element of power system operation, involving prediction of the future level of demand to serve as the basis for supply and demand planning. This paper presents the development of a novel clustering-based fuzzy wavelet neural network (CB-FWNN) model and validates its prediction on the short-term electric load forecasting of the Power System of the Greek Island of Crete. The proposed model is obtained from the traditional Takagi-Sugeno-Kang fuzzy system by replacing the THEN part of fuzzy rules with a "multiplication" wavelet neural network (MWNN). Multidimensional Gaussian type of activation functions have been used in the IF part of the fuzzyrules. A Fuzzy Subtractive Clustering scheme is employed as a pre-processing technique to find out the initial set and adequate number of clusters and ultimately the number of multiplication nodes in MWNN, while Gaussian Mixture Models with the Expectation Maximization algorithm are utilized for the definition of the multidimensional Gaussians. The results corresponding to the minimum and maximum power load indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models.

  16. Statistical Language Modeling for Historical Documents using Weighted Finite-State Transducers and Long Short-Term Memory

    OpenAIRE

    Al Azawi, Mayce

    2015-01-01

    The goal of this work is to develop statistical natural language models and processing techniques based on Recurrent Neural Networks (RNN), especially the recently introduced Long Short- Term Memory (LSTM). Due to their adapting and predicting abilities, these methods are more robust, and easier to train than traditional methods, i.e., words list and rule-based models. They improve the output of recognition systems and make them more accessible to users for browsing and reading...

  17. 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....

  18. Short-term estimation of GNSS TEC using a neural network model in Brazil

    Science.gov (United States)

    Ferreira, Arthur Amaral; Borges, Renato Alves; Paparini, Claudia; Ciraolo, Luigi; Radicella, Sandro M.

    2017-10-01

    This work presents a novel Neural Network (NN) model to estimate Total Electron Content (TEC) from Global Navigation Satellite Systems (GNSS) measurements in three distinct sectors in Brazil. The purpose of this work is to start the investigations on the development of a regional model that can be used to determine the vertical TEC over Brazil, aiming future applications on a near real-time frame estimations and short-term forecasting. The NN is used to estimate the GNSS TEC values at void locations, where no dual-frequency GNSS receiver that may be used as a source of data to GNSS TEC estimation is available. This approach is particularly useful for GNSS single-frequency users that rely on corrections of ionospheric range errors by TEC models. GNSS data from the first GLONASS network for research and development (GLONASS R&D network) installed in Latin America, and from the Brazilian Network for Continuous Monitoring of the GNSS (RMBC) were used on TEC calibration. The input parameters of the NN model are based on features known to influence TEC values, such as geographic location of the GNSS receiver, magnetic activity, seasonal and diurnal variations, and solar activity. Data from two ten-days periods (from DoY 154 to 163 and from 282 to 291) are used to train the network. Three distinct analyses have been carried out in order to assess time-varying and spatial performance of the model. At the spatial performance analysis, for each region, a set of stations is chosen to provide training data to the NN, and after the training procedure, the NN is used to estimate vTEC behavior for the test station which data were not presented to the NN in training process. An analysis is done by comparing, for each testing station, the estimated NN vTEC delivered by the NN and reference calibrated vTEC. Also, as a second analysis, the network ability to forecast one day after the time interval (DoY 292) based on information of the second period of investigation is also assessed

  19. 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...

  20. A Neural Network Model of the Visual Short-Term Memory

    DEFF Research Database (Denmark)

    Petersen, Anders; Kyllingsbæk, Søren; Hansen, Lars Kai

    2009-01-01

    In this paper a neural network model of Visual Short-Term Memory (VSTM) is presented. The model links closely with Bundesen’s (1990) well-established mathematical theory of visual attention. We evaluate the model’s ability to fit experimental data from a classical whole and partial report study....... Previous statistic models have successfully assessed the spatial distribution of visual attention; our neural network meets this standard and offers a neural interpretation of how objects are consolidated in VSTM at the same time. We hope that in the future, the model will be able to fit temporally...

  1. Multisensory integration during short-term music reading training enhances both uni- and multisensory cortical processing.

    Science.gov (United States)

    Paraskevopoulos, Evangelos; Kuchenbuch, Anja; Herholz, Sibylle C; Pantev, Christo

    2014-10-01

    The human ability to integrate the input of several sensory systems is essential for building a meaningful interpretation out of the complexity of the environment. Training studies have shown that the involvement of multiple senses during training enhances neuroplasticity, but it is not clear to what extent integration of the senses during training is required for the observed effects. This study intended to elucidate the differential contributions of uni- and multisensory elements of music reading training in the resulting plasticity of abstract audiovisual incongruency identification. We used magnetoencephalography to measure the pre- and posttraining cortical responses of two randomly assigned groups of participants that followed either an audiovisual music reading training that required multisensory integration (AV-Int group) or a unisensory training that had separate auditory and visual elements (AV-Sep group). Results revealed a network of frontal generators for the abstract audiovisual incongruency response, confirming previous findings, and indicated the central role of anterior prefrontal cortex in this process. Differential neuroplastic effects of the two types of training in frontal and temporal regions point to the crucial role of multisensory integration occurring during training. Moreover, a comparison of the posttraining cortical responses of both groups to a group of musicians that were tested using the same paradigm revealed that long-term music training leads to significantly greater responses than the short-term training of the AV-Int group in anterior prefrontal regions as well as to significantly greater responses than both short-term training protocols in the left superior temporal gyrus (STG).

  2. Visual Short-Term Memory Activity in Parietal Lobe Reflects Cognitive Processes beyond Attentional Selection.

    Science.gov (United States)

    Sheremata, Summer L; Somers, David C; Shomstein, Sarah

    2018-02-07

    Visual short-term memory (VSTM) and attention are distinct yet interrelated processes. While both require selection of information across the visual field, memory additionally requires the maintenance of information across time and distraction. VSTM recruits areas within human (male and female) dorsal and ventral parietal cortex that are also implicated in spatial selection; therefore, it is important to determine whether overlapping activation might reflect shared attentional demands. Here, identical stimuli and controlled sustained attention across both tasks were used to ask whether fMRI signal amplitude, functional connectivity, and contralateral visual field bias reflect memory-specific task demands. While attention and VSTM activated similar cortical areas, BOLD amplitude and functional connectivity in parietal cortex differentiated the two tasks. Relative to attention, VSTM increased BOLD amplitude in dorsal parietal cortex and decreased BOLD amplitude in the angular gyrus. Additionally, the tasks differentially modulated parietal functional connectivity. Contrasting VSTM and attention, intraparietal sulcus (IPS) 1-2 were more strongly connected with anterior frontoparietal areas and more weakly connected with posterior regions. This divergence between tasks demonstrates that parietal activation reflects memory-specific functions and consequently modulates functional connectivity across the cortex. In contrast, both tasks demonstrated hemispheric asymmetries for spatial processing, exhibiting a stronger contralateral visual field bias in the left versus the right hemisphere across tasks, suggesting that asymmetries are characteristic of a shared selection process in IPS. These results demonstrate that parietal activity and patterns of functional connectivity distinguish VSTM from more general attention processes, establishing a central role of the parietal cortex in maintaining visual information. SIGNIFICANCE STATEMENT Visual short-term memory (VSTM) and

  3. Reduced short-term memory capacity in Alzheimer's disease: the role of phonological, lexical, and semantic processing.

    Science.gov (United States)

    Caza, Nicole; Belleville, Sylvie

    2008-05-01

    Individuals with Alzheimer's disease (AD) are often reported to have reduced verbal short-term memory capacity, typically attributed to their attention/executive deficits. However, these individuals also tend to show progressive impairment of semantic, lexical, and phonological processing which may underlie their low short-term memory capacity. The goals of this study were to assess the contribution of each level of representation (phonological, lexical, and semantic) to immediate serial recall performance in 18 individuals with AD, and to examine how these linguistic effects on short-term memory were modulated by their reduced capacity to manipulate information in short-term memory associated with executive dysfunction. Results showed that individuals with AD had difficulty recalling items that relied on phonological representations, which led to increased lexicality effects relative to the control group. This finding suggests that patients have a greater reliance on lexical/semantic information than controls, possibly to make up for deficits in retention and processing of phonological material. This lexical/semantic effect was not found to be significantly correlated with patients' capacity to manipulate verbal material in short-term memory, indicating that language processing and executive deficits may independently contribute to reducing verbal short-term memory capacity in AD.

  4. 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.

  5. Shared filtering processes link attentional and visual short-term memory capacity limits.

    Science.gov (United States)

    Bettencourt, Katherine C; Michalka, Samantha W; Somers, David C

    2011-09-30

    Both visual attention and visual short-term memory (VSTM) have been shown to have capacity limits of 4 ± 1 objects, driving the hypothesis that they share a visual processing buffer. However, these capacity limitations also show strong individual differences, making the degree to which these capacities are related unclear. Moreover, other research has suggested a distinction between attention and VSTM buffers. To explore the degree to which capacity limitations reflect the use of a shared visual processing buffer, we compared individual subject's capacities on attentional and VSTM tasks completed in the same testing session. We used a multiple object tracking (MOT) and a VSTM change detection task, with varying levels of distractors, to measure capacity. Significant correlations in capacity were not observed between the MOT and VSTM tasks when distractor filtering demands differed between the tasks. Instead, significant correlations were seen when the tasks shared spatial filtering demands. Moreover, these filtering demands impacted capacity similarly in both attention and VSTM tasks. These observations fail to support the view that visual attention and VSTM capacity limits result from a shared buffer but instead highlight the role of the resource demands of underlying processes in limiting capacity.

  6. Effect of short-term escitalopram treatment on neural activation during emotional processing.

    Science.gov (United States)

    Maron, Eduard; Wall, Matt; Norbury, Ray; Godlewska, Beata; Terbeck, Sylvia; Cowen, Philip; Matthews, Paul; Nutt, David J

    2016-01-01

    Recent functional magnetic resonance (fMRI) imaging studies have revealed that subchronic medication with escitalopram leads to significant reduction in both amygdala and medial frontal gyrus reactivity during processing of emotional faces, suggesting that escitalopram may have a distinguishable modulatory effect on neural activation as compared with other serotonin-selective antidepressants. In this fMRI study we aimed to explore whether short-term medication with escitalopram in healthy volunteers is associated with reduced neural response to emotional processing, and whether this effect is predicted by drug plasma concentration. The neural response to fearful and happy faces was measured before and on day 7 of treatment with escitalopram (10mg) in 15 healthy volunteers and compared with those in a control unmedicated group (n=14). Significantly reduced activation to fearful, but not to happy facial expressions was observed in the bilateral amygdala, cingulate and right medial frontal gyrus following escitalopram medication. This effect was not correlated with plasma drug concentration. In accordance with previous data, we showed that escitalopram exerts its rapid direct effect on emotional processing via attenuation of neural activation in pathways involving medial frontal gyrus and amygdala, an effect that seems to be distinguishable from that of other SSRIs. © The Author(s) 2015.

  7. A Probabilistic Short-Term Water Demand Forecasting Model Based on the Markov Chain

    Directory of Open Access Journals (Sweden)

    Francesca Gagliardi

    2017-07-01

    Full Text Available This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals covering the expected total variability. More specifically, two models based on homogeneous and non-homogeneous Markov chains were developed and presented. These models, together with two benchmark models (based on artificial neural network and naïve methods, were applied to three real-life case studies for the purpose of forecasting the respective water demands from 1 to 24 h ahead. The results obtained show that the model based on a homogeneous Markov chain provides more accurate short-term forecasts than the one based on a non-homogeneous Markov chain, which is in line with the artificial neural network model. Both Markov chain models enable probabilistic information regarding the stochastic demand forecast to be easily obtained.

  8. Statistical Models for Tornado Climatology: Long and Short-Term Views.

    Science.gov (United States)

    Elsner, James B; Jagger, Thomas H; Fricker, Tyler

    2016-01-01

    This paper estimates regional tornado risk from records of past events using statistical models. First, a spatial model is fit to the tornado counts aggregated in counties with terms that control for changes in observational practices over time. Results provide a long-term view of risk that delineates the main tornado corridors in the United States where the expected annual rate exceeds two tornadoes per 10,000 square km. A few counties in the Texas Panhandle and central Kansas have annual rates that exceed four tornadoes per 10,000 square km. Refitting the model after removing the least damaging tornadoes from the data (EF0) produces a similar map but with the greatest tornado risk shifted south and eastward. Second, a space-time model is fit to the counts aggregated in raster cells with terms that control for changes in climate factors. Results provide a short-term view of risk. The short-term view identifies a shift of tornado activity away from the Ohio Valley under El Niño conditions and away from the Southeast under positive North Atlantic oscillation conditions. The combined predictor effects on the local rates is quantified by fitting the model after leaving out the year to be predicted from the data. The models provide state-of-the-art views of tornado risk that can be used by government agencies, the insurance industry, and the general public.

  9. Posture-based processing in visual short-term memory for actions.

    Science.gov (United States)

    Vicary, Staci A; Stevens, Catherine J

    2014-01-01

    Visual perception of human action involves both form and motion processing, which may rely on partially dissociable neural networks. If form and motion are dissociable during visual perception, then they may also be dissociable during their retention in visual short-term memory (VSTM). To elicit form-plus-motion and form-only processing of dance-like actions, individual action frames can be presented in the correct or incorrect order. The former appears coherent and should elicit action perception, engaging both form and motion pathways, whereas the latter appears incoherent and should elicit posture perception, engaging form pathways alone. It was hypothesized that, if form and motion are dissociable in VSTM, then recognition of static body posture should be better after viewing incoherent than after viewing coherent actions. However, as VSTM is capacity limited, posture-based encoding of actions may be ineffective with increased number of items or frames. Using a behavioural change detection task, recognition of a single test posture was significantly more likely after studying incoherent than after studying coherent stimuli. However, this effect only occurred for spans of two (but not three) items and for stimuli with five (but not nine) frames. As in perception, posture and motion are dissociable in VSTM.

  10. Short-term droughts forecast using Markov chain model in Victoria, Australia

    Science.gov (United States)

    Rahmat, Siti Nazahiyah; Jayasuriya, Niranjali; Bhuiyan, Muhammed A.

    2017-07-01

    A comprehensive risk management strategy for dealing with drought should include both short-term and long-term planning. The objective of this paper is to present an early warning method to forecast drought using the Standardised Precipitation Index (SPI) and a non-homogeneous Markov chain model. A model such as this is useful for short-term planning. The developed method has been used to forecast droughts at a number of meteorological monitoring stations that have been regionalised into six (6) homogenous clusters with similar drought characteristics based on SPI. The non-homogeneous Markov chain model was used to estimate drought probabilities and drought predictions up to 3 months ahead. The drought severity classes defined using the SPI were computed at a 12-month time scale. The drought probabilities and the predictions were computed for six clusters that depict similar drought characteristics in Victoria, Australia. Overall, the drought severity class predicted was quite similar for all the clusters, with the non-drought class probabilities ranging from 49 to 57 %. For all clusters, the near normal class had a probability of occurrence varying from 27 to 38 %. For the more moderate and severe classes, the probabilities ranged from 2 to 13 % and 3 to 1 %, respectively. The developed model predicted drought situations 1 month ahead reasonably well. However, 2 and 3 months ahead predictions should be used with caution until the models are developed further.

  11. Kinetic modeling of the purging of activated carbon after short term methyl iodide loading

    International Nuclear Information System (INIS)

    Friedrich, V.; Lux, I.

    1991-01-01

    A bimolecular reaction model containing the physico-chemical parameters of the adsorption and desorption was developed earlier to describe the kinetics of methyl iodide retention by activated carbon adsorber. Both theoretical model and experimental investigations postulated constant upstream methyl iodide concentration till the maximum break-through. The work reported here includes the extension of the theoretical model to the general case when the concentration of the challenging gas may change in time. The effect of short term loading followed by purging with air, and an impulse-like increase in upstream gas concentration has been simulated. The case of short term loading and subsequent purging has been experimentally studied to validate the model. The investigations were carried out on non-impregnated activated carbon. A 4 cm deep carbon bed had been challenged by methyl iodide for 30, 90, 120 and 180 min and then purged with air, downstream methyl iodide concentration had been measured continuously. The main characteristics of the observed downstream concentration curves (time and slope of break-through, time and amplitude of maximum values) showed acceptable agreement with those predicted by the model

  12. 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.

  13. Research on Short-Term Wind Power Prediction Based on Combined Forecasting Models

    Directory of Open Access Journals (Sweden)

    Zhang Chi

    2016-01-01

    Full Text Available Short-Term wind power forecasting is crucial for power grid since the generated energy of wind farm fluctuates frequently. In this paper, a physical forecasting model based on NWP and a statistical forecasting model with optimized initial value in the method of BP neural network are presented. In order to make full use of the advantages of the models presented and overcome the limitation of the disadvantage, the equal weight model and the minimum variance model are established for wind power prediction. Simulation results show that the combination forecasting model is more precise than single forecasting model and the minimum variance combination model can dynamically adjust weight of each single method, restraining the forecasting error further.

  14. Short term global health experiences and local partnership models: a framework.

    Science.gov (United States)

    Loh, Lawrence C; Cherniak, William; Dreifuss, Bradley A; Dacso, Matthew M; Lin, Henry C; Evert, Jessica

    2015-12-18

    Contemporary interest in in short-term experiences in global health (STEGH) has led to important questions of ethics, responsibility, and potential harms to receiving communities. In addressing these issues, the role of local engagement through partnerships between external STEGH facilitating organization(s) and internal community organization(s) has been identified as crucial to mitigating potential pitfalls. This perspective piece offers a framework to categorize different models of local engagement in STEGH based on professional experiences and a review of the existing literature. This framework will encourage STEGH stakeholders to consider partnership models in the development and evaluation of new or existing programs.The proposed framework examines the community context in which STEGH may occur, and considers three broad categories: number of visiting external groups conducting STEGH (single/multiple), number of host entities that interact with the STEGH (none/single/multiple), and frequency of STEGH (continuous/intermittent). These factors culminate in a specific model that provides a description of opportunities and challenges presented by each model. Considering different models, single visiting partners, working without a local partner on an intermittent (or even one-time) basis provided the greatest flexibility to the STEGH participants, but represented the least integration locally and subsequently the greatest potential harm for the receiving community. Other models, such as multiple visiting teams continuously working with a single local partner, provided an opportunity for centralization of efforts and local input, but required investment in consensus-building and streamlining of processes across different groups. We conclude that involving host partners in the design, implementation, and evaluation of STEGH requires more effort on the part of visiting STEGH groups and facilitators, but has the greatest potential benefit for meaningful, locally

  15. A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation

    Directory of Open Access Journals (Sweden)

    Yuan-Kang Wu

    2014-01-01

    Full Text Available The increasing use of solar power as a source of electricity has led to increased interest in forecasting its power output over short-time horizons. Short-term forecasts are needed for operational planning, switching sources, programming backup, reserve usage, and peak load matching. However, the output of a photovoltaic (PV system is influenced by irradiation, cloud cover, and other weather conditions. These factors make it difficult to conduct short-term PV output forecasting. In this paper, an experimental database of solar power output, solar irradiance, air, and module temperature data has been utilized. It includes data from the Green Energy Office Building in Malaysia, the Taichung Thermal Plant of Taipower, and National Penghu University. Based on the historical PV power and weather data provided in the experiment, all factors that influence photovoltaic-generated energy are discussed. Moreover, five types of forecasting modules were developed and utilized to predict the one-hour-ahead PV output. They include the ARIMA, SVM, ANN, ANFIS, and the combination models using GA algorithm. Forecasting results show the high precision and efficiency of this combination model. Therefore, the proposed model is suitable for ensuring the stable operation of a photovoltaic generation system.

  16. Nonparametric Stochastic Model for Uncertainty Quantifi cation of Short-term Wind Speed Forecasts

    Science.gov (United States)

    AL-Shehhi, A. M.; Chaouch, M.; Ouarda, T.

    2014-12-01

    Wind energy is increasing in importance as a renewable energy source due to its potential role in reducing carbon emissions. It is a safe, clean, and inexhaustible source of energy. The amount of wind energy generated by wind turbines is closely related to the wind speed. Wind speed forecasting plays a vital role in the wind energy sector in terms of wind turbine optimal operation, wind energy dispatch and scheduling, efficient energy harvesting etc. It is also considered during planning, design, and assessment of any proposed wind project. Therefore, accurate prediction of wind speed carries a particular importance and plays significant roles in the wind industry. Many methods have been proposed in the literature for short-term wind speed forecasting. These methods are usually based on modeling historical fixed time intervals of the wind speed data and using it for future prediction. The methods mainly include statistical models such as ARMA, ARIMA model, physical models for instance numerical weather prediction and artificial Intelligence techniques for example support vector machine and neural networks. In this paper, we are interested in estimating hourly wind speed measures in United Arab Emirates (UAE). More precisely, we predict hourly wind speed using a nonparametric kernel estimation of the regression and volatility functions pertaining to nonlinear autoregressive model with ARCH model, which includes unknown nonlinear regression function and volatility function already discussed in the literature. The unknown nonlinear regression function describe the dependence between the value of the wind speed at time t and its historical data at time t -1, t - 2, … , t - d. This function plays a key role to predict hourly wind speed process. The volatility function, i.e., the conditional variance given the past, measures the risk associated to this prediction. Since the regression and the volatility functions are supposed to be unknown, they are estimated using

  17. The processing of images of biological threats in visual short-term memory.

    Science.gov (United States)

    Quinlan, Philip T; Yue, Yue; Cohen, Dale J

    2017-08-30

    The idea that there is enhanced memory for negatively, emotionally charged pictures was examined. Performance was measured under rapid, serial visual presentation (RSVP) conditions in which, on every trial, a sequence of six photo-images was presented. Briefly after the offset of the sequence, two alternative images (a target and a foil) were presented and participants attempted to choose which image had occurred in the sequence. Images were of threatening and non-threatening cats and dogs. The target depicted either an animal expressing an emotion distinct from the other images, or the sequences contained only images depicting the same emotional valence. Enhanced memory was found for targets that differed in emotional valence from the other sequence images, compared to targets that expressed the same emotional valence. Further controls in stimulus selection were then introduced and the same emotional distinctiveness effect obtained. In ruling out possible visual and attentional accounts of the data, an informal dual route topic model is discussed. This places emphasis on how visual short-term memory reveals a sensitivity to the emotional content of the input as it unfolds over time. Items that present with a distinctive emotional content stand out in memory. © 2017 The Author(s).

  18. Transmodal comparison of auditory, motor, and visual post-processing with and without intentional short-term memory maintenance.

    Science.gov (United States)

    Bender, Stephan; Behringer, Stephanie; Freitag, Christine M; Resch, Franz; Weisbrod, Matthias

    2010-12-01

    To elucidate the contributions of modality-dependent post-processing in auditory, motor and visual cortical areas to short-term memory. We compared late negative waves (N700) during the post-processing of single lateralized stimuli which were separated by long intertrial intervals across the auditory, motor and visual modalities. Tasks either required or competed with attention to post-processing of preceding events, i.e. active short-term memory maintenance. N700 indicated that cortical post-processing exceeded short movements as well as short auditory or visual stimuli for over half a second without intentional short-term memory maintenance. Modality-specific topographies pointed towards sensory (respectively motor) generators with comparable time-courses across the different modalities. Lateralization and amplitude of auditory/motor/visual N700 were enhanced by active short-term memory maintenance compared to attention to current perceptions or passive stimulation. The memory-related N700 increase followed the characteristic time-course and modality-specific topography of the N700 without intentional memory-maintenance. Memory-maintenance-related lateralized negative potentials may be related to a less lateralised modality-dependent post-processing N700 component which occurs also without intentional memory maintenance (automatic memory trace or effortless attraction of attention). Encoding to short-term memory may involve controlled attention to modality-dependent post-processing. Similar short-term memory processes may exist in the auditory, motor and visual systems. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  19. Short-Term City Electric Load Forecasting with Considering Temperature Effects: An Improved ARIMAX Model

    Directory of Open Access Journals (Sweden)

    Herui Cui

    2015-01-01

    Full Text Available Short-term electric load is significantly affected by weather, especially the temperature effects in summer. External factors can result in mutation structures in load data. Under the influence of the external temperature factors, city electric load cannot be easily forecasted as usual. This research analyzes the relationship between electricity load and daily temperature in city. An improved ARIMAX model is proposed in this paper to deal with the mutation data structures. It is found that information amount of the improved ARIMAX model is smaller than that of the classic method and its relative error is less than AR, ARMA and Sigmoid-Function ANN models. The forecasting results are more accurately fitted. This improved model is highly valuable when dealing with mutation data structure in the field of load forecasting. And it is also an effective technique in forecasting electric load with temperature effects.

  20. Multivariate time series modeling of short-term system scale irrigation demand

    Science.gov (United States)

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

    2015-12-01

    Travel time limits the ability of irrigation system operators to react to short-term irrigation demand fluctuations that result from variations in weather, including very hot periods and rainfall events, as well as the various other pressures and opportunities that farmers face. Short-term system-wide irrigation demand forecasts can assist in system operation. Here we developed a multivariate time series (ARMAX) model to forecast irrigation demands with respect to aggregated service points flows (IDCGi, ASP) and off take regulator flows (IDCGi, OTR) based across 5 command areas, which included area covered under four irrigation channels and the study area. These command area specific ARMAX models forecast 1-5 days ahead daily IDCGi, ASP and IDCGi, OTR using the real time flow data recorded at the service points and the uppermost regulators and observed meteorological data collected from automatic weather stations. The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). During the evaluation period, NSE for IDCGi, ASP and IDCGi, OTR across 5 command areas were ranged 0.98-0.78. These models were capable of generating skillful forecasts (MSSS ⩾ 0.5 and ACC ⩾ 0.6) of IDCGi, ASP and IDCGi, OTR for all 5 lead days and IDCGi, ASP and IDCGi, OTR forecasts were better than using the long term monthly mean irrigation demand. Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware. Further, IDCGi, ASP and IDCGi, OTR forecasts have improved the operators' ability to react for near future irrigation demand fluctuations as the developed ARMAX time series models were self-adaptive to reflect the short-term changes in the irrigation demand with respect to various pressures and opportunities that farmers' face, such as

  1. A Short-Term Photovoltaic Power Prediction Model Based on an FOS-ELM Algorithm

    Directory of Open Access Journals (Sweden)

    Jidong Wang

    2017-04-01

    Full Text Available With the increasing proportion of photovoltaic (PV power in power systems, the problem of its fluctuation and intermittency has become more prominent. To reduce the negative influence of the use of PV power, we propose a short-term PV power prediction model based on the online sequential extreme learning machine with forgetting mechanism (FOS-ELM, which can constantly replace outdated data with new data. We use historical weather data and historical PV power data to predict the PV power in the next period of time. The simulation result shows that this model has the advantages of a short training time and high accuracy. This model can help the power dispatch department schedule generation plans as well as support spatial and temporal compensation and coordinated power control, which is important for the security and stability as well as the optimal operation of power systems.

  2. Comparative evaluation of short-term leach tests for heavy metal release from mineral processing waste

    Science.gov (United States)

    Al-Abed, S. R.; Hageman, P.L.; Jegadeesan, G.; Madhavan, N.; Allen, D.

    2006-01-01

    Evaluation of metal leaching using a single leach test such as the Toxicity Characteristic Leaching Procedure (TCLP) is often questionable. The pH, redox potential (Eh), particle size and contact time are critical variables in controlling metal stability, not accounted for in the TCLP. This paper compares the leaching behavior of metals in mineral processing waste via short-term extraction tests such as TCLP, Field Leach Test (FLT) used by USGS and deionized water extraction tests. Variation in the extracted amounts was attributed to the use of different particle sizes, extraction fluid and contact time. In the controlled pH experiments, maximum metal extraction was obtained at acidic pH for cationic heavy metals such as Cu, Pb and Zn, while desorption of Se from the waste resulted in high extract concentrations in the alkaline region. Precipitation of iron, caused by a pH increase, probably resulted in co-precipitation and immobilization of Cu, Pb and Zn in the alkaline pH region. A sequential extraction procedure was performed on the original waste and the solid residue from the Eh-pH experiments to determine the chemical speciation and distribution of the heavy metals. In the as-received waste, Cu existed predominantly in water soluble or sulfidic phases, with no binding to carbonates or iron oxides. Similar characteristics were observed for Pb and Zn, while Se existed mostly associated with iron oxides or sulfides. Adsorption/co-precipitation of Cu, Se and Pb on precipitated iron hydroxides was observed in the experimental solid residues, resulting in metal immobilization above pH 7.

  3. Short term memory for serial order: Unraveling individual differences in the use of processes and changes across tasks

    NARCIS (Netherlands)

    G.V. Koppenol-Gonzalez (Gabriela); S. Bouwmeester (Samantha); J.K. Vermunt (Jeroen)

    2013-01-01

    textabstractIn this study we investigated whether we could distinguish the use of specific verbal and visual short term memory (STM) processes in children, or whether the differences in memory performance could be interpreted only in terms of quantitative differences. First, the number of processes

  4. Short term memory for serial order : Unraveling individual differences in the use of processes and changes across tasks

    NARCIS (Netherlands)

    Gonzalez Marin, G.V.; Bouwmeester, S.; Vermunt, J.K.

    2013-01-01

    In this study we investigated whether we could distinguish the use of specific verbal and visual short term memory (STM) processes in children, or whether the differences in memory performance could be interpreted only in terms of quantitative differences. First, the number of processes involved in

  5. Short-Term Forecasting Models for Photovoltaic Plants: Analytical versus Soft-Computing Techniques

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2013-01-01

    Full Text Available We present and compare two short-term statistical forecasting models for hourly average electric power production forecasts of photovoltaic (PV plants: the analytical PV power forecasting model (APVF and the multiplayer perceptron PV forecasting model (MPVF. Both models use forecasts from numerical weather prediction (NWP tools at the location of the PV plant as well as the past recorded values of PV hourly electric power production. The APVF model consists of an original modeling for adjusting irradiation data of clear sky by an irradiation attenuation index, combined with a PV power production attenuation index. The MPVF model consists of an artificial neural network based model (selected among a large set of ANN optimized with genetic algorithms, GAs. The two models use forecasts from the same NWP tool as inputs. The APVF and MPVF models have been applied to a real-life case study of a grid-connected PV plant using the same data. Despite the fact that both models are quite different, they achieve very similar results, with forecast horizons covering all the daylight hours of the following day, which give a good perspective of their applicability for PV electric production sale bids to electricity markets.

  6. A phenomenological memristor model for short-term/long-term memory

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Ling, E-mail: 2006chenling2006@163.com [College of Computer Science, Chongqing University, Chongqing 400044 (China); Li, Chuandong, E-mail: licd@cqu.edu.cn [College of Computer Science, Chongqing University, Chongqing 400044 (China); Huang, Tingwen [Texas A and M University at Qatar, Doha, B.O. Box 23874 (Qatar); Ahmad, Hafiz Gulfam [College of Computer Science, Chongqing University, Chongqing 400044 (China); Chen, Yiran [Electrical and Computer Engineering, University of Pittsburgh, PA 15261 (United States)

    2014-08-14

    Memristor is considered to be a natural electrical synapse because of its distinct memory property and nanoscale. In recent years, more and more similar behaviors are observed between memristors and biological synapse, e.g., short-term memory (STM) and long-term memory (LTM). The traditional mathematical models are unable to capture the new emerging behaviors. In this article, an updated phenomenological model based on the model of the Hewlett–Packard (HP) Labs has been proposed to capture such new behaviors. The new dynamical memristor model with an improved ion diffusion term can emulate the synapse behavior with forgetting effect, and exhibit the transformation between the STM and the LTM. Further, this model can be used in building new type of neural networks with forgetting ability like biological systems, and it is verified by our experiment with Hopfield neural network. - Highlights: • We take the Fick diffusion and the Soret diffusion into account in the ion drift theory. • We develop a new model based on the old HP model. • The new model can describe the forgetting effect and the spike-rate-dependent property of memristor. • The new model can solve the boundary effect of all window functions discussed in [13]. • A new Hopfield neural network with the forgetting ability is built by the new memristor model.

  7. A phenomenological memristor model for short-term/long-term memory

    International Nuclear Information System (INIS)

    Chen, Ling; Li, Chuandong; Huang, Tingwen; Ahmad, Hafiz Gulfam; Chen, Yiran

    2014-01-01

    Memristor is considered to be a natural electrical synapse because of its distinct memory property and nanoscale. In recent years, more and more similar behaviors are observed between memristors and biological synapse, e.g., short-term memory (STM) and long-term memory (LTM). The traditional mathematical models are unable to capture the new emerging behaviors. In this article, an updated phenomenological model based on the model of the Hewlett–Packard (HP) Labs has been proposed to capture such new behaviors. The new dynamical memristor model with an improved ion diffusion term can emulate the synapse behavior with forgetting effect, and exhibit the transformation between the STM and the LTM. Further, this model can be used in building new type of neural networks with forgetting ability like biological systems, and it is verified by our experiment with Hopfield neural network. - Highlights: • We take the Fick diffusion and the Soret diffusion into account in the ion drift theory. • We develop a new model based on the old HP model. • The new model can describe the forgetting effect and the spike-rate-dependent property of memristor. • The new model can solve the boundary effect of all window functions discussed in [13]. • A new Hopfield neural network with the forgetting ability is built by the new memristor model

  8. Short-Term Power Forecasting Model for Photovoltaic Plants Based on Historical Similarity

    Directory of Open Access Journals (Sweden)

    M. Sonia Terreros-Olarte

    2013-05-01

    Full Text Available This paper proposes a new model for short-term forecasting of electric energy production in a photovoltaic (PV plant. The model is called HIstorical SImilar MIning (HISIMI model; its final structure is optimized by using a genetic algorithm, based on data mining techniques applied to historical cases composed by past forecasted values of weather variables, obtained from numerical tools for weather prediction, and by past production of electric power in a PV plant. The HISIMI model is able to supply spot values of power forecasts, and also the uncertainty, or probabilities, associated with those spot values, providing new useful information to users with respect to traditional forecasting models for PV plants. Such probabilities enable analysis and evaluation of risk associated with those spot forecasts, for example, in offers of energy sale for electricity markets. The results of spot forecasting of an illustrative example obtained with the HISIMI model for a real-life grid-connected PV plant, which shows high intra-hour variability of its actual power output, with forecasting horizons covering the following day, have improved those obtained with other two power spot forecasting models, which are a persistence model and an artificial neural network model.

  9. Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters

    Directory of Open Access Journals (Sweden)

    Hongshan Zhao

    2012-05-01

    Full Text Available Short-term solar irradiance forecasting (STSIF is of great significance for the optimal operation and power predication of grid-connected photovoltaic (PV plants. However, STSIF is very complex to handle due to the random and nonlinear characteristics of solar irradiance under changeable weather conditions. Artificial Neural Network (ANN is suitable for STSIF modeling and many research works on this topic are presented, but the conciseness and robustness of the existing models still need to be improved. After discussing the relation between weather variations and irradiance, the characteristics of the statistical feature parameters of irradiance under different weather conditions are figured out. A novel ANN model using statistical feature parameters (ANN-SFP for STSIF is proposed in this paper. The input vector is reconstructed with several statistical feature parameters of irradiance and ambient temperature. Thus sufficient information can be effectively extracted from relatively few inputs and the model complexity is reduced. The model structure is determined by cross-validation (CV, and the Levenberg-Marquardt algorithm (LMA is used for the network training. Simulations are carried out to validate and compare the proposed model with the conventional ANN model using historical data series (ANN-HDS, and the results indicated that the forecast accuracy is obviously improved under variable weather conditions.

  10. Short-Term Photovoltaic Power Generation Forecasting Based on Multivariable Grey Theory Model with Parameter Optimization

    Directory of Open Access Journals (Sweden)

    Zhifeng Zhong

    2017-01-01

    Full Text Available Owing to the environment, temperature, and so forth, photovoltaic power generation volume is always fluctuating and subsequently impacts power grid planning and operation seriously. Therefore, it is of great importance to make accurate prediction of the power generation of photovoltaic (PV system in advance. In order to improve the prediction accuracy, in this paper, a novel particle swarm optimization algorithm based multivariable grey theory model is proposed for short-term photovoltaic power generation volume forecasting. It is highlighted that, by integrating particle swarm optimization algorithm, the prediction accuracy of grey theory model is expected to be highly improved. In addition, large amounts of real data from two separate power stations in China are being employed for model verification. The experimental results indicate that, compared with the conventional grey model, the mean relative error in the proposed model has been reduced from 7.14% to 3.53%. The real practice demonstrates that the proposed optimization model outperforms the conventional grey model from both theoretical and practical perspectives.

  11. 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)

  12. Probalistisk short-term risk modeling for back-end fuel cycle and waste management facilities

    International Nuclear Information System (INIS)

    Kjellbert, N.A.

    1980-03-01

    This study of probabilistic short-term risk modeling of back-end fuel cycle and waste management facilities represents the continuation of work started in 1977. The purpose of the report is to present a more detailed survey of models and analysis techniques that mey be applicable. The definition of the risk concept and the nature of the facilities and events which are to be analyzed are described. The most important criteria are that the model or method shall be quantitative, logically/scientifically based, and be able to handle systems of some complexity. Several formalized analysis methods are described, most of them emanating from reliability theory. No single model will fulfill all criteria simultaneously, to the degree desired. Nevertheless, fault tree analysis seems to be an efficient tool in many applications, although it must probably be used together with other models in most cases. Other methodologies described can also be useful, such as failure modes and effects analysis, renewal theory and Markov chains, reliability block diagrams, event trees and cause/consequence diagrams, the GO methodology, Monte Carlo simulation, and, often necessary, various consequence modeling techniques. (author)

  13. Spatio-temporal modelling for short term wind power forecasts. Why, when and how.

    Science.gov (United States)

    Lenzi, Amanda; Steinsland, Ingelin; Pinson, Pierre

    2017-04-01

    This study is based on a case study of 349 wind farms in Western Denmark with available energy production every 15 minutes for 6 years. Our aim is to do short term forecasting up to 5 hours ahead based on previous observations. We want sharp and calibrated probabilistic forecasts for both individual wind farms and for aggregated energy production, for example the energy production in the whole region. To obtain this we propose two Bayesian spatio-temporal models, and obtain full probabilistic forecasts of wind power. The models are based on the stochastic partial differential equation (SPDE) approach to spatial-temporal modelling which enables fast inference using integrated nested Laplace approximations (INLA) as well as dimension reduction. We provide detailed analysis on the forecast performances on the individual and aggregated level based on appropriate metrics tailored for probability forecasts for both the spatial temporal models as well as for temporal models for individual wind farms. The case study as well as simulation studies demonstrate that forecasts that are individually reliable do not need to produce an aggregated forecasts that are reliable. Indeed, the case study shows that even when all individual forecasts are calibrated can the aggregated forecasts be so uncalibrated that less that 20% of the observations fall within the 95% forecast interval. T he results and methodology are both relevant for wind power forecasts in other regions as well as for spatial-temporal modeling and decisions in general.

  14. The valuation of equity warrants under the fractional Vasicek process of the short-term interest rate

    Science.gov (United States)

    Xiao, Weilin; Zhang, Weiguo; Zhang, Xili; Chen, Xiaoyan

    2014-01-01

    Motivated by the empirical evidence of long range dependence in short-term interest rates and considering the long maturities of equity warrants, we propose the fractional Vasicek model to describe the dynamics of the short rate in the pricing environment of equity warrants. Using the partial differential equation approach, we present a valuation model for equity warrants under the assumption that the short rate follows the fractional Vasicek process. After identifying the pricing model for equity warrants, we provide the parameter estimation procedure for the proposed pricing model. Since obtaining the values of equity warrants from the proposed model needs to solve a nonlinear equation, we employ a hybrid intelligent algorithm to get around this optimization problem. Furthermore, to illustrate the practicality of our proposed model, we conduct an empirical study to ascertain the performance of our proposed model using the data from China’s warrant market and the China Foreign Exchange Trade System. The comparison of traditional models (such as the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model) with our proposed model is also presented. The empirical results show that the mean absolute percentage error of our pricing model is 10.30%. By contrast, the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model applied to the same warrant produce mean absolute errors of 35.26%, 37.67%, 33.40%, 32.81%, respectively. Thus the long memory property in stochastic interest rates cannot be ignored in determining the valuation of equity warrants.

  15. Capacity and precision in an animal model of visual short-term memory.

    Science.gov (United States)

    Lara, Antonio H; Wallis, Jonathan D

    2012-03-14

    Temporary storage of information in visual short-term memory (VSTM) is a key component of many complex cognitive abilities. However, it is highly limited in capacity. Understanding the neurophysiological nature of this capacity limit will require a valid animal model of VSTM. We used a multiple-item color change detection task to measure macaque monkeys' VSTM capacity. Subjects' performance deteriorated and reaction times increased as a function of the number of items in memory. Additionally, we measured the precision of the memory representations by varying the distance between sample and test colors. In trials with similar sample and test colors, subjects made more errors compared to trials with highly discriminable colors. We modeled the error distribution as a Gaussian function and used this to estimate the precision of VSTM representations. We found that as the number of items in memory increases the precision of the representations decreases dramatically. Additionally, we found that focusing attention on one of the objects increases the precision with which that object is stored and degrades the precision of the remaining. These results are in line with recent findings in human psychophysics and provide a solid foundation for understanding the neurophysiological nature of the capacity limit of VSTM.

  16. 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.

  17. Machine Learning Techniques for Modelling Short Term Land-Use Change

    Directory of Open Access Journals (Sweden)

    Mileva Samardžić-Petrović

    2017-11-01

    Full Text Available The representation of land use change (LUC is often achieved by using data-driven methods that include machine learning (ML techniques. The main objectives of this research study are to implement three ML techniques, Decision Trees (DT, Neural Networks (NN, and Support Vector Machines (SVM for LUC modeling, in order to compare these three ML techniques and to find the appropriate data representation. The ML techniques are applied on the case study of LUC in three municipalities of the City of Belgrade, the Republic of Serbia, using historical geospatial data sets and considering nine land use classes. The ML models were built and assessed using two different time intervals. The information gain ranking technique and the recursive attribute elimination procedure were implemented to find the most informative attributes that were related to LUC in the study area. The results indicate that all three ML techniques can be used effectively for short-term forecasting of LUC, but the SVM achieved the highest agreement of predicted changes.

  18. Intensive Short-Term Dynamic Psychotherapy for generalized anxiety disorder: A pilot effectiveness and process-outcome study.

    Science.gov (United States)

    Lilliengren, Peter; Johansson, Robert; Town, Joel M; Kisely, Steve; Abbass, Allan

    2017-11-01

    The objective of this study was to evaluate the clinical- and cost-effectiveness of Intensive Short-Term Dynamic Psychotherapy (ISTDP) for generalized anxiety disorder (GAD). We further aimed to examine if a key clinical process within the ISTDP framework, termed the level of mobilization of unprocessed complex emotions (MUCE), was related to outcome. The sample consisted of 215 adult patients (60.9% female) with GAD and comorbid conditions treated in a tertiary mental health outpatient setting. The patients were provided an average of 8.3 sessions of ISTDP delivered by 38 therapists. The level of MUCE in treatment was assessed from videotaped sessions by a rater blind to treatment outcome. Year-by-year healthcare costs were derived independently from government databases. Multilevel growth models indicated significant decreases in psychiatric symptoms and interpersonal problems during treatment. These gains were corroborated by reductions in healthcare costs that continued for 4 years post-treatment reaching normal population means. Further, we found that the in-treatment level of MUCE was associated with larger treatment effects, underlining the significance of emotional experiencing and processing in the treatment of GAD. We conclude that ISTDP appears to reduce symptoms and costs associated with GAD and that the ISTDP framework may be useful for understanding key therapeutic processes in this challenging clinical population. Controlled studies of ISTDP for GAD are warranted. Copyright © 2017 John Wiley & Sons, Ltd.

  19. A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition.

    Directory of Open Access Journals (Sweden)

    Margarita Zachariou

    Full Text Available Memories are believed to be represented in the synaptic pathways of vastly interconnected networks of neurons. The plasticity of synapses, that is, their strengthening and weakening depending on neuronal activity, is believed to be the basis of learning and establishing memories. An increasing number of studies indicate that endocannabinoids have a widespread action on brain function through modulation of synaptic transmission and plasticity. Recent experimental studies have characterised the role of endocannabinoids in mediating both short- and long-term synaptic plasticity in various brain regions including the hippocampus, a brain region strongly associated with cognitive functions, such as learning and memory. Here, we present a biophysically plausible model of cannabinoid retrograde signalling at the synaptic level and investigate how this signalling mediates depolarisation induced suppression of inhibition (DSI, a prominent form of short-term synaptic depression in inhibitory transmission in hippocampus. The model successfully captures many of the key characteristics of DSI in the hippocampus, as observed experimentally, with a minimal yet sufficient mathematical description of the major signalling molecules and cascades involved. More specifically, this model serves as a framework to test hypotheses on the factors determining the variability of DSI and investigate under which conditions it can be evoked. The model reveals the frequency and duration bands in which the post-synaptic cell can be sufficiently stimulated to elicit DSI. Moreover, the model provides key insights on how the state of the inhibitory cell modulates DSI according to its firing rate and relative timing to the post-synaptic activation. Thus, it provides concrete suggestions to further investigate experimentally how DSI modulates and is modulated by neuronal activity in the brain. Importantly, this model serves as a stepping stone for future deciphering of the role of

  20. A short-term model of COPD identifies a role for mast cell tryptase

    Science.gov (United States)

    Beckett, Emma L.; Stevens, Richard L.; Jarnicki, Andrew G.; Kim, Richard Y.; Hanish, Irwan; Hansbro, Nicole G.; Deane, Andrew; Keely, Simon; Horvat, Jay C.; Yang, Ming; Oliver, Brian G.; van Rooijen, Nico; Inman, Mark D.; Adachi, Roberto; Soberman, Roy J.; Hamadi, Sahar; Wark, Peter A.; Foster, Paul S.; Hansbro, Philip M.

