WorldWideScience

Sample records for modeling short-term processes

  1. 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

  2. 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

  3. A continuous time model for a short-term multiproduct batch process scheduling

    Directory of Open Access Journals (Sweden)

    Jenny Díaz Ramírez

    2018-01-01

    Full Text Available In the chemical industry, it is common to find production systems characterized by having a single stage or a previously identified bottleneck stage, with multiple non-identical parallel stations and with setup costs that depend on the production sequence. This paper proposes a mixed integer production-scheduling model that identifies lot size and product sequence that maximize profit. It considers multiple typical industry conditions, such as penalties for noncompliance or out of service periods of the productive units (or stations for preventive maintenance activities. The model was validated with real data from an oil chemical company.  Aiming to analyze its performance, we applied the model to 155 instances of production, which were obtained using Monte Carlo technique on the historical production data of the same company.  We obtained an average 12 % reduction in the total cost of production and a 19 % increase in the estimated profit.

  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. Abnormal presynaptic short-term plasticity and information processing in a mouse model of fragile X syndrome.

    Science.gov (United States)

    Deng, Pan-Yue; Sojka, David; Klyachko, Vitaly A

    2011-07-27

    Fragile X syndrome (FXS) is the most common inherited form of intellectual disability and the leading genetic cause of autism. It is associated with the lack of fragile X mental retardation protein (FMRP), a regulator of protein synthesis in axons and dendrites. Studies on FXS have extensively focused on the postsynaptic changes underlying dysfunctions in long-term plasticity. In contrast, the presynaptic mechanisms of FXS have garnered relatively little attention and are poorly understood. Activity-dependent presynaptic processes give rise to several forms of short-term plasticity (STP), which is believed to control some of essential neural functions, including information processing, working memory, and decision making. The extent of STP defects and their contributions to the pathophysiology of FXS remain essentially unknown, however. Here we report marked presynaptic abnormalities at excitatory hippocampal synapses in Fmr1 knock-out (KO) mice leading to defects in STP and information processing. Loss of FMRP led to enhanced responses to high-frequency stimulation. Fmr1 KO mice also exhibited abnormal synaptic processing of natural stimulus trains, specifically excessive enhancement during the high-frequency spike discharges associated with hippocampal place fields. Analysis of individual STP components revealed strongly increased augmentation and reduced short-term depression attributable to loss of FMRP. These changes were associated with exaggerated calcium influx in presynaptic neurons during high-frequency stimulation, enhanced synaptic vesicle recycling, and enlarged readily-releasable and reserved vesicle pools. These data suggest that loss of FMRP causes abnormal STP and information processing, which may represent a novel mechanism contributing to cognitive impairments in FXS.

  6. 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

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

    OpenAIRE

    Imanaka, Kuniyasu; Funase, Kozo; Yamauchi, Masaki

    1995-01-01

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

  8. 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.

  9. Short term load forecasting: two stage modelling

    Directory of Open Access Journals (Sweden)

    SOARES, L. J.

    2009-06-01

    Full Text Available This paper studies the hourly electricity load demand in the area covered by a utility situated in the Seattle, USA, called Puget Sound Power and Light Company. Our proposal is put into proof with the famous dataset from this company. We propose a stochastic model which employs ANN (Artificial Neural Networks to model short-run dynamics and the dependence among adjacent hours. The model proposed treats each hour's load separately as individual single series. This approach avoids modeling the intricate intra-day pattern (load profile displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is evaluated in similiar mode a TLSAR (Two-Level Seasonal Autoregressive model proposed by Soares (2003 using the years of 1995 and 1996 as the holdout sample. Moreover, we conclude that non linearity is present in some series of these data. The model results are analyzed. The experiment shows that our tool can be used to produce load forecasting in tropical climate places.

  10. 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.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  12. Morphological processing with deficient phonological short-term memory.

    Science.gov (United States)

    Kavé, Gitit; Ze'ev, Hagit Bar; Lev, Anita

    2007-07-01

    This paper investigates the processing of Hebrew derivational morphology in an individual (S.E.) with deficient phonological short-term memory. In comparison to 10 age- and education-matched men, S.E. was impaired on digit span tasks and demonstrated no recency effect in word list recall. S.E. had low word retention span, but he exhibited phonological similarity and word length effects. His ability to make lexical decisions was intact. In a paired-associate test S.E. successfully learned semantically and morphologically related pairs but not phonologically related pairs, and his learning of nonwords was facilitated by the presence of Hebrew consonant roots. Semantic and morphological similarity enhanced immediate word recall. Results show that S.E. is capable of conducting morphological decomposition of Hebrew-derived words despite his phonological deficit, suggesting that transient maintenance of morphological constituents is independent of temporary storage and rehearsal of phonological codes, and that each is processed separately within short-term memory.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  14. 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.

  15. 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.

  16. 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

  17. Enhanced long-term and impaired short-term spatial memory in GluA1 AMPA receptor subunit knockout mice: evidence for a dual-process memory model.

    Science.gov (United States)

    Sanderson, David J; Good, Mark A; Skelton, Kathryn; Sprengel, Rolf; Seeburg, Peter H; Rawlins, J Nicholas P; Bannerman, David M

    2009-06-01

    The GluA1 AMPA receptor subunit is a key mediator of hippocampal synaptic plasticity and is especially important for a rapidly-induced, short-lasting form of potentiation. GluA1 gene deletion impairs hippocampus-dependent, spatial working memory, but spares hippocampus-dependent spatial reference memory. These findings may reflect the necessity of GluA1-dependent synaptic plasticity for short-term memory of recently visited places, but not for the ability to form long-term associations between a particular spatial location and an outcome. This hypothesis is in concordance with the theory that short-term and long-term memory depend on dissociable psychological processes. In this study we tested GluA1-/- mice on both short-term and long-term spatial memory using a simple novelty preference task. Mice were given a series of repeated exposures to a particular spatial location (the arm of a Y-maze) before their preference for a novel spatial location (the unvisited arm of the maze) over the familiar spatial location was assessed. GluA1-/- mice were impaired if the interval between the trials was short (1 min), but showed enhanced spatial memory if the interval between the trials was long (24 h). This enhancement was caused by the interval between the exposure trials rather than the interval prior to the test, thus demonstrating enhanced learning and not simply enhanced performance or expression of memory. This seemingly paradoxical enhancement of hippocampus-dependent spatial learning may be caused by GluA1 gene deletion reducing the detrimental effects of short-term memory on subsequent long-term learning. Thus, these results support a dual-process model of memory in which short-term and long-term memory are separate and sometimes competitive processes.

  18. 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.

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

    Science.gov (United States)

    Nairne, James S

    2002-01-01

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

  20. 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…

  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. Short-Term Power Plant GHG Emissions Forecasting Model

    International Nuclear Information System (INIS)

    Vidovic, D.

    2016-01-01

    In 2010, the share of greenhouse gas (GHG) emissions from power generation in the total emissions at the global level was about 25 percent. From January 1st, 2013 Croatian facilities have been involved in the European Union Emissions Trading System (EU ETS). The share of the ETS sector in total GHG emissions in Croatia in 2012 was about 30 percent, where power plants and heat generation facilities contributed to almost 50 percent. Since 2013 power plants are obliged to purchase all emission allowances. The paper describes the short-term climate forecasting model of greenhouse gas emissions from power plants while covering the daily load diagram of the system. Forecasting is done on an hourly domain typically for one day, it is possible and more days ahead. Forecasting GHG emissions in this way would enable power plant operators to purchase additional or sell surplus allowances on the market at the time. Example that describes the operation of the above mentioned forecasting model is given at the end of the paper.(author).

  3. 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.

  4. 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)

  5. 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."

  6. 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.

  7. 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.

  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

    /Kattegat area and in the western Baltic influence the water mass properties (high oxygen solubility). Eastward oriented transports of these well-oxygenated highly saline water masses may have a significant positive impact on the Baltic cod reproduction volume in the Bornholm Basin. Finally, we analysed how...... large scale and local atmospheric forcing conditions are related to the identified major processes affecting the reproduction volume. (C) 2002 Elsevier Science B.V. All rights reserved....

  9. Short-term generation scheduling model of Fujian hydro system

    Energy Technology Data Exchange (ETDEWEB)

    Wang Jinwen [School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)], E-mail: dr.jinwen.wang@gmail.com

    2009-04-15

    The Fujian hydropower system (FHS) is one of the provincial hydropower systems with the most complicated hydraulic topology in China. This paper describes an optimization program that is required by Fujian Electric Power Company Ltd. (FEPCL) to aid the shift engineers in making decisions with the short-term hydropower scheduling such that the generation benefit can be maximal. The problem involves 27 reservoirs and is formulated as a nonlinear and discrete programming. It is a very challenging task to solve such a large-scale problem. In this paper, the Lagrangian multipliers are introduced to decompose the primal problem into a hydro subproblem and many individual plant-based subproblems, which are respectively solved by the improved simplex-like method (SLM) and the dynamic programming (DP). A numerical example is given and the derived solution is very close to the optimal one, with the distance in benefit less than 0.004%. All the data needed for the numerical example are presented in detail for further tests and studies from more experts and researchers.

  10. Short-term generation scheduling model of Fujian hydro system

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jinwen [School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2009-04-15

    The Fujian hydropower system (FHS) is one of the provincial hydropower systems with the most complicated hydraulic topology in China. This paper describes an optimization program that is required by Fujian Electric Power Company Ltd. (FEPCL) to aid the shift engineers in making decisions with the short-term hydropower scheduling such that the generation benefit can be maximal. The problem involves 27 reservoirs and is formulated as a nonlinear and discrete programming. It is a very challenging task to solve such a large-scale problem. In this paper, the Lagrangian multipliers are introduced to decompose the primal problem into a hydro subproblem and many individual plant-based subproblems, which are respectively solved by the improved simplex-like method (SLM) and the dynamic programming (DP). A numerical example is given and the derived solution is very close to the optimal one, with the distance in benefit less than 0.004%. All the data needed for the numerical example are presented in detail for further tests and studies from more experts and researchers. (author)

  11. Ordered Short-Term Memory Differs in Signers and Speakers: Implications for Models of Short-Term Memory

    Science.gov (United States)

    Bavelier, Daphne; Newport, Elissa L.; Hall, Matt; Supalla, Ted; Boutla, Mrim

    2008-01-01

    Capacity limits in linguistic short-term memory (STM) are typically measured with forward span tasks in which participants are asked to recall lists of words in the order presented. Using such tasks, native signers of American Sign Language (ASL) exhibit smaller spans than native speakers ([Boutla, M., Supalla, T., Newport, E. L., & Bavelier, D.…

  12. 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)

  13. Error analysis of short term wind power prediction models

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-04-15

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

  14. Presynaptic learning and memory with a persistent firing neuron and a habituating synapse: a model of short term persistent habituation.

    Science.gov (United States)

    Ramanathan, Kiruthika; Ning, Ning; Dhanasekar, Dhiviya; Li, Guoqi; Shi, Luping; Vadakkepat, Prahlad

    2012-08-01

    Our paper explores the interaction of persistent firing axonal and presynaptic processes in the generation of short term memory for habituation. We first propose a model of a sensory neuron whose axon is able to switch between passive conduction and persistent firing states, thereby triggering short term retention to the stimulus. Then we propose a model of a habituating synapse and explore all nine of the behavioral characteristics of short term habituation in a two neuron circuit. We couple the persistent firing neuron to the habituation synapse and investigate the behavior of short term retention of habituating response. Simulations show that, depending on the amount of synaptic resources, persistent firing either results in continued habituation or maintains the response, both leading to longer recovery times. The effectiveness of the model as an element in a bio-inspired memory system is discussed.

  15. Ordered short-term memory differs in signers and speakers: Implications for models of short-term memory

    OpenAIRE

    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, Supalla, Newport, & Bavelier, 2004). Here, we test the hypothesis that this population difference reflects differences in the way speakers and signers maintain temporal order information in short-te...

  16. 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.

  17. 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

  18. 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)

  19. A Probabilistic Palimpsest Model of Visual Short-term Memory

    Science.gov (United States)

    Matthey, Loic; Bays, Paul M.; Dayan, Peter

    2015-01-01

    Working memory plays a key role in cognition, and yet its mechanisms remain much debated. Human performance on memory tasks is severely limited; however, the two major classes of theory explaining the limits leave open questions about key issues such as how multiple simultaneously-represented items can be distinguished. We propose a palimpsest model, with the occurrent activity of a single population of neurons coding for several multi-featured items. Using a probabilistic approach to storage and recall, we show how this model can account for many qualitative aspects of existing experimental data. In our account, the underlying nature of a memory item depends entirely on the characteristics of the population representation, and we provide analytical and numerical insights into critical issues such as multiplicity and binding. We consider representations in which information about individual feature values is partially separate from the information about binding that creates single items out of multiple features. An appropriate balance between these two types of information is required to capture fully the different types of error seen in human experimental data. Our model provides the first principled account of misbinding errors. We also suggest a specific set of stimuli designed to elucidate the representations that subjects actually employ. PMID:25611204

  20. 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…

  1. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-07-01

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

  3. 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

  4. 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)

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

    International Nuclear Information System (INIS)

    Lihn, M.L.

    1989-03-01

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

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

    Science.gov (United States)

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

    2016-03-01

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

  7. 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...

  8. Folk music style modelling by recurrent neural networks with long short term memory units

    OpenAIRE

    Sturm, Bob; Santos, João Felipe; Korshunova, Iryna

    2015-01-01

    We demonstrate two generative models created by training a recurrent neural network (RNN) with three hidden layers of long short-term memory (LSTM) units. This extends past work in numerous directions, including training deeper models with nearly 24,000 high-level transcriptions of folk tunes. We discuss our on-going work.

  9. 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…

  10. 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…

  11. Simple and reliable procedure for the evaluation of short-term dynamic processes in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Popovic, D P

    1986-10-01

    An efficient approach is presented to the solution of the short-term dynamics model in power systems. It consists of an adequate algebraic treatment of the original system of nonlinear differential equations, using linearization, decomposition and Cauchy's formula. The simple difference equations obtained in this way are incorporated into a model of the electrical network, which is of a low order compared to the ones usually used. Newton's method is applied to the model formed in this way, which leads to a simple and reliable iterative procedure. The characteristics of the procedure developed are demonstrated on examples of transient stability analysis of real power systems. 12 refs.

  12. 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

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

    Science.gov (United States)

    Jarrold, C; Baddeley, A D

    2001-10-01

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

  14. 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. PMID:25505409

  15. 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.

  16. Competitive short-term and long-term memory processes in spatial habituation.

    Science.gov (United States)

    Sanderson, David J; Bannerman, David M

    2011-04-01

    Exposure to a spatial location leads to habituation of exploration such that, in a novelty preference test, rodents subsequently prefer exploring a novel location to the familiar location. According to Wagner's (1981) theory of memory, short-term and long-term habituation are caused by separate and sometimes opponent processes. In the present study, this dual-process account of memory was tested. Mice received a series of exposure training trials to a location before receiving a novelty preference test. The novelty preference was greater when tested after a short, rather than a long, interval. In contrast, the novelty preference was weaker when exposure training trials were separated by a short, rather than a long interval. Furthermore, it was found that long-term habituation was determined by the independent effects of the amount of exposure training and the number of exposure training trials when factors such as the intertrial interval and the cumulative intertrial interval were controlled. A final experiment demonstrated that a long-term reduction of exploration could be caused by a negative priming effect due to associations formed during exploration. These results provide evidence against a single-process account of habituation and suggest that spatial habituation is determined by both short-term, recency-based memory and long-term, incrementally strengthened memory.

  17. 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

  18. 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...

  19. Short-term and long-term earthquake occurrence models for Italy: ETES, ERS and LTST

    Directory of Open Access Journals (Sweden)

    Maura Murru

    2010-11-01

    Full Text Available This study describes three earthquake occurrence models as applied to the whole Italian territory, to assess the occurrence probabilities of future (M ≥5.0 earthquakes: two as short-term (24 hour models, and one as long-term (5 and 10 years. The first model for short-term forecasts is a purely stochastic epidemic type earthquake sequence (ETES model. The second short-term model is an epidemic rate-state (ERS forecast based on a model that is physically constrained by the application to the earthquake clustering of the Dieterich rate-state constitutive law. The third forecast is based on a long-term stress transfer (LTST model that considers the perturbations of earthquake probability for interacting faults by static Coulomb stress changes. These models have been submitted to the Collaboratory for the Study of Earthquake Predictability (CSEP for forecast testing for Italy (ETH-Zurich, and they were locked down to test their validity on real data in a future setting starting from August 1, 2009.

  20. 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....

  1. 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

  2. Psychological Mindedness and Psychotherapy Process in Short-Term Group Therapy.

    Science.gov (United States)

    Kealy, David; Sierra-Hernandez, Carlos A; Piper, William E; Joyce, Anthony S; Weideman, Rene; Ogrodniczuk, John S

    2017-01-01

    Psychological mindedness is regarded as an important patient characteristic that can influence the course of psychotherapy. The purpose of this study was to investigate the relationship between patients' capacity for psychological mindedness and aspects of the group psychotherapy process as experienced and rated by therapists and other group members. Participants were 110 patients who completed two forms of short-term group therapy for the treatment of complicated grief. Psychological mindedness was assessed at pretreatment by external raters using a video-interview procedure. Group therapists assessed patients' therapeutic work and therapeutic alliance following each group therapy session. Therapists and other group members rated each patient's expression of emotion and provided appraisals of their cohesion to each patient throughout the course of therapy. Psychological mindedness was found to be positively associated with several group process variables as rated by the therapist and other group members.

  3. 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...

  4. Modelling the short term interest with stochastic differential equation in continuous time: linear versus non-linear mode

    OpenAIRE

    2014-01-01

    M.Com. (Financial Economics) Recently, there has been a growth in the bond market. This growth has brought with it an ever-increasing volume and range of interest rate depended derivative products known as interest rate derivatives. Amongst the variables used in pricing these derivative products is the short-term interest rate. A numbers of short-term interest rate models that are used to fit the short-term interest rate exist. Therefore, understanding the features characterised by various...

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

    Directory of Open Access Journals (Sweden)

    Haixiang Zang

    2016-01-01

    Full Text Available 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 (EEMD, runs test (RT, and relevance vector machine (RVM. First, in order to reduce the complexity of data, the original wind power sequence is decomposed into a plurality of intrinsic mode function (IMF components and residual (RES component by using EEMD. Next, we use the RT method to reconstruct the components and obtain three new components characterized by the fine-to-coarse order. Finally, we obtain the overall forecasting results (with preestablished confidence levels by superimposing the forecasting results of each new component. Our results show that, compared with existing methods, our proposed short-term interval forecasting method has less forecasting errors, narrower interval widths, and larger interval coverage percentages. Ultimately, our forecasting model is more suitable for engineering applications and other forecasting methods for new energy.

  6. Short-Term Fuzzy Load Forecasting Model Using Genetic–Fuzzy and Ant Colony–Fuzzy Knowledge Base Optimization

    Directory of Open Access Journals (Sweden)

    Murat Luy

    2018-05-01

    Full Text Available The estimation of hourly electricity load consumption is highly important for planning short-term supply–demand equilibrium in sources and facilities. Studies of short-term load forecasting in the literature are categorized into two groups: classical conventional and artificial intelligence-based methods. Artificial intelligence-based models, especially when using fuzzy logic techniques, have more accurate load estimations when datasets include high uncertainty. However, as the knowledge base—which is defined by expert insights and decisions—gets larger, the load forecasting performance decreases. This study handles the problem that is caused by the growing knowledge base, and improves the load forecasting performance of fuzzy models through nature-inspired methods. The proposed models have been optimized by using ant colony optimization and genetic algorithm (GA techniques. The training and testing processes of the proposed systems were performed on historical hourly load consumption and temperature data collected between 2011 and 2014. The results show that the proposed models can sufficiently improve the performance of hourly short-term load forecasting. The mean absolute percentage error (MAPE of the monthly minimum in the forecasting model, in terms of the forecasting accuracy, is 3.9% (February 2014. The results show that the proposed methods make it possible to work with large-scale rule bases in a more flexible estimation environment.

  7. Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

    Science.gov (United States)

    Kirkil, Gokhan

    2017-04-01

    Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

  8. A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

    Science.gov (United States)

    Fiebig, Florian

    2017-01-01

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and

  9. A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

    Science.gov (United States)

    Fiebig, Florian; Lansner, Anders

    2017-01-04

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Levels of processing and the coding of position cues in motor short-term memory.

    Science.gov (United States)

    Ho, L; Shea, J B

    1978-06-01

    The present study investigated the appropriateness of the levels-of-processing framework of memory for explaining retention of information in motor short-term memory. Subjects were given labels descriptive of the positions to be remembered by the experimenter (EL), were given no labels (NL), or provided their own labels (SL). A control group (CONT) was required to count backwards during the presentation of the criterion positions. The inclusion of a 30-sec filled retention interval as well as 0-sec and 30-sec unfilled retention intervals tested a prediction by Craik and Lockhart (1972), when attention is diverted from an item, information will be lost at a rate appropriate to its level of processing - that is, slower rates for deeper levels. Groups EL and SL had greater accuracy at recall for all three retention intervals than groups CONT and NL. In addition, there was no significant increase in error between 30-sec unfilled and 30-sec filled intervals for groups EL and SL, while there was a significant increase in error for groups CONT and NL. The data were interpreted in terms of Craik and Lockhart's (1972) levels-of-processing approach to memory.

  15. Ontogeny of sensorimotor gating and short-term memory processing throughout the adolescent period in rats

    Directory of Open Access Journals (Sweden)

    Anja A. Goepfrich

    2017-06-01

    Full Text Available Adolescence and puberty are highly susceptible developmental periods during which the neuronal organization and maturation of the brain is completed. The endocannabinoid (eCB system, which is well known to modulate cognitive processing, undergoes profound and transient developmental changes during adolescence. With the present study we were aiming to examine the ontogeny of cognitive skills throughout adolescence in male rats and clarify the potential modulatory role of CB1 receptor signalling. Cognitive skills were assessed repeatedly every 10th day in rats throughout adolescence. All animals were tested for object recognition memory and prepulse inhibition of the acoustic startle reflex. Although cognitive performance in short-term memory as well as sensorimotor gating abilities were decreased during puberty compared to adulthood, both tasks were found to show different developmental trajectories throughout adolescence. A low dose of the CB1 receptor antagonist/inverse agonist SR141716 was found to improve recognition memory specifically in pubertal animals while not affecting behavioral performance at other ages tested. The present findings demonstrate that the developmental trajectory of cognitive abilities does not occur linearly for all cognitive processes and is strongly influenced by pubertal maturation. Developmental alterations within the eCB system at puberty onset may be involved in these changes in cognitive processing.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. Short-term acclimation to warmer temperatures accelerates leaf carbon exchange processes across plant types.

    Science.gov (United States)

    Smith, Nicholas G; Dukes, Jeffrey S

    2017-11-01

    While temperature responses of photosynthesis and plant respiration are known to acclimate over time in many species, few studies have been designed to directly compare process-level differences in acclimation capacity among plant types. We assessed short-term (7 day) temperature acclimation of the maximum rate of Rubisco carboxylation (V cmax ), the maximum rate of electron transport (J max ), the maximum rate of phosphoenolpyruvate carboxylase carboxylation (V pmax ), and foliar dark respiration (R d ) in 22 plant species that varied in lifespan (annual and perennial), photosynthetic pathway (C 3 and C 4 ), and climate of origin (tropical and nontropical) grown under fertilized, well-watered conditions. In general, acclimation to warmer temperatures increased the rate of each process. The relative increase in different photosynthetic processes varied by plant type, with C 3 species tending to preferentially accelerate CO 2 -limited photosynthetic processes and respiration and C 4 species tending to preferentially accelerate light-limited photosynthetic processes under warmer conditions. R d acclimation to warmer temperatures caused a reduction in temperature sensitivity that resulted in slower rates at high leaf temperatures. R d acclimation was similar across plant types. These results suggest that temperature acclimation of the biochemical processes that underlie plant carbon exchange is common across different plant types, but that acclimation to warmer temperatures tends to have a relatively greater positive effect on the processes most limiting to carbon assimilation, which differ by plant type. The acclimation responses observed here suggest that warmer conditions should lead to increased rates of carbon assimilation when water and nutrients are not limiting. © 2017 John Wiley & Sons Ltd.

  4. 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.

  5. 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).

  6. Short-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

    2018-04-01

    Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

  7. 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.

  8. Developing a Local Neurofuzzy Model for Short-Term Wind Power Forecasting

    Directory of Open Access Journals (Sweden)

    E. Faghihnia

    2014-01-01

    Full Text Available Large scale integration of wind generation capacity into power systems introduces operational challenges due to wind power uncertainty and variability. Therefore, accurate wind power forecast is important for reliable and economic operation of the power systems. Complexities and nonlinearities exhibited by wind power time series necessitate use of elaborative and sophisticated approaches for wind power forecasting. In this paper, a local neurofuzzy (LNF approach, trained by the polynomial model tree (POLYMOT learning algorithm, is proposed for short-term wind power forecasting. The LNF approach is constructed based on the contribution of local polynomial models which can efficiently model wind power generation. Data from Sotavento wind farm in Spain was used to validate the proposed LNF approach. Comparison between performance of the proposed approach and several recently published approaches illustrates capability of the LNF model for accurate wind power forecasting.

  9. 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.

  10. [Economic Short-Term Cost Model for Stereotactic Radiotherapy of Neovascular AMD].

    Science.gov (United States)

    Neubauer, A S; Reznicek, L; Minartz, C; Ziemssen, F

    2016-08-01

    Stereotactic radiation therapy (Oraya, OT) is available as a second line therapy for patients who, despite intensive anti-VEGF therapy for neovascular AMD, do not show an improvement in CNV. As OT is expensive (5,308 €), the short term economics for starting this therapy were investigated. A short-term cost model was set up in MS Excel with a two year time horizon. On the basis of the data of the randomised, controlled INTREPID pivotal trial and current treatment practice in Germany, the costs were compared of conventional anti-VEGF therapy, with or without a single OT treatment. Patients with an active lesion after initial anti-VEGF therapy and a maximum lesion diameter ≤ 4 mm were included. Modeled cost components/aspects were direct savings from injection number, control follow-up examinations and aids, as well as anti-VEGF switches. Costs for Germany were employed and a univariate sensitivity analysis was performed to address the existing uncertainty. For the patients with a maximum AMD lesion diameter ≤ 4 mm and a macula volume > 7.4 mm(3), the INTREPID trial showed a mean reduction of 3.68 intravitreal injections for 16 Gy radiation versus sham over a time period of 2 years. These 3.68 IVM result in ~ 4,500 € direct cost savings. Moreover, due to the higher response rate with 16 Gy radiation, the number of follow-up visits and aids can be reduced, which results in savings between 207 € and 1,224 € over 2 years. After radiation, fewer anti-VEGF switches for low or non-responders are expected, which is modeled to result in ~ 1.7 fewer injections over 2 years. Due to overall fewer injections, fewer endophthalmitis cases would be expected. However, endophthalmitis and microvascular abnormalities, which can be observed in a few cases, are associated with low or non-quantifiable costs in this cost-cost comparison model. In summary, cost reductions of between 6,400 and 8,500 € are predicted in the model over two years

  11. 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

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

    Directory of Open Access Journals (Sweden)

    Salpasaranis Konstantinos

    2011-01-01

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

  13. 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

  14. 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.

  15. 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.

  16. 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)

  17. 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)

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

    Science.gov (United States)

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

    2017-05-01

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

  19. 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.

  20. Short-Term Solar Irradiance Forecasts Using Sky Images and Radiative Transfer Model

    Directory of Open Access Journals (Sweden)

    Juan Du

    2018-05-01

    Full Text Available In this paper, we propose a novel forecast method which addresses the difficulty in short-term solar irradiance forecasting that arises due to rapidly evolving environmental factors over short time periods. This involves the forecasting of Global Horizontal Irradiance (GHI that combines prediction sky images with a Radiative Transfer Model (RTM. The prediction images (up to 10 min ahead are produced by a non-local optical flow method, which is used to calculate the cloud motion for each pixel, with consecutive sky images at 1 min intervals. The Direct Normal Irradiance (DNI and the diffuse radiation intensity field under clear sky and overcast conditions obtained from the RTM are then mapped to the sky images. Through combining the cloud locations on the prediction image with the corresponding instance of image-based DNI and diffuse radiation intensity fields, the GHI can be quantitatively forecasted for time horizons of 1–10 min ahead. The solar forecasts are evaluated in terms of root mean square error (RMSE and mean absolute error (MAE in relation to in-situ measurements and compared to the performance of the persistence model. The results of our experiment show that GHI forecasts using the proposed method perform better than the persistence model.

  1. Short-term airing by natural ventilation - modeling and control strategies.

    Science.gov (United States)

    Perino, M; Heiselberg, P

    2009-10-01

    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 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 for temperature and IAQ control. However, in order to promote a wider applications of these systems, an improvement in the knowledge of their working principles and the availability of new design and simulation tools is necessary. In this context, the paper analyses and presents the results of a research 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. Practical Implications Numerical and experimental analyses have proved that short-term airing by intermittent ventilation is an effective measure to satisfactorily control IAQ. Different control strategies have been investigated to optimize the capabilities of the systems. The proposed zonal model has provided good performances and could be adopted as a design tool, while CFD simulations can be profitably used for detailed studies of the pollutant concentration distribution in a room and to address local discomfort problems.

  2. Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2017-10-01

    Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.

  3. Get the gist? The effects of processing depth on false recognition in short-term and long-term memory

    OpenAIRE

    Flegal, Kristin E.; Reuter-Lorenz, Patricia A.

    2014-01-01

    Gist-based processing has been proposed to account for robust false memories in the converging-associates task. The deep-encoding processes known to enhance verbatim memory also strengthen gist memory and increase distortions of long-term memory (LTM). Recent research has demonstrated that compelling false memory illusions are relatively delay-invariant, also occurring under canonical short-term memory (STM) conditions. To investigate the contributions of gist to false memory at short and lon...

  4. 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.

  5. 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.

  6. 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.

  7. Modeling Long-Term Fluvial Incision : Shall we Care for the Details of Short-Term Fluvial Dynamics?

    Science.gov (United States)

    Lague, D.; Davy, P.

    2008-12-01

    Fluvial incision laws used in numerical models of coupled climate, erosion and tectonics systems are mainly based on the family of stream power laws for which the rate of local erosion E is a power function of the topographic slope S and the local mean discharge Q : E = K Qm Sn. The exponents m and n are generally taken as (0.35, 0.7) or (0.5, 1), and K is chosen such that the predicted topographic elevation given the prevailing rates of precipitation and tectonics stay within realistic values. The resulting topographies are reasonably realistic, and the coupled system dynamics behaves somehow as expected : more precipitation induces increased erosion and localization of the deformation. Yet, if we now focus on smaller scale fluvial dynamics (the reach scale), recent advances have suggested that discharge variability, channel width dynamics or sediment flux effects may play a significant role in controlling incision rates. These are not factored in the simple stream power law model. In this work, we study how these short- term details propagate into long-term incision dynamics within the framework of surface/tectonics coupled numerical models. To upscale the short term dynamics to geological timescales, we use a numerical model of a trapezoidal river in which vertical and lateral incision processes are computed from fluid shear stress at a daily timescale, sediment transport and protection effects are factored in, as well as a variable discharge. We show that the stream power law model might still be a valid model but that as soon as realistic effects are included such as a threshold for sediment transport, variable discharge and dynamic width the resulting exponents m and n can be as high as 2 and 4. This high non-linearity has a profound consequence on the sensitivity of fluvial relief to incision rate. We also show that additional complexity does not systematically translates into more non-linear behaviour. For instance, considering only a dynamical width

  8. 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

  9. 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)

  10. 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...

  11. 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.

  12. An Agent-Based Model for the Role of Short-Term Memory Enhancement in the Emergence of Grammatical Agreement.

    Science.gov (United States)

    Vera, Javier

    2018-01-01

    What is the influence of short-term memory enhancement on the emergence of grammatical agreement systems in multi-agent language games? Agreement systems suppose that at least two words share some features with each other, such as gender, number, or case. Previous work, within the multi-agent language-game framework, has recently proposed models stressing the hypothesis that the emergence of a grammatical agreement system arises from the minimization of semantic ambiguity. On the other hand, neurobiological evidence argues for the hypothesis that language evolution has mainly related to an increasing of short-term memory capacity, which has allowed the online manipulation of words and meanings participating particularly in grammatical agreement systems. Here, the main aim is to propose a multi-agent language game for the emergence of a grammatical agreement system, under measurable long-range relations depending on the short-term memory capacity. Computer simulations, based on a parameter that measures the amount of short-term memory capacity, suggest that agreement marker systems arise in a population of agents equipped at least with a critical short-term memory capacity.

  13. 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.

  14. 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…

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. Language differences in verbal short-term memory do not exclusively originate in the process of subvocal rehearsal.

    Science.gov (United States)

    Thorn, A S; Gathercole, S E

    2001-06-01

    Language differences in verbal short-term memory were investigated in two experiments. In Experiment 1, bilinguals with high competence in English and French and monolingual English adults with extremely limited knowledge of French were assessed on their serial recall of words and nonwords in both languages. In all cases recall accuracy was superior in the language with which individuals were most familiar, a first-language advantage that remained when variation due to differential rates of articulation in the two languages was taken into account. In Experiment 2, bilinguals recalled lists of English and French words with and without concurrent articulatory suppression. First-language superiority persisted under suppression, suggesting that the language differences in recall accuracy were not attributable to slower rates of subvocal rehearsal in the less familiar language. The findings indicate that language-specific differences in verbal short-term memory do not exclusively originate in the subvocal rehearsal process. It is suggested that one source of language-specific variation might relate to the use of long-term knowledge to support short-term memory performance.

  20. Model and economic uncertainties in balancing short-term and long-term objectives in water-flooding optimization.

    NARCIS (Netherlands)

    Siraj, M.M.; Hof, Van den P.M.J.; Jansen, J.D.

    2015-01-01

    Model-based optimization of oil production has a significant scope to increase ultimate recovery or financial life-cycle performance. The Net Present Value (NPV) objective in such an optimization framework, because of its nature, focuses on the long-term gains while the short-term production is not

  1. 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...

  2. 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.

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

    International Nuclear Information System (INIS)

    Wang, Jun; Mccabe, Mckinleigh; Wu, Lei; Dong, Xiaomeng; Wang, Xianmao; Haskin, Troy Christopher; Corradini, Michael L.

    2017-01-01

    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

  4. 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

  5. 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...

  6. 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.

  7. 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

  8. 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

  9. A fast network solution by the decoupled procedure during short-term dynamic processes in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Popovic, D P; Stefanovic, M D [Nikola Tesla Inst., Belgrade (YU). Power System Dept.

    1990-01-01

    A simple, fast and reliable decoupled procedure for solving the network problems during short-term dynamic processes in power systems is presented. It is based on the Newton-Raphson method applied to the power balance equations, which include the effects of generator saliency and non-impedance loads, with further modifications resulting from the physical properties of the phenomena under study. The good convergence characteristics of the developed procedure are demonstrated, and a comparison is made with the traditional method based on the current equation and the triangularized admittance matrix, using the example of stability analysis of the Yugoslav power grid. (author).

  10. 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.

  11. Long-Term Impairment of Sound Processing in the Auditory Midbrain by Daily Short-Term Exposure to Moderate Noise

    Directory of Open Access Journals (Sweden)

    Liang Cheng

    2017-01-01

    Full Text Available Most citizen people are exposed daily to environmental noise at moderate levels with a short duration. The aim of the present study was to determine the effects of daily short-term exposure to moderate noise on sound level processing in the auditory midbrain. Sound processing properties of auditory midbrain neurons were recorded in anesthetized mice exposed to moderate noise (80 dB SPL, 2 h/d for 6 weeks and were compared with those from age-matched controls. Neurons in exposed mice had a higher minimum threshold and maximum response intensity, a longer first spike latency, and a higher slope and narrower dynamic range for rate level function. However, these observed changes were greater in neurons with the best frequency within the noise exposure frequency range compared with those outside the frequency range. These sound processing properties also remained abnormal after a 12-week period of recovery in a quiet laboratory environment after completion of noise exposure. In conclusion, even daily short-term exposure to moderate noise can cause long-term impairment of sound level processing in a frequency-specific manner in auditory midbrain neurons.

  12. 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.

  13. 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.

  14. The role of inhibition for working memory processes: ERP evidence from a short-term storage task.

    Science.gov (United States)

    Getzmann, Stephan; Wascher, Edmund; Schneider, Daniel

    2018-05-01

    Human working memory is the central unit for short-term storage of information. In addition to the selection and adequate storage of relevant information, the suppression of irrelevant stimuli from the environment seems to be of importance for working memory processes. To learn more about the interplay of information uptake and inhibition of irrelevant information, the present study used ERP measures and a short-term storage and retrieval task, in which pairs of either numbers or letters had to be compared. Random sequences of four stimuli (two numbers and two letters) were presented, with either the numbers or the letters being relevant for comparison. The analysis of ERPs to each of the four stimuli indicated more pronounced P2 and P3b amplitudes for relevant than irrelevant stimuli. In contrast, the N2 (reflecting inhibitory control) was only elicited by irrelevant stimuli. Moreover, the N2 amplitude of the second irrelevant stimulus was associated with behavioral performance, indicating the importance of inhibition of task-irrelevant stimuli for working memory processes. In sum, the findings demonstrate the role of cognitive control mechanisms for protecting relevant contents in working memory against irrelevant information. © 2017 Society for Psychophysiological Research.

  15. 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.

  16. Consequences of mild traumatic brain injury on information processing assessed with attention and short-term memory tasks.

    Science.gov (United States)

    Malojcic, Branko; Mubrin, Zdenko; Coric, Bojana; Susnic, Mirica; Spilich, George J

    2008-01-01

    In this investigation, we explored the impact of mild traumatic brain injury (mTBI) upon short term or working memory and attention. The performance of 37 individuals with mTBI was compared with that of 53 age, sex and education-matched controls. All participants were staff members or individuals seeking medical care at a University hospital serving a large metropolitan area. A battery of computerized tests measured sustained visual attention, short-term memory (STM), simple reaction time, and decision time. Individuals with mTBI showed a performance deficit at sustained visual attention, STM scanning and a trend towards slowing in choice decision making. These observed changes in the cognitive performance of mTBI individuals are hypothesized to be a consequence of impaired central information processing. Our results suggest that mTBI can elicit meaningful cognitive deficits for several months post-injury. Additionally, we believe that the tasks employed in the current investigation demonstrate their utility for understanding cognitive deficits in mTBI individuals.

  17. A High Precision Artificial Neural Networks Model for Short-Term Energy Load Forecasting

    Directory of Open Access Journals (Sweden)

    Ping-Huan Kuo

    2018-01-01

    Full Text Available One of the most important research topics in smart grid technology is load forecasting, because accuracy of load forecasting highly influences reliability of the smart grid systems. In the past, load forecasting was obtained by traditional analysis techniques such as time series analysis and linear regression. Since the load forecast focuses on aggregated electricity consumption patterns, researchers have recently integrated deep learning approaches with machine learning techniques. In this study, an accurate deep neural network algorithm for short-term load forecasting (STLF is introduced. The forecasting performance of proposed algorithm is compared with performances of five artificial intelligence algorithms that are commonly used in load forecasting. The Mean Absolute Percentage Error (MAPE and Cumulative Variation of Root Mean Square Error (CV-RMSE are used as accuracy evaluation indexes. The experiment results show that MAPE and CV-RMSE of proposed algorithm are 9.77% and 11.66%, respectively, displaying very high forecasting accuracy.

  18. 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…

  19. 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…

  20. 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.

  1. 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.

  2. 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.

  3. DIAPARK. A theoretical model for radiological assessments after short-term release and deposition of radionuclides

    International Nuclear Information System (INIS)

    Eklund, J.; Mueller, H.; Proehl, G.; Jacob, P.

    1995-05-01

    The DIAPARK program package is an enhancement of the ECOSYS-87 model for radioecological assessment, developed by GSF. The program version of the ECOSYS-87 model covers primarily the results and information derived from measurements performed after the Chernobyl reactor accident. Much importance has been attached to making the model fit for customized adjustment by modification of model parameters in order to be able to take into account the various conditions in various regions. The program package allows calculation of the deposition and interception, food contamination (as determined by plant contamination, contamination of animal products, radioactivity levels changed by storage and processing), doses resulting from ingestion and inhalation, and external exposure. (HP) [de

  4. Hydrological modelling of the Mabengnong catchment in the southeast Tibet with support of short term intensive precipitation observation

    Science.gov (United States)

    Wang, L.; Zhang, F.; Zhang, H.; Scott, C. A.; Zeng, C.; SHI, X.