    2013-01-01

    Background Cigarette smoke-induced chronic obstructive pulmonary disease (COPD) is a life-threatening inflammatory disorder of the lung. The development of effective therapies for COPD has been hampered by the lack of an animal model that mimics the human disease in a short time-frame. Objectives To create an early onset mouse model of cigarette smoke-induced COPD that develops the hallmark features of the human condition in a short time-frame. To use this model to better understand pathogenesis and the roles of macrophages and mast cells (MCs) in COPD. Methods Tightly controlled amounts of cigarette smoke were delivered to the airways of mice, and the development of the pathological features of COPD was assessed. The roles of macrophages and MC tryptase in pathogenesis were evaluated using depletion and in vitro studies and MC protease-6 deficient mice. Results After just 8 weeks of smoke exposure, wild-type mice developed chronic inflammation, mucus hypersecretion, airway remodeling, emphysema, and reduced lung function. These characteristic features of COPD were glucocorticoid-resistant and did not spontaneously resolve. Systemic effects on skeletal muscle and the heart, and increased susceptibility to respiratory infections also were observed. Macrophages and tryptase-expressing MCs were required for the development of COPD. Recombinant MC tryptase induced pro-inflammatory responses from cultured macrophages. Conclusion A short-term mouse model of cigarette smoke-induced COPD was developed in which the characteristic features of the disease were induced more rapidly than existing models. The model can be used to better understand COPD pathogenesis, and we show a requirement for macrophages and tryptase-expressing MCs. PMID:23380220

  1. Least square regression based integrated multi-parameteric demand modeling for short term load forecasting

    International Nuclear Information System (INIS)

    Halepoto, I.A.; Uqaili, M.A.

    2014-01-01

    Nowadays, due to power crisis, electricity demand forecasting is deemed an important area for socioeconomic development and proper anticipation of the load forecasting is considered essential step towards efficient power system operation, scheduling and planning. In this paper, we present STLF (Short Term Load Forecasting) using multiple regression techniques (i.e. linear, multiple linear, quadratic and exponential) by considering hour by hour load model based on specific targeted day approach with temperature variant parameter. The proposed work forecasts the future load demand correlation with linear and non-linear parameters (i.e. considering temperature in our case) through different regression approaches. The overall load forecasting error is 2.98% which is very much acceptable. From proposed regression techniques, Quadratic Regression technique performs better compared to than other techniques because it can optimally fit broad range of functions and data sets. The work proposed in this paper, will pave a path to effectively forecast the specific day load with multiple variance factors in a way that optimal accuracy can be maintained. (author)

  2. Neural processing of short-term recurrence in songbird vocal communication.

    Directory of Open Access Journals (Sweden)

    Gabriël J L Beckers

    Full Text Available BACKGROUND: Many situations involving animal communication are dominated by recurring, stereotyped signals. How do receivers optimally distinguish between frequently recurring signals and novel ones? Cortical auditory systems are known to be pre-attentively sensitive to short-term delivery statistics of artificial stimuli, but it is unknown if this phenomenon extends to the level of behaviorally relevant delivery patterns, such as those used during communication. METHODOLOGY/PRINCIPAL FINDINGS: We recorded and analyzed complete auditory scenes of spontaneously communicating zebra finch (Taeniopygia guttata pairs over a week-long period, and show that they can produce tens of thousands of short-range contact calls per day. Individual calls recur at time scales (median interval 1.5 s matching those at which mammalian sensory systems are sensitive to recent stimulus history. Next, we presented to anesthetized birds sequences of frequently recurring calls interspersed with rare ones, and recorded, in parallel, action and local field potential responses in the medio-caudal auditory forebrain at 32 unique sites. Variation in call recurrence rate over natural ranges leads to widespread and significant modulation in strength of neural responses. Such modulation is highly call-specific in secondary auditory areas, but not in the main thalamo-recipient, primary auditory area. CONCLUSIONS/SIGNIFICANCE: Our results support the hypothesis that pre-attentive neural sensitivity to short-term stimulus recurrence is involved in the analysis of auditory scenes at the level of delivery patterns of meaningful sounds. This may enable birds to efficiently and automatically distinguish frequently recurring vocalizations from other events in their auditory scene.

  3. Improving inferences from short-term ecological studies with Bayesian hierarchical modeling: white-headed woodpeckers in managed forests.

    Science.gov (United States)

    Linden, Daniel W; Roloff, Gary J

    2015-08-01

    Pilot studies are often used to design short-term research projects and long-term ecological monitoring programs, but data are sometimes discarded when they do not match the eventual survey design. Bayesian hierarchical modeling provides a convenient framework for integrating multiple data sources while explicitly separating sample variation into observation and ecological state processes. Such an approach can better estimate state uncertainty and improve inferences from short-term studies in dynamic systems. We used a dynamic multistate occupancy model to estimate the probabilities of occurrence and nesting for white-headed woodpeckers Picoides albolarvatus in recent harvest units within managed forests of northern California, USA. Our objectives were to examine how occupancy states and state transitions were related to forest management practices, and how the probabilities changed over time. Using Gibbs variable selection, we made inferences using multiple model structures and generated model-averaged estimates. Probabilities of white-headed woodpecker occurrence and nesting were high in 2009 and 2010, and the probability that nesting persisted at a site was positively related to the snag density in harvest units. Prior-year nesting resulted in higher probabilities of subsequent occurrence and nesting. We demonstrate the benefit of forest management practices that increase the density of retained snags in harvest units for providing white-headed woodpecker nesting habitat. While including an additional year of data from our pilot study did not drastically alter management recommendations, it changed the interpretation of the mechanism behind the observed dynamics. Bayesian hierarchical modeling has the potential to maximize the utility of studies based on small sample sizes while fully accounting for measurement error and both estimation and model uncertainty, thereby improving the ability of observational data to inform conservation and management strategies.

  4. Short term memory decays and high presentation rates hurry this decay: The Murdock free recall experiments interpreted in the Tagging/Retagging model

    OpenAIRE

    Tarnow, Dr. Eugen

    2009-01-01

    I show that the curious free recall data of Murdock (1962) can be explained by the Tagging/Retagging model of short term memory (Tarnow, 2009 and 2008) in which a short term memory item is a tagged long term memory item. The tagging (linear in time) corresponds to the synaptic process of exocytosis and the loss of tagging (logarithmic in time) corresponds to synaptic endocytosis. The Murdock recent item recall probabilities follow a logarithmic decay with time of recall. The slope of the d...

  5. Long-term consequences of a short-term hypergravity load in a snail model

    Science.gov (United States)

    Martynova, Marina G.; Shabelnikov, Sergej V.; Bystrova, Olga A.

    2015-07-01

    Here we focused on the dynamic processes in the snail at different time after short-term hypergravity load (STHL) by monitoring the state of neuroendocrine and immune systems, the nucleic acid synthesis levels in the atrial cells, and the behaviour of the atrial granular cells (GCs). We observed that immediately after centrifugation (14 g for 15 min) in the snail haemolymph concentration of dopamine and noradrenaline (measured by high-performance liquid chromatography) and the number of circulating haemocytes and their proliferative activity (estimated by the direct cell counting and [3H]thymidine incorporation, respectively) increased significantly, whereas the concentration of adrenaline decreased. Twenty-four hours after STHL, the levels of catecholamines and haemocytes returned to their control values. In the atrial epicardial and endothelial cells, a notable drop of transcription activity (evaluated by [3H]uridine autoradiography) from the baseline in the immediate post-STHL period was followed by its gradual increase reaching a maximum at the day 5 and subsequent decrease to control value by the day 10. In endothelial cells, DNA-synthesizing activity (evaluated by [3H]thymidine autoradiography) equal to zero before and just after STHL, increased significantly at the day 5, and decreased by the day 10. The atrial GCs underwent total degranulation. Formed as a result small ungranulated cells exhibited DNA synthesis. Afterwards, most probably, the GCs divided and regranulated. One month after STHL the GC population had been restored. Overall, STHL has triggered an immediate reaction of the neuroendocrine and immune systems and initiated long-lasting processes at a cellular level, which included alterations in activity of nucleic acid syntheses in the epicardial and endothelial cells and remodelling of the GC population in the atrium.

  6. Energy storage systems impact on the short-term frequency stability of distributed autonomous microgrids, an analysis using aggregate models

    DEFF Research Database (Denmark)

    Serban, Ioan; Teodorescu, Remus; Marinescu, Corneliu

    2013-01-01

    This study analyses the integration impact of battery energy storage systems (BESSs) on the short-term frequency control in autonomous microgrids (MGs). Short-term frequency stability relates with the primary or speed control level, as defined in the regulations of the classical grids. The focus...... with both inertial response and an adaptive droop characteristic during battery state-of-charge limitations. The conducted analysis is accomplished by adopting aggregated models for the involved control mechanisms. The developed model is analysed in frequency domain, whereas an experimental test bench...

  7. Comfrey (Symphytum Officinale. l.) and Experimental Hepatic Carcinogenesis: A Short-term Carcinogenesis Model Study.

    Science.gov (United States)

    Gomes, Maria Fernanda Pereira Lavieri; de Oliveira Massoco, Cristina; Xavier, José Guilherme; Bonamin, Leoni Villano

    2010-06-01

    Comfrey or Symphytum officinale (L.) (Boraginaceae) is a very popular plant used for therapeutic purposes. Since the 1980s, its effects have been studied in long-term carcinogenesis studies, in which Comfrey extract is administered at high doses during several months and the neoplastic hepatic lesions are evaluated. However, the literature on this topic is very poor considering the studies performed under short-term carcinogenesis protocols, such as the 'resistant hepatocyte model' (RHM). In these studies, it is possible to observe easily the phenomena related to the early phases of tumor development, since pre-neoplastic lesions (PNLs) rise in about 1-2 months of chemical induction. Herein, the effects of chronic oral treatment of rats with 10% Comfrey ethanolic extract were evaluated in a RHM. Wistar rats were sequentially treated with N-nitrosodiethylamine (ip) and 2-acetilaminofluorene (po), and submitted to hepatectomy to induce carcinogenesis promotion. Macroscopic/microscopic quantitative analysis of PNL was performed. Non-parametric statistical tests (Mann-Whitney and χ(2)) were used, and the level of significance was set at P ≤ 0.05. Comfrey treatment reduced the number of pre-neoplastic macroscopic lesions up to 1 mm (P ≤ 0.05), the percentage of oval cells (P = 0.0001) and mitotic figures (P = 0.007), as well as the number of Proliferating Cell Nuclear Antigen (PCNA) positive cells (P = 0.0001) and acidophilic pre-neoplastic nodules (P = 0.05). On the other hand, the percentage of cells presenting megalocytosis (P = 0.0001) and vacuolar degeneration (P = 0.0001) was increased. Scores of fibrosis, glycogen stores and the number of nucleolus organizing regions were not altered. The study indicated that oral treatment of rats with 10% Comfrey alcoholic extract reduced cell proliferation in this model.

  8. Short Term Intervention Model for Enhancing Divergent Thinking among School Aged Children

    Science.gov (United States)

    Doron, Eyal

    2016-01-01

    Creative ability can be developed and improved through intervention and training. This study presents a unique and innovative intervention program for enhancing creative thinking among children, focusing on divergent thinking skills. The program was designed as a short-term (10 weeks) training and conducted with 150 school students ranging in age…

  9. The attention-weighted sample-size model of visual short-term memory

    DEFF Research Database (Denmark)

    Smith, Philip L.; Lilburn, Simon D.; Corbett, Elaine A.

    2016-01-01

    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...

  10. 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

  11. Grouping Influences Output Interference in Short-term Memory: A Mixture Modeling Study.

    Science.gov (United States)

    Kang, Min-Suk; Oh, Byung-Il

    2016-01-01

    Output interference is a source of forgetting induced by recalling. We investigated how grouping influences output interference in short-term memory. In Experiment 1, the participants were asked to remember four colored items. Those items were grouped by temporal coincidence as well as spatial alignment: two items were presented in the first memory array and two were presented in the second, and the items in both arrays were either vertically or horizontally aligned as well. The participants then performed two recall tasks in sequence by selecting a color presented at a cued location from a color wheel. In the same-group condition, the participants reported both items from the same memory array; however, in the different-group condition, the participants reported one item from each memory array. We analyzed participant responses with a mixture model, which yielded two measures: guess rate and precision of recalled memories. The guess rate in the second recall was higher for the different-group condition than for the same-group condition; however, the memory precisions obtained for both conditions were similarly degraded in the second recall. In Experiment 2, we varied the probability of the same- and different-group conditions with a ratio of 3 to 7. We expected output interference to be higher in the same-group condition than in the different-group condition. This is because items of the other group are more likely to be probed in the second recall phase and, thus, protecting those items during the first recall phase leads to a better performance. Nevertheless, the same pattern of results was robustly reproduced, suggesting grouping shields the grouped items from output interference because of the secured accessibility. We discussed how grouping influences output interference.

  12. Grouping influences output interference in short-term memory: a mixture modeling study

    Directory of Open Access Journals (Sweden)

    Min-Suk eKang

    2016-05-01

    Full Text Available Output interference is a source of forgetting induced by recalling. We investigated how grouping influences output interference in short-term memory. In Experiment 1, the participants were asked to remember four colored items. Those items were grouped by temporal coincidence as well as spatial alignment: two items were presented in the first memory array and two were presented in the second, and the items in both arrays were either vertically or horizontally aligned as well. The participants then performed two recall tasks in sequence by selecting a color presented at a cued location from a color wheel. In the same-group condition, the participants reported both items from the same memory array; however, in the different-group condition, the participants reported one item from each memory array. We analyzed participant responses with a mixture model, which yielded two measures: guess rate and precision of recalled memories. The guess rate in the second recall was higher for the different-group condition than for the same-group condition; however, the memory precisions obtained for both conditions were similarly degraded in the second recall. In Experiment 2, we varied the probability of the same- and different-group conditions with a ratio of 3 to 7. We expected output interference to be higher in the same-group condition than in the different-group condition. This is because items of the other group are more likely to be probed in the second recall phase and, thus, protecting those items during the first recall phase leads to a better performance. Nevertheless, the same pattern of results was robustly reproduced, suggesting grouping shields the grouped items from output interference because of the secured accessibility. We discussed how grouping influences output interference.

  13. Comfrey (Symphytum officinale. L. and Experimental Hepatic Carcinogenesis: A Short-Term Carcinogenesis Model Study

    Directory of Open Access Journals (Sweden)

    Maria Fernanda Pereira Lavieri Gomes

    2010-01-01

    Full Text Available Comfrey or Symphytum officinale (L. (Boraginaceae is a very popular plant used for therapeutic purposes. Since the 1980s, its effects have been studied in long-term carcinogenesis studies, in which Comfrey extract is administered at high doses during several months and the neoplastic hepatic lesions are evaluated. However, the literature on this topic is very poor considering the studies performed under short-term carcinogenesis protocols, such as the ‘resistant hepatocyte model’ (RHM. In these studies, it is possible to observe easily the phenomena related to the early phases of tumor development, since pre-neoplastic lesions (PNLs rise in about 1–2 months of chemical induction. Herein, the effects of chronic oral treatment of rats with 10% Comfrey ethanolic extract were evaluated in a RHM. Wistar rats were sequentially treated with N-nitrosodiethylamine (ip and 2-acetilaminofluorene (po, and submitted to hepatectomy to induce carcinogenesis promotion. Macroscopic/microscopic quantitative analysis of PNL was performed. Non-parametric statistical tests (Mann–Whitney and χ2 were used, and the level of significance was set at P ≤ 0.05. Comfrey treatment reduced the number of pre-neoplastic macroscopic lesions up to 1 mm (P ≤ 0.05, the percentage of oval cells (P = 0.0001 and mitotic figures (P = 0.007, as well as the number of Proliferating Cell Nuclear Antigen (PCNA positive cells (P = 0.0001 and acidophilic pre-neoplastic nodules (P = 0.05. On the other hand, the percentage of cells presenting megalocytosis (P = 0.0001 and vacuolar degeneration (P = 0.0001 was increased. Scores of fibrosis, glycogen stores and the number of nucleolus organizing regions were not altered. The study indicated that oral treatment of rats with 10% Comfrey alcoholic extract reduced cell proliferation in this model.

  14. A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network

    International Nuclear Information System (INIS)

    Yu, Feng; Xu, Xiaozhong

    2014-01-01

    Highlights: • A detailed data processing will make more accurate results prediction. • Taking a full account of more load factors to improve the prediction precision. • Improved BP network obtains higher learning convergence. • Genetic algorithm optimized by chaotic cat map enhances the global search ability. • The combined GA–BP model improved by modified additional momentum factor is superior to others. - Abstract: This paper proposes an appropriate combinational approach which is based on improved BP neural network for short-term gas load forecasting, and the network is optimized by the real-coded genetic algorithm. Firstly, several kinds of modifications are carried out on the standard neural network to accelerate the convergence speed of network, including improved additional momentum factor, improved self-adaptive learning rate and improved momentum and self-adaptive learning rate. Then, it is available to use the global search capability of optimized genetic algorithm to determine the initial weights and thresholds of BP neural network to avoid being trapped in local minima. The ability of GA is enhanced by cat chaotic mapping. In light of the characteristic of natural gas load for Shanghai, a series of data preprocessing methods are adopted and more comprehensive load factors are taken into account to improve the prediction accuracy. Such improvements facilitate forecasting efficiency and exert maximum performance of the model. As a result, the integration model improved by modified additional momentum factor gets more ideal solutions for short-term gas load forecasting, through analyses and comparisons of the above several different combinational algorithms

  15. Impact of Participating in a Short-Term Intervention Model of Sports Education Camps for Children with Visual Impairments

    Science.gov (United States)

    Mc Mahon, John M.

    2013-01-01

    This three-paper format dissertation explores three topics relevant to participating in a short-term model Sports Education Camp for youth with vision impairments. The three papers are independent studies, yet build upon each other by first measuring physical performance in certain skills, then exploring their levels of self-perception, body mass…

  16. A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model

    International Nuclear Information System (INIS)

    Wang, Jianzhou; Hu, Jianming

    2015-01-01

    With the increasing importance of wind power as a component of power systems, the problems induced by the stochastic and intermittent nature of wind speed have compelled system operators and researchers to search for more reliable techniques to forecast wind speed. This paper proposes a combination model for probabilistic short-term wind speed forecasting. In this proposed hybrid approach, EWT (Empirical Wavelet Transform) is employed to extract meaningful information from a wind speed series by designing an appropriate wavelet filter bank. The GPR (Gaussian Process Regression) model is utilized to combine independent forecasts generated by various forecasting engines (ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM)) in a nonlinear way rather than the commonly used linear way. The proposed approach provides more probabilistic information for wind speed predictions besides improving the forecasting accuracy for single-value predictions. The effectiveness of the proposed approach is demonstrated with wind speed data from two wind farms in China. The results indicate that the individual forecasting engines do not consistently forecast short-term wind speed for the two sites, and the proposed combination method can generate a more reliable and accurate forecast. - Highlights: • The proposed approach can make probabilistic modeling for wind speed series. • The proposed approach adapts to the time-varying characteristic of the wind speed. • The hybrid approach can extract the meaningful components from the wind speed series. • The proposed method can generate adaptive, reliable and more accurate forecasting results. • The proposed model combines four independent forecasting engines in a nonlinear way.

  17. Accident tolerant clad material modeling by MELCOR: Benchmark for SURRY Short Term Station Black Out

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jun, E-mail: jwang564@wisc.edu [College of Engineering, The University of Wisconsin-Madison, Madison 53706 (United States); Mccabe, Mckinleigh [College of Engineering, The University of Wisconsin-Madison, Madison 53706 (United States); Wu, Lei [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China); Dong, Xiaomeng [College of Engineering, The University of Wisconsin-Madison, Madison 53706 (United States); Wang, Xianmao [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China); Haskin, Troy Christopher [College of Engineering, The University of Wisconsin-Madison, Madison 53706 (United States); Corradini, Michael L., E-mail: corradini@engr.wisc.edu [College of Engineering, The University of Wisconsin-Madison, Madison 53706 (United States)

    2017-03-15

    Highlights: • Thermo-physical and oxidation kinetics properties calculation and analysis of FeCrAl. • Properties modelling of FeCrAl in MELCOR. • Benchmark calculation of Surry nuclear power plant. - Abstract: Accident tolerant fuel and cladding materials are being investigated to provide a greater resistance to fuel degradation, oxidation and melting if long-term cooling is lost in a Light Water Reactor (LWR) following an accident such as a Station Blackout (SBO) or Loss of Coolant Accident (LOCA). Researchers at UW-Madison are analyzing an SBO sequence and examining the effect of a loss of auxiliary feedwater (AFW) with the MELCOR systems code. Our research work considers accident tolerant cladding materials (e.g., FeCrAl alloy) and their effect on the accident behavior. We first gathered the physical properties of this alternative cladding material via literature review and compared it to the usual zirconium alloys used in LWRs. We then developed a model for the Surry reactor for a Short-term SBO sequence and examined the effect of replacing FeCrAl for Zircaloy cladding. The analysis uses MELCOR, Version 1.8.6 YR, which is developed by Idaho National Laboratory in collaboration with MELCOR developers at Sandia National Laboratories. This version allows the user to alter the cladding material considered, and our study examines the behavior of the FeCrAl alloy as a substitute for Zircaloy. Our benchmark comparisons with the Sandia National Laboratory’s analysis of Surry using MELCOR 1.8.6 and the more recent MELCOR 2.1 indicate good overall agreement through the early phases of the accident progression. When FeCrAl is substituted for Zircaloy to examine its performance, we confirmed that FeCrAl slows the accident progression and reduce the amount of hydrogen generated. Our analyses also show that this special version of MELCOR can be used to evaluate other potential ATF cladding materials, e.g., SiC as well as innovative coatings on zirconium cladding

  18. Application of Quantitative Models, MNLR and ANN in Short Term Forecasting of Ship Data

    OpenAIRE

    P.Oliver Jayaprakash; K. Gunasekaran

    2011-01-01

    Forecasting has been the trouble-free way for the port authorities to derive the future expected values of service time of Bulk cargo ships handled at ports of South India. The short term forecasting could be an effective tool for estimating the resource requirements of recurring ships of similar tonnage and Cargo. Forecasting the arrival data related to port based ship operations customarily done using the standard algorithms and assumptions. The regular forecasting methods were decompositio...

  19. 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.

  20. Examining the short term effects of emotion under an Adaptation Level Theory model of tinnitus perception.

    Science.gov (United States)

    Durai, Mithila; O'Keeffe, Mary G; Searchfield, Grant D

    2017-03-01

    Existing evidence suggests a strong relationship between tinnitus and emotion. The objective of this study was to examine the effects of short-term emotional changes along valence and arousal dimensions on tinnitus outcomes. Emotional stimuli were presented in two different modalities: auditory and visual. The authors hypothesized that (1) negative valence (unpleasant) stimuli and/or high arousal stimuli will lead to greater tinnitus loudness and annoyance than positive valence and/or low arousal stimuli, and (2) auditory emotional stimuli, which are in the same modality as the tinnitus, will exhibit a greater effect on tinnitus outcome measures than visual stimuli. Auditory and visual emotive stimuli were administered to 22 participants (12 females and 10 males) with chronic tinnitus, recruited via email invitations send out to the University of Auckland Tinnitus Research Volunteer Database. Emotional stimuli used were taken from the International Affective Digital Sounds- Version 2 (IADS-2) and the International Affective Picture System (IAPS) (Bradley and Lang, 2007a, 2007b). The Emotion Regulation Questionnaire (Gross and John, 2003) was administered alongside subjective ratings of tinnitus loudness and annoyance, and psychoacoustic sensation level matches to external sounds. Males had significantly different emotional regulation scores than females. Negative valence emotional auditory stimuli led to higher tinnitus loudness ratings in males and females and higher annoyance ratings in males only; loudness matches of tinnitus remained unchanged. The visual stimuli did not have an effect on tinnitus ratings. The results are discussed relative to the Adaptation Level Theory Model of Tinnitus. The results indicate that the negative valence dimension of emotion is associated with increased tinnitus magnitude judgements and gender effects may also be present, but only when the emotional stimulus is in the auditory modality. Sounds with emotional associations may be

  1. Short-term Periodization Models: Effects on Strength and Speed-strength Performance.

    Science.gov (United States)

    Hartmann, Hagen; Wirth, Klaus; Keiner, Michael; Mickel, Christoph; Sander, Andre; Szilvas, Elena

    2015-10-01

    Dividing training objectives into consecutive phases to gain morphological adaptations (hypertrophy phase) and neural adaptations (strength and power phases) is called strength-power periodization (SPP). These phases differ in program variables (volume, intensity, and exercise choice or type) and use stepwise intensity progression and concomitant decreasing volume, converging to peak intensity (peaking phase). Undulating periodization strategies rotate these program variables in a bi-weekly, weekly, or daily fashion. The following review addresses the effects of different short-term periodization models on strength and speed-strength both with subjects of different performance levels and with competitive athletes from different sports who use a particular periodization model during off-season, pre-season, and in-season conditioning. In most periodization studies, it is obvious that the strength endurance sessions are characterized by repetition zones (12-15 repetitions) that induce muscle hypertrophy in persons with a low performance level. Strictly speaking, when examining subjects with a low training level, many periodization studies include mainly hypertrophy sessions interspersed with heavy strength/power sessions. Studies have demonstrated equal or statistically significant higher gains in maximal strength for daily undulating periodization compared with SPP in subjects with a low to moderate performance level. The relatively short intervention period and the lack of concomitant sports conditioning call into question the practical value of these findings for competitive athletes. Possibly owing to differences in mesocycle length, conditioning programs, and program variables, competitive athletes either maintained or improved strength and/or speed-strength performance by integrating daily undulating periodization and SPP during off-season, pre-season and in-season conditioning. In high-performance sports, high-repetition strength training (>15) should be

  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. Quantification of compensatory processes of postnatal hypoxia in newborn piglets applying short-term nonlinear dynamics analysis

    Directory of Open Access Journals (Sweden)

    Walter Bernd

    2011-10-01

    Full Text Available Abstract Background Newborn mammals suffering from moderate hypoxia during or after birth are able to compensate a transitory lack of oxygen by adapting their vital functions. Exposure to hypoxia leads to an increase in the sympathetic tone causing cardio-respiratory response, peripheral vasoconstriction and vasodilatation in privileged organs like the heart and brain. However, there is only limited information available about the time and intensity changes of the underlying complex processes controlled by the autonomic nervous system. Methods In this study an animal model involving seven piglets was used to examine an induced state of circulatory redistribution caused by moderate oxygen deficit. In addition to the main focus on the complex dynamics occurring during sustained normocapnic hypoxia, the development of autonomic regulation after induced reoxygenation had been analysed. For this purpose, we first introduced a new algorithm to prove stationary conditions in short-term time series. Then we investigated a multitude of indices from heart rate and blood pressure variability and from bivariate interactions, also analysing respiration signals, to quantify the complexity of vegetative oscillations influenced by hypoxia. Results The results demonstrated that normocapnic hypoxia causes an initial increase in cardiovascular complexity and variability, which decreases during moderate hypoxia lasting one hour (p Conclusions In conclusion, indices from linear and nonlinear dynamics reflect considerable temporal changes of complexity in autonomous cardio-respiratory regulation due to normocapnic hypoxia shortly after birth. These findings might be suitable for non-invasive clinical monitoring of hypoxia-induced changes of autonomic regulation in newborn humans.

  4. Time-series regression models to study the short-term effects of environmental factors on health

    OpenAIRE

    Tobías, Aureli; Saez, Marc

    2004-01-01

    Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological pu...

  5. Downscaling of Short-Term Precipitation from Regional Climate Models for Sustainable Urban Planning

    Directory of Open Access Journals (Sweden)

    Holger Hoppe

    2012-05-01

    Full Text Available A framework for downscaling precipitation from RCM projections to the high resolutions in time and space required in the urban hydrological climate change impact assessment is outlined and demonstrated. The basic approach is that of Delta Change, developed for both continuous and event-based applications. In both cases, Delta Change Factors (DCFs are calculated which represent the expected future change of some key precipitation statistics. In the continuous case, short-term precipitation from climate projections are analysed in order to estimate DCFs associated with different percentiles in the frequency distribution of non-zero intensities. The DCFs may then be applied to an observed time series, producing a realisation of a future time series. The event-based case involves downscaling of Intensity-Duration-Frequency (IDF curves based on extreme value analysis of annual maxima using the Gumbel distribution. The resulting DCFs are expressed as a function of duration and frequency (i.e., return period and may be used to estimate future design storms. The applications are demonstrated in case studies focusing on the expected changes in short-term precipitation statistics until 2100 in the cities of Linz (Austria and Wuppertal (Germany. The downscaling framework is implemented in the climate service developed within the EU-project SUDPLAN.

  6. 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.

  7. Evaluation of the E mu-pim-1 transgenic mouse model for short-term carcinogenicity testing

    DEFF Research Database (Denmark)

    van Kreijl, C. F.; van Oordt, C. W. V.; Kroese, E. D.

    1998-01-01

    The value of the chronic rodent carcinogenicity assay in adequately predicting cancer risk in humans has become a matter of debate over the past few years. Therefore, more rapid and accurate alternative tests are urgently needed. Transgenic mouse models, those harboring genetic changes that are r......The value of the chronic rodent carcinogenicity assay in adequately predicting cancer risk in humans has become a matter of debate over the past few years. Therefore, more rapid and accurate alternative tests are urgently needed. Transgenic mouse models, those harboring genetic changes...... with regard to its usefulness in short-term carcinogenicity testing. It has been shown that the model is primarily suitable as a sensitive short-term assay for genotoxic carcinogens that not only induce (at least) gene mutations and/or large deletions and rearrangements but that also sufficiently target...

  8. Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model

    Directory of Open Access Journals (Sweden)

    Wenlei Bai

    2017-12-01

    Full Text Available The deterministic methods generally used to solve DC optimal power flow (OPF do not fully capture the uncertainty information in wind power, and thus their solutions could be suboptimal. However, the stochastic dynamic AC OPF problem can be used to find an optimal solution by fully capturing the uncertainty information of wind power. That uncertainty information of future wind power can be well represented by the short-term future wind power scenarios that are forecasted using the generalized dynamic factor model (GDFM—a novel multivariate statistical wind power forecasting model. Furthermore, the GDFM can accurately represent the spatial and temporal correlations among wind farms through the multivariate stochastic process. Fully capturing the uncertainty information in the spatially and temporally correlated GDFM scenarios can lead to a better AC OPF solution under a high penetration level of wind power. Since the GDFM is a factor analysis based model, the computational time can also be reduced. In order to further reduce the computational time, a modified artificial bee colony (ABC algorithm is used to solve the AC OPF problem based on the GDFM forecasting scenarios. Using the modified ABC algorithm based on the GDFM forecasting scenarios has resulted in better AC OPF’ solutions on an IEEE 118-bus system at every hour for 24 h.

  9. Long and Short-Term Memory Processes in Cortically Damaged Patients.

    Science.gov (United States)

    1981-01-01

    NEUROLINGUISTICS .................. 4 a. Psycholinguistics ....................................... 4 Processing Steps...11 b. Neurolinguistics ....................................... 12 Language Comprehension ................................. 13 Phonological Aspects...populations (e.g., Korsakoff patients). -- - --- ---- --- 7 -- --- -- ~- - T I. PSYCHOLINGUISTICS AND NEUROLINGUISTICS This chapter will attempt to specify

  10. Interacting adaptive processes with different timescales underlie short-term motor learning.

    Directory of Open Access Journals (Sweden)

    Maurice A Smith

    2006-06-01

    Full Text Available Multiple processes may contribute to motor skill acquisition, but it is thought that many of these processes require sleep or the passage of long periods of time ranging from several hours to many days or weeks. Here we demonstrate that within a timescale of minutes, two distinct fast-acting processes drive motor adaptation. One process responds weakly to error but retains information well, whereas the other responds strongly but has poor retention. This two-state learning system makes the surprising prediction of spontaneous recovery (or adaptation rebound if error feedback is clamped at zero following an adaptation-extinction training episode. We used a novel paradigm to experimentally confirm this prediction in human motor learning of reaching, and we show that the interaction between the learning processes in this simple two-state system provides a unifying explanation for several different, apparently unrelated, phenomena in motor adaptation including savings, anterograde interference, spontaneous recovery, and rapid unlearning. Our results suggest that motor adaptation depends on at least two distinct neural systems that have different sensitivity to error and retain information at different rates.

  11. Complex Network Structure Influences Processing in Long-Term and Short-Term Memory

    Science.gov (United States)

    Vitevitch, Michael S.; Chan, Kit Ying; Roodenrys, Steven

    2012-01-01

    Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological…

  12. Short-Term Memory and Auditory Processing Disorders: Concurrent Validity and Clinical Diagnostic Markers

    Science.gov (United States)

    Maerlender, Arthur

    2010-01-01

    Auditory processing disorders (APDs) are of interest to educators and clinicians, as they impact school functioning. Little work has been completed to demonstrate how children with APDs perform on clinical tests. In a series of studies, standard clinical (psychometric) tests from the Wechsler Intelligence Scale for Children, Fourth Edition…

  13. Effects of short-term quetiapine treatment on emotional processing, sleep and circadian rhythms.

    Science.gov (United States)

    Rock, Philippa L; Goodwin, Guy M; Wulff, Katharina; McTavish, Sarah F B; Harmer, Catherine J

    2016-03-01

    Quetiapine is an atypical antipsychotic that can stabilise mood from any index episode of bipolar disorder. This study investigated the effects of seven-day quetiapine administration on sleep, circadian rhythms and emotional processing in healthy volunteers. Twenty healthy volunteers received 150 mg quetiapine XL for seven nights and 20 matched controls received placebo. Sleep-wake actigraphy was completed for one week both pre-dose and during drug treatment. On Day 8, participants completed emotional processing tasks. Actigraphy revealed that quetiapine treatment increased sleep duration and efficiency, delayed final wake time and had a tendency to reduce within-day variability. There were no effects of quetiapine on subjective ratings of mood or energy. Quetiapine-treated participants showed diminished bias towards positive words and away from negative words during recognition memory. Quetiapine did not significantly affect facial expression recognition, emotional word categorisation, emotion-potentiated startle or emotional word/faces dot-probe vigilance reaction times. These changes in sleep timing and circadian rhythmicity in healthy volunteers may be relevant to quetiapine's therapeutic actions. Effects on emotional processing did not emulate the effects of antidepressants. The effects of quetiapine on sleep and circadian rhythms in patients with bipolar disorder merit further investigation to elucidate its mechanisms of action. © The Author(s) 2016.

  14. A model to forecast short-term snowmelt runoff using synoptic observations of streamflow, temperature, and precipitation

    Science.gov (United States)

    Tangborn, Wendell V.

    1980-01-01

    Snowmelt runoff is forecast with a statistical model that utilizes daily values of stream discharge, gaged precipitation, and maximum and minimum observations of air temperature. Synoptic observations of these variables are made at existing low- and medium-altitude weather stations, thus eliminating the difficulties and expense of new, high-altitude installations. Four model development steps are used to demonstrate the influence on prediction accuracy of basin storage, a preforecast test season, air temperature (to estimate ablation), and a prediction based on storage. Daily ablation is determined by a technique that employs both mean temperature and a radiative index. Radiation (both long- and short-wave components) is approximated by using the range in daily temperature, which is shown to be closely related to mean cloud cover. A technique based on the relationship between prediction error and prediction season weather utilizes short-term forecasts of precipitation and temperature to improve the final prediction. Verification of the model is accomplished by a split sampling technique for the 1960–1977 period. Short- term (5–15 days) predictions of runoff throughout the main snowmelt season are demonstrated for mountain drainages in western Washington, south-central Arizona, western Montana, and central California. The coefficient of prediction (Cp) based on actual, short-term predictions for 18 years is for Thunder Creek (Washington), 0.69; for South Fork Flathead River (Montana), 0.45; for the Black River (Arizona), 0.80; and for the Kings River (California), 0.80.

  15. Expression, processing and transcriptional regulation of granulysin in short-term activated human lymphocytes

    Directory of Open Access Journals (Sweden)

    Groscurth Peter

    2007-06-01

    Full Text Available Abstract Background Granulysin, a cytotoxic protein expressed in human natural killer cells and activated T lymphocytes, exhibits cytolytic activity against a variety of intracellular microbes. Expression and transcription have been partially characterised in vitro and four transcripts (NKG5, 519, 520, and 522 were identified. However, only a single protein product of 15 kDa was found, which is subsequently processed to an active 9 kDa protein. Results In this study we investigated generation of granulysin in lymphokine activated killer (LAK cells and antigen (Listeria specific T-cells. Semiquantitative RT-PCR revealed NKG5 to be the most prominent transcript. It was found to be up-regulated in a time-dependent manner in LAK cells and antigen specific T-cells and their subsets. Two isoforms of 519 mRNA were up-regulated under IL-2 and antigen stimulation. Moreover, two novel transcripts, without any known function, comprising solely parts of the 5 prime region of the primary transcript, were detected. A significant increase of granulysin expressing LAK cells as well as antigen specific T-cells was shown by fluorescence microscopy. On the subset level, increase in CD4+ granulysin expressing cells was found only under antigen stimulation. Immunoblotting showed the 15 kDa form of granulysin to be present in the first week of stimulation either with IL-2 or with bacterial antigen. Substantial processing to the 9 kDa form was detected during the first week in LAK cells and in the second week in antigen specific T-cells. Conclusion This first comprehensive study of granulysin gene regulation in primary cultured human lymphocytes shows that the regulation of granulysin synthesis in response to IL-2 or bacterial antigen stimulation occurs at several levels: RNA expression, extensive alternative splicing and posttranslational processing.

  16. Markov Chain Modelling for Short-Term NDVI Time Series Forecasting

    Directory of Open Access Journals (Sweden)

    Stepčenko Artūrs

    2016-12-01

    Full Text Available In this paper, the NDVI time series forecasting model has been developed based on the use of discrete time, continuous state Markov chain of suitable order. The normalised difference vegetation index (NDVI is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation; therefore, it is an important variable for vegetation forecasting. A Markov chain is a stochastic process that consists of a state space. This stochastic process undergoes transitions from one state to another in the state space with some probabilities. A Markov chain forecast model is flexible in accommodating various forecast assumptions and structures. The present paper discusses the considerations and techniques in building a Markov chain forecast model at each step. Continuous state Markov chain model is analytically described. Finally, the application of the proposed Markov chain model is illustrated with reference to a set of NDVI time series data.

  17. Short term preservation of hide using vacuum: influence on properties of hide and of processed leather.

    Science.gov (United States)

    Gudro, Ilze; Valeika, Virgilijus; Sirvaitytė, Justa

    2014-01-01

    The objective of this work was to investigate vacuum influence on hide preservation time and how it affects hide structure. It was established that vacuum prolongs the storage time without hide tissue putrefaction up to 21 days when the storage temperature is 4°C. The microorganisms act for all storage times, but the action is weak and has no observable influence on the quality of hide during the time period mentioned. The hide shrinkage temperature decrease is negligible, which shows that breaking of intermolecular bonds does not occur. Optical microscopy, infrared spectroscopy and differential scanning calorimetry also did not show any structural changes which can influence the quality of leather produced from such hide. The qualitative indexes of wet blue processed under laboratory conditions and of leather produced during industrial trials are presented. Indexes such as chromium compounds exhaustion, content of chromium in leather, content of soluble matter in dichloromethane, strength properties, and shrinkage temperature were determined. Properties of the leather produced from vacuumed hide under industrial conditions conformed to the requirements of shoe upper leather.

  18. Short-Term Molecular Acclimation Processes of Legume Nodules to Increased External Oxygen Concentration

    Science.gov (United States)

    Avenhaus, Ulrike; Cabeza, Ricardo A.; Liese, Rebecca; Lingner, Annika; Dittert, Klaus; Salinas-Riester, Gabriela; Pommerenke, Claudia; Schulze, Joachim

    2016-01-01

    Nitrogenase is an oxygen labile enzyme. Microaerobic conditions within the infected zone of nodules are maintained primarily by an oxygen diffusion barrier (ODB) located in the nodule cortex. Flexibility of the ODB is important for the acclimation processes of nodules in response to changes in external oxygen concentration. The hypothesis of the present study was that there are additional molecular mechanisms involved. Nodule activity of Medicago truncatula plants were continuously monitored during a change from 21 to 25 or 30% oxygen around root nodules by measuring nodule H2 evolution. Within about 2 min of the increase in oxygen concentration, a steep decline in nitrogenase activity occurred. A quick recovery commenced about 8 min later. A qPCR-based analysis of the expression of genes for nitrogenase components showed a tendency toward upregulation during the recovery. The recovery resulted in a new constant activity after about 30 min, corresponding to approximately 90% of the pre-treatment level. An RNAseq-based comparative transcriptome profiling of nodules at that point in time revealed that genes for nodule-specific cysteine-rich (NCR) peptides, defensins, leghaemoglobin and chalcone and stilbene synthase were significantly upregulated when considered as a gene family. A gene for a nicotianamine synthase-like protein (Medtr1g084050) showed a strong increase in count number. The gene appears to be of importance for nodule functioning, as evidenced by its consistently high expression in nodules and a strong reaction to various environmental cues that influence nodule activity. A Tnt1-mutant that carries an insert in the coding sequence (cds) of that gene showed reduced nitrogen fixation and less efficient acclimation to an increased external oxygen concentration. It was concluded that sudden increases in oxygen concentration around nodules destroy nitrogenase, which is quickly counteracted by an increased neoformation of the enzyme. This reaction might be

  19. Short-term molecular acclimation processes of legume nodules to increased external oxygen concentration

    Directory of Open Access Journals (Sweden)

    Ulrike eAvenhaus

    2016-01-01

    Full Text Available Nitrogenase is an oxygen labile enzyme. Microaerobic conditions within the infected zone of nodules are maintained primarily by an oxygen diffusion barrier located in the nodule cortex. Flexibility of the oxygen diffusion barrier is important for the acclimation processes of nodules in response to changes in external oxygen concentration. The hypothesis of the present study was that there are additional molecular mechanisms involved. Nodule activity of Medicago truncatula plants were continuously monitored during a change from 21 to 25 or 30 % oxygen around root nodules by measuring nodule H2 evolution. Within about two minutes of the increase in oxygen concentration, a steep decline in nitrogenase activity occurred. A quick recovery commenced about eight minutes later. A qPCR-based analysis of the expression of genes for nitrogenase components showed a tendency towards upregulation during the recovery. The recovery resulted in a new constant activity after about 30 minutes, corresponding to approximately 90 % of the pre-treatment level. An RNAseq-based comparative transcriptome profiling of nodules at that point in time revealed that genes for nodule-specific cysteine-rich (NCR peptides, defensins, leghaemoglobin and chalcone and stilbene synthase were significantly upregulated when considered as a gene family. A gene for a nicotianamine synthase-like protein (Medtr1g084050 showed a strong increase in count number. The gene appears to be of importance for nodule functioning, as evidenced by its consistently high expression in nodules and a strong reaction to various environmental cues that influence nodule activity. A Tnt1-mutant that carries an insert in the coding sequence (cds of that gene showed reduced nitrogen fixation and less efficient acclimation to an increased external oxygen concentration. It was concluded that sudden increases in oxygen concentration around nodules destroy nitrogenase, which is quickly counteracted by an increased

  20. Short-term treatment with flumazenil restores long-term object memory in a mouse model of Down syndrome.

    Science.gov (United States)

    Colas, Damien; Chuluun, Bayarsaikhan; Garner, Craig C; Heller, H Craig

    2017-04-01

    Down syndrome (DS) is a common genetic cause of intellectual disability yet no pro-cognitive drug therapies are approved for human use. Mechanistic studies in a mouse model of DS (Ts65Dn mice) demonstrate that impaired cognitive function is due to excessive neuronal inhibitory tone. These deficits are normalized by chronic, short-term low doses of GABA A receptor (GABA A R) antagonists in adult animals, but none of the compounds investigated are approved for human use. We explored the therapeutic potential of flumazenil (FLUM), a GABA A R antagonist working at the benzodiazepine binding site that has FDA approval. Long-term memory was assessed by the Novel Object Recognition (NOR) testing in Ts65Dn mice after acute or short-term chronic treatment with FLUM. Short-term, low, chronic dose regimens of FLUM elicit long-lasting (>1week) normalization of cognitive function in both young and aged mice. FLUM at low dosages produces long lasting cognitive improvements and has the potential of fulfilling an unmet therapeutic need in DS. Copyright © 2017. Published by Elsevier Inc.

  1. A joint stochastic-deterministic approach for long-term and short-term modelling of monthly flow rates

    Science.gov (United States)

    Stojković, Milan; Kostić, Srđan; Plavšić, Jasna; Prohaska, Stevan

    2017-01-01

    The authors present a detailed procedure for modelling of mean monthly flow time-series using records of the Great Morava River (Serbia). The proposed procedure overcomes a major challenge of other available methods by disaggregating the time series in order to capture the main properties of the hydrologic process in both long-run and short-run. The main assumption of the conducted research is that a time series of monthly flow rates represents a stochastic process comprised of deterministic, stochastic and random components, the former of which can be further decomposed into a composite trend and two periodic components (short-term or seasonal periodicity and long-term or multi-annual periodicity). In the present paper, the deterministic component of a monthly flow time-series is assessed by spectral analysis, whereas its stochastic component is modelled using cross-correlation transfer functions, artificial neural networks and polynomial regression. The results suggest that the deterministic component can be expressed solely as a function of time, whereas the stochastic component changes as a nonlinear function of climatic factors (rainfall and temperature). For the calibration period, the results of the analysis infers a lower value of Kling-Gupta Efficiency in the case of transfer functions (0.736), whereas artificial neural networks and polynomial regression suggest a significantly better match between the observed and simulated values, 0.841 and 0.891, respectively. It seems that transfer functions fail to capture high monthly flow rates, whereas the model based on polynomial regression reproduces high monthly flows much better because it is able to successfully capture a highly nonlinear relationship between the inputs and the output. The proposed methodology that uses a combination of artificial neural networks, spectral analysis and polynomial regression for deterministic and stochastic components can be applied to forecast monthly or seasonal flow rates.