    2017-12-01

    Precipitation is one of the crucial inputs for models used to better understand hydrological processes. In high mountain areas, it is a difficult task to obtain a reliable precipitation data set describing the spatial and temporal characteristic due to the limited meteorological observations and high variability of precipitation. This study carries out intensive observation of precipitation in a high mountain catchment in the southeast of the Tibet during July to August 2013. According to the rain gauges set up at different altitudes, it is found that precipitation is greatly influenced by altitude. The observed precipitation is used to depict the precipitation gradient (PG) and hourly distribution (HD), showing that the average duration is around 0.1, 0.8 and 6.0 hours and the average PG is 0.10, 0.28 and 0.26 mm/d/100m for trace, light and moderate rain, respectively. Based on the gridded precipitation derived from the PG and HD and the nearby Linzhi meteorological station at lower altitude, a distributed biosphere hydrological model based on water and energy budgets (WEB-DHM) is applied to simulate the hydrological processes. Beside the observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are also used for model calibration and validation. The resulting runoff, SCA and LST simulations are all reasonable. Sensitivity analyses indicate that runoff is greatly underestimated without considering PG, illustrating that short-term intensive precipitation observation contributes to improving hydrological modelling of poorly gauged high mountain catchments.

  5. 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.

  6. [Short-term sentence memory in children with auditory processing disorders].

    Science.gov (United States)

    Kiese-Himmel, C

    2010-05-01

    To compare sentence repetition performance of different groups of children with Auditory Processing Disorders (APD) and to examine the relationship between age or respectively nonverbal intelligence and sentence recall. Nonverbal intelligence was measured with the COLOURED MATRICES, in addition the children completed a standardized test of SENTENCE REPETITION (SR) which requires to repeat spoken sentences (subtest of the HEIDELBERGER SPRACHENTWICKLUNGSTEST). Three clinical groups (n=49 with monosymptomatic APD; n=29 with APD+developmental language impairment; n=14 with APD+developmental dyslexia); two control groups (n=13 typically developing peers without any clinical developmental disorder; n=10 children with slight reduced nonverbal intelligence). The analysis showed a significant group effect (p=0.0007). The best performance was achieved by the normal controls (T-score 52.9; SD 6.4; Min 42; Max 59) followed by children with monosymptomatic APD (43.2; SD 9.2), children with the co-morbid-conditions APD+developmental dyslexia (43.1; SD 10.3), and APD+developmental language impairment (39.4; SD 9.4). The clinical control group presented the lowest performance, on average (38.6; SD 9.6). Accordingly, language-impaired children and children with slight reductions in intelligence could poorly use their grammatical knowledge for SR. A statistically significant improvement in SR was verified with the increase of age with the exception of children belonging to the small group with lowered intelligence. This group comprised the oldest children. Nonverbal intelligence correlated positively with SR only in children with below average-range intelligence (0.62; p=0.054). The absence of APD, SLI as well as the presence of normal intelligence facilitated the use of phonological information for SR.

  7. 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

  8. 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.

  9. Short-term electricity price forecast based on the improved hybrid model

    International Nuclear Information System (INIS)

    Dong Yao; Wang Jianzhou; Jiang He; Wu Jie

    2011-01-01

    Highlights: → The proposed models can detach high volatility and daily seasonality of electricity price. → The improved hybrid forecast models can make full use of the advantages of individual models. → The proposed models create commendable improvements that are relatively satisfactorily for current research. → The proposed models do not require making complicated decisions about the explicit form. - Abstract: Half-hourly electricity price in power system are volatile, electricity price forecast is significant information which can help market managers and participants involved in electricity market to prepare their corresponding bidding strategies to maximize their benefits and utilities. However, the fluctuation of electricity price depends on the common effect of many factors and there is a very complicated random in its evolution process. Therefore, it is difficult to forecast half-hourly prices with traditional only one model for different behaviors of half-hourly prices. This paper proposes the improved forecasting model that detaches high volatility and daily seasonality for electricity price of New South Wales in Australia based on Empirical Mode Decomposition, Seasonal Adjustment and Autoregressive Integrated Moving Average. The prediction errors are analyzed and compared with the ones obtained from the traditional Seasonal Autoregressive Integrated Moving Average model. The comparisons demonstrate that the proposed model can improve the prediction accuracy noticeably.

  10. Short-term electricity price forecast based on the improved hybrid model

    Energy Technology Data Exchange (ETDEWEB)

    Dong Yao, E-mail: dongyao20051987@yahoo.cn [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Wang Jianzhou, E-mail: wjz@lzu.edu.cn [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Jiang He; Wu Jie [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China)

    2011-08-15

    Highlights: {yields} The proposed models can detach high volatility and daily seasonality of electricity price. {yields} The improved hybrid forecast models can make full use of the advantages of individual models. {yields} The proposed models create commendable improvements that are relatively satisfactorily for current research. {yields} The proposed models do not require making complicated decisions about the explicit form. - Abstract: Half-hourly electricity price in power system are volatile, electricity price forecast is significant information which can help market managers and participants involved in electricity market to prepare their corresponding bidding strategies to maximize their benefits and utilities. However, the fluctuation of electricity price depends on the common effect of many factors and there is a very complicated random in its evolution process. Therefore, it is difficult to forecast half-hourly prices with traditional only one model for different behaviors of half-hourly prices. This paper proposes the improved forecasting model that detaches high volatility and daily seasonality for electricity price of New South Wales in Australia based on Empirical Mode Decomposition, Seasonal Adjustment and Autoregressive Integrated Moving Average. The prediction errors are analyzed and compared with the ones obtained from the traditional Seasonal Autoregressive Integrated Moving Average model. The comparisons demonstrate that the proposed model can improve the prediction accuracy noticeably.

  11. 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.

  12. Long- and short-term exposure to PM2.5 and mortality: using novel exposure models.

    Science.gov (United States)

    Kloog, Itai; Ridgway, Bill; Koutrakis, Petros; Coull, Brent A; Schwartz, Joel D

    2013-07-01

    Many studies have reported associations between ambient particulate matter (PM) and adverse health effects, focused on either short-term (acute) or long-term (chronic) PM exposures. For chronic effects, the studied cohorts have rarely been representative of the population. We present a novel exposure model combining satellite aerosol optical depth and land-use data to investigate both the long- and short-term effects of PM2.5 exposures on population mortality in Massachusetts, United States, for the years 2000-2008. All deaths were geocoded. We performed two separate analyses: a time-series analysis (for short-term exposure) where counts in each geographic grid cell were regressed against cell-specific short-term PM2.5 exposure, temperature, socioeconomic data, lung cancer rates (as a surrogate for smoking), and a spline of time (to control for season and trends). In addition, for long-term exposure, we performed a relative incidence analysis using two long-term exposure metrics: regional 10 × 10 km PM2.5 predictions and local deviations from the cell average based on land use within 50 m of the residence. We tested whether these predicted the proportion of deaths from PM-related causes (cardiovascular and respiratory diseases). For short-term exposure, we found that for every 10-µg/m increase in PM 2.5 exposure there was a 2.8% increase in PM-related mortality (95% confidence interval [CI] = 2.0-3.5). For the long-term exposure at the grid cell level, we found an odds ratio (OR) for every 10-µg/m increase in long-term PM2.5 exposure of 1.6 (CI = 1.5-1.8) for particle-related diseases. Local PM2.5 had an OR of 1.4 (CI = 1.3-1.5), which was independent of and additive to the grid cell effect. We have developed a novel PM2.5 exposure model based on remote sensing data to assess both short- and long-term human exposures. Our approach allows us to gain spatial resolution in acute effects and an assessment of long-term effects in the entire population rather than a

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

    Directory of Open Access Journals (Sweden)

    Qiang Shang

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

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

    Science.gov (United States)

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

    2018-06-01

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

  15. 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

  16. 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.

  17. Get the gist? The effects of processing depth on false recognition in short-term and long-term memory.

    Science.gov (United States)

    Flegal, Kristin E; Reuter-Lorenz, Patricia A

    2014-07-01

    Gist-based processing has been proposed to account for robust false memories in the converging-associates task. The deep-encoding processes known to enhance verbatim memory also strengthen gist memory and increase distortions of long-term memory (LTM). Recent research has demonstrated that compelling false memory illusions are relatively delay-invariant, also occurring under canonical short-term memory (STM) conditions. To investigate the contributions of gist to false memory at short and long delays, processing depth was manipulated as participants encoded lists of four semantically related words and were probed immediately, following a filled 3- to 4-s retention interval, or approximately 20 min later, in a surprise recognition test. In two experiments, the encoding manipulation dissociated STM and LTM on the frequency, but not the phenomenology, of false memory. Deep encoding at STM increases false recognition rates at LTM, but confidence ratings and remember/know judgments are similar across delays and do not differ as a function of processing depth. These results suggest that some shared and some unique processes underlie false memory illusions at short and long delays.

  18. 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.

  19. Selective surface oxidation and segregation upon short term annealing of model alloys and industrial steel grades

    Energy Technology Data Exchange (ETDEWEB)

    Swaminathan, S.

    2007-07-01

    Segregation and selective oxidation phenomena of minor alloying elements during annealing of steel sheets lead to the formation of bare spots after hot-dip galvanizing. This thesis highlights the influence of annealing conditions and the effect of alloying elements on the selective oxidation in model alloys and some industrial steel grades. Model alloys of binary (Fe-2Si, Fe-2Mn, Fe-0.8Cr), ternary (Fe-2Mn-2Si, Fe-2Mn-0.8Cr, Fe-1Mn-0.8Cr, Fe-1Si-0.8Cr, Fe-2Si-0.8Cr) and quarternary (Fe-2Mn-2Si-0.8Cr) systems were studied. In the case of steels, standard grade interstitial free (IF) steels and experimental grade tensile strength 1000 MPa steel were investigated. All specimens were annealed at 820 C in N{sub 2}-5%H{sub 2} gas atmospheres with the wide range of dew points (i.e. -80 to 0 C). The surface chemistry after annealing and its wettability with liquid Zn have been correlated as a function of dew points by simulating the hot-dip galvanizing process at laboratory scale. (orig.)

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

    Science.gov (United States)

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

    2016-09-01

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

  1. 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.

  2. 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.

  3. 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)

  4. 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 approac...... and combinations most commonly used for treatment of colorectal cancer. In summary, short-term spheroid culture of primary colorectal adenocarcinoma cells represents a promising in vitro model for use in personalized medicine....... 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...

  5. A model of microsaccade-related neural responses induced by short-term depression in thalamocortical synapses

    Directory of Open Access Journals (Sweden)

    Wujie eYuan

    2013-04-01

    Full Text Available Microsaccades during fixation have been suggested to counteract visual fading. Recent experi- ments have also observed microsaccade-related neural responses from cellular record, scalp elec- troencephalogram (EEG and functional magnetic resonance imaging (fMRI. The underlying mechanism, however, is not yet understood and highly debated. It has been proposed that the neural activity of primary visual cortex (V1 is a crucial component for counteracting visual adaptation. In this paper, we use computational modeling to investigate how short-term depres- sion (STD in thalamocortical synapses might affect the neural responses of V1 in the presence of microsaccades. Our model not only gives a possible synaptic explanation for microsaccades in counteracting visual fading, but also reproduces several features in experimental findings. These modeling results suggest that STD in thalamocortical synapses plays an important role in microsaccade-related neural responses and the model may be useful for further investigation of behavioral properties and functional roles of microsaccades.

  6. A model of microsaccade-related neural responses induced by short-term depression in thalamocortical synapses

    Science.gov (United States)

    Yuan, Wu-Jie; Dimigen, Olaf; Sommer, Werner; Zhou, Changsong

    2013-01-01

    Microsaccades during fixation have been suggested to counteract visual fading. Recent experiments have also observed microsaccade-related neural responses from cellular record, scalp electroencephalogram (EEG), and functional magnetic resonance imaging (fMRI). The underlying mechanism, however, is not yet understood and highly debated. It has been proposed that the neural activity of primary visual cortex (V1) is a crucial component for counteracting visual adaptation. In this paper, we use computational modeling to investigate how short-term depression (STD) in thalamocortical synapses might affect the neural responses of V1 in the presence of microsaccades. Our model not only gives a possible synaptic explanation for microsaccades in counteracting visual fading, but also reproduces several features in experimental findings. These modeling results suggest that STD in thalamocortical synapses plays an important role in microsaccade-related neural responses and the model may be useful for further investigation of behavioral properties and functional roles of microsaccades. PMID:23630494

  7. 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.

  8. 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.

  9. 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.

  10. 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. PMID:28249033

  11. 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.

  12. 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....

  13. 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.

  14. 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.

  15. 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.

  16. 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

    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...

  17. Risk adjustment models for short-term outcomes after surgical resection for oesophagogastric cancer.

    Science.gov (United States)

    Fischer, C; Lingsma, H; Hardwick, R; Cromwell, D A; Steyerberg, E; Groene, O

    2016-01-01

    Outcomes for oesophagogastric cancer surgery are compared with the aim of benchmarking quality of care. Adjusting for patient characteristics is crucial to avoid biased comparisons between providers. The study objective was to develop a case-mix adjustment model for comparing 30- and 90-day mortality and anastomotic leakage rates after oesophagogastric cancer resections. The study reviewed existing models, considered expert opinion and examined audit data in order to select predictors that were consequently used to develop a case-mix adjustment model for the National Oesophago-Gastric Cancer Audit, covering England and Wales. Models were developed on patients undergoing surgical resection between April 2011 and March 2013 using logistic regression. Model calibration and discrimination was quantified using a bootstrap procedure. Most existing risk models for oesophagogastric resections were methodologically weak, outdated or based on detailed laboratory data that are not generally available. In 4882 patients with oesophagogastric cancer used for model development, 30- and 90-day mortality rates were 2·3 and 4·4 per cent respectively, and 6·2 per cent of patients developed an anastomotic leak. The internally validated models, based on predictors selected from the literature, showed moderate discrimination (area under the receiver operating characteristic (ROC) curve 0·646 for 30-day mortality, 0·664 for 90-day mortality and 0·587 for anastomotic leakage) and good calibration. Based on available data, three case-mix adjustment models for postoperative outcomes in patients undergoing curative surgery for oesophagogastric cancer were developed. These models should be used for risk adjustment when assessing hospital performance in the National Health Service, and tested in other large health systems. © 2015 BJS Society Ltd Published by John Wiley & Sons Ltd.

  18. A nested-grid limited-area model for short term weather forecasting

    Science.gov (United States)

    Wong, V. C.; Zack, J. W.; Kaplan, M. L.; Coats, G. D.

    1983-01-01

    The present investigation is concerned with a mesoscale atmospheric simulation system (MASS), incorporating the sigma-coordinate primitive equations. The present version of this model (MASS 3.0) has 14 vertical layers, with the upper boundary at 100 mb. There are 128 x 96 grid points in each layer. The earlier version of this model (MASS 2.0) has been described by Kaplan et al. (1982). The current investigation provides a summary of major revisions to that version and a description of the parameterization schemes which are presently included in the model. The planetary boundary layer (PBL) is considered, taking into account aspects of generalized similarity theory and free convection, the surface energy budget, the surface moisture budget, and prognostic equations for the depth h of the PBL. A cloud model is discussed, giving attention to stable precipitation, and cumulus convection.

  19. 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)

  20. A planning model for the short-term management of cash.

    Science.gov (United States)

    Broyles, Robert W; Mattachione, Steven; Khaliq, Amir

    2011-02-01

    This paper develops a model that enables the health administrator to identify the balance that minimizes the projected cost of holding cash. Adopting the principles of mathematical expectation, the model estimates the expected total costs of adopting each of the several strategies concerning the cash balance that the organization might maintain. Expected total costs consist of anticipated short costs, resulting from a potential shortage of funds. Long costs are associated with a potential surplus of funds and an opportunity cost represented by foregone investment income. Of importance to the model is the potential for the health service organization to realize a surplus of funds during periods characterized by a net cash disbursement. The paper also develops an interactive spreadsheet that enables the administrator to perform sensitivity analysis and examine the response of the desired or target cash balance to changes in the parameters that define the expected long and short cost functions.

  1. 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

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

    CSIR Research Space (South Africa)

    Anele, AO

    2017-11-01

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

  3. Modelling self-optimised short term load forecasting for medium voltage loads using tunning fuzzy systems and Artificial Neural Networks

    International Nuclear Information System (INIS)

    Mahmoud, Thair S.; Habibi, Daryoush; Hassan, Mohammed Y.; Bass, Octavian

    2015-01-01

    Highlights: • A novel Short Term Medium Voltage (MV) Load Forecasting (STLF) model is presented. • A knowledge-based STLF error control mechanism is implemented. • An Artificial Neural Network (ANN)-based optimum tuning is applied on STLF. • The relationship between load profiles and operational conditions is analysed. - Abstract: This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) models, which allows self-adaptation with respect to the load operational conditions. Specifically, a knowledge-based FeedBack Tunning Fuzzy System (FBTFS) is proposed to instantaneously correlate the information about the demand profile and its operational conditions to make decisions for controlling the model’s forecasting error rate. To maintain minimum forecasting error under various operational scenarios, the FBTFS adaptation was optimised using a Multi-Layer Perceptron Artificial Neural Network (MLPANN), which was trained using Backpropagation algorithm, based on the information about the amount of error and the operational conditions at time of forecasting. For the sake of comparison and performance testing, this mechanism was added to the conventional forecasting methods, i.e. Nonlinear AutoRegressive eXogenous-Artificial Neural Network (NARXANN), Fuzzy Subtractive Clustering Method-based Adaptive Neuro Fuzzy Inference System (FSCMANFIS) and Gaussian-kernel Support Vector Machine (GSVM), and the measured forecasting error reduction average in a 12 month simulation period was 7.83%, 8.5% and 8.32% respectively. The 3.5 MW variable load profile of Edith Cowan University (ECU) in Joondalup, Australia, was used in the modelling and simulations of this model, and the data was provided by Western Power, the transmission and distribution company of the state of Western Australia.

  4. 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.

  5. Vascular and hepatic impact of short-term intermittent hypoxia in a mouse model of metabolic syndrome.

    Directory of Open Access Journals (Sweden)

    Wojciech Trzepizur

    Full Text Available Experimental models of intermittent hypoxia (IH have been developed during the last decade to investigate the consequences of obstructive sleep apnea. IH is usually associated with detrimental metabolic and vascular outcomes. However, paradoxical protective effects have also been described depending of IH patterns and durations applied in studies. We evaluated the impact of short-term IH on vascular and metabolic function in a diet-induced model of metabolic syndrome (MS.Mice were fed either a standard diet or a high fat diet (HFD for 8 weeks. During the final 14 days of each diet, animals were exposed to either IH (1 min cycle, FiO2 5% for 30s, FiO2 21% for 30s; 8 h/day or intermittent air (FiO2 21%. Ex-vivo vascular reactivity in response to acetylcholine was assessed in aorta rings by myography. Glucose, insulin and leptin levels were assessed, as well as serum lipid profile, hepatic mitochondrial activity and tissue nitric oxide (NO release.Mice fed with HFD developed moderate markers of dysmetabolism mimicking MS, including increased epididymal fat, dyslipidemia, hepatic steatosis and endothelial dysfunction. HFD decreased mitochondrial complex I, II and IV activities and increased lactate dehydrogenase (LDH activity in liver. IH applied to HFD mice induced a major increase in insulin and leptin levels and prevented endothelial dysfunction by restoring NO production. IH also restored mitochondrial complex I and IV activities, moderated the increase in LDH activity and liver triglyceride accumulation in HFD mice.In a mouse model of MS, short-term IH increases insulin and leptin levels, restores endothelial function and mitochondrial activity and limits liver lipid accumulation.

  6. 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.

  7. How to Say No: Single- and Dual-Process Theories of Short-Term Recognition Tested on Negative Probes

    Science.gov (United States)

    Oberauer, Klaus

    2008-01-01

    Three experiments with short-term recognition tasks are reported. In Experiments 1 and 2, participants decided whether a probe matched a list item specified by its spatial location. Items presented at study in a different location (intrusion probes) had to be rejected. Serial position curves of positive, new, and intrusion probes over the probed…

  8. 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…

  9. 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.…

  10. 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

  11. 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...

  12. 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.

  13. Adequacy of the Ultra-Short-Term HRV to Assess Adaptive Processes in Youth Female Basketball Players.

    Science.gov (United States)

    Nakamura, Fabio Y; Pereira, Lucas A; Cal Abad, Cesar C; Cruz, Igor F; Flatt, Andrew A; Esco, Michael R; Loturco, Irineu

    2017-02-01

    Heart rate variability has been widely used to monitor athletes' cardiac autonomic control changes induced by training and competition, and recently shorter recording times have been sought to improve its practicality. The aim of this study was to test the agreement between the (ultra-short-term) natural log of the root-mean-square difference of successive normal RR intervals (lnRMSSD - measured in only 1 min post-1 min stabilization) and the criterion lnRMSSD (measured in the last 5 min out of 10 min of recording) in young female basketball players. Furthermore, the correlation between training induced delta change in the ultra-short-term lnRMSSD and the criterion lnRMSSD was calculated. Seventeen players were assessed at rest pre- and post-eight weeks of training. Trivial effect sizes (-0.03 in the pre- and 0.10 in the post- treatment) were found in the comparison between the ultra-short-term lnRMSSD (3.29 ± 0.45 and 3.49 ± 0.35 ms, in the pre- and post-, respectively) and the criterion lnRMSSD (3.30 ± 0.40 and 3.45 ± 0.41 ms, in the pre- and post-, respectively) (intraclass correlation coefficient = 0.95 and 0.93). In both cases, the response to training was significant, with Pearson's correlation of 0.82 between the delta changes of the ultra-short-term lnRMSSD and the criterion lnRMSSD. In conclusion, the lnRMSSD can be calculated within only 2 min of data acquisition (the 1 st min discarded) in young female basketball players, with the ultra-short-term measure presenting similar sensitivity to training effects as the standard criterion measure.

  14. Initial Experience With the New Ahmed Glaucoma Valve Model M4: Short-term Results.

    Science.gov (United States)

    Cvintal, Victor; Moster, Marlene R; Shyu, Andrew P; McDermott, Katie; Ekici, Feyzahan; Pro, Michael J; Waisbourd, Michael

    2016-05-01

    To evaluate the clinical outcomes of the new Ahmed glaucoma valve (AGV) model M4. The device consists of a porous polyethylene shell designed for improved tissue integration and reduced encapsulation of the plate for better intraocular pressure (IOP) control. Medical records of patients with an AGV M4 implantation between December 1, 2012 and December 31, 2013 were reviewed. The main outcome measure was surgical failure, defined as either (1) IOP21 mm Hg and/or glaucoma, and/or (3) loss of light perception. Seventy-five eyes of 73 patients were included. Postoperative IOP at all follow-up visits significantly decreased from a baseline IOP of 31.2 mm Hg (P<0.01). However, IOP increased significantly at 3 months (20.4 mm Hg), 6 months (19.3 mm Hg), and 12 months (20.3 mm Hg) compared with 1 month (13.8 mm Hg) postoperatively (P<0.05). At 6 months and 1 year, the cumulative probability of failure was 32% and 72%, respectively. The AGV M4 effectively reduced IOP in the first postoperative month, but IOP steadily increased thereafter. Consequently, failure rates were high after 1 year of follow-up.

  15. Modelling short term individual exposure from airborne hazardous releases in urban environments

    International Nuclear Information System (INIS)

    Bartzis, J.G.; Efthimiou, G.C.; Andronopoulos, S.

    2015-01-01

    Highlights: • The statistical behavior of the variability of individual exposure is described with a beta function. • The extreme value in the beta function is properly addressed by [5] correlation. • Two different datasets gave clear support to the proposed novel theory and its hypotheses. - Abstract: A key issue, in order to be able to cope with deliberate or accidental atmospheric releases of hazardous substances, is the ability to reliably predict the individual exposure downstream the source. In many situations, the release time and/or the health relevant exposure time is short compared to mean concentration time scales. In such a case, a significant scatter of exposure levels is expected due to the stochastic nature of turbulence. The problem becomes even more complex when dispersion occurs over urban environments. The present work is the first attempt to approximate on generic terms, the statistical behavior of the abovementioned variability with a beta distribution probability density function (beta-pdf) which has proved to be quite successful. The important issue of the extreme concentration value in beta-pdf seems to be properly addressed by the [5] correlation in which global values of its associated constants are proposed. Two substantially different datasets, the wind tunnel Michelstadt experiment and the field Mock Urban Setting Trial (MUST) experiment gave clear support to the proposed novel theory and its hypotheses. In addition, the present work can be considered as basis for further investigation and model refinements.

  16. Modelling short term individual exposure from airborne hazardous releases in urban environments

    Energy Technology Data Exchange (ETDEWEB)

    Bartzis, J.G., E-mail: bartzis@uowm.gr [University of Western Macedonia, Dept. of Mechanical Engineering, Sialvera & Bakola Str., 50100, Kozani (Greece); Efthimiou, G.C.; Andronopoulos, S. [Environmental Research Laboratory, INRASTES, NCSR Demokritos, Patriarchou Grigoriou & Neapoleos Str., 15310, Aghia Paraskevi (Greece)

    2015-12-30

    Highlights: • The statistical behavior of the variability of individual exposure is described with a beta function. • The extreme value in the beta function is properly addressed by [5] correlation. • Two different datasets gave clear support to the proposed novel theory and its hypotheses. - Abstract: A key issue, in order to be able to cope with deliberate or accidental atmospheric releases of hazardous substances, is the ability to reliably predict the individual exposure downstream the source. In many situations, the release time and/or the health relevant exposure time is short compared to mean concentration time scales. In such a case, a significant scatter of exposure levels is expected due to the stochastic nature of turbulence. The problem becomes even more complex when dispersion occurs over urban environments. The present work is the first attempt to approximate on generic terms, the statistical behavior of the abovementioned variability with a beta distribution probability density function (beta-pdf) which has proved to be quite successful. The important issue of the extreme concentration value in beta-pdf seems to be properly addressed by the [5] correlation in which global values of its associated constants are proposed. Two substantially different datasets, the wind tunnel Michelstadt experiment and the field Mock Urban Setting Trial (MUST) experiment gave clear support to the proposed novel theory and its hypotheses. In addition, the present work can be considered as basis for further investigation and model refinements.

  17. 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.

  18. Relative association of processing speed, short-term memory and sustained attention with task on gait speed: a study of community-dwelling people 50 years and older.

    Science.gov (United States)

    Killane, Isabelle; Donoghue, Orna A; Savva, George M; Cronin, Hilary; Kenny, Rose Anne; Reilly, Richard B

    2014-11-01

    For single gait tasks, associations have been reported between gait speed and cognitive domains. However, few studies have evaluated if this association is altered in dual gait tasks given gait speed changes with complexity and nature of task. We evaluated relative contributions of specific elements of cognitive function (including sustained attention and processing speed) to dual task gait speed in a nationally representative population of community-dwelling adults over 50 years. Gait speed was obtained using the GaitRite walkway during three gait tasks: single, cognitive (alternate letters), and motor (carrying a filled glass). Linear regression models, adjusted for covariates, were constructed to predict the relative contributions of seven neuropsychological tests to gait speed differences and to investigate gait task effects. The mean age and gait speed of the population (n = 4,431, 55% women) was 62.4 years (SD = 8.2) and 135.85 cm/s (SD = 20.20, single task), respectively. Poorer processing speed, short-term memory, and sustained attention were major cognitive contributors to slower gait speed for all gait tasks. Both dual gait tasks were robust to covariate adjustment and had a significant additional executive function element not found for the single gait task. For community-dwelling older adults processing speed, short-term memory and sustained attention were independently associated with gait speed for all gait tasks. Dual gait tasks were found to highlight specific executive function elements. This result forms a baseline value for dual task gait speed. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Short term decisions for long term problems - The effect of foresight on model based energy systems analysis

    International Nuclear Information System (INIS)

    Keppo, Ilkka; Strubegger, Manfred

    2010-01-01

    This paper presents the development and demonstration of a limited foresight energy system model. The presented model is implemented as an extension to a large, linear optimization model, MESSAGE. The motivation behind changing the model is to provide an alternative decision framework, where information for the full time frame is not available immediately and sequential decision making under incomplete information is implied. While the traditional optimization framework provides the globally optimal decisions for the modeled problem, the framework presented here may offer a better description of the decision environment, under which decision makers must operate. We further modify the model to accommodate flexible dynamic constraints, which give an option to implement investments faster, albeit with a higher cost. Finally, the operation of the model is demonstrated using a moving window of foresight, with which decisions are taken for the next 30 years, but can be reconsidered later, when more information becomes available. We find that the results demonstrate some of the pitfalls of short term planning, e.g. lagging investments during earlier periods lead to higher requirements later during the century. Furthermore, the energy system remains more reliant on fossil based energy carriers, leading to higher greenhouse gas emissions.

  20. 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...

  1. A Quantitative and Qualitative Assessment of Verbal Short-Term Memory and Phonological Processing in 8-Year-Olds with a History of Repetitive Otitis Media

    Science.gov (United States)

    Majerus, Steve; Amand, Pierre; Boniver, Vincent; Demanez, Jean-Pierre; Demanez, Laurent; Van der Linden, Martial

    2005-01-01

    Language outcome in children experiencing fluctuant hearing loss due to otitis media (OME) remains highly equivocal. In the current study, we assessed performance on highly sensitive verbal short-term memory (STM), new word learning and phonological processing tasks in 8-year-old children who had suffered from recurrent OME before the age of 3.…

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

    Science.gov (United States)

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

    2017-03-01

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

  3. 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)

  4. Probabilistic short-term forecasting of eruption rate at Kīlauea Volcano using a physics-based model

    Science.gov (United States)

    Anderson, K. R.

    2016-12-01

    Deterministic models of volcanic eruptions yield predictions of future activity conditioned on uncertainty in the current state of the system. Physics-based eruption models are well-suited for deterministic forecasting as they can relate magma physics with a wide range of observations. Yet, physics-based eruption forecasting is strongly limited by an inadequate understanding of volcanic systems, and the need for eruption models to be computationally tractable. At Kīlauea Volcano, Hawaii, episodic depressurization-pressurization cycles of the magma system generate correlated, quasi-exponential variations in ground deformation and surface height of the active summit lava lake. Deflations are associated with reductions in eruption rate, or even brief eruptive pauses, and thus partly control lava flow advance rates and associated hazard. Because of the relatively well-understood nature of Kīlauea's shallow magma plumbing system, and because more than 600 of these events have been recorded to date, they offer a unique opportunity to refine a physics-based effusive eruption forecasting approach and apply it to lava eruption rates over short (hours to days) time periods. A simple physical model of the volcano ascribes observed data to temporary reductions in magma supply to an elastic reservoir filled with compressible magma. This model can be used to predict the evolution of an ongoing event, but because the mechanism that triggers events is unknown, event durations are modeled stochastically from previous observations. A Bayesian approach incorporates diverse data sets and prior information to simultaneously estimate uncertain model parameters and future states of the system. Forecasts take the form of probability distributions for eruption rate or cumulative erupted volume at some future time. Results demonstrate the significant uncertainties that still remain even for short-term eruption forecasting at a well-monitored volcano - but also the value of a physics

  5. Left TPJ activity in verbal working memory: implications for storage- and sensory-specific models of short term memory.

    Science.gov (United States)

    Ravizza, Susan M; Hazeltine, Eliot; Ruiz, Sandra; Zhu, David C

    2011-04-15

    Patients with damage to the left temporoparietal junction (TPJ) have a low verbal span without concomitant deficits in speech perception. This pattern of cognitive impairment is taken as evidence for a dedicated phonological buffer that plays little role in perception (storage-specific account). In contrast, other research suggests that items are maintained and perceived in the same regions (sensory-specific account). In an fMRI study, we demonstrate that the left TPJ does not respond in a way predicted of a phonological buffer; that is, activity in this region is not sustained during encoding or maintenance. Instead, a region in the superior temporal gyrus that has been associated with both speech perception and production demonstrated the expected profile of a store: it was more active in the verbal condition than the object condition and was active during both encoding and maintenance. These results support the sensory-specific account of short term memory rather than the storage-specific account. Based on the pattern of activity in the left TPJ, we suggest that the impairment of verbal working memory observed in patients with TPJ damage may be due to diminished attentional processes rather than reduced storage capacity. Copyright © 2010 Elsevier Inc. All rights reserved.

  6. Modeling of hot tensile and short-term creep strength for LWR piping materials under severe accident conditions

    International Nuclear Information System (INIS)

    Harada, Y.; Maruyama, Y.; Chino, E.; Shibazaki, H.; Kudo, T.; Hidaka, A.; Hashimoto, K.; Sugimoto, J.

    2000-01-01

    The analytical study on severe accident shows the possibility of the reactor coolant system (RCS) piping failure before reactor pressure vessel failure under the high primary pressure sequence at pressurized water reactors. The establishment of the high-temperature strength model of the realistic RCS piping materials is important in order to predict precisely the accident progression and to evaluate the piping behavior with small uncertainties. Based on material testing, the 0.2% proof stress and the ultimate tensile strength above 800degC were given by the equations of second degree as a function of the reciprocal absolute temperature considering the strength increase due to fine precipitates for the piping materials. The piping materials include type 316 stainless steel, type 316 stainless steel of nuclear grade, CF8M cast duplex stainless steel and STS410 carbon steel. Also the short-term creep rupture time and the minimum creep rate at high-temperature were given by the modified Norton's Law as a function of stress and temperature considering the effect of the precipitation formation and resolution on the creep strength. The present modified Norton's Law gives better results than the conventional Larson-Miller method. Correlating the creep data (the applied stress versus the minimum creep rate) with the tensile data (the 0.2% proof stress or the ultimate tensile strength versus the strain rate), it was found that the dynamic recrystallization significantly occurred at high-temperature. (author)

  7. Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2017-12-01

    Full Text Available Accurate solar photovoltaic (PV power forecasting is an essential tool for mitigating the negative effects caused by the uncertainty of PV output power in systems with high penetration levels of solar PV generation. Weather classification based modeling is an effective way to increase the accuracy of day-ahead short-term (DAST solar PV power forecasting because PV output power is strongly dependent on the specific weather conditions in a given time period. However, the accuracy of daily weather classification relies on both the applied classifiers and the training data. This paper aims to reveal how these two factors impact the classification performance and to delineate the relation between classification accuracy and sample dataset scale. Two commonly used classification methods, K-nearest neighbors (KNN and support vector machines (SVM are applied to classify the daily local weather types for DAST solar PV power forecasting using the operation data from a grid-connected PV plant in Hohhot, Inner Mongolia, China. We assessed the performance of SVM and KNN approaches, and then investigated the influences of sample scale, the number of categories, and the data distribution in different categories on the daily weather classification results. The simulation results illustrate that SVM performs well with small sample scale, while KNN is more sensitive to the length of the training dataset and can achieve higher accuracy than SVM with sufficient samples.

  8. Short-term streamflow forecasting with global climate change implications A comparative study between genetic programming and neural network models

    Science.gov (United States)

    Makkeasorn, A.; Chang, N. B.; Zhou, X.

    2008-05-01

    SummarySustainable water resources management is a critically important priority across the globe. While water scarcity limits the uses of water in many ways, floods may also result in property damages and the loss of life. To more efficiently use the limited amount of water under the changing world or to resourcefully provide adequate time for flood warning, the issues have led us to seek advanced techniques for improving streamflow forecasting on a short-term basis. This study emphasizes the inclusion of sea surface temperature (SST) in addition to the spatio-temporal rainfall distribution via the Next Generation Radar (NEXRAD), meteorological data via local weather stations, and historical stream data via USGS gage stations to collectively forecast discharges in a semi-arid watershed in south Texas. Two types of artificial intelligence models, including genetic programming (GP) and neural network (NN) models, were employed comparatively. Four numerical evaluators were used to evaluate the validity of a suite of forecasting models. Research findings indicate that GP-derived streamflow forecasting models were generally favored in the assessment in which both SST and meteorological data significantly improve the accuracy of forecasting. Among several scenarios, NEXRAD rainfall data were proven its most effectiveness for a 3-day forecast, and SST Gulf-to-Atlantic index shows larger impacts than the SST Gulf-to-Pacific index on the streamflow forecasts. The most forward looking GP-derived models can even perform a 30-day streamflow forecast ahead of time with an r-square of 0.84 and RMS error 5.4 in our study.

  9. What do short-term and long-term relationships look like? Building the relationship coordination and strategic timing (ReCAST) model.

    Science.gov (United States)

    Eastwick, Paul W; Keneski, Elizabeth; Morgan, Taylor A; McDonald, Meagan A; Huang, Sabrina A

    2018-05-01

    Close relationships research has examined committed couples (e.g., dating relationships, marriages) using intensive methods that plot relationship development over time. But a substantial proportion of people's real-life sexual experiences take place (a) before committed relationships become "official" and (b) in short-term relationships; methods that document the time course of relationships have rarely been applied to these contexts. We adapted a classic relationship trajectory-plotting technique to generate the first empirical comparisons between the features of people's real-life short-term and long-term relationships across their entire timespan. Five studies compared long-term and short-term relationships in terms of the timing of relationship milestones (e.g., flirting, first sexual intercourse) and the occurrence/intensity of important relationship experiences (e.g., romantic interest, strong sexual desire, attachment). As romantic interest was rising and partners were becoming acquainted, long-term and short-term relationships were indistinguishable. Eventually, romantic interest in short-term relationships plateaued and declined while romantic interest in long-term relationships continued to rise, ultimately reaching a higher peak. As relationships progressed, participants evidenced more features characteristic of the attachment-behavioral system (e.g., attachment, caregiving) in long-term than short-term relationships but similar levels of other features (e.g., sexual desire, self-promotion, intrasexual competition). These data inform a new synthesis of close relationships and evolutionary psychological perspectives called the Relationship Coordination and Strategic Timing (ReCAST) model. ReCAST depicts short-term and long-term relationships as partially overlapping trajectories (rather than relationships initiated with distinct strategies) that differ in their progression along a normative relationship development sequence. (PsycINFO Database Record (c

  10. Sodium nitroprusside enhanced cardiopulmonary resuscitation improves short term survival in a porcine model of ischemic refractory ventricular fibrillation.

    Science.gov (United States)

    Yannopoulos, Demetris; Bartos, Jason A; George, Stephen A; Sideris, George; Voicu, Sebastian; Oestreich, Brett; Matsuura, Timothy; Shekar, Kadambari; Rees, Jennifer; Aufderheide, Tom P

    2017-01-01

    Sodium nitroprusside (SNP) enhanced CPR (SNPeCPR) demonstrates increased vital organ blood flow and survival in multiple porcine models. We developed a new, coronary occlusion/ischemia model of prolonged resuscitation, mimicking the majority of out-of-hospital cardiac arrests presenting with shockable rhythms. SNPeCPR will increase short term (4-h) survival compared to standard 2015 Advanced Cardiac Life Support (ACLS) guidelines in an ischemic refractory ventricular fibrillation (VF), prolonged CPR model. Sixteen anesthetized pigs had the ostial left anterior descending artery occluded leading to ischemic VF arrest. VF was untreated for 5min. Basic life support was performed for 10min. At minute 10 (EMS arrival), animals received either SNPeCPR (n=8) or standard ACLS (n=8). Defibrillation (200J) occurred every 3min. CPR continued for a total of 45min, then the balloon was deflated simulating revascularization. CPR continued until return of spontaneous circulation (ROSC) or a total of 60min, if unsuccessful. SNPeCPR animals received 2mg of SNP at minute 10 followed by 1mg every 5min until ROSC. Standard ACLS animals received 0.5mg epinephrine every 5min until ROSC. Primary endpoints were ROSC and 4-h survival. All SNPeCPR animals (8/8) achieved sustained ROSC versus 2/8 standard ACLS animals within one hour of resuscitation (p=0.04). The 4-h survival was significantly improved with SNPeCPR compared to standard ACLS, 7/8 versus 1/8 respectively, p=0.0019. SNPeCPR significantly improved ROSC and 4-h survival compared with standard ACLS CPR in a porcine model of prolonged ischemic, refractory VF cardiac arrest. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. 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

  12. The Demonstration of Short-Term Consolidation.

    Science.gov (United States)

    Jolicoeur, Pierre; Dell'Acqua, Roberto

    1998-01-01

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

  13. 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.

  14. 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.

  15. 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…

  16. Evaluation of Short Term Memory Span Function In Children

    Directory of Open Access Journals (Sweden)

    Barış ERGÜL

    2016-12-01

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

  17. 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

    of T-cell lymphomas. Because of the low incidence of spontaneous tumors and the increased sensitivity to N-ethyl-N-nitrosourea-induced carcinogenesis, E mu-pim-1 mice were suggested to be one of the first potential and attractive candidates to be used in short-term carcinogenicity testing...