  2. 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.

  3. Remediation of language processing in aphasia: Improving activation and maintenance of linguistic representations in (verbal) short-term memory.

    Science.gov (United States)

    Kalinyak-Fliszar, Michelene; Kohen, Francine; Martin, Nadine

    2011-01-01

    BACKGROUND: Verbal short-term memory (STM) impairments are invariably present in aphasia. Word processing involves a minimal form of verbal STM, i.e., the time course over which semantic and phonological representations are activated and maintained until they are comprehended, produced, or repeated. Thus it is reasonable that impairments of word processing and verbal STM may co-occur. The co-occurrence of language and STM impairments in aphasia has motivated an active area of research that has revealed much about the relationship of these two systems and the effect of their impairment on language function and verbal learning (Freedman & Martin, 2001; Martin & Saffran, 1999; Trojano & Grossi, 1995). In keeping with this view a number of researchers have developed treatment protocols to improve verbal STM in order to improve language function (e.g., Koenig-Bruhin & Studer-Eichenberger, 2007). This account of aphasia predicts that treatment of a fundamental ability, such as STM, which supports language function, should lead to improvements that generalise to content and tasks beyond those implemented in treatment. AIMS: We investigated the efficacy of a treatment for language impairment that targets two language support processes: verbal short-term memory (STM) and executive processing, in the context of a language task (repetition). We hypothesised that treatment of these abilities would improve repetition abilities and performance on other language tasks that require STM. METHOD: A single-participant, multiple-baseline, multiple-probe design across behaviours was used with a participant with conduction aphasia. The treatment involved repetition of words and nonwords under three "interval" conditions, which varied the time between hearing and repeating the stimulus. Measures of treatment effects included acquisition, maintenance, and follow-up data, effect sizes, and pre- and post-treatment performance on a test battery that varies the STM and executive function

  4. An one-parametric model of the Earth's magnetosphere and short-term prediction of the Kp index

    Science.gov (United States)

    Romaschenko, Yuri A.; Starodubtsev, Sergey A.; Sharin, Egor P.

    2017-11-01

    In this paper a simple one-parameter mathematical model of the Earth's magnetosphere is proposed and implemented. The main idea is to introduce a parameter a, which is a distance from the center of the Earth to a subsolar point of the magnetosphere. The parameter a is expressed through a speed of solar wind plasma, density and magnitude of an interplanetary magnetic field as well as magnitude of magnetic moment of the Earth's dipole. It is shown that a is expressed in terms of a planetary index of magnetic activity. The model can be used for a short-term forecast of magnetic activity in near-earth space.

  5. Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape

    International Nuclear Information System (INIS)

    Serinaldi, Francesco

    2011-01-01

    In the context of the liberalized and deregulated electricity markets, price forecasting has become increasingly important for energy company's plans and market strategies. Within the class of the time series models that are used to perform price forecasting, the subclasses of methods based on stochastic time series and causal models commonly provide point forecasts, whereas the corresponding uncertainty is quantified by approximate or simulation-based confidence intervals. Aiming to improve the uncertainty assessment, this study introduces the Generalized Additive Models for Location, Scale and Shape (GAMLSS) to model the dynamically varying distribution of prices. The GAMLSS allow fitting a variety of distributions whose parameters change according to covariates via a number of linear and nonlinear relationships. In this way, price periodicities, trends and abrupt changes characterizing both the position parameter (linked to the expected value of prices), and the scale and shape parameters (related to price volatility, skewness, and kurtosis) can be explicitly incorporated in the model setup. Relying on the past behavior of the prices and exogenous variables, the GAMLSS enable the short-term (one-day ahead) forecast of the entire distribution of prices. The approach was tested on two datasets from the widely studied California Power Exchange (CalPX) market, and the less mature Italian Power Exchange (IPEX). CalPX data allow comparing the GAMLSS forecasting performance with published results obtained by different models. The study points out that the GAMLSS framework can be a flexible alternative to several linear and nonlinear stochastic models. - Research Highlights: ► Generalized Additive Models for Location, Scale and Shape (GAMLSS) are used to model electricity prices' time series. ► GAMLSS provide the entire dynamicaly varying distribution function of prices resorting to a suitable set of covariates that drive the instantaneous values of the parameters

  6. The role of short-term memory and visuo-spatial skills in numerical magnitude processing: Evidence from Turner syndrome.

    Directory of Open Access Journals (Sweden)

    Lucie Attout

    Full Text Available Most studies on magnitude representation have focused on the visual modality with no possibility of disentangling the influence of visuo-spatial skills and short-term memory (STM abilities on quantification processes. This study examines this issue in patients with Turner syndrome (TS, a genetic condition characterized by a specific cognitive profile frequently associating poor mathematical achievement, low spatial skills and reduced STM abilities. In order to identify the influence of visuo-spatial and STM processing on numerical magnitude abilities, twenty female participants with TS and twenty control female participants matched for verbal IQ and education level were administered a series of magnitude comparison tasks. The tasks differed on the nature of the magnitude to be processed (continuous, discrete and symbolic magnitude, on visuo-spatial processing requirement (no/high and on STM demands (low in simultaneous presentation vs. high in sequential presentation. Our results showed a lower acuity when participants with TS compared the numerical magnitudes of stimuli presented sequentially (low visuo-spatial processing and high STM load: Dot sequence and Sound sequence while no difference was observed in the numerical comparison of sets presented simultaneously. In addition, the group difference in sequential tasks disappeared when controlling for STM abilities. Finally, both groups demonstrated similar performance when comparing continuous or symbolic magnitude stimuli and they exhibited comparable subitizing abilities. These results highlight the importance of STM abilities in extracting numerosity through a sequential presentation and underline the importance of considering the impact of format presentation on magnitude judgments.

  7. Short-term to seasonal variability in factors driving primary productivity in a shallow estuary: Implications for modeling production

    Science.gov (United States)

    Canion, Andy; MacIntyre, Hugh L.; Phipps, Scott

    2013-10-01

    The inputs of primary productivity models may be highly variable on short timescales (hourly to daily) in turbid estuaries, but modeling of productivity in these environments is often implemented with data collected over longer timescales. Daily, seasonal, and spatial variability in primary productivity model parameters: chlorophyll a concentration (Chla), the downwelling light attenuation coefficient (kd), and photosynthesis-irradiance response parameters (Pmchl, αChl) were characterized in Weeks Bay, a nitrogen-impacted shallow estuary in the northern Gulf of Mexico. Variability in primary productivity model parameters in response to environmental forcing, nutrients, and microalgal taxonomic marker pigments were analysed in monthly and short-term datasets. Microalgal biomass (as Chla) was strongly related to total phosphorus concentration on seasonal scales. Hourly data support wind-driven resuspension as a major source of short-term variability in Chla and light attenuation (kd). The empirical relationship between areal primary productivity and a combined variable of biomass and light attenuation showed that variability in the photosynthesis-irradiance response contributed little to the overall variability in primary productivity, and Chla alone could account for 53-86% of the variability in primary productivity. Efforts to model productivity in similar shallow systems with highly variable microalgal biomass may benefit the most by investing resources in improving spatial and temporal resolution of chlorophyll a measurements before increasing the complexity of models used in productivity modeling.

  8. Assessment of Granger causality by nonlinear model identification: application to short-term cardiovascular variability.

    Science.gov (United States)

    Faes, Luca; Nollo, Giandomenico; Chon, Ki H

    2008-03-01

    A method for assessing Granger causal relationships in bivariate time series, based on nonlinear autoregressive (NAR) and nonlinear autoregressive exogenous (NARX) models is presented. The method evaluates bilateral interactions between two time series by quantifying the predictability improvement (PI) of the output time series when the dynamics associated with the input time series are included, i.e., moving from NAR to NARX prediction. The NARX model identification was performed by the optimal parameter search (OPS) algorithm, and its results were compared to the least-squares method to determine the most appropriate method to be used for experimental data. The statistical significance of the PI was assessed using a surrogate data technique. The proposed method was tested with simulation examples involving short realizations of linear stochastic processes and nonlinear deterministic signals in which either unidirectional or bidirectional coupling and varying strengths of interactions were imposed. It was found that the OPS-based NARX model was accurate and sensitive in detecting imposed Granger causality conditions. In addition, the OPS-based NARX model was more accurate than the least squares method. Application to the systolic blood pressure and heart rate variability signals demonstrated the feasibility of the method. In particular, we found a bilateral causal relationship between the two signals as evidenced by the significant reduction in the PI values with the NARX model prediction compared to the NAR model prediction, which was also confirmed by the surrogate data analysis. Furthermore, we found significant reduction in the complexity of the dynamics of the two causal pathways of the two signals as the body position was changed from the supine to upright. The proposed is a general method, thus, it can be applied to a wide variety of physiological signals to better understand causality and coupling that may be different between normal and diseased

  9. Functional diversity and functional traits of periphytic algae during a short-term successional process in a Neotropical floodplain lake.

    Science.gov (United States)

    Dunck, B; Rodrigues, L; Bicudo, D C

    2015-08-01

    Due to the lack of knowledge in periphytic algae functional diversity patterns during successional processes in floodplains, the present study aimed to analyze the dynamics of the functional traits and functional diversity of periphytic species during a short-term successional process in a floodplain lake. The functional traits analyzed were size class, growth form, strength of attachment to the substratum, and functional strategies. We evaluated the dynamics of these traits, considering richness, density and biovolume during an 18-day colonization in two hydrological periods. The functional diversity was assessed using the mean pairwise distance index (MPD). Dominant functional traits during the colonization changed in association with the flood pulse. Under the pulse effect, higher development of C-S strategist, loosely attached, filamentous and nanoperiphytic species occurred. The highest values of functional diversity were associated with the algal biomass peak during the colonization and the high water hydrological period, possibly indicating greater efficiency in the ecosystem functioning. These findings show the importance of the functional traits approach in periphyton studies and that the selection of functional traits must be performed taking into account traits that represent the species niche.

  10. Functional diversity and functional traits of periphytic algae during a short-term successional process in a Neotropical floodplain lake

    Directory of Open Access Journals (Sweden)

    B Dunck

    Full Text Available AbstractDue to the lack of knowledge in periphytic algae functional diversity patterns during successional processes in floodplains, the present study aimed to analyze the dynamics of the functional traits and functional diversity of periphytic species during a short-term successional process in a floodplain lake. The functional traits analyzed were size class, growth form, strength of attachment to the substratum, and functional strategies. We evaluated the dynamics of these traits, considering richness, density and biovolume during an 18-day colonization in two hydrological periods. The functional diversity was assessed using the mean pairwise distance index (MPD. Dominant functional traits during the colonization changed in association with the flood pulse. Under the pulse effect, higher development of C-S strategist, loosely attached, filamentous and nanoperiphytic species occurred. The highest values of functional diversity were associated with the algal biomass peak during the colonization and the high water hydrological period, possibly indicating greater efficiency in the ecosystem functioning. These findings show the importance of the functional traits approach in periphyton studies and that the selection of functional traits must be performed taking into account traits that represent the species niche.

  11. 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.

  12. Modeling of short-term mechanism of arterial pressure control in the cardiovascular system: object-oriented and acausal approach.

    Science.gov (United States)

    Kulhánek, Tomáš; Kofránek, Jiří; Mateják, Marek

    2014-11-01

    This letter introduces an alternative approach to modeling the cardiovascular system with a short-term control mechanism published in Computers in Biology and Medicine, Vol. 47 (2014), pp. 104-112. We recommend using abstract components on a distinct physical level, separating the model into hydraulic components, subsystems of the cardiovascular system and individual subsystems of the control mechanism and scenario. We recommend utilizing an acausal modeling feature of Modelica language, which allows model variables to be expressed declaratively. Furthermore, the Modelica tool identifies which are the dependent and independent variables upon compilation. An example of our approach is introduced on several elementary components representing the hydraulic resistance to fluid flow and the elastic response of the vessel, among others. The introduced model implementation can be more reusable and understandable for the general scientific community. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. A new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting

    International Nuclear Information System (INIS)

    Wang, Bo; Tai, Neng-ling; Zhai, Hai-qing; Ye, Jian; Zhu, Jia-dong; Qi, Liang-bo

    2008-01-01

    In this paper, a new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting is proposed. Auto-regressive (AR) and moving average (MA) with exogenous variables (ARMAX) has been widely applied in the load forecasting area. Because of the nonlinear characteristics of the power system loads, the forecasting function has many local optimal points. The traditional method based on gradient searching may be trapped in local optimal points and lead to high error. While, the hybrid method based on evolutionary algorithm and particle swarm optimization can solve this problem more efficiently than the traditional ways. It takes advantage of evolutionary strategy to speed up the convergence of particle swarm optimization (PSO), and applies the crossover operation of genetic algorithm to enhance the global search ability. The new ARMAX model for short-term load forecasting has been tested based on the load data of Eastern China location market, and the results indicate that the proposed approach has achieved good accuracy. (author)

  14. On the Influence of Weather Forecast Errors in Short-Term Load Forecasting Models

    OpenAIRE

    Fay, D.; Ringwood, John; Condon, M.

    2004-01-01

    Weather information is an important factor in load forecasting models. This weather information usually takes the form of actual weather readings. However, online operation of load forecasting models requires the use of weather forecasts, with associated weather forecast errors. A technique is proposed to model weather forecast errors to reflect current accuracy. A load forecasting model is then proposed which combines the forecasts of several load forecasting models. This approach allows the...

  15. Facilitation or disengagement? Attention bias in facial affect processing after short-term violent video game exposure.

    Directory of Open Access Journals (Sweden)

    Yanling Liu

    Full Text Available Previous research has been inconsistent on whether violent video games exert positive and/or negative effects on cognition. In particular, attentional bias in facial affect processing after violent video game exposure continues to be controversial. The aim of the present study was to investigate attentional bias in facial recognition after short term exposure to violent video games and to characterize the neural correlates of this effect. In order to accomplish this, participants were exposed to either neutral or violent video games for 25 min and then event-related potentials (ERPs were recorded during two emotional search tasks. The first search task assessed attentional facilitation, in which participants were required to identify an emotional face from a crowd of neutral faces. In contrast, the second task measured disengagement, in which participants were required to identify a neutral face from a crowd of emotional faces. Our results found a significant presence of the ERP component, N2pc, during the facilitation task; however, no differences were observed between the two video game groups. This finding does not support a link between attentional facilitation and violent video game exposure. Comparatively, during the disengagement task, N2pc responses were not observed when participants viewed happy faces following violent video game exposure; however, a weak N2pc response was observed after neutral video game exposure. These results provided only inconsistent support for the disengagement hypothesis, suggesting that participants found it difficult to separate a neutral face from a crowd of emotional faces.

  16. Facilitation or disengagement? Attention bias in facial affect processing after short-term violent video game exposure.

    Science.gov (United States)

    Liu, Yanling; Lan, Haiying; Teng, Zhaojun; Guo, Cheng; Yao, Dezhong

    2017-01-01

    Previous research has been inconsistent on whether violent video games exert positive and/or negative effects on cognition. In particular, attentional bias in facial affect processing after violent video game exposure continues to be controversial. The aim of the present study was to investigate attentional bias in facial recognition after short term exposure to violent video games and to characterize the neural correlates of this effect. In order to accomplish this, participants were exposed to either neutral or violent video games for 25 min and then event-related potentials (ERPs) were recorded during two emotional search tasks. The first search task assessed attentional facilitation, in which participants were required to identify an emotional face from a crowd of neutral faces. In contrast, the second task measured disengagement, in which participants were required to identify a neutral face from a crowd of emotional faces. Our results found a significant presence of the ERP component, N2pc, during the facilitation task; however, no differences were observed between the two video game groups. This finding does not support a link between attentional facilitation and violent video game exposure. Comparatively, during the disengagement task, N2pc responses were not observed when participants viewed happy faces following violent video game exposure; however, a weak N2pc response was observed after neutral video game exposure. These results provided only inconsistent support for the disengagement hypothesis, suggesting that participants found it difficult to separate a neutral face from a crowd of emotional faces.

  17. Why chunking should be considered as an explanation for developmental change before short-term memory capacity and processing speed

    Directory of Open Access Journals (Sweden)

    Gary eJones

    2012-06-01

    Full Text Available The chunking hypothesis suggests that during the repeated exposure of stimulus material, information is organized into increasingly larger chunks. Many researchers have not considered the full power of the chunking hypothesis as both a learning mechanism and as an explanation of human behavior. Indeed, in developmental psychology there is relatively little mention of chunking and yet it can be the underlying cause of some of the mechanisms of development that have been proposed. This paper illustrates the chunking hypothesis in the domain of nonword repetition, a task that is a strong predictor of a child’s language learning. A computer simulation of nonword repetition that instantiates the chunking mechanism shows that: (1 chunking causes task behavior to improve over time, consistent with children’s performance; and (2 chunking causes perceived changes in areas such as short-term memory capacity and processing speed that are often cited as mechanisms of child development. Researchers should be cautious when considering explanations of developmental data, since chunking may be able to explain differences in performance without the need for additional mechanisms of development.

  18. 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.

  19. 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....

  20. Comparison Of Short Term Rainfall Forecasts For Model Based Flow Prediction In Urban Drainage Systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; 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....

  1. Linear and non-linear autoregressive models for short-term wind speed forecasting

    International Nuclear Information System (INIS)

    Lydia, M.; Suresh Kumar, S.; Immanuel Selvakumar, A.; Edwin Prem Kumar, G.

    2016-01-01

    Highlights: • Models for wind speed prediction at 10-min intervals up to 1 h built on time-series wind speed data. • Four different multivariate models for wind speed built based on exogenous variables. • Non-linear models built using three data mining algorithms outperform the linear models. • Autoregressive models based on wind direction perform better than other models. - Abstract: Wind speed forecasting aids in estimating the energy produced from wind farms. The soaring energy demands of the world and minimal availability of conventional energy sources have significantly increased the role of non-conventional sources of energy like solar, wind, etc. Development of models for wind speed forecasting with higher reliability and greater accuracy is the need of the hour. In this paper, models for predicting wind speed at 10-min intervals up to 1 h have been built based on linear and non-linear autoregressive moving average models with and without external variables. The autoregressive moving average models based on wind direction and annual trends have been built using data obtained from Sotavento Galicia Plc. and autoregressive moving average models based on wind direction, wind shear and temperature have been built on data obtained from Centre for Wind Energy Technology, Chennai, India. While the parameters of the linear models are obtained using the Gauss–Newton algorithm, the non-linear autoregressive models are developed using three different data mining algorithms. The accuracy of the models has been measured using three performance metrics namely, the Mean Absolute Error, Root Mean Squared Error and Mean Absolute Percentage Error.

  2. Individualized Short-Term Core Temperature Prediction in Humans Using Biomathematical Models

    Science.gov (United States)

    2008-05-05

    first-principles models [16]–[18] be- cause it has been traditionally used by the Army to analyze the human response to heat stress and was readily...it provides sufficient warning time to prevent thermal stress injuries while allowing the models to produce data-driven predictions of acceptable...results presented in this study relate to the potential portability of data-driven models across physically fit, young athletes and soldiers performing

  3. Human models of migraine - short-term pain for long-term gain

    DEFF Research Database (Denmark)

    Ashina, Messoud; Hansen, Jakob Møller; Á Dunga, Bára Oladóttir

    2017-01-01

    mechanisms by experimentally inducing migraine attacks. In this Review, we summarize the existing experimental models of migraine in humans, including those that exploit nitric oxide, histamine, neuropeptide and prostaglandin signalling. We describe the development and use of these models in the discovery...... of molecular pathways that are responsible for initiation of migraine attacks. Combining experimental human models with advanced imaging techniques might help to identify biomarkers of migraine, and in the ongoing search for new and better migraine treatments, human models will have a key role in the discovery...

  4. 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...... prediction (NWP) model and produce quantitative estimations of nowcast uncertainty. In real time control of urban drainage systems, nowcasting is used to increase the margin for decision-making. The spatial extent of urban drainag e catchments is very small in a meteorological context. This is a problem...... by the relative standard deviation. A significant result of this Ph.D. study is major improvements in predictability of DMI HIRLAM NWP model by assimilation of REM data. A new nudging assimilation method developed at DMI was used to assimilate the REM data. The assimilation technique enhances convection in case...

  5. Noise model based ν-support vector regression with its application to short-term wind speed forecasting.

    Science.gov (United States)

    Hu, Qinghua; Zhang, Shiguang; Xie, Zongxia; Mi, Jusheng; Wan, Jie

    2014-09-01

    Support vector regression (SVR) techniques are aimed at discovering a linear or nonlinear structure hidden in sample data. Most existing regression techniques take the assumption that the error distribution is Gaussian. However, it was observed that the noise in some real-world applications, such as wind power forecasting and direction of the arrival estimation problem, does not satisfy Gaussian distribution, but a beta distribution, Laplacian distribution, or other models. In these cases the current regression techniques are not optimal. According to the Bayesian approach, we derive a general loss function and develop a technique of the uniform model of ν-support vector regression for the general noise model (N-SVR). The Augmented Lagrange Multiplier method is introduced to solve N-SVR. Numerical experiments on artificial data sets, UCI data and short-term wind speed prediction are conducted. The results show the effectiveness of the proposed technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Mitigation of short-term disturbance negative impacts in the agent-based model of a production companies network

    Science.gov (United States)

    Shevchuk, G. K.; Berg, D. B.; Zvereva, O. M.; Medvedeva, M. A.

    2017-11-01

    This article is devoted to the study of a supply chain disturbance impact on manufacturing volumes in a production system network. Each network agent's product can be used as a resource by other system agents (manufacturers). A supply chain disturbance can lead to operating cease of the entire network. Authors suggest using of short-term partial resources reservation to mitigate negative consequences of such disturbances. An agent-based model with a reservation algorithm compatible with strategies for resource procurement in terms of financial constraints was engineered. This model works in accordance with the static input-output Leontief 's model. The results can be used for choosing the ways of system's stability improving, and protecting it from various disturbances and imbalance.

  7. 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 series models (i.e., autoregressive (AR), moving average (MA), autoregressive-moving average (ARMA), and ARMA with exogenous variable (ARMAX)) introduced by Box and Jenkins (1970), feed-forward back-propagation neural network (FFBP-NN), and hybrid model...

  8. Human models of migraine - short-term pain for long-term gain.

    Science.gov (United States)

    Ashina, Messoud; Hansen, Jakob Møller; Á Dunga, Bára Oladóttir; Olesen, Jes

    2017-12-01

    Migraine is a complex disorder characterized by recurrent episodes of headache, and is one of the most prevalent and disabling neurological disorders. A key feature of migraine is that various factors can trigger an attack, and this phenomenon provides a unique opportunity to investigate disease mechanisms by experimentally inducing migraine attacks. In this Review, we summarize the existing experimental models of migraine in humans, including those that exploit nitric oxide, histamine, neuropeptide and prostaglandin signalling. We describe the development and use of these models in the discovery of molecular pathways that are responsible for initiation of migraine attacks. Combining experimental human models with advanced imaging techniques might help to identify biomarkers of migraine, and in the ongoing search for new and better migraine treatments, human models will have a key role in the discovery of future targets for more-specific and more-effective mechanism-based antimigraine drugs.

  9. Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

    International Nuclear Information System (INIS)

    Nguyen, Hang T.; Nabney, Ian T.

    2010-01-01

    This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their NMSEs are 0.02314 and 0.15384 respectively. (author)

  10. Short term load forecasting technique based on the seasonal exponential adjustment method and the regression model

    International Nuclear Information System (INIS)

    Wu, Jie; Wang, Jianzhou; Lu, Haiyan; Dong, Yao; Lu, Xiaoxiao

    2013-01-01

    Highlights: ► The seasonal and trend items of the data series are forecasted separately. ► Seasonal item in the data series is verified by the Kendall τ correlation testing. ► Different regression models are applied to the trend item forecasting. ► We examine the superiority of the combined models by the quartile value comparison. ► Paired-sample T test is utilized to confirm the superiority of the combined models. - Abstract: For an energy-limited economy system, it is crucial to forecast load demand accurately. This paper devotes to 1-week-ahead daily load forecasting approach in which load demand series are predicted by employing the information of days before being similar to that of the forecast day. As well as in many nonlinear systems, seasonal item and trend item are coexisting in load demand datasets. In this paper, the existing of the seasonal item in the load demand data series is firstly verified according to the Kendall τ correlation testing method. Then in the belief of the separate forecasting to the seasonal item and the trend item would improve the forecasting accuracy, hybrid models by combining seasonal exponential adjustment method (SEAM) with the regression methods are proposed in this paper, where SEAM and the regression models are employed to seasonal and trend items forecasting respectively. Comparisons of the quartile values as well as the mean absolute percentage error values demonstrate this forecasting technique can significantly improve the accuracy though models applied to the trend item forecasting are eleven different ones. This superior performance of this separate forecasting technique is further confirmed by the paired-sample T tests

  11. A spatiotemporal geostatistical hurdle model approach for short-term deforestation prediction

    NARCIS (Netherlands)

    Ribeiro Sales, Marcio; Bruin, De Sytze; Herold, Martin; Kyriakidis, Phaedon; Souza, Carlos

    2017-01-01

    This paper introduces and tests a geostatistical spatiotemporal hurdle approach for predicting the spatial distribution of future deforestation (one to three years ahead in time). The method accounts for neighborhood effects by modeling the auto-correlation of occurrence and intensity of

  12. Short term evaluation of an anatomically shaped polycarbonate urethane total meniscus replacement in a goat model

    NARCIS (Netherlands)

    Vrancken, A.C.T.; Madej, W.; Hannink, G.; Verdonschot, Nicolaas Jacobus Joseph; van Tienen, T.G.; Buma, P.

    2015-01-01

    Purpose: Since the treatment options for symptomatic total meniscectomy patients are still limited, an anatomically shaped, polycarbonate urethane (PCU), total meniscus replacement was developed. This study evaluates the in vivo performance of the implant in a goat model, with a specific focus on

  13. 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.

  14. Teen Tobacco Court: A Determination of the Short-Term Outcomes of Judicial Processes with Teens Engaging in Tobacco Possession.

    Science.gov (United States)

    Langer, Lilly M.; Warheit, George J.

    2000-01-01

    Investigated the impact of a tobacco citation and subsequent court appearance on teens who possessed tobacco, examining offenders' attitudes and behaviors following citation and court appearance. Surveys and interviews indicated that being ticketed and appearing in teen tobacco court had significant, positive, short-term impacts on large numbers…

  15. Sentence Processing as a Function of Syntax, Short Term Memory Capacity, the Meaningfulness of the Stimulus and Age

    Science.gov (United States)

    Gamlin, Peter J.

    1971-01-01

    Examines the effects of short term memory (STM) capacity, meaningfulness of stimuli, and age upon listeners' structuring of sentences. Results show that the interaction between STM capacity and meaningfulness (1) approached significance when data were collapsed over both age levels, and (2) was significant for one age level. Tables and references.…

  16. Short-Term Memory Performance in 7- and 8-Year-Old Children: The Relationship between Phonological and Pitch Processing

    Science.gov (United States)

    Flagge, Ashley Gaal; Estis, Julie M.; Moore, Robert E.

    2016-01-01

    Purpose: The relationship between short-term memory for phonology and pitch was explored by examining accuracy scores for typically developing children for 5 experimental tasks: immediate nonword repetition (NWR), nonword repetition with an 8-s silent interference (NWRS), pitch discrimination (PD), pitch discrimination with an 8-s silent…

  17. 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

  18. Short-term impacts of enhanced Greenland freshwater fluxes in an eddy-permitting ocean model

    Directory of Open Access Journals (Sweden)

    R. Marsh

    2010-07-01

    Full Text Available In a sensitivity experiment, an eddy-permitting ocean general circulation model is forced with realistic freshwater fluxes from the Greenland Ice Sheet, averaged for the period 1991–2000. The fluxes are obtained with a mass balance model for the ice sheet, forced with the ERA-40 reanalysis dataset. The freshwater flux is distributed around Greenland as an additional term in prescribed runoff, representing seasonal melting of the ice sheet and a fixed year-round iceberg calving flux, for 8.5 model years. By adding Greenland freshwater fluxes with realistic geographical distribution and seasonality, the experiment is designed to investigate the oceanic response to a sudden and spatially/temporally uniform amplification of ice sheet melting and discharge, rather than localized or gradual changes in freshwater flux. The impacts on regional hydrography and circulation are investigated by comparing the sensitivity experiment to a control experiment, without additional fluxes. By the end of the sensitivity experiment, the majority of additional fresh water has accumulated in Baffin Bay, and only a small fraction has reached the interior of the Labrador Sea, where winter mixed layer depth is sensitive to small changes in salinity. As a consequence, the impact on large-scale circulation is very slight. An indirect impact of strong freshening off the west coast of Greenland is a small anti-cyclonic component to the circulation around Greenland, which opposes the wind-driven cyclonic circulation and reduces net southward flow through the Canadian Archipelago by ~10%. Implications for the post-2000 acceleration of Greenland mass loss are discussed.

  19. Dimensionality reduction of a pathological voice quality assessment system based on Gaussian mixture models and short-term cepstral parameters.

    Science.gov (United States)

    Godino-Llorente, Juan Ignacio; Gómez-Vilda, Pedro; Blanco-Velasco, Manuel

    2006-10-01

    Voice diseases have been increasing dramatically in recent times due mainly to unhealthy social habits and voice abuse. These diseases must be diagnosed and treated at an early stage, especially in the case of larynx cancer. It is widely recognized that vocal and voice diseases do not necessarily cause changes in voice quality as perceived by a listener. Acoustic analysis could be a useful tool to diagnose this type of disease. Preliminary research has shown that the detection of voice alterations can be carried out by means of Gaussian mixture models and short-term mel cepstral parameters complemented by frame energy together with first and second derivatives. This paper, using the F-Ratio and Fisher's discriminant ratio, will demonstrate that the detection of voice impairments can be performed using both mel cesptral vectors and their first derivative, ignoring the second derivative.

  20. Short-term spheroid culture of primary colorectal cancer cells as an in vitro model for personalizing cancer medicine

    DEFF Research Database (Denmark)

    Jeppesen, Maria; Hagel, Grith; Glenthoj, Anders

    2017-01-01

    Chemotherapy treatment of cancer remains a challenge due to the molecular and functional heterogeneity displayed by tumours originating from the same cell type. The pronounced heterogeneity makes it difficult for oncologists to devise an effective therapeutic strategy for the patient. One approach...... for increasing treatment efficacy is to test the chemosensitivity of cancer cells obtained from the patient's tumour. 3D culture represents a promising method for modelling patient tumours in vitro. The aim of this study was therefore to evaluate how closely short-term spheroid cultures of primary colorectal...... cancer cells resemble the original tumour. Colorectal cancer cells were isolated from human tumour tissue and cultured as spheroids. Spheroid cultures were established with a high success rate and remained viable for at least 10 days. The spheroids exhibited significant growth over a period of 7 days...

  1. Long-term earthquake forecasts based on the epidemic-type aftershock sequence (ETAS model for short-term clustering

    Directory of Open Access Journals (Sweden)

    Jiancang Zhuang

    2012-07-01

    Full Text Available Based on the ETAS (epidemic-type aftershock sequence model, which is used for describing the features of short-term clustering of earthquake occurrence, this paper presents some theories and techniques related to evaluating the probability distribution of the maximum magnitude in a given space-time window, where the Gutenberg-Richter law for earthquake magnitude distribution cannot be directly applied. It is seen that the distribution of the maximum magnitude in a given space-time volume is determined in the longterm by the background seismicity rate and the magnitude distribution of the largest events in each earthquake cluster. The techniques introduced were applied to the seismicity in the Japan region in the period from 1926 to 2009. It was found that the regions most likely to have big earthquakes are along the Tohoku (northeastern Japan Arc and the Kuril Arc, both with much higher probabilities than the offshore Nankai and Tokai regions.

  2. Short Term Evaluation of an Anatomically Shaped Polycarbonate Urethane Total Meniscus Replacement in a Goat Model.

    Directory of Open Access Journals (Sweden)

    A C T Vrancken

    Full Text Available Since the treatment options for symptomatic total meniscectomy patients are still limited, an anatomically shaped, polycarbonate urethane (PCU, total meniscus replacement was developed. This study evaluates the in vivo performance of the implant in a goat model, with a specific focus on the implant location in the joint, geometrical integrity of the implant and the effect of the implant on synovial membrane and articular cartilage histopathological condition.The right medial meniscus of seven Saanen goats was replaced by the implant. Sham surgery (transection of the MCL, arthrotomy and MCL suturing was performed in six animals. The contralateral knee joints of both groups served as control groups. After three months follow-up the following aspects of implant performance were evaluated: implant position, implant deformation and the histopathological condition of the synovium and cartilage.Implant geometry was well maintained during the three month implantation period. No signs of PCU wear were found and the implant did not induce an inflammatory response in the knee joint. In all animals, implant fixation was compromised due to suture breakage, wear or elongation, likely causing the increase in extrusion observed in the implant group. Both the femoral cartilage and tibial cartilage in direct contact with the implant showed increased damage compared to the sham and sham-control groups.This study demonstrates that the novel, anatomically shaped PCU total meniscal replacement is biocompatible and resistant to three months of physiological loading. Failure of the fixation sutures may have increased implant mobility, which probably induced implant extrusion and potentially stimulated cartilage degeneration. Evidently, redesigning the fixation method is necessary. Future animal studies should evaluate the improved fixation method and compare implant performance to current treatment standards, such as allografts.

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

    Science.gov (United States)

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

    2012-01-01

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

  4. 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...

  5. k-Nearest Neighbor Neural Network Models for Very Short-Term Global Solar Irradiance Forecasting Based on Meteorological Data

    Directory of Open Access Journals (Sweden)

    Chao-Rong Chen

    2017-02-01

    Full Text Available This paper proposes a novel methodology for very short term forecasting of hourly global solar irradiance (GSI. The proposed methodology is based on meteorology data, especially for optimizing the operation of power generating electricity from photovoltaic (PV energy. This methodology is a combination of k-nearest neighbor (k-NN algorithm modelling and artificial neural network (ANN model. The k-NN-ANN method is designed to forecast GSI for 60 min ahead based on meteorology data for the target PV station which position is surrounded by eight other adjacent PV stations. The novelty of this method is taking into account the meteorology data. A set of GSI measurement samples was available from the PV station in Taiwan which is used as test data. The first method implements k-NN as a preprocessing technique prior to ANN method. The error statistical indicators of k-NN-ANN model the mean absolute bias error (MABE is 42 W/m2 and the root-mean-square error (RMSE is 242 W/m2. The models forecasts are then compared to measured data and simulation results indicate that the k-NN-ANN-based model presented in this research can calculate hourly GSI with satisfactory accuracy.

  6. GLP-1 and energy balance: an integrated model of short-term and long-term control

    Science.gov (United States)

    Barrera, Jason G.; Sandoval, Darleen A.; D’Alessio, David A.; Seeley, Randy J.

    2014-01-01

    Glucagon-like peptide 1 (GLP-1), a peptide secreted from the intestine in response to nutrient ingestion, is perhaps best known for its effect on glucose-stimulated insulin secretion. GLP-1 is also secreted from neurons in the caudal brainstem, and it is well-established that, in rodents, central administration of GLP-1 potently reduces food intake. Over the past decade, GLP-1 has emerged not only as an essential component of the system that regulates blood glucose levels but also as a viable therapeutic target for the treatment of type 2 diabetes mellitus. However, although GLP-1 receptor agonists are known to produce modest but statistically significant weight loss in patients with diabetes mellitus, our knowledge of how endogenous GLP-1 regulates food intake and body weight remains limited. The purpose of this Review is to discuss the evolution of our understanding of how endogenous GLP-1 modulates energy balance. Specifically, we consider contributions of both central and peripheral GLP-1 and propose an integrated model of short-term and long-term control of energy balance. Finally, we discuss this model with respect to current GLP-1-based therapies and suggest ongoing research in order to maximize the effectiveness of GLP-1-based treatment of obesity. PMID:21647189

  7. Modelling and short-term forecasting of daily peak power demand in Victoria using two-dimensional wavelet based SDP models

    International Nuclear Information System (INIS)

    Truong, Nguyen-Vu; Wang, Liuping; Wong, Peter K.C.

    2008-01-01

    Power demand forecasting is of vital importance to the management and planning of power system operations which include generation, transmission, distribution, as well as system's security analysis and economic pricing processes. This paper concerns the modeling and short-term forecast of daily peak power demand in the state of Victoria, Australia. In this study, a two-dimensional wavelet based state dependent parameter (SDP) modelling approach is used to produce a compact mathematical model for this complex nonlinear dynamic system. In this approach, a nonlinear system is expressed by a set of linear regressive input and output terms (state variables) multiplied by the respective state dependent parameters that carry the nonlinearities in the form of 2-D wavelet series expansions. This model is identified based on historical data, descriptively representing the relationship and interaction between various components which affect the peak power demand of a certain day. The identified model has been used to forecast daily peak power demand in the state of Victoria, Australia in the time period from the 9th of August 2007 to the 24th of August 2007. With a MAPE (mean absolute prediction error) of 1.9%, it has clearly implied the effectiveness of the identified model. (author)

  8. Sedimentary process and recent morphological evolution in the Arcahon lagoon, France: a long and short term approaches

    Science.gov (United States)

    Arriagada-Gonzalez, Joselyn; Sottolichio, Aldo

    2017-04-01

    The Arcachon lagoon is a mesotidal embayment in the south Atlantic coast of France. Its total surface is about 174 km2, where 65% is formed of tidal flats. Previous studies have shown a relative stable morphology over a period of 126 years, and a very long infilling trend, with a total accretion rarely exceeding + 0.5m in some areas. This is consistent with the fact that fine sediment input from rivers is very low. However at the tidal short term, erosion of mudflats can reach several centimeters, especially under energetic windy conditions. Additionally, recent high-frequency monitoring showed that tidal flats experience erosion and accretion of several dm at the seasonal scale, following the annual cycle of seagrass Zostera noltei, which develops on the intertidal areas. These patterns support the most recent observations made by end-users of the lagoon, which point out relative infilling of the channels and increase of turbidity in the water. The whole set the observations suggest that a mobile stock of surficial sediment is available in the lagoon, which contributes to the accretion of the flats, but is also transported towards the channels, when erosive conditions prevail. The aim of this presentation is to show the patterns and conditions of mobility of this stock of sediment. In this work, a set of unpublished data of physical forcing, sediment dynamics and bathymetry of the lagoon, are analyzed over a period of 148 years (1864-2012), which an intermediate scale between the long-term and short-term scales, with bathymetric and LIDAR surveys. In addition, we performed a short-term analysis based on the monitoring of altimetric and granulometric variations in the northern area of the lagoon. We show that accretion and erosion rates are significant at the annual scale with clear trends of exchanges between the center of the lagoon and the internal banks. There is a spatial and temporal difference in the long-term sedimentary balance between each period analyzed

  9. The short-term effects of an integrated care model for the frail elderly on health, quality of life, health care use and satisfaction with care

    Directory of Open Access Journals (Sweden)

    Wilhelmina Mijntje Looman

    2014-12-01

    Full Text Available Purpose: This study explores the short-term value of integrated care for the frail elderly by evaluating the effects of the Walcheren Integrated Care Model on health, quality of life, health care use and satisfaction with care after three months. Intervention: Frailty was preventively detected in elderly living at home with the Groningen Frailty Indicator. Geriatric nurse practitioners and secondary care geriatric nursing specialists were assigned as case managers and co-ordinated the care agreed upon in a multidisciplinary meeting. The general practitioner practice functions as a single entry point and supervises the co-ordination of care. The intervention encompasses task reassignment between nurses and doctors and consultations between primary, secondary and tertiary care providers. The entire process was supported by multidisciplinary protocols and web-based patient files. Methods: The design of this study was quasi-experimental. In this study, 205 frail elderly patients of three general practitioner practices that implemented the integrated care model were compared with 212 frail elderly patients of five general practitioner practices that provided usual care. The outcomes were assessed using questionnaires. Baseline measures were compared with a three-month follow-up by chi-square tests, t-tests and regression analysis. Results and conclusion: In the short term, the integrated care model had a significant effect on the attachment aspect of quality of life. The frail elderly patients were better able to obtain the love and friendship they desire. The use of care did not differ despite the preventive element and the need for assessments followed up with case management in the integrated care model. In the short term, there were no significant changes in health. As frailty is a progressive state, it is assumed that three months are too short to influence changes in health with integrated care models. A more longitudinal approach is

  10. Hemispheric specialisation in selective attention and short-term memory: A fine-coarse model of left and right ear disadvantages

    Directory of Open Access Journals (Sweden)

    John E. Marsh

    2013-12-01

    Full Text Available Serial short-term memory is impaired by irrelevant sound, particularly when the sound changes acoustically. This acoustic effect is larger when the sound is presented to the left compared to the right ear (a left-ear disadvantage. Serial memory appears relatively insensitive to distraction from the semantic properties of a background sound. In contrast, short-term free recall of semantic-category exemplars is impaired by the semantic properties of background speech and relatively insensitive to the sound’s acoustic properties. This semantic effect is larger when the sound is presented to the right compared to the left ear (a right-ear disadvantage. In this paper, we outline a speculative neurocognitive fine-coarse model of these hemispheric differences in relation to short-term memory and selective attention, and explicate empirical directions in which this model can be critically evaluated.

  11. Modeling the Effects of Trait Diversity on Short-term Adaptive Capacity and Long-term Productivity of Phytoplankton Communities

    Science.gov (United States)

    Smith, S. L.; Vallina, S. M.; Merico, A.

    2016-02-01

    We examine Biodiversity and Ecosystem Function (BEF) in a model phytoplankton community, using two recently developed mechanisms for sustaining diversity. The Trait Diffusion (TD) formulation represents the maintenance of diversity via endogenous mechanisms, such as inter-generational trait plasticity and rapid evolution. The 'Kill-the-Winner' (KTW) formulation for grazing sustains prey biodiversity via the exogenous mechanism of active prey switching. We implement both TD and KTW in a continuous trait-distribution model using simplified size-scalings to define a gleaner-opportunist trade-off for a phytoplankton community. By simulating semi-continuous culture experiments with periodic external dilutions, we test the dynamic response of the phytoplankton community to different scenarios of pulsed nutrient supply. We quantify the short-term Adaptive Capacity (AC) of the community by the specific growth rate averaged over the first 3 days of perturbations, and the Long-term Productivity (LP) by its average over the entire 120 day period of perturbations. When either the frequency or intensity of pulses is low, both AC and LP tend to decrease with diversity (and vice versa). Trait diversity has more impact on AC, particularly for pulses of high frequency or intensity, for which it tends to increase gradually at first, then steeply, and then to saturate with increasing diversity. For pulses of moderate intensity and frequency, increasing trait diversity from low to moderate levels leads to a trade-off between enhancing AC while slightly decreasing LP. Ultimately, we find that sustaining diversity increases the speed at which the phytoplankton community changes its composition in terms of size and hence nutrient acquisition traits, which may have implications for the transfer of productivity through the foodweb.

  12. 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…

  13. Transcranial direct current stimulation improves short-term memory in an animal model of attention-deficit/hyperactivity disorder.

    Science.gov (United States)

    Leffa, Douglas Teixeira; de Souza, Andressa; Scarabelot, Vanessa Leal; Medeiros, Liciane Fernandes; de Oliveira, Carla; Grevet, Eugenio Horacio; Caumo, Wolnei; de Souza, Diogo Onofre; Rohde, Luis Augusto Paim; Torres, Iraci L S

    2016-02-01

    Attention deficit hyperactivity disorder (ADHD) is characterized by impairing levels of hyperactivity, impulsivity and inattention. However, different meta-analyses have reported disruptions in short and long-term memory in ADHD patients. Previous studies indicate that mnemonic dysfunctions might be the result of deficits in attentional circuits, probably due to ineffective dopaminergic modulation of hippocampal synaptic plasticity. In this study we aimed to evaluate the potential therapeutic effects of a neuromodulatory technique, transcranial direct current stimulation (tDCS), in short-term memory (STM) deficits presented by the spontaneous hypertensive rats (SHR), the most widely used animal model of ADHD. Adult male SHR and Wistar Kyoto rats (WKY) were subjected to a constant electrical current of 0.5 mA intensity applied on the frontal cortex for 20 min/day during 8 days. STM was evaluated with an object recognition test conducted in an open field. Exploration time and locomotion were recorded, and brain regions were dissected to determine dopamine and BDNF levels. SHR spent less time exploring the new object when compared to WKY, and tDCS improved object recognition deficits in SHR without affecting WKY performance. Locomotor activity was higher in SHR and it was not affected by tDCS. After stimulation, dopamine levels were increased in the hippocampus and striatum of both strains, while BDNF levels were increased only in the striatum of WKY. These findings suggest that tDCS on the frontal cortex might be able to improve STM deficits present in SHR, which is potentially related to dopaminergic neurotransmission in the hippocampus and striatum of those animals. Copyright © 2016. Published by Elsevier B.V.