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

    Science.gov (United States)

    Nosofsky, Robert M; Cox, Gregory E; Cao, Rui; Shiffrin, Richard M

    2014-11-01

    Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across diverse conditions that manipulated relations between targets and foils across trials. Subjects saw lists of from 1 to 16 items followed by a single item recognition probe. In a varied-mapping condition, targets and foils could switch roles across trials; in a consistent-mapping condition, targets and foils never switched roles; and in an all-new condition, on each trial a completely new set of items formed the memory set. In the varied-mapping and all-new conditions, mean correct response times (RTs) and error proportions were curvilinear increasing functions of memory set size, with the RT results closely resembling ones from hybrid visual-memory search experiments reported by Wolfe (2012). In the consistent-mapping condition, new-probe RTs were invariant with set size, whereas old-probe RTs increased slightly with increasing study-test lag. With appropriate choice of psychologically interpretable free parameters, the model accounted well for the complete set of results. The work provides support for the hypothesis that a common set of processes involving exemplar-based familiarity may govern long-term and short-term probe recognition across wide varieties of memory- search conditions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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. PMID:24936174

  4. Short-Term Free Recall and Sequential Memory for Pictures and Words: A Simultaneous-Successive Processing Interpretation.

    Science.gov (United States)

    Randhawa, Bikkar S.; And Others

    1982-01-01

    Replications of two basic experiments in support of the dual-coding processing model with grade 10 and college subjects used pictures, concrete words, and abstract words as stimuli presented at fast and slow rates for immediate and sequential recall. Results seem to be consistent with predictions of simultaneous-successive cognitive theory. (MBR)

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

    Directory of Open Access Journals (Sweden)

    Simon Gorin

    Full Text Available 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.

  6. 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.

  7. 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

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Steve eMajerus

    2013-07-01

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

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

    Science.gov (United States)

    Majerus, Steve

    2013-01-01

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

  11. Hardware and software for automating the process of studying high-speed gas flows in wind tunnels of short-term action

    Science.gov (United States)

    Yakovlev, V. V.; Shakirov, S. R.; Gilyov, V. M.; Shpak, S. I.

    2017-10-01

    In this paper, we propose a variant of constructing automation systems for aerodynamic experiments on the basis of modern hardware-software means of domestic development. The structure of the universal control and data collection system for performing experiments in wind tunnels of continuous, periodic or short-term action is proposed. The proposed hardware and software development tools for ICT SB RAS and ITAM SB RAS, as well as subsystems based on them, can be widely applied to any scientific and experimental installations, as well as to the automation of technological processes in production.

  12. 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

    fractions A grain size or sieve analysis typically yields the mass fraction of each particle size class after dispersing all of the material. However...ER D C TR -1 6- 2 Ocean Dredged Material Disposal Site (ODMDS) Authorization and Short-Term FATE (STFATE) Model Analysis 2014 – 2015...Term FATE (STFATE) Model Analysis 2014 – 2015 Working Group Findings Report Jase D. Ousley Coastal and Hydraulics Laboratory U.S. Army Engineer

  13. 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.

  14. The integration of familiarity and recollection information in short-term recognition: modeling speed-accuracy trade-off functions.

    Science.gov (United States)

    Göthe, Katrin; Oberauer, Klaus

    2008-05-01

    Dual process models postulate familiarity and recollection as the basis of the recognition process. We investigated the time-course of integration of the two information sources to one recognition judgment in a working memory task. We tested 24 subjects with a response signal variant of the modified Sternberg recognition task (Oberauer, 2001) to isolate the time course of three different probe types indicating different combinations of familiarity and source information. We compared two mathematical models implementing different ways of integrating familiarity and recollection. Within each model, we tested three assumptions about the nature of the familiarity signal, with familiarity having (a) only positive values, indicating similarity of the probe with the memory list, (b) only negative values, indicating novelty, or (c) both positive and negative values. Both models provided good fits to the data. A model combining the outputs of both processes additively (Integration Model) gave an overall better fit to the data than a model based on a continuous familiarity signal and a probabilistic all-or-none recollection process (Dominance Model).

  15. Identity processes and coping strategies in college students : Short-term longitudinal dynamics and the role of personality

    NARCIS (Netherlands)

    Luyckx, K.; Klimstra, T.A.; Duriez, B.; Schwartz, S.J.; Vanhalst, J.

    2012-01-01

    Coping strategies and identity processes are hypothesized to influence one another over time. This three-wave longitudinal study (N = 458; 84.9% women) examined, for the first time, how and to what extent identity processes (i.e., commitment making, identification with commitment, exploration in

  16. Utilizing an Adaptive Grey Model for Short-Term Time Series Forecasting: A Case Study of Wafer-Level Packaging

    Directory of Open Access Journals (Sweden)

    Che-Jung Chang

    2013-01-01

    Full Text Available The wafer-level packaging process is an important technology used in semiconductor manufacturing, and how to effectively control this manufacturing system is thus an important issue for packaging firms. One way to aid in this process is to use a forecasting tool. However, the number of observations collected in the early stages of this process is usually too few to use with traditional forecasting techniques, and thus inaccurate results are obtained. One potential solution to this problem is the use of grey system theory, with its feature of small dataset modeling. This study thus uses the AGM(1,1 grey model to solve the problem of forecasting in the pilot run stage of the packaging process. The experimental results show that the grey approach is an appropriate and effective forecasting tool for use with small datasets and that it can be applied to improve the wafer-level packaging process.

  17. 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...

  18. 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.

  19. 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.

  20. 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 ca...

  1. The interactive effects of fire and diversity on short-term responses of ecosystem processes in experimental mediterranean grasslands.

    Science.gov (United States)

    Dimitrakopoulos, Panayiotis G; Siamantziouras, Akis-Stavros D; Galanidis, Alexandros; Mprezetou, Irene; Troumbis, Andreas Y

    2006-06-01

    We conducted a field experiment using constructed communities to test whether species richness contributed to the maintenance of ecosystem processes under fire disturbance. We studied the effects of diversity components (i.e., species richness and species composition) upon productivity, structural traits of vegetation, decomposition rates, and soil nutrients between burnt and unburnt experimental Mediterranean grassland communities. Our results demonstrated that fire and species richness had interactive effects on aboveground biomass production and canopy structure components. Fire increased biomass production of the highest-richness communities. The effects of fire on aboveground biomass production at different levels of species richness were derived from changes in both vertical and horizontal canopy structure of the communities. The most species-rich communities appeared to be more resistant to fire in relation to species-poor ones, due to both compositional and richness effects. Interactive effects of fire and species richness were not important for belowground processes. Decomposition rates increased with species richness, related in part to increased levels of canopy structure traits. Fire increased soil nutrients and long-term decomposition rate. Our results provide evidence that composition within richness levels had often larger effects on the stability of aboveground ecosystem processes in the face of fire disturbance than species richness per se.

  2. Enhancing links between visual short term memory, visual attention and cognitive control processes through practice: An electrophysiological insight.

    Science.gov (United States)

    Fuggetta, Giorgio; Duke, Philip A

    2017-05-01

    The operation of attention on visible objects involves a sequence of cognitive processes. The current study firstly aimed to elucidate the effects of practice on neural mechanisms underlying attentional processes as measured with both behavioural and electrophysiological measures. Secondly, it aimed to identify any pattern in the relationship between Event-Related Potential (ERP) components which play a role in the operation of attention in vision. Twenty-seven participants took part in two recording sessions one week apart, performing an experimental paradigm which combined a match-to-sample task with a memory-guided efficient visual-search task within one trial sequence. Overall, practice decreased behavioural response times, increased accuracy, and modulated several ERP components that represent cognitive and neural processing stages. This neuromodulation through practice was also associated with an enhanced link between behavioural measures and ERP components and with an enhanced cortico-cortical interaction of functionally interconnected ERP components. Principal component analysis (PCA) of the ERP amplitude data revealed three components, having different rostro-caudal topographic representations. The first component included both the centro-parietal and parieto-occipital mismatch triggered negativity - involved in integration of visual representations of the target with current task-relevant representations stored in visual working memory - loaded with second negative posterior-bilateral (N2pb) component, involved in categorising specific pop-out target features. The second component comprised the amplitude of bilateral anterior P2 - related to detection of a specific pop-out feature - loaded with bilateral anterior N2, related to detection of conflicting features, and fronto-central mismatch triggered negativity. The third component included the parieto-occipital N1 - related to early neural responses to the stimulus array - which loaded with the second

  3. The processing of spatial information in short-term memory: insights from eye tracking the path length effect.

    Science.gov (United States)

    Guérard, Katherine; Tremblay, Sébastien; Saint-Aubin, Jean

    2009-10-01

    Serial memory for spatial locations increases as the distance between successive stimuli locations decreases. This effect, known as the path length effect [Parmentier, F. B. R., Elford, G., & Maybery, M. T. (2005). Transitional information in spatial serial memory: Path characteristics affect recall performance. Journal of Experimental Psychology: Learning, Memory & Cognition, 31, 412-427], was investigated in a systematic manner using eye tracking and interference procedures to explore the mechanisms responsible for the processing of spatial information. In Experiment 1, eye movements were monitored during a spatial serial recall task--in which the participants have to remember the location of spatially and temporally separated dots on the screen. In the experimental conditions, eye movements were suppressed by requiring participants to incessantly move their eyes between irrelevant locations. Ocular suppression abolished the path length effect whether eye movements were prevented during item presentation or during a 7s retention interval. In Experiment 2, articulatory suppression was combined with a spatial serial recall task. Although articulatory suppression impaired performance, it did not alter the path length effect. Our results suggest that rehearsal plays a key role in serial memory for spatial information, though the effect of path length seems to involve other processes located at encoding, such as the time spent fixating each location and perceptual organization.

  4. 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)

  5. Directed coupling in local field potentials of macaque V4 during visual short-term memory revealed by multivariate autoregressive models

    Directory of Open Access Journals (Sweden)

    Gregor M Hoerzer

    2010-05-01

    Full Text Available Processing and storage of sensory information is based on the interaction between different neural populations rather than the isolated activity of single neurons. In order to characterize the dynamic interaction and transient cooperation of sub-circuits within a neural network, multivariate autoregressive (MVAR models have proven to be an important analysis tool. In this study, we apply directed functional coupling based on MVAR models and describe the temporal and spatial changes of functional coupling between simultaneously recorded local field potentials (LFP in extrastriate area V4 during visual memory. Specifically, we compare the strength and directional relations of coupling based on Generalized Partial Directed Coherence (GDPC measures while two rhesus monkeys perform a visual short-term memory task. In both monkeys we find increases in theta power during the memory period that are accompanied by changes in directed coupling. These interactions are most prominent in the low frequency range encompassing the theta band (3-12~Hz and, more importantly, are asymmetric between pairs of recording sites. Furthermore, we find that the degree of interaction decreases as a function of distance between electrode positions, suggesting that these interactions are a predominantly local phenomenon. Taken together, our results show that directed coupling measures based on MVAR models are able to provide important insights into the spatial and temporal formation of local functionally coupled ensembles during visual memory in V4. Moreover, our findings suggest that visual memory is accompanied not only by a temporary increase of oscillatory activity in the theta band, but by a direction-dependent change in theta coupling, which ultimately represents a change in functional connectivity within the neural circuit.

  6. 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.

  7. 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

  8. Evaluation of Short Term Memory Span Function In Children

    OpenAIRE

    Barış ERGÜL; Arzu ALTIN YAVUZ; Ebru GÜNDOĞAN AŞIK

    2016-01-01

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

  9. Construction of long-term isochronous stress-strain curves by a modeling of short-term creep curves for a Grade 9Cr-1Mo steel

    International Nuclear Information System (INIS)

    Kim, Woo-Gon; Yin, Song-Nan; Koo, Gyeong-Hoi

    2009-01-01

    This study dealt with the construction of long-term isochronous stress-strain curves (ISSC) by a modeling of short-term creep curves for a Grade 9Cr-1Mo steel (G91) which is a candidate material for structural applications in the next generation nuclear reactors as well as in fusion reactors. To do this, tensile material data used in the inelastic constitutive equations was obtained by tensile tests at 550degC. Creep curves were obtained by a series of creep tests with different stress levels of 300MPa to 220MPa at an identical controlled temperature of 550degC. On the basis of these experimental data, the creep curves were characterized by Garofalo's creep model. Three parameters of P 1 , P 2 and P 3 in Garofalo's model were properly optimized by a nonlinear least square fitting (NLSF) analysis. The stress dependency of the three parameters was found to be a linear relationship. But, the P 3 parameter representing the steady state creep rate exhibited a two slope behavior with different stress exponents at a transient stress of about 250 MPa. The long-term creep curves of the G91 steel was modeled by Garofalo's model with only a few short-term creep data. Using the modeled creep curves, the long-term isochronous curves up to 10 5 hours were successfully constructed. (author)

  10. 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

  11. Mental rotation impairs attention shifting and short-term memory encoding: neurophysiological evidence against the response-selection bottleneck model of dual-task performance.

    Science.gov (United States)

    Pannebakker, Merel M; Jolicœur, Pierre; van Dam, Wessel O; Band, Guido P H; Ridderinkhof, K Richard; Hommel, Bernhard

    2011-09-01

    Dual tasks and their associated delays have often been used to examine the boundaries of processing in the brain. We used the dual-task procedure and recorded event-related potentials (ERPs) to investigate how mental rotation of a first stimulus (S1) influences the shifting of visual-spatial attention to a second stimulus (S2). Visual-spatial attention was monitored by using the N2pc component of the ERP. In addition, we examined the sustained posterior contralateral negativity (SPCN) believed to index the retention of information in visual short-term memory. We found modulations of both the N2pc and the SPCN, suggesting that engaging mechanisms of mental rotation impairs the deployment of visual-spatial attention and delays the passage of a representation of S2 into visual short-term memory. Both results suggest interactions between mental rotation and visual-spatial attention in capacity-limited processing mechanisms indicating that response selection is not pivotal in dual-task delays and all three processes are likely to share a common resource like executive control. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Processing of fine grained AISI 304L austenitic stainless steel by cold rolling and high-temperature short-term annealing

    Science.gov (United States)

    Naghizadeh, Meysam; Mirzadeh, Hamed

    2018-05-01

    An advanced thermomechanical process based on the formation and reversion of deformation-induced martensite was used to refine the grain size and enhance the hardness of an AISI 304L austenitic stainless steel. Both low and high reversion annealing temperatures and also the repetition of the whole thermomechanical cycle were considered. While a microstructure with average austenite grain size of a few micrometers was achieved based on cold rolling and high-temperature short-term annealing, an extreme grain refinement up to submicrometer regime was obtained by cold rolling followed by low-temperature long-term annealing. However, the required annealing time was found to be much longer, which negates its appropriateness for industrial production. While a magnificent grain refinement was achieved by one pass of the high-temperature thermomechanical process, the reduction in grain size was negligible by the repetition of the whole cycle. It was found that the hardness of the thermomechanically processed material is much higher than that of the as-received material. The results of the present work were shown to be compatible with the general trend of grain size dependence of hardness for AISI 304L stainless steel based on the Hall-Petch relationship. The results were also discussed based on the X-ray evaluation of dislocation density by modified Williamson-Hall plots.

  13. A Short-Term Outage Model of Wind Turbines with Doubly Fed Induction Generators Based on Supervisory Control and Data Acquisition Data

    Directory of Open Access Journals (Sweden)

    Peng Sun

    2016-10-01

    Full Text Available This paper presents a short-term wind turbine (WT outage model based on the data collected from a wind farm supervisory control and data acquisition (SCADA system. Neural networks (NNs are used to establish prediction models of the WT condition parameters that are dependent on environmental conditions such as ambient temperature and wind speed. The prediction error distributions are discussed and used to calculate probabilities of the operation of protection relays (POPRs that were caused by the threshold exceedance of the environmentally sensitive parameters. The POPRs for other condition parameters are based on the setting time of the operation of protection relays. The union probability method is used to integrate the probabilities of operation of each protection relay to predict the WT short term outage probability. The proposed method has been used for real 1.5 MW WTs with doubly fed induction generators (DFIGs. The results show that the proposed method is more effective in WT outage probability prediction than traditional methods.

  14. 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.

  15. Inhaled nitric oxide improves short term memory and reduces the inflammatory reaction in a mouse model of mild traumatic brain injury.

    Science.gov (United States)

    Liu, Ping; Li, Yong-Sheng; Quartermain, David; Boutajangout, Allal; Ji, Yong

    2013-07-19

    Although the mechanisms underlying mild traumatic brain injury (mTBI) are becoming well understood, treatment options are still limited. In the present study, mTBI was induced by a weight drop model to produce a closed head injury to mice and the effect of inhaled nitric oxide (INO) was evaluated by a short term memory task (object recognition task) and immunohistochemical staining of glial fibrillary acidic protein (GFAP) and CD45 for the detection of reactive astrocytes and microglia. Results showed that mTBI model did not produce brain edema, skull fracture or sensorimotor coordination dysfunctions. Mice did however exhibit a significant deficit in short term memory (STM) and strong inflammatory reaction in the ipsilateral cortex and hippocampus compared to sham-injured controls 24h after mTBI. Additional groups of untreated mice tested 3 and 7 days later, demonstrated that recognition memory had recovered to normal levels by Day 3. Mice treated with 10ppm INO for 4 or 8h, beginning immediately after TBI demonstrated significantly improved STM at 24h when compared with room air controls (pshort durations of INO prevents this memory loss and also attenuates the inflammatory response. These findings may have relevance for the treatment of patients diagnosed with concussion. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. 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.

  17. Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: an integrated modelling approach in maize.

    Science.gov (United States)

    Chenu, Karine; Chapman, Scott C; Hammer, Graeme L; McLean, Greg; Salah, Halim Ben Haj; Tardieu, François

    2008-03-01

    Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

  18. 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.

  19. 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.

  20. Why do short term workers have high mortality?

    DEFF Research Database (Denmark)

    Kolstad, Henrik; Olsen, Jørn

    1999-01-01

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

  1. REMI and ROUSE: Quantitative Models for Long-Term and Short-Term Priming in Perceptual Identification

    NARCIS (Netherlands)

    E.J. Wagenmakers (Eric-Jan); R. Zeelenberg (René); D.E. Huber (David); J.G.W. Raaijmakers (Jeroen)

    2003-01-01

    textabstractThe REM model originally developed for recognition memory (Shiffrin & Steyvers, 1997) has recently been extended to implicit memory phenomena observed during threshold identification of words. We discuss two REM models based on Bayesian principles: a model for long-term priming (REMI;

  2. Short-term electricity prices forecasting based on support vector regression and Auto-regressive integrated moving average modeling

    International Nuclear Information System (INIS)

    Che Jinxing; Wang Jianzhou

    2010-01-01

    In this paper, we present the use of different mathematical models to forecast electricity price under deregulated power. A successful prediction tool of electricity price can help both power producers and consumers plan their bidding strategies. Inspired by that the support vector regression (SVR) model, with the ε-insensitive loss function, admits of the residual within the boundary values of ε-tube, we propose a hybrid model that combines both SVR and Auto-regressive integrated moving average (ARIMA) models to take advantage of the unique strength of SVR and ARIMA models in nonlinear and linear modeling, which is called SVRARIMA. A nonlinear analysis of the time-series indicates the convenience of nonlinear modeling, the SVR is applied to capture the nonlinear patterns. ARIMA models have been successfully applied in solving the residuals regression estimation problems. The experimental results demonstrate that the model proposed outperforms the existing neural-network approaches, the traditional ARIMA models and other hybrid models based on the root mean square error and mean absolute percentage error.

  3. 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.

  4. Impact of Bio-optical Data Assimilation on Short-term Coupled Physical, Bio-optical Model Predictions

    Science.gov (United States)

    2013-04-30

    photosynthetically active radiation (PAR) which drives photosynthesis of the ecosystem model, and relevant to the forecast of the underwater light...highly uncertain model parameters. Only P\\ and PI are prognostic variables in (1) and (2). [is] Phytoplankton photosynthesis in the biochemical model...Application to remote sensing and database activities, Mar. Chem., #5(2004), 41-61. Cossarini G.. P. F. J. Lcrmusiaux. and C. Solidoro (2009), Lagoon of

  5. 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.

  6. 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 catchments and are applied in a daily version of the model. The results demonstrate the importance of ensuring that field observations are measuring the same hydrological variables as the model simulations. At one study site, there was a mismatch in the soil...

  7. Long-term power generation expansion planning with short-term demand response: Model, algorithms, implementation, and electricity policies

    Science.gov (United States)

    Lohmann, Timo

    Electric sector models are powerful tools that guide policy makers and stakeholders. Long-term power generation expansion planning models are a prominent example and determine a capacity expansion for an existing power system over a long planning horizon. With the changes in the power industry away from monopolies and regulation, the focus of these models has shifted to competing electric companies maximizing their profit in a deregulated electricity market. In recent years, consumers have started to participate in demand response programs, actively influencing electricity load and price in the power system. We introduce a model that features investment and retirement decisions over a long planning horizon of more than 20 years, as well as an hourly representation of day-ahead electricity markets in which sellers of electricity face buyers. This combination makes our model both unique and challenging to solve. Decomposition algorithms, and especially Benders decomposition, can exploit the model structure. We present a novel method that can be seen as an alternative to generalized Benders decomposition and relies on dynamic linear overestimation. We prove its finite convergence and present computational results, demonstrating its superiority over traditional approaches. In certain special cases of our model, all necessary solution values in the decomposition algorithms can be directly calculated and solving mathematical programming problems becomes entirely obsolete. This leads to highly efficient algorithms that drastically outperform their programming problem-based counterparts. Furthermore, we discuss the implementation of all tailored algorithms and the challenges from a modeling software developer's standpoint, providing an insider's look into the modeling language GAMS. Finally, we apply our model to the Texas power system and design two electricity policies motivated by the U.S. Environment Protection Agency's recently proposed CO2 emissions targets for the

  8. 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%.

  9. Benefits of spatiotemporal modeling for short-term wind power forecasting at both individual and aggregated levels

    DEFF Research Database (Denmark)

    Lenzi, Amanda; Steinsland, Ingelin; Pinson, Pierre

    2018-01-01

    The share of wind energy in total installed power capacity has grown rapidly in recent years. Producing accurate and reliable forecasts of wind power production, together with a quantification of the uncertainty, is essential to optimally integrate wind energy into power systems. We build...... spatiotemporal models for wind power generation and obtain full probabilistic forecasts from 15 min to 5 h ahead. Detailed analyses of forecast performances on individual wind farms and aggregated wind power are provided. The predictions from our models are evaluated on a data set from wind farms in western...... Denmark using a sliding window approach, for which estimation is performed using only the last available measurements. The case study shows that it is important to have a spatiotemporal model instead of a temporal one to achieve calibrated aggregated forecasts. Furthermore, spatiotemporal models have...

  10. 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

  11. Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters

    OpenAIRE

    Fusco, Francesco; Ringwood, John

    2010-01-01

    Time domain control of wave energy converters requires knowledge of future incident wave elevation in order to approach conditions for optimal energy extraction. Autoregressive models revealed to be a promising approach to the prediction of future values of the wave elevation only from its past history. Results on real wave observations from different ocean locations show that AR models allow to achieve very good predictions for more than one wave period in the future if ...

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. Comparison of Multi-shot Models for Short-term Re-identification of People using RGB-D Sensors

    DEFF Research Database (Denmark)

    Møgelmose, Andreas; Bahnsen, Chris; Moeslund, Thomas B.

    2015-01-01

    This work explores different types of multi-shot descriptors for re-identification in an on-the-fly enrolled environment using RGB-D sensors. We present a full re-identification pipeline complete with detection, segmentation, feature extraction, and re-identification, which expands on previous work...... by using multi-shot descriptors modeling people over a full camera pass instead of single frames with no temporal linking. We compare two different multi-shot models; mean histogram and histogram series, and test them each in 3 different color spaces. Both histogram descriptors are assisted by a depth...

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

    NARCIS (Netherlands)

    Nascimento, do A.F.; Mendona, E.D.; Leite, L.F.C.; Scholberg, J.M.S.; Neves, J.C.L.

    2012-01-01

    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

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

    Science.gov (United States)

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

    2014-02-01

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

  19. 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.

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

    Science.gov (United States)

    Zhao, Xiukuan; Liu, Libo; Ning, Baiqi

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

  1. 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.

  2. 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

  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. 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.

  5. 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)

  6. 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.

    2012-01-01

    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…

  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-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.

  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. The Role of Short-term Consolidation in Memory Persistence

    OpenAIRE

    Timothy J. Ricker

    2015-01-01

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

  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. 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.

  15. 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.

  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; 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)

  17. Short-term Memory of Deep RNN

    OpenAIRE

    Gallicchio, Claudio

    2018-01-01

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

  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. A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Xike Zhang

    2018-05-01

    Full Text Available Daily land surface temperature (LST forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD coupled with Machine Learning (ML algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijaing stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs and a single residue item. Then, the Partial Autocorrelation Function (PACF is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE, Mean Absolute Error (MAE, Mean Absolute Percentage Error (MAPE, Root Mean Square Error (RMSE, Pearson Correlation Coefficient (CC and Nash-Sutcliffe Coefficient of Efficiency (NSCE. To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN, LSTM and Empirical Mode Decomposition (EMD coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other

  20. A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.

    Science.gov (United States)

    Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

    2018-05-21

    Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijaing stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five

  1. 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.

  2. 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

  3. Induction of a specific strong polyantigenic cellular immune response after short-term chemotherapy controls bacillary reactivation in murine and guinea pig experimental models of tuberculosis.

    Science.gov (United States)

    Guirado, Evelyn; Gil, Olga; Cáceres, Neus; Singh, Mahavir; Vilaplana, Cristina; Cardona, Pere-Joan

    2008-08-01

    RUTI is a therapeutic vaccine that is generated from detoxified and liposomed Mycobacterium tuberculosis cell fragments that has demonstrated its efficacy in the control of bacillus reactivation after short-term chemotherapy. The aim of this study was to characterize the cellular immune response generated after the therapeutic administration of RUTI and to corroborate the lack of toxicity of the vaccine. Mouse and guinea pig experimental models were infected with a low-dose M. tuberculosis aerosol. RUTI-treated animals showed the lowest bacillary load in both experimental models. RUTI also decreased the percentage of pulmonary granulomatous infiltration in the mouse and guinea pig models. This was not the case after Mycobacterium bovis BCG treatment. Cellular immunity was studied through the characterization of the intracellular gamma interferon (IFN-gamma)-producing cells after the splenocytes' stimulation with M. tuberculosis-specific structural and growth-related antigens. Our data show that the difference between the therapeutic administration of BCG and RUTI resides mainly in the stronger activation of IFN-gamma(+) CD4(+) cells and CD8(+) cells against tuberculin purified protein derivative, ESAT-6, and Ag85B that RUTI generates. Both vaccines also triggered a specific immune response against the M. tuberculosis structural antigens Ag16kDa and Ag38kDa and a marked mRNA expression of IFN-gamma, tumor necrosis factor, interleukin-12, inducible nitric oxide synthase, and RANTES in the lung. The results show that RUTI's therapeutic effect is linked not only to the induction of a Th1 response but also to the stimulation of a quicker and stronger specific immunity against structural and growth-related antigens that reduces both the bacillary load and the pulmonary pathology.

  4. 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.

  5. Comparison of MELCOR modeling techniques and effects of vessel water injection on a low-pressure, short-term, station blackout at the Grand Gulf Nuclear Station

    International Nuclear Information System (INIS)

    Carbajo, J.J.

    1995-06-01

    A fully qualified, best-estimate MELCOR deck has been prepared for the Grand Gulf Nuclear Station and has been run using MELCOR 1.8.3 (1.8 PN) for a low-pressure, short-term, station blackout severe accident. The same severe accident sequence has been run with the same MELCOR version for the same plant using the deck prepared during the NUREG-1150 study. A third run was also completed with the best-estimate deck but without the Lower Plenum Debris Bed (BH) Package to model the lower plenum. The results from the three runs have been compared, and substantial differences have been found. The timing of important events is shorter, and the calculated source terms are in most cases larger for the NUREG-1150 deck results. However, some of the source terms calculated by the NUREG-1150 deck are not conservative when compared to the best-estimate deck results. These results identified some deficiencies in the NUREG-1150 model of the Grand Gulf Nuclear Station. Injection recovery sequences have also been simulated by injecting water into the vessel after core relocation started. This marks the first use of the new BH Package of MELCOR to investigate the effects of water addition to a lower plenum debris bed. The calculated results indicate that vessel failure can be prevented by injecting water at a sufficiently early stage. No pressure spikes in the vessel were predicted during the water injection. The MELCOR code has proven to be a useful tool for severe accident management strategies

  6. 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

  7. 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.

  8. FFT transformed quantitative EEG analysis of short term memory load.

    Science.gov (United States)

    Singh, Yogesh; Singh, Jayvardhan; Sharma, Ratna; Talwar, Anjana

    2015-07-01

    The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.

  9. 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.

  10. Short-term plasticity as a neural mechanism supporting memory and attentional functions.

    Science.gov (United States)

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

    2011-11-08

    Based on behavioral studies, several relatively distinct perceptual and cognitive functions have been defined in cognitive psychology such as sensory memory, short-term memory, and selective attention. Here, we review evidence suggesting that some of these functions may be supported by shared underlying neuronal mechanisms. Specifically, we present, based on an integrative review of the literature, a hypothetical model wherein short-term plasticity, in the form of transient center-excitatory and surround-inhibitory modulations, constitutes a generic processing principle that supports sensory memory, short-term memory, involuntary attention, selective attention, and perceptual learning. In our model, the size and complexity of receptive fields/level of abstraction of neural representations, as well as the length of temporal receptive windows, increases as one steps up the cortical hierarchy. Consequently, the type of input (bottom-up vs. top down) and the level of cortical hierarchy that the inputs target, determine whether short-term plasticity supports purely sensory vs. semantic short-term memory or attentional functions. Furthermore, we suggest that rather than discrete memory systems, there are continuums of memory representations from short-lived sensory ones to more abstract longer-duration representations, such as those tapped by behavioral studies of short-term memory. Copyright © 2011 Elsevier B.V. All rights reserved.

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

    KAUST Repository

    Zhu, Xinxin; Genton, Marc G.

    2012-01-01

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

  12. 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.

  13. 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; Reis Lara, Aleluia; 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.

  14. 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.

  15. Short-Term Memory in Habituation and Dishabituation

    Science.gov (United States)

    Whitlow, Jesse William, Jr.

    1975-01-01

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

  16. Short term depression unmasks the ghost frequency.

    Directory of Open Access Journals (Sweden)

    Tjeerd V Olde Scheper

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

  17. 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.

  18. 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).

  19. 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.

  20. 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.

  1. 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.

  2. Investigating domain-general short-term memory for order versus specific item memory in developmental dyslexia

    OpenAIRE

    Hachmann, Wibke Maria

    2012-01-01

    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. At the same time, models of short-term memory increasingly incorporate a distinction of order and item processing. This work aims to investigate whether serial order processing deficiencies in dyslexia can be traced back to a selective impairment of short-term memory for serial order, and whether this impairment also aff...

  3. 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.

  4. Measuring Short-term Energy Security

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-07-01

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

  5. A Conceptual Model for Calculating the Return of Costs Invested in the Creation of an Economic Security Service, During a Short-Term Period

    Directory of Open Access Journals (Sweden)

    Melikhova Tetiana O.

    2018-02-01

    Full Text Available The article is aimed at suggesting methods for calculating the short-term period of return of costs invested in creation of an economic security service. The article considers approaches to calculation of the period of return of costs, advanced at the level of enterprise, which build the methodical basis for definition of such period. At the level of structural subdivisions of enterprise, which do not produce products, it is suggested to use conditional money flow as a source of financing advanced costs. The calculation of the short-term return on investment at the enterprise level provides for: allocation of expenses for the permanent and the replacement parts during the year; determination of the production of money flow and the money flow accumulated during the year. Annual depreciation payments are the basis of fixed costs. Methods of determination of the gross, net, valid, and specified periods of return of costs, advanced during the year for introduction of an economic security service at enterprise, have been suggested.

  6. 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

  7. 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

  8. Short-term memory and dual task performance

    Science.gov (United States)

    Regan, J. E.

    1982-01-01

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

  9. Short-term plasticity in auditory cognition.

    Science.gov (United States)

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

    2007-12-01

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

  10. Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

    Science.gov (United States)

    Seeley, Karen M.

    2004-01-01

    This article examines the challenges specific to short-term intercultural treatments and recently developed approaches to intercultural treatments based on notions of cultural knowledge and cultural competence. The article introduces alternative approaches to short-term intercultural treatments based on ethnographic inquiry adapted for clinical…

  11. 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.

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

    OpenAIRE

    Jones, Gary; Macken, Bill

    2017-01-01

    Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term...

  13. The Conceptual Model of Calculating the Return Period of the Costs for Creation of the Enterprise’s Economic Security Service in the Short-Term Period

    Directory of Open Access Journals (Sweden)

    Melikhova Tetiana O.

    2018-03-01

    Full Text Available Determination of the return period of the costs, advanced for the creation of economic security service of enterprise during a year, involves consideration of interaction of the conditional money flow, accumulated for a certain number of months, and the constant costs. The main component of the constant costs are the annual depreciation deductions. The return period is considered as gross, net, valid, and specified. The gross (net, valid, and specified return period is the time, wherein the gross conditional money flow, equal to the advanced costs, will be accumulated. The gross return period, taking account of the effect of time factor, is proposed to be defined as the ratio of annual depreciation deductions increased by the annual compounding coefficient to the conditional average monthly gross money flow, increased by the average monthly inflation index. As for the short-term period, a relationship between the gross, net, valid, and specified return periods of the costs, advanced to the creation of the economic security service, has been identified. The net (valid, specified return period is equal to the gross period adjusted to the coefficient of excess of the gross conditional money flow, accumulated in the gross period, over the net (valid, specified conditional cash flow.

  14. 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...

  15. Radiation induced processes in moss cells. Short term and long term radiation responses of special interest after microbeam uv irradiation of the haploid moss cells of Funaria hygrometrica

    Energy Technology Data Exchange (ETDEWEB)

    Doehren, R v [Mainz Univ. (F.R. Germany). Inst. fuer Biochemie

    1975-01-01

    The moss F.h. shows apical growth in the protonema cells which spread radially from the spor. Every apical daughter cell during the state of 'Caulonema' and just before in the state of 'Caulonema Primanen' initiates cell division as soon as more than twice the length of the mother cell is reached. All this allows to follow radiation effects in single cells conveniently. UV irradiation on the range of 254 nm and 280 nm delivered at different parts of the cell area delays cell division markedly may suppress it, and is able to stop the process of growing in relation to the delivered dose and to the irradiated area as well. In case of irradiation of the area next to where the membrane is just being formed - that is to say next to the phragmoplast - the new membrane will be wrongly oriented. In particular giant cells are occurring in the case of nucleus irradiation during early prophase.

  16. Nuisance forecasting. Univariate modelling and very-short-term forecasting of winter smog episodes; Immissionsprognose. Univariate Modellierung und Kuerzestfristvorhersage von Wintersmogsituationen

    Energy Technology Data Exchange (ETDEWEB)

    Schlink, U.

    1996-12-31

    The work evaluates specifically the nuisance data provided by the measuring station in the centre of Leipig during the period from 1980 to 1993, with the aim to develop an algorithm for making very short-term forecasts of excessive nuisances. Forecasting was to be univariate, i.e., based exclusively on the half-hourly readings of SO{sub 2} concentrations taken in the past. As shown by Fourier analysis, there exist three main and mutually independent spectral regions: the high-frequency sector (period < 12 hours) of unstable irregularities, the seasonal sector with the periods of 24 and 12 hours, and the low-frequency sector (period > 24 hours). After breaking the measuring series up into components, the low-frequency sector is termed trend component, or trend for short. For obtaining the components, a Kalman filter is used. It was found that smog episodes are most adequately described by the trend component. This is therefore more closely investigated. The phase representation then shows characteristic trajectories of the trends. (orig./KW) [Deutsch] In der vorliegende Arbeit wurden speziell die Immissionsdaten der Messstation Leipzig-Mitte des Zeitraumes 1980-1993 mit dem Ziel der Erstellung eines Algorithmus fuer die Kuerzestfristprognose von Ueberschreitungssituationen untersucht. Die Prognosestellung sollte allein anhand der in der Vergangenheit registrierten Halbstundenwerte der SO{sub 2}-Konzentration, also univariat erfolgen. Wie die Fourieranalyse zeigt, gibt es drei wesentliche und voneinander unabhaengige Spektralbereiche: Den hochfrequenten Bereich (Periode <12 Stunden) der instabilen Irregularitaeten, den saisonalen Anteil mit den Perioden von 24 und 12 Stunden und den niedrigfrequenten Bereich (Periode >24 Stunden). Letzterer wird nach einer Zerlegung der Messreihe in Komponenten als Trendkomponente (oder kurz Trend) bezeichnet. Fuer die Komponentenzerlegung wird ein Kalman-Filter verwendet. Es stellt sich heraus, dass Smogepisoden am deutlichsten

  17. 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

  18. 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.

  19. Fast Weight Long Short-Term Memory

    OpenAIRE

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

    2018-01-01

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

  20. 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.

  1. Circadian modulation of short-term memory in Drosophila.

    Science.gov (United States)

    Lyons, Lisa C; Roman, Gregg

    2009-01-01

    Endogenous biological clocks are widespread regulators of behavior and physiology, allowing for a more efficient allocation of efforts and resources over the course of a day. The extent that different processes are regulated by circadian oscillators, however, is not fully understood. We investigated the role of the circadian clock on short-term associative memory formation using a negatively reinforced olfactory-learning paradigm in Drosophila melanogaster. We found that memory formation was regulated in a circadian manner. The peak performance in short-term memory (STM) occurred during the early subjective night with a twofold performance amplitude after a single pairing of conditioned and unconditioned stimuli. This rhythm in memory is eliminated in both timeless and period mutants and is absent during constant light conditions. Circadian gating of sensory perception does not appear to underlie the rhythm in short-term memory as evidenced by the nonrhythmic shock avoidance and olfactory avoidance behaviors. Moreover, central brain oscillators appear to be responsible for the modulation as cryptochrome mutants, in which the antennal circadian oscillators are nonfunctional, demonstrate robust circadian rhythms in short-term memory. Together these data suggest that central, rather than peripheral, circadian oscillators modulate the formation of short-term associative memory and not the perception of the stimuli.

  2. Holding Multiple Items in Short Term Memory: A Neural Mechanism

    Science.gov (United States)

    Rolls, Edmund T.; Dempere-Marco, Laura; Deco, Gustavo

    2013-01-01

    Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging. PMID:23613789

  3. 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.

  4. 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.

  5. 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

  6. Cascades in model steels: The effect of cementite (Fe3C) and Cr23C6 particles on short-term crystal damage

    Science.gov (United States)

    Henriksson, K. O. E.

    2015-06-01

    Ferritic stainless steel can be modeled as an iron matrix containing precipitates of cementite (Fe3C) and Cr23C6. When used in nuclear power production the steels in the vicinity of the core start to accumulate damage due to neutrons. The role of the afore-mentioned carbides in this process is not well understood. In order to clarify the situation bulk cascades created by primary recoils in model steels have been carried out in the present work. Investigated configurations consisted of bulk ferrite containing spherical particles (diameter of 4 nm) of either (1) Fe3C or (2) Cr23C6. Primary recoils were initiated at different distances from the inclusions, with recoil energies varying between 100 eV and 1 keV. Results for the number of point defects such as vacancies and antisites are presented. These findings indicate that defects are also remaining when cascades are started outside the carbide inclusions. The work uses a recently developed Abell-Brenner-Tersoff potential for the Fe-Cr-C system.

  7. Proteomic analysis of a model unicellular green alga, Chlamydomonas reinhardtii, during short-term exposure to irradiance stress reveals significant down regulation of several heat-shock proteins.

    Science.gov (United States)

    Mahong, Bancha; Roytrakul, Suttiruk; Phaonaklop, Narumon; Wongratana, Janewit; Yokthongwattana, Kittisak

    2012-03-01

    Oxygenic photosynthetic organisms often suffer from excessive irradiance, which cause harmful effects to the chloroplast proteins and lipids. Photoprotection and the photosystem II repair processes are the mechanisms that plants deploy to counteract the drastic effects from irradiance stress. Although the protective and repair mechanisms seemed to be similar in most plants, many species do confer different level of tolerance toward high light. Such diversity may originate from differences at the molecular level, i.e., perception of the light stress, signal transduction and expression of stress responsive genes. Comprehensive analysis of overall changes in the total pool of proteins in an organism can be performed using a proteomic approach. In this study, we employed 2-DE/LC-MS/MS-based comparative proteomic approach to analyze total proteins of the light sensitive model unicellular green alga Chlamydomonas reinhardtii in response to excessive irradiance. Results showed that among all the differentially expressed proteins, several heat-shock proteins and molecular chaperones were surprisingly down-regulated after 3-6 h of high light exposure. Discussions were made on the possible involvement of such down regulation and the light sensitive nature of this model alga.