  14. Empirical evidence for musical syntax processing? Computer simulations reveal the contribution of auditory short-term memory.

    Science.gov (United States)

    Bigand, Emmanuel; Delbé, Charles; Poulin-Charronnat, Bénédicte; Leman, Marc; Tillmann, Barbara

    2014-01-01

    During the last decade, it has been argued that (1) music processing involves syntactic representations similar to those observed in language, and (2) that music and language share similar syntactic-like processes and neural resources. This claim is important for understanding the origin of music and language abilities and, furthermore, it has clinical implications. The Western musical system, however, is rooted in psychoacoustic properties of sound, and this is not the case for linguistic syntax. Accordingly, musical syntax processing could be parsimoniously understood as an emergent property of auditory memory rather than a property of abstract processing similar to linguistic processing. To support this view, we simulated numerous empirical studies that investigated the processing of harmonic structures, using a model based on the accumulation of sensory information in auditory memory. The simulations revealed that most of the musical syntax manipulations used with behavioral and neurophysiological methods as well as with developmental and cross-cultural approaches can be accounted for by the auditory memory model. This led us to question whether current research on musical syntax can really be compared with linguistic processing. Our simulation also raises methodological and theoretical challenges to study musical syntax while disentangling the confounded low-level sensory influences. In order to investigate syntactic abilities in music comparable to language, research should preferentially use musical material with structures that circumvent the tonal effect exerted by psychoacoustic properties of sounds.

  15. Empirical evidence for musical syntax processing? Computer simulations reveal the contribution of auditory short-term memory

    Directory of Open Access Journals (Sweden)

    Emmanuel eBigand

    2014-06-01

    Full Text Available During the last decade, it has been argued that 1 music processing involves syntactic representations similar to those observed in language, and 2 that music and language share similar syntactic-like processes and neural resources. This claim is important for understanding the origin of music and language abilities and, furthermore, it has clinical implications. The Western musical system, however, is rooted in psychoacoustic properties of sound, and this is not the case for linguistic syntax. Accordingly, musical syntax processing could be parsimoniously understood as an emergent property of auditory memory rather than a property of abstract processing similar to linguistic processing. To support this view, we simulated numerous empirical studies that investigated the processing of harmonic structures, using a model based on the accumulation of sensory information in auditory memory. The simulations revealed that most of the musical syntax manipulations used with behavioral and neurophysiological methods as well as with developmental and cross-cultural approaches can be accounted for by the auditory memory model. This led us to question whether current research on musical syntax can really be compared with linguistic processing. Our simulation also raises methodological and theoretical challenges to study musical syntax while disentangling the confounded low-level sensory influences. In order to investigate syntactic abilities in music comparable to language, research should preferentially use musical material with structures that circumvent the tonal effect exerted by psychoacoustic properties of sounds.

  16. Modelling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics

    Directory of Open Access Journals (Sweden)

    Bahar eMoezzi

    2014-12-01

    Full Text Available We propose several modifications to an existing computational model of stochastic vesicle release in inner hair cell ribbon synapses, with the aim of producing simulated auditory nerve fibre spiking data that more closely matches empirical data. Specifically, we studied the inter-spike-interval (ISI distribution, and long and short term ISI correlations in spontaneous spiking in post-synaptic auditory nerve fibres. We introduced short term plasticity to the pre-synaptic release probability, in a manner analogous to standard stochastic models of cortical short term synaptic depression. This modification resulted in a similar distribution of vesicle release intervals to that estimated from empirical data. We also introduced a biophysical stochastic model of calcium channel opening and closing, but showed that this model is insufficient for generating a match with empirically observed spike correlations. However, by combining a phenomenological model of channel noise and our short term depression model, we generated short and long term correlations in auditory nerve spontaneous activity that qualitatively match empirical data.

  17. THE PROCESS OF SHORT-TERM AND LONG-TERM PRICE INTEGRATION IN THE BENIN MAIZE MARKET

    NARCIS (Netherlands)

    LUTZ, C; VANTILBURG, A; VANDERKAMP, BJ

    1995-01-01

    This paper reviews the methodology used to study the price integration process in spatially separated spot markets, and applies if to the Benin maize market. An Autoregressive Distributed Lag Model is derived to take into account the sluggishness of price adjustments. Hypothesis testing concerns

  18. Comparison of the Short-Term Forecasting Accuracy on Battery Electric Vehicle between Modified Bass and Lotka-Volterra Model: A Case Study of China

    Directory of Open Access Journals (Sweden)

    Shunxi Li

    2017-01-01

    Full Text Available The potential demand of battery electric vehicle (BEV is the base of the decision-making to the government policy formulation, enterprise manufacture capacity expansion, and charging infrastructure construction. How to predict the future amount of BEV accurately is very important to the development of BEV both in practice and in theory. The present paper tries to compare the short-term accuracy of a proposed modified Bass model and Lotka-Volterra (LV model, by taking China’s BEV development as the case study. Using the statistics data of China’s BEV amount of 21 months from Jan 2015 to Sep 2016, we compare the simulation accuracy based on the value of mean absolute percentage error (MAPE and discuss the forecasting capacity of the two models according to China’s government expectation. According to the MAPE value, the two models have good prediction accuracy, but the Bass model is more accurate than LV model. Bass model has only one dimension and focuses on the diffusion trend, while LV model has two dimensions and mainly describes the relationship and competing process between the two populations. In future research, the forecasting advantages of Bass model and LV model should be combined to get more accurate predicting effect.

  19. Domain-Generality of Timing-Based Serial Order Processes in Short-Term Memory: New Insights from Musical and Verbal Domains.

    Science.gov (United States)

    Gorin, Simon; Kowialiewski, Benjamin; Majerus, Steve

    2016-01-01

    Several models in the verbal domain of short-term memory (STM) consider a dissociation between item and order processing. This view is supported by data demonstrating that different types of time-based interference have a greater effect on memory for the order of to-be-remembered items than on memory for the items themselves. The present study investigated the domain-generality of the item versus serial order dissociation by comparing the differential effects of time-based interfering tasks, such as rhythmic interference and articulatory suppression, on item and order processing in verbal and musical STM domains. In Experiment 1, participants had to maintain sequences of verbal or musical information in STM, followed by a probe sequence, this under different conditions of interference (no-interference, rhythmic interference, articulatory suppression). They were required to decide whether all items of the probe list matched those of the memory list (item condition) or whether the order of the items in the probe sequence matched the order in the memory list (order condition). In Experiment 2, participants performed a serial order probe recognition task for verbal and musical sequences ensuring sequential maintenance processes, under no-interference or rhythmic interference conditions. For Experiment 1, serial order recognition was not significantly more impacted by interfering tasks than was item recognition, this for both verbal and musical domains. For Experiment 2, we observed selective interference of the rhythmic interference condition on both musical and verbal order STM tasks. Overall, the results suggest a similar and selective sensitivity to time-based interference for serial order STM in verbal and musical domains, but only when the STM tasks ensure sequential maintenance processes.

  20. Health economic modeling to assess short-term costs of maternal overweight, gestational diabetes, and related macrosomia - a pilot evaluation.

    Science.gov (United States)

    Lenoir-Wijnkoop, Irene; van der Beek, Eline M; Garssen, Johan; Nuijten, Mark J C; Uauy, Ricardo D

    2015-01-01

    Despite the interest in the impact of overweight and obesity on public health, little is known about the social and economic impact of being born large for gestational age or macrosomic. Both conditions are related to maternal obesity and/or gestational diabetes mellitus (GDM) and associated with increased morbidity for mother and child in the perinatal period. Poorly controlled diabetes during pregnancy, pre- pregnancy maternal obesity and/or excessive maternal weight gain during pregnancy are associated with intermittent periods of fetal exposure to hyperglycemia and subsequent hyperinsulinemia, leading to increased birth weight (e.g., macrosomia), body adiposity, and glycogen storage in the liver. Macrosomia is associated with an increased risk of developing obesity and type 2 diabetes mellitus later in life. Provide insight in the short-term health-economic impact of maternal overweight, GDM, and related macrosomia. To this end, a health economic framework was designed. This pilot study also aims to encourage further health technology assessments, based on country- and population-specific data. The estimation of the direct health-economic burden of maternal overweight, GDM and related macrosomia indicates that associated healthcare expenditures are substantial. The calculation of a budget impact of GDM, based on a conservative approach of our model, using USA costing data, indicates an annual cost of more than $1,8 billion without taking into account long-term consequences. Although overweight and obesity are a recognized concern worldwide, less attention has been given to the health economic consequences of these conditions in women of child-bearing age and their offspring. The presented outcomes underline the need for preventive management strategies and public health interventions on life style, diet and physical activity. Also, the predisposition in people of Asian ethnicity to develop diabetes emphasizes the urgent need to collect more country

  1. Neural markers of age-related reserve and decline in visual processing speed and visual short-term memory capacity

    DEFF Research Database (Denmark)

    Wiegand, Iris

    2013-01-01

    Attentional performance is assumed to be a major source of general cognitive abilities in older age. The present study aimed at identifying neural markers of preserved and declined basic visual attention functions in aging individuals. For groups of younger and older adults, we modeled general...... capacity parameters, visual perceptual processing speed C and vSTM storage capacity K, based on Bundesen’s formal ‘Theory of Visual Attention’, and recorded ERPs of the same participants. First, in both age groups, parameters were correlated with the same distinct ERP markers of C and K, respectively...... in older adults, performance in both parameters was related to two further distinct ERP correlates: older participants with higher relative to lower processing speed showed larger anterior N1 amplitudes and older participants with higher relative to lower storage capacity exhibited a right...

  2. Neural markers of age-related reserve and decline in visual processing speed and visual short-term memory capacity

    DEFF Research Database (Denmark)

    Wiegand, Iris

    2013-01-01

    Attentional performance is assumed to be a major source of general cognitive abilities in older age. The present study aimed at identifying neural markers of preserved and declined basic visual attention functions in aging individuals. For groups of younger and older adults, we modeled general...... capacity parameters, visual perceptual processing speed C and vSTM storage capacity K, based on Bundesen’s formal ‘Theory of Visual Attention’, and recorded ERPs of the same participants. First, in both age groups, parameters were correlated with the same distinct ERP markers of C and K, respectively...

  3. 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.

  4. 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.

  5. Short-term dispersal of Fukushima-derived radionuclides off Japan: modeling efforts and model-data intercomparison

    Directory of Open Access Journals (Sweden)

    I. I. Rypina

    2013-07-01

    Full Text Available The Great East Japan Earthquake and tsunami that caused a loss of power at the Fukushima nuclear power plants (FNPP resulted in emission of radioactive isotopes into the atmosphere and the ocean. In June of 2011, an international survey measuring a variety of radionuclide isotopes, including 137Cs, was conducted in surface and subsurface waters off Japan. This paper presents the results of numerical simulations specifically aimed at interpreting these observations and investigating the spread of Fukushima-derived radionuclides off the coast of Japan and into the greater Pacific Ocean. Together, the simulations and observations allow us to study the dominant mechanisms governing this process, and to estimate the total amount of radionuclides in discharged coolant waters and atmospheric airborne radionuclide fallout. The numerical simulations are based on two different ocean circulation models, one inferred from AVISO altimetry and NCEP/NCAR reanalysis wind stress, and the second generated numerically by the NCOM model. Our simulations determine that > 95% of 137Cs remaining in the water within ~600 km of Fukushima, Japan in mid-June 2011 was due to the direct oceanic discharge. The estimated strength of the oceanic source is 16.2 ± 1.6 PBq, based on minimizing the model-data mismatch. We cannot make an accurate estimate for the atmospheric source strength since most of the fallout cesium had left the survey area by mid-June. The model explained several key features of the observed 137Cs distribution. First, the absence of 137Cs at the southernmost stations is attributed to the Kuroshio Current acting as a transport barrier against the southward progression of 137Cs. Second, the largest 137Cs concentrations were associated with a semi-permanent eddy that entrained 137Cs-rich waters, collecting and stirring them around the eddy perimeter. Finally, the intermediate 137Cs concentrations at the westernmost stations are attributed to younger, and

  6. MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 1: Theory

    OpenAIRE

    Dominicis, M.; Pinardi, N.; Zodiatis, G.; Lardner, R.

    2013-01-01

    The processes of transport, diffusion and transformation of surface oil in seawater can be simulated using a Lagrangian model formalism coupled with Eulerian circulation models. This paper describes the formalism and the conceptual assumptions of a Lagrangian marine surface oil slick numerical model and rewrites the constitutive equations in a modern mathematical framework. The Lagrangian numerical representation of the oil slick requires three different state variables: the...

  7. Empirical evidence for musical syntax processing? Computer simulations reveal the contribution of auditory short-term memory

    OpenAIRE

    Bigand, Emmanuel; Delbé, Charles; Poulin-Charronnat, Bénédicte; Leman, Marc; Tillmann, Barbara

    2014-01-01

    During the last decade, it has been argued that (1) music processing involves syntactic representations similar to those observed in language, and (2) that music and language share similar syntactic-like processes and neural resources. This claim is important for understanding the origin of music and language abilities and, furthermore, it has clinical implications. The Western musical system, however, is rooted in psychoacoustic properties of sound, and this is not the case for linguistic sy...

  8. Towards an integrative model of visual short-term memory maintenance: Evidence from the effects of attentional control, load, decay, and their interactions in childhood.

    Science.gov (United States)

    Shimi, Andria; Scerif, Gaia

    2017-12-01

    Over the past decades there has been a surge of research aiming to shed light on the nature of capacity limits to visual short-term memory (VSTM). However, an integrative account of this evidence is currently missing. We argue that investigating parameters constraining VSTM in childhood suggests a novel integrative model of VSTM maintenance, and that this in turn informs mechanisms of VSTM maintenance in adulthood. Over 3 experiments with 7-year-olds and young adults (total N=206), we provide evidence for multiple cognitive processes interacting to constrain VSTM performance. While age-related increases in storage capacity are undisputable, we replicate the finding that attentional processes control what information will be encoded and maintained in VSTM in the face of increased competition. Therefore, a central process to the current model is attentional refreshment, a mechanism that it is thought to reactivate and strengthen the signal of the visual representations. Critically, here we also show that attentional influences on VSTM are further constrained by additional factors, traditionally studied to the exclusion of each other, such as memory load and temporal decay. We propose that these processes work synergistically in an elegant manner to capture the adult-end state, whereas their less refined efficiency and modulations in childhood account for the smaller VSTM capacity that 7-year-olds demonstrate compared to older individuals. We conclude that going beyond the investigation of single cognitive mechanisms, to their interactions, holds the promise to understand both developing and fully developed maintenance in VSTM. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Modeling the Short-Term Effect of Traffic and Meteorology on Air Pollution in Turin with Generalized Additive Models

    Directory of Open Access Journals (Sweden)

    Pancrazio Bertaccini

    2012-01-01

    Full Text Available Vehicular traffic plays an important role in atmospheric pollution and can be used as one of the key predictors in air-quality forecasting models. The models that can account for the role of traffic are especially valuable in urban areas, where high pollutant concentrations are often observed during particular times of day (rush hour and year (winter. In this paper, we develop a generalized additive models approach to analyze the behavior of concentrations of nitrogen dioxide (NO2, and particulate matter (PM10, collected at the environmental monitoring stations distributed throughout the city of Turin, Italy, from December 2003 to April 2005. We describe nonlinear relationships between predictors and pollutants, that are adjusted for unobserved time-varying confounders. We examine several functional forms for the traffic variable and find that a simple form can often provide adequate modeling power. Our analysis shows that there is a saturation effect of traffic on NO2, while such saturation is less evident in models linking traffic to PM10 behavior, having adjusted for meteorological covariates. Moreover, we consider the proposed models separately by seasons and highlight similarities and differences in the predictors’ partial effects. Finally, we show how forecasting can help in evaluating traffic regulation policies.

  10. Designing the input vector to ANN-based models for short-term load forecast in electricity distribution systems

    International Nuclear Information System (INIS)

    Santos, P.J.; Martins, A.G.; Pires, A.J.

    2007-01-01

    The present trend to electricity market restructuring increases the need for reliable short-term load forecast (STLF) algorithms, in order to assist electric utilities in activities such as planning, operating and controlling electric energy systems. Methodologies such as artificial neural networks (ANN) have been widely used in the next hour load forecast horizon with satisfactory results. However, this type of approach has had some shortcomings. Usually, the input vector (IV) is defined in a arbitrary way, mainly based on experience, on engineering judgment criteria and on concern about the ANN dimension, always taking into consideration the apparent correlations within the available endogenous and exogenous data. In this paper, a proposal is made of an approach to define the IV composition, with the main focus on reducing the influence of trial-and-error and common sense judgments, which usually are not based on sufficient evidence of comparative advantages over previous alternatives. The proposal includes the assessment of the strictly necessary instances of the endogenous variable, both from the point of view of the contiguous values prior to the forecast to be made, and of the past values representing the trend of consumption at homologous time intervals of the past. It also assesses the influence of exogenous variables, again limiting their presence at the IV to the indispensable minimum. A comparison is made with two alternative IV structures previously proposed in the literature, also applied to the distribution sector. The paper is supported by a real case study at the distribution sector. (author)

  11. Designing the input vector to ANN-based models for short-term load forecast in electricity distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Santos, P.J. [LabSEI-ESTSetubal-Department of Electrical Engineering at Escola Superior de Tecnologia, Polytechnic Institute of Setubal Rua Vale de Chaves Estefanilha, 2910-761 Setubal (Portugal); Martins, A.G. [Department of Electrical Engineering, FCTUC/INESC, Polo 2 University of Coimbra, Pinhal de Marrocos, 3030 Coimbra (Portugal); Pires, A.J. [LabSEI-ESTSetubal-Department of Electrical Engineering at Escola Superior de Tecnologia, Polytechnic Institute of Setubal Rua Vale de, Chaves Estefanilha, 2910-761 Setubal (Portugal)

    2007-05-15

    The present trend to electricity market restructuring increases the need for reliable short-term load forecast (STLF) algorithms, in order to assist electric utilities in activities such as planning, operating and controlling electric energy systems. Methodologies such as artificial neural networks (ANN) have been widely used in the next hour load forecast horizon with satisfactory results. However, this type of approach has had some shortcomings. Usually, the input vector (IV) is defined in a arbitrary way, mainly based on experience, on engineering judgment criteria and on concern about the ANN dimension, always taking into consideration the apparent correlations within the available endogenous and exogenous data. In this paper, a proposal is made of an approach to define the IV composition, with the main focus on reducing the influence of trial-and-error and common sense judgments, which usually are not based on sufficient evidence of comparative advantages over previous alternatives. The proposal includes the assessment of the strictly necessary instances of the endogenous variable, both from the point of view of the contiguous values prior to the forecast to be made, and of the past values representing the trend of consumption at homologous time intervals of the past. It also assesses the influence of exogenous variables, again limiting their presence at the IV to the indispensable minimum. A comparison is made with two alternative IV structures previously proposed in the literature, also applied to the distribution sector. The paper is supported by a real case study at the distribution sector. (author)

  12. Short-term treatment of equine wounds with orf virus IL-10 and VEGF-E dampens inflammation and promotes repair processes without accelerating closure.

    Science.gov (United States)

    Bodaan, Christa J; Wise, Lyn M; Wakelin, Kirsty A; Stuart, Gabriella S; Real, Nicola C; Mercer, Andrew A; Riley, Christopher B; Theoret, Christine

    2016-11-01

    Healing is delayed in limb wounds relative to body wounds of horses, partly because of sustained inflammation and inefficient angiogenesis. In laboratory animals, proteins derived from orf virus modulate these processes and enhance healing. We aimed to compare immune cell trafficking and the inflammatory, vascular, and epidermal responses in body and limb wounds of horses and then to investigate the impact of orf virus interleukin-10 and vascular endothelial growth factor-E on these processes. Standardized excisional wounds were created on the body and forelimb of horses and their progression monitored macroscopically until healed. Tissue samples were harvested to measure the expression of genes regulating inflammation and repair (quantitative polymerase chain reaction) and to observe epithelialization (histology), innate immune cell infiltration, and angiogenesis (immunofluorescence). Delayed healing of limb wounds was characterized by intensified and extended pro-inflammatory signaling and exacerbated innate immune response, concomitant with the absence of anti-inflammatory eIL-10. Blood vessels were initially more permeable and then matured belatedly, concomitant with retarded production of angiogenic factors. Epithelial coverage was achieved belatedly in limb wounds. Viral proteins were administered to wounds of one body and one limb site/horse at days 1-3, while wounds at matching sites served as controls. Treatment dampened pro-inflammatory gene expression and the innate immune response in all wounds. It also improved angiogenic gene expression, but primarily in body wounds, where it altered blood vessel density and myofibroblast persistence. Moreover, the viral proteins increased epithelialization of all wounds. The short-term viral protein therapy did not, however, improve the healing rate of wounds in either location, likely due to suboptimal dosing. In conclusion, we have further detailed the processes contributing to protracted healing in limb wounds of

  13. Intensive short-term dynamic psychotherapy for severe music performance anxiety: assessment, process, and outcome of psychotherapy with a professional orchestral musician.

    Science.gov (United States)

    Kenny, Dianna T; Arthey, Stephen; Abbass, Allan

    2014-03-01

    This paper reports on the process and outcome of therapy using intensive short-term dynamic psychotherapy (ISTDP) with a professional musician who had suffered severe music performance anxiety over the course of his entire 30-year career. In this paper, we describe the nature of the therapy, the case history of the musician, the first assessment and trial therapy session, and the course and successful outcome of therapy. The patient underwent 10 sessions of ISTDP over a period of 4 months. This paper reports on the first 6 sessions, which were most relevant to the understanding and treatment of the patient's severe music performance anxiety. This case study is the first reported application of ISTDP to a professional musician. We believe that this case study provides initial support that moderate to severe performance anxiety, in at least some cases, has its origins in unresolved complex emotions and defences arising from ruptures to early attachment relationships.

  14. A model study of the response of mesospheric ozone to short-term solar ultraviolet flux variations

    Science.gov (United States)

    Summers, M. E.; Bevilacqua, R. M.; Strobel, D. F.; Zhu, Xun; Deland, M. T.; Allen, M.; Keating, G. M.

    1990-01-01

    An investigation is conducted in order to determine the relative importance of several modeled processes in controlling the magnitude and phase of the mesospheric ozone response. A detailed one-dimensional modeling study of the mesospheric ozone response to solar UV flux variations is conducted to remove some of the deficiencies in previous studies. This study is also used to examine specifically the importance of solar zenith angle, self-consistent calculation of water vapor abundance, and temperature feedback with a nonlocal thermodynamic equilibrium radiation model. The photochemical model is described, and the assumptions made for the purpose of comparing model results with the observed ozone response obtained from a statistical analysis of Solar Mesosphere Explorer data (Keating et al., 1987) are discussed. The numerical results for the theoretical ozone response are presented. The results of selected time-dependent calculations are considered to illustrate the degree to which a relatively simple model of the mesosphere is able to capture the major characteristics of the observed response.

  15. On the time course of short-term forgetting: a human experimental model for the sense of balance.

    Science.gov (United States)

    Tribukait, Arne; Eiken, Ola

    2016-02-01

    The primary aim of this study was to establish whether the decline of the memory of an angular displacement, detected by the semicircular canals, is best characterized by an exponential function or by a power function. In 27 subjects a conflict was created between the semicircular canals and the graviceptive systems. Subjects were seated, facing forwards, in the gondola of a large centrifuge. The centrifuge was accelerated from stationary to 2.5Gz. While the swing out of the gondola (66°) during acceleration constitutes a frontal plane angular-displacement stimulus to the semicircular canals, the graviceptive systems persistently signal that the subject is upright. During 6 min at 2.5Gz the perceived head and body position was recorded; in darkness the subject repeatedly adjusted the orientation of a luminous line so that it appeared to be horizontal. Acceleration of the centrifuge induced a sensation of tilt which declined with time in a characteristic way. A three-parameter exponential function (Y = Ae(-bt) + C) and a power function (Y = At(-b) + C) were fitted to the data points. The inter-individual variability was considerable. In the vast majority of cases, however, the exponential function provided a better fit (in terms of RMS error) than the power function. The mean exponential function was: y = 27.8e(-0.018t) + 0.5°, where t is time in seconds. Findings are discussed with connection to possible underlying neural mechanisms; in particular, the head-direction system and short-term potentiation and persistent action potential firing in the hippocampus are considered.

  16. Using Ensemble Short-Term Initialized Coupled NASA GEOS5 Climate Model Integrations to Study Convective Bias Growth

    Science.gov (United States)

    Cohen, Charlie; Robertson, Franklin; Molod, Andrea

    2014-01-01

    The representation of convective processes, particularly deep convection in the tropics, remains a persistent problem in climate models. In fact structural biases in the distribution of tropical rainfall in the CMIP5 models is hardly different than that of the CMIP3 versions. Given that regional climate change at higher latitudes is sensitive to the configuration of tropical forcing, this persistent bias is a major issue for the credibility of climate change projections. In this study we use model output from integrations of the NASA Global Earth Observing System Five (GEOS5) climate modeling system to study the evolution of biases in the location and intensity of convective processes. We take advantage of a series of hindcast experiments done in support of the US North American Multi-Model Ensemble (NMME) initiative. For these experiments a nine-month forecast using a coupled model configuration is made approximately every five days over the past 30 years. Each forecast is started with an updated analysis of the ocean, atmosphere and land states. For a given calendar month we have approximately 180 forecasts with daily means of various quantities. These forecasts can be averaged to essentially remove "weather scales" and highlight systematic errors as they evolve. Our primary question is to ask how the spatial structure of daily mean precipitation over the tropics evolves from the initial state and what physical processes are involved. Errors in parameterized convection, various water and energy fluxes and the divergent circulation are found to set up on fast time scales (order five days) compared to errors in the ocean, although SST changes can be non-negligible over that time. For the month of June the difference between forecast day five versus day zero precipitation looks quite similar to the difference between the June precipitation climatology and that from the Global Precipitation Climatology Project (GPCP). We focus much of our analysis on the influence of

  17. Validation of a short-term shoreline evolution model and coastal risk management implications. The case of the NW Portuguese coast (Ovar-Marinha Grande)

    Science.gov (United States)

    Cenci, Luca; Giuseppina Persichillo, Maria; Disperati, Leonardo; Oliveira, Eduardo R.; de Fátima Lopes Alves, Maria; Boni, Giorgio; Pulvirenti, Luca; Phillips, Mike

    2015-04-01

    Coastal zones are fragile and dynamic environments where environmental, economic and social aspects are interconnected. While these areas are often highly urbanised, they are especially vulnerable to natural hazards (e.g. storms, floods, erosion, storm surges). Hence, high risk affects people and goods in several coastal zones throughout the world. The recent storms that hit the European coasts (Hercules, Christian and Stephanie, among others) showed the high vulnerability of these territories. Integrated Coastal Management (ICM) deals with the sustainable development of coastal zones by taking into account the different aspects that affect them, including risks adaptation and mitigation. Accurate mapping of shoreline position through time and models to predict shoreline evolution play a fundamental role for coastal zone risk management. In this context, spaceborne remote sensing is fundamental because it provides synoptic and multitemporal information that allow the extraction of shorelines' proxies. These are stable coastal features (e.g. the vegetation lines, the foredune toe, etc.) that can be mapped instead of the proper shoreline, which is an extremely dynamic boundary. The use of different proxies may provide different evolutionary patterns for the same study area; therefore it is important to assess which is the most suitable, given the environmental characteristics of a specific area. In Portugal, the coastal stretch between Ovar and Marinha Grande is one of the greatest national challenges in terms of integrated management of resources and risks. This area is characterised by intense erosive processes that largely exceed the shoreline's retreat predictions made in the first Coastal Zone Management Plan, developed in 2000. The aim of this work was to assess the accuracy of a new model of shoreline evolution implemented in 2013 in order to check its robustness for short-term predictions. The method exploited the potentialities of the Landsat archive

  18. The BACHD Rat Model of Huntington Disease Shows Signs of Fronto-Striatal Dysfunction in Two Operant Conditioning Tests of Short-Term Memory.

    Science.gov (United States)

    Clemensson, Erik Karl Håkan; Clemensson, Laura Emily; Riess, Olaf; Nguyen, Huu Phuc

    2017-01-01

    The BACHD rat is a recently developed transgenic animal model of Huntington disease, a progressive neurodegenerative disorder characterized by extensive loss of striatal neurons. Cognitive impairments are common among patients, and characterization of similar deficits in animal models of the disease is therefore of interest. The present study assessed the BACHD rats' performance in the delayed alternation and the delayed non-matching to position test, two Skinner box-based tests of short-term memory function. The transgenic rats showed impaired performance in both tests, indicating general problems with handling basic aspects of the tests, while short-term memory appeared to be intact. Similar phenotypes have been found in rats with fronto-striatal lesions, suggesting that Huntington disease-related neuropathology might be present in the BACHD rats. Further analyses indicated that the performance deficit in the delayed alternation test might be due to impaired inhibitory control, which has also been implicated in Huntington disease patients. The study ultimately suggests that the BACHD rats might suffer from neuropathology and cognitive impairments reminiscent of those of Huntington disease patients.

  19. The BACHD Rat Model of Huntington Disease Shows Signs of Fronto-Striatal Dysfunction in Two Operant Conditioning Tests of Short-Term Memory.

    Directory of Open Access Journals (Sweden)

    Erik Karl Håkan Clemensson

    Full Text Available The BACHD rat is a recently developed transgenic animal model of Huntington disease, a progressive neurodegenerative disorder characterized by extensive loss of striatal neurons. Cognitive impairments are common among patients, and characterization of similar deficits in animal models of the disease is therefore of interest. The present study assessed the BACHD rats' performance in the delayed alternation and the delayed non-matching to position test, two Skinner box-based tests of short-term memory function. The transgenic rats showed impaired performance in both tests, indicating general problems with handling basic aspects of the tests, while short-term memory appeared to be intact. Similar phenotypes have been found in rats with fronto-striatal lesions, suggesting that Huntington disease-related neuropathology might be present in the BACHD rats. Further analyses indicated that the performance deficit in the delayed alternation test might be due to impaired inhibitory control, which has also been implicated in Huntington disease patients. The study ultimately suggests that the BACHD rats might suffer from neuropathology and cognitive impairments reminiscent of those of Huntington disease patients.

  20. Modelling of long-term and short-term mechanisms of arterial pressure control in the cardiovascular system: an object-oriented approach.

    Science.gov (United States)

    Fernandez de Canete, J; Luque, J; Barbancho, J; Munoz, V

    2014-04-01

    A mathematical model that provides an overall description of both the short- and long-term mechanisms of arterial pressure regulation is presented. Short-term control is exerted through the baroreceptor reflex while renal elimination plays a role in long-term control. Both mechanisms operate in an integrated way over the compartmental model of the cardiovascular system. The whole system was modelled in MODELICA, which uses a hierarchical object-oriented modelling strategy, under the DYMOLA simulation environment. The performance of the controlled system was analysed by simulation in light of the existing hypothesis and validation tests previously performed with physiological data, demonstrating the effectiveness of both regulation mechanisms under physiological and pathological conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. 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.

  2. Short-Term Price Forecasting Models Based on Artificial Neural Networks for Intraday Sessions in the Iberian Electricity Market

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2016-09-01

    Full Text Available This paper presents novel intraday session models for price forecasts (ISMPF models for hourly price forecasting in the six intraday sessions of the Iberian electricity market (MIBEL and the analysis of mean absolute percentage errors (MAPEs obtained with suitable combinations of their input variables in order to find the best ISMPF models. Comparisons of errors from different ISMPF models identified the most important variables for forecasting purposes. Similar analyses were applied to determine the best daily session models for price forecasts (DSMPF models for the day-ahead price forecasting in the daily session of the MIBEL, considering as input variables extensive hourly time series records of recent prices, power demands and power generations in the previous day, forecasts of demand, wind power generation and weather for the day-ahead, and chronological variables. ISMPF models include the input variables of DSMPF models as well as the daily session prices and prices of preceding intraday sessions. The best ISMPF models achieved lower MAPEs for most of the intraday sessions compared to the error of the best DSMPF model; furthermore, such DSMPF error was very close to the lowest limit error for the daily session. The best ISMPF models can be useful for MIBEL agents of the electricity intraday market and the electric energy industry.

  3. Calibration and validation of models for short-term decomposition and N mineralization of plant residues in the tropics

    Directory of Open Access Journals (Sweden)

    Alexandre Ferreira do Nascimento

    2012-12-01

    Full Text Available Insight of nutrient release patterns associated with the decomposition of plant residues is important for their effective use as a green manure in food production systems. Thus, this study aimed to evaluate the ability of the Century, APSIM and NDICEA simulation models for predicting the decomposition and N mineralization of crop residues in the tropical Atlantic forest biome, Brazil. The simulation models were calibrated based on actual decomposition and N mineralization rates of three types of crop residues with different chemical and biochemical composition. The models were also validated for different pedo-climatic conditions and crop residues conditions. In general, the accuracy of decomposition and N mineralization improved after calibration. Overall RMSE values for the decomposition and N mineralization of the crop materials varied from 7.4 to 64.6% before models calibration compared to 3.7 to 16.3 % after calibration. Therefore, adequate calibration of the models is indispensable for use them under humid tropical conditions. The NDICEA model generally outperformed the other models. However, the decomposition and N mineralization was not very accurate during the first 30 days of incubation, especially for easily decomposable crop residues. An additional model variable may be required to capture initial microbiological growth as affected by the moisture dynamics of the residues, as is the case in surface residues decomposition models.

  4. Using generalized linear models to estimate selectivity from short-term recoveries of tagged red drum Sciaenops ocellatus: Effects of gear, fate, and regulation period

    Science.gov (United States)

    Burdick, Summer M.; Hightower, Joseph E.; Bacheler, Nathan M.; Paramore, Lee M.; Buckel, Jeffrey A.; Pollock, Kenneth H.

    2010-01-01

    Estimating the selectivity patterns of various fishing gears is a critical component of fisheries stock assessment due to the difficulty in obtaining representative samples from most gears. We used short-term recoveries (n = 3587) of tagged red drum Sciaenops ocellatus to directly estimate age- and length-based selectivity patterns using generalized linear models. The most parsimonious models were selected using AIC, and standard deviations were estimated using simulations. Selectivity of red drum was dependent upon the regulation period in which the fish was caught, the gear used to catch the fish (i.e., hook-and-line, gill nets, pound nets), and the fate of the fish upon recovery (i.e., harvested or released); models including all first-order interactions between main effects outperformed models without interactions. Selectivity of harvested fish was generally dome-shaped and shifted toward larger, older fish in response to regulation changes. Selectivity of caught-and-released red drum was highest on the youngest and smallest fish in the early and middle regulation periods, but increased on larger, legal-sized fish in the late regulation period. These results suggest that catch-and-release mortality has consistently been high for small, young red drum, but has recently become more common in larger, older fish. This method of estimating selectivity from short-term tag recoveries is valuable because it is simpler than full tag-return models, and may be more robust because yearly fishing and natural mortality rates do not need to be modeled and estimated.

  5. A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

    International Nuclear Information System (INIS)

    Feng, Cong; Cui, Mingjian; Hodge, Bri-Mathias; Zhang, Jie

    2017-01-01

    Highlights: • An ensemble model is developed to produce both deterministic and probabilistic wind forecasts. • A deep feature selection framework is developed to optimally determine the inputs to the forecasting methodology. • The developed ensemble methodology has improved the forecasting accuracy by up to 30%. - Abstract: With the growing wind penetration into the power system worldwide, improving wind power forecasting accuracy is becoming increasingly important to ensure continued economic and reliable power system operations. In this paper, a data-driven multi-model wind forecasting methodology is developed with a two-layer ensemble machine learning technique. The first layer is composed of multiple machine learning models that generate individual forecasts. A deep feature selection framework is developed to determine the most suitable inputs to the first layer machine learning models. Then, a blending algorithm is applied in the second layer to create an ensemble of the forecasts produced by first layer models and generate both deterministic and probabilistic forecasts. This two-layer model seeks to utilize the statistically different characteristics of each machine learning algorithm. A number of machine learning algorithms are selected and compared in both layers. This developed multi-model wind forecasting methodology is compared to several benchmarks. The effectiveness of the proposed methodology is evaluated to provide 1-hour-ahead wind speed forecasting at seven locations of the Surface Radiation network. Numerical results show that comparing to the single-algorithm models, the developed multi-model framework with deep feature selection procedure has improved the forecasting accuracy by up to 30%.

  6. DEVELOPING A MODULAR PORTFOLIO SELECTION MODEL FOR SHORT-TERM AND LONGTERM MARKET TRENDS AND MASS PSYCHOLOGY

    Directory of Open Access Journals (Sweden)

    M. Jasemi

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: In an effort to model stock markets, many researchers have developed portfolio selection models to maximise investor satisfaction. However, this field still needs more accurate and comprehensive models. Development of these models is difficult because of unpredictable economic, social, and political variables that affect stock market behaviour. In this paper, a new model with three modules for portfolio optimisation is presented. The first module derives the efficient frontier through a new approach; the second presents an intelligent mechanism for emitting trading signals; while the third module integrates the outputs of the first two modules. Some important features of the model in comparison with others are: 1 consideration of investors’ emotions – the psychology of the market – that arises from the three above-mentioned factors; 2 significant loosening of simplifying assumptions about markets and stocks; and 3 greater sensitivity to new data.

    AFRIKAANSE OPSOMMING: In ‘n poging om aandelemarkte te modelleer het verskeie navorsers portefeulje-seleksiemodelle ontwikkel om beleggers se tevredenheid te maksimiseer. Desnieteenstaande word meer akkurate en omvattende modelle benodig. Die ontwikkeling van hierdie modelle word bemoeilik deur die onvoorspelbare ekonomiese, sosiale en politiese veranderlikes wat aandelemarkte se gedrag raak. In hierdie artikel word ‘n nuwe model voorgehou wat bestaan uit drie modules vir portefeulje-optimisering. Die eerste module bepaal die doelmatigheidsgrens op ‘n nuwe metode; die tweede hou ‘n intelligente meganisme voor om transaksieseine te lewer terwyl die derde module die uitsette van die eerste twee modules integreer. Sommige van die belangrike eienskappe van die model wat dit van ander onderskei is: 1 konsiderasie van die beleggers se emosies – die sielkunde van die mark – wat ontstaan vanweë die genoemde faktore; 2 betekenisvolle verslapping van die

  7. Understanding phonological memory deficits in boys with attention-deficit/hyperactivity disorder (ADHD): dissociation of short-term storage and articulatory rehearsal processes.

    Science.gov (United States)

    Bolden, Jennifer; Rapport, Mark D; Raiker, Joseph S; Sarver, Dustin E; Kofler, Michael J

    2012-08-01

    The current study dissociated and examined the two primary components of the phonological working memory subsystem--the short-term store and articulatory rehearsal mechanism--in boys with ADHD (n = 18) relative to typically developing boys (n = 15). Word lists of increasing length (2, 4, and 6 words per trial) were presented to and recalled by children following a brief (3 s) interval to assess their phonological short-term storage capacity. Children's ability to utilize the articulatory rehearsal mechanism to actively maintain information in the phonological short-term store was assessed using word lists at their established memory span but with extended rehearsal times (12 s and 21 s delays). Results indicate that both phonological shortterm storage capacity and articulatory rehearsal are impaired or underdeveloped to a significant extent in boys with ADHD relative to typically developing boys, even after controlling for age, SES, IQ, and reading speed. Larger magnitude deficits, however, were apparent in short-term storage capacity (ES = 1.15 to 1.98) relative to articulatory rehearsal (ES = 0.47 to 1.02). These findings are consistent with previous reports of deficient phonological short-term memory in boys with ADHD, and suggest that future attempts to develop remedial cognitive interventions for children with ADHD will need to include active components that require children to hold increasingly more information over longer time intervals.

  8. Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis.

    Science.gov (United States)

    Hemmati, Reza; Saboori, Hedayat

    2016-05-01

    Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics.

  9. Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis

    Science.gov (United States)

    Hemmati, Reza; Saboori, Hedayat

    2016-01-01

    Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. PMID:27222741

  10. A possibilistic model to determine the cost of environmental quality in mid/short term planning of an electricity distribution system

    International Nuclear Information System (INIS)

    Schweickardt, Gustavo Alejandro; Gimenez Alvarez, Juan Manuel

    2012-01-01

    This work presents a Possibilistic Optimization Model to determine the Dynamic Environmental Quality Cost, applied on an Electricity Distribution System and measured as Network System Visual Impact. The Mid/Short Term Planning is the Regulatory Control Period. A multicriteria optimization approach is proposed, and for each criterion, non-stochastic uncertainties are recognized and represented by mean the introduction of Fuzzy Sets. In this way, a possibility in the occurrence of criteria variables values is established. In addition, as consequence of uncertainties of criteria preference ranking, a Model to obtain criteria Priority Vector is introduced. The Environmental Quality Cost determination is based in the relationship between the Investment Cost and an Impact Index of Network System Environmental Quality, proposed in this work. Finally, a simulation on a real system and the most important conclusions are presented.

  11. A Hybrid Neural Network and H-P Filter Model for Short-Term Vegetable Price Forecasting

    Directory of Open Access Journals (Sweden)

    Youzhu Li

    2014-01-01

    Full Text Available This paper is concerned with time series data for vegetable prices, which have a great impact on human’s life. An accurate forecasting method for prices and an early-warning system in the vegetable market are an urgent need in people’s daily lives. The time series price data contain both linear and nonlinear patterns. Therefore, neither a current linear forecasting nor a neural network can be adequate for modeling and predicting the time series data. The linear forecasting model cannot deal with nonlinear relationships, while the neural network model alone is not able to handle both linear and nonlinear patterns at the same time. The linear Hodrick-Prescott (H-P filter can extract the trend and cyclical components from time series data. We predict the linear and nonlinear patterns and then combine the two parts linearly to produce a forecast from the original data. This study proposes a structure of a hybrid neural network based on an H-P filter that learns the trend and seasonal patterns separately. The experiment uses vegetable prices data to evaluate the model. Comparisons with the autoregressive integrated moving average method and back propagation artificial neural network methods show that our method has higher accuracy than the others.

  12. Using targeted short-term field investigations to calibrate and evaluate the structure of a hydrological model

    CSIR Research Space (South Africa)

    Hughes, DA

    2013-02-01

    Full Text Available This study combines the application of a hydrological model with the use of field data derived from short period measurement campaigns at two sites, one a low topography forested area and the other a steep grassland catchment. The main objective...

  13. Comparative analysis of methods for modelling the short-term probability distribution of extreme wind turbine loads

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov

    2016-01-01

    extrapolation techniques: the Weibull, Gumbel and Pareto distributions and a double-exponential asymptotic extreme value function based on the ACER method. For the successful implementation of a fully automated extrapolation process, we have developed a procedure for automatic identification of tail threshold...... levels, based on the assumption that the response tail is asymptotically Gumbel distributed. Example analyses were carried out, aimed at comparing the different methods, analysing the statistical uncertainties and identifying the factors, which are critical to the accuracy and reliability...

  14. Using a Process Dissociation Approach to Assess Verbal Short-Term Memory for Item and Order Information in a Sample of Individuals with a Self-Reported Diagnosis of Dyslexia.

    Science.gov (United States)

    Wang, Xiaoli; Xuan, Yifu; Jarrold, Christopher

    2016-01-01

    Previous studies have examined whether difficulties in short-term memory for verbal information, that might be associated with dyslexia, are driven by problems in retaining either information about to-be-remembered items or the order in which these items were presented. However, such studies have not used process-pure measures of short-term memory for item or order information. In this work we adapt a process dissociation procedure to properly distinguish the contributions of item and order processes to verbal short-term memory in a group of 28 adults with a self-reported diagnosis of dyslexia and a comparison sample of 29 adults without a dyslexia diagnosis. In contrast to previous work that has suggested that individuals with dyslexia experience item deficits resulting from inefficient phonological representation and language-independent order memory deficits, the results showed no evidence of specific problems in short-term retention of either item or order information among the individuals with a self-reported diagnosis of dyslexia, despite this group showing expected difficulties on separate measures of word and non-word reading. However, there was some suggestive evidence of a link between order memory for verbal material and individual differences in non-word reading, consistent with other claims for a role of order memory in phonologically mediated reading. The data from the current study therefore provide empirical evidence to question the extent to which item and order short-term memory are necessarily impaired in dyslexia.

  15. Short-Term Wind Speed Forecasting Study and Its Application Using a Hybrid Model Optimized by Cuckoo Search

    Directory of Open Access Journals (Sweden)

    Xuejun Chen

    2015-01-01

    Full Text Available The support vector regression (SVR and neural network (NN are both new tools from the artificial intelligence field, which have been successfully exploited to solve various problems especially for time series forecasting. However, traditional SVR and NN cannot accurately describe intricate time series with the characteristics of high volatility, nonstationarity, and nonlinearity, such as wind speed and electricity price time series. This study proposes an ensemble approach on the basis of 5-3 Hanning filter (5-3H and wavelet denoising (WD techniques, in conjunction with artificial intelligence optimization based SVR and NN model. So as to confirm the validity of the proposed model, two applicative case studies are conducted in terms of wind speed series from Gansu Province in China and electricity price from New South Wales in Australia. The computational results reveal that cuckoo search (CS outperforms both PSO and GA with respect to convergence and global searching capacity, and the proposed CS-based hybrid model is effective and feasible in generating more reliable and skillful forecasts.

  16. Effect of skin metabolism on dermal delivery of testosterone: qualitative assessment using a new short-term skin model.