  8. In vitro short-term exposure to air pollution PM{sub 2.5-0.3} induced cell cycle alterations and genetic instability in a human lung cell coculture model

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Imane [Université de Lille, Lille (France); EA4492-UCEIV, Université du Littoral-Côte d’Opale, Dunkerque (France); Lebanese Atomic Energy Commission – CNRS, Beirut (Lebanon); Verdin, Anthony [Université de Lille, Lille (France); EA4492-UCEIV, Université du Littoral-Côte d’Opale, Dunkerque (France); Escande, Fabienne [Centre de Biologie Pathologie, Centre Hospitalier Régional et Universitaire, Lille (France); Saint-Georges, Françoise [Université de Lille, Lille (France); Groupement Hospitalier de l’Institut Catholique de Lille, Lille (France); Cazier, Fabrice [Université de Lille, Lille (France); Centre Commun de Mesures, Université du Littoral-Côte d’Opale, Dunkerque (France); Mulliez, Philippe [Université de Lille, Lille (France); Groupement Hospitalier de l’Institut Catholique de Lille, Lille (France); Courcot, Dominique; Shirali, Pirouz [Université de Lille, Lille (France); EA4492-UCEIV, Université du Littoral-Côte d’Opale, Dunkerque (France); Gosset, Pierre [Université de Lille, Lille (France); Groupement Hospitalier de l’Institut Catholique de Lille, Lille (France); and others

    2016-05-15

    Although its adverse health effects of air pollution particulate matter (PM2.5) are well-documented and often related to oxidative stress and pro-inflammatory response, recent evidence support the role of the remodeling of the airway epithelium involving the regulation of cell death processes. Hence, the overarching goals of the present study were to use an in vitro coculture model, based on human AM and L132 cells to study the possible alteration of TP53-RB gene signaling pathways (i.e. cell cycle phases, gene expression of TP53, BCL2, BAX, P21, CCND1, and RB, and protein concentrations of their active forms), and genetic instability (i.e. LOH and/or MSI) in the PM{sub 2.5-0.3}-exposed coculture model. PM{sub 2.5-0.3} exposure of human AM from the coculture model induced marked cell cycle alterations after 24 h, as shown by increased numbers of L132 cells in subG1 and S+G2 cell cycle phases, indicating apoptosis and proliferation. Accordingly, activation of the TP53-RB gene signaling pathways after the coculture model exposure to PM{sub 2.5-0.3} was reported in the L132 cells. Exposure of human AM from the coculture model to PM{sub 2.5-0.3} resulted in MS alterations in 3p chromosome multiple critical regions in L132 cell population. Hence, in vitro short-term exposure of the coculture model to PM{sub 2.5-0.3} induced cell cycle alterations relying on the sequential occurrence of molecular abnormalities from TP53-RB gene signaling pathway activation and genetic instability. - Highlights: • Better knowledge on health adverse effects of air pollution PM{sub 2.5}. • Human alveolar macrophage and normal human epithelial lung cell coculture. • Molecular abnormalities from TP53-RB gene signaling pathway. • Loss of heterozygosity and microsatellite instability. • Pathologic changes in morphology and number of cells in relation to airway remodeling.

  9. 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.

  10. 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

  11. Real-time energy resources scheduling considering short-term and very short-term wind forecast

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

    2012-07-01

    This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

  12. 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.

  13. 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…

  14. Scalable data-driven short-term traffic prediction

    NARCIS (Netherlands)

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

    2017-01-01

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

  15. Retention interval affects visual short-term memory encoding.

    Science.gov (United States)

    Bankó, Eva M; Vidnyánszky, Zoltán

    2010-03-01

    Humans can efficiently store fine-detailed facial emotional information in visual short-term memory for several seconds. However, an unresolved question is whether the same neural mechanisms underlie high-fidelity short-term memory for emotional expressions at different retention intervals. Here we show that retention interval affects the neural processes of short-term memory encoding using a delayed facial emotion discrimination task. The early sensory P100 component of the event-related potentials (ERP) was larger in the 1-s interstimulus interval (ISI) condition than in the 6-s ISI condition, whereas the face-specific N170 component was larger in the longer ISI condition. Furthermore, the memory-related late P3b component of the ERP responses was also modulated by retention interval: it was reduced in the 1-s ISI as compared with the 6-s condition. The present findings cannot be explained based on differences in sensory processing demands or overall task difficulty because there was no difference in the stimulus information and subjects' performance between the two different ISI conditions. These results reveal that encoding processes underlying high-precision short-term memory for facial emotional expressions are modulated depending on whether information has to be stored for one or for several seconds.

  16. Long story short: an introduction to the short-term and long-term Six Sigma quality and its importance in the laboratory medicine for the management of extra-analytical processes.

    Science.gov (United States)

    Ialongo, Cristiano; Bernardini, Sergio

    2018-06-18

    There is a compelling need for quality tools that enable effective control of the extra-analytical phase. In this regard, Six Sigma seems to offer a valid methodological and conceptual opportunity, and in recent times, the International Federation of Clinical Chemistry and Laboratory Medicine has adopted it for indicating the performance requirements for non-analytical laboratory processes. However, the Six Sigma implies a distinction between short-term and long-term quality that is based on the dynamics of the processes. These concepts are still not widespread and applied in the field of laboratory medicine although they are of fundamental importance to exploit the full potential of this methodology. This paper reviews the Six Sigma quality concepts and shows how they originated from Shewhart's control charts, in respect of which they are not an alternative but a completion. It also discusses the dynamic nature of process and how it arises, concerning particularly the long-term dynamic mean variation, and explains why this leads to the fundamental distinction of quality we previously mentioned.

  17. A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

    Science.gov (United States)

    Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

    2016-06-01

    To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

  18. 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.

  19. 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...

  20. Mental rotation impairs attention shifting and short-term memory encoding: neurophysiological evidence against the response-selection bottleneck model of dual-task performance

    NARCIS (Netherlands)

    Pannebakker, M.M.; van Dam, W.O.; Band, G.P.H.; Ridderinkhof, K.R.; Hommel, B.

    2011-01-01

    Dual tasks and their associated delays have often been used to examine the boundaries of processing in the brain. We used the dual-task procedure and recorded event-related potentials (ERPs) to investigate how mental rotation of a first stimulus (S1) influences the shifting of visual-spatial

  1. FORECASTING ENERGY CONSUMPTION IN SHORT-TERM AND LONG-TERM PERIOD BY USING ARIMAX MODEL IN THE CONSTRUCTION AND MATERIALS SECTOR IN THAILAND

    Directory of Open Access Journals (Sweden)

    Pruethsan Sutthichaimethee

    2017-07-01

    Full Text Available This study aims to analyze the forecasting of energy consumption in the Construction and Materials sectors. The scope of the study covers the forecasting periods of energy consumption for the next 10 years, 2017-2026, 20 years, 2017-2036, and 30 years, 2017-2046, by using ARIMAX Model. The prediction results show that these models are effective in the forecast measured by RMSE, MAE, and MAPE. The results show that from the first model (2,1,1, which predicted the duration of 10 years, 2017-2026, indicates that Thailand has increased an energy consumption rate with the average of 18.09%, while the second model (2,1,2 with the prediction of 20 years, 2017-2036, Thailand arises its energy consumption up to 37.32%. In addition, the third model (2,1,3 predicted the duration of 30 years from 2017 to 2046, and it has found that Thailand increases its energy consumption up to 49.72%.

  2. Short term benefits for laparoscopic colorectal resection.

    Science.gov (United States)

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

    2005-07-20

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

  3. 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...... to 41% for non-digested and 35% for digested manure in the loamy sand. In the sandy soil corresponding C retention was 37 and 29%. The higher C retention from non-digested compared to digested manure differed from the incubation study and was mainly due to the model response to the optimized parameters...

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

    Science.gov (United States)

    Thomas, Diana M; Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

    2015-03-01

    Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing model. The AUC statistic quantified the ROC curve's capacity to classify participants likely to lose models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. © 2015 American Society for Nutrition.

  5. The Use of Indirect Estimates of Soil Moisture to Initialize Coupled Models and its Impact on Short-Term and Seasonal Simulations

    Science.gov (United States)

    Lapenta, William M.; Crosson, William; Dembek, Scott; Lakhtakia, Mercedes

    1998-01-01

    It is well known that soil moisture is a characteristic of the land surface that strongly affects the partitioning of outgoing radiation into sensible and latent heat which significantly impacts both weather and climate. Detailed land surface schemes are now being coupled to mesoscale atmospheric models in order to represent the effect of soil moisture upon atmospheric simulations. However, there is little direct soil moisture data available to initialize these models on regional to continental scales. As a result, a Soil Hydrology Model (SHM) is currently being used to generate an indirect estimate of the soil moisture conditions over the continental United States at a grid resolution of 36 Km on a daily basis since 8 May 1995. The SHM is forced by analyses of atmospheric observations including precipitation and contains detailed information on slope soil and landcover characteristics.The purpose of this paper is to evaluate the utility of initializing a detailed coupled model with the soil moisture data produced by SHM.

  6. Decay uncovered in nonverbal short-term memory.

    Science.gov (United States)

    Mercer, Tom; McKeown, Denis

    2014-02-01

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

  7. Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study)123

    Science.gov (United States)

    Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

    2015-01-01

    Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve’s capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Results: Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). Conclusions: The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. The POUNDS Lost study was registered at clinicaltrials.gov as NCT00072995. PMID:25733628

  8. 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.

  9. 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

  10. Short-Term Energy Outlook: Quarterly projections. Fourth quarter 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-11-05

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the fourth quarter of 1993 through the fourth quarter of 1994. Values for the third quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications.

  11. 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

  12. 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

  13. 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

  14. 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.

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

    Science.gov (United States)

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

    2016-12-01

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

  16. 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.

  17. [Short-term crisis psychotherapy in children with posttraumatic stress disorder in the frames of the "Dobryakov-Nikol'skaya" rehabilitation model].

    Science.gov (United States)

    Dobriakov, I V; Nikol'skaia, I M

    2009-01-01

    Peculiarities of the model of medical-psychological help elaborated by the authors are presented on the example of the psychotherapeutic work with children, victims of the terror act in Beslan. A complex of methods which includes "debriefing", and using of tails and games in the combination with the technique of serial drawings and stories was applied in accordance to rules of crisis psychotherapy. Results demonstrate that the methods described allow to get into contact to the child, discover and remove his/her emotional experience related to the traumatic situation.

  18. 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.

  19. 大气水汽同位素组成的短期变异特征%Short-term variations of vapor isotope ratios reveal the influence of atmospheric processes

    Institute of Scientific and Technical Information of China (English)

    张世春; 孙晓敏; 王建林; 于贵瑞; 温学发

    2011-01-01

    Stable isotopes of atmospheric water vapor reveal rich information on water movement and phase changes in the atmosphere. Here we presented two nearly continuous time-series of δD and δ18O of atmospheric water vapor (δv) measured at hourly intervals in surface air in Beijing and above a winter wheat canopy in Shijiazhuang using in-situ measurement technique. During the precipitation events, the δv values in both Beijing and Shijiazhuang were in the state of equilibrium with precipitation water, revealing the influence of precipitation processes. However, the δv departures from the equilibrium state were positively correlated with local relative humidity. Note that the δv tended to enrich in Beijing, but deplete in Shijiazhuang during the precipitation events, which mainly resulted from the influence of transpiration processes that enriched the δv in Shijiazhuang. On seasonal time-scale, the δvvalues were log-linear functions of water vapor mixing ratios in both Beijing and Shijiazhuang. The water vapor mixing ratio was an excellent predictor of the δv by the Rayleigh distillation mechanisms, indicating that air mass advection could also play an important role in determining the δv. On a diurnal time-scale, the δv reached the minimum in the early afternoon hours in Beijing which was closely related to the atmospheric processes of boundary layer entrainment. During the peak of growing season of winter wheat, however, the δv reached the minimum in the early morning, and increased gradually through the daytime, and reached the maximum in the late afternoon, which was responsible by the interaction between boundary layer entrainment and the local atmospheric processes, such as transpiration and dew formation. This study has the implications for the important role of vegetation in determining the surface δv and highlights the need to conduct δv measurement on short-term (e.g. diurnal) time scales.

  20. 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.

  1. A model-independent comparison of the rates of uptake and short term retention of 47Ca and 85Sr by the skeleton.

    Science.gov (United States)

    Reeve, J; Hesp, R

    1976-12-22

    1. A method has been devised for comparing the impulse response functions of the skeleton for two or more boneseeking tracers, and for estimating the contribution made by measurement errors to the differences between any pair of impulse response functions. 2. Comparisons were made between the calculated impulse response functions for 47Ca and 85Sr obtained in simultaneous double tracer studies in sixteen subjects. Collectively the differences between the 47Ca and 85Sr functions could be accounted for entirely by measurement errors. 3. Because the calculation of an impulse response function requires fewer a priori assumptions than other forms of mathematical analysis, and automatically corrects for differences induced by recycling of tracer and non-identical rates of excretory plasma clearance of tracer, it is concluded that differences shown in previous in vivo studies between the fluxes of Ca and Sr into bone can be fully accounted for by undetermined oversimplifications in the various mathematical models used to analyse the results of those studies. 85Sr is therefore an adequate tracer for bone calcium in most in vivo studies.

  2. Effects of 1H + 16O Charged Particle Irradiation on Short-Term Memory and Hippocampal Physiology in a Murine Model.

    Science.gov (United States)

    Kiffer, Frederico; Carr, Hannah; Groves, Thomas; Anderson, Julie E; Alexander, Tyler; Wang, Jing; Seawright, John W; Sridharan, Vijayalakshmi; Carter, Gwendolyn; Boerma, Marjan; Allen, Antiño R

    2018-01-01

    Radiation from galactic cosmic rays (GCR) poses a significant health risk for deep-space flight crews. GCR are unique in their extremely high-energy particles. With current spacecraft shielding technology, some of the predominant particles astronauts would be exposed to are 1 H + 16 O. Radiation has been shown to cause cognitive deficits in mice. The hippocampus plays a key role in memory and cognitive tasks; it receives information from the cortex, undergoes dendritic-dependent processing and then relays information back to the cortex. In this study, we investigated the effects of combined 1 H + 16 O irradiation on cognition and dendritic structures in the hippocampus of adult male mice three months postirradiation. Six-month-old male C57BL/6 mice were irradiated first with 1 H (0.5 Gy, 150 MeV/n) and 1 h later with 16 O (0.1 Gy, 600 MeV/n) at the NASA Space Radiation Laboratory (Upton, NY). Three months after irradiation, animals were tested for hippocampus-dependent cognitive performance using the Y-maze. Upon sacrifice, molecular and morphological assessments were performed on hippocampal tissues. During Y-maze testing, the irradiated mice failed to distinguish the novel arm, spending approximately the same amount of time in all three arms during the retention trial relative to sham-treated controls. Irradiated animals also showed changes in expression of glutamate receptor subunits and synaptic density-associated proteins. 1 H + 16 O radiation compromised dendritic morphology in the cornu ammonis 1 and dentate gyrus within the hippocampus. These data indicate cognitive injuries due to 1 H + 16 O at three months postirradiation.

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

    Science.gov (United States)

    Camacho-Alonso, Fabio; López-Jornet, Pía; Vicente-Hernández, Ascensión

    2013-05-01

    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. 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). 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. The administration of bisphosphonates increases the fracture resistance in mandible and femur.

  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 LNG-markets

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  6. Short-term uranium price formation: a methodology

    International Nuclear Information System (INIS)

    Hsieh, L.Y.; de Graffenried, C.L.

    1987-01-01

    One of the major problems in analyzing the short-term uranium market is the lack of a well-defined spot market price. The two primary sources of price data covering the US uranium market are the series published by the US Dept. of Energy (DOE) and by the Nuclear Exchange Corporation (NUEXCO), a private brokerage firm. Because of the differences in both definition and coverage, these two series are not directly comparable. In this study, an econometric model was developed for analyzing the interrelationship between short-term uranium price (NUEXCO exchange value), supply, demand, and future price expectations formed by market participants. The validity of this model has been demonstrated by the fact that all simulation statistics derived are highly significant. Three forecasting scenarios were developed in this study

  7. 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.

  8. Short-term memory in networks of dissociated cortical neurons.

    Science.gov (United States)

    Dranias, Mark R; Ju, Han; Rajaram, Ezhilarasan; VanDongen, Antonius M J

    2013-01-30

    Short-term memory refers to the ability to store small amounts of stimulus-specific information for a short period of time. It is supported by both fading and hidden memory processes. Fading memory relies on recurrent activity patterns in a neuronal network, whereas hidden memory is encoded using synaptic mechanisms, such as facilitation, which persist even when neurons fall silent. We have used a novel computational and optogenetic approach to investigate whether these same memory processes hypothesized to support pattern recognition and short-term memory in vivo, exist in vitro. Electrophysiological activity was recorded from primary cultures of dissociated rat cortical neurons plated on multielectrode arrays. Cultures were transfected with ChannelRhodopsin-2 and optically stimulated using random dot stimuli. The pattern of neuronal activity resulting from this stimulation was analyzed using classification algorithms that enabled the identification of stimulus-specific memories. Fading memories for different stimuli, encoded in ongoing neural activity, persisted and could be distinguished from each other for as long as 1 s after stimulation was terminated. Hidden memories were detected by altered responses of neurons to additional stimulation, and this effect persisted longer than 1 s. Interestingly, network bursts seem to eliminate hidden memories. These results are similar to those that have been reported from similar experiments in vivo and demonstrate that mechanisms of information processing and short-term memory can be studied using cultured neuronal networks, thereby setting the stage for therapeutic applications using this platform.

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

    Science.gov (United States)

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

    2017-11-01

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

  10. Robust Short-Term Memory without Synaptic Learning

    OpenAIRE

    Johnson, Samuel; Marro, J.; Torres, Joaquin J.

    2013-01-01

    Short-term memory in the brain cannot in general be explained the way long-term memory can ??? as a gradual modification of synaptic weights ??? since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining inf...

  11. 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.

  12. 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

  13. Is visual short-term memory depthful?

    Science.gov (United States)

    Reeves, Adam; Lei, Quan

    2014-03-01

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

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

    Science.gov (United States)

    Barzegarjalali, Saeid; Parker, Alice C

    2016-08-01

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

  15. 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.

  16. 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

  17. 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.

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

    Science.gov (United States)

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

    2011-01-01

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

  19. 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.

  20. 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.

  1. Short Term Memory, Working Memory, and Syntactic Comprehension in Aphasia

    Science.gov (United States)

    Caplan, David; Michaud, Jennifer; Hufford, Rebecca

    2013-01-01

    Sixty one people with aphasia were tested on ten tests of short term memory (STM) and for the ability to use syntactic structure to determine the meanings of eleven types of sentences in three tasks – object manipulation, picture matching and picture matching with self-paced listening. Multilevel models showed relationships between measures of the ability to retain and manipulate item and order information in STM and accuracy and RT, and a greater relationship between these STM measures and accuracy and RT for several more complex sentence types in individual tasks. There were no effects of measures of STM that reflect the use of phonological codes or rehearsal on comprehension. There was only one effect of STM measures on self-paced listening times. There were double dissociations between performance on STM and individual comprehension tasks, indicating that normal STM is not necessary to perform normally on these tasks. The results are most easily related to the view that STM plays a facilitatory role in supporting the use of the products of the comprehension process to accomplish operations related to tasks. PMID:23865692

  2. 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.

  3. Resolving semantic and proactive interference in memory over the short-term.

    Science.gov (United States)

    Atkins, Alexandra S; Berman, Marc G; Reuter-Lorenz, Patricia A; Lewis, Richard L; Jonides, John

    2011-07-01

    Interference is a major source of short-term errors of memory. The present investigation explores the relationship between two important forms of interference: proactive interference (PI), induced by the need to reject recently studied items no longer relevant to task performance, and semantic interference (SI), induced by the need to reject lures sharing a meaningful relationship with current memoranda. We explore the possibility that shared cognitive control processes are recruited to resolve both forms of interference. In Experiment 1, we find that the requirement to engage in articulatory suppression during the retention interval of tasks that induce either PI or SI increases both forms of interference similarly and selectively. In Experiment 2, we develop a task to examine PI and SI within the same experimental context. The results show interactive effects between factors that lead to the two forms of interference. Taken together, these findings support contextual-cuing models of short-term remembering (Nairne, Annual Review of Psychology, 53, 53-81 2002), where the context in which retrieval occurs can influence susceptibility to interference. Lastly, we discuss several theoretical hypotheses concerning the cognitive control processes that are recruited to resolve SI and PI in short-term remembering.

  4. Weighted integration of short-term memory and sensory signals in the oculomotor system.

    Science.gov (United States)

    Deravet, Nicolas; Blohm, Gunnar; de Xivry, Jean-Jacques Orban; Lefèvre, Philippe

    2018-05-01

    Oculomotor behaviors integrate sensory and prior information to overcome sensory-motor delays and noise. After much debate about this process, reliability-based integration has recently been proposed and several models of smooth pursuit now include recurrent Bayesian integration or Kalman filtering. However, there is a lack of behavioral evidence in humans supporting these theoretical predictions. Here, we independently manipulated the reliability of visual and prior information in a smooth pursuit task. Our results show that both smooth pursuit eye velocity and catch-up saccade amplitude were modulated by visual and prior information reliability. We interpret these findings as the continuous reliability-based integration of a short-term memory of target motion with visual information, which support modeling work. Furthermore, we suggest that saccadic and pursuit systems share this short-term memory. We propose that this short-term memory of target motion is quickly built and continuously updated, and constitutes a general building block present in all sensorimotor systems.

  5. 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.

  6. Identity modulates short-term memory for facial emotion.

    Science.gov (United States)

    Galster, Murray; Kahana, Michael J; Wilson, Hugh R; Sekuler, Robert

    2009-12-01

    For some time, the relationship between processing of facial expression and facial identity has been in dispute. Using realistic synthetic faces, we reexamined this relationship for both perception and short-term memory. In Experiment 1, subjects tried to identify whether the emotional expression on a probe stimulus face matched the emotional expression on either of two remembered faces that they had just seen. The results showed that identity strongly influenced recognition short-term memory for emotional expression. In Experiment 2, subjects' similarity/dissimilarity judgments were transformed by multidimensional scaling (MDS) into a 2-D description of the faces' perceptual representations. Distances among stimuli in the MDS representation, which showed a strong linkage of emotional expression and facial identity, were good predictors of correct and false recognitions obtained previously in Experiment 1. The convergence of the results from Experiments 1 and 2 suggests that the overall structure and configuration of faces' perceptual representations may parallel their representation in short-term memory and that facial identity modulates the representation of facial emotion, both in perception and in memory. The stimuli from this study may be downloaded from http://cabn.psychonomic-journals.org/content/supplemental.

  7. 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

  8. 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.

  9. 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.

  10. The effect of visual arrangement on visuospatial short-term memory: Insights from children with 22q11.2 deletion syndrome.

    Science.gov (United States)

    Attout, Lucie; Noël, Marie-Pascale; Rousselle, Laurence

    2018-04-11

    Recent models of visuospatial (VSSP) short-term memory postulate the existence of two dissociable mechanisms depending on whether VSSP information is presented simultaneously or sequentially. However, they do not specify to what extent VSSP short-term memory is under the influence of general VSSP processing. This issue was examined in people with 22q11.2 deletion syndrome, a genetic condition involving a VSSP deficit. The configuration of VSSP information was manipulated (structured vs. unstructured) to explore the impact of arrangement on VSSP short-term memory. Two presentation modes were used to see whether the VSSP arrangement has the same impact on simultaneous and sequential short-term memory. Compared to children matched on chronological age, children with 22q11.2 deletion syndrome showed impaired performance only for structured arrangement, regardless of the presentation mode, suggesting an influence of VSSP processing on VSSP short-term memory abilities. A revised cognitive architecture for a model of VSSP short-term memory is proposed.

  11. Short Term Airing by Natural Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per; Perino, M.

    2010-01-01

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

  12. Economics of solar energy: Short term costing

    Science.gov (United States)

    Klee, H.

    The solar economics based on life cycle costs are refuted as both imaginary and irrelevant. It is argued that predicting rates of inflation and fuel escalation, expected life, maintenance costs, and legislation over the next ten to twenty years is pure guesswork. Furthermore, given the high mobility level of the U.S. population, the average consumer is skeptical of long run arguments which will pay returns only to the next owners. In the short term cost analysis, the house is sold prior to the end of the expected life of the system. The cash flow of the seller and buyer are considered. All the relevant factors, including the federal tax credit and the added value of the house because of the solar system are included.

  13. 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.

  14. 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.

  15. 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......, thereby displaying a significant interaction between the two factors. The interaction between target and distracter set size in IPS could not be accounted for by a simple explanation in terms of number of items accessing VSTM. Instead, it led us to a model where items accessing VSTM receive differential...

  16. 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.

  17. 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…

  18. 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...

  19. 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 ...

  20. Continuity of Landsat observations: Short term considerations

    Science.gov (United States)

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

    2011-01-01

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

  1. Fuzzy approach for short term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-04-15

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

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

    OpenAIRE

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

    2012-01-01

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

  3. MHz gravitational waves from short-term anisotropic inflation

    International Nuclear Information System (INIS)

    Ito, Asuka; Soda, Jiro

    2016-01-01

    We reveal the universality of short-term anisotropic inflation. As a demonstration, we study inflation with an exponential type gauge kinetic function which is ubiquitous in models obtained by dimensional reduction from higher dimensional fundamental theory. It turns out that an anisotropic inflation universally takes place in the later stage of conventional inflation. Remarkably, we find that primordial gravitational waves with a peak amplitude around 10 −26 ∼10 −27 are copiously produced in high-frequency bands 10 MHz∼100 MHz. If we could detect such gravitational waves in future, we would be able to probe higher dimensional fundamental theory.

  4. Neural circuit mechanisms of short-term memory

    Science.gov (United States)

    Goldman, Mark

    Memory over time scales of seconds to tens of seconds is thought to be maintained by neural activity that is triggered by a memorized stimulus and persists long after the stimulus is turned off. This presents a challenge to current models of memory-storing mechanisms, because the typical time scales associated with cellular and synaptic dynamics are two orders of magnitude smaller than this. While such long time scales can easily be achieved by bistable processes that toggle like a flip-flop between a baseline and elevated-activity state, many neuronal systems have been observed experimentally to be capable of maintaining a continuum of stable states. For example, in neural integrator networks involved in the accumulation of evidence for decision making and in motor control, individual neurons have been recorded whose activity reflects the mathematical integral of their inputs; in the absence of input, these neurons sustain activity at a level proportional to the running total of their inputs. This represents an analog form of memory whose dynamics can be conceptualized through an energy landscape with a continuum of lowest-energy states. Such continuous attractor landscapes are structurally non-robust, in seeming violation of the relative robustness of biological memory systems. In this talk, I will present and compare different biologically motivated circuit motifs for the accumulation and storage of signals in short-term memory. Challenges to generating robust memory maintenance will be highlighted and potential mechanisms for ameliorating the sensitivity of memory networks to perturbations will be discussed. Funding for this work was provided by NIH R01 MH065034, NSF IIS-1208218, Simons Foundation 324260, and a UC Davis Ophthalmology Research to Prevent Blindness Grant.

  5. Very short-term probabilistic forecasting of wind power with generalized logit-Normal distributions

    DEFF Research Database (Denmark)

    Pinson, Pierre

    2012-01-01

    and probability masses at the bounds. Both auto-regressive and conditional parametric auto-regressive models are considered for the dynamics of their location and scale parameters. Estimation is performed in a recursive least squares framework with exponential forgetting. The superiority of this proposal over......Very-short-term probabilistic forecasts, which are essential for an optimal management of wind generation, ought to account for the non-linear and double-bounded nature of that stochastic process. They take here the form of discrete–continuous mixtures of generalized logit–normal distributions...

  6. Prospective testing of Coulomb short-term earthquake forecasts

    Science.gov (United States)

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

    2009-12-01

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

  7. Short-term effect of two education methods on oral health among hearing impairment children

    Directory of Open Access Journals (Sweden)

    Shiva Pouradeli

    2016-12-01

    CONCLUSION: Both video and dental model effectively improve the oral health of children with HI in short term. Continuous school-based oral health education programs, particularly for HI children, need to be considered.

  8. 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

  9. Robust short-term memory without synaptic learning.

    Directory of Open Access Journals (Sweden)

    Samuel Johnson

    Full Text Available 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.

  10. 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.

  11. 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

  12. 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

  13. Hydroxychloroquine retinopathy after short-term therapy.

    Science.gov (United States)

    Phillips, Brandon N; Chun, Dal W

    2014-01-01

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

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

    Science.gov (United States)

    Gorin, Simon; Mengal, Pierre; Majerus, Steve

    2018-07-01

    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.

  15. 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.

  16. Short-term effects of playing computer games on attention.

    Science.gov (United States)

    Tahiroglu, Aysegul Yolga; Celik, Gonca Gul; Avci, Ayse; Seydaoglu, Gulsah; Uzel, Mehtap; Altunbas, Handan

    2010-05-01

    The main aim of the present study is to investigate the short-term cognitive effects of computer games in children with different psychiatric disorders and normal controls. One hundred one children are recruited for the study (aged between 9 and 12 years). All participants played a motor-racing game on the computer for 1 hour. The TBAG form of the Stroop task was administered to all participants twice, before playing and immediately after playing the game. Participants with improved posttest scores, compared to their pretest scores, used the computer on average 0.67 +/- 1.1 hr/day, while the average administered was measured at 1.6 +/- 1.4 hr/day and 1.3 +/- 0.9 hr/day computer use for participants with worse or unaltered scores, respectively. According to the regression model, male gender, younger ages, duration of daily computer use, and ADHD inattention type were found to be independent risk factors for worsened posttest scores. Time spent playing computer games can exert a short-term effect on attention as measured by the Stroop test.

  17. Study of short term memory status in adult bipolar disorder patients in south Indian population.

    Science.gov (United States)

    Aslam, Mohammed; Siddiq, Mohamed; Dhundasi, Salim A; Das, Kusal K; Kulkarni, B R

    2011-01-01

    The present study was undertaken to establish short term memory status in bipolar disorder cases as compared with normal age and sex matched control group in Bijapur (Karnataka). Results showed that a significant decrease in short term memory status in bipolar disorder cases as compared to their control group .Loss of attention, decreased processing speed and executive function patterns may be the probable causes of such observations.

  18. Distraction in Verbal Short-Term Memory: Insights from Developmental Differences

    OpenAIRE

    Elliott, Emily; Hughes, Robert W.; Briganti, A; Joseph, Tanya Nicolette; Marsh, John Everett; Macken, William J.

    2016-01-01

    The contribution of two mechanisms of auditory distraction in verbal serial short-term memory-interference with the serial rehearsal processes used to support short-term recall and general attentional diversion-was investigated by exploiting differences in auditory distraction in children and adults. Experiment 1 showed that serial rehearsal plays a role in children's as well as adults' distractibility: Auditory distraction from irrelevant speech was greater for both children and adults as th...

  19. 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.

  20. 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.

  1. 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...

  2. Short-term plasticity as a neural mechanism supporting memory and attentional functions

    OpenAIRE

    Jääskeläinen, Iiro P.; Ahveninen, Jyrki; Andermann, Mark L.; Belliveau, John W.; Raij, Tommi; Sams, Mikko

    2011-01-01

    Based on behavioral studies, several relatively distinct perceptual and cognitive functions have been defined in cognitive psychology such as sensory memory, short-term memory, and selective attention. Here, we review evidence suggesting that some of these functions may be supported by shared underlying neuronal mechanisms. Specifically, we present, based on an integrative review of the literature, a hypothetical model wherein short-term plasticity, in the form of transient center-excitatory ...

  3. 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.

  4. 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.

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

    Institute of Scientific and Technical Information of China (English)

    2013-01-01

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

  6. Dissociating Measures of Consciousness from Measures of Short-Term Memory

    DEFF Research Database (Denmark)

    Sørensen, Thomas Alrik; Ásgeirsson, Árni Gunnar; Staugaard, Camilla Funch

    Often, the contents of consciousness are equated with the contents of short-term memory (or working memory), sometimes to a point where they are treated as identical entities. In the present study we aimed to investigate whether they may be modulated independently and thus dissociated from each...... 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...... conscious experience of the stimulus in every trial (Ramsøy & Overgaard, 2004; Overgaard & Sørensen, 2004). We trained observers to report their experience of a visual target stimulus on the four-point PAS scale; ranging from “no experience” to “clear experience”. To measure short-term memory we used...

  7. 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.

  8. 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

  9. Operations Management in Short Term Power Markets

    DEFF Research Database (Denmark)

    Heide-Jørgensen, Ditte Mølgård

    Electricity market models have often been modelled as deterministic or at most two-stage stochastic models with an hourly time resolution. This thesis looks into possible ways of extending such models and formulating new models to handle both higher time resolution than hourly and stochastics wit...

  10. 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.

  11. 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

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

    Science.gov (United States)

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

    2016-01-01

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

  13. Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

    Science.gov (United States)

    Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

    2018-05-01

    We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

  14. 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.

  15. 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.

  16. Implementing a short-term family support group.

    Science.gov (United States)

    Koontz, E; Cox, D; Hastings, S

    1991-05-01

    1. Although family involvement has been increasingly recognized as a vital component in the treatment and care of the mentally ill, little has been written about efforts to provide education and support to the families of patients hospitalized for short-term evaluation and treatment. 2. The family education and support group provided emotional support and critical information to increase family members' coping and problem solving abilities, and enabled them to return to a pre-crisis or higher level of functioning. 3. The family education and support group not only enhances the assessment and planning phases of the nursing process, but it also can serve as a useful intervention for strengthening the patient's major support system.

  17. 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

  18. 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

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

    NARCIS (Netherlands)

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

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

  20. Comparison of Sugammadex and Neostigmine in Short Term Surgery

    Directory of Open Access Journals (Sweden)

    Fatih Koc

    2014-03-01

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

  1. 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)

  2. Short-term energy outlook annual supplement, 1993

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-08-06

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

  3. 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

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

    Science.gov (United States)

    Leopold, Thomas; Raab, Marcel

    2011-01-01

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

  5. 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.

  6. Short-Term Market Risks Implied by Weekly Options

    DEFF Research Database (Denmark)

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

    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......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......" by the level of market volatility and elude standard asset pricing models....

  7. 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.

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

    Science.gov (United States)

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

    2013-04-01

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

  9. 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)

  10. [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.

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

    Science.gov (United States)

    Jones, Gary; Macken, Bill

    2018-02-01

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

  12. 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.

  13. 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.

  14. 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)

  15. Short-term wind power prediction

    DEFF Research Database (Denmark)

    Joensen, Alfred K.

    2003-01-01

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

  16. 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.

  17. 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.

  18. 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)

  19. Online short-term solar power forecasting

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  20. 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…

  1. 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...

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    Korinko M.D.

    2017-03-01

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

  4. 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.

  5. Mid-latitude summer response of the middle atmosphere to short-term solar UV changes

    Directory of Open Access Journals (Sweden)

    P. Keckhut

    1995-06-01

    Full Text Available Temperature and wind data obtained with Rayleigh lidar since 1979 and Russian rockets since 1964 are analyzed to deduce the summer response of the middle atmosphere to short-term solar UV changes. The equivalent width of the 1083 nm He I line is used as a proxy to monitor the short-term UV flux changes. Spectral analyses are performed on 108-day windows to extract the 27-day component from temperature, wind and solar data sets. Linear regressions between these spectral harmonics show some significant correlations around 45 km at mid-latitudes. For large 27-day solar cycles, amplitudes of 2 K and 6 m s-1 are calculated for temperature data series over the south of France (44°N, and on wind data series over Volgograd (49°N, respectively. Cross-spectrum analyses have indicated correlations between these atmospheric parameters and the solar proxy with a phase lag of less than 2 days. These statistically correlative results, which provide good qualitative agreement with numerical simulations, are both obtained at mid-latitude. However, the observed amplitudes are larger than expected, with numerical models suggesting that dynamical processes such as equatorial or gravity waves may be responsible.

  6. Mid-latitude summer response of the middle atmosphere to short-term solar UV changes

    Directory of Open Access Journals (Sweden)

    P. Keckhut

    Full Text Available Temperature and wind data obtained with Rayleigh lidar since 1979 and Russian rockets since 1964 are analyzed to deduce the summer response of the middle atmosphere to short-term solar UV changes. The equivalent width of the 1083 nm He I line is used as a proxy to monitor the short-term UV flux changes. Spectral analyses are performed on 108-day windows to extract the 27-day component from temperature, wind and solar data sets. Linear regressions between these spectral harmonics show some significant correlations around 45 km at mid-latitudes. For large 27-day solar cycles, amplitudes of 2 K and 6 m s-1 are calculated for temperature data series over the south of France (44°N, and on wind data series over Volgograd (49°N, respectively. Cross-spectrum analyses have indicated correlations between these atmospheric parameters and the solar proxy with a phase lag of less than 2 days. These statistically correlative results, which provide good qualitative agreement with numerical simulations, are both obtained at mid-latitude. However, the observed amplitudes are larger than expected, with numerical models suggesting that dynamical processes such as equatorial or gravity waves may be responsible.

  7. 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.

  8. About the distinction between working memory and short-term memory

    Directory of Open Access Journals (Sweden)

    Bart eAben

    2012-08-01

    Full Text Available The theoretical concepts short-term memory (STM and working memory (WM have been used to refer to the maintenance and the maintenance plus manipulation of memory, respectively. Although they are conceptually different, the use of the terms STM and WM in literature is not always strict. Short-term memory and WM are different theoretical concepts that are assumed to reflect different cognitive functions. However, correlational studies have not been able to separate both constructs consistently and there is evidence for a large or even complete overlap. The emerging view from neurobiological studies is partly different, although there are conceptual problems troubling the interpretation of findings. In this regard, there is a crucial role for the tasks that are used to measure STM or WM (simple and complex span tasks, respectively and for the cognitive load reflected by factors like attention and processing speed that may covary between and within these tasks. These conceptual issues are discussed based on several abstract models for the relation between STM and WM.

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

    Science.gov (United States)

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

    2016-12-01

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

  10. Slave systems in verbal short-term memory.

    Science.gov (United States)

    Caplan, David; Waters, Gloria; Howard, David

    2012-01-01

    The model of performance in short-term memory (STM) tasks that has been most influential in cognitive neuropsychological work on deficits of STM is the "working memory" model mainly associated with the work of Alan Baddeley and his colleagues. This paper reviews the model. We examine the development of this theory in studies that account for STM performances in normal (non-brain-damaged) individuals, and then review the application of this theory to neuropsychological cases and specifications, modifications, and extensions of the theory that have been suggested on the basis of these cases. Our approach is to identify the major phenomena that have been discussed and to examine selected papers dealing with those phenomena in some detail. The main contribution is a review of the WM model that includes both normative and neuropsychological data. We conclude that the WM model has many inconsistencies and empirical inadequacies, and that cognitive neuropsychologists might benefit from considering other models when they attempt to describe and explain patients' performances on STM tasks.

  11. Slave systems in verbal short-term memory

    Science.gov (United States)

    Caplan, David; Waters, Gloria; Howard, David

    2013-01-01

    Background The model of performance in short-term memory (STM) tasks that has been most influential in cognitive neuropsychological work on deficits of STM is the “working memory” model mainly associated with the work of Alan Baddeley and his colleagues. Aim This paper reviews the model. We examine the development of this theory in studies that account for STM performances in normal (non-brain-damaged) individuals, and then review the application of this theory to neuropsychological cases and specifications, modifications, and extensions of the theory that have been suggested on the basis of these cases. Our approach is to identify the major phenomena that have been discussed and to examine selected papers dealing with those phenomena in some detail. Main Contribution The main contribution is a review of the WM model that includes both normative and neuropsychological data. Conclusions We conclude that the WM model has many inconsistencies and empirical inadequacies, and that cognitive neuropsychologists might benefit from considering other models when they attempt to describe and explain patients’ performances on STM tasks. PMID:24347786

  12. 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

  13. 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

  14. 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.

  15. A Visual Short-Term Memory Advantage for Objects of Expertise

    Science.gov (United States)

    Curby, Kim M.; Glazek, Kuba; Gauthier, Isabel

    2009-01-01

    Visual short-term memory (VSTM) is limited, especially for complex objects. Its capacity, however, is greater for faces than for other objects; this advantage may stem from the holistic nature of face processing. If the holistic processing explains this advantage, object expertise--which also relies on holistic processing--should endow experts…

  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 traditio......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...... 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...... 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....

  17. 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. (author)

  18. Statistical short-term earthquake prediction.