    Science.gov (United States)

    Jacques, C; Perdu, E; Jamin, E L; Cravedi, J P; Mavon, A; Duplan, H; Zalko, D

    2014-01-01

    The skin is a metabolically active organ expressing biotransformation enzymes able to metabolize both endogenous molecules and xenobiotics. We investigated the impact of metabolism on the delivery of testosterone through the skin with an ex vivo pig ear skin system as an alternative model for human skin. Penetration, absorption and metabolic capabilities were investigated up to 72 h after application of [(14)C]-testosterone doses of 50-800 nmol on either fresh or frozen skin, with the latter model being metabolically inactive. Testosterone absorption and metabolite production were monitored by radio-HPLC and gas chromatography-mass spectrometry. Testosterone absorption through frozen skin was much lower, irrespective of the dose of testosterone applied, compared to fresh skin. Using fresh skin samples, >95% of the radioactivity recovered in culture media, as well as the skin itself, corresponded to metabolites. These results were compared with the metabolic data obtained from other in vitro systems (liver and skin microsomes). The present work leads to the conclusion that most of the enzymatic activities expressed in liver fractions are also expressed in pig and human skin. The metabolic activity of the skin can modulate the biological activity of pharmaceuticals (and xenobiotics). Consequently, it can also greatly affect transdermal drug delivery.

  17. Short term synaptic depression improves information transfer in perceptual multistability

    OpenAIRE

    Kilpatrick, Zachary P.

    2013-01-01

    Competitive neural networks are often used to model the dynamics of perceptual bistability. Switching between percepts can occur through fluctuations and/or a slow adaptive process. Here, we analyze switching statistics in competitive networks with short term synaptic depression and noise. We start by analyzing a ring model that yields spatially structured solutions and complement this with a study of a space-free network whose populations are coupled with mutual inhibition. Dominance times a...

  18. Are short-term focused training courses on a phantom model using porcine gall bladder useful for trainees in acquiring basic laparoscopic skills?

    Science.gov (United States)

    Bansal, Virinder Kumar; Panwar, Rajesh; Misra, Mahesh C; Bhattacharjee, Hemanga K; Jindal, Vikas; Loli, Athiko; Goswami, Amit; Krishna, Asuri; Tamang, Tseten

    2012-04-01

    The best training method in laparoscopic surgery has not been defined. We evaluated the efficacy of laparoscopic skills acquisition in a short-term focused program. Two hundred fifty-six participants undergoing training on a phantom model were divided into 2 groups. Group 1 had no exposure and group 2 had performed a few laparoscopic surgeries. Acquisition of laparoscopic skills was assessed by operation time and the modified Global Operative Assessment of Laparoscopic Skills (GOALS) scale. A questionnaire was sent to the participants after 3 to 6 months for assessment of impact of training. There was a statistically significant improvement in the assessed parameters and in the mean score of all 5 domains of GOALS. The participants in group 2 performed better than those in group 1 in the first case. The difference between both the groups disappeared after the training. Participants who responded to the questionnaire felt that training helped them in improving their performance in the operation theater.

  19. A Rodent Model of Night-Shift Work Induces Short-Term and Enduring Sleep and Electroencephalographic Disturbances.

    Science.gov (United States)

    Grønli, Janne; Meerlo, Peter; Pedersen, Torhild T; Pallesen, Ståle; Skrede, Silje; Marti, Andrea R; Wisor, Jonathan P; Murison, Robert; Henriksen, Tone E G; Rempe, Michael J; Mrdalj, Jelena

    2017-02-01

    Millions of people worldwide are working at times that overlap with the normal time for sleep. Sleep problems related to the work schedule may mediate the well-established relationship between shift work and increased risk for disease, occupational errors and accidents. Yet, our understanding of causality and the underlying mechanisms that explain this relationship is limited. We aimed to assess the consequences of night-shift work for sleep and to examine whether night-shift work-induced sleep disturbances may yield electrophysiological markers of impaired maintenance of the waking brain state. An experimental model developed in rats simulated a 4-day protocol of night-work in humans. Two groups of rats underwent 8-h sessions of enforced ambulation, either at the circadian time when the animal was physiologically primed for wakefulness (active-workers, mimicking day-shift) or for sleep (rest-workers, mimicking night-shift). The 4-day rest-work schedule induced a pronounced redistribution of sleep to the endogenous active phase. Rest-work also led to higher electroencephalogram (EEG) slow-wave (1-4 Hz) energy in quiet wakefulness during work-sessions, suggesting a degraded waking state. After the daily work-sessions, being in their endogenous active phase, rest-workers slept less and had higher gamma (80-90 Hz) activity during wake than active-workers. Finally, rest-work induced an enduring shift in the main sleep period and attenuated the accumulation of slow-wave energy during NREM sleep. A comparison of recovery data from 12:12 LD and constant dark conditions suggests that reduced time in NREM sleep throughout the recorded 7-day recovery phase induced by rest-work may be modulated by circadian factors. Our data in rats show that enforced night-work-like activity during the normal resting phase has pronounced acute and persistent effects on sleep and waking behavior. The study also underscores the potential importance of animal models for future studies on the

  20. Short-term rescue of neonatal lethality in a mouse model of propionic acidemia by gene therapy.

    Science.gov (United States)

    Hofherr, Sean E; Senac, Julien S; Chen, Christopher Y; Palmer, Donna J; Ng, Philip; Barry, Michael A

    2009-02-01

    Propionic acidemia (PA) is a metabolic disorder that causes mental retardation and that can be fatal if untreated. PA is inherited in an autosomal recessive fashion involving mutations in PCCA or PCCB encoding the alpha and beta subunits of propionyl-CoA carboxylase (PCC). Current treatment is based on dietary restriction of substrate amino acids, which attenuates symptoms. However, patients still experience episodes of hyperammonemia that can cause progressive neurologic damage. In this paper, we have tested gene therapy approaches to PA in a stringent mouse model of PCCA deficiency, in which homozygous knockout mice are born but die within 36 hr. In this work, we have delivered first-generation and helper-dependent adenovirus serotype 5 (Ad5) vectors expressing the human PCCA cDNA by intraperitoneal injection into newborn mice. Unmodified Ad5 vectors mediated extensive transduction of the peritoneum with weak liver transduction as determined by luciferase imaging and dsRed expression. In contrast, modification of Ad5 with polyethylene glycol detargeted the virus from the peritoneum and retargeted it for transduction in the liver. When vectors expressing PCCA were injected, significant increases in life span were observed for both the unmodified and polyethylene glycol (PEG)-modified Ad5 vectors. However, this rescue was transient. Similarly, adeno-associated virus serotype 8-mediated transduction also produced only transient rescue. These data show first proof of principle for gene therapy of PA and demonstrate the potential utility of PEG to modify viral tropism in an actual gene therapy application.

  1. A capacity expansion model dealing with balancing requirements, short-term operations and long-run dynamics

    International Nuclear Information System (INIS)

    Villavicencio, Manuel

    2017-01-01

    One of the challenges of current power systems is presented by the need to adequately integrate increasing shares of variable renewable energies (VRE) such as wind and photovoltaic (PV) technologies. The study of capacity investments under this context raises refreshed interrogations about the optimal power generation mix when considering system adequacy, operability and reliability issues. This paper analyses the influence of such considerations and adopts a resource-adequacy approach to propose a stylized capacity expansion model (CEM) that endogenously optimize investments in both generation capacity and new flexibility options such as electric energy storage (EES) and demand side management (DSM) capabilities. Three formulations are tested in order to seize the relevance of system dynamics representation over the valuation of capacity and flexibility investments. In each formulation the complexity of the representation of operating constraints increases. The resource-adequacy approach is then enlarged with a multi-service representation of the power system introducing non-contingency reserve considerations. Therefore, investments decisions are enhanced by information from system operations requirements given by the hourly economic dispatch and also by a reliability criterion given by reserve needs. The formulations are tested on a case study in order to capture the trade-offs of adding more details on the system representation while exogenously imposing supplementary VRE penetration. The results obtained show the importance of adopting a sufficiently detailed representation of system requirements to accurately capture the value of capacity and flexibility when important VRE penetration levels are to be studied, but also to appropriately estimate resulting system cost and CO 2 emissions. (author)

  2. Solar Activity from 2006 to 2014 and Short-term Forecasts of Solar Proton Events Using the ESPERTA Model

    Energy Technology Data Exchange (ETDEWEB)

    Alberti, T.; Lepreti, F. [Dipartimento di Fisica, Università della Calabria, Ponte P. Bucci, Cubo 31C, 87036, Rende (CS) (Italy); Laurenza, M.; Storini, M.; Consolini, G. [INAF-IAPS, Via del Fosso del Cavaliere 100, I-00133, Roma (Italy); Cliver, E. W., E-mail: tommaso.alberti@unical.it, E-mail: monica.laurenza@iaps.inaf.it [National Solar Observatory, Boulder, CO (United States)

    2017-03-20

    To evaluate the solar energetic proton (SEP) forecast model of Laurenza et al., here termed ESPERTA, we computed the input parameters (soft X-ray (SXR) fluence and ∼1 MHz radio fluence) for all ≥M2 SXR flares from 2006 to 2014. This database is outside the 1995–2005 interval on which ESPERTA was developed. To assess the difference in the general level of activity between these two intervals, we compared the occurrence frequencies of SXR flares and SEP events for the first six years of cycles 23 (1996 September–2002 September) and 24 (2008 December–2014 December). We found a reduction of SXR flares and SEP events of 40% and 46%, respectively, in the latter period. Moreover, the numbers of ≥M2 flares with high values of SXR and ∼1 MHz fluences (>0.1 J m{sup −2} and >6 × 10{sup 5} sfu × minute, respectively) are both reduced by ∼30%. A somewhat larger percentage decrease of these two parameters (∼40% versus ∼30%) is obtained for the 2006–2014 interval in comparison with 1995–2005. Despite these differences, ESPERTA performance was comparable for the two intervals. For the 2006–2014 interval, ESPERTA had a probability of detection (POD) of 59% (19/32) and a false alarm rate (FAR) of 30% (8/27), versus a POD = 63% (47/75) and an FAR = 42% (34/81) for the original 1995–2005 data set. In addition, for the 2006–2014 interval the median (average) warning time was estimated to be ∼2 hr (∼7 hr), versus ∼6 hr (∼9 hr), for the 1995–2005 data set.

  3. Effects of curcumin on short-term spatial and recognition memory, adult neurogenesis and neuroinflammation in a streptozotocin-induced rat model of dementia of Alzheimer's type.

    Science.gov (United States)

    Bassani, Taysa B; Turnes, Joelle M; Moura, Eric L R; Bonato, Jéssica M; Cóppola-Segovia, Valentín; Zanata, Silvio M; Oliveira, Rúbia M M W; Vital, Maria A B F

    2017-09-29

    Curcumin is a natural polyphenol with evidence of antioxidant, anti-inflammatory and neuroprotective properties. Recent evidence also suggests that curcumin increases cognitive performance in animal models of dementia, and this effect would be related to its capacity to enhance adult neurogenesis. The aim of this study was to test the hypothesis that curcumin treatment would be able to preserve cognition by increasing neurogenesis and decreasing neuroinflammation in the model of dementia of Alzheimer's type induced by an intracerebroventricular injection of streptozotocin (ICV-STZ) in Wistar rats. The animals were injected with ICV-STZ or vehicle and curcumin treatments (25, 50 and 100mg/kg, gavage) were performed for 30days. Four weeks after surgery, STZ-lesioned animals exhibited impairments in short-term spatial memory (Object Location Test (OLT) and Y maze) and short-term recognition memory (Object Recognition Test - ORT), decreased cell proliferation and immature neurons (Ki-67- and doublecortin-positive cells, respectively) in the subventricular zone (SVZ) and dentate gyrus (DG) of hippocampus, and increased immunoreactivity for the glial markers GFAP and Iba-1 (neuroinflammation). Curcumin treatment in the doses of 50 and 100mg/kg prevented the deficits in recognition memory in the ORT, but not in spatial memory in the OLT and Y maze. Curcumin treatment exerted only slight improvements in neuroinflammation, resulting in no improvements in hippocampal and subventricular neurogenesis. These results suggest a positive effect of curcumin in object recognition memory which was not related to hippocampal neurogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Development of Brazilian prototypes for short-term psychotherapies

    Directory of Open Access Journals (Sweden)

    Fernanda Barcellos Serralta

    Full Text Available Abstract Introduction: The Psychotherapy Process Q-Set (PQS prototype method is used to measure the extent to which ideal processes of different psychotherapies are present in real cases, allowing researchers to examine how adherence to these models relates to or predicts change. Results from studies of short-term psychotherapies suggest that the original psychodynamic prototype is more suitable for studying psychoanalysis and long-term psychodynamic psychotherapy than its time-limited counterparts. Furthermore, culture probably influences how therapies are typically conducted in a given country. Therefore, it seems appropriate to develop Brazilian prototypes on which to base studies of short-term psychodynamic and cognitive-behavioral processes in this country. Objective: To develop prototypes for studying processes of short-term psychotherapies and to examine the degree of adherence of two real psychotherapy cases to these models. Methods: Expert clinicians used the PQS to rate a hypothetical ideal session of either short-term psychodynamic psychotherapy (STPP or cognitive-behavioral therapy (CBT. Ratings were submitted to Q-type factor analysis to confirm the two groups. Regressive factor scores were rank ordered to describe the prototypes. These ideal models were correlated with ratings of actual therapy processes in two complete psychotherapy cases, one STPP and the other CBT. Results: Agreement levels between expert ratings were high and the two ideal models were confirmed. As expected, the PQS ratings for actual STPP and CBT cases had significant correlations with their respective ideal models, but the STPP case also adhered to the CBT prototype. Conclusion: Overall, the findings reveal the adequacy of the prototypes for time-limited therapies, providing initial support of their validity.

  5. Short-term treatment with the GABAA receptor antagonist pentylenetetrazole produces a sustained pro-cognitive benefit in a mouse model of Down's syndrome.

    Science.gov (United States)

    Colas, D; Chuluun, B; Warrier, D; Blank, M; Wetmore, D Z; Buckmaster, P; Garner, C C; Heller, H C

    2013-07-01

    Down's syndrome is a common genetic cause of intellectual disability, for which there are no drug therapies. Mechanistic studies in a model of Down's syndrome [Ts65Dn (TS) mice] demonstrated that impaired cognitive function was due to excessive neuronal inhibitory tone. These deficits were normalized by low doses of GABAA receptor antagonists in adult animals. In this study, we explore the therapeutic potential of pentylenetetrazole, a GABAA receptor antagonist with a history of safe use in humans. Long-term memory was assessed by the novel object recognition test in different cohorts of TS mice after a delay following a short-term chronic treatment with pentylenetetrazole. Seizure susceptibility, an index of treatment safety, was studied by means of EEG, behaviour and hippocampus morphology. EEG spectral analysis was used as a bio-marker of the treatment. PTZ has a wide therapeutic window (0.03-3 mg·kg(-1)) that is >10-1000-fold below its seizure threshold and chronic pentylenetetrazole treatment did not lower the seizure threshold. Short-term, low, chronic dose regimens of pentylenetetrazole elicited long-lasting (>1 week) normalization of cognitive function in young and aged mice. Pentylenetetrazole effectiveness was dependent on the time of treatment; cognitive performance improved after treatment during the light (inactive) phase, but not during the dark (active) phase. Chronic pentylenetetrazole treatment normalized EEG power spectra in TS mice. Low doses of pentylenetetrazole were safe, produced long-lasting cognitive improvements and have the potential of fulfilling an unmet therapeutic need in Down's syndrome. © 2013 The Authors. British Journal of Pharmacology © 2013 The British Pharmacological Society.

  6. Resting-state functional connectivity changes due to acute and short-term valproic acid administration in the baboon model of GGE

    Directory of Open Access Journals (Sweden)

    Felipe S. Salinas

    2017-01-01

    Full Text Available Resting-state functional connectivity (FC is altered in baboons with genetic generalized epilepsy (GGE compared to healthy controls (CTL. We compared FC changes between GGE and CTL groups after intravenous injection of valproic acid (VPA and following one-week of orally administered VPA. Seven epileptic (2 females and six CTL (3 females baboons underwent resting-state fMRI (rs-fMRI at 1 baseline, 2 after intravenous acute VPA administration (20 mg/kg, and 3 following seven-day oral, subacute VPA therapy (20–80 mg/kg/day. FC was evaluated using a data-driven approach, while regressing out the group-wise effects of age, gender and VPA levels. Sixteen networks were identified by independent component analysis (ICA. Each network mask was thresholded (z > 4.00; p < 0.001, and used to compare group-wise FC differences between baseline, intravenous and oral VPA treatment states between GGE and CTL groups. At baseline, FC was increased in most cortical networks of the GGE group but decreased in the thalamic network. After intravenous acute VPA, FC increased in the basal ganglia network and decreased in the parietal network of epileptic baboons to presumed nodes associated with the epileptic network. After oral VPA therapy, FC was decreased in GGE baboons only the orbitofrontal networks connections to the primary somatosensory cortices, reflecting a reversal from baseline comparisons. VPA therapy affects FC in the baboon model of GGE after a single intravenous dose—possibly by facilitating subcortical modulation of the epileptic network and suppressing seizure generation—and after short-term oral VPA treatment, reversing the abnormal baseline increases in FC in the orbitofrontal network. While there is a need to correlate these FC changes with simultaneous EEG recording and seizure outcomes, this study demonstrates the feasibility of evaluating rs-fMRI effects of antiepileptic medications even after short-term exposure.

  7. WRF model sensitivity to land surface model and cumulus parameterization under short-term climate extremes over the southern Great Plains of the United States

    Science.gov (United States)

    Lisi Pei; Nathan Moore; Shiyuan Zhong; Lifeng Luo; David W. Hyndman; Warren E. Heilman; Zhiqiu. Gao

    2014-01-01

    Extreme weather and climate events, especially short-term excessive drought and wet periods over agricultural areas, have received increased attention. The Southern Great Plains (SGP) is one of the largest agricultural regions in North America and features the underlying Ogallala-High Plains Aquifer system worth great economic value in large part due to production...

  8. 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.

  9. Short period forecasting of catchment-scale precipitation. Part II: a water-balance storm model for short-term rainfall and flood forecasting

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2000-01-01

    Full Text Available A simple two-dimensional rainfall model, based on advection and conservation of mass in a vertical cloud column, is investigated for use in short-term rainfall and flood forecasting at the catchment scale under UK conditions. The model is capable of assimilating weather radar, satellite infra-red and surface weather observations, together with forecasts from a mesoscale numerical weather prediction model, to obtain frequently updated forecasts of rainfall fields. Such data assimilation helps compensate for the simplified model dynamics and, taken together, provides a practical real-time forecasting scheme for catchment scale applications. Various ways are explored for using information from a numerical weather prediction model (16.8 km grid within the higher resolution model (5 km grid. A number of model variants is considered, ranging from simple persistence and advection methods used as a baseline, to different forms of the dynamic rainfall model. Model performance is assessed using data from the Wardon Hill radar in Dorset for two convective events, on 10 June 1993 and 16 July 1995, when thunderstorms occurred over southern Britain. The results show that (i a simple advection-type forecast may be improved upon by using multiscan radar data in place of data from the lowest scan, and (ii advected, steady-state predictions from the dynamic model, using 'inferred updraughts', provides the best performance overall. Updraught velocity is inferred at the forecast origin from the last two radar fields, using the mass-balance equation and associated data and is held constant over the forecast period. This inference model proves superior to the buoyancy parameterisation of updraught employed in the original formulation. A selection of the different rainfall forecasts is used as input to a catchment flow forecasting model, the IH PDM (Probability Distributed Moisture model, to assess their effect on flow forecast accuracy for the 135 km2 Brue catchment

  10. A Novel Hybrid Model Based on Extreme Learning Machine, k-Nearest Neighbor Regression and Wavelet Denoising Applied to Short-Term Electric Load Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-05-01

    Full Text Available Electric load forecasting plays an important role in electricity markets and power systems. Because electric load time series are complicated and nonlinear, it is very difficult to achieve a satisfactory forecasting accuracy. In this paper, a hybrid model, Wavelet Denoising-Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EWKM, which combines k-Nearest Neighbor (KNN and Extreme Learning Machine (ELM based on a wavelet denoising technique is proposed for short-term load forecasting. The proposed hybrid model decomposes the time series into a low frequency-associated main signal and some detailed signals associated with high frequencies at first, then uses KNN to determine the independent and dependent variables from the low-frequency signal. Finally, the ELM is used to get the non-linear relationship between these variables to get the final prediction result for the electric load. Compared with three other models, Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EKM, Wavelet Denoising-Extreme Learning Machine (WKM and Wavelet Denoising-Back Propagation Neural Network optimized by k-Nearest Neighbor Regression (WNNM, the model proposed in this paper can improve the accuracy efficiently. New South Wales is the economic powerhouse of Australia, so we use the proposed model to predict electric demand for that region. The accurate prediction has a significant meaning.

  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. A novel two-stage stochastic programming model for uncertainty characterization in short-term optimal strategy for a distribution company

    International Nuclear Information System (INIS)

    Ahmadi, Abdollah; Charwand, Mansour; Siano, Pierluigi; Nezhad, Ali Esmaeel; Sarno, Debora; Gitizadeh, Mohsen; Raeisi, Fatima

    2016-01-01

    In order to supply the demands of the end users in a competitive market, a distribution company purchases energy from the wholesale market while other options would be in access in the case of possessing distributed generation units and interruptible loads. In this regard, this study presents a two-stage stochastic programming model for a distribution company energy acquisition market model to manage the involvement of different electric energy resources characterized by uncertainties with the minimum cost. In particular, the distribution company operations planning over a day-ahead horizon is modeled as a stochastic mathematical optimization, with the objective of minimizing costs. By this, distribution company decisions on grid purchase, owned distributed generation units and interruptible load scheduling are determined. Then, these decisions are considered as boundary constraints to a second step, which deals with distribution company's operations in the hour-ahead market with the objective of minimizing the short-term cost. The uncertainties in spot market prices and wind speed are modeled by means of probability distribution functions of their forecast errors and the roulette wheel mechanism and lattice Monte Carlo simulation are used to generate scenarios. Numerical results show the capability of the proposed method. - Highlights: • Proposing a new a stochastic-based two-stage operations framework in retail competitive markets. • Proposing a Mixed Integer Non-Linear stochastic programming. • Employing roulette wheel mechanism and Lattice Monte Carlo Simulation.

  13. Capturing the sensitivity of land-use regression models to short-term mobile monitoring campaigns using air pollution micro-sensors.

    Science.gov (United States)

    Minet, L; Gehr, R; Hatzopoulou, M

    2017-11-01

    The development of reliable measures of exposure to traffic-related air pollution is crucial for the evaluation of the health effects of transportation. Land-use regression (LUR) techniques have been widely used for the development of exposure surfaces, however these surfaces are often highly sensitive to the data collected. With the rise of inexpensive air pollution sensors paired with GPS devices, we witness the emergence of mobile data collection protocols. For the same urban area, can we achieve a 'universal' model irrespective of the number of locations and sampling visits? Can we trade the temporal representation of fixed-point sampling for a larger spatial extent afforded by mobile monitoring? This study highlights the challenges of short-term mobile sampling campaigns in terms of the resulting exposure surfaces. A mobile monitoring campaign was conducted in 2015 in Montreal; nitrogen dioxide (NO 2 ) levels at 1395 road segments were measured under repeated visits. We developed LUR models based on sub-segments, categorized in terms of the number of visits per road segment. We observe that LUR models were highly sensitive to the number of road segments and to the number of visits per road segment. The associated exposure surfaces were also highly dissimilar. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Diverse Short-Term Dynamics of Inhibitory Synapses Converging on Striatal Projection Neurons: Differential Changes in a Rodent Model of Parkinson’s Disease

    Directory of Open Access Journals (Sweden)

    Janet Barroso-Flores

    2015-01-01

    Full Text Available Most neurons in the striatum are projection neurons (SPNs which make synapses with each other within distances of approximately 100 µm. About 5% of striatal neurons are GABAergic interneurons whose axons expand hundreds of microns. Short-term synaptic plasticity (STSP between fast-spiking (FS interneurons and SPNs and between SPNs has been described with electrophysiological and optogenetic techniques. It is difficult to obtain pair recordings from some classes of interneurons and due to limitations of actual techniques, no other types of STSP have been described on SPNs. Diverse STSPs may reflect differences in presynaptic release machineries. Therefore, we focused the present work on answering two questions: Are there different identifiable classes of STSP between GABAergic synapses on SPNs? And, if so, are synapses exhibiting different classes of STSP differentially affected by dopamine depletion? Whole-cell voltage-clamp recordings on SPNs revealed three classes of STSPs: depressing, facilitating, and biphasic (facilitating-depressing, in response to stimulation trains at 20 Hz, in a constant ionic environment. We then used the 6-hydroxydopamine (6-OHDA rodent model of Parkinson’s disease to show that synapses with different STSPs are differentially affected by dopamine depletion. We propose a general model of STSP that fits all the dynamics found in our recordings.

  15. A trend fixed on firstly and seasonal adjustment model combined with the ε-SVR for short-term forecasting of electricity demand

    International Nuclear Information System (INIS)

    Wang Jianzhou; Zhu Wenjin; Zhang Wenyu; Sun Donghuai

    2009-01-01

    Short-term electricity demand forecasting has always been an essential instrument in power system planning and operation by which an electric utility plans and dispatches loading so as to meet system demand. The accuracy of the dispatching system, derived from the accuracy of demand forecasting and the forecasting algorithm used, will determines the economic of the power system operation as well as the stability of the whole society. This paper presents a combined ε-SVR model considering seasonal proportions based on development tendencies from history data. We use one-order moving averages to produce a comparatively smooth data series, taking the averaging period as the interval that can effectively eliminate the seasonal variation. We used the smoothed data series as the training set input for the ε-SVR model and obtained the corresponding forecasting value. Afterward, we accounted for the previously removed seasonal variation. As a case, we forecast northeast electricity demand of China using the new method. We demonstrated that this simple procedure has very satisfactory overall performance by an analysis of variance with relative verification and validation. Significant reductions in forecast errors were achieved.

  16. A trend fixed on firstly and seasonal adjustment model combined with the epsilon-SVR for short-term forecasting of electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Wang Jianzhou [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Zhu Wenjin, E-mail: crying.1@hotmail.co [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Zhang Wenyu [College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000 (China); Sun Donghuai [Key Laboratory of Western Chinas Environmental Systems (Ministry of Education) College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000 (China)

    2009-11-15

    Short-term electricity demand forecasting has always been an essential instrument in power system planning and operation by which an electric utility plans and dispatches loading so as to meet system demand. The accuracy of the dispatching system, derived from the accuracy of demand forecasting and the forecasting algorithm used, will determines the economic of the power system operation as well as the stability of the whole society. This paper presents a combined epsilon-SVR model considering seasonal proportions based on development tendencies from history data. We use one-order moving averages to produce a comparatively smooth data series, taking the averaging period as the interval that can effectively eliminate the seasonal variation. We used the smoothed data series as the training set input for the epsilon-SVR model and obtained the corresponding forecasting value. Afterward, we accounted for the previously removed seasonal variation. As a case, we forecast northeast electricity demand of China using the new method. We demonstrated that this simple procedure has very satisfactory overall performance by an analysis of variance with relative verification and validation. Significant reductions in forecast errors were achieved.

  17. A trend fixed on firstly and seasonal adjustment model combined with the {epsilon}-SVR for short-term forecasting of electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jianzhou; Zhu, Wenjin [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Zhang, Wenyu [College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000 (China); Sun, Donghuai [Key Laboratory of Western Chinas Environmental Systems (Ministry of Education) College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000 (China)

    2009-11-15

    Short-term electricity demand forecasting has always been an essential instrument in power system planning and operation by which an electric utility plans and dispatches loading so as to meet system demand. The accuracy of the dispatching system, derived from the accuracy of demand forecasting and the forecasting algorithm used, will determines the economic of the power system operation as well as the stability of the whole society. This paper presents a combined {epsilon}-SVR model considering seasonal proportions based on development tendencies from history data. We use one-order moving averages to produce a comparatively smooth data series, taking the averaging period as the interval that can effectively eliminate the seasonal variation. We used the smoothed data series as the training set input for the {epsilon}-SVR model and obtained the corresponding forecasting value. Afterward, we accounted for the previously removed seasonal variation. As a case, we forecast northeast electricity demand of China using the new method. We demonstrated that this simple procedure has very satisfactory overall performance by an analysis of variance with relative verification and validation. Significant reductions in forecast errors were achieved. (author)

  18. 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.

  19. 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

  20. 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.

  1. Tolerance in a rat cardiac allograft model after short-term treatment with LF 08-0299. Absence of clonal deletion and evidence of CD4+ suppressor cells.

    Science.gov (United States)

    Andoins, C; de Fornel, D; Annat, J; Dutartre, P

    1996-12-15

    LF 08-0299 is a new immunosuppressive compound. In a fully mismatched rat cardiac allograft model (Dark Agouti [DA]-->Lewis [LEW]), long-term unresponsiveness was observed after LF 08-0299 short-term treatment (20 days). Survival of additional cardiac and skin DA allografts, and rejection of third-party (Brown Norway [BN]) skin allografts demonstrated induction of a donor-specific tolerance state. The aim of this study was to investigate mechanisms of cardiac acceptance in this model. LEW rats with long-term surviving heart grafts (LTS LEW) were examined for their immune proliferative and cytotoxic responses toward donors (DA) and third-party (BN) antigens. Normal proliferative responses were observed and limiting dilution analysis did not reveal a reduction of T cytotoxic cell precursors. In our model, tolerance exists despite the presence of cells reactive with donor alloantigens. In vivo adoptive transfer of serum from LTS LEW failed to transfer unresponsiveness, indicating that serum factors do not seem to be involved in tolerance maintenance. Transfer of spleen cells, obtained from LTS LEW, showed specific prolongation of DA cardiac allografts in syngeneic hosts. Moreover, these cells were able to induce the rejection of third-party BN grafts. These results suggest that although LTS LEW possessed suppressor cells, they remained immunocompetent in recognizing and responding to third-party alloantigens. Purified CD4+ cells transferred unresponsiveness to secondary hosts, but CD8+ cells did not. Taken together, these results suggest that tolerance to donor alloantigens after treatment with LF 08-0299 in the rat cardiac allograft model is most likely due to induction of specific CD4+ suppressor cell activity, rather than induction of suppressive serum factor and selective elimination of antidonor helper or cytotoxic cell precursors (clonal deletion).

  2. Mechanisms controlling primary and new production in a global ecosystem model – Part II: The role of the upper ocean short-term periodic and episodic mixing events

    Directory of Open Access Journals (Sweden)

    E. E. Popova

    2006-01-01

    Full Text Available The use of 6 h, daily, weekly and monthly atmospheric forcing resulted in dramatically different predictions of plankton productivity in a global 3-D coupled physical-biogeochemical model. Resolving the diurnal cycle of atmospheric variability by use of 6 h forcing, and hence also diurnal variability in UML depth, produced the largest difference, reducing predicted global primary and new production by 25% and 10% respectively relative to that predicted with daily and weekly forcing. This decrease varied regionally, being a 30% reduction in equatorial areas primarily because of increased light limitation resulting from deepening of the mixed layer overnight as well as enhanced storm activity, and 25% at moderate and high latitudes primarily due to increased grazing pressure resulting from late winter stratification events. Mini-blooms of phytoplankton and zooplankton occur in the model during these events, leading to zooplankton populations being sufficiently well developed to suppress the progress of phytoplankton blooms. A 10% increase in primary production was predicted in the peripheries of the oligotrophic gyres due to increased storm-induced nutrient supply end enhanced winter production during the short term stratification events that are resolved in the run forced by 6 h meteorological fields. By resolving the diurnal cycle, model performance was significantly improved with respect to several common problems: underestimated primary production in the oligotrophic gyres; overestimated primary production in the Southern Ocean; overestimated magnitude of the spring bloom in the subarctic Pacific Ocean, and overestimated primary production in equatorial areas. The result of using 6 h forcing on predicted ecosystem dynamics was profound, the effects persisting far beyond the hourly timescale, and having major consequences for predicted global and new production on an annual basis.

  3. Measures of short-term memory: a historical review.

    Science.gov (United States)

    Richardson, John T E

    2007-07-01

    Following Ebbinghaus (1885/1964), a number of procedures have been devised to measure short-term memory using immediate serial recall: digit span, Knox's (1913) cube imitation test and Corsi's (1972) blocks task. Understanding the cognitive processes involved in these tasks was obstructed initially by the lack of a coherent concept of short-term memory and later by the mistaken assumption that short-term and long-term memory reflected distinct processes as well as different kinds of experimental task. Despite its apparent conceptual simplicity, a variety of cognitive mechanisms are responsible for short-term memory, and contemporary theories of working memory have helped to clarify these. Contrary to the earliest writings on the subject, measures of short-term memory do not provide a simple measure of mental capacity, but they do provide a way of understanding some of the key mechanisms underlying human cognition.

  4. Molecular Analysis of a Short-term Model of β-Glucans-Trained Immunity Highlights the Accessory Contribution of GM-CSF in Priming Mouse Macrophages Response

    Directory of Open Access Journals (Sweden)

    Sarah Walachowski

    2017-09-01

    Full Text Available β-Glucans (BGs are glucose polymers present in the fungal cell wall (CW and, as such, are recognized by innate immune cells as microbial-associated pattern through Dectin-1 receptor. Recent studies have highlighted the ability of the pathogenic yeast Candida albicans or its CW-derived β(1,3 (1,6-glucans to increase human monocytes cytokine secretion upon secondary stimulation, a phenomenon now referred as immune training. This ability of monocytes programming confers BGs an undeniable immunotherapeutic potential. Our objective was to determine whether BGs from Saccharomyces cerevisiae, a non-pathogenic yeast, are endowed with such a property. For this purpose, we have developed a short-term training model based on lipopolysaccharide re-stimulation of mouse bone marrow-derived macrophages primed with S. cerevisiae BGs. Through a transcriptome analysis, we demonstrated that BGs induced a specific gene expression signature involving the PI3K/AKT signaling pathway as in human monocytes. Moreover, we showed that over-expression of Csf2 (that encodes for GM-CSF was a Dectin-1-dependent feature of BG-induced priming of macrophages. Further experiments confirmed that GM-CSF up-regulated Dectin-1 cell surface expression and amplified macrophages response along BG-mediated training. However, the blockade of GM-CSFR demonstrated that GM-CSF was not primarily required for BG-induced training of macrophages although it can substantially improve it. In addition, we found that mouse macrophages trained with BGs upregulated their expression of the four and a half LIM-only protein 2 (Fhl2 in a Dectin-1-dependent manner. Consistently, we observed that intracellular levels of FHL2 increased after stimulation of macrophages with BGs. In conclusion, our experiments provide new insights on GM-CSF contribution to the training of cells from the monocytic lineage and highlights FHL2 as a possible regulator of BG-associated signaling.

  5. Health economic modelling to assess short-term costs of maternal overweight, gestational diabetes and related macrosomia – a pilot evaluation

    Directory of Open Access Journals (Sweden)

    Irene eLenoir-Wijnkoop

    2015-05-01

    Full Text Available Background: Despite the interest in the impact of overweight and obesity on public health, little is known about the social and economic impact of being born large for gestational age or macrosomic. Both conditions are related to maternal obesity and/or gestational diabetes (GDM and associated with increased morbidity for mother and child in the perinatal period. Poorly controlled diabetes during pregnancy, pre- pregnancy maternal obesity and/or excessive maternal weight gain during pregnancy are associated with intermittent periods of fetal exposure to hyperglycemia and subsequent hyperinsulinemia, leading to increased birth weight (e.g. macrosomia, body adiposity and glycogen storage in the liver. Macrosomia is associated with an increased risk of developing obesity and type 2 diabetes mellitus later in life.Objective: Provide insight in the short-term health-economic impact of maternal overweight, gestational diabetes (GDM and related macrosomia. To this end, a health economic framework was designed. This pilot study also aims to encourage further health technology assessments, based on country- and population-specific data. Results: The estimation of the direct health-economic burden of maternal overweight, GDM and related macrosomia indicates that associated healthcare expenditures are substantial. The calculation of a budget impact of GDM, based on a conservative approach of our model, using USA costing data, indicates an annual cost of more than $1,8 billion without taking into account long-term consequences.Conclusion: Although overweight and obesity are a recognized concern worldwide, less attention has been given to the health economic consequences of these conditions in women of child-bearing age and their offspring. The presented outcomes underline the need for preventive management strategies and public health interventions on life style, diet and physical activity. Also, the predisposition in people of Asian ethnicity to develop

  6. Corneal-protective effects of an artificial tear containing sodium hyaluronate and castor oil on a porcine short-term dry eye model.

    Science.gov (United States)

    Hasegawa, Takashi; Amako, Hideki; Yamamoto, Takeshi; Tazawa, Mariko; Sakamoto, Yuji

    2014-09-01

    The corneal-protective effects of an artificial tear containing sodium hyaluronate (SH) and castor oil (CO) were evaluated on a porcine short-term dry eye model. Fresh porcine eyes with an intact cornea were treated with an artificial tear of saline, SH solution (0.1%, 0.5% or 1%), CO solution (0.5%, 1% or 5%) or a mixture solution containing 0.5% SH and 1% CO and then desiccated for 60, 90 or 180 min. To assess corneal damage, the eyes were stained with methylene blue (MB) or lissamine green (LG). The staining score of MB, absorbance of MB extracted from the cornea and staining density of LG increased significantly with increasing desiccation time in untreated and all artificial tear-treated eyes, although there were no significant differences in staining scores and absorbance of MB between eyes treated continuously with saline and 1% SH-treated ones at 60 and 90 min of desiccation or the mixture-treated eyes at 60 min of desiccation. No significant differences in the staining density of LG were also found between continuous saline-treated eyes and ones desiccated for 60 min and treated with 1% SH and the mixture. Mild cytoplasmic vacuolations were histopathologically observed in the basal and wing cells in eyes desiccated for 60 min and treated with 1% SH and the mixture. The mixture solution containing 0.5% SH and 1% CO has protective effects against corneal desiccation similar to those of 1% SH and would be helpful as an artificial tear.

  7. 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.

  8. Enhancing global climate policy ambition towards a 1.5 °C stabilization: a short-term multi-model assessment

    Science.gov (United States)

    Vrontisi, Zoi; Luderer, Gunnar; Saveyn, Bert; Keramidas, Kimon; Alelui Reisa, Lara; Baumstark, Lavinia; Bertram, Christoph; Sytze de Boer, Harmen; Drouet, Laurent; Fragkiadakis, Kostas; Fricko, Oliver; Fujimori, Shinichiro; Guivarch, Celine; Kitous, Alban; Krey, Volker; Kriegler, Elmar; Broin, Eoin Ó.; Paroussos, Leonidas; van Vuuren, Detlef

    2018-04-01

    The Paris Agreement is a milestone in international climate policy as it establishes a global mitigation framework towards 2030 and sets the ground for a potential 1.5 °C climate stabilization. To provide useful insights for the 2018 UNFCCC Talanoa facilitative dialogue, we use eight state-of-the-art climate-energy-economy models to assess the effectiveness of the Intended Nationally Determined Contributions (INDCs) in meeting high probability 1.5 and 2 °C stabilization goals. We estimate that the implementation of conditional INDCs in 2030 leaves an emissions gap from least cost 2 °C and 1.5 °C pathways for year 2030 equal to 15.6 (9.0–20.3) and 24.6 (18.5–29.0) GtCO2eq respectively. The immediate transition to a more efficient and low-carbon energy system is key to achieving the Paris goals. The decarbonization of the power supply sector delivers half of total CO2 emission reductions in all scenarios, primarily through high penetration of renewables and energy efficiency improvements. In combination with an increased electrification of final energy demand, low-carbon power supply is the main short-term abatement option. We find that the global macroeconomic cost of mitigation efforts does not reduce the 2020–2030 annual GDP growth rates in any model more than 0.1 percentage points in the INDC or 0.3 and 0.5 in the 2 °C and 1.5 °C scenarios respectively even without accounting for potential co-benefits and avoided climate damages. Accordingly, the median GDP reductions across all models in 2030 are 0.4%, 1.2% and 3.3% of reference GDP for each respective scenario. Costs go up with increasing mitigation efforts but a fragmented action, as implied by the INDCs, results in higher costs per unit of abated emissions. On a regional level, the cost distribution is different across scenarios while fossil fuel exporters see the highest GDP reductions in all INDC, 2 °C and 1.5 °C scenarios.

  9. Short-term sleep deprivation stimulates hippocampal neurogenesis in rats following global cerebral ischemia/reperfusion.

    Directory of Open Access Journals (Sweden)

    Oumei Cheng

    Full Text Available Sleep deprivation (SD plays a complex role in central nervous system (CNS diseases. Recent studies indicate that short-term SD can affect the extent of ischemic damage. The aim of this study was to investigate whether short-term SD could stimulate hippocampal neurogenesis in a rat model of global cerebral ischemia/reperfusion (GCIR.One hundred Sprague-Dawley rats were randomly divided into Sham, GCIR and short-term SD groups based on different durations of SD; the short-term SD group was randomly divided into three subgroups: the GCIR+6hSD*3d-treated, GCIR+12hSD-treated and GCIR+12hSD*3d-treated groups. The GCIR rat model was induced via the bilateral occlusion of the common carotid arteries and hemorrhagic hypotension. The rats were sleep-deprived starting at 48 h following GCIR. A Morris water maze test was used to assess learning and memory ability; cell proliferation and differentiation were analyzed via 5-bromodeoxyuridine (BrdU and neuron-specific enolase (NSE, respectively, at 14 and 28 d; the expression of hippocampal BDNF was measured after 7 d.The different durations of short-term SD designed in our experiment exhibited improvement in cognitive function as well as increased hippocampal BDNF expression. Additionally, the short-term SD groups also showed an increased number of BrdU- and BrdU/NSE-positive cells compared with the GCIR group. Of the three short-term SD groups, the GCIR+12hSD*3d-treated group experienced the most substantial beneficial effects.Short-term SD, especially the GCIR+12hSD*3d-treated method, stimulates neurogenesis in the hippocampal dentate gyrus (DG of rats that undergo GCIR, and BDNF may be an underlying mechanism in this process.

  10. 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.

  11. Health economic modeling to assess short-term costs of maternal overweight, gestational diabetes, and related macrosomia – a pilot evaluation

    Science.gov (United States)

    Lenoir-Wijnkoop, Irene; van der Beek, Eline M.; Garssen, Johan; Nuijten, Mark J. C.; Uauy, Ricardo D.

    2015-01-01

    Background: Despite the interest in the impact of overweight and obesity on public health, little is known about the social and economic impact of being born large for gestational age or macrosomic. Both conditions are related to maternal obesity and/or gestational diabetes mellitus (GDM) and associated with increased morbidity for mother and child in the perinatal period. Poorly controlled diabetes during pregnancy, pre- pregnancy maternal obesity and/or excessive maternal weight gain during pregnancy are associated with intermittent periods of fetal exposure to hyperglycemia and subsequent hyperinsulinemia, leading to increased birth weight (e.g., macrosomia), body adiposity, and glycogen storage in the liver. Macrosomia is associated with an increased risk of developing obesity and type 2 diabetes mellitus later in life. Objective: Provide insight in the short-term health-economic impact of maternal overweight, GDM, and related macrosomia. To this end, a health economic framework was designed. This pilot study also aims to encourage further health technology assessments, based on country- and population-specific data. Results: The estimation of the direct health-economic burden of maternal overweight, GDM and related macrosomia indicates that associated healthcare expenditures are substantial. The calculation of a budget impact of GDM, based on a conservative approach of our model, using USA costing data, indicates an annual cost of more than $1,8 billion without taking into account long-term consequences. Conclusion: Although overweight and obesity are a recognized concern worldwide, less attention has been given to the health economic consequences of these conditions in women of child-bearing age and their offspring. The presented outcomes underline the need for preventive management strategies and public health interventions on life style, diet and physical activity. Also, the predisposition in people of Asian ethnicity to develop diabetes emphasizes the

  12. Short-term geomorphological evolution of proglacial systems

    Science.gov (United States)

    Carrivick, Jonathan L.; Heckmann, Tobias

    2017-06-01

    Proglacial systems are amongst the most rapidly changing landscapes on Earth, as glacier mass loss, permafrost degradation and more episodes of intense rainfall progress with climate change. This review addresses the urgent need to quantitatively define proglacial systems not only in terms of spatial extent but also in terms of functional processes. It firstly provides a critical appraisal of prevailing conceptual models of proglacial systems, and uses this to justify compiling data on rates of landform change in terms of planform, horizontal motion, elevation changes and sediment budgets. These data permit us to produce novel summary conceptual diagrams that consider proglacial landscape evolution in terms of a balance of longitudinal and lateral water and sediment fluxes. Throughout, we give examples of newly emerging datasets and data processing methods because these have the potential to assist with the issues of: (i) a lack of knowledge of proglacial systems within high-mountain, arctic and polar regions, (ii) considerable inter- and intra-catchment variability in the geomorphology and functioning of proglacial systems, (iii) problems with the magnitude of short-term geomorphological changes being at the threshold of detection, (iv) separating short-term variability from longer-term trends, and (v) of the representativeness of plot-scale field measurements for regionalisation and for upscaling. We consider that understanding of future climate change effects on proglacial systems requires holistic process-based modelling to explicitly consider feedbacks and linkages, especially between hillslope and valley-floor components. Such modelling must be informed by a new generation of repeated distributed topographic surveys to detect and quantify short-term geomorphological changes.

  13. 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.

  14. The nature of short-term consolidation in visual working memory.

    Science.gov (United States)

    Ricker, Timothy J; Hardman, Kyle O

    2017-11-01

    Short-term consolidation is the process by which stable working memory representations are created. This process is fundamental to cognition yet poorly understood. The present work examines short-term consolidation using a Bayesian hierarchical model of visual working memory recall to determine the underlying processes at work. Our results show that consolidation functions largely through changing the proportion of memory items successfully maintained until test. Although there was some evidence that consolidation affects representational precision, this change was modest and could not account for the bulk of the consolidation effect on memory performance. The time course of the consolidation function and selective influence of consolidation on specific serial positions strongly indicates that short-term consolidation induces an attentional blink. The blink leads to deficits in memory for the immediately following item when time pressure is introduced. Temporal distinctiveness accounts of the consolidation process are tested and ruled out. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  15. Micro package of short term wireless implantable microfabricated systems.

    Science.gov (United States)

    Bu, Leping; Cong, Peng; Kuo, Hung-I; Ye, Xuesong; Ko, Wen

    2009-01-01

    Package is a critical part in biomedical implantable systems. Many factors affecting the host body and the life time of implantable systems need to be considered. Package becomes more critical for microfabricated systems with wireless charging and communication. This paper presents the first phase study on micro package techniques for short term (30 to 90 days) implantable systems. A MEMS implantable telemetry model system was designed for packaging evaluation. The transmitter was custom designed and fabricated using MOSIS processes and an external receiver was designed and built for data collection. For short term implantable systems, medical grade silicone outer coating is used for "tissue compatibility"; while multilayer polymeric and nanometer-thin metal or ceramic films were used for inner coatings to provide mechanical strength and to block vapor and moisture penetration. The total coating thickness is less than 0.6 mm. The electrical performances (leakage resistance) of test board and model devices coated with various package materials and processes are evaluated in 40 degrees C saline. This paper presents: the model system; the evaluation methods and analysis of failure modes of polymeric coating on test boards; the solution to the failures and suggested coating techniques of polymeric materials; and the evaluation of model systems packaged with multi-layer coatings in 40 degrees C saline. The expected performance of developed packaging method was verified by experiments. Implantable wireless MEMS system can be packaged with thin multilayer materials to have an expected life time greater than 30 days.

  16. Short-Term Antiretroviral Treatment Recommendations Based on Sensitivity Analysis of a Mathematical Model for HIV Infection of CD₄⁺Τ Cells.

    Science.gov (United States)

    Croicu, Ana-Maria; Jarrett, Angela M; Cogan, N G; Hussaini, M Yousuff

    2017-11-01

    HIV infection is one of the most difficult infections to control and manage. The most recent recommendations to control this infection vary according to the guidelines used (US, European, WHO) and are not patient-specific. Unfortunately, no two individuals respond to infection and treatment quite the same way. The purpose of this paper is to make use of the uncertainty and sensitivity analysis to investigate possible short-term treatment options that are patient-specific. We are able to identify the most significant parameters that are responsible for ART outcome and to formulate some insights into the ART success.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. Cyclic injection, storage, and withdrawal of heated water in a sandstone aquifer at St. Paul, Minnesota--Analysis of thermal data and nonisothermal modeling of short-term test cycles

    Science.gov (United States)

    Miller, Robert T.; Delin, G.N.

    2002-01-01

    In May 1980, the University of Minnesota began a project to evaluate the feasibility of storing heated water (150 degrees Celsius) in the Franconia-Ironton Galesville aquifer (183 to 245 meters below land surface) and later recovering it for space heating. The University's steam-generation facilities supplied high-temperature water for injection. The Aquifer Thermal-Energy Storage system is a doublet-well design in which the injection-withdrawal wells are spaced approximately 250 meters apart. Water was pumped from one of the wells through a heat exchanger, where heat was added or removed. This water was then injected back into the aquifer through the other well. Four short-term test cycles were completed. Each cycle consisted of approximately equal durations of injection and withdrawal ranging from 5.25 to 8.01 days. Equal rates of injection and withdrawal, ranging from 17.4 to 18.6 liters per second, were maintained for each short-term test cycle. Average injection temperatures ranged from 88.5 to 117.9 degrees Celsius. Temperature graphs for selected depths at individual observation wells indicate that the Ironton and Galesville Sandstones received and stored more thermal energy than the upper part of the Franconia Formation. Clogging of the Ironton Sandstone was possibly due to precipitation of calcium carbonate or movement of fine-grain material or both. Vertical-profile plots indicate that the effects of buoyancy flow were small within the aquifer. A three-dimensional, anisotropic, nonisothermal, ground-water-flow, and thermal-energy-transport model was constructed to simulate the four short-term test cycles. The model was used to simulate the entire short-term testing period of approximately 400 days. The only model properties varied during model calibration were longitudinal and transverse thermal dispersivities, which, for final calibration, were simulated as 3.3 and 0.33 meters, respectively. The model was calibrated by comparing model-computed results to

  2. 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

  3. 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.

  4. Mixed methods evaluation of the impact of a short term training program on sterile processing knowledge, practice, and attitude in three hospitals in Benin

    Directory of Open Access Journals (Sweden)

    Olive Fast

    2018-02-01

    Full Text Available Abstract Background Proper sterile processing is fundamental to safe surgical practice and optimal patient outcomes. Sterile processing practices in low and middle-income countries often fall short of recommended standards. The impact of education and training on sterile processing practices in low and middle-income countries is unknown. We designed a sterile processing education course, including mentoring, and aimed to evaluate the impact on participants’ personal knowledge, skills, and practices. We also aimed to identify institutional changes in sterile processing practices at participants’ work places. Methods A mixed methods design study was conducted using a Hospital Sterile Processing Assessment Tool, knowledge tests, and open-ended interviews. Results Education and mentoring improved how workers understood and approached their work and to what they paid attention. Sterile processing workers were also better able to identify resources available to do their work and showed improved understanding of the impact of their work on patient safety. Conclusions Health care organizations seeking to improve surgical outcomes can find easy wins requiring minimal cost expenditures by paying attention to sterile processing practices. Investing in education and low-cost resources, such as cleaning detergents and brushes, must be part of any quality improvement initiative aimed at providing safe surgery in low and middle-income countries.

  5. Short-Term Planning of Hybrid Power System

    Science.gov (United States)

    Knežević, Goran; Baus, Zoran; Nikolovski, Srete

    2016-07-01

    In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.

  6. 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...

  7. Short-term dynamics of intertidal microphytobenthic biomass. Mathematical modelling [La dynamique a court terme de la biomasse du microphytobenthos intertidal. Formalisation mathematique

    Science.gov (United States)

    Guarini, J.-M.; Gros, P.; Blanchard, G.F.; Bacher, C.

    1999-01-01

    We formulate a deterministic mathematical model to describe the dynamics of the microphytobenthos of intertidal mudflats. It is 'minimal' because it only takes into account the essential processes governing the functioning of the system: the autotrophic production, the active upward and downward migrations of epipelic microalgae, the saturation of the mud surface by a biofilm of diatoms and the global net loss rates of biomass. According to the photic environment of the benthic diatoms inhabiting intertidal mudflats, and to their migration rhythm, the model is composed of two sub-systems of ordinary differential equations; they describe the simultaneous evolution of the biomass 'S' concentrated in the mud surface biofilm - the photic layer - and of the biomass 'F' diluted in the topmost centimetre of the mud - the aphotic layer. Qualitatively, the model solutions agree fairly well with the in situ observed dynamics of the S + F biomass. The study of the mathematical properties of the model, under some simplifying assumptions, shows the convergence of solutions to a stable cyclic equilibrium, whatever the frequencies of the physical synchronizers of the production. The sensitivity analysis reveals the necessity of a better knowledge of the processes of biomass losses, which so far are uncertain, and may further vary in space and time.

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Short-term energy outlook: Quarterly projections. Second quarter 1995

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-05-02

    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 projections 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 second quarter of 1995 through the fourth quarter of 1996. Values for the first quarter of 1995, 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, compiled into the second 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.

  15. 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

  16. Mercury simulations within GMOS: Analysis of short-term observational episodes

    Directory of Open Access Journals (Sweden)

    Travnikov O.

    2013-04-01

    Full Text Available A number of contemporary chemical transport models for mercury are applied within the framework of the EU GMOS project to study principal processes of mercury transport and transformations in the atmosphere. Each model is involved in simulation of short-term episodes corresponding to particular Hg measurement campaigns in Europe and other regions. In order to evaluate different physical and chemical mechanisms the models perform sensitivity runs with various parameterizations and/or combinations of considered processes. The modeling results are compared to detailed measurements of Hg species (Hg0/TGM, RGM, HgP with high temporal resolution (hours aiming at reproduction of short-term temporal variability of Hg air concentration.

  17. 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

  18. Short-term memory deficits correlate with hippocampal-thalamic functional connectivity alterations following acute sleep restriction.

    Science.gov (United States)

    Chengyang, Li; Daqing, Huang; Jianlin, Qi; Haisheng, Chang; Qingqing, Meng; Jin, Wang; Jiajia, Liu; Enmao, Ye; Yongcong, Shao; Xi, Zhang

    2017-08-01

    Acute sleep restriction heavily influences cognitive function, affecting executive processes such as attention, response inhibition, and memory. Previous neuroimaging studies have suggested a link between hippocampal activity and short-term memory function. However, the specific contribution of the hippocampus to the decline of short-term memory following sleep restriction has yet to be established. In the current study, we utilized resting-state functional magnetic resonance imaging (fMRI) to examine the association between hippocampal functional connectivity (FC) and the decline of short-term memory following total sleep deprivation (TSD). Twenty healthy adult males aged 20.9 ± 2.3 years (age range, 18-24 years) were enrolled in a within-subject crossover study. Short-term memory and FC were assessed using a Delay-matching short-term memory test and a resting-state fMRI scan before and after TSD. Seed-based correlation analysis was performed using fMRI data for the left and right hippocampus to identify differences in hippocampal FC following TSD. Subjects demonstrated reduced alertness and a decline in short-term memory performance following TSD. Moreover, fMRI analysis identified reduced hippocampal FC with the superior frontal gyrus (SFG), temporal regions, and supplementary motor area. In addition, an increase in FC between the hippocampus and bilateral thalamus was observed, the extent of which correlated with short-term memory performance following TSD. Our findings indicate that the disruption of hippocampal-cortical connectivity is linked to the decline in short-term memory observed after acute sleep restriction. Such results provide further evidence that support the cognitive impairment model of sleep deprivation.

  19. 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…

  20. Attentional priorities and access to short-term memory

    DEFF Research Database (Denmark)

    Gillebert, Celine; Dyrholm, Mads; Vangkilde, Signe Allerup

    2012-01-01

    The intraparietal sulcus (IPS) has been implicated in selective attention as well as visual short-term memory (VSTM). To contrast mechanisms of target selection, distracter filtering, and access to VSTM, we combined behavioral testing, computational modeling and functional magnetic resonance...

  1. Reformulating and Testing the Perfectionism Model of Binge Eating among Undergraduate Women: A Short-Term, Three-Wave Longitudinal Study

    Science.gov (United States)

    Mackinnon, Sean P.; Sherry, Simon B.; Graham, Aislin R.; Stewart, Sherry H.; Sherry, Dayna L.; Allen, Stephanie L.; Fitzpatrick, Skye; McGrath, Daniel S.

    2011-01-01

    The perfectionism model of binge eating (PMOBE) is an integrative model explaining why perfectionism is related to binge eating. This study reformulates and tests the PMOBE, with a focus on addressing limitations observed in the perfectionism and binge-eating literature. In the reformulated PMOBE, concern over mistakes is seen as a destructive…

  2. 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...

  3. 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.

  4. Report on the use of stability parameters and mesoscale modelling in short-term prediction[Wind speed at wind farm sites

    Energy Technology Data Exchange (ETDEWEB)

    Badger, J.; Giebel, G.; Guo Larsen, X.; Skov Nielsen, T.; Aalborg Nielsen, H.; Madsen, Henrik; Toefting, J.

    2007-06-15

    In this report investigations using atmospheric stability measures to improve wind speed predictions at wind farm sites are described. Various stability measures have been calculated based on numerical weather prediction model output. Their ability to improve the wind speed predictions is assessed at three locations. One of the locations is in complex terrain. Mesoscale modelling has been carried out using KAMM at this location. The characteristics of the measured winds are captured well by the mesoscale modelling. It can be seen that the atmospheric stability plays an important role in determining how the flow is influence by the terrain. A prediction system employing a look-up table approach based on wind class simulations is presented. The mesoscale modelling results produced by KAMM were validated using an alternative mesoscale model called WRF. A good agreement in the results of KAMM and WRF was found. It is shown that including a stability parameter in physical and/or statistical modelling can improve the wind speed predictions at a wind farm site. A concept for the inclusion of a stability measure in the WPPT prediction system is presented, and the testing of the concept is outlined. (au)

  5. Long-term manure carbon sequestration in soil simulated with the Daisy model on the basis of short-term incubation study

    DEFF Research Database (Denmark)

    Karki, Yubaraj Kumar; Børgesen, Christen Duus; Thomsen, Ingrid Kaag

    2013-01-01

    This study focused on simulating the long-term soil carbon sequestration after application of anaerobically digested and non-digested cattle manure using the Daisy model. The model was parameterized and calibrated for soil carbon (C) release during a 247 days incubation study including a coarse...... application of the two manures (70 kg organic manure N ha-1 plus 90 kg mineral N ha-1) and compared with a mineral N reference (120 kg N ha-1 yr-1). Carbon retention in soil was related to the initial C in non-digested manure, and after 52 years of repeated manure application extra C retention was equivalent...

  6. Short-term simvastatin treatment has no effect on plasma cytokine response in a human in vivo model of low-grade inflammation

    DEFF Research Database (Denmark)

    Erikstrup, C; Ullum, H; Pedersen, Bente Klarlund

    2006-01-01

    Statins reduce plasma cholesterol, but clinical trials and in vitro studies indicate that they might also possess anti-inflammatory properties. The effect of simvastatin on circulating cytokines and leucocytes was evaluated in a human in vivo model of low-grade inflammation. Thirty young healthy...

  7. Preservation of Long-Term Memory and Synaptic Plasticity Despite Short-Term Impairments in the Tc1 Mouse Model of Down Syndrome

    Science.gov (United States)

    Morice, Elise; Andreae, Laura C.; Cooke, Sam F.; Vanes, Lesley; Fisher, Elizabeth M. C.; Tybulewicz, Victor L. J.; Bliss, Timothy V. P.

    2008-01-01

    Down syndrome (DS) is a genetic disorder arising from the presence of a third copy of the human chromosome 21 (Hsa21). Recently, O'Doherty and colleagues in an earlier study generated a new genetic mouse model of DS (Tc1) that carries an almost complete Hsa21. Since DS is the most common genetic cause of mental retardation, we have undertaken a…

  8. Ocean Dredged Material Disposal Site (ODMDS) Authorization and Short-Term FATE (STFATE) Model Analysis: 2014-2015 Working Group Findings Report

    Science.gov (United States)

    2016-03-01

    Section 103 processes with the USEPA. STFATE enables the computation of the physical fate of dredged material disposed in open water and simulates the...concentrations, with greater reduction where current velocity is low. Discharge while traveling against or transverse to the current has similar impacts while...based on educated guess presented by Koh and Chang (1973), as are CFRIC and FRICTN. CDRAG and CFRIC are used to compute the form drag and skin

  9. 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 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.

  10. Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008–2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion

    Science.gov (United States)

    Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

    2016-01-01

    Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic

  11. Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

    Science.gov (United States)

    Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

    2016-01-01

    Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across

  12. Short-term forecasting of the chloride content in the mineral waters of the Ustroń Health Resort using SARIMA and Holt-Winters models

    Directory of Open Access Journals (Sweden)

    Dąbrowska Dominika

    2015-12-01

    Full Text Available The Ustroń S.A. Health Resort (southern Poland uses iodide-bromide mineral waters taken from Middle and Upper Devonian limestones and dolomites with a mineralisation range of 110-130 g/dm3 for curative purposes. Two boreholes - U-3 and U3-A drilled in the early 1970s were exploited. The aim of this paper is to estimate changes in mineral water quality of the Ustroń Health Resort by taking into consideration chloride content in the water from the U-3 borehole. The data has included the results of monthly analyses of chlorides from 2005 to 2015 during the tests carried out by the Mining Department of the Health Resort. The triple exponential smoothing (ETS function and the Seasonal Autoregressive Integrated Moving Average (SARIMA method of modelling time series were used for the calculations. The ability to properly forecast mineral water quality can result in a good status of the exploitation borehole and a limited number of failures in the exploitation system. Because of the good management of health resorts, it is possible to acquire more satisfied customers. The main goal of the article involves the real-time forecast accuracy, obtained results show that the proposed methods are effective for such situations. Presented methods made it possible to obtain a 24-month point and interval forecast. The results of these analyses indicate that the chloride content is forecast to be in the range of 72 to 83 g/l from 2015 to 2017. While comparing the two methods of analysis, a narrower range of forecast values and, therefore, greater accuracy were obtained for the ETS function. The good performance of the ETS model highlights its utility compared with complicated physically based numerical models.

  13. Short-term energy outlook, Quarterly projections. Third quarter 1993

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-08-04

    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.

  14. 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.

  15. 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

  16. 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

  17. A New Strategy for Short-Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Yi Yang

    2013-01-01

    Full Text Available Electricity is a special energy which is hard to store, so the electricity demand forecasting remains an important problem. Accurate short-term load forecasting (STLF plays a vital role in power systems because it is the essential part of power system planning and operation, and it is also fundamental in many applications. Considering that an individual forecasting model usually cannot work very well for STLF, a hybrid model based on the seasonal ARIMA model and BP neural network is presented in this paper to improve the forecasting accuracy. Firstly the seasonal ARIMA model is adopted to forecast the electric load demand day ahead; then, by using the residual load demand series obtained in this forecasting process as the original series, the follow-up residual series is forecasted by BP neural network; finally, by summing up the forecasted residual series and the forecasted load demand series got by seasonal ARIMA model, the final load demand forecasting series is obtained. Case studies show that the new strategy is quite useful to improve the accuracy of STLF.

  18. A teacher-consultation approach to social skills training for pre-kindergarten children: treatment model and short-term outcome effects.

    Science.gov (United States)

    Han, Susan S; Catron, Thomas; Weiss, Bahr; Marciel, Kristen K

    2005-12-01

    This study evaluated the post-treatment outcome effects of a classroom-based social skills program for pre-kindergarten children, using a teacher-consultation model. The pre-K RECAP (Reaching Educators, Children, and Parents) program is a semi-structured, cognitive-behavioral skills training program that provides teachers with in-classroom consultation on program implementation and classroom-wide behavior management. Data on children's social skills and behavior problems were collected from parents and teachers at pre- and post-treatment, for 149 children aged 4-5 years (of whom 56% were girls). Significant treatment effects were found for teacher but not parent reports, with treatment group children improving significantly more than comparison group children in their teacher-rated social skills and internalizing and externalizing problems. These results provide some preliminary support for the efficacy of the program on children's social skills and behavior problems, and for a teacher-consultation model for training teachers to implement school-based mental health programs.

  19. Short-term exposure to dim light at night disrupts rhythmic behaviors and causes neurodegeneration in fly models of tauopathy and Alzheimer's disease.

    Science.gov (United States)

    Kim, Mari; Subramanian, Manivannan; Cho, Yun-Ho; Kim, Gye-Hyeong; Lee, Eunil; Park, Joong-Jean

    2018-01-08

    The accumulation and aggregation of phosphorylated tau proteins in the brain are the hallmarks for the onset of Alzheimer's disease (AD). In addition, disruptions in circadian rhythms (CRs) with altered sleep-wake cycles, dysregulation of locomotion, and increased memory defects have been reported in patients with AD. Drosophila flies that have an overexpression of human tau protein in neurons exhibit most of the symptoms of human patients with AD, including locomotion defects and neurodegeneration. Using the fly model for tauopathy/AD, we investigated the effects of an exposure to dim light at night on AD symptoms. We used a light intensity of 10 lux, which is considered the lower limit of light pollution in many countries. After the tauopathy flies were exposed to the dim light at night for 3 days, the flies showed disrupted CRs, altered sleep-wake cycles due to increased pTau proteins and neurodegeneration, in the brains of the AD flies. The results indicate that the nighttime exposure of tauopathy/AD model Drosophila flies to dim light disrupted CR and sleep-wake behavior and promoted neurodegeneration. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Analysis of the short-term overproduction capability of variable speed wind turbines

    DEFF Research Database (Denmark)

    Hansen, Anca Daniela; Altin, Müfit; Margaris, Ioannis D.

    2014-01-01

    Emphasis in this article is on variable speed wind turbines (VSWTs) capability to provide short-term overproduction and better understanding of VSWTs’ mechanical and electrical limits to deliver such support. VSWTs’ short-term overproduction capability is of primary concern for the transmission...... system operators (TSOs) in the process of restoring critical situations during large frequency excursions in power systems with high wind power penetration. This study is conducted on a simplified generic model for VSWTs with full scale power converter (Type IV), which includes several adjustments...... and extensions of the Type IV standard wind turbine model proposed by the IEC Committee in IEC 61400-27-1. This modified standard model is able to account for dynamic features relevant for integrating active power ancillary services in wind power plants, such as frequency support capabilities. The performance...

  1. The Short-Term Effect of Ambient Temperature on Mortality in Wuhan, China: A Time-Series Study Using a Distributed Lag Non-Linear Model

    Directory of Open Access Journals (Sweden)

    Yunquan Zhang

    2016-07-01

    Full Text Available Less evidence concerning the association between ambient temperature and mortality is available in developing countries/regions, especially inland areas of China, and few previous studies have compared the predictive ability of different temperature indictors (minimum, mean, and maximum temperature on mortality. We assessed the effects of temperature on daily mortality from 2003 to 2010 in Jiang’an District of Wuhan, the largest city in central China. Quasi-Poisson generalized linear models combined with both non-threshold and double-threshold distributed lag non-linear models (DLNM were used to examine the associations between different temperature indictors and cause-specific mortality. We found a U-shaped relationship between temperature and mortality in Wuhan. Double-threshold DLNM with mean temperature performed best in predicting temperature-mortality relationship. Cold effect was delayed, whereas hot effect was acute, both of which lasted for several days. For cold effects over lag 0–21 days, a 1 °C decrease in mean temperature below the cold thresholds was associated with a 2.39% (95% CI: 1.71, 3.08 increase in non-accidental mortality, 3.65% (95% CI: 2.62, 4.69 increase in cardiovascular mortality, 3.87% (95% CI: 1.57, 6.22 increase in respiratory mortality, 3.13% (95% CI: 1.88, 4.38 increase in stroke mortality, and 21.57% (95% CI: 12.59, 31.26 increase in ischemic heart disease (IHD mortality. For hot effects over lag 0–7 days, a 1 °C increase in mean temperature above the hot thresholds was associated with a 25.18% (95% CI: 18.74, 31.96 increase in non-accidental mortality, 34.10% (95% CI: 25.63, 43.16 increase in cardiovascular mortality, 24.27% (95% CI: 7.55, 43.59 increase in respiratory mortality, 59.1% (95% CI: 41.81, 78.5 increase in stroke mortality, and 17.00% (95% CI: 7.91, 26.87 increase in IHD mortality. This study suggested that both low and high temperature were associated with increased mortality in Wuhan, and

  2. Short-term effect of zoledronic acid upon fracture resistance of the mandibular condyle and femoral head in an animal model

    Science.gov (United States)

    López-Jornet, Pía; Vicente-Hernández, Ascensión

    2013-01-01

    Objective: The aim of this study was to compare the effects in terms of resistance to fracture of the mandibular condyle and femoral head following different doses of zoledronic acid in an animal model. Study design: A total of 80 adult male Sprague-Dawley rats were included in a prospective randomized study. The animals were randomly divided into four groups of 20 rats each. Group 1 (control) received sterile saline solution, while groups 2, 3 and 4 received a accumulated dose of 0.2 mg, 0.4 mg and 0.6 mg of zoledronic acid, respectively. The animals were sacrificed 28 days after the last dose, and the right hemimandible and the right femur were removed. The fracture strength was measured (in Newtons) with a universal test machine using a 1 kN load connected to a metal rod with one end angled at 30 degrees. The cross-head speed was 1 mm/min. Later, the specimens were observed under a scanning electron microscope with backscattered electron imaging (SEM-BSE). At last, chemical analysis and elemental mapping of the mineral bone composition were generated using a microanalytical system based on energy-dispersive and X-ray spectrometry (EDX). Results: A total of 160 fracture tests were performed. The fracture resistance increased in mandible and femur with a higher accumulated dose of zoledronic acid. Statistically significant differences were recorded versus the controls with all the studies groups. The chemical analysis in mandible showed a significantly increased of calcium and phosphorous to compare the control with all of the study groups; however, in femur no statistically significant differences between the four study groups were observed. Conclusions: The administration of bisphosphonates increases the fracture resistance in mandible and femur. Key words:Zoledronic acid, bisphosphonates, animal experimentation, fracture test. PMID:23524420

  3. Can climate sensitivity be estimated from short-term relationships of top-of-atmosphere net radiation and surface temperature?

    International Nuclear Information System (INIS)

    Lin Bing; Min Qilong; Sun Wenbo; Hu Yongxiang; Fan, Tai-Fang

    2011-01-01

    Increasing the knowledge in climate radiative feedbacks is critical for current climate studies. This work focuses on short-term relationships between global mean surface temperature and top-of-atmosphere (TOA) net radiation. The relationships may be used to characterize the climate feedback as suggested by some recent studies. As those recent studies, an energy balance model with ocean mixed layer and both radiative and non-radiative heat sources is used here. The significant improvement of current model is that climate system memories are considered. Based on model simulations, short-term relationship between global mean surface temperature and TOA net radiation (or the linear striation feature as suggested by previous studies) might represent climate feedbacks when the system had no memories. However, climate systems with the same short-term feedbacks but different memories would have a similar linear striation feature. This linear striation feature reflects only fast components of climate feedbacks and may not represent the total climate feedback even when the memory length of climate systems is minimal. The potential errors in the use of short-term relationships in estimations of climate sensitivity could be big. In short time scales, fast climate processes may overwhelm long-term climate feedbacks. Thus, the climate radiative feedback parameter obtained from short-term data may not provide a reliable estimate of climate sensitivity. This result also suggests that long-term observations of global surface temperature and TOA radiation are critical in the understanding of climate feedbacks and sensitivities.

  4. 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.

  5. 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.

  6. Short Term Airing by Natural Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per; Perino, M.

    2010-01-01

    principles is necessary. The present study analyses and presents the results of an experimental evaluation of airing performance in terms of ventilation characteristics, IAQ and thermal comfort. It includes investigations of the consequences of opening time, opening frequency, opening area and expected...... 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...... and can provide both acceptable IAQ and thermal comfort conditions in buildings....

  7. 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...... to read, we found an increase in VSTM capacity for letters while the capacity for line drawings (Snodgrass & Vanderwart, 1980) remained unchanged. 2) In further investigations, we found that Japanese readers had a larger VSTM capacity for Japanese Kanji symbols than non-Japanese readers while the capacity...

  8. Comparison of costs and outcomes of dapagliflozin with other glucose-lowering therapy classes added to metformin using a short-term cost-effectiveness model in the US setting.

    Science.gov (United States)

    Chakravarty, Abhiroop; Rastogi, Mohini; Dhankhar, Praveen; Bell, Kelly F

    2018-05-01

    To compare 1-year costs and benefits of dapagliflozin (DAPA), a sodium-glucose cotransporter-2 (SGLT-2) inhibitor, with those of other treatments for type 2 diabetes (T2D), such as glucagon-like peptide-1 receptor agonists (GLP-1RAs), sulfonylureas (SUs), thiazolidinediones (TZDs), and dipeptidyl peptidase-4 inhibitors (DPP-4i), all combined with metformin. A short-term decision-analytic model with a 1-year time horizon was developed from a payer's perspective in the United States setting. Costs and benefits associated with four clinical end-points (glycated hemoglobin [A1C], body weight, systolic blood pressure [SBP], and risk of hypoglycemia) were evaluated in the analysis. The impact of DAPA and other glucose-lowering therapy classes on these clinical end-points was estimated from a network meta-analysis (NMA). Data for costs and quality-adjusted life-years (QALYs) associated with a per-unit change in these clinical end-points were taken from published literature. Drug prices were taken from an annual wholesale price list. All costs were inflation-adjusted to December 2016 costs using the medical care component of the consumer price index. Total costs (both medical and drug costs), total QALYs, and incremental cost-effectiveness ratios (ICERs) were estimated. Sensitivity analyses (SA) were performed to explore uncertainty in the inputs. To assess face validity, results from the short-term model were compared with long-term models published for these drugs. The total annual medical cost for DAPA was less than that for GLP-1RA ($186 less), DPP-4i ($1,142 less), SU ($2,474 less), and TZD ($1,640 less). Treatment with DAPA resulted in an average QALY gain of 0.0107, 0.0587, 0.1137, and 0.0715 per treated patient when compared with GLP-1RA, DPP-4i, SU, and TZD, respectively. ICERs for DAPA vs SU and TZD were $19,005 and $25,835, respectively. DAPA was a cost-saving option when compared with GLP-1RAs and DPP-4is. Among all four clinical end-points, change in weight

  9. 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.

  10. Predictors of outcome after short-term stabilization with buprenorphine.

    Science.gov (United States)

    Hillhouse, Maureen; Canamar, Catherine P; Ling, Walter

    2013-03-01

    Using buprenorphine as a medication to treat opioid dependence is becoming more prevalent as illicit opiate use increases. Identifying the characteristics of opiate dependent individuals best suited to benefit from buprenorphine would improve guidelines for its administration. This study evaluates baseline and treatment participation variables for predicting positive response to short-term stabilization with buprenorphine. Data include demographic, drug use, and other variables collected from participants undergoing stabilization over a 4-week period before being tapered off buprenorphine in a short-term detoxification process. Outcome variables include opioid use and retention. Logistic regression results indicate several characteristics associated with opioid use at the end of the stabilization period. These include being older, having no criminal history, and less opiate use. Criminal activity and opioid use in the last 30 days were significantly associated with shorter treatment stays. The benefits of identifying individual characteristics that may predict treatment response are discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. 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.

  12. 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

  13. Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

    Science.gov (United States)

    Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

    2018-03-01

    Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

  14. Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

    Directory of Open Access Journals (Sweden)

    C. Beer

    2018-03-01

    Full Text Available Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i when taking into account future changes in short-term variability of meteorological variables and (ii when representing dynamic snow and lichen and bryophyte functions in land surface models.

  15. The Role of Short Term Synaptic Plasticity in Temporal Coding of Neuronal Networks

    Science.gov (United States)

    Chandrasekaran, Lakshmi

    2008-01-01

    Short term synaptic plasticity is a phenomenon which is commonly found in the central nervous system. It could contribute to functions of signal processing namely, temporal integration and coincidence detection by modulating the input synaptic strength. This dissertation has two parts. First, we study the effects of short term synaptic plasticity…

  16. 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…

  17. Short-term energy outlook: Quarterly projections, fourth quarter 1997

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-10-14

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections for printed publication in January, April, July, and October in the Short-Term Energy Outlook. The details of these projections, as well as monthly updates on or about the 6th of each interim month, are available on the internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. The forecast period for this issue of the Outlook extends from the fourth quarter of 1997 through the fourth quarter of 1998. Values for the fourth quarter of 1997, 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 fourth quarter 1997 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. 19 tabs.

  18. 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.

  19. Audiovisual integration facilitates monkeys' short-term memory.

    Science.gov (United States)

    Bigelow, James; Poremba, Amy

    2016-07-01

    Many human behaviors are known to benefit from audiovisual integration, including language and communication, recognizing individuals, social decision making, and memory. Exceptionally little is known about the contributions of audiovisual integration to behavior in other primates. The current experiment investigated whether short-term memory in nonhuman primates is facilitated by the audiovisual presentation format. Three macaque monkeys that had previously learned an auditory delayed matching-to-sample (DMS) task were trained to perform a similar visual task, after which they were tested with a concurrent audiovisual DMS task with equal proportions of auditory, visual, and audiovisual trials. Parallel to outcomes in human studies, accuracy was higher and response times were faster on audiovisual trials than either unisensory trial type. Unexpectedly, two subjects exhibited superior unimodal performance on auditory trials, a finding that contrasts with previous studies, but likely reflects their training history. Our results provide the first demonstration of a bimodal memory advantage in nonhuman primates, lending further validation to their use as a model for understanding audiovisual integration and memory processing in humans.

  20. 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.

  1. 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.

  2. 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

  3. [Short-term relationships between urban atmospheric pollution and respiratory mortality: time series studies].

    Science.gov (United States)

    Filleul, L; Zeghnoun, A; Declercq, C; Le Goaster, C; Le Tertre, A; Eilstein, D; Medina, S; Saviuc, P; Prouvost, H; Cassadou, S; Pascal, L; Quénel, P

    2001-09-01

    Time series studies conducted in the field of air pollution aim at testing and quantifying short-term relations which can exist between daily air pollution levels and daily health effects. The method used for this type of survey has sometimes been misunderstood mainly because individual factors and indoor exposure to air pollutants were not taken into account. The adjustment on these individual confounding factors commonly used in classic epidemiologic studies (case-control studies, cohort studies) is not adequate to times series studies which are based on aggregate data. This is different for those factors that change over time according to the levels of air pollution (meteorological conditions, influenza epidemics, trend of health cases) which, when being analysed, must be taken into account either indirectly through time modelling or directly through non-linear modelling processes. During this last decade, numerous studies using the time series method have been published and have found short-term associations between daily levels of air pollution commonly observed and daily respiratory mortality. The consistency of the numerous results published in the international literature are more arguments in favour of non-confounding short-term relations between air pollution and respiratory mortality.

  4. 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.

  5. 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...... and Cavanagh (2004) have raised the question that the capacity of VSTM is dependent on visual complexity rather than the number of objects. We hypothesise that VSTM capacity is dependent on both the objective and subjective complexity of visual stimuli. Contrary to Alvarez and Cavanagh, who argue for the role...... of objective complexity, it seems that subjective complexity - which is dependent on the familiarity of the stimulus - plays a more important role than the objective visual complexity of the objects stored. In two studies, we explored how familiarity influences the capacity of VSTM. 1) In children learning...

  6. SHORT-TERM FORECASTING OF MORTGAGE LENDING

    Directory of Open Access Journals (Sweden)

    Irina V. Orlova

    2013-01-01

    Full Text Available The article considers the methodological and algorithmic problems arising in modeling and forecasting of time series of mortgage loans. Focuses on the processes of formation of the levels of time series of mortgage loans and the problem of choice and identification of models in the conditions of small samples. For forecasting options are selected and implemented a model of autoregressive and moving average, which allowed to obtain reliable forecasts.

  7. A Short Term Seismic Hazard Assessment in Christchurch, New Zealand, After the M 7.1, 4 September 2010 Darfield Earthquake: An Application of a Smoothing Kernel and Rate-and-State Friction Model

    Directory of Open Access Journals (Sweden)

    Chung-Han Chan

    2012-01-01

    Full Text Available The Mw 6.3, 21 February 2011 Christchurch, New Zealand, earthquake is regarded as an aftershock of the M 7.1, 4 September 2010 Darfield earthquake. However, it caused severe damage in the downtown Christchurch. Such a circumstance points out the importance of an aftershock sequence in seismic hazard evaluation and suggests the re-evaluation of a seismic hazard immediately after a large earthquake occurrence. For this purpose, we propose a probabilistic seismic hazard assessment (PSHA, which takes the disturbance of a short-term seismicity rate into account and can be easily applied in comparison with the classical PSHA. In our approach, the treatment of the background seismicity rate is the same as in the zoneless approach, which considers a bandwidth function as a smoothing Kernel in neighboring region of earthquakes. The rate-and-state friction model imparted by the Coulomb stress change of large earthquakes is used to calculate the fault-interaction-based disturbance in seismicity rate for PSHA. We apply this approach to evaluate the seismic hazard in Christchurch after the occurrence of the M 7.1, 4 September 2010 Darfield earthquake. Results show an increase of seismic hazards due to the stress increase in the region around the rupture plane, which extended to Christchurch. This provides a suitable basis for the application of a time-dependent PSHA using updating earthquake information.

  8. Representation of Instantaneous and Short-term Loudness in the Human Cortex

    Directory of Open Access Journals (Sweden)

    Andrew eThwaites

    2016-04-01

    Full Text Available Acoustic signals pass through numerous transforms in the auditory system before perceptual attributes such as loudness and pitch are derived. However, relatively little is known as to exactly when these transformations happen, and where, cortically or sub-cortically, they occur. In an effort to examine this, we investigated the latencies and locations of cortical entrainment to two transforms predicted by a model of loudness perception for time-varying sounds: the transforms were instantaneous loudness and short-term loudness, where the latter is hypothesized to be derived from the former and therefore should occur later in time. Entrainment of cortical activity was estimated by electro- and magneto-encephalographic (EMEG activity, recorded while healthy subjects listened to continuous speech. There was entrainment to instantaneous loudness bilaterally at 45 ms, 100 ms and 165 ms, in Heschl’s gyrus, dorsal lateral sulcus and Heschl’s gyrus respectively. Entrainment to short-term loudness was found in both the dorsal lateral sulcus and superior temporal sulcus at 275 ms. These results suggest that short-term loudness is derived from instantaneous loudness, and that this derivation occurs after processing in sub-cortical structures.

  9. Psychomotor Ability and Short-term Memory, and Reading and Mathematics Achievement in Children.

    Science.gov (United States)

    Murrihy, Cherée; Bailey, Maria; Roodenburg, John

    2017-08-01

    The aim of our study was to examine whether the findings from previous research, indicating the role of short-term memory as a mediator of the relationship between motor coordination and academic achievement in adolescents, is also evident in a younger child population. The study utilized a quantative cross-sectional design involving 133 children aged 8-12. The McCarron Assessment of Neuromuscular Development (MAND) provided four indicators of psychomotor ability (Finger Nose, Walking, Balancing, and Jumping). The Woodcock-Johnson Cognitive battery and the Automated Working Memory Assessment (AWMA) provided two measures of short-term memory (Numbers Reversed and Digit Recall) and the WJIII Achievement battery provided two measures of reading achievement (Letter-word Identification and Passage Comprehension) and two measures of mathematics achievement (Applied Problems and Calculation). Structural equation modeling was used, controlling for age, processing speed, crystallized, and fluid intelligence where appropriate. The results found support for the hypothesis that short-term memory fully mediates the relationship between psychomotor ability and reading and mathematics achievement. These findings indicate the significant affect of psychomotor ability on learning outcomes and consequently the need to assess these in considering learning difficulties, and as such these findings also advance understanding of developmental neural mechanisms underpinning the relationships. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  10. Short-term prediction towards the 21st century

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Joensen, Alfred K.; Madsen, Henrik

    2000-01-01

    A new chapter in the continued and exiting story of short-term prediction has begun! The paper will describe a new project funded by the Dnaisn Ministry of Energy where all the Danish utilities (Elkraft, ELsam, Eltra, and SEAS) will participate. The goal of the project is to develop and implement...... on-line a model combining the RISO and IMM models. This will ensure that the best forecasts are giveen on all prediction horizons form the very short range (o-9 hours) to the very long range (36-48 hours)....

  11. 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.

  12. Estimating short-term synaptic plasticity from pre- and postsynaptic spiking

    Science.gov (United States)

    Malyshev, Aleksey; Stevenson, Ian H.

    2017-01-01

    Short-term synaptic plasticity (STP) critically affects the processing of information in neuronal circuits by reversibly changing the effective strength of connections between neurons on time scales from milliseconds to a few seconds. STP is traditionally studied using intracellular recordings of postsynaptic potentials or currents evoked by presynaptic spikes. However, STP also affects the statistics of postsynaptic spikes. Here we present two model-based approaches for estimating synaptic weights and short-term plasticity from pre- and postsynaptic spike observations alone. We extend a generalized linear model (GLM) that predicts postsynaptic spiking as a function of the observed pre- and postsynaptic spikes and allow the connection strength (coupling term in the GLM) to vary as a function of time based on the history of presynaptic spikes. Our first model assumes that STP follows a Tsodyks-Markram description of vesicle depletion and recovery. In a second model, we introduce a functional description of STP where we estimate the coupling term as a biophysically unrestrained function of the presynaptic inter-spike intervals. To validate the models, we test the accuracy of STP estimation using the spiking of pre- and postsynaptic neurons with known synaptic dynamics. We first test our models using the responses of layer 2/3 pyramidal neurons to simulated presynaptic input with different types of STP, and then use simulated spike trains to examine the effects of spike-frequency adaptation, stochastic vesicle release, spike sorting errors, and common input. We find that, using only spike observations, both model-based methods can accurately reconstruct the time-varying synaptic weights of presynaptic inputs for different types of STP. Our models also capture the differences in postsynaptic spike responses to presynaptic spikes following short vs long inter-spike intervals, similar to results reported for thalamocortical connections. These models may thus be useful

  13. 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…

  14. Short-term variations in seismic hazard

    Science.gov (United States)

    Whiteside, Lowell Stanley

    1999-11-01

    Accurate forecasting of short term seismic hazard has not progressed as rapidly as forecasting of other natural hazards such as severe weather, solar storms, tsunamis and volcanic eruptions. Part of the reason for this is that until recently, little useful statistical work has been done on triggering causes of earthquakes beyond studies on the gradual accumulation of strain through plate tectonic motions. The Landers earthquake in southern California on June 28, 1992, which apparently triggered seismicity throughout one million square kilometers of the western United States, provided incentive into further studies relating to the triggering of earthquakes by external causes. In this thesis 29 possible external triggering agents are examined in relation to variations in seismicity in 67 regional and local seismicity catalogs. The 29 agents of triggering are classified into four groups: those which cause vertical strains, horizontal strains, and instantaneous and delayed agents related to the earth's space environment. For each regional catalog a set of time-dependent coefficients of triggering is calculated from the previous history of earthquakes and suspected triggering agents. This pre-history distribution function can be used to forecast the likelihood of changes in regional seismicity given the occurrence of specific triggering agents in the future. By examining daily periodicities of earthquakes in 20 local catalogs from 1934 through 1999, it is found that external triggering agents have an effect on intensity of free-earth oscillations, varying their amplitude depending on the nature of the agent. Finally, we apply the results of this study to the Mammoth Lakes region of east-central California in an earthquake forecasting experiment. Expected daily numbers of microearthquakes based on triggering have been sent in a weekly forecast during the period November 1997 to May 1999 to a group of five geophysicists. The results (7 correct forecasts of major changes

  15. 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...

  16. 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 ...

  17. Degeneracy in the regulation of short-term plasticity and synaptic filtering by presynaptic mechanisms.

    Science.gov (United States)

    Mukunda, Chinmayee L; Narayanan, Rishikesh

    2017-04-15

    We develop a new biophysically rooted, physiologically constrained conductance-based synaptic model to mechanistically account for short-term facilitation and depression, respectively through residual calcium and transmitter depletion kinetics. We address the specific question of how presynaptic components (including voltage-gated ion channels, pumps, buffers and release-handling mechanisms) and interactions among them define synaptic filtering and short-term plasticity profiles. Employing global sensitivity analyses (GSAs), we show that near-identical synaptic filters and short-term plasticity profiles could emerge from disparate presynaptic parametric combinations with weak pairwise correlations. Using virtual knockout models, a technique to address the question of channel-specific contributions within the GSA framework, we unveil the differential and variable impact of each ion channel on synaptic physiology. Our conclusions strengthen the argument that parametric and interactional complexity in biological systems should not be viewed from the limited curse-of-dimensionality standpoint, but from the evolutionarily advantageous perspective of providing functional robustness through degeneracy. Information processing in neurons is known to emerge as a gestalt of pre- and post-synaptic filtering. However, the impact of presynaptic mechanisms on synaptic filters has not been quantitatively assessed. Here, we developed a biophysically rooted, conductance-based model synapse that was endowed with six different voltage-gated ion channels, calcium pumps, calcium buffer and neurotransmitter-replenishment mechanisms in the presynaptic terminal. We tuned our model to match the short-term plasticity profile and band-pass structure of Schaffer collateral synapses, and performed sensitivity analyses to demonstrate that presynaptic voltage-gated ion channels regulated synaptic filters through changes in excitability and associated calcium influx. These sensitivity analyses

  18. Short-term and long-term variability of standard deviation scores for size in children.

    Science.gov (United States)

    Sheehy, A; Gasser, T; Largo, R; Molinari, L

    2002-01-01

    To quantify long-term and short-term variability in the standard deviation scores (SDS's) for six skeletal size variables and body mass index (BMI) in children and to compare average values of these quantities for boys with those of girls and to make comparisons across variables. The analysis is based on measurements made regularly for 120 boys and 112 girls from 1 month until 20 years for seven variables (standing height, sitting height, leg height, arm length, biiliac width, bihumeral width and BMI) as part of the first Zurich longitudinal growth study. Variation in these scores due to variablity in the timing of the pubertal spurt (PS) is separated out by rescaling the age axis on an individual basis and comparing children with the same developmental age rather than the same chronological age. For a given child, the relationship between the value of its SDS and age is modelled as the sum of an arbitrary (child dependent) smooth function plus an error term. The long-term variability for that child is defined to be the mean square of the departures of this smooth function from its mean level while the short-term variability is defined to be the variance of the error term. Girls' SDS scores have significantly more long-term variability than those of boys, while there is no significant difference between the sexes for short-term variability. Bihumeral width, BMI and sitting height have significantly more long-term variation than the other variables. Bihumeral width and BMI have the largest short-term variability and standing height has the smallest. Correlations between long-term variability and adult size and timing and intensity of the PS were small. A useful way of assessing long-term and short-term variability of SDS's, which is widely applicable has been described and applied to data relating to the growth of children. The results of this analysis are intriguing. Why is the underlying growth process of girls more variable than that of boys? Differences across

  19. Atmospheric corrosion of carbon steel resulting from short term exposures

    International Nuclear Information System (INIS)

    Balasubramanian, R.; Cook, D.C.; Perez, T.; Reyes, J.

    1998-01-01

    The study of corrosion products from short term atmospheric exposures of carbon steel, is very important to understand the processes that lead to corrosion of steels, and ultimately improve the performance of such steel in highly corrosive environments. Many regions along the Gulf of Mexico have extremely corrosive environments due to high mean annual temperature, humidity, time-of-wetness and every high atmospheric pollutants. The process the formation of corrosion products resulting from short term exposure of carbon steel, both as a function of environmental conditions and exposure time, has been investigated. Two sets of coupons were exposed at marine and marine locations, in Campeche, Mexico. Each set was exposed between 1 and 12 months to study the corrosion as a function of time. During the exposure periods, the relative humidity, rainfall, mean temperature, wind speed and wind direction were monitored along with the chloride and sulfur dioxide concentrations in the air. The corroded coupons were analyzed by Moessbauer, Raman, Infrared spectroscopies and X-ray diffraction in order to completely identify the oxides and map their location in the corrosion coating. Scattering and transmission Moessbauer analysis showed some layering of the oxides with lepidocrocite and akaganeite closer to the surface. The fraction of akaganeite phase increased at sites with higher chloride concentrations. A detailed analysis on the development of the oxide phases as a function of exposure time and environmental conditions will be presented. (Author)

  20. Robust Short-Term Memory without Synaptic Learning

    Science.gov (United States)

    Johnson, Samuel; Marro, J.; Torres, Joaquín 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 information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings. PMID:23349664

  1. A method for short term electricity spot price forecasting

    International Nuclear Information System (INIS)

    Koreneff, G.; Seppaelae, A.; Lehtonen, M.; Kekkonen, V.; Laitinen, E.; Haekli, J.; Antila, E.

    1998-01-01

    In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

  2. A method for short term electricity spot price forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Koreneff, G.; Seppaelae, A.; Lehtonen, M.; Kekkonen, V. [VTT Energy, Espoo (Finland); Laitinen, E.; Haekli, J. [Vaasa Univ. (Finland); Antila, E. [ABB Transmit Oy (Finland)

    1998-08-01

    In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

  3. Effective Short-term Forecasting of Wind Farms Power

    Directory of Open Access Journals (Sweden)

    Elżbieta Bogalecka

    2015-09-01

    Full Text Available Forecasting a specific wind farm’s (WF generation capacity within a 24 hour perspective requires both a reliable forecast of wind, as well as supporting tools. This tool is a dedicated model of wind farm power. This model should include not only general rules of wind to mechanical energy conversion, but also the farm’s specific features. There are many factors that influence a farm’s generation capacity, and any forecast of it, even with an accurate weather forecast, carries error. This paper presents analytical, statistical, and neuron models of wind farm power. The study is based on data from a real wind farm. Most attention is paid to the neuron models, due to a neuron network’s capability to restore farm-specific details. The research aims to answer the headline question: whether and to what extent a wind farm’s power can be forecast short-term?

  4. Temporal grouping effects in musical short-term memory.

    Science.gov (United States)

    Gorin, Simon; Mengal, Pierre; Majerus, Steve

    2017-12-11

    Recent theoretical accounts of verbal and visuo-spatial short-term memory (STM) have proposed the existence of domain-general mechanisms for the maintenance of serial order information. These accounts are based on the observation of similar behavioural effects across several modalities, such as temporal grouping effects. Across two experiments, the present study aimed at extending these findings, by exploring a STM modality that has received little interest so far, STM for musical information. Given its inherent rhythmic, temporal and serial organisation, the musical domain is of interest for investigating serial order STM processes such as temporal grouping. In Experiment 1, the data did not allow to determine the presence or the absence of temporal grouping effects. In Experiment 2, we observed that temporal grouping of tone sequences during encoding improves short-term recognition for serially presented probe tones. Furthermore, the serial position curves included micro-primacy and micro-recency effects, which are the hallmark characteristic of temporal grouping. Our results suggest that the encoding of serial order information in musical STM may be supported by temporal positional coding mechanisms similar to those reported in the verbal domain.

  5. Visual short-term memory and aging in chess players.

    Science.gov (United States)

    Charness, N

    1981-09-01

    Young (M = 20 years) and older (M = 54 years) equally skilled chessplayers reconstructed slides of chess diagrams shown for 1, 2, and 4 sec either immediately or following 15 sec of interpolated processing. Recall was more accurate for younger players, with the gap widening as viewing time increased. Interpolated processing decreased accuracy and increased retrieval time equally in the two groups. Measures of chunking indicated no age-related differences. These results imply that there is an age-related deficit in encoding but not retrieval for visual short-term memory. Since young and old were affected equivalently by interpolated processing, it appears likely that they have similar memory consolidation functions. Since the players were equally skilled, the results contradict the view that skill in chess derives primarily from encoding ability.

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

    Science.gov (United States)

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

    2008-05-01

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

  7. Short term exposure to cooking fumes and pulmonary function

    Directory of Open Access Journals (Sweden)

    Qvenild Torgunn

    2009-05-01

    Full Text Available Abstract Background Exposure to cooking fumes may have different deleterious effects on the respiratory system. The aim of this study was to look at possible effects from inhalation of cooking fumes on pulmonary function. Methods Two groups of 12 healthy volunteers (A and B stayed in a model kitchen for two and four hours respectively, and were monitored with spirometry four times during twenty four hours, on one occasion without any exposure, and on another with exposure to controlled levels of cooking fumes. Results The change in spirometric values during the day with exposure to cooking fumes, were not statistically significantly different from the changes during the day without exposure, with the exception of forced expiratory time (FET. The change in FET from entering the kitchen until six hours later, was significantly prolonged between the exposed and the unexposed day with a 15.7% increase on the exposed day, compared to a 3.2% decrease during the unexposed day (p-value = 0.03. The same tendency could be seen for FET measurements done immediately after the exposure and on the next morning, but this was not statistically significant. Conclusion In our experimental setting, there seems to be minor short term spirometric effects, mainly affecting FET, from short term exposure to cooking fumes.

  8. Short-term facilitation may stabilize parametric working memory trace

    Directory of Open Access Journals (Sweden)

    Vladimir eItskov

    2011-10-01

    Full Text Available Networks with continuous set of attractors are considered to be a paradigmatic model for parametric working memory, but require fine-tuning of connections and are thus structurally unstable. Here we analyzed the network with ring attractor, where connections are not perfectly tuned and the activity state therefore drifts in the absence of the stabilizing stimulus. We derive an analytical expression for the drift dynamics and conclude that the network cannot function as working memory for a period of several seconds, a typical delay time in monkey memory experiments. We propose that short-term synaptic facilitation in recurrent connections significantly improves the robustness of the model by slowing down the drift of activity bump. Extending the calculation of the drift velocity to network with synaptic facilitation, we conclude that facilitation can slow down the drift by a large factor, rendering the network suitable as a model of working memory.

  9. 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.

  10. 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...

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

    OpenAIRE

    Korinko M.D.; Kushnir Y.O.

    2017-01-01

    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, th...

  12. Insensitivity of visual short-term memory to irrelevant visual information.

    Science.gov (United States)

    Andrade, Jackie; Kemps, Eva; Werniers, Yves; May, Jon; Szmalec, Arnaud

    2002-07-01

    Several authors have hypothesized that visuo-spatial working memory is functionally analogous to verbal working memory. Irrelevant background speech impairs verbal short-term memory. We investigated whether irrelevant visual information has an analogous effect on visual short-term memory, using a dynamic visual noise (DVN) technique known to disrupt visual imagery (Quinn & McConnell, 1996b). Experiment I replicated the effect of DVN on pegword imagery. Experiments 2 and 3 showed no effect of DVN on recall of static matrix patterns, despite a significant effect of a concurrent spatial tapping task. Experiment 4 showed no effect of DVN on encoding or maintenance of arrays of matrix patterns, despite testing memory by a recognition procedure to encourage visual rather than spatial processing. Serial position curves showed a one-item recency effect typical of visual short-term memory. Experiment 5 showed no effect of DVN on short-term recognition of Chinese characters, despite effects of visual similarity and a concurrent colour memory task that confirmed visual processing of the characters. We conclude that irrelevant visual noise does not impair visual short-term memory. Visual working memory may not be functionally analogous to verbal working memory, and different cognitive processes may underlie visual short-term memory and visual imagery.

  13. The application of knemometry to measure childhood short-term growth among the indigenous Shuar of Ecuador.

    Science.gov (United States)

    Urlacher, Samuel S; Snodgrass, J Josh; Liebert, Melissa A; Cepon-Robins, Tara J; Gildner, Theresa E; Sugiyama, Lawrence S

    2016-06-01

    Knemometry, the precise measurement of lower leg (LL) length, suggests that childhood short-term (e.g., weekly) growth is a dynamic, nonlinear process. However, owing to the large size and complexity of the traditional knemometer device, previous study of short-term growth among children has been restricted predominantly to clinical settings in industrialized Western nations. The aim of the present study is to address this limitation and promote broader understandings of global variation in childhood development by: (1) describing a custom-built portable knemometer and assessing its performance in the field; and (2) demonstrating the potential application of such a device by characterizing childhood short-term LL growth among the indigenous Shuar of Amazonian Ecuador. Mixed-longitudinal LL length data were collected weekly from 336 Shuar children age 5-12 years old using the custom portable knemometer (n = 1,145 total observations). Device performance and Shuar short-term LL growth were explored using linear mixed effects models and descriptive statistics. The portable knemometer performed well across a range of participant characteristics and possesses a low technical error of measurement of 0.18 mm. Shuar childhood LL growth averages 0.47 mm/week (SD = 0.75 mm/week), but exhibits large between- and within-individual variation. Knemometry can be reliably performed in the field, providing a means for evaluating childhood short-term growth among genetically and ecologically diverse populations. Preliminary findings suggest that Shuar weekly LL growth is comparable in mean magnitude but likely more variable than reported for healthy Western children. Future work will further explore these patterns. Am J Phys Anthropol 160:353-357, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  14. Fuzzy system applications for short-term electric load forecasting

    Science.gov (United States)

    Al-Kandari, Ahmad Mohammad

    Load forecasting is an important function in economic power generation, allocation between plants (Unit Commitment Scheduling), maintenance scheduling, and for system security applications such as peak shaving by power interchange with interconnected utilities. In this thesis the problem of fuzzy short term load forecasting is formulated and solved. The thesis starts with a discussion of conventional algorithms used in short-term load forecasting. These algorithms are based on least error squares and least absolute value. The theory behind each algorithm is explained. Three different models are developed and tested in the first part of the thesis. The first model (A) is a regression model that takes into account the weather parameters in summer and winter seasons. The second model (B) is a harmonics based model, which does not account for weather parameters, but considers the parameters as a function of time. Model (B) can be used where variations in weather parameters are not available. Finally, model (C) is created as a hybrid combination of models A and B. The parameters of the three models are estimated using the two static estimation algorithms and are used later to predict the load for twenty-four hours ahead. The results obtained are discussed and conclusions are drawn for these models. In the second part of the thesis new fuzzy models are developed for crisp load power with fuzzy load parameters and for fuzzy load power with fuzzy load parameters. Three fuzzy models (A), (B) and (C) are developed. The fuzzy load model (A) is a fuzzy linear regression model for summer and winter seasons. Model (B) is a harmonic fuzzy model, which does not account for weather parameters. Finally fuzzy load model (C) is a hybrid combination of fuzzy load models (A) and (B). Estimating the fuzzy parameters for the three models turns out to be one of linear optimization. The fuzzy parameters are obtained for the three models. These parameters are used to predict the load as a

  15. Gummed-up memory: chewing gum impairs short-term recall.

    Science.gov (United States)

    Kozlov, Michail D; Hughes, Robert W; Jones, Dylan M

    2012-01-01

    Several studies have suggested that short-term memory is generally improved by chewing gum. However, we report the first studies to show that chewing gum impairs short-term memory for both item order and item identity. Experiment 1 showed that chewing gum reduces serial recall of letter lists. Experiment 2 indicated that chewing does not simply disrupt vocal-articulatory planning required for order retention: Chewing equally impairs a matched task that required retention of list item identity. Experiment 3 demonstrated that manual tapping produces a similar pattern of impairment to that of chewing gum. These results clearly qualify the assertion that chewing gum improves short-term memory. They also pose a problem for short-term memory theories asserting that forgetting is based on domain-specific interference given that chewing does not interfere with verbal memory any more than tapping. It is suggested that tapping and chewing reduce the general capacity to process sequences.

  16. Analysis of short-term reactor cavity transient

    International Nuclear Information System (INIS)

    Cheng, T.C.; Fischer, S.R.

    1981-01-01

    Following the transient of a hypothetical loss-of-coolant accident (LOCA) in a nuclear reactor, peak pressures are reached within the first 0.03 s at different locations inside the reactor cavity. Due to the complicated multidimensional nature of the reactor cavity, the short-term analysis of the LOCA transient cannot be performed by using traditional containment codes, such as CONTEMPT. The advanced containment code, BEACON/MOD3, developed at the Idaho National Engineering Laboratory (INEL), can be adapted for such analysis. This code provides Eulerian, one and two-dimensional, nonhomogeneous, nonequilibrium flow modeling as well as lumped parameter, homogeneous, equilibrium flow modeling for the solution of two-component, two-phase flow problems. The purpose of this paper is to demonstrate the capability of the BEACON code to analyze complex containment geometry such as a reactor cavity

  17. Routes to short term memory indexing: Lessons from deaf native users of American Sign Language

    Science.gov (United States)

    Hirshorn, Elizabeth A.; Fernandez, Nina M.; Bavelier, Daphne

    2012-01-01

    Models of working memory (WM) have been instrumental in understanding foundational cognitive processes and sources of individual differences. However, current models cannot conclusively explain the consistent group differences between deaf signers and hearing speakers on a number of short-term memory (STM) tasks. Here we take the perspective that these results are not due to a temporal order-processing deficit in deaf individuals, but rather reflect different biases in how different types of memory cues are used to do a given task. We further argue that the main driving force behind the shifts in relative biasing is a consequence of language modality (sign vs. speech) and the processing they afford, and not deafness, per se. PMID:22871205

  18. International short-term medical service trips: guidelines from the literature and perspectives from the field.

    Science.gov (United States)

    Chapin, Erica; Doocy, Shannon

    2010-01-01

    The increasing interest in practising medicine overseas has outpaced research conducted to evaluate its effectiveness and the development of guidelines from evidence-based best practices. Short-term medical teams regularly travel to provide medical care, yet there is little research on the impact or practices of these missions. This study assessed current practices and challenges of short-term medical service teams, using questionnaire-based interviews of 40 participants in recent medical service trips. Study results and a review of recommendations in peer-reviewed journals were used to develop guidelines for international short-term medical trips in relation to mission, collaboration, education and capacity building, provider qualifications, appropriate donations, and cultural sensitivity and understanding. Guidelines that inform models, approaches, best practices and minimum standards for short-term medical service trips should be adopted so that improved and sustainable outcomes can be consistently achieved.

  19. Stochastic short-term maintenance scheduling of GENCOs in an oligopolistic electricity market

    International Nuclear Information System (INIS)

    Fotouhi Ghazvini, Mohammad Ali; Canizes, Bruno; Vale, Zita; Morais, Hugo

    2013-01-01

    Highlights: ► Decision making under uncertainty. ► Stochastic Mixed Integer Quadratic Programming applied to short-term maintenance scheduling. ► Outage scheduling in Oligopolistic electricity markets. ► Generation companies maintenance scheduling. -- Abstract: In the proposed model, the independent system operator (ISO) provides the opportunity for maintenance outage rescheduling of generating units before each short-term (ST) time interval. Long-term (LT) scheduling for 1 or 2 years in advance is essential for the ISO and the generation companies (GENCOs) to decide their LT strategies; however, it is not possible to be exactly followed and requires slight adjustments. The Cournot-Nash equilibrium is used to characterize the decision-making procedure of an individual GENCO for ST intervals considering the effective coordination with LT plans. Random inputs, such as parameters of the demand function of loads, hourly demand during the following ST time interval and the expected generation pattern of the rivals, are included as scenarios in the stochastic mixed integer program defined to model the payoff-maximizing objective of a GENCO. Scenario reduction algorithms are used to deal with the computational burden. Two reliability test systems were chosen to illustrate the effectiveness of the proposed model for the ST decision-making process for future planned outages from the point of view of a GENCO.

  20. 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.

  1. 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.

  2. Emulating short-term synaptic dynamics with memristive devices

    Science.gov (United States)

    Berdan, Radu; Vasilaki, Eleni; Khiat, Ali; Indiveri, Giacomo; Serb, Alexandru; Prodromakis, Themistoklis

    2016-01-01

    Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

  3. Short term load forecasting using fuzzy neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Bakirtzis, A.G.; Theocharis, J.B.; Kiartzis, S.J.; Satsios, K.J. [Aristotle Univ. of Thessaloniki (Greece). Dept. of Electrical and Computer Engineering

    1995-08-01

    This paper presents the development of a fuzzy system for short term load forecasting. The fuzzy system has the network structure and the training procedure of a neural network and is called Fuzzy Neural Network (FNN). A FNN initially creates a rule base from existing historical load data. The parameters of the rule base are then tuned through a training process, so that the output of the FNN adequately matches the available historical load data. Once trained, the FNN can be used to forecast future loads. Test results show that the FNN can forecast future loads with an accuracy comparable to that of neural networks, while its training is much faster than that of neural networks.

  4. 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)

  5. Short-term memories with a stochastic perturbation

    Energy Technology Data Exchange (ETDEWEB)

    Pontes, Jose C.A. de [Departamento de Fisica, Universidade Federal do Parana, 81531-990 Curitiba, PR (Brazil); Batista, Antonio M. [Departamento de Matematica e Estatistica, Universidade Estadual de Ponta Grossa, 84030-900 Ponta Grossa, PR (Brazil); Viana, Ricardo L. [Departamento de Fisica, Universidade Federal do Parana, 81531-990 Curitiba, PR (Brazil); Lopes, Sergio R. [Departamento de Fisica, Universidade Federal do Parana, 81531-990 Curitiba, PR (Brazil)

    2005-03-01

    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.

  6. 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

  7. Short-term growth in asthmatic children using fluticasone propionate

    NARCIS (Netherlands)

    Visser, M. J.; van Aalderen, W. M.; Elliott, B. M.; Odink, R. J.; Brand, P. L.

    1998-01-01

    Inhaled corticosteroids may reduce short-term growth velocity in asthmatic children and knemometry is the most sensitive tool to detect this short-term growth suppression. To compare lower leg growth velocity, as measured by knemometry, in asthmatic children during and after treatment with inhaled

  8. Short-term growth in asthmatic children using fluticasone propionate

    NARCIS (Netherlands)

    Visser, MJ; van Aalderen, WMC; Elliott, BM; Odink, RJ; Brand, PLP

    Background: Inhaled corticosteroids may reduce short-term growth velocity in asthmatic children and knemometry is the most sensitive tool to detect this short-term growth suppression. Study objective: To compare lower leg growth velocity, as measured by knemometry, in asthmatic children during and

  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. The epidemiology of long- and short-term cancer survivors

    DEFF Research Database (Denmark)

    Jarlbæk, Lene; Christensen, Linda; Bruera, Eduardo

    2014-01-01

    , 2.4% lung cancer. Short-term survivors: 21% lung cancer, 7.2% breast cancer. Chemotherapy was provided to 15% of all patients, and to 10% of the 60 + year olds. Discussion. The epidemiology of long- and short-term survivors shows significant differences with regard to age at TOCD, cancer types...

  11. 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

  12. Intercultural Competence in Short-Term Study Abroad

    Science.gov (United States)

    Nguyen, Annie

    2017-01-01

    Assessment is growing for short-term study abroad as the majority of students (63.1%) continue to choose this option (Institute of International Education, 2016). This study uses the Intercultural Effectiveness Scale (IES) to examine the impact of short-term study abroad programs on students' overall intercultural competency and the connections…

  13. The effects of short-term hypergravity on Caenorhabditis elegans

    Science.gov (United States)

    Saldanha, Jenifer N.; Pandey, Santosh; Powell-Coffman, Jo Anne

    2016-08-01

    As we seek to recognize the opportunities of advanced aerospace technologies and spaceflight, it is increasingly important to understand the impacts of hypergravity, defined as gravitational forces greater than those present on the earth's surface. The nematode Caenorhabditis elegans has been established as a powerful model to study the effects of altered gravity regimens and has displayed remarkable resilience to space travel. In this study, we investigate the effects of short-term and defined hypergravity exposure on C. elegans motility, brood size, pharyngeal pumping rates, and lifespan. The results from this study advance our understanding of the effects of shorter durations of exposure to increased gravitational forces on C. elegans, and also contribute to the growing body of literature on the impacts of altered gravity regimens on earth's life forms.

  14. The Delicate Analysis of Short-Term Load Forecasting

    Science.gov (United States)

    Song, Changwei; Zheng, Yuan

    2017-05-01

    This paper proposes a new method for short-term load forecasting based on the similar day method, correlation coefficient and Fast Fourier Transform (FFT) to achieve the precision analysis of load variation from three aspects (typical day, correlation coefficient, spectral analysis) and three dimensions (time dimension, industry dimensions, the main factors influencing the load characteristic such as national policies, regional economic, holidays, electricity and so on). First, the branch algorithm one-class-SVM is adopted to selection the typical day. Second, correlation coefficient method is used to obtain the direction and strength of the linear relationship between two random variables, which can reflect the influence caused by the customer macro policy and the scale of production to the electricity price. Third, Fourier transform residual error correction model is proposed to reflect the nature of load extracting from the residual error. Finally, simulation result indicates the validity and engineering practicability of the proposed method.

  15. Short-Term Market Risks Implied by Weekly Options

    DEFF Research Database (Denmark)

    Andersen, Torben Gustav; Fusari, Nicola; Todorov, Viktor

    We study short-term market risks implied by weekly S&P 500 index options. The introduction of weekly options has dramatically shifted the maturity profile of traded options over the last five years, with a substantial proportion now having expiry within one week. Such short-dated options provide...... a direct way to study volatility and jump risks. Unlike longer-dated options, they are largely insensitive to the risk of intertemporal shifts in the economic environment. Adopting a novel semi-nonparametric approach, we uncover variation in the negative jump tail risk which is not spanned by market...... volatility and helps predict future equity returns. Incidents of tail shape shifts coincide with mispricing of standard parametric models for longer-dated options. As such, our approach allows for easy identification of periods of heightened concerns about negative tail events that are not always "signaled...

  16. Sleep deprivation accelerates delay-related loss of visual short-term memories without affecting precision.

    Science.gov (United States)

    Wee, Natalie; Asplund, Christopher L; Chee, Michael W L

    2013-06-01

    Visual short-term memory (VSTM) is an important measure of information processing capacity and supports many higher-order cognitive processes. We examined how sleep deprivation (SD) and maintenance duration interact to influence the number and precision of items in VSTM using an experimental design that limits the contribution of lapses at encoding. For each trial, participants attempted to maintain the location and color of three stimuli over a delay. After a retention interval of either 1 or 10 seconds, participants reported the color of the item at the cued location by selecting it on a color wheel. The probability of reporting the probed item, the precision of report, and the probability of reporting a nonprobed item were determined using a mixture-modeling analysis. Participants were studied twice in counterbalanced order, once after a night of normal sleep and once following a night of sleep deprivation. Sleep laboratory. Nineteen healthy college age volunteers (seven females) with regular sleep patterns. Approximately 24 hours of total SD. SD selectively reduced the number of integrated representations that can be retrieved after a delay, while leaving the precision of object information in the stored representations intact. Delay interacted with SD to lower the rate of successful recall. Visual short-term memory is compromised during sleep deprivation, an effect compounded by delay. However, when memories are retrieved, they tend to be intact.

  17. Adaptive short-term electricity price forecasting using artificial neural networks in the restructured power markets

    International Nuclear Information System (INIS)

    Yamin, H.Y.; Shahidehpour, S.M.; Li, Z.

    2004-01-01

    This paper proposes a comprehensive model for the adaptive short-term electricity price forecasting using Artificial Neural Networks (ANN) in the restructured power markets. The model consists: price simulation, price forecasting, and performance analysis. The factors impacting the electricity price forecasting, including time factors, load factors, reserve factors, and historical price factor are discussed. We adopted ANN and proposed a new definition for the MAPE using the median to study the relationship between these factors and market price as well as the performance of the electricity price forecasting. The reserve factors are included to enhance the performance of the forecasting process. The proposed model handles the price spikes more efficiently due to considering the median instead of the average. The IEEE 118-bus system and California practical system are used to demonstrate the superiority of the proposed model. (author)

  18. [Short-term memory characteristics of vibration intensity tactile perception on human wrist].

    Science.gov (United States)

    Hao, Fei; Chen, Li-Juan; Lu, Wei; Song, Ai-Guo

    2014-12-25

    In this study, a recall experiment and a recognition experiment were designed to assess the human wrist's short-term memory characteristics of tactile perception on vibration intensity, by using a novel homemade vibrotactile display device based on the spatiotemporal combination vibration of multiple micro vibration motors as a test device. Based on the obtained experimental data, the short-term memory span, recognition accuracy and reaction time of vibration intensity were analyzed. From the experimental results, some important conclusions can be made: (1) The average short-term memory span of tactile perception on vibration intensity is 3 ± 1 items; (2) The greater difference between two adjacent discrete intensities of vibrotactile stimulation is defined, the better average short-term memory span human wrist gets; (3) There is an obvious difference of the average short-term memory span on vibration intensity between the male and female; (4) The mechanism of information extraction in short-term memory of vibrotactile display is to traverse the scanning process by comparison; (5) The recognition accuracy and reaction time performance of vibrotactile display compares unfavourably with that of visual and auditory. The results from this study are important for designing vibrotactile display coding scheme.

  19. 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.

  20. 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.

  1. Auditory short-term memory in the primate auditory cortex

    Science.gov (United States)

    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 short-term memory (pSTM), is tractable to study in nonhuman primates, whose brain architecture and behavioral repertoire are comparable to our own. This review discusses recent advances in the behavioral and neurophysiological study of auditory memory with a focus on single-unit recordings from macaque monkeys performing delayed-match-to-sample (DMS) tasks. Monkeys appear to employ pSTM to solve these tasks, as evidenced by the impact of interfering stimuli on memory performance. In several regards, pSTM in monkeys resembles pitch memory in humans, and may engage similar neural mechanisms. Neural correlates of DMS performance have been observed throughout the auditory and prefrontal cortex, defining a network of areas supporting auditory STM with parallels to that supporting visual STM. These correlates include persistent neural firing, or a suppression of firing, during the delay period of the memory task, as well as suppression or (less commonly) enhancement of sensory responses when a sound is repeated as a ‘match’ stimulus. Auditory STM is supported by a distributed temporo-frontal network in which sensitivity to stimulus history is an intrinsic feature of auditory processing. PMID:26541581

  2. Auditory short-term memory in the primate auditory cortex.

    Science.gov (United States)

    Scott, Brian H; Mishkin, Mortimer

    2016-06-01

    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 short-term memory (pSTM), is tractable to study in nonhuman primates, whose brain architecture and behavioral repertoire are comparable to our own. This review discusses recent advances in the behavioral and neurophysiological study of auditory memory with a focus on single-unit recordings from macaque monkeys performing delayed-match-to-sample (DMS) tasks. Monkeys appear to employ pSTM to solve these tasks, as evidenced by the impact of interfering stimuli on memory performance. In several regards, pSTM in monkeys resembles pitch memory in humans, and may engage similar neural mechanisms. Neural correlates of DMS performance have been observed throughout the auditory and prefrontal cortex, defining a network of areas supporting auditory STM with parallels to that supporting visual STM. These correlates include persistent neural firing, or a suppression of firing, during the delay period of the memory task, as well as suppression or (less commonly) enhancement of sensory responses when a sound is repeated as a ׳match' stimulus. Auditory STM is supported by a distributed temporo-frontal network in which sensitivity to stimulus history is an intrinsic feature of auditory processing. This article is part of a Special Issue entitled SI: Auditory working memory. Published by Elsevier B.V.

  3. Operations Management in Short Term Power Markets

    DEFF Research Database (Denmark)

    Heide-Jørgensen, Ditte Mølgård

    without losing computational tractability. The high time resolution is crucial to correctly describe renewables, such as wind power, and capture how they affect the system and the system costs, since they are often fluctuating and hard to predict, also within the hour. The thesis consists of four chapters...... is on a balancing market model like in the Nordic countries with high time resolution, and it takes extensive balancing rules into consideration. We look into how wind forecast errors can be handled in a system with a large and increasing amount of wind power and at what costs. The project was done in collaboration...... minutes. The stochastic input is the electricity price modelled as a time inhomogenous Markov chain that the power producer uses to maximise profits. To maintain computational tractability with such high time resolution and stochastics the model is solved with dynamic programming. The two models differ...

  4. Short-term wind power prediction

    DEFF Research Database (Denmark)

    Joensen, Alfred K.

    2003-01-01

    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, and to imple......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......, 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...

  5. 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)

  6. Short term solar radiation forecasting: Island versus continental sites

    International Nuclear Information System (INIS)

    Boland, John; David, Mathieu; Lauret, Philippe

    2016-01-01

    Due its intermittency, the large-scale integration of solar energy into electricity grids is an issue and more specifically in an insular context. Thus, forecasting the output of solar energy is a key feature to efficiently manage the supply-demand balance. In this paper, three short term forecasting procedures are applied to island locations in order to see how they perform in situations that are potentially more volatile than continental locations. Two continental locations, one coastal and one inland are chosen for comparison. At the two time scales studied, ten minute and hourly, the island locations prove to be more difficult to forecast, as shown by larger forecast errors. It is found that the three methods, one purely statistical combining Fourier series plus linear ARMA models, one combining clear sky index models plus neural net models, and a third using a clear sky index plus ARMA, give similar forecasting results. It is also suggested that there is great potential of merging modelling approaches on different horizons. - Highlights: • Solar energy forecasting is more difficult for insular than continental sites. • Fourier series plus linear ARMA models are one forecasting method tested. • Clear sky index models plus neural net models are also tested. • Clear sky index models plus linear ARMA is also an option. • All three approaches have similar skill.

  7. 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)

  8. A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Chengshi Tian

    2018-03-01

    Full Text Available Short-term load forecasting plays an indispensable role in electric power systems, which is not only an extremely challenging task but also a concerning issue for all society due to complex nonlinearity characteristics. However, most previous combined forecasting models were based on optimizing weight coefficients to develop a linear combined forecasting model, while ignoring that the linear combined model only considers the contribution of the linear terms to improving the model’s performance, which will lead to poor forecasting results because of the significance of the neglected and potential nonlinear terms. In this paper, a novel nonlinear combined forecasting system, which consists of three modules (improved data pre-processing module, forecasting module and the evaluation module is developed for short-term load forecasting. Different from the simple data pre-processing of most previous studies, the improved data pre-processing module based on longitudinal data selection is successfully developed in this system, which further improves the effectiveness of data pre-processing and then enhances the final forecasting performance. Furthermore, the modified support vector machine is developed to integrate all the individual predictors and obtain the final prediction, which successfully overcomes the upper drawbacks of the linear combined model. Moreover, the evaluation module is incorporated to perform a scientific evaluation for the developed system. The half-hourly electrical load data from New South Wales are employed to verify the effectiveness of the developed forecasting system, and the results reveal that the developed nonlinear forecasting system can be employed in the dispatching and planning for smart grids.

  9. Attention Problems, Phonological Short-Term Memory, and Visuospatial Short-Term Memory: Differential Effects on Near- and Long-Term Scholastic Achievement

    Science.gov (United States)

    Sarver, Dustin E.; Rapport, Mark D.; Kofler, Michael J.; Scanlan, Sean W.; Raiker, Joseph S.; Altro, Thomas A.; Bolden, Jennifer

    2012-01-01

    The current study examined individual differences in children's phonological and visuospatial short-term memory as potential mediators of the relationship among attention problems and near- and long-term scholastic achievement. Nested structural equation models revealed that teacher-reported attention problems were associated negatively with…

  10. Very-short-term wind power probabilistic forecasts by sparse vector autoregression

    DEFF Research Database (Denmark)

    Dowell, Jethro; Pinson, Pierre

    2016-01-01

    A spatio-temporal method for producing very-shortterm parametric probabilistic wind power forecasts at a large number of locations is presented. Smart grids containing tens, or hundreds, of wind generators require skilled very-short-term forecasts to operate effectively, and spatial information...... is highly desirable. In addition, probabilistic forecasts are widely regarded as necessary for optimal power system management as they quantify the uncertainty associated with point forecasts. Here we work within a parametric framework based on the logit-normal distribution and forecast its parameters....... The location parameter for multiple wind farms is modelled as a vector-valued spatiotemporal process, and the scale parameter is tracked by modified exponential smoothing. A state-of-the-art technique for fitting sparse vector autoregressive models is employed to model the location parameter and demonstrates...

  11. Nonlinear Dynamical Modes as a Basis for Short-Term Forecast of Climate Variability

    Science.gov (United States)

    Feigin, A. M.; Mukhin, D.; Gavrilov, A.; Seleznev, A.; Loskutov, E.

    2017-12-01

    We study abilities of data-driven stochastic models constructed by nonlinear dynamical decomposition of spatially distributed data to quantitative (short-term) forecast of climate characteristics. We compare two data processing techniques: (i) widely used empirical orthogonal function approach, and (ii) nonlinear dynamical modes (NDMs) framework [1,2]. We also make comparison of two kinds of the prognostic models: (i) traditional autoregression (linear) model and (ii) model in the form of random ("stochastic") nonlinear dynamical system [3]. We apply all combinations of the above-mentioned data mining techniques and kinds of models to short-term forecasts of climate indices based on sea surface temperature (SST) data. We use NOAA_ERSST_V4 dataset (monthly SST with space resolution 20 × 20) covering the tropical belt and starting from the year 1960. We demonstrate that NDM-based nonlinear model shows better prediction skill versus EOF-based linear and nonlinear models. Finally we discuss capability of NDM-based nonlinear model for long-term (decadal) prediction of climate variability. [1] D. Mukhin, A. Gavrilov, E. Loskutov , A.Feigin, J.Kurths, 2015: Principal nonlinear dynamical modes of climate variability, Scientific Reports, rep. 5, 15510; doi: 10.1038/srep15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J., 2016: Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. [3] Ya. Molkov, D. Mukhin, E. Loskutov, A. Feigin, 2012: Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.

  12. 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 obser......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...

  13. 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.

  14. Olfactory short-term memory encoding and maintenance - an event-related potential study.

    Science.gov (United States)

    Lenk, Steffen; Bluschke, Annet; Beste, Christian; Iannilli, Emilia; Rößner, Veit; Hummel, Thomas; Bender, Stephan

    2014-09-01

    This study examined whether the memory encoding and short term maintenance of olfactory stimuli is associated with neurophysiological activation patterns which parallel those described for sensory modalities such as vision and auditory. We examined olfactory event-related potentials in an olfactory change detection task in twenty-four healthy adults and compared the measured activation to that found during passive olfactory stimulation. During the early olfactory post-processing phase, we found a sustained negativity over bilateral frontotemporal areas in the passive perception condition which was enhanced in the active memory task. There was no significant lateralization in either experimental condition. During the maintenance interval at the end of the delay period, we still found sustained activation over bilateral frontotemporal areas which was more negative in trials with correct - as compared to incorrect - behavioural responses. This was complemented by a general significantly stronger frontocentral activation. Summarizing, we were able to show that olfactory short term memory involves a parallel sequence of activation as found in other sensory modalities. In addition to olfactory-specific frontotemporal activations in the memory encoding phase, we found slow cortical potentials over frontocentral areas during the memory maintenance phase indicating the activation of a supramodal memory maintenance system. These findings could represent the neurophysiological underpinning of the 'olfactory flacon', the olfactory counter-part to the visual sketchpad and phonological loop embedded in Baddeley's working memory model. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. A comparison of serial order short-term memory effects across verbal and musical domains.

    Science.gov (United States)

    Gorin, Simon; Mengal, Pierre; Majerus, Steve

    2018-04-01

    Recent studies suggest that the mechanisms involved in the short-term retention of serial order information may be shared across short-term memory (STM) domains such as verbal and visuospatial STM. Given the intrinsic sequential organization of musical material, the study of STM for musical information may be particularly informative about serial order retention processes and their domain-generality. The present experiment examined serial order STM for verbal and musical sequences in participants with no advanced musical expertise and experienced musicians. Serial order STM for verbal information was assessed via a serial order reconstruction task for digit sequences. In the musical domain, serial order STM was assessed using a novel melodic sequence reconstruction task maximizing the retention of tone order information. We observed that performance for the verbal and musical tasks was characterized by sequence length as well as primacy and recency effects. Serial order errors in both tasks were characterized by similar transposition gradients and ratios of fill-in:infill errors. These effects were observed for both participant groups, although the transposition gradients and ratios of fill-in:infill errors showed additional specificities for musician participants in the musical task. The data support domain-general serial order STM effects but also suggest the existence of additional domain-specific effects. Implications for models of serial order STM in verbal and musical domains are discussed.

  16. Short-term airing by natural ventilation

    DEFF Research Database (Denmark)

    Perino, Marco; Heiselberg, Per

    2009-01-01

    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. This kind of system frequently integrates...... that was aimed at developing and validating numerical models for the analysis of buoyancy driven single-sided natural ventilation systems. Once validated, these models can be used to optimize control strategies in order to achieve satisfactory indoor comfort conditions and IAQ....... traditional mechanical ventilation components with natural ventilation devices, such as motorized windows and louvers. Among the various 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...

  17. 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....... The method is applied for horizons of up to 42 hours. Solar heating systems naturally come with a hot water tank, which can be utilized for energy storage also for other energy sources. Thereby such systems can become an important part of energy systems with a large share of uncontrollable energy sources......-adaptive linear models. The approach is similar to the one by Bacher et al. (2009), but contains additional effects due to differences between solar thermal collectors and photovoltaics. Numerical weather predictions provided by Danish Meteorological Institute are used as input. The applied models adapt over time...

  18. Effect of Short-Term Hypergravity Treatment on Mouse 2-Cell Embryo Development

    Science.gov (United States)

    Ning, Li-Na; Lei, Xiao-Hua; Cao, Yu-Jing; Zhang, Yun-Fang; Cao, Zhong-Hong; Chen, Qi; Duan, En-Kui

    2015-11-01

    Though there are numerous biological experiments, which have been performed in a space environment, to study the physiological effect of space travel on living organisms, while the potential effect of weightlessness or short-term hypergravity on the reproductive system in most species, particularly in mammalian is still controversial and unclear. In our previous study, we investigated the effect of space microgravity on the development of mouse 4-cell embryos by using Chinese SJ-8. .Unexpectedly, we did not get any developed embryo during the space-flight. Considering that the process of space experiment is quite different from most experiments done on earth in several aspects such as, the vibration and short-term hypergravity during the rock launching and landing. Thus we want to know whether the short-term hypergravity produced by the launch process affect the early embryo development in mice, and howthe early embryos respond to the hypergravity. In present study, we are mimicking the short-term hypergravity during launch by using a centrifuge to investigate its influence on the development of early embryo (2-cell) in mice. We also examined the actin filament distribution in 2-cell embryos by immunostaining to test their potential capacity of development under short-term hypergravity exposure. Our results showed that most 2-cell embryos in the hypergravity exposure groups developed into blastocysts with normal morphology after 72h cultured in vitro, and there is no obvious difference in the development rate of blastocyst formation compared to the control. Moreover, there were no statistically significant differences in birth rates after oviduct transfer of 2-cell mouse embryos exposed on short-term hypergravity compared with 1 g condition. In addition, the well-organized actin distribution appeared in 2-cell embryos after exposed on hypergravity and also in the subsequent developmental blastocysts. Taken together, our data shows that short-term exposure in

  19. Short-term regulation of hydro powerplants. Studies on the environmental effects

    International Nuclear Information System (INIS)

    Sinisalmi, T.; Riihimaeki, J.; Vehanen, T.; Yrjaenae, T.

    1997-01-01

    The publication is a final report on a project studying effects of short-term regulation of hydro power plants. The project consists of two parts: (1) examining and developing methods for evaluation, (2) applying methods in a case study at the Oulujoki River. The economic value of short-term regulation was studied with a model consisting of an optimization model and a river simulation model. Constraints on water level or discharge variations could be given to the power plants and their economical influence could be studied. Effects on shoreline recreation use due to water level fluctuation were studied with a model where various effects are made commensurable and expressed in monetary terms. A literature survey and field experiments were used to study the methods for assessing effects of short-term regulation on river habitats. The state and development needs of fish stocks and fisheries in large regulated rivers were studied and an environmental classification was made. Remedial measures for the short-term regulated rivers were studied with a literature survey and enquiries. A comprehensive picture of the various effects of short-term regulation was gained in the case study in Oulujoki River (110 km long, 7 power plants). Harmful effects can be reduced with the given recommendations of remedial measures on environment and the usage of the hydro power plants. (orig.) 52 refs

  20. Short-term regulation of hydro powerplants. Studies on the environmental effects

    Energy Technology Data Exchange (ETDEWEB)

    Sinisalmi, T. [ed.; Forsius, J.; Muotka, J.; Soimakallio, H. [Imatran Voima Oy, Vantaa (Finland); Riihimaeki, J. [VTT, Espoo (Finland); Vehanen, T. [Finnish Game and Fisheries Research Inst. (Finland); Yrjaenae, T. [North Ostrobothnia Regional Environmental Centre, Oulu (Finland)

    1997-12-31

    The publication is a final report on a project studying effects of short-term regulation of hydro power plants. The project consists of two parts: (1) examining and developing methods for evaluation, (2) applying methods in a case study at the Oulujoki River. The economic value of short-term regulation was studied with a model consisting of an optimization model and a river simulation model. Constraints on water level or discharge variations could be given to the power plants and their economical influence could be studied. Effects on shoreline recreation use due to water level fluctuation were studied with a model where various effects are made commensurable and expressed in monetary terms. A literature survey and field experiments were used to study the methods for assessing effects of short-term regulation on river habitats. The state and development needs of fish stocks and fisheries in large regulated rivers were studied and an environmental classification was made. Remedial measures for the short-term regulated rivers were studied with a literature survey and enquiries. A comprehensive picture of the various effects of short-term regulation was gained in the case study in Oulujoki River (110 km long, 7 power plants). Harmful effects can be reduced with the given recommendations of remedial measures on environment and the usage of the hydro power plants. (orig.) 52 refs.

  1. A short-term scheduling for the optimal operation of biorefineries

    International Nuclear Information System (INIS)

    Grisi, E.F.; Yusta, J.M.; Khodr, H.M.

    2011-01-01

    This work presents an analysis of the inherent potentialities and characteristics of the sugarcane industries that produce sugar, bioethanol, biogas and bioelectricity and that are being described as 'Biorefineries'. These Biorefineries are capable of producing bio-energy under diverse forms, intended for their own internal consumption and for external sales and marketing. A complex model and simulation are carried out of the processes of a sugarcane industry, with the data characteristic as well as the production costs, prices of products and considerations on the energy demand by basic processes. A Mixed-Integer Linear Programming (MILP) optimization problem formulation and an analysis of optimal solutions in short-term operation are described, taking into account the production cost functions of each commodity and the incomes obtained from selling electricity and other products. The objective is to maximize the hourly plant economic profit in the different scenarios considered in a real case study.

  2. Short-Term Load Forecasting for Microgrids Based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Antonio J. Sanchez-Esguevillas

    2013-03-01

    Full Text Available Electricity is indispensable and of strategic importance to national economies. Consequently, electric utilities make an effort to balance power generation and demand in order to offer a good service at a competitive price. For this purpose, these utilities need electric load forecasts to be as accurate as possible. However, electric load depends on many factors (day of the week, month of the year, etc., which makes load forecasting quite a complex process requiring something other than statistical methods. This study presents an electric load forecast architectural model based on an Artificial Neural Network (ANN that performs Short-Term Load Forecasting (STLF. In this study, we present the excellent results obtained, and highlight the simplicity of the proposed model. Load forecasting was performed in a geographic location of the size of a potential microgrid, as microgrids appear to be the future of electric power supply.

  3. 'EMU equity markets' return variance and spill over effects from short-term interest rates

    DEFF Research Database (Denmark)

    Hou, Ai Jun

    2013-01-01

    The DCF (Discounted Cash flow) Model provides the theoretical background for the possible impact of interest rate changes on equity prices. This paper examines the spillover effects from the movement of short term interest rates to equity markets within the Euro area. The empirical study is carried...... out by estimating a Markov Switching GJR-M model with a Bayesian based Markov Chain Monte Carlo (MCMC) methodology. The result indicates that stock markets in the Euro area display a significant two regimes with distinct characteristics. Within a high variance, low mean state (a bear market regime......), stock returns have a negative relationship with the volatility, and the volatility process responds asymmetrically to shocks to equity returns, especially to bad news. The other regime (a bull market regime) appears to be a high mean, low variance state, within which the returns have a positive...

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

    Science.gov (United States)

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

    2011-10-30

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

  5. 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...

  6. 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 ...

  7. 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.

  8. 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.

  9. Decreased synaptic plasticity in the medial prefrontal cortex underlies short-term memory deficits in 6-OHDA-lesioned rats.

    Science.gov (United States)

    Matheus, Filipe C; Rial, Daniel; Real, Joana I; Lemos, Cristina; Ben, Juliana; Guaita, Gisele O; Pita, Inês R; Sequeira, Ana C; Pereira, Frederico C; Walz, Roger; Takahashi, Reinaldo N; Bertoglio, Leandro J; Da Cunha, Cláudio; Cunha, Rodrigo A; Prediger, Rui D

    2016-03-15

    Parkinson's disease (PD) is characterized by motor dysfunction associated with dopaminergic degeneration in the dorsolateral striatum (DLS). However, motor symptoms in PD are often preceded by short-term memory deficits, which have been argued to involve deregulation of medial prefrontal cortex (mPFC). We now used a 6-hydroxydopamine (6-OHDA) rat PD model to explore if alterations of synaptic plasticity in DLS and mPFC underlie short-term memory impairments in PD prodrome. The bilateral injection of 6-OHDA (20μg/hemisphere) in the DLS caused a marked loss of dopaminergic neurons in the substantia nigra (>80%) and decreased monoamine levels in the striatum and PFC, accompanied by motor deficits evaluated after 21 days in the open field and accelerated rotarod. A lower dose of 6-OHDA (10μg/hemisphere) only induced a partial degeneration (about 60%) of dopaminergic neurons in the substantia nigra with no gross motor impairments, thus mimicking an early premotor stage of PD. Notably, 6-OHDA (10μg)-lesioned rats displayed decreased monoamine levels in the PFC as well as short-term memory deficits evaluated in the novel object discrimination and in the modified Y-maze tasks; this was accompanied by a selective decrease in the amplitude of long-term potentiation in the mPFC, but not in DLS, without changes of synaptic transmission in either brain regions. These results indicate that the short-term memory dysfunction predating the motor alterations in the 6-OHDA model of PD is associated with selective changes of information processing in PFC circuits, typified by persistent changes of synaptic plasticity. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. 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.

  11. 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.

  12. 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...

  13. Some risks related to the short-term trading of natural gas

    International Nuclear Information System (INIS)

    Ahmed El Hachemi Mazighi

    2004-01-01

    Traditionally guided by long-term contracts, the international natural gas trade is experiencing new methods of operating, based on the short term and more flexibility. Today, indeed, the existence of uncommitted quantities of natural gas, combined with gas price discrepancies among different regions of the world, gives room for the expansion of the spot-trading of gas. The main objective of this paper is to discuss three fundamental risks related to the short-term trading of natural gas: volume risk, price risk and infrastructure risk. The defenders Of globalisation argue that the transition from the long-term to the short-term trading of natural gas is mainly a question of access to gas reserves, decreasing costs of gas liquefaction, the building of liquefied natural gas (LNG) fleets and regasification facilities and third-party access to the infrastructure. This process needs to be as short as possible, so that the risks related to the transition process will disappear rapidly. On the other hand, the detractors of globalisation put the emphasis on the complexity of the gas value chain and on the fact that eliminating long- term contracts increases the risks inherent to the international natural gas business. In this paper, we try to untangle and assess the risks related to the short-term trading of natural gas. Our main conclusions are: the short-term trading of gas is far from riskless; volume risk requires stock-building in both consuming and producing countries. (author)

  14. Short-term memory in the service of executive control functions

    Directory of Open Access Journals (Sweden)

    Farshad Alizadeh Mansouri

    2015-12-01

    Full Text Available Short-term memory is a crucial cognitive function for supporting on-going and upcoming behaviours, allowing storage of information across delay periods. The content of this memory may typically include tangible information about features such as the shape, colour or texture of an object, its location and motion relative to the body, or phonological information. The neural correlate of these short-term memories has been found in different brain areas involved in organizing perceptual or motor functions. In particular, neuronal activity in different prefrontal areas encodes task-related information corresponding to short-term memory across delay periods, and lesions in the prefrontal cortex severely affect the ability to hold this type of memory. Recent studies have further expanded the scope and possible role of short-term memory by showing that information of abstract entities such as a behaviour-guiding rule, or the occurrence of a conflict in information processing; can also be maintained in short-term memory and used for adjusting the allocation of executive control in dynamic environments. It has also been shown that neuronal activity in the dorsolateral prefrontal and orbitofrontal cortices encodes information about such abstract entities. These findings suggest that the prefrontal cortex plays crucial roles in organizing goal-directed behaviour by supporting various mnemonic processes that maintain a wide range of information in the service of executive control of on-going or upcoming behaviour.

  15. Short-term energy outlook, quarterly projections, first quarter 1998

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-01-01

    The forecast period for this issue of the Outlook extends from the first quarter of 1998 through the fourth quarter of 1999. Values for the fourth quarter of 1997, 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 first quarter 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. 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 adjusted by EIA to reflect EIA assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 24 figs., 19 tabs.

  16. A POSTSYNAPTIC ROLE FOR SHORT-TERM NEURONAL FACILITATION IN DENDRITIC SPINES

    Directory of Open Access Journals (Sweden)

    Sunggu Yang

    2016-09-01

    Full Text Available Synaptic plasticity is a fundamental component of information processing in the brain. Presynaptic facilitation in response to repetitive stimuli, often referred to as paired-pulse facilitation (PPF, is a dominant form of short-term synaptic plasticity. Recently, an additional cellular mechanism for short-term facilitation (short-term postsynaptic plasticity has been proposed. While a dendritic mechanism was described in hippocampus, its expression has not yet been demonstrated at the levels of the spine. Furthermore, it is unknown whether the mechanism can be expressed in other brain regions, such as sensory cortex. Here, we demonstrated that a postsynaptic response can be facilitated by prior spine excitation in both hippocampal and cortical neurons, using 3D digital holography and two-photon calcium imaging. The coordinated action of pre- and post-synaptic plasticity may provide a more thorough account of information processing in the brain.

  17. Short-term power plant operation scheduling in thermal systems with long-term boundary conditions

    International Nuclear Information System (INIS)

    Wolter, H.

    1990-01-01

    For the first time, the modeling of long-term quantitative conditions within the short-term planning of the application of power stations is made via their shadow prices. It corresponds to a decomposition of the quantitative conditions by means of the method of the Langrange relaxation. The shadow prices determined by the planning for energy application regarding long- term quantitative conditions pass into the short-term planning for power station application and subsidize or rather punish the application of limited amounts as for as they are not claimed for sufficiently or excessively. The clear advantage of this modeling is that the short-term planning of power station application can deviate from the envisioned energy application regarding the total optimum, because the shadow prices contain all information about the cost effect of the energy shifts in the residual total period, which become necessary due to the deviations in the short-term period to be planned in the current short-term period. (orig./DG) [de

  18. 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).

  19. Congenital Amusia: A Short-Term Memory Deficit for Non-Verbal, but Not Verbal Sounds

    Science.gov (United States)

    Tillmann, Barbara; Schulze, Katrin; Foxton, Jessica M.

    2009-01-01

    Congenital amusia refers to a lifelong disorder of music processing and is linked to pitch-processing deficits. The present study investigated congenital amusics' short-term memory for tones, musical timbres and words. Sequences of five events (tones, timbres or words) were presented in pairs and participants had to indicate whether the sequences…

  20. Cognitive Backward Masking: A Window Into the Formation of a Short-Term Memory Trace

    NARCIS (Netherlands)

    Nieuwenstein, Mark; Wyble, Brad

    2012-01-01

    Working memory consolidation denotes the process that enables sensory information to be stored in short-term memory. What is currently unclear is how long this process takes and whether it continues after a stimulus has been masked. Here, we address these matters by examining whether the

  1. Axonal protection by short-term hyperglycemia with involvement of autophagy in TNF-induced optic nerve degeneration

    Directory of Open Access Journals (Sweden)

    Kana eSase

    2015-10-01

    Full Text Available Previous reports showed that short-term hyperglycemia protects optic nerve axons in a rat experimental hypertensive glaucoma model. In this study, we investigated whether short-term hyperglycemia prevents tumor necrosis factor (TNF-induced optic nerve degeneration in rats and examined the role of autophagy in this axon change process. In phosphate-buffered saline-treated rat eyes, no significant difference in axon number between the normoglycemic (NG and streptozotocin-induced hyperglycemic (HG groups was seen at 2weeks. Substantial degenerative changes in the axons were noted 2 weeks after intravitreal injection of TNF in the NG group. However, the HG group showed significant protective effects on axons against TNF-induced optic nerve degeneration compared with the NG group. This protective effect was significantly inhibited by 3-methyladenine, an autophagy inhibitor. Immunoblot analysis showed that the LC3-II level in the optic nerve was increased in the HG group compared with the NG group. Increased p62 protein levels in the optic nerve after TNF injection was observed in the NG group, and this increase was inhibited in the HG group. Electron microscopy showed that autophagosomes were increased in optic nerve axons in the HG group. Immunohistochemical study showed that LC3 was colocalized with nerve fibers in the retina and optic nerve in both the NG and HG groups. Short-term hyperglycemia protects axons against TNF-induced optic nerve degeneration. This axonal-protective effect may be associated with autophagy machinery.

  2. 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.

  3. 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

  4. Sequential dynamics in visual short-term memory.

    Science.gov (United States)

    Kool, Wouter; Conway, Andrew R A; Turk-Browne, Nicholas B

    2014-10-01

    Visual short-term memory (VSTM) is thought to help bridge across changes in visual input, and yet many studies of VSTM employ static displays. Here we investigate how VSTM copes with sequential input. In particular, we characterize the temporal dynamics of several different components of VSTM performance, including: storage probability, precision, variability in precision, guessing, and swapping. We used a variant of the continuous-report VSTM task developed for static displays, quantifying the contribution of each component with statistical likelihood estimation, as a function of serial position and set size. In Experiments 1 and 2, storage probability did not vary by serial position for small set sizes, but showed a small primacy effect and a robust recency effect for larger set sizes; precision did not vary by serial position or set size. In Experiment 3, the recency effect was shown to reflect an increased likelihood of swapping out items from earlier serial positions and swapping in later items, rather than an increased rate of guessing for earlier items. Indeed, a model that incorporated responding to non-targets provided a better fit to these data than alternative models that did not allow for swapping or that tried to account for variable precision. These findings suggest that VSTM is updated in a first-in-first-out manner, and they bring VSTM research into closer alignment with classical working memory research that focuses on sequential behavior and interference effects.

  5. Short-Term Dynamical Interactions Among Extrasolar Planets

    Science.gov (United States)

    Laughlin, Gregory; Chambers, John E.; DiVincenzi, Donald (Technical Monitor)

    2001-01-01

    We show that short-term perturbations among massive planets in multiple planet systems can result in radial velocity variations of the central star which differ substantially from velocity variations derived assuming the planets are executing independent Keplerian motions. We discuss two alternate fitting methods which can lead to an improved dynamical description of multiple planet systems. In the first method, the osculating orbital elements are determined via a Levenberg-Marquardt minimization scheme driving an N-body integrator. The second method is an improved analytic model in which orbital elements such as the periods and longitudes of periastron are allowed to vary according to a simple model for resonant interactions between the planets. Both of these methods can potentially determine the true masses for the planets by eliminating the sin(i) degeneracy inherent in fits that assume independent Keplerian motions. As more radial velocity data is accumulated from stars such as GJ876, these methods should allow for unambiguous determination of the planetary masses and relative inclinations.

  6. Short-term repeatability of insulin resistance indexes in older adults. The Atherosclerosis Risk in Communities Study.

    Science.gov (United States)

    Poon, Anna K; Meyer, Michelle L; Reaven, Gerald; Knowles, Joshua W; Selvin, Elizabeth; Pankow, James S; Couper, David; Loehr, Laura; Heiss, Gerardo

    2018-03-29

    The homeostatic model assessment of insulin resistance (HOMA-IR) and triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) are insulin resistance indexes routinely used in clinical and population-based studies, but their short-term repeatability are not well characterized. To quantify the short-term repeatability of insulin resistances indexes and their analytes, consisting of fasting glucose and insulin for HOMA-IR, and triglyceride and high-density lipoprotein cholesterol (HDL-C) for TG/HDL-C. Prospective cohort study. A total of 102 adults 68 to 88 years old without diabetes attended an initial exam and repeat exam (mean 46 days; range 28 to 102 days). Blood samples were collected, processed, shipped, and assayed following a standardized protocol. Repeatability was quantified using the intraclass correlation coefficient (ICC) and within-person coefficient of variation (CV). Minimum detectable change (MDC95) and minimum detectable difference (MDD95) were quantified. For HOMA-IR, insulin, and fasting glucose, the ICCs were 0.70, 0.68, and 0.70; their respective within-person CVs were 30.4%, 28.8%, and 5.6%. For TG/HDL-C, triglyceride, and HDL-C, the ICCs were 0.80, 0.68, and 0.91; their respective within-person CVs were 23.0%, 20.6%, and 8.2%. The MDC95 for HOMA-IR was 2.3 and for TG/HDL-C was 1.4. The MDD95 for a sample of n=100 for HOMA-IR was 0.8 and for TG/HDL-C was 0.6. Short-term repeatability was fair to good for HOMA-IR and excellent for TG/HDL-C according to suggested benchmarks, reflecting the short-term variability of their analytes. These measurement properties can inform the use of these indexes in clinical and population-based studies.

  7. Simulating the Effects of Short-Term Synaptic Plasticity on Postsynaptic Dynamics in the Globus Pallidus

    Directory of Open Access Journals (Sweden)

    Moran eBrody

    2013-08-01

    Full Text Available The rat globus pallidus (GP is one of the nuclei of the basal ganglia and plays an important role in a variety of motor and cognitive processes. In vivo studies have shown that repetitive stimulation evokes complex modulations of GP activity. In vitro and computational studies have suggested that short-term synaptic plasticity (STP could be one of the underlying mechanisms. The current study used simplified single compartment modeling to explore the possible effect of STP on the activity of GP neurons during low and high frequency stimulation. To do this we constructed a model of a GP neuron connected to a small network of neurons from the three major input sources to GP neurons: striatum (Str, subthalamic nucleus (STN and GP collaterals. All synapses were implemented with a kinetic model of STP. The in vitro recordings of responses to low frequency repetitive stimulation were highly reconstructed, including rate changes and locking to the stimulus. Mainly involved were fast forms of plasticity which have been found at these synapses. . The simulations were qualitatively compared to a data set previously recorded in vitro in our lab. Reconstructions of experimental responses to high frequency stimulation required adding slower forms of plasticity to the STN and GP collateral synapses, as well as adding metabotropic receptors to the STN-GP synapses. These finding suggest the existence of as yet unreported slower short-term dynamics in the GP. The computational model made additional predictions about GP activity during low and high frequency stimulation that may further our understanding of the mechanisms underlying repetative stimulation of the GP.

  8. Short-term Suicide Risk After Psychiatric Hospital Discharge.

    Science.gov (United States)

    Olfson, Mark; Wall, Melanie; Wang, Shuai; Crystal, Stephen; Liu, Shang-Min; Gerhard, Tobias; Blanco, Carlos

    2016-11-01

    Although psychiatric inpatients are recognized to be at increased risk for suicide immediately after hospital discharge, little is known about the extent to which their short-term suicide risk varies across groups with major psychiatric disorders. To describe the risk for suicide during the 90 days after hospital discharge for adults with first-listed diagnoses of depressive disorder, bipolar disorder, schizophrenia, substance use disorder, and other mental disorders in relation to inpatients with diagnoses of nonmental disorders and the general population. This national retrospective longitudinal cohort included inpatients aged 18 to 64 years in the Medicaid program who were discharged with a first-listed diagnosis of a mental disorder (depressive disorder, bipolar disorder, schizophrenia, substance use disorder, and other mental disorder) and a 10% random sample of inpatients with diagnoses of nonmental disorders. The cohort included 770 643 adults in the mental disorder cohort, 1 090 551 adults in the nonmental disorder cohort, and 370 deaths from suicide from January 1, 2001, to December 31, 2007. Data were analyzed from March 5, 2015, to June 6, 2016. Suicide rates per 100 000 person-years were determined for each study group during the 90 days after hospital discharge and the demographically matched US general population. Adjusted hazard ratios (ARHs) of short-term suicide after hospital discharge were also estimated by Cox proportional hazards regression models. Information on suicide as a cause of death was obtained from the National Death Index. In the overall population of 1 861 194 adults (27% men; 73% women; mean [SD] age, 35.4 [13.1] years), suicide rates for the cohorts with depressive disorder (235.1 per 100 000 person-years), bipolar disorder (216.0 per 100 000 person-years), schizophrenia (168.3 per 100 000 person-years), substance use disorder (116.5 per 100 000 person-years), and other mental disorders (160.4 per 100 000

  9. Genetic deletion of melanin-concentrating hormone neurons impairs hippocampal short-term synaptic plasticity and hippocampal-dependent forms of short-term memory.

    Science.gov (United States)

    Le Barillier, Léa; Léger, Lucienne; Luppi, Pierre-Hervé; Fort, Patrice; Malleret, Gaël; Salin, Paul-Antoine

    2015-11-01

    The cognitive role of melanin-concentrating hormone (MCH) neurons, a neuronal population located in the mammalian postero-lateral hypothalamus sending projections to all cortical areas, remains poorly understood. Mainly activated during paradoxical sleep (PS), MCH neurons have been implicated in sleep regulation. The genetic deletion of the only known MCH receptor in rodent leads to an impairment of hippocampal dependent forms of memory and to an alteration of hippocampal long-term synaptic plasticity. By using MCH/ataxin3 mice, a genetic model characterized by a selective deletion of MCH neurons in the adult, we investigated the role of MCH neurons in hippocampal synaptic plasticity and hippocampal-dependent forms of memory. MCH/ataxin3 mice exhibited a deficit in the early part of both long-term potentiation and depression in the CA1 area of the hippocampus. Post-tetanic potentiation (PTP) was diminished while synaptic depression induced by repetitive stimulation was enhanced suggesting an alteration of pre-synaptic forms of short-term plasticity in these mice. Behaviorally, MCH/ataxin3 mice spent more time and showed a higher level of hesitation as compared to their controls in performing a short-term memory T-maze task, displayed retardation in acquiring a reference memory task in a Morris water maze, and showed a habituation deficit in an open field task. Deletion of MCH neurons could thus alter spatial short-term memory by impairing short-term plasticity in the hippocampus. Altogether, these findings could provide a cellular mechanism by which PS may facilitate memory encoding. Via MCH neuron activation, PS could prepare the day's learning by increasing and modulating short-term synaptic plasticity in the hippocampus. © 2015 Wiley Periodicals, Inc.

  10. 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

    This literature study investigated methods and areas to deduce climate change and climate patterns, looking for short-term cycle phenomena and the means to interpret them. Many groups are actively engaged in intensive climate-related research. Ongoing research might be (overly) simplified into three categories: (1) historic data on weather that can be used for trend analysis and modeling; (2) detailed geological, biological (subfossil), and analytical (geochemical, radiocarbon, etc.) studies covering the last 10,000 years (about since last glaciation); and (3) geological, paleontological, and analytical (geochemical, radiometric, etc.) studies over millions of years. Of importance is our ultimate ability to join these various lines of inquiry into an effective means of interpretation. At this point, the process of integration is fraught with methodological troubles and misconceptions about what each group can contribute. This project has met its goals to the extent that it provided an opportunity to study resource materials and consider options for future effort toward the goal of understanding the natural climate variation that has shaped our current civilization. A further outcome of this project is a proposed methodology based on ''climate sections'' that provides spatial and temporal correlation within a region. The method would integrate cultural and climate data to establish the climate history of a region with increasing accuracy with progressive study and scientific advancement (e. g., better integration of regional and global models). The goal of this project is to better understand natural climatic variations in the recent past (last 5000 years). The information generated by this work is intended to provide better context within which to examine global climate change. The ongoing project will help to establish a basis upon which to interpret late Holocene short-term climate variability as evidenced in various studies in the northern

  11. Dissociating Measures of Consciousness from Measures of Short-Term Memory

    DEFF Research Database (Denmark)

    Sørensen, Thomas Alrik; Ásgeirsson, Árni Gunnar; Staugaard, Camilla Funch

    other. Previously, we have demonstrated that introspective access and conscious content can affect ERP’s and behaviour in observers during a visual task (Overgaard, Koivisto, Sørensen, Vangkilde, & Revonsuo, 2006). If introspective access to content can modulate performance, one may question...... if conscious content simply can be reduced to a cognitive process like short-term memory. In two experiments, we combined two different measures of short-term memory capacity to investigate how manipulations of set-size affect performance in observers with the Perceptual Awareness Scale (PAS) to measure...... found that increasing task-load through varying set-sizes affected performance in the short-term memory task as well as in the PAS ratings systematically in the both experiments. Interestingly, the two experiments also revealed systematic set-size effect within each of the individual PAS categories...

  12. Dimension-based attention in visual short-term memory.

    Science.gov (United States)

    Pilling, Michael; Barrett, Doug J K

    2016-07-01

    We investigated how dimension-based attention influences visual short-term memory (VSTM). This was done through examining the effects of cueing a feature dimension in two perceptual comparison tasks (change detection and sameness detection). In both tasks, a memory array and a test array consisting of a number of colored shapes were presented successively, interleaved by a blank interstimulus interval (ISI). In Experiment 1 (change detection), the critical event was a feature change in one item across the memory and test arrays. In Experiment 2 (sameness detection), the critical event was the absence of a feature change in one item across the two arrays. Auditory cues indicated the feature dimension (color or shape) of the critical event with 80 % validity; the cues were presented either prior to the memory array, during the ISI, or simultaneously with the test array. In Experiment 1, the cue validity influenced sensitivity only when the cue was given at the earliest position; in Experiment 2, the cue validity influenced sensitivity at all three cue positions. We attributed the greater effectiveness of top-down guidance by cues in the sameness detection task to the more active nature of the comparison process required to detect sameness events (Hyun, Woodman, Vogel, Hollingworth, & Luck, Journal of Experimental Psychology: Human Perception and Performance, 35; 1140-1160, 2009).

  13. 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.

  14. Visual short-term memory for oriented, colored objects

    Science.gov (United States)

    Shin, Hongsup; Ma, Wei Ji

    2017-01-01

    A central question in the study of visual short-term memory (VSTM) has been whether its basic units are objects or features. Most studies addressing this question have used change detection tasks in which the feature value before the change is highly discriminable from the feature value after the change. This approach assumes that memory noise is negligible, which recent work has shown not to be the case. Here, we investigate VSTM for orientation and color within a noisy-memory framework, using change localization with a variable magnitude of change. A specific consequence of the noise is that it is necessary to model the inference (decision) stage. We find that (a) orientation and color have independent pools of memory resource (consistent with classic results); (b) an irrelevant feature dimension is either encoded but ignored during decision-making, or encoded with low precision and taken into account during decision-making; and (c) total resource available in a given feature dimension is lower in the presence of task-relevant stimuli that are neutral in that feature dimension. We propose a framework in which feature resource comes both in packaged and in targeted form. PMID:28813568

  15. Reconciling long-term cultural diversity and short-term collective social behavior.

    Science.gov (United States)

    Valori, Luca; Picciolo, Francesco; Allansdottir, Agnes; Garlaschelli, Diego

    2012-01-24

    An outstanding open problem is whether collective social phenomena occurring over short timescales can systematically reduce cultural heterogeneity in the long run, and whether offline and online human interactions contribute differently to the process. Theoretical models suggest that short-term collective behavior and long-term cultural diversity are mutually excluding, since they require very different levels of social influence. The latter jointly depends on two factors: the topology of the underlying social network and the overlap between individuals in multidimensional cultural space. However, while the empirical properties of social networks are intensively studied, little is known about the large-scale organization of real societies in cultural space, so that random input specifications are necessarily used in models. Here we use a large dataset to perform a high-dimensional analysis of the scientific beliefs of thousands of Europeans. We find that interopinion correlations determine a nontrivial ultrametric hierarchy of individuals in cultural space. When empirical data are used as inputs in models, ultrametricity has strong and counterintuitive effects. On short timescales, it facilitates a symmetry-breaking phase transition triggering coordinated social behavior. On long timescales, it suppresses cultural convergence by restricting it within disjoint groups. Moreover, ultrametricity implies that these results are surprisingly robust to modifications of the dynamical rules considered. Thus the empirical distribution of individuals in cultural space appears to systematically optimize the coexistence of short-term collective behavior and long-term cultural diversity, which can be realized simultaneously for the same moderate level of mutual influence in a diverse range of online and offline settings.

  16. 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.

  17. Some risks related to the short-term trading of natural gas

    International Nuclear Information System (INIS)

    Mazighi, Ahmed El Hachemi

    2004-01-01

    Traditionally guided by long-term contracts, the international natural gas trade is experiencing new methods of operating, based on the short term and more flexibility. Today, indeed, the existence of uncommitted quantities of natural gas, combined with gas price discrepancies among different regions of the world, gives room for the expansion of the spot-trading of gas. The main objective of this paper is to discuss three fundamental risks related to the short-term trading of natural gas: volume risk, price risk and infrastructure risk. The defenders of globalisation argue that the transition from the long-term to the short-term trading of natural gas is mainly a question of access to gas reserves, decreasing costs of gas liquefaction, the building of liquefied natural gas (LNG) fleets and regasification facilities and third-party access to the infrastructure. This process needs to be as short as possible, so that the risks related to the transition process will disappear rapidly. On the other hand, the detractors of globalisation put the emphasis on the complexity of the gas value chain and on the fact that eliminating long-term contracts increases the risks inherent to the international natural gas business. In this paper, we try to untangle and assess the risks related to the short-term trading of natural gas. Our main conclusions are: the short-term trading of gas is far from riskless; volume risk requires stock-building in both consuming and producing countries; price risk, through the high volatility for gas, induces an increase in options prices; there is no evidence to suggest that money-lenders' appetite for financing gas infrastructure projects will continue in a short-term trading system. This would be a threat to consumers' security of supply. (Author)

  18. 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.

  19. 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.

  20. The role of short-term memory impairment in nonword repetition, real word repetition, and nonword decoding: A case study.

    Science.gov (United States)

    Peter, Beate

    2017-09-21

    In a companion study, adults with dyslexia and adults with a probable history of childhood apraxia of speech showed evidence of difficulty with processing sequential information during nonword repetition, multisyllabic real word repetition and nonword decoding. Results suggested that some errors arose in visual encoding during nonword reading, all levels of processing but especially short-term memory storage/retrieval during nonword repetition, and motor planning and programming during complex real word repetition. To further investigate the role of short-term memory, a participant with short-term memory impairment (MI) was recruited. MI was confirmed with poor performance during a sentence repetition and three nonword repetition tasks, all of which have a high short-term memory load, whereas typical performance was observed during tests of reading, spelling, and static verbal knowledge, all with low short-term memory loads. Experimental results show error-free performance during multisyllabic real word repetition but high counts of sequence errors, especially migrations and assimilations, during nonword repetition, supporting short-term memory as a locus of sequential processing deficit during nonword repetition. Results are also consistent with the hypothesis that during complex real word repetition, short-term memory is bypassed as the word is recognized and retrieved from long-term memory prior to producing the word.

  1. Conceptual Short Term Memory in perception and thought

    Directory of Open Access Journals (Sweden)

    Mary C. Potter

    2012-04-01

    Full Text Available Conceptual short term memory (CSTM is a theoretical construct that provides one answer to the question of how perceptual and conceptual processes are related. CSTM is a mental buffer and processor in which current perceptual stimuli and their associated concepts from long term memory (LTM are represented briefly, allowing meaningful patterns or structures to be identified (Potter, 1993, 1999, 2009. CSTM is different from and complementary to other proposed forms of working memory: it is engaged extremely rapidly, has a large but ill-defined capacity, is largely unconscious, and is the basis for the unreflective understanding that is characteristic of everyday experience. The key idea behind CSTM is that most cognitive processing occurs without review or rehearsal of material in standard working memory and with little or no conscious reasoning. When one perceives a meaningful stimulus such as a word, picture, or object, it is rapidly identified at a conceptual level and in turn activates associated information from long term memory. New links among concurrently active concepts are formed in CSTM, shaped by parsing mechanisms of language or grouping principles in scene perception and by higher-level knowledge and current goals. The resulting structure represents the gist of a picture or the meaning of a sentence, and it is this structure that we are conscious of and that can be maintained in standard working memory and consolidated into long term memory. Momentarily activated information that is not incorporated into such structures either never becomes conscious or is rapidly forgotten. This whole cycle--identification of perceptual stimuli, memory recruitment, structuring, consolidation in long term memory, and forgetting of nonstructured material--may occur in less than 1 second when viewing a pictured scene or reading a sentence. The evidence for such a process is reviewed and its implications for the relation of perception and cognition are

  2. 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).

  3. 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.

  4. Short-term tocolytics for preterm delivery – current perspectives

    Directory of Open Access Journals (Sweden)

    Haas DM

    2014-03-01

    Full Text Available David M Haas, Tara Benjamin, Renata Sawyer, Sara K QuinneyDepartment of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN, USAAbstract: Administration of short-term tocolytic agents can prolong pregnancy for women in preterm labor. Prolonging pregnancy has many benefits because it allows for other proven interventions, such as antenatal corticosteroid administration, to be accomplished. This review provides an overview of currently utilized tocolytic agents and the evidence demonstrating their efficacy for prolonging pregnancy by at least 48 hours. General pharmacological principles for the clinician regarding drugs in pregnancy are also briefly discussed. In general, while the choice of the best first-line short-term tocolytic drug is not clear, it is evident that use of these agents has a clear place in current obstetric therapeutics.Keywords: tocolytics, short-term, preterm delivery

  5. The stability of short-term hearing outcome after stapedotomy

    DEFF Research Database (Denmark)

    Andersen, Steven Arild Wuyts; Öhman, Malin Charlotta; Sørensen, Mads Sølvsten

    2015-01-01

    CONCLUSION: Current guidelines recommend reporting short-term results of > 12 months after treatment of conductive hearing loss. This study suggests that short-term hearing results after stapedotomy recorded at the 3-month follow-up are without loss of vital information compared with data from...... the currently recommended > 12-month follow-up. The use of 3-month data in reporting outcome could reduce the bias inherent to the loss to follow-up at 12 months. OBJECTIVE: To investigate the stability of short-term postoperative hearing after stapedotomy for otosclerosis. METHODS: This was a prospective...... database study; 371 cases with otosclerosis were registered in the database between August 2004 and June 2013. We included the 166 primary cases and 37 revision cases that had attended both follow-ups. RESULTS: The mean changes in postoperative hearing thresholds between the 3-month and 12-month follow...

  6. Recent onmiddellijk geheugenonderzoek bij zwakzinnigen [Investigation of short term memory in mentally retarded subjects

    NARCIS (Netherlands)

    Bunt, A.A.

    1975-01-01

    The aim of this literature review is to get a preliminary answer to the problem of the type of information processing deficit of undifferentiated retardates (with an IQ of about 70). Taking the topic of verbal short-term memory as a framework, it appears that children or adults of a subnormal

  7. Experimental Study of Short-Term Training in Social Cognition in Pre-Schoolers

    Science.gov (United States)

    Houssa, Marine; Nader-Grosbois, Nathalie; Jacobs, Emilie

    2014-01-01

    Using an experimental approach, our study examined the differentiated effects on pre-schoolers' social cognition of two short-term social information processing (SIP) and Theory of Mind (ToM) training sessions dealing with emotions and beliefs. The links between ToM, SIP, and social adjustment or externalizing behavior were examined. 47…

  8. Visual Short-Term Memory Capacity for Simple and Complex Objects

    Science.gov (United States)

    Luria, Roy; Sessa, Paola; Gotler, Alex; Jolicoeur, Pierre; Dell'Acqua, Roberto

    2010-01-01

    Does the capacity of visual short-term memory (VSTM) depend on the complexity of the objects represented in memory? Although some previous findings indicated lower capacity for more complex stimuli, other results suggest that complexity effects arise during retrieval (due to errors in the comparison process with what is in memory) that is not…

  9. Short-Term Memory Stages in Sign vs. Speech: The Source of the Serial Span Discrepancy

    Science.gov (United States)

    Hall, Matthew L.; Bavelier, Daphne

    2011-01-01

    Speakers generally outperform signers when asked to recall a list of unrelated verbal items. This phenomenon is well established, but its source has remained unclear. In this study, we evaluate the relative contribution of the three main processing stages of short-term memory--perception, encoding, and recall--in this effect. The present study…

  10. Potentials of short term and long term cryopreserved sperm of the ...

    African Journals Online (AJOL)

    Jane

    2010-10-11

    Oct 11, 2010 ... the short-term and long-term storage of catfish sperm would enable economic growth in fresh water catfish aquaculture and reduce Nigeria's reliance on imported fish. Cryopreservation is the process of storing biological materials at below freezing temperatures using cryodiluents to protect the biological ...

  11. Phonological and Sensory Short-Term Memory Are Correlates and Both Affected in Developmental Dyslexia

    Science.gov (United States)

    Laasonen, Marja; Virsu, Veijo; Oinonen, Suvi; Sandbacka, Mirja; Salakari, Anita; Service, Elisabet

    2012-01-01

    We investigated whether poor short-term memory (STM) in developmental dyslexia affects the processing of sensory stimulus sequences in addition to phonological material. STM for brief binary non-verbal stimuli (light flashes, tone bursts, finger touches, and their crossmodal combinations) was studied in 20 Finnish adults with dyslexia and 24…

  12. Short term and long term impact of vegetation recovery on seasonal streamflows

    Science.gov (United States)

    Lana-Renault, Noemí; Karssenberg, Derek; Bierkens, Mark; Serrano Muela, M. Pilar

    2015-04-01

    Changes in stream flow due to changes in vegetation cover have been reported worldwide and it is commonly accepted that a decrease in annual water follows afforestation, and the opposite effect occurs when forests are converted into shorter vegetation or croplands. Besides the focus put on the changes in annual water yields, there is a growing interest in looking at the effects of afforestation on the seasonal pattern and duration of stream flows. This is important from an ecological point of view and for water resources management, especially in locations where seasonal water shortages are reported. Conclusions in this respect are not straight forward because of the complex relationships among water fluxes at sub-annual scale, especially the existing temporal lags between vegetation processes (evaporation and transpiration) and the soil water storage and water outflows. Changes in stream flows due to afforestation have been mostly explained by changes in canopy interception and vegetation evapotranspiration. However, a land cover change also modifies other associated landscape characteristics such as soil properties or topography, especially when considering long-term impacts In this study, we provide a quantitative analysis of the relative contribution of soils and vegetation to changes on stream flows in relation to vegetation recovery. This way we can assess the hydrological impact of short-term and long-term vegetation recovery. This is of special interest in order to assess the overall hydrological impact of natural re-vegetation of former agricultural land or deforested areas, and of reforestation programs. For this purpose, we use an approach based on hydrological data collected in two neighboring small catchments with similar topography but different land cover (abandoned land recolonized by shrubs and natural forest, respectively), and an advanced modeling approach based on the application of a process-based hydrological model. The two catchments are

  13. 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.

  14. [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.

  15. Emotion in short-term psychotherapy: an introduction.

    Science.gov (United States)

    Magnavita, Jeffrey J

    2006-05-01

    Our understanding of the importance of emotion in psychopathology, personality, and psychotherapy has been rapidly advancing. New findings from neuroscience support the centrality of emotion as a convergent force in shaping individuals and relationships. Emotion-focused short-term psychotherapy capitalizes on the power of emotion to accelerate the course of treatment. This article provides a brief historical background on the development of affective science, offers some ways in which emotion can enhance clinical utility, and introduces the Journal of Clinical Psychology: In Session issue devoted to emotion-focused, short-term psychotherapy. (c) 2006 Wiley Periodicals, Inc. J Clin Psychol: In Session 62: 517-522, 2006.

  16. A short-term group with drug users in prison

    Directory of Open Access Journals (Sweden)

    Roberta Campo

    2014-09-01

    Full Text Available This article describes a short term group, according to the viewpoint of group analysis theory. The experience was made in the prison of Sicily. The group was composed by prisoners in the protected area with issues of addiction. The article highlights the usefulness of a work on the Motivation to change through the device of the group. Furthermore, it underlines how much of the work in this context was to encourage participants in the transition to reflection, critical to work on yourself. We walk through fragments of sessions, those were the main themes emerged: the relationship, responsibility, guilt, punishment.Keywords: Addiction, Motivation to change, Short-term group

  17. ANN-based short-term wastewater flow prediction for better WWTP control

    OpenAIRE

    Plonka, Leslaw; Miksch, Korneliusz

    2010-01-01

    This paper presents an approach to predict the amount of the wastewater which enters wastewater treatment plant, using artificial neural network. The method presented can be used to give short-term predictions of wastewater inflow-rate. The described neural network model uses a very tiny set of data commonly collected by WWTP control systems. ? ?????? ?????????? ?????? ?? ????????????? ????????? ??????? ???, ?? ????????? ?? ???????????? ? ????????????? ??????? ????????? ??????. ?????...

  18. Short-term effects of a peer group intervention for HIV prevention ...

    African Journals Online (AJOL)

    This report describes the implementation and short-term results of a peer group intervention for HIV prevention on the HIV-related attitudes, knowledge and behaviours of primary school teachers in Malawi. The intervention, based on the social-cognitive learning model, took place in 2000 at two teacher training colleges ...

  19. SEXUAL BEHAVIOUR, SPERM QUANTITY AND QUALITY AFTER SHORT-TERM STREPTOZOTOCIN-INDUCED HYPERGLYCAEMIA IN RATS.

    Science.gov (United States)

    Studies of diabetes mellitus in the streptozotocin rat model suggest that sexual dysfunctions may result from diabetes-induced alterations of the neuroendocrine-reproductive tract axis. Our investigation was performed to better define the effects of short-term hyperglycemia on ra...

  20. Review of short-term demand forecasting methods and selection of ...

    African Journals Online (AJOL)

    Review of short-term demand forecasting methods and selection of the appropriate model for softwood sawmills in Tanzania. ... Tanzania Journal of Forestry and Nature Conservation. Journal Home ... This paper reviewed and tested forecasting methods for use-appropriateness in forecasting lumber demands in the sawmill

  1. Neural Network-based Load Forecasting and Error Implication for Short-term Horizon

    NARCIS (Netherlands)

    Khuntia, S.R.; Rueda Torres, José L.; van der Meijden, M.A.M.M.

    2016-01-01

    Load forecasting is considered vital along with many other important entities required for assessing the reliability of power system. Thus, the primary concern is not to forecast load with a novel model, rather to forecast load with the highest accuracy. Short-term load forecast accuracy is often

  2. Temporal Clustering and Sequencing in Short-Term Memory and Episodic Memory

    Science.gov (United States)

    Farrell, Simon

    2012-01-01

    A model of short-term memory and episodic memory is presented, with the core assumptions that (a) people parse their continuous experience into episodic clusters and (b) items are clustered together in memory as episodes by binding information within an episode to a common temporal context. Along with the additional assumption that information…

  3. Short-term responses to selection for parameters of the allometric ...

    African Journals Online (AJOL)

    model also seems to be of value in genetic studies and some of its parameters ... day without withholding food and water prior to measure- ment. ..... and observed responses (Figure 2) compared well during the initial stages of selection (three and four generations respect- ively). In the short term, the direct responses to ...

  4. Unmasking Stem/Progenitor Cell Properties in Differentiated Epithelial Cells Using Short-term Transplantation

    National Research Council Canada - National Science Library

    Lewis, Michael T

    2007-01-01

    ...) To determine the range of mammary stem cell types participating in gland regeneration. 2) To develop the short-term transplantation assay as a means by which critical regulators of stem and progenitor cell behavior can be discovered and evaluated. Relevance: Studies will provide a direct test of prevailing stem cell models.

  5. Unmasking Stem/Progenitor Cell Properties in Differentiated Epithelial Cells Using Short-term Transplantation

    National Research Council Canada - National Science Library

    Lewis, Michael T

    2006-01-01

    ...) To determine the range of mammary stem cell types participating in gland regeneration. 2) To develop the short-term transplantation assay as a means by which critical regulators of stem and progenitor cell behavior can be discovered and evaluated. Relevance: Studies will provide a direct test of prevailing stem cell models.

  6. Short-term carbon partitioning fertilizer responses vary among two full-sib loblolly pine clones

    Science.gov (United States)

    Jeremy P. Stovall; John R. Seiler; Thomas R. Fox

    2012-01-01

    We investigated the effects of fertilizer application on the partitioning of gross primary productivity (GPP) between contrasting full-sib clones of Pinus taeda (L.). Our objective was to determine if fertilizer growth responses resulted from similar short-term changes to partitioning. A modeling approach incorporating respiratory carbon (C) fluxes,...

  7. Short-Term Memory for Order but Not for Item Information Is Impaired in Developmental Dyslexia

    Science.gov (United States)

    Hachmann, Wibke M.; Bogaerts, Louisa; Szmalec, Arnaud; Woumans, Evy; Duyck, Wouter; Job, Remo

    2014-01-01

    Recent findings suggest that people with dyslexia experience difficulties with the learning of serial order information during the transition from short-to long-term memory (Szmalec et al. "Journal of Experimental Psychology: Learning, Memory, & Cognition" 37(5): 1270-1279, 2011). At the same time, models of short-term memory…

  8. A Combined Methodology of Adaptive Neuro-Fuzzy Inference System and Genetic Algorithm for Short-term Energy Forecasting

    Directory of Open Access Journals (Sweden)

    KAMPOUROPOULOS, K.

    2014-02-01

    Full Text Available This document presents an energy forecast methodology using Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithms (GA. The GA has been used for the selection of the training inputs of the ANFIS in order to minimize the training result error. The presented algorithm has been installed and it is being operating in an automotive manufacturing plant. It periodically communicates with the plant to obtain new information and update the database in order to improve its training results. Finally the obtained results of the algorithm are used in order to provide a short-term load forecasting for the different modeled consumption processes.

  9. Short-Term Limb Immobilization Affects Cognitive Motor Processes

    Science.gov (United States)

    Toussaint, Lucette; Meugnot, Aurore

    2013-01-01

    We examined the effects of a brief period of limb immobilization on the cognitive level of action control. A splint placed on the participants' left hand was used as a means of immobilization. We used a hand mental rotation task to investigate the immobilization-induced effects on motor imagery performance (Experiments 1 and 2) and a number mental…

  10. Inter-daily variability of a strong thermally-driven wind system over the Atacama Desert of South America: synoptic forcing and short-term predictability using the GFS global model

    Science.gov (United States)

    Jacques-Coper, Martín; Falvey, Mark; Muñoz, Ricardo C.

    2015-07-01

    Crucial aspects of a strong thermally-driven wind system in the Atacama Desert in northern Chile during the extended austral winter season (May-September) are studied using 2 years of measurement data from the Sierra Gorda 80-m meteorological mast (SGO, 22° 56' 24″ S; 69° 7' 58″ W, 2,069 m above sea level (a.s.l.)). Daily cycles of atmospheric variables reveal a diurnal (nocturnal) regime, with northwesterly (easterly) flow and maximum mean wind speed of 8 m/s (13 m/s) on average. These distinct regimes are caused by pronounced topographic conditions and the diurnal cycle of the local radiative balance. Wind speed extreme events of each regime are negatively correlated at the inter-daily time scale: High diurnal wind speed values are usually observed together with low nocturnal wind speed values and vice versa. The associated synoptic conditions indicate that upper-level troughs at the coastline of southwestern South America reinforce the diurnal northwesterly wind, whereas mean undisturbed upper-level conditions favor the development of the nocturnal easterly flow. We analyze the skill of the numerical weather model Global Forecast System (GFS) in predicting wind speed at SGO. Although forecasted wind speeds at 800 hPa do show the diurnal and nocturnal phases, observations at 80 m are strongly underestimated by the model. This causes a pronounced daily cycle of root-mean-squared error (RMSE) and bias in the forecasts. After applying a simple Model Output Statistics (MOS) post-processing, we achieve a good representation of the wind speed intra-daily and inter-daily variability, a first step toward reducing the uncertainties related to potential wind energy projects in the region.

  11. 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)

  12. 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

  13. Absenteeism and short-term disability associated with breast cancer.

    Science.gov (United States)

    Fu, Alex Z; Chen, Lei; Sullivan, Sean D; Christiansen, Neal P

    2011-11-01

    Few data exist related to the impact of breast cancer on work absenteeism and short-term disability. This retrospective study estimated the extent and costs of breast cancer-associated production loss using a large medical and pharmacy claims database from a US commercially insured population between January 2003 and December 2007. Women aged ≥ 18 years with ≥ 2 breast cancer diagnoses within 90 days were selected. Controls were matched to cases based on index date (first breast cancer diagnosis), age, region, employer, and health insurance type. Outcomes were days absent from work and days with short-term disability. Costs were estimated using daily wage rates. 856 and 2,668 patients were selected for absenteeism and short-term disability, respectively, with a mean age of 49 and 50 years. Average number of absenteeism days was 35 and 21, and short-term disability days were 51 and 5, for cases and controls, respectively, within the post-index year (both P disability were $1,911 and $6,157 (P breast cancer patient per year. This study suggests that breast cancer is associated with work-related productivity loss within the first year of diagnosis that may be a substantial cost to employers.

  14. 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)

  15. 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…

  16. 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...

  17. 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...

  18. 22 CFR 62.21 - Short-term scholars.

    Science.gov (United States)

    2010-04-01

    ... shall satisfy the definition of a short-term scholar as set forth in § 62.4. (e) Cross-cultural... shall be exempted from the requirements of providing cross-cultural activities and orientation as set... lecturing, observing, consulting, training, or demonstrating special skills at research institutions...

  19. 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. ... and fracture tables are not readily available. They have excellent to good outcomes in rate of callus formation, limb length and limb alignment outcomes.

  20. Short-term storage of Atlantic sturgeon spermatozoa

    Science.gov (United States)

    There is significant interest to restore the Atlantic sturgeon, a species of concern. Biologists are interested in both the short-term storage and cryopreservation of semen to maximize availability of viable spermatozoa whenever a rare ripe female is found and available for spawning. We conducted sh...